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0 بررسی ارتباط شاخص‌های پیوند از دور با مؤلفه‌های بارشی و دمایی (مطالعه موردی: ایستگاه همدید کرج) Examination of relationship between teleconnection indexes on temperature and precipitation components (Case Study: Karaj Synoptic Stations) https://ije.ut.ac.ir/article_62414.html 10.22059/ije.2017.62414 0 ﺩﺭ ﭼﻨﺪ ﺩهۀ ﺍﺧﻴﺮ ﺍﻓﺰﺍﻳﺶ ﺍﻃﻼﻋﺎﺕ ﺑﺸﺮ دربارۀ ﺍﻗﻠﻴﻢ ﺯﻣﻴﻦ ﻭ ﺩﻏﺪﻏۀ ﺍﻧﺴﺎﻥ ﺍﺯ ﺗﻐﻴﻴﺮﺍﺕ ﺁﺏ ﻭ ﻫﻮﺍﻳﻲ ﺩﺭ ﺁﻳﻨﺪﻩ، ﻣﻮﺟﺐ ﺷﻨﺎﺧﺖ ﺩﻗﻴﻖ‏ﺗﺮ ﻣﺆﻟﻔﻪ‏ﻫﺎﻱ تأثیرگذار ﺑﺮ ﺍﻗﻠﻴﻢ ﺯﻣﻴﻦ ﺷﺪﻩ ﺍﺳﺖ. از پدیده‏های اقلیمی‌ای که تغییرات آنها موجب ناهنجاری‏های بزرگ آب و هوایی به‏ویژه در دما و بارش در بسیاری از نقاط جهان می‏شود، الگوهای پیوند از دور هستند که آشکارسازی روابط بین پارامترهای اقلیمی و آنها برای شناخت بیشتر نوسانات و تغییرپذیری اقلیمی در هر منطقه اهمیت فراوانی دارد. بنابراین، در این پژوهش ارتباط الگوهای بزرگ‌مقیاس و شناخته‌شدۀ آن از جمله شاخص نوسان جنوبی (SOI)، شاخص نوسان اطلس شمالی (NAO)، شاخص آرام آمریکای شمالی (PNA)، شاخص چند‌متغیرۀ انسو (MEI) و نوسان دهه‏ای اقیانوس آرام (PDO) با نُه مؤلفۀ دمایی و بارشی به‏صورت ماهانه در ایستگاه همدید کرج طی دورۀ آماری 26 ساله (1985‌ـ 2010) تجزیه و تحلیل شد. ابتدا، نرمال‌بودن سری داده‏های مطالعه‌شده بر اساس آزمون کلموگروف‌ـ اسمیرنوف تأیید شد. در ادامه به‏منظور بررسی ارتباط بین الگوهای بزرگ‌مقیاس با مؤلفه‏های دمایی و بارشی، از ضریب همبستگی پیرسون استفاده شد. همبستگی‏ها به‏صورت ماهانۀ بدون تأخیر و با تأخیر یک‌ماهه ارزیابی شد. نتایج نشان داد بیشترین ارتباط بین شاخص NAO و مؤلفه‏های دمایی و بارشی در ماه‏های فصل پاییز و زمستان مشاهده می‏شود و این تأثیرگذاری‏ها روی ماه‏های فصل پاییز بیشتر از ماه‏های فصل زمستان است. شاخص SOI ارتباط بیشتری با مؤلفه‏های بارشی دارد. تأثیر این شاخص بر بارش ماه‏های فصول پاییز و زمستان آشکارتر است در حالی که شاخص MEI با مؤلفه‏های دمایی ارتباط بیشتر‌ی را نشان می‏دهد و برای مؤلفه‏های بارشی ارتباط خاصی مشاهده نمی‌شود. ‌اثرگذاری این شاخص به‏ویژه بر پارامترهای دمایی ماه‏های آوریل و می در فصل بهار و ماه دسامبر در اواخر فصل پاییز شدید‏تر است. ارتباط شاخص PDO بر مؤلفه‏های بارشی و دمایی منطقه نیز در ماه می در اواسط فصل بهار بیشتر مشاهده می‏شود و شاخص PNA فقط بر مؤلفه‏های دمایی مؤثر است و در ماه‏های دسامبر و فوریه ارتباط بیشتری دارد. نتایج به‌دست‌آمده به‌منظور درک و شناخت بیشتر از تغییرپذیری مؤلفه‏های دمایی و بارشی حائز اهمیت است.   1 Over the recent decades, human knowledge on earth's climate and his concern about climate change in the future has increased, which has contributed to precise identification of the factors influencing earth's climate. One of the climate phenomena, the change of which causes great anomalies of climate, particularly on temperature and precipitation patterns in many parts of the world, is teleconnection, and it is very important to  reveal the relationship between them and climatic parameters for a better understanding of volatility and climate variability in every area. In this study, the relationship between large-scale and well-known patterns such as the Southern Oscillation Index (SOI), North Atlantic oscillation (NAO), Pacific North America (PNA), Multivariate ENSO Index (MEI) and (PDO) with 9 temperature and precipitation variables in the Karaj synoptic station in a monthly basis were analyzed over the 26-year period (2010-1985). First, the normality of the data series based on the Kolmogorov - Smirnov was confirmed. In order to examine the relationship between large-scale patterns with temperature and precipitation variables, the Pearson correlation coefficient was used. The correlations were assessed on a monthly basis without delay and a delay of one month. The results showed that there is a relationship between the NAO index and the temperature and precipitation variables mostly in autumn and winter months and the impact on the autumn months is higher than the winter months. SOI index is more related with the precipitation variables; this index was clearly shown to play a greater role in autumn and winter months, while the MEI index shows a higher correlation with the temperature variables and not particular relation was shown with precipitation variables for this index. Role and impact of this index, in particular on temperature parameters of April and May in spring and December in late autumn, is stronger. The relationship of PDO index with temperature and precipitation variables in May is observed more in the middle of spring. PNA index is effective only on temperature variables, showing higher relationship in December and February. The obtained results are important for greater understanding of the temperature and precipitation variability. 641 651 مسعود گودرزی Massoud Goudarzi استادیار، پژوهشکدۀ حفاظت خاک و آبخیزداری، تهران Iran massoudgoodarzi@yahoo.com حمزه احمدی Hamzeh Ahmadi دانشجوی دکتری، دانشکدۀ جغرافیا و علوم محیطی، دانشگاه حکیم سبزواری، سبزوار Iran massoudgoodarzy@gmail.com سید اسعد حسینی Seyed Asaad Hosseini دکتری، دانشکدۀ علوم انسانی، دانشگاه محقق اردبیلی، اردبیل Iran hosseini.asad8@gmail.com ENSO precipitation climate indexes teleconnection temperature منابع##[1].      Rodriguez-Puebla, C, Encinas, A H. Nieto, S, Garmendia, J, 1998, Spatial and temporal patterns of annual precipitation variability over the Iberian Peninsula. International Journal of Climatology, 18(3): 299-316.##[2].      GhvidelRahimi, Y, Farajzadeh, M, Hatami, D, 2015, Analysis of the relationship between the North Sea - Caspian pattern and minimum temperatures in Iran, Journal of geographical space 5: 137 -159. [Persian]##[3].      Ahmadi. M, 2014, Analyzing on the relationship among Teleconnection Patterns (TP) and Iran’s Precipitation Characteristics (IPC). PhD Thesis, Geographical and Remote sensing Department, Faculty of Humanities, Tarbiat Modares University. [Persian]##[4].      GhvidelRahimi, Y, Farajzadeh, M, Kakapour, S, 2014, Study the affecting of North Sea - Caspian pattern on autumn rainfall fluctuations in the West and Northwest regions of Iran. Journal of Geography and Planning, 49: 217 -230. [Persian]##[5].      Kkosravi, M, ,2004, Study of relationship between atmospheric circulation macro-scale patterns of Northern Hemisphere with drought in Sistan and Baluchestan, geography and development, 3: 167-188. [Persian]##[6].      Karamouz M., Ramezani, F., Razavi, S, 2007, Forecasting the long-term of rainfall through meteorological signals: Application of Artificial Neural Networks, Seventh International Congress on Civil Engineering. Tehran, 11 p. 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Nordemann D.J.R, 2012, Variability of rainfall and temperature (1912–2008) parameters measured from Santa Maria (29°41′S, 53°48′W) and their connections with ENSO and solar activity, Journal of Atmospheric and Solar-Terrestrial Physics, 77: 152-160.##[12].   Rasanen, T A, Kummu, M, 2013, Spatiotemporal influences of ENSO on precipitation and flood pulse in the Mekong River Basin, Journal of Hydrology, 476: 154-168.##[13].   Hamedani Azmoodehfar, M. Azarmsa, S.A, 2013, Assessment the Effect of ENSO on Weather Temperature Changes Using Fuzzy Analysis (Case Study: Chabahar). PCBEE Procedia, 5: 508 – 513.##[14].   Daneshmand, H., Tavousi, T., Khosravi, M., Tavakoli, S, 2015, Modeling minimum temperature using adaptive neuro-fuzzy inference system based on spectral analysis of climate indices: A case study in Iran. Journal of the Saudi Society of Agricultural Sciences, 14(1): 33-40.##[15].   Sun, X. Thyer, M. Renard, B, Lang M. 2014. 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0 شبیه‌سازی و پیش‌بینی خشکسالی با استفاده از روش CA Markov در دشت نجف‌آباد Simulation and prediction of drought using Cellular Automata and Markov methods in Najaf Abad plain https://ije.ut.ac.ir/article_62415.html 10.22059/ije.2017.62415 0 خشکسالی پدیده‌ای است که بین پارامترهای مؤثر در آن ارتباط خطی وجود ندارد. بنابراین، محققان برای بررسی آن به روش‌های غیرخطی مانند اتوماسیون سلولی نیاز دارند. این روش در تحقیقات مختص به پیش‌بینی خشکسالی کمتر استفاده شده است. این در حالی است که از روش اتوماسیون سلولی به‌علت داشتن ساختار ساده و زیادبودن قابلیت بصری می‌توان به‌عنوان روشی مناسب در پیش‌بینی خشکسالی استفاده کرد. این مطالعه با هدف مدل‌سازی خشکسالی برای سال 2020 با استفاده از اتوماسیون سلولی و تصاویر ماهوارۀ لندست در دشت نجف‌آباد انجام شده است. ابتدا تصاویر سری زمانی تبخیر و تعرق برای سال‌های 1995، 2008 و 2015 ‌طبقه‌بندی و نقشۀ پهنه‌بندی وضعیت خشکسالی در این سال‌ها تهیه شد. در گام بعدی، با بهره‌گیری از روش اتوماسیون سلولی وضعیت خشکسالی هریک از طبقات در سال 2020 تخمین زده شد. نتیجۀ به‌دست‌آمده از شاخص کاپا 63/0 و توافق بین نقشۀ واقعی و پیش‌بینی‌شده ((M(m)، 85/0 است که بیان‌کنندۀ مطلوب‌بودن معادلۀ تخمین‌زده‌شده در این تحقیق است. از سوی دیگر، نقشۀ پراکندگی احتمال وقوع تغییرات در سال 2020 گویای آن است که اگر شرایط به همین صورت ادامه یابد و تغییری در نوع و الگوی کشت منطقه ایجاد نشود، تقریباً همۀ نواحی‌ای که در سال 2015 با خطر وقوع خشکسالی مواجه هستند، در سال 2020 با شدت بیشتر و به‌طور وسیع‌تری با وقوع خشکسالی روبه‌رو می‌شوند.   1 The governing factors of drought are non-linearly correlated. Therefore, researcher needs to apply nonlinear methods such as CA to model and predict the drought. CA and its derivatives are among novel methods of drought simulation that rarely used for predicting the drought. While such methods have simple structures, they provide high visual capabilities for drought monitoring. This paper investigates drought in Najaf Abad plain using Markov, CA Markov and Landsat satellite images. First, satellite image time series of transpiration were classified for 1995, 2008 and 2015, and the land zonation of drought condition was estimated. Then, the drought in 2020 was predicted using CA Markov. The Kappa index is 0.63 and the agreement between actual and predicted map (M (m)) is 0.85. Our findings showed that our proposed model can suitably predict the drought. In addition, the drought distribution map showing the possibility of changes in 2020, suggests that if the situation continues and no changes in the type of cultivation and cropping pattern happen, all areas in danger of drought in 2015, will face drought more intensely and more widely, in 2020. 653 662 روزا ابراهیمیان Roza Ebrahimian کارشناس ارشد سنجش از دور و سیستم اطلاعات جغرافیایی، دانشکدۀ محیط زیست و انرژی، دانشگاه آزاد اسلامی واحد علوم و تحقیقات، تهران‌ Iran roza_ebrahimian@yahoo.com علی اصغر آل شیخ Ali Asghar Aleshikh استاد، دانشکدۀ مهندسی نقشه‌‏برداری، دانشگاه صنعتی خواجه نصیرالدین طوسی، تهران‌ Iran alesheikh@kntu.ac.ir ابوالفضل مسعودیان Abolfazl Masodian استاد، دانشکدۀ جغرافیا و علوم انسانی، دانشگاه اصفهان Iran porcista@yahoo.ie Drought evapotranspiration Najaf Abad Basin Markov and cellular automation system [1]. Askarizade M, Behniafar A, Zabol Abasi F, Malbosi Sh. Regionalization of drought with index percentage of normal (PN) and deciles (DC) in Khorasan Razavi Province. Journal of human settlements planning. 2015;3(7):27. [Persian]##[2]. Fathi merj A, Heidarian A. Evaluation of meteorological drought, agricultural and hydrological using GIS in Khozestan province. Iran-Watershed Management Science & Engineering. 2010;7(23):19-32. [Persian]##[3]. Samadi H, Ebrahimi A. Drought and surface water and groundwater resources. Drought Impacts and its Mitigation Approaches. First ed. Sahrekord University: Soroosh; 2010.p. 115. [Persian]## [4]. Niknam H, Ajdari moghadam M, Khosravi M. Neuro-fuzzy model patterns and telecommunications to predict drought Case Study: Zahedan. 4th international congress of the Islamic World Geographers. Zahedan. 2010. [Persian]##[5]. Reza zade R, Mir Ahmadi M. Cellular Automation is a new method for simulation of urban growth. Journal of Technology of Education. 2008;4(6):47-55. [Persian]##[6]. Alam J, Rahman M, Sadaat A. Monitoring Meteorological and Agricultural Drought dynamics in Barind Region Bangladesh using Standard Precipitation Index and Markov Chain Model. Journal of Geomatics and Geosciences. 2013;3(3):511-524.##[7]. Avilés A, Célleri R, Solera A, Paredes J. Probabilistic Forecasting of Drought events using Markov Chain- and Bayesian Network-Based Models: A Case Study of an Andean Regulated River Basin. Journal of water. 2016;8(37): 1.##[8]. Edalat Gostar M, Farzadian M, Amiri N. Stochastic models for prediction of drought in the county of Shiraz. National Conference on management of Water Crisis. Marvdasht. 2008. [Persian]##[9]. Hasan Zade E, Abdi Kordani A, Fakheri fard A. Prediction of drought using genetic algorithms and neural network model. Journal of water and wastewater. 2009;23(3):48-59. [Persian]##[10]. Rostami A, Razmkhah H, Fatahi M. Monitoring and development of artificial neural network model to predict drought using SPI index case study: Kohgiluyeh and Boyer. Faculty of Agriculture, Islamic Azad University of Shiraz. 2011:1. [Persian]##[11]. Darzi F, Safavi H, Mamanposh A. Modeling of return flow from Nekooabad network to Najaf Abad basin. Second Conference on Water Resources of Iran. Isfahan. 2006. [Persian]##[12]. Phedge N, Muralikrishna I V, Chalapatirao K V. Study of cellular Automata Models for urban growth. www. GIS Development.net.##[13]. OSullivan D. Exploring spatial process dynamics using irregular Cellular Automaton models. Journal of Geographical Analysis. 2001;33(1):1-18.##[14]. White R, Engelen G. High resolution integrated modeling of the spatial Dynamics of urban and regional systems, Computers, environment and urban System. 2000;24:383-400.##[15]. OSullivan D, Torrens P. Cellular models of urban systems. In: Bandini S, Worsch T, editor. Theory and Practical Issues on Cellular Automata. First ed. London: Springer; 2001.p. 108-116.##[16]. Ahadnejad M, Rabet A. Evaluation and forecast of Haman impacts based on land use changes using multi temporal satellite imagery and GIS: a case study on Zanjan. Journal of the Indian Society of Remote Sensing. 2009;37(4):659–669.##[17]. Hadavi F. Evaluation of physical development of the Zanjan city for optimized planning using GIS techniques. 1th National conference and exhibition Geomatics and conference of International Remote sensing. Tehran. 2011. [Persian]##

0 اولویت‌بندی مناطق احداث سد زیرزمینی با استفاده از روش میانگین هندسی در محیط سامانه اطلاعات جغرافیایی Prioritization of potential areas for construction of underground dam using geometric average method in geographical information system https://ije.ut.ac.ir/article_62494.html 10.22059/ije.2017.62494 0 یکی از راه‏های برطرف‌کردن کمبودهای فصلی آب، استفاده از آب‏های زیرزمینی است. از آنجا که انتخاب محل مناسب برای احداث سد زیرزمینی به‌منظور ذخیره‌سازی آب‌ مسئله‌ای مهم و چالش‏برانگیز است، استفاده از روشی با کمترین خطا در مطالعۀ این مناطق ضروری است. هدف این پژوهش انتخاب بهینۀ مکان‏های مناسب برای احداث سد زیرزمینی، در حوضۀ آبخیز همدان‌ـ بهار با استفاده از یک روش جدید در محیط سامانۀ اطلاعات جغرافیایی (GIS)، به‌منظور کاهش خطا بوده است. بر این اساس، ابتدا معیارهای لازم و تأثیرگذار در انتخاب مکان مناسب برای احداث سد زیرزمینی شامل چگالی آبراهه، فاصله از قنات، چشمه و چاه، زمین‏شناسی، شیب، فاصله از گسل، نزدیکی به جاده و روستا و کاربری اراضی شناسایی شد. سپس لایه‏های اطلاعاتی مختلف در محیط GIS و با استفاده از تابع لجستیکی (انتقال به دامنۀ صفر و یک)، وزن‏دار شدند و در نهایت همۀ نقشه‏های وزن‏دار با استفاده از رابطۀ میانگین هندسی تلفیق شدند تا مدل نشان‌دهندۀ مناطق مناسب برای احداث سد زیرزمینی به‌صورت یک نقشه تولید شود. نتایج مطالعه نشان داد روش به‌کار گرفته‌شده می‏تواند به‌شکل مطلوبی محدودۀ ‌مطالعه‌شده را کوچک کند و حدود 10 درصد از کل آبراهه‏ها را به‌عنوان آبراهه‏های مناسب برای احداث سد زیرزمینی شناسایی و معرفی کند.             1 Exploitation of underground water resources is a way to modulate the shortage of seasonal water. In this regard, proper site selection for constructing underground dam to reserve waters is a challenging issue. Thus, using an approach with minimum error is essential. The purpose of this paper was optimum selection of potential sites for constructing underground dam in Hamedan-Bahar catchment basin using a new GIS-based approach to reduce the error. For this purpose, the efficient criteria of a proper site to make underground dam were first recognized. These criteria include density of drainages, separation of the aqueducts, spring and wells, geological appropriate, slope, fault density, proximity to roads and villages and special conditions of land use. Then, different evidence layers were weighted in [0, 1] range using logistic function in geographic information system. Finally, the weighted evidence layers were integrated using geometric average function. Thus, a model representing favorable areas for making underground dam was generated. The results obtained introduced less than 10% of the streams (respecting the whole streams in the study area) as suitable, and demonstrated that the method applied can be used efficiently to delimit the study area and to recognize suitable streams for construction of underground dam. 663 672 مهیار یوسفی Mahyar Yousefi استادیار گروه مهندسی معدن، دانشکدۀ فنی و مهندسی، دانشگاه ملایر Iran m.yousefi.eng@gmail.com بهنوش فرخ زاده Behnoosh Farokhzadeh استادیار گروه مرتع و آبخیزداری، دانشکدۀ منابع طبیعی و محیط زیست، دانشگاه ملایر Iran b.farokhzadeh@malayeru.ac.ir سمیرا بساطی. Samira Basati دانشجوی کارشناسی ارشد آبخیزداری، دانشکدۀ منابع طبیعی و محیط زیست، دانشگاه ملایر Iran Multi-Criteria Decision Making Integration Hamedan-Bahar catchment basin Locating weighting criteria منابع##[1]. Kheirkhah Zarkesh MM, Naseri HR, Daodi MH, Salami H. 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A justification report on extending the ban on exploitation of groundwater resources in the Hamedan-bahar basin, Office of Water resources, Office of water supply, Hamedan Regional Water Authority. 2009. (In Persian)##[19]. Yousefi M, Carranza EJM. Prediction-area (P-A) plot and C-A fractal analysis to classify and evaluate evidential maps for mineral prospectivity modeling. Computers & Geosciences. 2015; 79: 69-81.##[20]. Wang JQ, Zhang Z.H. Multi-criteria decision-making method with incomplete certain information based on intuitionistic fuzzy number, Control and Decision. 2009; 24: 226–230.##[21]. Wang JQ, Zhang ZH. Aggregation operators on intuitionistic trapezoidal fuzzy number and its application to multi-criteria decision making problems, Journal of Systems Engineering and Electronics. 2009; 20: 321–326.##[22]. Wang YM, Chin KS, Yang JB. Measuring the performances of decision making units using geometric average efficiency. 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0 مدل سازی تغییرات مکانی آب معادل برف بر اساس عوامل توپوگرافی و اقلیمی (مطالعه موردی: حوزه آبخیز سهرورد استان زنجان) Spatial distribution of snow water equivalent modeling based on topography and climatic factors (Case Study: Sohravard watershed, Zanjan Province) https://ije.ut.ac.ir/article_62495.html 10.22059/ije.2017.62495 0 داشتن اطلاعات در زمینۀ عمق، چگالی و آب معادل برف برای مدیریت منابع آب در مناطق کوهستانی اجتناب‏ناپذیر است. از طرفی، به‌دلیل مسائل مالی، شرایط اقلیمی نامساعد و صعب‏العبور‌بودن مناطق کوهستانی، اندازه‏گیری‌ها نقطه‌ای است که تعمیم آن به سطوح بزرگ خطای زیادی دارد. یکی از روش‌ها برای پیش‌بینی آب معادل برف، بررسی ارتباط بین آب معادل برف با عوامل مؤثر است. بدین‌منظور حوضۀ آبخیز کوهستانی سهرورد استان زنجان انتخاب شد. داده‏های اولیه تهیه و نقشه‏های مورد نیاز شامل نقشه‏های مدل رقومی ارتفاع، شیب، جهت شیب، شمالی‌بودن، شرقی‌بودن، انحنای افقی، انحنای عمودی، شاخص وضعیت توپوگرافی و تابش خورشیدی استخراج شد. سپس، هنگام بارش اوج برف، عمق برف به تعداد 150 نمونه به روش هایپرکیوب لاتین و چگالی برف به تعداد 18 نمونه به‌روش تصادفی اندازه‏گیری شد. محاسبات شاخص بادپناهی برای نقاط اندازه‏گیری‌شدۀ عمق برف انجام شد. در مرحلۀ بعد با انجام رگرسیون بین آب معادل برف با عوامل مؤثر، رابطۀ کمی بین آنها تعیین شد. کارایی مدل‏ها با شاخص‏های آماری میانگین خطا، میانگین خطای مطلق، ریشۀ میانگین مربعات خطا و ضریب همبستگی تعیین شد. نتایج نشان داد در حوضۀ آبخیز یادشده با روش رگرسیون گام‌به‌گام می‏توان آب معادل برف را برآورد کرد. همچنین براساس نتایج، هرچند عامل اقلیمی شاخص باد‌پناهی حجم زیاد محاسبات را دارد؛ ولی دخالت‌دادن آن سبب افزایش کارایی مدل در برآورد آب معادل برف می‏شود. آب معادل برف بیشترین همبستگی معنا‏دار را با ارتفاع برابر با 607/0 و کمترین همبستگی معنا‏دار را با شمالی‌بودن برابر با 204/0 در محدودۀ مطالعاتی دارد. ضرایب همبستگی بین متغیر وابستۀ آب معادل برف با متغیر مستقل شاخص بادپناهی نشان می‏دهد فاصلۀ 300 متری، مؤثرترین فاصلۀ بر‌هم‌کنش باد و پستی و بلندی‌ها در ایجاد شرایط بادپناهی و بادروبی است. ضریب تغییرات عمق و چگالی برف اندازه‌گیری‌شده به‌ترتیب برابر با 14/54 ‌و 89/7 درصد است.     1 It is inevitable to obtain necessary data including snow depth, snow density and snow water equivalent (SWE) in order to manage water resources in mountains areas. On the other hand, due to financial constraints, unfair weather and impassability of mountainous areas, measurement is limited to the points, and its generalization to larger areas is associated with large errors. A method for predicting the SWE is investigation the relationship between the SWE and effective factors. Therefore, in this research, mountainous Sohravard watershed located in Zanjan Province was selected as the case study. The required data and maps including Digital Elevation Model (DEM), slope, aspect, northern, eastern, profile curvature, plan curvature, topography position index and solar radiation maps were extracted. Then, during the peak of snowfall in the area, snow depth of 150 points and snow density of 18 points were measured using Latin Hypercube and random sampling methods, respectively. The calculation of upwind slope was carried out for the measured snow points. In the next step, the quantitative relation between the SWE and effective factors was determined by fitting a regression relationship. The efficiency of the created models was evaluated by statistical criteria including mean bias error, mean absolute error, root mean square error and correlation coefficient(R). The results showed that SWE in the studied watershed could be estimated by using stepwise regression.  As the results show, although climate factor of upwind slope requires high computing, its incorporation in the model can lead to increased model efficiency in the SWE estimation. The SWE had the highest significant correlation equal to 0.607 with the elevation, and the lowest significant correlation equal to 0.204 to the northern part of the study area. Correlation coefficient between the dependent variable SWE and independent variable upwind slope shows that 300 meters distance is the most effective distance of the interaction of wind and terrain in creation of wind sheltering and wind deflation. Coefficient of variation in snow depth and snow density measurements is 54.14% and 7.89%, respectively. 673 686 حجت اله گنج خانلو Hojatolah Ganjkhanlo دانشجوی آبخیزداری، دانشکدۀ منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس Iran hojat.ghanjkhanlo@yahoo.com مهدی وفاخواه Mehdi Vafakhah دانشیار، دانشکدۀ منابع طبیعی و علوم دریایی، دانشگاه تربیت مدرس Iran vafakhah@modares.ac.ir علی فتح زاده Ali Fathzadeh دانشیار، دانشکدۀ منابع طبیعی، دانشگاه اردکان Iran afathzadeh@gmail.com حسین زینی وند Hossein Zeinivand دانشیار، دانشکدۀ منابع طبیعی، دانشگاه لرستان Iran hzeinivand@gmail.com Latin hypercube sampling Snow water equivalent Stepwise regression upwind slope [1]. Porhemmat J. 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0 بررسی رابطه زمانی خشکسالی هواشناسی و هیدرولوژیکی در حوزه آبریز کرخه Investigation of relationship between meteorological and hydrological drought in Karkheh watershed https://ije.ut.ac.ir/article_62496.html 10.22059/ije.2017.62496 0 خشکسالی از جمله بلایای طبیعی است که به‌شدت تحت تأثیر نوسانات اقلیمی است و مجموعه‏ای از مشکلات پیچیده را در بخش‏های مختلف ایجاد می‏کند. هدف پژوهش حاضر، بررسی رابطۀ زمانی خشکسالی هواشناسی و هیدرولوژیکی در حوضۀ آبریز کرخه است. برای رسیدن به این هدف، از آمار 26 ایستگاه باران‏‏سنج و هشت ایستگاه هیدرومتری استفاده شد. در بخشی از تحقیق برای آگاهی از تأخیر جریان‏ها نسبت به بارش‏ها در حالت واقعی، ضریب همبستگی پیرسون بین بارش و دبی جریان با تأخیرهای زمانی مختلف محاسبه شد. سپس دو شاخص بارش استانداردشده (SPI) و شاخص خشکسالی جریانات رودخانه‏ای (SDI) به‏ترتیب برای ارزیابی خشکسالی هواشناسی و هیدرولوژیکی انتخاب شدند. مقادیر شاخص‏ها در گام زمانی کوتاه‌مدت (یک‌ماهه و سه‌ماهه)، میان‏مدت (شش‌ماهه) و بلندمدت (12‌ماهه) در نرم‌افزار DrinC محاسبه شد. همچنین ضریب همبستگی بین دو شاخص SPI و SDI در کل حوضه و دو زیر‌حوضۀ قره‏سو و گاماسیاب بررسی شد. نتایج نشان داد بین ضریب همبستگی بارش‌ـ دبی جریان و دو شاخص SPI-SDI در چهار گام زمانی رابطۀ مستقیم و معنا‏داری در سطح 99 درصد وجود دارد. هر چند در هر چهار گام زمانی (کوتاه‌مدت، میان‌مدت و بلندمدت) ضریب همبستگی از سطح معنا‏داری برخوردار است؛ مقدار ضریب همبستگی در حالت بدون تأخیر زمانی نسبت به سایر موارد با تأخیر زمانی بیشتر است. بنابراین، می‏توان نتیجه گرفت که خشکسالی هیدرولوژیکی با تأخیر زمانی خیلی کوتاه در حوضۀ آبریز کرخه پس از خشکسالی هواشناسی رخ می‏دهد. همچنین به‏دلیل همسویی ضرایب همبستگی و عدم تأخیر زمانی در هر دو حالت، دو شاخص یادشده به‌خوبی شرایط خشکسالی هواشناسی و هیدرولوژیکی را نشان می‏دهند.   1 Drought is one of the natural disasters which is strongly influenced by climatic fluctuations and makes a set of complex problems in various parts. The current study aims for investigation of time relationship between meteorological and hydrological drought in Karkhe catchment. For this purpose, 26 rain gauge stations and 8 gauging stations were used. In part of research, for understanding delay trends in comparison with precipitation in reality, Pearson correlation coefficient between precipitation and discharge was calculated with different time delays. Two indices (SPI and SDI index) were selected for examining Meteorological drought and hydrological drought. Index values in short term step (1 to 3 months), medium-term (6 months) and long term (12 months) was calculated by DrinC software. The results showed that there is 99% direct significant correlation between precipitation-discharge and two SPI-SDI indices in four steps of time. However, the correlation coefficient is significant for any four time steps, but the value of correlation coefficient  has more delay time in a mood with no delay time compared to other cases. Therefore, we can conclude that drought occurs simultaneously in the catchment Karkhe meteorologically and hydrologically. Also, due to the lack of consistent correlation coefficients and delay time in both cases, two aforementioned indices properly show drought conditions. 687 698 راضیه کوشکی Razieh Koushki دانش‌آموختۀ کارشناسی‏ ارشد هواشناسی کشاورزی، دانشکدۀ کویرشناسی، دانشگاه سمنان Iran r.koushki67@gmail.com محمد رحیمی Mohammad Rahimi دانشیار، دانشکدۀ کویرشناسی، دانشگاه سمنان Iran r.koushki@semnan.ac.ir مجتبی امیری Mojtaba Amiri استادیار، دانشکدۀ منابع طبیعی، دانشگاه سمنان Iran mojtabaamiri@semnan.ac.ir مجید محمدی Majid Mohammadi استادیار، دانشکدۀ منابع طبیعی، دانشگاه سمنان Iran mohammady.wme@gmail.com جعفر دستورانی Jafar Dastorani استادیار، دانشکدۀ منابع طبیعی، دانشگاه سمنان Iran jdastorani@gmail.com Drought meteorological drought hydrological correlation Pearson basin Karkhe منابع##[1]. Mozafari Gh. Unconformity in meteorological ang hydrological drought in two neighboring basin at north montain slope of shirkoh yazd. Journal of spatial planning. 2006;10 (2): 173-190. [Persian].##[2]. Khazayi M, Telvari A. Hydrological drought frequency distribution analysis. Journal of Geography and Urban Development. 2003; (2): 45-56. [Persian].##[3]. Eivazi M, Mosaedi A. Monitoring and spatial analysis of meteorological drought in golestan province using geostatistical methods., Journal of range and watershed management, iranian journal of natural resources. 2011; 64: 65-78. [Persian].##[4]. Alavi Nia H, Sadatinejad j, Abdullah Kh. Provide a model for prediction of hydrological drought in Karoon-1 basin. Environmental Erosion Research Journal. 2011; (1): 45-56. [Persian].##[5]. Rzayyklantry d. Check meteorological and hydrological drought in East Mazandaran. Gorgan University of Agricultural Sciences and Natural Resources. 2011 Master thesis.##[6]. 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0 برآورد تبادل آب بین تالاب‏ و آبخوان (مطالعۀ موردی تالاب‏ کانی‏برازان) Estimation of wetland-aquifer exchanges (Case Study: Kaniborazan wetland) https://ije.ut.ac.ir/article_62503.html 10.22059/ije.2017.62503 0 چکیده ارتباط و اندرکنش آب سطحی و آب زیرزمینی می‏تواند بین پهنه‏های آب سطحی (مانند رودخانه‏ها، دریاچه‏ها و تالاب‏ها) و منابع آب زیرزمینی رخ دهد. کمّی‌کردن مقدار تبادل آب بین تالاب و آبخوان از مراحل مهم در مطالعاتی مانند بیلان آب و تعیین نیاز‏های زیست‏محیطی است. در این مطالعه به‌منظور برآورد نیاز آبی تالاب کانی‏برازان واقع در حاشیۀ جنوبی دریاچۀ ارومیه، روی مؤلفۀ آب زیرزمینی تمرکز شده است. نتایج این مطالعه بیان می‌کند که در دورۀ زمانی بررسی‌شده از سال 1377 تا 1394، با توجه به آستانۀ گرادیان هیدرولیکی، تالاب کانی‏برازان همواره از منابع آب زیرزمینی تغذیه شده است. در سال‏های 1377، 1381 و 1394 مقادیر تغذیۀ تالاب از منابع آب زیرزمینی بیشترین مقدار را داشته و به‌ترتیب برابر با 11/4، 09/5 و 78/3 میلیون مترمکعب در سال برآورد شده است. مقدار متوسط سالانۀ عمق این تالاب کمتر از 16 سانتی‌متر برآورد شده است. اثر زهکش‏ها، کانال‏ها و انهار سنتی بر تالاب هم طی دورۀ زمانی یادشده بررسی شده‏اند. نتایج نشان می‏دهد این منابع آبی تأثیر مهمی در تأمین آب تالاب دارند. بر اساس داده و اطلاعات موجود، برای مثال در سال‏های 1385 و 1394، چنانچه اثر زهکش‏ها، کانال‏ها و انهار سنتی بر تالاب‏ در نظر گرفته نشود، به‌ترتیب کاهشی حدود 15 و 30 درصد در حجم آب تالاب تخمین زده می‌شود.     1 Surface water and groundwater interactions can occur between surface water bodies (such as rivers, lakes, and wetlands) and groundwater resources. Quantifying water exchange between a wetland and an underlying aquifer is an important task for studies in such fields as water budgets and environmental water requirements. In this study, the groundwater component from controlling factors on wetland water level is considered to determine the water requirements of Kaniborazan wetland, located at the southern part of Urmia Lake. The results of the present study indicate that during the assessment period of 1998-2015, Kaniborazan wetland has been always recharged from underlying groundwater resources considering the hydraulic gradient threshold of this wetland. These recharge values have been maximum for 1998, 2002, and 2015 with the annual value of 4.11, 5.09, and 3.78 MCM, respectively. The mean annual value of this wetland depth has been estimated to be less than 16 cm. The impacts of drainage system, channels, and traditional streams have been investigated on this wetland during the assessment period. The obtained results show that these sources have a significant effect on the water supply of the wetland. Based on the available data and information, for example for 2006 and 2015, not taking the impacts of drainage system, channels, and traditional streams on this wetland into account will lead to the wetland water volume reduction of about 15% and 30%, respectively. 699 709 حامد کتابچی Hamed Ketabchi استادیار، دانشکدۀ مهندسی منابع آب، دانشگاه تربیت مدرس Iran h.ketabchi@modares.ac.ir داود محمودزاده Davood Mahmoodzadeh دانشجوی دکتری، دانشکدۀ مهندسی عمران، دانشگاه تهران Iran d.mahmoodzadeh@ut.ac.ir رضا فرهودی هفدران Reza Farhoudi Hafdaran کارشناس ارشد، دانشکدۀ مهندسی منابع آب، دانشگاه تربیت مدرس Iran reza.farhoudi@modares.ac.ir Aquifer drainage system Groundwater Resources water exchanges wetland منابع##[1]. Rafiei Y, Malekmohamadi B, Abkar AA, Yavari A, Ramezani-Mehrian M, Zahrabi H. Assessment of wetlands environmental changes and protected areas using temporal images Landsat TM (Case Study: Neyriz Wetland). Journal of Environmental Study. 2011; 37(57), 65-76##[2]. Ayafat SA. Wetland Benefits, Compiled by: John Davies and Gordon Claridge, Supported by: IWRB, WA, AWB and Supervised by: Anoushirvan Najafi and Esmail Kahrom. 2000.##[3]. Ganjidoust H, Ayati B, Khara H, Khodaparast SH, Akbarzadeh A, Ahmadzadeh T, Shaban L, Nezami A , Zolfi Nejhad K. Investigation of environmental pollution in Shiah Keshim wetland. Environmental Sciences. 2009; 6(3), 117-132. [Persian].##[4]. Wang Y, Mitchell BR, Nugranad-Marzilli J, Bonynge G, Zhou Y, Shriver G. Remote sensing of land-cover change and landscape context of the National Parks: A case study of the northeast temperate network. Remote Sensing of Environment. 2009; 113(7), 1453-1461.##[5]. Jones DA, Hansen AJ, Bly K, Doherty K, Verschuyl JP, Paugh JI, Story SJ. 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0 ارزیابی تأثیرات اقتصادی و هیدرولوژیکی تغییرات اقلیم در حوضۀ آبخیز خررود Assessment of the economic and hydrological effects of the climate change on Kharrood Watershed https://ije.ut.ac.ir/article_62504.html 10.22059/ije.2017.62504 0 در مطالعۀ حاضر ابتدا الگوی رفتاری متغیر اقلیمی بارش طی دورۀ 1365‌ـ 1393 در سطح حوضۀ‏ آبخیز خررود بررسی شد. سپس از یک سیستم مدل‏سازی بیوفیزیکی- اقتصادی برای ارزیابی تأثیر تغییرات اقلیم ناشی از کاهش بارش بر متغیرهای هیدرولوژیکی (منابع آب در دسترس و ارزش واقعی نهادۀ آب آبیاری) و اقتصادی (تولیدات کشاورزی و سود ناخالص کشاورزان) تحت سناریوهای مختلف (تغییر اقلیم ملایم، متوسط و شدید) استفاده شد. سیستم مدل‏سازی یادشده، شامل تابع عملکرد محصولات مبتنی بر میزان بارش (جزء بیوفیزیکی مدل) و رهیافت برنامه‏ریزی ریاضی اثباتی (جزء اقتصادی مدل) بود که طی سه مرحلۀ پیاپی در محیط نرم‏افزاری GAMS 24.1 حل شد. داده‏های مورد نیاز از طریق ایستگاه‏های باران‏سنجی و اداره‌های ذی‌ربط در استان قزوین جمع‏آوری شد. الگوی رفتاری بارش نشان داد این متغیر اقلیمی پس از سال 1380 در سطح حوضۀ آبخیز خررود روندی کاهشی را طی کرده است. نتایج مدل نشان داد تغییرات اقلیم ناشی از کاهش بارش تحت سناریوهای ملایم تا شدید به کاهش 3/11 تا 0/23 درصد در منابع آب در دسترس، افزایش 08/7 تا 22/15 درصد در ارزش اقتصادی آب آبیاری، کاهش 14/5 تا 39/16 درصد در مجموع سطح زیر کشت محصولات آبی و کاهش 58/6 تا 41/13 درصد در سود ناخالص کشاورزان حوضۀ‏ آبخیز خررود نسبت به شرایط سال مبنا یا پایه منجر شده است. بیشترین کاهش منابع آب در دسترس نیز تحت سناریوی تغییر اقلیم شدید و به میزان 15/29 میلیون مترمکعب حاصل شد. در پایان برای مقابله با آثار تغییر اقلیم و حفاظت از منابع آب در سطح این حوضۀ آبخیز، به‏کارگیری تکنیک‏های کم‏آبیاری، تعیین نرخ آب‏بها برای کشاورزان بر اساس ملاحظۀ برابری، آیش‏گذاری اراضی و ارائۀ تسهیلات به کشاورزان برای تجهیز مزارع به سیستم‏های نوین آبیاری پیشنهاد شد.         1 In the present study, first the behavioral patterns of precipitation climatic variable over the period 1985-2014 in Kharrood watershed was investigated. Then, in order to analyze the effects of climate change resulting from reduced rainfall under different scenarios (i.e. mild, moderate and severe) on hydrological (available water resources and economic value of irrigation water) and economic (agricultural products and farmers’ gross profit) variables, a biophysical-economic modeling system was used. The aforementioned modeling system includes the products yield function based on rainfall (biophysical part of model) and positive mathematical programming approach (economic part of model) solved in consecutive three stages and in the GAMS 24.1 software. The required data were collected referring to the rain gauge stations and the relevant agencies in Qazvin province. Behavioral pattern of precipitation showed that this climate variable reduced in Kharrood watershed after year 2001. The results of proposed model showed that climate change resulting from reduced rainfall under mild to severe scenarios decreases the available water resources from 11/3 to 23/0 %, increases the economic value of irrigation water from 7/08 to 15/22 %, decreases the total acreage of water crops from 5/14 to 16/39 % and decreases the farmers’ gross profit from 6/58 to 13/41 % compared to the base year. The highest decrease of the available water resources in Kharrod watershed was obtained under severe scenarios and at a rate of 15/29 million cubic meters. Finally, use of deficit irrigation techniques, determination of the rate of water charge for farmers on the basis of equality consideration, fallow-lands and provision of facilities to farmers in order to equip their lands with new irrigation systems were proposed in order to deal with the effects of climate change and protect water resources in this watershed.   711 724 ابوذر پرهیزکاری Abozar Parhizkari دانشجوی دکتری اقتصاد کشاورزی، دانشگاه پیام نور تهران Iran abozar.parhizkari@yahoo.com سعید یزدانی Saeed Yazdani استاد گروه اقتصاد کشاورزی، دانشگاه تهران Iran syazdani@ut.ac.ir Behavioral pattern of precipitation climate change hydrological variables sustainability of water resources biophysical-economic model منابع##[1]. Parhizkari A. Determination economic value of irrigation water and farmer’s response to price and non-price policies in Qazvin province, the thesis submitted for the degree of M.Sc in the field of agricultural economics, University of Zabol, Iran, 2013; 130 P. 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0 ارزیابی و مقایسۀ روش‏های نسبت فراوانی، شاخص آماری و آنتروپی برای تهیۀ نقشۀ پتانسیل آب زیرزمینی با استفاده از سیستم اطلاعات جغرافیایی (مطالعۀ موردی: شهرستان جهرم) Evaluation and comparison of frequency ratio, statistic index and entropy methods for groundwater potential mapping using GIS (Case Study: Jahrom Township) https://ije.ut.ac.ir/article_62505.html 10.22059/ije.2017.62505 0 آب زیرزمینی به‏عنوان یکی از منابع ارزشمند‌ تازۀ آب در نظر گرفته می‏شود. با افزایش سریع جمعیت انسان، تقاضا برای آب‏های زیرزمینی افزایش‏ یافته است. تهیۀ نقشۀ مناطق بالقوۀ آب زیرزمینی می‏تواند کمک شایان توجهی به تعیین، محافظت و مدیریت چشمه‏های آب زیرزمینی کند. هدف از این تحقیق، تهیۀ نقشۀ پتانسیل چشمه‏های آب زیرزمینی در شهرستان جهرم با استفاده از روش‏های نسبت فراوانی، شاخص آماری و آنتروپی است. نوآوری تحقیق حاضر، به‏کارگیری روش شاخص آماری برای اولین‌بار به‌منظور تهیۀ نقشۀ پتانسیل آب زیرزمینی و مقایسۀ آن با دو روش آنتروپی و نسبت فراوانی است. دوازده معیار هیدرولوژی، زمین‏شناسی و جغرافیای طبیعی که بر موقعیت چشمه‏ها اثر می‏گذارند، در نظر گرفته شد و در محیط ArcGIS این داده‏ها پردازش و آماده شد. این معیارها شامل درجۀ شیب، جهت شیب، ارتفاع، شاخص توپوگرافی رطوبت (TWI)، طول شیب، شاخص توان آبراهه (SPI)، فاصله از رودخانه، فاصله از گسل، فاصله از جاده، تراکم گسل، کاربری اراضی و زمین‏شناسی است. پس از تهیۀ نقشۀ پتانسیل آب‏های زیرزمینی با این سه روش، برای ارزیابی نتایج از منحنی تشخیص عملکرد نسبی (ROC) استفاده شد. از 103 چشمه معرفی‏شده در این تحقیق، 73 چشمه (70 درصد) برای تهیۀ نقشۀ پتانسیل آب زیرزمینی و 30 چشمه (30 درصد) برای ارزیابی مدل استفاده شد. سطح زیر‌منحنی (AUC) به‏دست‏آمده از منحنی تشخیص عملکرد نسبی، نشان‏دهندۀ دقت 91 درصد برای مدل شاخص آماری، دقت 92 درصد برای مدل نسبت فراوانی و دقت 7/92 برای مدل آنتروپی برآورد شد. نتایج این ارزیابی نشان‏دهندۀ دقت عالی برای این سه مدل و برتری مدل آنتروپی نسبت به دو مدل دیگر است. همچنین بر اساس مدل آنتروپی لایه‏های شاخص توان آبراهه، ارتفاع، شیب و کاربری اراضی بیشترین تأثیر را بر پتانسیل آب زیرزمینی در منطقۀ مطالعه‌شده داشته‏اند.     1 Groundwater is considered one of the most valuable fresh water resources. The rapid increase in human population has increased the demand for groundwater supplies for drinking, agricultural, and industrial purposes. It is necessary to provide groundwater spring potential maps for implementing a successful groundwater determination, protection, and management program. The main objective of this study was to produce groundwater spring potential maps in the Jahrom region, using frequency ratio, statistic index and entropy methods. Twelve hydrological-geological-physiographical (HGP) factors influencing locations of springs were considered in this research and processed in ArcGIS environment. These factors include slope degree, slope aspect, altitude, topographic wetness index (TWI), slope length (LS), distance to roads, distance to rivers, distance to faults, lithology, land use and fault density. The predicted results from the three models were validated using the receiver operating characteristics curve (ROC). From 103 springs identified, 70 (≈70 %) locations were used for the spring potential mapping, while the remaining 33 (≈30 %) springs were used for the model validation. The area under the curve (AUC) for the statistic index model was calculated to be %91 and for frequency ratio and entropy the AUC to be %92 and %92.7, respectively. 725 736 سید وحید رضوی ترمه Seyyed Vahid Razavi Termeh دانشجوی کارشناسی ارشد GIS، دانشکدۀ مهندسی ژئودزی و ژئوماتیک، دانشگاه صنعتی خواجه‏ نصیرالدین طوسی Iran vrazavi70@gmail.com محمد سعدی مسگری Mohammad Saedi Mesgari دانشیار گروه سیستم اطلاعات مکانی، دانشکدۀ مهندسی ژئودزی و ژئوماتیک، دانشگاه صنعتی خواجه ‏نصیرالدین طوسی Iran mesgari@kntu.ac.ir کاظم کاظمی kazem kazemi دانشجوی کارشناسی ارشد GIS، دانشکدۀ مهندسی ژئودزی و ژئوماتیک، دانشگاه صنعتی خواجه‏ نصیرالدین طوسی Iran kazem_k_1369@yahoo.com Spring potential mapping frequency ratio method statistic index method entropy method منابع##Todd DK, Mays LW. 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0 شاخص مدیریت خشکسالی هیدروژئولوژیکی (HDMI) به عنوان روشی برای مدیریت منابع آب زیرزمینی در شرایط خشکسالی ، مطالعه موردی: دشت دیر- آبدان، استان بوشهر Hydrogeological drought management index (HDMI) as a tool for groundwater resource management under drought conditions (Case Study: Dayyer-Abdan district, Boushehr province) https://ije.ut.ac.ir/article_62506.html 10.22059/ije.2017.62506 0 پدیدۀ خشکسالی آثار منفی بزرگی بر منابع آب و محیط‏های وابسته به آن می‏گذارد و در برخی سال‏ها خسار‌ت‌های جبران‌ناپذیری را سبب می‏‌شود. یکی از انواع مهم این پدیده، خشکسالی آب زیرزمینی است که بر اثر تغذیۀ ناکافی آبخوان‏ها به‌وجود می‏آید. هدف از این مطالعه بررسی تأثیر خشکسالی و مدیریت منابع آب زیرزمینی دشت دیر‌ـ آبدان در استان بوشهر است. برای این کار از آمار و داده‏هایی مانند بارندگی، تراز سطح آب زیرزمینی، نتایج آنالیز شیمیایی چاه‏های پایش کیفی و دبی چاه‏های بهره‏برداری استفاده شده است. وضعیت خشکسالی با استفاده از شاخص بارش استاندارد (SPI) و شاخص‏ منبع آب زیرزمینی (GRI) بررسی شده است. در این تحقیق شاخص جدیدی به نام شاخص مدیریت خشکسالی هیدروژئولوژیکی (HDMI) معرفی شده است. این شاخص ترکیبی از شاخص منبع آب زیرزمینی (GRI)، شاخص اصلاح‌شدۀ هدایت الکتریکی (MSECI) و شاخص استاندارد‌شدۀ دبی چاه‏های بهره‏برداری (SWDI) است. بر اساس نتایج به‌دست‌آمده میانگین شاخص خشکسالی آب زیرزمینی کمتر از 1- است. این موضوع نشان‏دهندۀ خشکسالی آب زیرزمینی با شدت متوسط است. این خشکسالی سبب تخریب کیفیت آب زیرزمینی نیز شده است. با توجه به شاخص MSECI، بحرانی‏ترین بخش آبخوان مناطق جنوبی آن است. از دیدگاه پتانسیل کمی آبخوان (شاخص SWDI) نیز مناسب‏ترین بخش آبخوان مناطق شمالی آن است. بر اساس میزان شاخص مدیریت خشکسالی هیدروژئولوژیکی، کمترین میزان شاخص HDMI (کمتر از 4-) در بخش جنوبی محدودۀ دیر‌ـ آبدان و در مجاورت خلیج فارس دیده می‏شود، بنابراین بهره‏برداری از آبخوان در این مناطق توصیه نمی‏شود.   1 Drought has major negative effects on water resources and its related environments. Sometimes the drought damages are irreparable. Groundwater drought is one of the most important droughts caused by insufficient groundwater recharge. This study aims to evaluate the effect of drought on groundwater resources of  Dayyer-Abdan district, south of Boushehr province. Data and information such as rainfall, groundwater level, well discharge rates and groundwater quality data were used for this purpose. The Standardized Precipitation Index (SPI) and Groundwater Resource Index (GRI) were used to assess the drought situation. A new index called Hydrogeological Drought Management Index (HDMI) is introduced in this research. The HDMI index is a combination of Groundwater Resource Index (GRI), the Modified Standardized Electrical Conductivity Index (MSECI) and Standardized Well Discharge Index (SWDI). Based on the obtained results, average of GRI index is less than -1, indicating a moderate groundwater drought. Groundwater drought also has destroyed the groundwater quality. From the groundwater quality view point (MSECI index), the most critical zone of the aquifer is located in the southern part of the study area. From the aquifer potential view point (SWDI index), the most suitable groundwater zone is in the northern parts of the study area.  The southern parts of the Dayyer-Abdan district (adjacent to the Persian Gulf) have the lowest amounts of HDMI index (less than -4). So  exploitation of groundwater is not recommended in these areas. 737 748 محمد فاریابی Muhammad Faryabi استادیار دانشکدۀ منابع طبیعی، دانشگاه جیرفت، جیرفت Iran faryabi753@yahoo.com جابر مظفری زاده Jaber Mozaffarizade دانشجوی دکتری هیدروژئولوژی، بخش علوم زمین، دانشگاه شیراز، شیراز Iran mozaffarizade-j@yahoo.com Groundwater Drought hydrogeological drought management index (HDMI) Dayyer-Abdan district ]. Fayabi M, Kalantari N. Evaluation of drought phenomena in Rod e Zard basin, Khuzestan province. 10th seminar on irrigation and evaporation decrease. 2009. [Persian].##[2]. 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0 ارزیابی نقش طرح پخش سیلاب سرچاهان‌ـ هرمزگان در تغذیۀ مصنوعی آب زیرزمینی Evaluation of the role of Sarcahan-Floodwater spreading in the artificial groundwater recharge https://ije.ut.ac.ir/article_62507.html 10.22059/ije.2017.62507 0 اگرچه بیشتر اقلیم کشور ایران خشک و نیمه‌خشک است، سالانه حجم شایان توجهی آب از طریق سیلاب‏ها از دسترس خارج می‏شود. بنابراین، سامانه‏های پخش سیلاب برای کنترل سیل و مواجهه با کم‏آبی قریب به سه دهه است که در کشور اجرا می‏شوند. هدف از این پژوهش، بررسی تأثیر شبکۀ پخش سیلاب منطقۀ سرچاهان استان هرمزگان بر تغذیۀ مصنوعی سفرۀ آب زیرزمینی با استفاده از راهکار حجم کنترلی است. سامانۀ پخش سیلاب یادشده در عرصه‏ای به مساحت 840 هکتار اجرا شده است. پس از بررسی آب‌نمود چاه‏ها، آب‌نگار بارش و حجم سیلاب‏های واردشده به سیستم، با بررسی نوسانات سطح آب زیرزمینی در چاه‏های مشاهده‏ای، تأثیر طرح پخش سیلاب در تغذیۀ مصنوعی سفرۀ آب زیرزمینی بررسی شد. نتایج نشان داد تراز آب زیرزمینی در چاه‏های مشاهده‏ای واقع در عرصه، بعد از سیل‏گیری‏های اولیه افزایش نسبی داشته‏اند به‌طوری که آب‌نمود چاه مشاهده‏ای واقع در عرصۀ پخش، افزایش شایان توجهی حدود 34/1 متر را نشان می‏دهد. همچنین، تغییرات سطح آب زیرزمینی در محدوده حجم کنترل با روند تغذیه/برداشت کاملاً همخوانی دارد و بر همین اساس در سال 1386 سطح آب زیرزمینی به میزان 43/4 متر افزایش داشته است. نتایج بررسی‏ها نشان داد در دشت گهکم-سعادت‏آباد، بارندگی‏های با بیش از 60 میلی‏متر یا بارش‏های متوالی با مقادیر زیاد، به تغذیه در عرصۀ پخش سیلاب منجر می‏شوند. در مجموع، نتایج تحقیق نشان داد پروژۀ پخش سیلاب سرچاهان در سال‏های بررسی‌شده نتوانسته است در حد انتظار سهم تغذیه را به شکل معنا‏داری افزایش دهد.     1 Despite the arid and semi-arid climate of Iran, a considerable volume of water becomes out of reach by annual flash flood events. Therefore, in order to solve the problem, Floodwater Spreading Systems have been implemented approximately over the past three decades. The aim of this study was to evaluate quantitative changes of the groundwater affected by the Sarcahan floodwater spreading which was implemented in Hormozgarn Province using Control Volume technique. Sarcahan floodwater spreading project has been implemented in an area of 2000 hectares. The well-hydrographs, rainfall histographs, and the fluctuation of groundwater at observation wells synchronizing with the frequency of flooding were used to evaluate the effect of the project on the groundwater. Examined observation wells showed a relative increase in the level of groundwater after the primarily flood controlling; in other words, the hydrograph of observation well located in the area of flooding has considerably increased by about 1.34 meters. Groundwater levels changes recorded at the observation wells are quite similar to the feeding/withdrawing ratio whereas in 2008 groundwater level increased by about 4.43 meters. Furthermore, in the Gahkom-Saadatabad the amount of rain more than 60 mm or continuous rainfall in large quantities can artificially recharge the aquifer. The results indicated that the Sarcahan project has not satisfactory effect on the groundwater according to predictions. 749 761 اباذر مصطفائی Abazar Mostafaei دکتری آب‌شناسی، پژوهشکدۀ حفاظت خاک و آبخیزداری، سازمان تحقیقات، آموزش و ترویج کشاورزی Iran abazar.mostafaei@gmail.com وحیده مرادنیا Vahideh Moradniya کارشناس ارشد آب زیرزمینی، پژوهشکدۀ حفاظت خاک و آبخیزداری، سازمان تحقیقات، آموزش و ترویج کشاورزی Iran vahidehmoradniya@gmail.com مسعود گودرزی Masoud Godarzi استادیار، پژوهشکدۀ حفاظت خاک و آبخیزداری، سازمان تحقیقات، آموزش و ترویج کشاورزی Iran massoudgoodarzi@yahoo.com Groundwater level Artificial recharge control volume fluctuation Sarcahan منابع##[1]. Kowsar S.A. Abkhandari (Aquifer Management): a Green Path to the Sustainable Development of Marginal Drylands. Journal of Mountain Science, 2005;2 (3): 233-243.##[2]. Ghahari G, Hashemi H, Berndtsson R. SPATE IRRIGATION OF BARLEY THROUGH FLOODWATER HARVESTING IN THE GAREH-BYGONE PLAIN, IRAN. IRRIGATION AND DRAINAGE. 2014; 63:599–611.##[3]. DAMAB(Basic Studies Department of Water Resources). Report of the plains country's ban. ABFA and Technical Office, Ministry of Energy. 2015. Tehran, Iran(In Persian).##[4]. Hashemi H, Berndtsson R, Persson M. Artificial recharge by floodwater spreading estimated by water balances and groundwater modelling in arid Iran. hydrological Sciences Journal – Journal des Sciences Hydrologiques. 2014; 60:336-350.##[5]. Kheirkhah Z.M. Decision Support System for Floodwater Spreading Site Selection in Iran..Ph.D thesis, Wageningen University, the Netherlands, 2005; 90-8504-256-9.##[6]. Kowsar S.A. Desertification Control through Floodwater Harvesting: The Current State of Know-How. In C. Lee & T. Schaaf (Eds.), The Future of Drylands. 2008. p. 229-241##[7]. Mostafaei A, Kalantari N, Kheirkhah M. Assessing the success of floodwater spreading projects using a fuzzy approach. Water Science and Technology. 2016;74(8):1980-1991.##[8]. Lotfollahzadeh D, ZarehMehrjerdi M, Kamali K. Investigation the effects of floodwater spreading on some soil properties at Sarchahan station, Hormozgan province. Pajouhesh & Sazandegi. 2007;76: 82-87 (In Persian).##[9]. Saadati H, Khayyam M. Survey of Flood water Spreading on quantitative changes of Vegetation Cover and Groundwater Recharge by Remote Sensing and GIS in Tasouj Aquifer in East Azarbayjan.Territory. 2009;5(19): 1-10) (In Persian).##[10].  Barkhordari J, Tireh‏ Shabankareh K, Mehrjerdi MZ, Khalkhali M. 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The Ninth National Conference on Watershed Management Science and Engineering Iran. 2013; Yazd (In Persian)##[19].  Viskarami K, Payamani A, Shahkarami A, Sepahvand A. The Effects of Water spreading on Groundwater Resources in Kohdasht Plain. J. Sci. & Technol. Agric. & Natur. Resour. Water and Soil Sci. 2013;17(65):153-161 (In Persian).##[20].  Pakparvar M, Walraevens K, Cheraghi SAM, Ghahari G, Cornelis W, Gabriels D, Kowsar SA. Assessment of groundwater recharge influenced by floodwater spreading: an integrated approach with limited accessible data. Hydrological Sciences Journal. 2017; 62(1): 1-18.##[21].  Bouwer H. Artificial recharge of groundwater: hydrogeology and engineering. Hydrogeology Journal 2002;10(1):121-142.##[22].  Singh SK. Groundwater Mound due to Artificial Recharge from Rectangular Areas. JOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING. Journal of Irrigation and Drainage Engineering. 2012;138(5):476-481.##[23].  Karamouz M, Ahmadi A, Akhbari M. Groundwater Hydrology: Engineering, Planning, and Management, CREC Press, Taylor & Francis Group. 2012;13 ISBN:978-1-4398-9121-6.##[24].  Glover RE, Ground water movement. US Bureau of Reclamation. Eng Monogr. 1964; 31, p 67.##[25].  Hantush MS. Growth and decay of ground water mounds in response to uniform percolation. Water Resour. Res. 1967; 3(1): 227–234.##[26].  Zaremehrjerdi M, Mahdian MH, Barkhordari J. Investigation the effect of floodwater spreading on soil infiltration in the Charcahan, Hormozgan. Iran-Watershed Management Science & Engineering. 2013;7(20):1-8 (In Persian).##[27].  Hemond HF, Fechner EJ. Chemical fate and transport in the environment. Accademic Press INC.USA. 1994; ISBN 0-12-340270-0. 331.##[28].  Warner JW, Molden D, Chehata M, Sunada DK. Mathematical analysis of artificial recharge from basins. Water Resour Bull. 1989; 25: 401- 411.##[29].   Mostafaei A, Kalantari N, Kheirkhah M. 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0 تبیین تحولات رخساره‌های هیدروشیمیایی آبخوان سراب با استفاده از روش‌های خوشه‌بندی میانگین فازی و تحلیل خوشه سلسله مراتبی Definition of Sarab Aquifer Hydrochemical Facies Distribution by means of Fuzzy C-Mean Clustering and Hierarchical Cluster Analysis Methods https://ije.ut.ac.ir/article_62624.html 10.22059/ije.2017.62624 0 در پژوهش حاضر، خوشه‏بندی مجموعه‏ای از داده‏های هیدروشیمیایی آبخوان سراب با استفاده از روش‏های خوشه‏بندی C-میانگین فازی (FCM) و تحلیل خوشۀ سلسله‌مراتبی (HCA) انجام شده و کاربرد آنها در تبیین رخساره‏های هیدروشیمیایی مطالعه شد. خوشه‏های آماری شباهت مکانی را بررسی می‏کنند و نشان می‏‏دهند خوشه‏ها مطابقت هیدروژئولوژیکی با رخساره‏های هیدروشیمیایی آبخوان دارند. نمونه‏های آب زیرزمینی با استفاده از بهینه‌کردن تعداد خوشه و درجۀ فازی‌شدگی با استفاده از روش C‌ـ میانگین فازی به چهار خوشه طبقه‏بندی شدند. از داده‏های 49 نمونه آب زیرزمینی و 12 متغیر هیدروشیمیایی منطقۀ مطالعه‌شده استفاده شد. نتایج این دو روش مراکز خوشه را تولید می‏کند که در تشخیص فرایندهای فیزیکی و شیمیایی تغییرات هیدروشیمی منطقۀ مطالعه‌شده مؤثر است. روش FCM روشی مناسب در تحلیل داده‏ها در بیان توزیع رخساره‏های هیدروشیمیایی است. نتایج نشان داد رویۀ خوشه‏بندی برای تخصیص نمونه‏های شیمیایی آب زیرزمینی به گروه‏های همگن توسط روش FCM ابزاری مهم در تشخیص رخساره‏های هیدروشیمیایی آبخوان است و این روش در تحلیل داده‏های مرزی، نسبت به روش HCA که تغییراتی واضح و ناگهانی دارد؛ تواناتر است.     1 In this research, clustering of a hydrochemical data set from Sarab plain aquifer has been carried out using Fuzzy C-Means (FCM) and Hierarchical Cluster Analysis (HCA) techniques and its application in delineation of hydrochemical facies has been studied. The statistical clusters analyze the spatial coherence indicating that that the clusters have a hydrogeological correspondence with aquifer hydrochemical facies. Groundwater samples were grouped into four classes using the fuzzy c-mean. The data set includes 49 water samples and 12 hydrochemical variables selected from the study area. The results obtained from both approaches presented cluster centers that can be used in order to identify the physical and chemical processes causing variations in the hydrochemistry variation of study area. The FCM method is potentially useful in establishing hydrochemical facies distribution. The results showed that the clustering scheme for partitioning water chemistry samples into homogeneous groups produced by FCM method is an important tool for determination of aquifer hydrochemical facies and the FCM method is more capable to investigate threshold data than HCA method which is characterized by sharp and abrupt variation. 763 773 میثم ودیعتی Meisam Vadiati دانشجوی دکتری، گروه علوم زمین، دانشکدۀ علوم طبیعی، دانشگاه تبریز، تبریز‌ Iran meysam.vadiati@gmail.com اصغر اصغری مقدم Asghar Asghari Moghaddam استاد، دانشکدۀ علوم طبیعی، دانشگاه تبریز، تبریز‌ Iran moghaddam@tabrizu.ac.ir محمد نخعی Muhammad Nakhaei استاد، دانشکدۀ علوم زمین، دانشگاه خوارزمی تهران، تهران‌ Iran nakhaeimohammad@gmail.com Groundwater hydrochemical facies Sarab Plain Clustering Fuzzy logic [1] Banoeng-Yakubo B, Yidana SM, Nti E. Hydrochemical analysis of groundwater using multivariate statistical methods—the Volta region, Ghana. KSCE Journal of Civil Engineering. 2009;13(1):55-63.##[2] Barbieri P, Adami G, Favretto A, Lutman A, Avoscan W, Reisenhofer E. Robust cluster analysis for detecting physico-chemical typologies of freshwater from wells of the plain of Friuli (northeastern Italy). Analytica Chimica Acta. 2001;440(2):161-70.##[3] Güler C, Thyne GD. Delineation of hydrochemical facies distribution in a regional groundwater system by means of fuzzy c‐means clustering. Water Resources Research. 2004;40(12).##[4] Güler C, Thyne GD, McCray JE, Turner KA. Evaluation of graphical and multivariate statistical methods for classification of water chemistry data. Hydrogeology journal. 2002;10(4):455-74.##[5] Zadeh LA. Fuzzy sets. Information and control. 1965;8(3):338-53.##[6] Taheri M. Introduction to Fuzzy set theory, second edition, Mashahd Jahad Daneshgahi, Inc; 1999 [Persian].##[7] Bezdek JC. Pattern Recognition with Fuzzy Objective Algorithms. Plenum Press New; 1981.##[8] Yousefi Rad M, Ahmadi M, Shafiei Haghshenas S. Mass rock clustering using C-Mean clustering. 4th National Proceeding of Economic Geology [Persian].##[9] Aghili R, Boromand Tesb S, Kahe M. The application of Fuzzy modeling based on C-mean clustering in estimation from evapotranspiration pan (Case study: Khuzestan Province). Soil and Water Conservation Researches. 2012:19(2)81-97 [Persian].##[10] Rantitsch G. Application of fuzzy clusters to quantify lithological background concentrations in stream-sediment geochemistry. Journal of Geochemical Exploration. 2000;71(1):73-82.##[11] Burrough PA, van Gaans PF, MacMillan RA. High-resolution landform classification using fuzzy k-means. Fuzzy sets and systems. 2000;113(1):37-52.##[12] Zhang CT, Chou KC, Maggiora GM. Predicting protein structural classes from amino acid composition: application of fuzzy clustering. Protein engineering. 1995;8(5):425-35.##[13] Azar E, Faraji H. Science of Fuzzy management, Ketabe Mehraban Nashr Press; 2006 [Persian].##[14] Jang JS. ANFIS: adaptive-network-based fuzzy inference system. IEEE transactions on systems, man, and cybernetics. 1993;23(3):665-85.##[15] Teshne Lab M, Safar Pour N, Afyouni D. Fuzzy systems and fuzzy control, Khaje Nasiredin Tousi Universty Press; 2007 [Persian].##[16] Hathaway RJ, Bezdek JC. Fuzzy c-means clustering of incomplete data. IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics). 2001;31(5):735-44.##[17] Zhang B, Song X, Zhang Y, Han D, Tang C, Yu Y, Ma Y. Hydrochemical characteristics and water quality assessment of surface water and groundwater in Songnen plain, Northeast China. Water research. 2012;46(8):2737-48.##[18] Davis, J.C. Statistics and data analysis in geology, New York: John Wiley and sons; 1986.##[19] Fetter, C.W. Contaminant hydrogeology, second edition, Prentic Hall, Inc; 1999.##

0 صحت‌سنجی روش‌های تحلیل سلسله‌مراتبی (AHP) و رگرسیون چند متغیره (MR) در پهنه‌بندی زمین لغزش (مطالعه موردی: حوزه آبخیر ولی‌عصر استان اردبیل) Verification methods of Analytical Hierarchy Process (AHP) and Multivariate Regression (MR) in landslide zoning (Case Study: Valiasr Watershed in Ardabil Province) https://ije.ut.ac.ir/article_62626.html 10.22059/ije.2017.62626 0 ارائۀ راه‏کارهای مفید برای پیشگیری و کاهش خسار‌ت‌های ناشی از زمین‌لغزش امری اجتناب‏ناپذیر است. از جملۀ این راه‏کارها، پیش‏بینی و پهنه‏بندی مناطق مستعد وقوع این حرکات است. بر همین اساس پژوهش حاضر به مقایسه و ارزیابی صحت دو روش تحلیل سلسله‌مراتبی (AHP) و رگرسیون چند‌متغیره (MR) در پهنه‏بندی خطر زمین‌لغزش در حوضۀ آبخیز ولی‏عصر با مساحت 198 کیلومتر‌مربع واقع در استان اردبیل پرداخت. شش عامل جهت جغرافیایی، شیب، ارتفاع، سنگ‏شناسی، کاربری اراضی و فاصله از رودخانه به‏عنوان مهم‏ترین عوامل مؤثر در وقوع زمین‌لغزش‏های منطقه شناخته شدند. در گام بعدی نقشه‏های پهنه‏بندی خطر زمین‌لغزش با هر دو روش AHP و MR در پنج طبقه تهیه شد. در نهایت، به‏منظور صحت‏سنجی دو روش استفاده‌شده، نقشه‏های تهیه‌شده با شاخص‏های نسبت تراکم (Dr) و شاخص مجموع کیفیت (Qs) مقایسه و ارزیابی شدند. نتایج نشان داد عوامل فاصله از رودخانه، جهت، شیب، کاربری اراضی، سنگ‏شناسی و ارتفاع به‌ترتیب با مقادیر 426/0، 173/0، 145/0، 134/0، 089/0 و 033/0 در روش تحلیل سلسله‌مراتبی و 531/0، 109/0، 344/0، 273/0، 123/0 و 061/0 در روش رگرسیون چند‌متغیره وزن‏دهی شدند. مقدار شاخص‏ نسبت تراکم و شاخص مجموع کیفیت به‏ترتیب، 51/5 و 44/0 برای روش‏ تحلیل سلسله‌مراتبی و 45/6 و 72/0 برای روش رگرسیون چند‌متغیره برآورد شد که نشان داد روش رگرسیون چند‌متغیره با میزان 28 درصد مغایرت با واقعیت صحت بیشتری نسبت به روش تحلیل سلسله‌مراتبی با 56 درصد مغایرت با واقعیت برای پهنه‏بندی خطر زمین‌لغزش در منطقۀ مطالعه‌شده دارد.         1 Providing effective solutions to prevent and reduce the damage caused by landslides is inevitable. Predicting and zoning landslides are among these solutions. Accordingly, the present study was conducted to compare and assess the accuracy of Analytical Hierarchy Process (AHP) and Multivariate Regression (MR) methods in landslide hazard zoning in Valiasr Watershed with an area of 198 km-2 located in western Ardebil Province. Six factors including aspect, slope, elevation, lithology, land use and distance from the river were known as the most effective factors in landslide occurrence in the study area. Landslide zones were then obtained in five classes using two AHP and MR methods. Finally, landslide zoning maps were compared and evaluated by Density ratio index (Dr) and Quality sum index (Qs) to assess the accuracy of two studied methods. The results showed that distance from river, slope, land use, lithology and height were weighting in 0.426, 0.173, 0.145, 0.134, 0.089, and 0.033 in the AHP methods and 0.531, 0.109, 0.344, 0.273, 0.123 and 0.061 in the MR method, respectively. The amount of two Dr and Qs indices were calculated to be 5.51 and 0.44 respectively in the AHP method and 6.45 and 0.72 respectively in MR method which indicated that MR method having 28% disagreement with reality was more accurate than AHP method having 56% disagreement with reality for landslide hazard in the study area. 775 789 محمد حسین قویمی پناه Mohammad Hossein Ghavimipanah دانشجوی کارشناسی‏ ارشد گروه مهندسی آبخیزداری، دانشکدۀ منابع طبیعی، دانشگاه تربیت ‏مدرس، نور Iran m.h.ghavimipanah1370@gmail.com عبدالواحد خالدی درویشان Abdulvahed Khaledi Darvishan استادیار گروه مهندسی آبخیزداری، دانشکدۀ منابع طبیعی، دانشگاه تربیت ‏مدرس، نور Iran a.khaledi@modares.ac.ir محمدرضا قویمی پناه Mohammad Reza Ghavimipanah دکتری تکتونیک‌ـ زمین‌شناسی، کارشناس زمین‏ شناسی شرکت طه (قرارگاه خاتم‌الانبیاء) Iran m.h.ghavimipanah1370111@gmail.com Density ratio index geographic information systems (GIS) mass movements quality sum index Petschko H, Brenning A, Bell R, Goetz J, Glade T. Assessing the quality of landslide susceptibility maps–case study Lower Austria. Nat. Hazards Earth Syst. Sci. 2014; 14(1): 95-118.‏##Oehorst BANO, Kjekstad D, Patel Z, Lubkowski JG, Knoeff G, Akkerman J. Determination of Socio-Economic Impact of Natural Disasters, Assessing socio-economic Impact in Europe, 2005; 173 p.##Agricultural Jihad Ministry. Landslide Study Group, Watershed, Ranges and Forests Organization. Report of Nation Landslide Database. 2004.##Gaprindashvili G, Van Westen CJ. Generation of a national landslide hazard and risk map for the country of Georgia. Nat. Hazards. 2016; 80(1): 69-101.‏##Pradhan B. An assessment of the use of an advanced neural network model with five different training strategies for the preparation of landslide susceptibility maps. J. Data Sci. 2011; 9(1): 65-81.‏##Pourghasemi HR, Moradi HR, Aghda SF, Gokceoglu C, Pradhan B. GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi-criteria evaluation models (North of Tehran, Iran). Arabian J. Geosciences. 2014; 7(5): 1857-1878.‏##Shahabi H, Khezri S, Ahmad BB, Hashim M. Landslide susceptibility mapping at central Zab basin, Iran: A comparison between analytical hierarchy process, frequency ratio and logistic regression models. Catena. 2014; 115: 55-70.‏##Sangchini EK, Emami SN, Tahmasebipour N, Pourghasemi HR, Naghibi SA, Arami SA, Pradhan B. Assessment and comparison of combined bivariate and AHP models with logistic regression for landslide susceptibility mapping in the Chaharmahal-e-Bakhtiari Province, Iran. Arabian J. Geosciences. 2016; 9(3): 1-15.‏##Das I, Sahoo S, Van Westen C, Stein A, Hack R. Landslide susceptibility assessment using logistic regression and its comparison with a rock mass classification system, along a road section in the northern Himalayas (India). Geomorphology. 2010; 114(4): 627-637.‏##Hyun-Joo O, Saro L. Cross-validation of logistic regression model for landslide susceptibility mapping at Ganeoung areas, Korea. Disaster Advances. 2010; 3(2): 44-55.‏##Bai S, Lü G, Wang J, Zhou P, Ding L. GIS-based rare events logistic regression for landslide-susceptibility mapping of Lianyungang, China. Environ. Earth Sci. 2011; 62(1): 139-149.‏##Yalcin A, Reis S, Aydinoglu AC, Yomralioglu T. A GIS-based comparative study of frequency ratio, analytical hierarchy process, bivariate statistics and logistics regression methods for landslide susceptibility mapping in Trabzon, NE Turkey. Catena. 2011; 85(3): 274-287.‏##Vasudevan N, Ramanathan K. Geological factors contributing to landslides: case studies of a few landslides in different regions of India. Earth Environ. Sci. 2016; 30(1): 012011.##Chang ZF, Chen XL, An XW, Cui JW. Contributing factors to the failure of an unusually large landslide triggered by the 2014 Ludian, Yunnan, China, Ms= 6.5 earthquake. Nat. Hazards Earth Syst. Sci. 2016; 16: 497-507.‏##Mia MT, Sultana N, Paul A. Studies on the Causes, Impacts and Mitigation Strategies of Landslide in Chittagong city, Bangladesh. J. Environ. Sci. Nat. Resour. 2016; 8(2): 1-5.‏##Pourghasemi HR, Moradi HR, Aghda SF. Landslide susceptibility mapping by binary logistic regression, analytical hierarchy process, and statistical index models and assessment of their performances. Nat. Hazards. 2013; 69(1): 749-779.‏##Motavali SA, Hosseinzade MM, Esmaeili R, Derafshi Kh. Landslide risk zoning assessment using Multivariate Regression (MR), logistic regression (LR), Analytical Hierarchy Process (AHP) and Fuzzy Logic (FL) (Case Study: Taleghan Watershed). Quantitative Geomorph. Res. 2014; 4(1): 1-20. (Persian)##Shiran k, Hajihashemijazi MR, Niknezhad SA, Rakhsha S. Landslide Risk Zoning Potential by Analytical Hierarchy Process (AHP) and Multivariate Regression (MR) (Case Study: Upstream of North Karoon Basin). Journal of Range and Watershed Management, Iranian J. Nat. Res. 2012; 65(3): 395-409.‏ (Persian).##Alkhasawneh MS, Ngah UK, Tay LT, Isa NAM. Determination of importance for comprehensive topographic factors on landslide hazard mapping using artificial neural network. Environ. Earth Sci. 2014; 72(3): 787-799.‏##Pourghasemi HR, Pradhan B, Gokceoglu C, Mohammadi M, Moradi HR. Application of weights-of-evidence and certainty factor models and their comparison in landslide susceptibility mapping at Haraz watershed, Iran. Arabian J. Geosciences. 2013; 6(7): 2351-2365.‏##Yalcin A. GIS-based Landslide Susceptibility Mapping Using Analytical Hierarchy Process and Bivariate Statistics in Ardesen (Turkey): Comparisons of results and confirmations. Catena. 2008; 72: 1-12.##Sharir K, Simon N, Roslee R. 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0 شبیه سازی توزیع دوبعدی سرعت جریان در رودخانه ها به کمک روش چیو (مطالعه موردی: رودخانه گرگان رود) Simulation of two-dimensional velocity distributions in rivers based on Chiu's theory (Case Study: Gorganrood River) https://ije.ut.ac.ir/article_62627.html 10.22059/ije.2017.62627 0 حل توزیع دوبعدی سرعت جریان در رودخانه‏ها (در جهات عرضی و عمقی) برای مدل‏سازی بسیاری از فرایند‏های هیدرولیکی از قبیل استخراج رابطۀ دبی‌ـ اشل رودخانه، محاسبۀ انتقال رسوب معلق و نیز تعیین تنش برشی مرزی نیاز است. در این تحقیق با استفاده از روش احتمالاتی چیو، روشی ساده برای شبیه‏سازی توزیع عرضی و قائم سرعت در رودخانه‏‏های مستقیم معرفی شده است. برای واسنجی و صحت‏سنجی این روش، ایدۀ جدیدی بر مبنای تخمین بهینۀ پارامتر آنتروپی در رودخانه به‌کار گرفته شد. نتایج تحقیق در ایستگاه هیدرومتری آق‏قلا واقع در رودخانۀ گرگان‌رود نشان داد میدان سرعت جریان به‏دست‌آمده از مدل چیو در مقایسه با داده‏های صحرایی دقت خوبی دارد. همچنین تحلیل آماری نتایج به‏دست‌آمده نشان داد میانگین خطای مطلق این مدل برای حل توزیع دوبعدی سرعت جریان در مراحل واسنجی و صحت‏سنجی به‏ترتیب حدود 2/5 و 5/3 درصد است. این میزان خطا برای تخمین دبی کل جریان رودخانه به‏ترتیب حدود 9/5 و 04/6 درصد است. با توجه به داده‏های اندک ورودی، این مدل مزیت عمده‏ای نسبت به سایر روش‏های موجود دارد.     1 Solution of stream-wise flow velocity in two dimensions (in width and depth directions) in rivers is essential for many hydraulic features such as stage-discharge rating curve development, suspended sediment transport estimation and boundary shear stress calculation. In this paper, using Chiu's entropy theory, a simple method has been proposed for simulation of vertical and transverse profiles of flow velocity in the straight rivers. For calibration and validation of the proposed method, a new idea based on the optimum estimation of entropy parameter in rivers was used. The results of this study at Aghghalla hydrometric station located on Gorganrood River showed that velocity flow field obtained by the Chiu's theory has suitable accuracy compared to the field data. Further, statistical analysis of the results revealed that the mean absolute errors of this method for solution of flow velocities in calibration and validation stages are 5.2% and 3.5%, respectively. These errors are 5.9% and 6.04% respectively for the total river flow discharge prediction. According to little input data, the proposed method has more advantage than other existing methods.      791 802 عبدالرضا ظهیری Abdolreza Zahiri دانشیار گروه مهندسی آب، دانشکدۀ مهندسی آب و خاک، دانشگاه علوم کشاورزی و منابع طبیعی گرگان Iran zahiri.areza@gmail.com فیروزه هاشمی Firoozeh Hashemi دانش ‏آموختۀ کارشناسی ارشد مهندسی عمران آب، دانشگاه آزاد واحد بندرعباس Iran hashemi.2714@yahoo.com ایمان یوسف آبادی Iman Yousefabadi دانش‏ آموختۀ کارشناسی ارشد مهندسی عمران آب Iran iman.yousefabadi@yahoo.com Chiu's theory probability Stage-discharge relationship vertical and transverse velocity distribution منابع##[1]. Chiu, CL, Entropy and probability concepts in hydraulics. Journal of Hydraulic Engineering. 1987 May 1; 113(5):583–600.##[2]. Kean, JW, Kuhnle, RA, Smith, JD, Alonso, CV, Longendoen, J. Test of a method to calculate near-bank velocity and boundary shear stress. Journal of Hydraulic Engineering. 2009 Feb 2; 135(7): 588-601.##[3]. Maghrebi, MF. Ball, JE. New Method for Estimation of Discharge. Journal of Hydraulic Engineering. 2006 Oct 1; 132(10): 1044-1051.##[4]. Seo, IW, Beak, KO. Estimation of the longitudinal dispersion coefficient using the velocity profile in natural stream. Journal of Hydraulic Engineering. 2004 Feb 19; 130(3): 227-236.##[5]. Chanson, H. The Hydraulics of open channel flow. An introduction basic principles, sediment motion, hydraulic modeling and design of hydraulic structures. Second Edition, Elsevier. 2004. 544 pp.##[6]. Chen, CL. An efficient method of discharge measurement. PhD Thesis, Dept. of Civil Engineering, University of Pittsburgh, PA. 1998. 345 pp.##[7]. Carlos, DJ, Chaudhry, FH. Experimental evaluation of 2-D entropy model for open-channel flow. Journal of Hydraulic Engineering. 1998 Oct 1; 124(10):1064-1067.## [8]. Ammari, A. Remini, B. Estimation of Algerian Rivers discharges based on Chiu’s equation. Arab Journal of Geosciences. 2010 Feb 6; 3:59–65.## [9]. 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0 واسنجی ضریب پریستلی تیلور در برآورد تبخیر از سطح آزاد آب (مطالعه موردی: مخزن سد مهاباد) Calibrating Priestley-Taylor coefficient to estimate free water surface evaporation (Case Study: Mahabad Dam Reservoir) https://ije.ut.ac.ir/article_62628.html 10.22059/ije.2017.62628 0 تبخیر تعرق واقعی یکی از مؤلفه‌های مهم بیلان آب هر حوضه است که اندازه‌گیری مستقیم آن در مقیاس حوضه امکان‌پذیر نیست و ناگزیر از روش‌های غیر‌مستقیم برآورد می‌شود. در این زمینه، مدل فرارفت خشکی که یکی از مدل‌های پرکاربرد از روابط مکملی است، بسیار مورد توجه قرار گرفته است. در مدل فرارفت خشکی به‌منظور زیادکردن دقت مدل، ضریب معادلۀ پریستلی‌ـ تیلور، به واسنجی نیاز دارد. هدف از این تحقیق، واسنجی ضریب پریستلی‌ـ تیلور در برآورد تبخیر پتانسیل با روش پنمن به‌منظور کاربرد آن در مدل فرارفت خشکی در حوضۀ دریاچۀ سد مهاباد است. داده‌های استفاده‌شده از ایستگاه سینوپتیک مهاباد که در فاصلۀ اندکی از سد مهاباد قرار دارد، برای طول دورۀ داده‌برداری 26 ساله (1365-1391) گردآوری شده است. نتایج مطالعه نشان می‌دهد این ضریب، تغییرات ماهانه در طول سال دارد و همچنین در ماه‌های گرم سال مقدار آن کاهش می‌یابد. بدین‌منظور بهتر است در محاسبات از مقادیر ماهانۀ آن استفاده شود. در منطقۀ مطالعه‌شده، مقدار میانگین کمینه و بیشینۀ این ضریب به‌ترتیب 01/1 و 68/1 به‌دست آمد. همچنین، میانگین 26سالۀ این ضریب برابر 25/1 محاسبه شده است.             1 Evapotranspiration is one of the important components of basin water balance which cannot be measured directly at the basin scale. Therefore, it is inevitably estimated through indirect methods. In this regard, the Advection Aridity model, one of the widely used models of complementary relationship, has attracted lots of attentions. Due to the existence of Priestley-Taylor equation in the Advection Aridity model, it is required to calibrate Priestley-Taylor coefficient to increase the accuracy of the model. The current research aims at calibrating Priestley-Taylor coefficient in estimation of potential evaporation through Penman method to apply it in the Advection Aridity model in the studied area of Mahabad dam reservoir, Iran. The required data were collected for a period of 26 years (1986-2012) from Mahabad 1st order meteorological station which is located a short distance from Mahabad reservoir. The results showed that Priestley-Taylor coefficient undergoes monthly changes during a year and decreases during the warm months of the year. Therefore, it is better to use its monthly values in calculations. In the area under study, its minimum and maximum averages were 1.01 and 1.68, respectively. Moreover, the long term average of this coefficient during a period of 26 years has been calculated to be 1.25. 803 815 آناهیتا قبادی Anahita Ghobadi دانشجوی کارشناسی ارشد گروه مهندسی محیط زیست، دانشکدۀ محیط زیست، واحد تهران غرب، دانشگاه آزاد اسلامی Iran ghobadi86a@yahoo.com پیمان دانشکار آراسته Peyman Daneshkar Arasteh دانشیار گروه علوم و مهندسی آب، دانشکدۀ فنی و مهندسی، دانشگاه بین‌المللی امام‌خمینی‌(ره)، قزوین Iran arasteh1348@yahoo.com سید مصطفی خضری Seyyed Mostafa Khezri دانشیار دانشکدۀ محیط زیست و انرژی، واحد علوم و تحقیقات، دانشگاه آزاد اسلامی Iran khezri@sharif.edu Priestley-Taylor coefficient Penman equation advection aridity model Bouchet hypothesis Mahabad dam reservoir Valizadeh Kamran Kh, Jahanbakhsh S, Zahedi M, Rezaee Banafsheh M. Actual evapotranspiration and its relation to land use analysis in GIS case study Meshkinshar city. Journal of Geographic Space. 2012; 37: 39-54 [Persian].##Poormohamadi S, Dastourani MT, Cheraghi SAM, Mokhtari MH, Rahimian MH. Evaluation and estimation of water balance components in dry areas by using remote sensing and GIS (Case Study: Yazd Manshad watershed). Journal of Water and Wastewater. 2011; 22(3): 99-108.##Bouchet RJ. Evapotranspiration Reelle et Potentielle Signification Climatique. International Assosciaton of Hydrological Sciences. 1963; 62: 134-142.##Brutsaert W, Stricker H. An advection aridity approach to estimate actual regional evapotranspiration.Water Resources Research. 1979; 15(2): 443-449.##Priestley CHB, Taylor RJ. On the assessment of surface heat flux and evaporation using large-scale parameters. Monthly Weather Review. 1972; 100(2): 81-92.##Arasteh PD, Tajrishy M. Calibrating Priestley Taylor model to estimate open water evaporation under regional advection using volume balance method case study Chahnimeh reservoir Iran. 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Forest categorization according to dry canopy evaporation rates in the growing season: comparison of the Priestley Taylor coefficient values from various observation sites. Hydrological Processes. 2005; 19(19): 3873-3896.##Allen RG, Pereira LS, Raes D, Smith M. Crop evapotranspiration guidelines for computing crop water requirements. Irrigation and Drainage FAO56. Rome. FAO. 1998.##www.wsanford.com/~wsanford/exo/sundials/DEC_Sun.html##Ulgen K, Hepbasli A. Solar radiation models Part 1: a review. Energy Sources. 2004; 26(5): 507-520.##Kamali GH, Moradi I. Solar radiation: fundamental and applications in agriculture and renewable energy. Atmospheric & Meteorological Research Center (ASMERC) Tehran. 2004 [Persian].##Penman HL. Natural evaporation from open water, bare soil and grass. Proceedings of the Royal Society of London Series A –Mathematical and Physical Sciences. 1948; 193: 193- 120.##Valiantzas J. 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0 مدل‌سازی مطلوبیت رویشگاه پسته ارگانیک (وحشی) (Pistacia vera) با استفاده از روش آنتروپی حداکثر(MaxEnt) در منطقه جنگلی سرخس (زیر حوزه گنبدلی استان خراسان رضوی) Habitat utility modeling of organic (wild) pistachios (Pistacia Vera) using Maximum Entropy Method (MaxEnt) in Sarakhs Forest Area (Gonbadli in khorasan Province) https://ije.ut.ac.ir/article_62636.html 10.22059/ije.2017.62636 0 پستۀ ارگانیک (وحشی) (Pistaciavera) از گونه‏های پهن‌برگ جنگلی است. یکی از رویشگاه‏های مهم جنگل طبیعی این گونه پسته در دنیا، در ایران و در استان خراسان رضوی (شمال غرب و جنوب غرب شهرستان سرخس) است. این جنگل علاوه بر خصوصیات اکولوژیکی منحصر‌به‌فرد، به‌دلیل ارزش اقتصادی پستۀ‏ ارگانیک تأثیر زیادی بر زندگی مردم منطقه و کشور دارد. متأسفانه به‌دلیل برداشت مستمر از یک سو و گسترش خشکسالی از سوی دیگر، حیات طبیعی این گونۀ منحصر‌به‌فرد و تجدید و توسعۀ آن به مخاطره افتاده است. درک پراکنش مکانی این گونه‏ که تأثیر بسزایی در ارزیابی حفاظت منطقه‏ای و توسعۀ آن دارد، موجب شناخت عوامل بوم‌شناختی تأثیر‌گذار در رویشگاه آن خواهد شد. بنابراین، مدل‏سازی این پراکنش بسیار مهم است. در این مطالعه با استفاده از روش آنتروپی ‏حداکثر براساس داده‏های ادافیکی، اقلیمی و فیزیوگرافی در شهرستان سرخس (زیر‌حوزۀ گنبدلی) به مدل‏سازی رویشگاه این گونه پرداخته شد. نتایج آزمون جکنایف در بررسی اهمیت متغیرها نشان داد تغییر در خصوصیات خاک مانند درصد سنگ‌ریزه، میزان نسبت جذب سطحی سدیم تبادلی؛ مقدار سدیم خاک؛ درصد گچ؛ عوامل اقلیمی (دما و بارندگی) و همچنین ارتفاع از سطح دریا؛ مهم‌ترین عوامل تأثیرگذار بر پراکنش رویشگاه هستند. دقت زیاد این مدل با ضریب کاپای برابر با 72/0 و AUC92/0 اثبات شد و نشان داد روش آنتروپی حداکثر برای مدل‌سازی رویشگاه مناسب است.       1 Organic (wild) Pistacia vera is a species of broadleaf forest. One of the most important natural forest habitats in the world is located at northwest and southwest of the city of Sarakhs, Khorasan Razavi Province, Iran. In addition, the unique ecological features of this habitat and the economic value of organic pistachio greatly impact the lives of people residing in this region and the country. Unfortunately, continuous overharvesting and drought-stricken development endanger natural life, regrowth and cultivation of this unique species. Understanding spatial distribution of this species plays a significant role in assessing regional protection and development; on the other hand, it can be helpful to recognize effective ecological factors on its habitat. Therefore, modeling this distribution is very important. In this paper, habitat modeling of this species is studied using maximum entropy method according to edaphic, climatic and physiographic data in the city of Sarakhs (in district of Gonbadli). The results of Jackknife test for surveying significance of variables shows that changes in soil properties such as gravel percentage, exchangeable sodium adsorption ratio, sodium content soil, gypsum, climatic factors (temperature and precipitation) and height above sea level are the most important factors affecting the distribution of habitats. The accuracy of model is assessed by kappa coefficient to be 0.72 and AUC 0.92. Moreover, the obtained  results reveal that maximum entropy method is an appropriate method for habitat modeling. 817 824 مهدی ضرابی Mahdi Zarabi استادیار دانشکدۀ علوم و فنون نوین دانشگاه تهران Iran mzarabi@ut.ac.ir رسول حقدادی Rasoul Haghdadi کارشناس ارشد رشتۀ اکوهیدرولوژی، دانشکدۀ علوم و فنون نوین دانشگاه تهران Iran rasoul.haghdadi@ut.ac.ir حسین یوسفی Hossein Yousefi استادیار دانشکدۀ علوم و فنون نوین دانشگاه تهران Iran hosseinyousefi@ut.ac.ir Organic (wild) Pistaciavera Maximum entropy habitat modeling Sarakhs (in district Gonbadli) E. Khosrojerdi, H. 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Soltani gerd faramarzi, "Habitat suitability modeling Eurotia ceratoides," Journal of Research Range, pp. 362-373, 2012, - [in Persian]##E. Pielou, "The use of point to plant distances in the study of the pattern of plant population," J.Ecology, vol. 47, pp. 607-613, 1959.##R. Anderson and E. Mart´ ınez-Meyer, "Modeling species’ geographic distributions for preliminary conservation assessments: an implementation with the spiny pocket mice (Heteromys) of Ecuador," Biol. Conser, vol. 116, pp. 167-179, 2004.##C. Graham, S. Ferrier, F. Huettman, C. Moritz and A. Peterson, "New developments in museum based informatics and applications in biodiversity analysis," Trends Ecol. Evol, vol. 19, pp. 497-503, 2004.##J. Elith, C. Graham, R. Anderson, M. Dudík, S. Ferrier, A. Guisan, R. Hijmans, F. Huettmann, J. Leathwick, A. Lehmann, J. Li, L. Lohmann, B. Loiselle and G. Manion, "Novel methods improve prediction of species’ distribution from occurrence data," Ecography, vol. 29, pp. 129-151, 2006.##A. Peterson and J. Shaw, "Lutzomyia vectors for cutaneous leishmaniasis in southern Brazil: ecological niche models, predicted geographic distribution, and climate change effects.," Int. J. Parasitol, vol. 33, pp. 919-931, 2003.##M. Zare chahoki, H. Piri sahragard and H. Azarnivand, "Habitat distribution model plant species in rangelands of Qom Sultan Hoz with maximum entropy method," Scientific Journal of Range, pp. 212-221, 2014, -[in Persian]##L. Khalasi ahwazi, M. Zare chahoki and s. z. Hosseni, "The geographic distribution of species habitat modeling Artemisia aucheri and Artemisia sieberi based on presence-based methods (MaxEnt and ENTFA)," Journal of Renewable Natural Resources Research, Vols. 57-73, p. 19, 2016, -[in persian]##D. Lemke, P. Hulme, J. Brown and T. W, "Distribution modelling of Japanese honeysuckle (Lonicera japonica) invasion in the Cumberland Plateau and Mountain Region, USA," Forest Ecology and Management, pp. 139-149, 2011.##H. Piri Sahragard and M. Zare Chahouki, "An evaluation of predictive habitat models performance of plant species in Hoze soltan rangelands of Qom province," Ecological Modelling, pp. 64-71, 2015.##S. Mahmoodi and M. Hakimian, Soil Fundamentals, Tehran: University of Tehran, 2008, - [Persian]##S. Phillips, K. Richardson, R. Scachetti-Pereira, J. Sober on, S. Williams, M. S. Wisz and N. E. Zammermann, "Novel methods improve predictions of species," Ecography, vol. 29, pp. 129-151, 2006.##

0 صحت سنجی روابط تعیین بارش مؤثر در مناطق پرباران و کم باران ایران (مطالعه موردی رشت و داران) Investigation of the determination relationship of effective rainfall in high rainfall and low rainfall zones (Case Study: Rasht and Daran) https://ije.ut.ac.ir/article_62638.html 10.22059/ije.2017.62638 0 با توجه به اهمیت حیاتی آب در زندگی بشر، شناخت دقیق کل باران و همچنین مقدار قابل استفاده یا مؤثر آن به‏منظور برنامه‏ریزی اقتصادی و آب مورد نیاز در صنعت، شرب و کشاورزی ضروری است. شناسایی و به‏کارگیری روشی مناسب برای برآورد بارش مؤثر به‌خصوص در کشت دیم اهمیت دوچندانی دارد. در پژوهش حاضر به‌منظور تعیین مناسب‏ترین روش تجربی برآورد بارش مؤثر در زراعت دیم، از داده‌های آماری بارندگی 20 ساله (1991 تا 2011) برای محصولات گندم، جو، نخود و عدس برای مناطق پربارش (رشت در استان گیلان) و نیز مناطق کم‌بارش (داران در استان اصفهان) استفاده شده است. در این پژوهش از پنج روش‏ تجربی مختلف تعیین بارش مؤثر از جمله: روش‏های سرویس حفاظت خاک ادارۀ کشاورزی ایالات متحده (SCS)، بارش قابل اطمینان، تجربی، وزارت کشاورزی ایالات متحده (USDA) و درصدی استفاده شده است. نتایج این ارزیابی نشان داده است در رشت همۀ روش‏های بارش مؤثر در زمینۀ کشت دیم قابل استفاده هستند، اما در داران، که یک منطقۀ کم‌باران است، برای استفاده از این روش‏ها لازم است که از قبل واسنجی شوند. نتایج نشان داده است به‏منظور اولویت‏بندی استفاده از روش‏های بررسی‌شده در این دو منطقه، روش‏های SCS و USDA برای رشت و روش‏های USDA و درصدی برای داران پیشنهاد می‏شود. از آنجا که میزان و زمان ریزش باران قابل کنترل نیست، می‏توان با به‌کارگیری تدابیری میزان کارایی بارش و در نتیجه بارش مؤثر را افزایش داد. از جمله می‏توان به کاهش رواناب سطحی، ذخیرۀ آب برای اوقات کم‌باران، کاهش عمق نفوذ آب و برنامه‏ریزی به‌منظور کشت گونه‏های منطبق بر رژیم بارش اشاره کرد.     1 Given the vital importance of water in human life, recognizing the effective use of rainfall and crop water requirement and economic planning are very important. Identifying and applying appropriate method for estimating effective rainfall, especially in rainfed is highly important. The current study aims to determine the most suitable experimental method for estimating effective rainfall for sowing Wheat, Barley, Peas and Lentils in high rainfall zones (Rasht in Gilan) as compared to low rainfall zones (Daran in Isfahan). In this study, five different experimental methods are presented in order to determine the effective rainfall including: the Soil Conservation Service (SCS), reliable method, empirical method, United States Department of Agriculture (USDA), and percentage method. The results show that all methods used for determination of  effective rainfall in Rasht are useful. However, these methods require to be pre-calibrated in order to determine the effective rainfall in Daran identified as a low rainfall area. Based on the obtained results, as regards prioritization of using the methods under study in these areas, SCS and USDA methods are proposed for Rasht, while the USDA and percentage methods are proposed for Daran. Since the amount and duration of rainfall is not controllable, effective strategies can be applied to increase   precipitation efficiency and consequently effective precipitation; these strategies include: reduction of surface runoff, water storage for times of low rainfall, reduced water depth penetration, and planning for the cultivation of plants that are consistent with the precipitation regime. 825 836 شمیم لاریجانی Shamim Larijani کارشناس ارشد آبیاری و زهکشی، گروه مهندسی آبیاری و آبادانی دانشگاه تهران، دانشکدۀ کشاورزی، دانشگاه تهران Iran shamim_larijani@ut.ac.ir محمد سالاریان Mohammad Salarian دانشجوی دکتری علوم و مهندسی آب، آبیاری و زهکشی، گروه علوم و مهندسی آب، دانشکدۀ کشاورزی، دانشگاه فردوسی مشهد Iran mohammad.salarian@mail.um.ac.ir امین علیزاده Amin Alizadeh استاد گروه علوم و مهندسی آب دانشکدۀ کشاورزی دانشگاه فردوسی مشهد Iran alizadeh@gmail.com تیمور سهرابی Teymour Sohrabi استاد گروه مهندسی آبیاری و آبادانی دانشکدۀ کشاورزی دانشگاه تهران Iran myousef@ut.ac.ir Effective Rainfall Runoff Experimental USDA SCS Rahimi J, Khalili A and Bazrafshan J. 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0 اثر رگبارهای متوالی بر مولفه‌های فرسایش پاشمانی طی دو شدت مختلف بارندگی در شرایط آزمایشگاهی Effects of consecutive storms on splash erosion components for two different rainfall intensities under laboratory conditions https://ije.ut.ac.ir/article_62640.html 10.22059/ije.2017.62640 0 واضح است که هیچ فرسایشی اتفاق نمی‏افتد مگر اینکه ابتدا جدایش توسط قطرات باران یا رواناب رخ دهد. فرسایش ناشی از اثر قطرات باران (RIIE) در نتیجۀ انرژی قطرات باران اتفاق می‏افتد. بدین‌منظور مجموعه‏ای از آزمایش‏ها برای بررسی اثر رگبارهای متوالی بر مؤلفه‏های RIIE (مانند پاشمان بالادست، پاشمان پایین‏دست، پاشمان خالص، پاشمان کل و نسبت پاشمان بالادست/پایین‏دست) برنامه‏ریزی شد. آزمایش‏ها تحت شدت‏های بارندگی 30 و 90 میلی‏متر در ساعت و در شیب پلات 5 درصد روی یک نمونه خاک جمع‏آوری‌شده از مراتع حوضۀ آبخیز کجور در شمال ایران در شرایط شبیه‏ساز باران و فرسایش خاک انجام پذیرفت. طبق نتایج مقایسۀ مؤلفه‏های پاشمان بالادست با پایین‏دست در شدت بارندگی 30 و همچنین در شدت بارندگی 90 میلی‏متر در ساعت در توالی‏های مختلف دلالت بر نبود اختلاف معنا‏دار در آنها (05/0 > P) با استفاده از آزمون تحلیل واریانس یک‏طرفه در نرم‌افزار آماری SPSS نسخۀ 22 داشته است. همچنین تحلیل نتایج مقایسه‏ای مؤلفه‏های RIIE شامل پاشمان بالادست، پاشمان پایین‏دست و پاشمان کل در توالی سوم، چهارم و پنجم در دو شدت بارندگی 30 و 90 میلی‏متر در ساعت در سطح 95 درصد معنا‏دار بود. در حالی ‏که پاشمان خالص و نسبت بالادست/ پایین‏دست تحت شدت‏های بارندگی 30 و 90 میلی‏متر در ساعت در توالی‏های مختلف رگبار غیر‌معنا‏دار (05/0 ≥ P) بوده است. همچنین نتایج بیان‌کنندۀ افزایش 5/2 برابری ضریب تغییرات پاشمان خالص و کل در شدت بارندگی 30 میلی‏متر در ساعت نسبت به 90 میلی‏متر در ساعت بود.       1 Obviously, no erosion occurs unless detachment takes place first, either by raindrop or runoff. The Raindrop-Impact-Induced Erosion (RIIE) occurs when detachment is caused by raindrop energy. For this purpose, a set of laboratorial experiments were scheduled to examine the effects of consecutive storms on RIIE components (i.e. upward splash, downward splash, net splash, total splash and upward splash/downward splash). The experiments were conducted for two different rainfall intensities of 30 and 90 mm h−1 at slope of 5% under rainfall simulation and soil erosion for a soil collected from Kojour rangeland watershed in the Alborz Mountains, northern of Iran. The comparative analysis of the results showed that there was no significant difference between upward with downward splash under rainfall intensity of 30 as well as under rainfall intensity of 90 mm h−1 in consecutive storms (p ≤ 0.05) using One-Way ANOVA in SPSS Statistics 22 software. In addition, the obtained results indicated that RIIE components viz. total and upward and downward splash were significantly different (p ≤ 0.01) under rainfall intensities of 30 and 90 mm h−1 in the third, fourth and fifth consecutive storms. However, net splash and upward/downward splash proportion was not significantly different (p > 0.05) under rainfall intensities of 30 and 90 mm h−1 in different consecutive storms. The results also indicated a 2.5-fold increase in coefficient of variation of net splash and total splash under rainfall intensity of 30 mm h-1 then the rainfall intensity of 90 mm h-1. 837 846 محبوبه کیانی هرچگانی Mahboobeh Kiani-Harchegani دانش ‏آموختۀ دکتری گروه مهندسی آبخیزداری، دانشکدۀ منابع ‏طبیعی، دانشگاه تربیت مدرّس و عضو انجمن آبخیزداری ایران Iran mahboobeh.kiyani20@gmail.com سید حمیدرضا صادقی Seyyed Hamidreza Sadeghi استاد گروه مهندسی آبخیزداری، دانشکدۀ منابع ‏طبیعی، دانشگاه تربیت مدرس Iran sadeghi@modares.ac.ir Event Storm Rainfall simulation splash cup net splash [1]. Terry JP. A rain splash component analysis to define mechanisms of soil detachment and transportation. Aust. J. Soil Res. 1998; 36: 525–542.##[2]. Kinnell PIA. Raindrop impact induced erosion processes and prediction: A review. Hydrol. Process. 2005; 19: 2815–2844.##[3]. Kinnell PIA. The influence of raindrop induced saltation on particle size distributions in sediment discharged by rain-impacted flow on planar surfaces. Catena. 2009;78(1): 2-11.##[4]. Kinnell, PIA. A review of the design and operation of runoff and soil loss plots. Catena. 2016; 145, 257-265.##[5]. Ellison WD. Studies of raindrop erosion. Agri. Eng. 1944; 25 (4): 131–136.##[6]. Ekern PC. Raindrop impact as a force initiating soil erosion. Soil Sci. Soc. Am. Proc. 1950; 15: 7–10.##[7]. Morgan RPC. Field studies of rainsplash erosion. Earth Surf. Process. 1978; 3: 295–299.##[8]. Bryan RB. The influence of slope angle on soil entrainment by sheetwash and rainsplash. Earth Surf. Process. 1979; 4: 43–58.##[9]. Torri D, Poesen J. The effect of soil surface slope on raindrop detachment. Catena. 1992; 19: 561–578.##[10]. Fan JC, Wu MF. Effects of soil strength, texture, slope steepness and rainfall intensity on interrill erosion of some soils in Taiwan. In10th International Soil Conservation Organization meeting, Purdue University, USDA-ARS national soil erosion research laboratory. 1999; May.##[11]. Barry DA, Sander GC, Jomaa S, Heng BCP, Parlange JY, Lisle IG. Hogarth WL. Exact solutions of the Hairsine-Rose precipitation-driven erosion model for a uniform grain size soil. J. Hydrol. 2010; 389 (3–4): 399–405.##[12]. Parsons AJ, Lascelles B. Rainfall simulation in geomorphology. Earth Surf. Process. Land. 2000; 25(7): 679-689.##[13]. Legout C, Leguédois S, Le Bissonnais Y, Malam Issa O. Splash distance and size distributions for various soils. Geoderma. 2005; 124: 279–292.##[14]. Goebes P, Seitz S, Geißler C, Lassu T, Peters P, Seeger M, Nadrowski, K. Scholten T. Momentum or kinetic energy – How do substrate properties influence the calculation of rainfall erosivity? J. Hydrol. 2014; 517: 310–316.##[15]. Fu S, Liu B, Liu H, Xu L. The effects of slope on interrill erosion at short slopes. Catena. 2011; 84: 29-34.##[16]. Ma RM, Li ZX, Cai CF, Wang JG. The dynamic response of splash erosion to aggregate mechanical breakdown through rainfall simulation events in Ultisols (subtropical China). Catena. 2014; 121: 279-287.##[17]. Khalili Moghadam B, Jabarifar M, Bagheri M, Shahbazi E. Effects of land use change on soil splash erosion in the semi-arid region of Iran. Geoderma. 2015; 241-242: 210-220.##[18]. Saedi T, Shorafa M, Gorji M, Khalili Moghadam. B, Indirect and direct effects of soil properties on soil splash erosion rate in calcareous soils of the central Zagross, Iran: A laboratory study. Geoderma. 2016; 271: 1-9.##[19]. Yusefi A, Farrokhian Firouzi A, Khalili Moghadam BEvaluation of temporal variation of splash erosion in different slopes and agricultural and forest land uses. J. Soil Water Resour. Conserv. 2014; 3(3): 11-20. (In Persian)##[20]. Khaledi Darvishan A, Sharifi Moghadam E. Effects of aggregate diameter on soil splash under laboratorial conditions. Iran-Water. Manag. Sci. Eng. 2016; 10(32): 33-38. (In Persian)##[21]. Sadeghi SHR, Kiani Harchegani M, Asadi H. Variability of particle size distributions of upward/downward splashed materials in different rainfall intensities and slope. Geoderma. 2017; 290: 100-106.##[22]. Kiani Harchegani M, Sadeghi SHR, Asadi H. Comparative analysis of the effects of rainfall intensity and experimental plot slope on raindrop impact induced erosion (RIIE). J. Water Soil Res. 2016; 46 (4): 631–640. (In Persian)##[23]. Kiani Harchegani M, Sadeghi SHR, Asadi H. Changeability of concentration and particle size distribution of effective sediment in initial and mature flow generation conditions under different slops and rainfall intensities, Iranian J Water. Eng. Manag. 2016; Accepted. (In Persian)##[24]. Mahdavi M. Applied Hydrology, Tehran University Press. 2002; 2: 437. (In Persian)##[25]. Abdollahi Z, Sadeghi SHR, Khaledi Darvishan A. Variation of simulated rainfall characteristics by permuting intake discharge and water pressure. Iran. Water. Manag. Sci. Eng. 2016; 10(34): 51-62. (In Persian)##[26]. Khaledi Darvishan A, Sadeghi SHR, Homaee M, Arabkhedri M. Measuring sheet erosion using synthetic colorcontrast aggregates. Hydrol. Process. 2014; 28(15): 4463-4471.##[27]. Kiani Harchegani M, Sadeghi SHR, Asadi H. Inter-storm variability of coefficient of variation of runoff volume and soil loss during rainfall and erosion simulation replicates, J. Ecohydrol. 2017; 4(1): 191-199. (In Persian)##[28]. Agassi M, Bradford JM. Methodologies for interrill soil erosion studies. Soil Till. Res. 1999; 49:277–287.##[29]. Sadeghi SHR, Kiani Harchegani M. Effects of sand mining on suspended sediment particle size distribution in Kojour forest river, Iran. J Agri. Sci. Tech. 2012; 14: 1637-1646.##[30]. Bayazidi A, Oladi B, Abbasi N. Data analysis by SPSS (PASW) 18 software. Abed Publication. 2009; 1: 250 p. (In Persian)##[31]. Le Bissonnais Y. Aggregate stability and assessment of soil crustability and erodibility: I. Theory and methodology. Euro. J. Soil Sci. 1996. 47: 425-437.##

0 اثر تغییر اقلیم بر دما و بارش سالانه استان زنجان با بررسی عدم قطعیت‌ها Climate change impact on annual precipitation and temperature of Zanjan province with uncertainties investigation https://ije.ut.ac.ir/article_62641.html 10.22059/ije.2017.62641 0 هدف از این تحقیق ارزیابی اثر تغییر اقلیم بر بارش و دمای میانگین مکانی استان زنجان در مقیاس سالانه با در‌نظر‌گرفتن عدم قطعیت‏‏ها‌ست. بدین‌منظور از مدل سالانۀ ARMA استفاده شد. سری‏های بارش و دمای سالانۀ میانگین مکانی استان محاسبه و سپس توسط مدل استوکستیک سالانه ARMA مدل‌سازی شد. 100 سری 30 سالۀ بارش و دمای سالانه برای میانگین مکانی استان تولید شد. توسط این مدل‏ها سناریوهای آیندۀ شش مدل GCM تحت سه سناریوی انتشار ریزمقیاس شد و برای هر سناریو، 100 سری 30 سالۀ بارش و دمای سالانۀ آینده تولید شد. با مقایسۀ دامنۀ 90‌ درصد آماره‏های دورۀ فعلی با دامنۀ 90‌ درصد مجموعه سناریوهای آینده، دامنۀ عدم قطعیت‏ها در نتایج بررسی شد. اعتبارسنجی مدل نشان از کفایت مدل برای شبیه‌سازی سری زمانی سالانۀ بارش و دما و کاهش مقیاس دارد. در حدود اطمینان 90 درصد، انتظار می‏رود دمای میانگین مکانی استان زنجان طی دورۀ 2035‌ـ 2064 از 6/0 تا 2/3 درجۀ سانتی‏گراد افزایش یابد و میانگین بارش از 25‌ درصد کاهش تا 15‌ درصد افزایش یابد. بر این مبنا عدم قطعیت‏های ناشی از ساختار مدل‏های GCM، نوسانات طبیعی اقلیم و سناریوهای انتشار شایان توجه است و لازم است در نظر گرفته شوند.     1 In this paper, climate change impact on annual precipitation and temperature series for Zanjan province was assessed and uncertainties were investigated. Spatial average of annual time series of precipitation and temperature for Zanjan province were calculated and then modelled using ARMA model and 100 annual precipitation and temperature series of length 30 years were generated for spatial average of Zanjan province. Using the models, future scenarios of 6 GCMs under 3 emission scenarios were downscaled and 100 annual precipitation and temperature series of length 30 years were generated for each of the scenarios. 90% bounds of the variable statistics for the current condition were compared with the 90% bounds of the corresponding values for all of the future scenarios and the uncertainties were investigated. Model validation showed that the models are adequate for generation of the annual temperature and precipitation series. In confidence level of 90%, it is expected that average temperature of Zanjan province increase from 0.6 to 3.2 ºC and average precipitation change from -25% to +15% in 2035-64 period. So, the uncertainty due to the GCMs structure and the emission scenarios are considerable and should be taken into account. 847 860 محمد رضا خزائی Mohammad Reza Khazaei استادیار، گروه مهندسی عمران، دانشگاه پیام نور Iran m_r_khazaee@yahoo.com مطلب بایزیدی Motalleb Bayazidi استادیار، گروه آب، دانشگاه آزاد اسلامی واحد سنندج Iran m.byzedi@gmail.com احمد شرافتی Ahmad Sharafati استادیار دانشکدۀ فنی و مهندسی، دانشگاه آزاد اسلامی واحد علوم و تحقیقات تهران Iran asharafati@gmail.com Annual model ARMA climate change stochastic Uncertainty 1. IPCC. Summary for Policymakers. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change; 2013.##2. IPCC. Climate change 2001. Impacts, Adaptation and Vulnerability. Contribution of Working Group II to the third assessment report of the Intergovernmental Panel on Climate Change. UK: Cambridge University Press; 2001.##3. Devkota L.P. and D.R. Gyawali. Impacts of climate change on hydrological regime and water resources management of the Koshi River Basin, Nepal. Journal of Hydrology: Regional Studies, 2015;4: 502–515.##4. Rana AK,FosterT,Bosshard J, Olsson and Bengtsson L. Impact of climate change on rainfall over Mumbai using Distribution-based Scaling of Global Climate Model projections. Journal of Hydrology: Regional Studies, 2014;1: 107–128.##5. Khazaei MR, Zahabiyoun B, and Saghafian B. Assessment of climate change impact on floods using weather generator and continuous rainfall-runoff model. International Journal of Climatology, 2012;32: 1997-2006.##6. Ahmadvand Kahrizi M, Rouhani H. Assessing the conservation impacts of climate change based on temperature projected on 21 century (Case study: Arazkoseh and Nodeh stations). Ecohydrology, 2017;3(4): 597-609 (in Persian).##7. Khazaei MR. Climate change impact assessment on hydrological regimes of a mountainous river basin in Iran. 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High-frequency and low-frequency variability in stochastic daily weather generator and its effect on agricultural and hydrologic modeling. Climatic Change, 2004;63: 145-179.##14. Khazaei MR, Ahmadi S, Saghafian B, and Zahabiyoun B. A new daily weather generator to preserve extremes and low-frequency variability. Climatic Change, 2013;119:631–645.##15. Reaney SM, andFowler HJ. Uncertainty estimation of climate change impacts on river flow incorporating stochastic downscaling and hydrological model parameterisation error sources, BHS 10th National Hydrology Symposium, Exeter, 2008.##16. Minville M, Brissette F, and Leconte R. Uncertainty of the impact of climate change on the hydrology of a nordic watershed. Journal of Hydrology, 2008;358:70-83.##17. Semenov MA. Development of high-resolution UKCIP02-based climate change scenarios in the UK. Agricultural and Forest Meteorology, 2007;144: 127-138.##18. Wilby RL, DawsonCW, and BarrowEM. SDSM - a decision support tool for the assessment of regional climate change impacts. Environmental Modelling & Software, 2002;17: 147-159.##19. Mavromatis T. and HansenJW. Interannual variability characteristics and simulated crop response of four stochastic weather generators, Agricultural and Forest Meteorology, 2001;109: 283-296.##20. Hansen JWand MavromatisT. Correcting low-frequency variability bias in stochastic weather generators. Agricultural and Forest Meteorology,2001;109:297-310.##21. Salahi B, Goudarzi M, HosseiniSA. Predicting the temperature and precipitation changes during the 2050s in Urmia Lake Basin. Watershed Engineering and Management, 2017;8(4): 425-438 (in Persian).##22. Rezaee M, Nahtaj M, Moghadamniya A, Abkar A, Rezaee M. Comparison of Artificial Neural Network and SDSM Methods in the Downscaling of Annual Rainfall in the HadCM3 Modelling (Case study: Kerman, Ravar and Rabor). Water Engineering, 2015;8(24): 25-40 (in Persian).##23. Semiromi ST, Moradi H, Khodagholi M. Predicted changes in some of climate variables using downscale model LARS-WG and output of HADCM3 model under different scenarios. Watershed Engineering and Management, 2015;7(2): 145-156 (in Persian).##24. Liu Y, Wu J,Liu Y, Hu BX,Hao Y, Huo X, et al. Analyzing effects of climate change on streamflow in a glacier mountain catchment using an ARMA model. Quaternary International, 2015;358:137-145.##25. Salas JD, Delleur JW, Yevjevich V, Lane WL. Applied modeling of hydrologic time series. Water Resources Publications, Littleton, CO, p 484, 1980.##

0 مکان‌یابی آب‌خوان‌های نواحی مرتعی با تصاویر ماهواره‌ای (مطالعه موردی: دشت شهرستان قروه) Site selection of aquifers of Ghorveh pasture areas using satellite images https://ije.ut.ac.ir/article_62643.html 10.22059/ije.2017.62643 0 در سال‏های اخیر با توجه به کمبود آب سطحی و افزایش جمعیت و توسعۀ کشاورزی، توجه به آب‏های زیرزمینی و مدیریت و استخراج آن افزایش یافته است. آب‌های زیرزمینی یکی از منابع باارزش آب شیرین محسوب می‏شوند، به‌گونه‏ای که این منبع به یکی از منابع حیاتی باارزش تبدیل شده است. استخراج آب زیرزمینی در سال‏های اخیر به پایین‌رفتن سطح این آب منجر شده است، به‌طوری ‏که از سال‌های 1365 و 1366 تا پایان سال 1393 به مقدار 9/19 متر در دشت قروه رسیده است و این دشت را به یکی از دشت‏های ممنوعه از 625 دشت ممنوعۀ کشور تبدیل کرده است. در این پژوهش با کمک داده‏های دورسنجی و GIS مناطق دارای پتانسیل آب زیرزمینی شناسایی شد. لایه‏هایی که برای مکان‏یابی آبخوان در این پژوهش ایجاد شدند، زمین‏شناسی، توپوگرافی و شیب، خطواره و تراکم خطواره، زهکشی و شبکۀ زهکشی، کاربری اراضی و نقشۀ پوشش گیاهی هستند. در نهایت نقشۀ نهایی با کمک لایه‏های مربوط به آن با روش فازی در محیط GIS به‌دست آمد. نقشۀ به‌دست‌آمده به پنج گروه دارای پتانسیل خیلی خوب، خوب، متوسط، ضعیف و خیلی ضعیف تقسیم شد. نتایج نشان داد مناطق دارای پتانسیل خوب و خیلی خوب با مساحت 136461 هکتار که حدود نصف مساحت دشت یادشده است، بیشتر در قسمت‏های شمالی و شرقی و منطبق بر زمین‏های آبرفتی و دارای پوشش گیاهی و شیب پایین و مناطق دارای پتانسیل‏های کمتر، بیشتر در قسمت‏های جنوبی و بر مناطق پرشیب و دارای پوشش سنگی مستحکم منطبق‌اند.       1 Over the recent years, given lack of surface water, population growth, and agricultural development, more attention has been paid to underground water, its management and extraction. This source is considered as one of the valuable resources of freshwater making it as one of the most valuable vital resources. Groundwater extraction, over the recent years, has given rise to decreased water level of this resource, that is, its level has decreased by an amount of 19.9m in the plain of Qorveh since 1986, 1987 until 2015. Therefore, the plain has become one of the forbidden plains out of 625 country plains. In recent years, integrating data of remote sensing (RS) and geographic information system (GIS) has increased for exploration of this valuable material. So that the combination of these two has become a point in the fields related to the issue of water. In this study, using (RS) and (GIS), data of potential areas of groundwater were identified. Layers created for site selection of aquifer in this study are as follows: geology, topography, slope, lineament, density of lineament, drainage, density of drainage, land use and vegetation of cover. Then, the final map was obtained using respective layers by means of fuzzy method in gis. The resulted map was divided into five groups of very good, good, average, weak and very weak. The results showed that the areas with good and very good potential with an area of 136461 hectare forming about half of the area of plain under study are located more in northern and eastern parts characterized by alluvial lands, vegetation and low slope, while regions with lower potential are located more in southern parts characterized by high slope areas covered with rock solid. 861 871 یوسف صالحی Yousef Salehi دانشجوی کارشناسی ارشد سنجش از دور و GIS، دانشکدۀ محیط زیست و انرژی، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات تهران Iran yoosefsalehi66@yahoo.com زهرا عزیزی Zahra Azizi استادیار گروه سنجش از دور و GIS، دانشکدۀ محیط زیست و انرژی، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات تهران Iran zazizi@srbiau.ac.ir حسین آقامحمدی Hossein Aghamohamadi استادیار گروه سنجش از دور و GIS، دانشکدۀ محیط زیست و انرژی، دانشگاه آزاد اسلامی، واحد علوم و تحقیقات تهران Iran hossein.aghamohammadi@gmail.com GIS RS Site selection Aquifer Fuzzy منابع##[1]. Zehtabian G, Khosravi H, Ghodsi M. High Demand in a Land of Water Scarcity: Iran. In: Graciela SM, Courel MF, editor. Water and Sustainability in Arid Regions. 1th ed. Netherlands: Springer ; 2001.p. 75-86.##[2]. Alizadeh A. Principles of applied Hydrology. 35nd ed. Mashhad: Imam Reza University; 2012. [Persian].##[3]. Sedaghat M. Land and water resources (groundwater). 6nd ed. Tehran: Payame noor university; 2008. [Persian].##[4]. Jha M, Kamii Y, Chikamori K. Cost-effective Approaches for Sustainable Groundwater Management in Alluvial Aquifer Systems. Water Resources Management. 2010; 23(2):219-233.##[5]. Mehdipoor A, Mehdipoor S, Haj Seyed Ali Khani N. The history of the aqueduct and its impact on civilization Iranians. International Conference on the aqueduct. Kerman. Iran. 2005. [Persian].##[6]. Joven PA, Yamaguchi S, Takada J. Characterization of Groundwater Potential of Agusan del Norte,Philippines, Spring Conference, Tokyo Institute of Technology. Japan. 2010.##[7]. Iran Water Resources Management Company. Assessment situation of groundwater resources in the country By the end year of 2014-2015. 2016. [Persian].##[8]. Thilagavathi N, Subramani T, Suresh M, Karunanidhi D. Mapping of groundwater potential zones in Salem Chalk Hills,Tamil Nadu, India, using remote sensing and GIS techniques. Environmental Monitoring and Assessment. 2015; 187(4):1-17.##[9]. Pinto D, Shrestha S, Babel MS, Ninsawat S. Delineation of groundwater potential zones in the Comoro watershed, Timor Leste using GIS, remote sensing and analytic hierarchy process (AHP) technique. Applied Water Science. 2015; 6(22):1-17.##[10]. Yamani M, Alizadeh SH. Potential mapping of groundwater resources using Analytical Hierarchy Process(AHP) Case study Basin Abadeh- Oghli Fars. Hydrogeomorphology. 2015; (1):131-144. [Persian].##[11]. Mohammadnezhadarogh V, Sayyad A, Golmohammadzadeh B. Mapping of areas prone to water Ground using GIS and MIF(case study: Urmia city). Research quantitative geomorphology. 2013; 2(3):45-58. [Persian].##[12]. Report Map 1: 50,000 Geological Organization of Iran. [Persian].##[13]. Abshirini E, Rangzan K, Khorshidi S. Potential mapping of groundwater resources using Weighted index overlay method in GIS environment (Case Study: within the anticline Pabdeh). Conferences of Geomatics. Tehran. Iran.2008. [Persian].##[14]. Rahimi D. Potential mapping of groundwater resources (case study: plain of Shahrekurd) Geography and environmental planning. 2012;22(4):127-142. [Persian].## [15]. Nag sk. Application of Remote Sensing and GIS in Groundwater Exploration. In: Ahmad SH, Jayakumar R, Salih AB, editor. Groundwater Dynamics in Hard Rock Aquifers. Earth Sciences & Geography , 1th ed. India: Springer; 2008.p. 87-92.##[16]. Magesh NS, Chandrasekar N, Soundranayagam JP. Delineation of groundwater potential zones in Theni district, Tamil Nadu, using remote sensing, GIS and MIF techniques. Geoscience Frontiers. 2012;3(2):189-196.##[17]. Rezvani A. Use of aerial and satellite photographs in geography. 3nd ed. Tehran: Payame noor university; 2012. [Persian].##[18]. Ghodrati M. Applied Learning of ARC GIS 10.2. 1nd ed. Tehran: Simaye Danesh; 2014. [Persian].##[19]. French, N. H, Ijaz Hussain. Water Spreading Manual Range management Record, West Pakistan Range Improvement scheme, Lahur., Pakistan, 1964: No. 1, 44P.##[20]. Viskarami I, Payamani K, Shahkarami A. A., Sepahvand A. The Effects of Water spreading on Groundwater Resources in Kohdasht Plain. J. Sci. & Technol. Agric. & Natur. Resour., Water and Soil Sci., 2013: Vol. 17(65): 153-161.##[21]. Senser, E., Davraz, A., and Ozcelik, M.. An integration of GIS and remote sensing in groundwater investigations: a case study in Burdur, Turkey. International Journal of hydrogeology. 2004: 13: 826-834.##

0 بررسی روش‌های نوین احیاء چاه‌های آب به منظور استفاده عملیاتی در کشور Investigating modern methods of water wells rehabilitation for use in Iran https://ije.ut.ac.ir/article_62644.html 10.22059/ije.2017.62644 0 یکی از معضلات چاه‏ها پس از بهره‌برداری طولانی‌مدت از آنها، ایجاد رسوبات روی لولۀ جدار یا شیارهای گراول پشت لوله است. این رسوبات به‌رغم وجود آب در بستر آبخوان، از نفوذ آب به درون چاه جلوگیری می‌کند و بنابراین میزان آبدهی چاه را به‌شدت کاهش می‏دهد. احیای چاه‏ها حذف رسوبات ایجاد‌شده در لولۀ جدار است. از گذشته روش‏هایی برای احیای چاه‏ها وجود داشته است، ولی امروزه با گسترش علم، تکنولوژی‏های جدیدی توسعه یافته است که راندمان بهتری دارد و موجب آسیب کمتری به سفرۀ آب زیرزمینی و محیط زیست می‏‌شود. در این پژوهش ابتدا روش‏های نوین احیای چاه‏ها بررسی می‌شود. سپس معیارهایی برای تشخیص مؤثربودن هر یک از روش‏ها برای اجرا در کشور پیشنهاد می‌شود. در ادامه روش‏های مؤثر شوک سیال و جت آب به‌دلیل بازدهی زیاد و صرف زمان و هزینۀ کمتر، به‌عنوان روش‏های مناسب برای استفاده در کشور انتخاب و توصیه شده‏اند.     1 One of the problems associated with long term use of wells is creation of deposits on well screen or gravel packs. The deposits, despite the presence of water in the context of the aquifer, prevent the penetration of water into the well. As a result, it greatly reduces the amount of water production of the well. Rehabilitation of wells is characterized by removing the deposits from the front and back of the well screen. So far, there have been some methods of well rehabilitation, nowadays, however, with the development of technology, more efficient methods have been developed causing less damage to the aquifer and the environment. In this study, new methods of well rehabilitation are investigated for implementation in Iran. A criterion for determining the efficiency of the methods is proposed. The method of air shock in combination to water jet is estimated to be more efficient with less time and cost consumption for implementation in Iran. 873 886 علیرضا هادی Alireza Hadi استادیار، دانشکدۀ علوم و فنون نوین، دانشگاه تهران Iran hrhadi@ut.ac.ir حامد رحیمی شعرباف Hamed Rahimi Sharbaf دانشجوی کارشناسی ارشد، دانشکدۀ مهندسی مکانیک، دانشگاه تربیت مدرس Iran h.rahimi.sh@gmail.com علی طهماسبی Ali Tahmasbi شرکت آب و فاضلاب روستایی استان لرستان، خرم‏ آباد Iran aattrrgg@yahoo.com Well rehabilitation design well development air shock water jet منابع##[1] Mansuy N. Water Well Rehabilitation – A Comprehensive Guide to Understanding Problems and Solutions. 4th ed. Florida: CRC Press - Lewis Publishers; 1999.##[2] Sonic Umwelttechnik GmbH. Well Rehabilitation with high-energetic Ultrasound. Sonic Information No. E1-09. 2014.##[3] Driscoll F G. Groundwater and Wells. 2nd ed. Minnesota: Johnson Screens; 1986.##[4] Thullner M, Van Cappellen P, Reginer P. Modeling the impact of microbial activity on redox dynamics in porus media. Geochimica et Cosmochimica Acta. 2005; 69(21):5005-5019.##[5] Mansuy N, Miller G P. Preventive Well Maintenance Reduces Costs. Subsurface Technologies Inc.2014.##[6] Petrauskas A. Increasing the efficiency of water well regeneration with ultrasound by using acoustic transducers consisting of elements in flexural vibration. 2009; 64(3):1392-2114.##[7] Frac-Packer. Accessed on 2000. http://www.flatwaterfleet.com/html/frac_packers.html.##[8] Common well problems and basic rehabilitation approaches. Accessed on 18 July 2014. http://www.agr.gc.ca/eng/science-and-innovation/agricultural-practices/water/wells-and-groundwater/water-wells/well-rehabilitation/?id=1371571333366.##[9] Smith S A. Recent innovations in well rehabilitation. Accessed on April 1994. http://www.groundwaterscience.com/resources/tech-article-library/94-recent-innovations-in-well-rehabilitation.html.##[10] Reece R. Water well rehabilition technologies and well asset management. Utility Service Group; 2014.##[11] AQUA FREED & AQUA GARD Case Studies. Accessed on Jun 2013. http://www.subsurfacetech.com/aqua-freed-case-studies.##[12] Save thousands by jetting your well and not re-drilling. Accessed on 2000. http://www.mrbillspump.com/residential_and_commercial_water_well_jetting.php.##[13] Developing and rehabilitating well screens in sand and gravel wells. Accessed on 2000. http://www.flatwaterfleet.com/html/jetting_tool.html.##[14] Hydro fracturing. Accessed on 2009. www.highyieldwater.com/3.html.##[15] Say goodbye to low-yielding wells with hydro-fracturing. Accessed on 2000. http://foglepump.com/hydro-fracting/2450777.##[16] Well Rehabilitation with high-energetic Ultrasound. Sonic Umwelttecchnik. SONIC Information No. E1-09. 2009, Accessed on April 2017. www.sonic-umwelttechnik.de.##[17] Results from practical application. Sonic Umwelttecchnik. SONIC Information No.E3. 2009. Accessed on April 2017. www.sonic-umwelttechnik.de.##[18] Gipsou T C. Method and apparatus for downhole oil well production stimulation. 1994; US Patent No. 5297631.##[19] Jansen J R, Taylor R W, Frazier W C. Method for improved water well production, 1996; US Patent No. 5579845.##[20] Bi-Product – Residuals – Explosives Free. Water Well Solutions. 2012. Accessed on April 2017. http://www.wwssg.com##[21] Mefford B, Hanna L J. Model tests of air burst and hydraulic back-flush cleaning efficiency for a cook cylindrical screen. Model Test Summary Report. 1997.##[22] Air impulse rehabilitiation results by project. Municipal Well & Pump. 2011. Accessed on April 2017. www.municipalwellandpump.co##

0 بررسی میزان تولید رسوب معلق حوزه آبخیز زیارت، گرگان در فصل های مختلف با استفاده از تکنیک منشایابی رسوب Investigating suspended sediment yield in Ziarat Drainage Basin, Gorgan in different seasons using sediment fingerprinting technique https://ije.ut.ac.ir/article_62646.html 10.22059/ije.2017.62646 0 ‌فرسایش خاک جدی‏ترین و غیرقابل‏برگشت‏ترین تهدید برای توسعۀ پایدار به‌شمار می‏رود. با توجه به روند افزایشی نرخ فرسایش و تولید رسوب، هدف از این پژوهش تعیین سهم نسبی هریک از واحدهای فرسایشی سطحی و زیرسطحی در حوضۀ آبخیز زیارت گرگان در سه فصل پاییز، زمستان و بهار با استفاده از فن منشأیابی رسوب است. بدین‌منظور تعداد 43 نمونه از منابع رسوب شامل کاربری‏های مرتع و کشاورزی (منابع سطحی) و کنار جاده و فرسایش کناره‏ای آبراهه (منابع زیرسطحی) و 14 نمونه از رسوبات معلق خروجی حوضه جمع‏آوری و غلظت 10 عنصر ژئوشیمیایی، به‌علاوۀ کربن آلی و سزیم 137 در نمونه‏ها اندازه‏گیری شد. با استفاده از آزمون‏های کروسکال والیس و تحلیل تشخیص ترکیب بهینه ردیاب‏ها تعیین شدند. درنهایت، با استفاده از مدل چندمتغیرۀ ترکیبی سهم نسبی هریک از منابع فرسایش در تولید رسوب در فصل‏های یادشده تعیین شد. نتایج نشان داد بیشترین سهم مربوط به فرسایش سطحی (کشاورزی و مراتع) در دو فصل زمستان و بهار است. همچنین فرسایش زیرسطحی (جاده و آبراهه) در فصل بهار با 4/60 درصد، میزان شایان ‏توجهی را به خود اختصاص داده است. نتایج این پژوهش می‏تواند در انتخاب روش مدیریت فرسایش و رسوب حوضۀ آبخیز زیارت در فصل‏های مختلف به‌کار آید.   1 Soil erosion is the most serious and irreversible threat to sustainable development. According to the increasing rate of soil erosion and sediment yield, the current study aimed to determine relative contribution of sediment sources in Ziarat catchment in fall, winter and spring seasons using sediment fingerprinting technique. In this regard, 43 samples from sediment sources including rangeland and cultivated land as surface erosion and stream bank and road verges as sub-surface erosion as well as 14 samples of suspended sediment at outlet of catchment were collected and concentration of geochemical tracers, organic carbon and 137Cs were measured. The optimum set of tracers was selected using the Kruskal-Wallis H test and discriminant function analysis. Finally, the relative contribution of sediment sources was determined through mixing model in different seasons. The results showed that the maximum relative contribution was related to surface erosion in winter and spring seasons. Sub-surface erosion in spring season with 60.4% also caused a large amount of sediment yield. The results of this study can be used to select the management strategies in soil erosion and sediment control of Ziarat catchment in different seasons. 887 895 کاظم نصرتی Kazem Nosrati دانشیار، دانشکدۀ علوم زمین، دانشگاه شهید بهشتی، تهران Iran k_nosrati@sbu.ac.ir سعیده جلالی Saeede Jalali کارشناس ارشد ژئومورفولوژی دانشگاه شهید بهشتی، تهران Iran jalali.sa.67@gmail.com Sediment fingerprinting seasonal erosion 137Cs Ziarat catchment منابع 1-     Morgan, R. P. C, Duzant, J. H. Modified MMF (Morgan–Morgan–Finney) model for evaluating effects of crops and vegetation cover on soil erosion. Earth Surface Processes and Landform. 2008,3: 3(1): 90 - 106##2-     Collins, A. L. Williams, L. J., Zhang, Y. S., Marius, M., Dungait, J. A. J., Smallman, D. J., Naden, P. S. Catchment source contributions to the sediment-bound organic matter degrading salmonid spawning gravels in a lowland river, southern England. Science of The Total Environment, 2001,3: 456: 181-195. 1.     Russel M. A., Walling D. E., and Hodgkinson R. A. Suspende sediment sources in two small lowland agricultural catchments in UK. Journal of Hydrology, 2003:252, 1-24 2.     Zapata F.. The use of environmental radionuclides as tracers in soil erosion and sedimentation investigation: Recent advances and future developments. Soil and tilage Research,2003: 69.3-13 3.     Hakimkhani Sh.. Investigation use of tracers in sediment tracing fluviall sediment, Poldasht station. Master science thesis. 2007.[In persian].##Koiter, A.,J., Lobb, D.A., Owens. P.N., Petticrew, E.L., Tiessen, K., Li, S.,. The behavioural characteris of sediment properties and their implications for sediment fingerprinting as an approach for identifying sediment sources in river basins. Earth sci. Rev. 2013. 125, 24-42##Walling D.E., The evolution of sediment sources fingerprinting investigations in fluvial system. Soils Sediments 2013: 13:1658-1675##Mabit L., Benmansour M., Abril J.M., Walling D,E., Meusburger K., Lurian A.R., Bernard C., Tarjan S., Owens P.N., Blake W.H., Alewell C. Fallout Pb210 as a soil and sediment tracering in catchment sediment budget investigation : a review Earth Sci. Rev. 2014:138:335-351##Walling D. E.,. Tracing suspende sediment sources in catchments and rivers systems, Science of the Total Environment. 2005: 334:159-184##Carreras N. M., Krein A., Gallart F., Iffly J. F., Pfister L., Haffman L., Owens P. N.,. Assessment of different parameter for discriminating potentioal suspende sediment sources and provenance: A multi scale study in Luxembourg. Geomorphology. 2010: 11:118-129##Collins A.L., Walling D. E., Leeks G. J. L.,. Fingerprinting the origin of fluvial suspended sediment in larger river basin: Combining assessment of spatial provenance and source type. Geografiska Annaler. 1997: 79(a): 239-254## Nostrati, K., Ascribing soil erosion of hillslope components to river sediment yield. Journal of Environmental Management. 2017: 194: 63-72##Tiecher T., Caner L., Minella J.P.G., Pellegrini A., Capoane V., Rasche J.W.A., Schaefer G.L., Rheinhimer D. Tracing sediment sources in two paired agricultural catchment with different riparian forest and wetland proportion in southern Brazil. Geoderma.2017:258:225-239##Zhao G., Mu X., Han M., An Z., Gao P., Sun W., Xu W.,. Sediment yield and sources in dam-controlled watershed on the northern Loess Plateau. Catena 2017:149:110-119##Du. P., Des E Walling.,. Fingerprinting surficial sources: Exploring some potential problems associated with the spatial variability of material properties. 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Hydrological Processes, 2012:24:1391-1403.##Gruszowski, K. E., Foster, I. D. L., Lees, J. A., & Charlesworth, S. M. Sediment sources and transport pathways in a rural catchment, Herefordshire, UK. Hydrological Processes, 2013: 17: 2665-2681.##Nosrati k, Govers G, Semmenes B.X, and Ward E,J.,. A mixing model to incorporate uncertainty in sediment fingerprinting. CATENA, 2014: 217: 173-180.##Rowan, J. S., Black, S. and Franks, S. W. Sediment fingerprinting as an environmental forensics tool explaining cyanobacteria blooms in lakes. Applied Geography, 2013: 32: 832-843.##D Haen K, Verstraeten G., Dusar B,. Degryse B., Heax J., Walkens M. Unravelling changing sediment sources in a Mediterranean mountain catchment Bayesian fingerprinting approach. HydrologicalProcesses. 2013: 27:896-927.##Carter, J., Owens, P N., Walling, D, E., and Leeks, Graham J. L. Fingerprinting suspended sediment sources in a large urban river system. 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Isot. 1996:47,699-707.##Collins A.L., Walling D.E., Sichingabula H.M., Suspended sediment source fingerprinting in small tropical catchment and managment implications,.  Applied Geography, 2001: 21:387-412.##Motha J.A., Wallbrink P.J., Hairsine P.B,. and Grayson R. B.. Determining the sources of suspende sediment in forested catchment in southeastern Australia. Water Resources Reasearch. 2003: 39(3): 1056-1070##Wallbrink, PJ, Murray, AS, Olley, JM, & Olive, LJ.. Determining sources and transit times of suspended sediment in the Murrumbidgee River, New South Wales, Australia, using fallout 137Cs and 210Pb. Water Resources Research, 1998:34(4), 879-887.##Caitcheon G. G, Olley J. M., Pantus F., Hancock G., and Leslie C.. The dominant erosion processes supplying fine sediment to three major rivers in tropical Australia. Geomorphology, 2012: 151-152. Pp.188-195##

0 بهینه‌سازی تعداد ایستگاه‌های باران‌سنجی ایران براساس روش‌‌های میان یابی و تحلیل مولفه‌های اصلی Optimization of the number of rain gage stations based on interpolation methods and principal components analysis in Iran https://ije.ut.ac.ir/article_62648.html 10.22059/ije.2017.62648 0   بهینه‏سازی تعداد ایستگاه‏های سینوپتیک در تخمین میزان بارندگی به لحاظ کاهش هزینۀ تعمیر و نگهداری، گامی مهم است. هدف اصلی این تحقیق، تعیین تعداد بهینۀ ایستگاه‏های سینوپتیک برای تخمین میزان بارندگی است. بر این اساس، ابتدا مقادیر باران ایستگاه‏های سینوپتیک مربوط به دورۀ آماری مشترک 14‌ساله از سازمان هواشناسی کشور اخذ شد و عملکرد پنج روش مختلف درون‏یابی ارزیابی شد. با توجه به نتایج، روش تابع پایۀ شعاعی (RBF)، با میزان خطای 63/0 به‌عنوان مناسب‏ترین برازش داده، انتخاب شد و سپس با استفاده از روش یادشده و PCA بهینه‏سازی ایستگاه‏ها صورت پذیرفت. بررسی‏های انجام‌شده نشان می‏دهد با حذف ایستگاه‏های سینوپتیک در روش PCA خطای برآورد RMSE از 48/0 به 52/0 نسبت به حالتی که از همۀ ایستگاه‏های سینوپتیک استفاده می‏شد، افزایش یافت و در روش میان‏یابی تابع پایۀ شعاعی میزان خطا از 63/0 به 55/0 کاهش یافت که بیان‌کنندۀ مناسب‌بودن این روش در بهینه‏سازی ایستگاه‏های سینوپتیک کشور است. نتایج بیان می‌کند که با حذف 34 نقطه در روش PCA و 22 نقطه در روش میان‏یابی تابع پایۀ شعاعی از شبکۀ ایستگاه‏های سینوپتیک ایران مقدار خطای به‌دست‌آمده قابل قبول است.   ‌   1 Optimization of the number of synoptic stations in the estimation of rainfall is an important step in terms of reducing the maintenance cost and saving the data collection. The main objective of this study was to determine the optimal number of synoptic stations to estimate the amount of rainfall in Iran. Accordingly, the amount of rainfall of synoptic stations related to a common 14-year period was received from the National Weather Service and the performances of five different interpolation methods were evaluated. Based on the results of radial basis function (RBF), with a margin of error of 0.63, this method was selected as the most appropriate method in fitting the data. Studies show that eliminating the synoptic stations in PCA method increases the estimation error of RMSE from 0.48 to 0.52 related given that all synoptic stations were used; moreover, in the radial basis function, interpolation method decreases from 0.63 to 0.55 which indicates the suitability of this method in the optimization of synoptic stations. The results indicate that through removing 34 and 22 points from the network of synoptic stations in Iran respectively in the PCA method and interpolation method of radial basis, the resulting error will acceptable. 897 910 زهرا گرکانی نژاد مشیزی Zahra Gerkani Nezhad Moshizi دانش ‏آموختۀ کارشناسی ارشد آبخیزداری، دانشکدۀ کشاورزی و منابع طبیعی، دانشگاه هرمزگان، بندرعباس Iran z.gerkani94@gmail.com فاطمه تیموری Fatemeh Teimouri دانش‏ آموختۀ کارشناسی ارشد آبخیزداری، دانشکدۀ کشاورزی و منابع طبیعی، دانشگاه هرمزگان، بندرعباس Iran f.teimouri93@gmail.com ام البنین بذرافشان Ommolbanin Bazrafshan استادیار، دانشکدۀ کشاورزی و منابع طبیعی، دانشگاه هرمزگان، بندرعباس Iran bazrafshan1361@gmail.com Optimization interpolation PCA Validation synoptic stations منابع##[1]     Yousefi H, Nohegar A, Khosravi Z, Azizabadi Farahani M. Drought Modeling and Management Using SPI and RDI Indexes (Case study: Markazi provin). The Univercity of Tehrans Scientific Journals Database. 2015; 2(3): 337- 344. (In Persian)##[2]     Mohammadi M, Karami H, Farzin S, Farokhi A. Prediction of Monthly Precipitation Based on Large-scale Climate Signals Using Intelligent Models and Multiple Linear Regression (Case Study: Semnan Synoptic Station), The Univercity of Tehrans Scientific Journals Database. 2017; 4(1): 201- 214. (In Persian)##[3]     Sajal KA, Abdullah GY, Nitin M. Optimal design of rain gauge network in the Middle Yarra River catchment, Australia. Hydrol.Process.2014.##[4]     Pardo-Igúzquiza E. Optimal selection of number and location of rainfall gauges for areal rainfall estimation using geostatistics and simulated annealing. Journal of Hydrology. 1998; 210: 206–220.##[5]     Xie, Y., bin Chen, T., Mei Lei, Jun Yang, Qing-jun Guo, Bo Song, Xiao-yong Zhou, 2011, Spatial distribution of soil heavy metal pollution estimated by different interpolation methods: Accuracy and uncertainty analysis, Chemosphere, Vol. 82, No. 3, PP. 468- 476.##[6]     Kassim AHM, Kottegoda NT. Rainfall network design through comparative kriging methods. Hydrological Sciences Journal. 1991; 36: 223–240.##[7]     Mohd Aziz M, Yusof F, Mohd Daud Z, Yusop A, Afif M. Optimal design of rain gauge network in Johor by using geostatistics and particle swarm optimization. International Journal of GEOMATE. 2016; 11(25): 2422-2428.##[8]     Adhikary SK, Yilmaz AG, Muttil N. Optimal design of rain gauge network in the Middle Yarra River catchment, Australia. HYDROLOGICAL PROCESSES. 2014; 29(3): 2582–2599.##[9]     Mishra AK, Coulibaly P. Developments in hydrometric network design: a review. Reviews of Geophysics. 2009. 47: RG2001.##[10]  Chebbi A, Bargaoui ZK, da Conceição Cunha M. Development of a method of robust rain gauge network optimization based on intensity-duration-frequency results. Hydrol. Earth Syst. Sci.2013; 17: 4259–4268.##[11]  Tsintikidis D, Georgakakos KP, Sperfslag JA, Smith DE, Carpenter TM. Precipitation Uncertainty and Raingage Network Design Within Folsum Lake watershed. Journal of Hydrologic Engineering.2002; 7(2): 175-184.##[12]  Dimitris M, Metaxa G. 2006. Geostatiscal Analisis of Spatial Variability of Rainfall and Optimal Design of a Rainguage Network, Water Resources Management. 2006; 10: 107-127.##[13]  Cheng KS, Wei C, Cheng YB, Yeh HC. Effect of spatial variation characteristics on contouring of design storm depth, Hydrol Process 2003; 17(9): 1755-69.##[14]  Barca E, Passarella G, Uricchio V. 2008. Optimal Extension of the Rain Gauge Monitoring Network of the Apulian Regional Consortium for Crop Protection, Environ Monittoring Assessment. 2008; 145(58): 375-386.##[15]  Karamouz M, Kerachian R, Akhbari M, Hafez B. Design of river water quality monitoring networks: a case study, Environ Model Assess 2009; 14(6): 705-14.##[16]  Shafiei M, Ghahraman B, Saghafian B. 2013. Evaluation and optimization of raingauge network based on probability kriging (case study: Gorgan-Rud watershed). Iran-Water Resources Research. 2013; 9(2): 9-18. (In Persian)##[17]  Adib A, Moslemzadeh M. Optimal Selection of Number of Rainfall Gauging Stations by Kriging and Genetic Algorithm Methods. International Journal of Optimization in Civil Engineering. 2016; 6(4):581-594.##[18]  Feki H, Slimani M, Cudennec CH. 2016. Geostatistically based optimization of a rainfall monitoring network extension: case of the climatically heterogeneous Tunisia. Hydrology Research.2016; 48(1).##[19]  Asakere H, Kriging interpolation method is used in the case of Iran, the interpolation of precipitation 12/26/1376. Journal of Geography and Development. 2004; 5(12): 25-42. (In Persian)##[20]  Gurunathan K, Ravichandran S. 1994. Analysis of water quality data using a multivariate statistical technique - a case study. IAHS Pub. 1994; 219.##[21]  Salah H. Geostatistical analysis of groundwater levels in the south Al Jabal Al Akhdar area using GIS. GIS Ostrava. 2009; 25: 1-10.##[22]  Taghizadeh R, Zareian M, Mahmudi SH, Heidari A, Sarmadian F. Evaluation methods temporal interpolation to determine the spatial variability of water quality characteristics of groundwater in Rafsanjan. Watershed Management Science and Engineering Iran. 2008; 2(5): 63-70. (In Persian)##[23]  Bastin G, Lorent B, Duque C, Gevers M. Optimal estimation of the average areal rainfall and optimal selection of rain gauge locations, Water Resour Res. 1984; 20(4): 463-70.##[24]  Webster R and Oliver MA. Geostatistics for Environmental Scientists. John Wiley and Sons, Ltd., Chichester, UK.2001; 271.##[25]  Asghari moghadam A, Nurani V, Nadiri A. Predict when and where the groundwater level in the city of Tabriz metro area using neural kriging model. Iran Water Resources Research. 2008; 13(1): 14-24. (In Persian)##[26]  Isaaks, E.H., Srivastava, R.M., 1989, An Introduction to Applied Geostatistic, Oxford University Press New York, P.561.##[27]  Sun Y, Kang S, Li F and Zhang L. Comparison of interpolation methods for depth to groundwater and its temporal and spatial variations in the Minqin oasis of northwest China. Environmental Modelling & Software. 2009; 24:1163-1170.##[28]  28. Camdevyren HN, Demyr A, Kanik S, Keskyn. “Use of principal component scores in multiple linear regression models for prediction of Chlorophyll-a in reservoirs.” Ecol. Model. 2005; 181: 581–589.##[29]  Manly BFJ. Multivariate statistical methods: A primer, 2nd Ed., Chapman and Hall, London.1986.##[30]  Lu, W. Z., W. J. Wang, X. K. Wang, Z. B. Xu and A. Y. T. Leung. “Using improved neural network to analyze RSP, NOX and NO2 levels in urban air in Mong Kok, Hong Kong.” Environmental Monitoring and Assessment. 2003; 87: 235–254.##Petersen W. 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0 تدقیق جداسازی جریان پایه با استفاده از آبدهی ماهانه طبیعی شده Scrutiny of base flow separation using natural monthly discharge https://ije.ut.ac.ir/article_62649.html 10.22059/ije.2017.62649 0 در مطالعات هیدرولوژی رژیم رودخانۀ طبیعی در نظر گرفته می‌شود که به‌دلیل توسعۀ کشاورزی و صنعت و دیگر مصارف در بسیاری از حوضه‌های کشور به‌ویژه حوضه‌های میانی چنین فرضی صحیح نیست. لازمۀ جداسازی جریان پایۀ رودخانه، دسترسی به رژیم طبیعی رودخانه در مقیاس زمانی روزانه است که با توجه به محدودیت روش‌های طبیعی‏سازی، آبدهی طبیعی در مقیاس زمانی سالانه و درنهایت ماهانه قابل محاسبه است. این مسئله سبب شده تخمین جریان پایۀ رودخانه با مشکل مواجه شود. از طرفی، به‌دلیل پیچیدگی ارتباط آب سطحی و آب زیرزمینی، تخمین مناسب از آن در بسیاری از آبخوان‏ها مشکل است. در این پژوهش، به‌منظور طبیعی‏سازی آبدهی ماهانۀ حوضۀ بلبر از روش حذف روند استفاده شد و از فیلتر دیجیتال بازگشتی الگوریتم اکهاردت به‌دلیل درنظرگرفتن خصوصیات آبخوان در محاسبۀ جریان پایه و قابلیت بهینه‌سازی پارامترهای فیلتر استفاده ‌شد. پارامترهای ثابت بازگشت و بیشترین شاخص جریان پایه برای آبدهی‌های ماهانه در شرایط طبیعی بهینه شد و جریان پایۀ ماهانه محاسبه شد که نتایج نشان داد می‏توان از آبدهی طبیعی ماهانه برای محاسبۀ جریان پایه با دقتی مشابه آبدهی طبیعی روزانه جریان پایه را محاسبه کرد.     1 In hydrology studies, the river regimes are considered to be natural while this assumption is not correct since the river water is used for developing agriculture, industry, and other needs, particularly in the middle basins. The requirement for river base flow separation is to have access to natural river regime on a daily basis, which, regarding the limitations of naturalization, natural river regime can be calculated on an annual or monthly basis. Therefore, the estimation of base flow has been faced with some difficulties. On the other side, due to the complex relation of surface water with groundwater, the estimation of base flow is too hard. Therefore, in this study, the removal process method was used for naturalizing monthly discharge of Belbar basin, and Eckhart RDF algorithm was used since it takes aquifer characteristics into account for calculating base flow and it has the ability to optimize its parameters. The constant parameters of return and the maximum base flow index for monthly natural river discharge in hydrometric stations of Belbar dam were optimized. Then, the monthly base flow was calculated and the results showed that the monthly natural river discharge can be used like the daily natural river discharge with the same accuracy. 911 921 امین عیدی پور Amin Eeidipour کارشناس ارشد شرکت مهندسین مشاور دزآب اهواز Iran amineidipour@gmail.com امیر پورحقی Amir Pourhaghi دانشجوی دکتری مهندسی منابع آب، دانشکدۀ مهندسی علوم آب، دانشگاه شهید چمران اهواز Iran amir_55_36@yahoo.com اکبر شکراللهی Akbar Shokrolahi کارشناس ارشد شرکت مهندسین مشاور دزآب اهواز Iran a_shokrolahi@gmail.com حسین یوسفی Hossein Yousefi استادیار دانشکدۀ علوم و فنون نوین دانشگاه تهران Iran hosseinyousefi@ut.ac.ir Base flow recursive digital filter natural discharge rock aquifer belbar dam منابع##Bayazidi S, Aliabad HM, Zafaranizade M. Natural discharge of hydrometric stations with Cindex (remove Trend amended), the Ninth International Conference of Civil Engineering, University of Isfahan; 2012 [Persian]##White KE, Sloto RA. Base-flow frequency characteristics of selected Pennsylvania Streams. US Department of the Interior, US Geological Survey; 1990.##Holtschlag DJ, Nicholas JR. Indirect ground-water discharge to the Great Lakes. US Geological Survey; 1998.##Hoos AB. Recharge rates and aquifer hydraulic characteristics for selected drainage basins in middle and east Tennessee. US Geological Survey; Books and Open-File Reports [distributor]; 1990.##Rutledge AT. Computer programs for describing the recession of ground-water discharge and for estimating mean ground-water recharge and discharge from streamflow records: Update;1998.##Mau DP, Winter TC. Estimating Ground‐Water Recharge from Streamflow Hydrographs for a Small Mountain Watershed in a Temperate Humid Climate, New Hampshire, USA. Ground Water. 1997 Mar. 1;35(2):291-304.##Chapman TG. Comment on “Evaluation of automated techniques for base flow and recession analyses” by RJ Nathan and TA McMahon. Water Resources Research. 1991 Jul. 1;27(7):1783-4.##Nathan RJ, McMahon TA. Evaluation of automated techniques for base flow and recession analyses. Water Resources Research. 1990 Jul. 1;26(7):1465-73.##Lyne V, Hollick M. Stochastic time-variable rainfall-runoff modelling. InInstitute of Engineers Australia National Conference 1979 Sep. (Vol. 1979, pp. 89-93).##Eckhardt K. How to construct recursive digital filters for baseflow separation. Hydrological processes. 2005 Feb. 15;19(2):507-15.##Eckhardt K. A comparison of baseflow indices, which were calculated with seven different baseflow separation methods. Journal of Hydrology. 2008 Apr. 30;352(1):168-73.##Gonzales AL, Nonner J, Heijkers J, Uhlenbrook S. Comparison of different base flow separation methods in a lowland catchment. Hydrology and Earth System Sciences. 2009 Nov. 4;13(11):2055-68.##Smakhtin VU. Estimating continuous monthly baseflow time series and their possible applications in the context of the ecological reserve. Water Sa. 2001 Apr 1;27(2):213-7.##Shoshtari MM. Hydraulic groundwater, Ahvaz:Shahid Chamran UniversityPress; 2010 [Persian]##Beard L. R. HEC-4 Monthly Streamflow Simulation.1971.##

0 مقایسه عددی شاخص‌های هواشناسی RAI و PNPI به منظور ارزیابی و پهنه‌بندی وضعیت خشکسالی در استان خوزستان Numerical comparison of RAI and PNPI meteorological indices to assess and quantify the drought situation in Khuzestan province https://ije.ut.ac.ir/article_62650.html 10.22059/ije.2017.62650 0 طی دهه‏های اخیر در میان بلایای طبیعی که جوامع انسانی را تحت تأثیر قرار داده است، تعداد و فراوانی خشکسالی بیشتر از سایر حوادث طبیعی بوده است. خشکسالی از جمله بلایای طبیعی است که در مقایسه با مخاطرات طبیعی نظیر بارش‏های سنگین و سیلاب‏ها، به‏طور خزنده شکل می‌گیرد و گسترش می‏یابد. برای بیان کمی خشکسالی شاخص‏های متعدد و متفاوتی وجود دارد. در پژوهش حاضر شاخص‏های درصد از نرمال بارندگی (PNPI) و ناهنجاری بارش (RAI)، وضعیت و تداوم خشکسالی در هشت ایستگاه آبادان، اهواز، بندر ماهشهر، بستان، مسجدسلیمان، امیدیه، رامهرمز و صفی‏آباد در استان خوزستان طی دورۀ آماری 1990‌ـ 2014 ‌بررسی شده است. نتایج نشان داد بر اساس شاخص PNPI شدیدترین خشکسالی طی دورۀ زمانی 1990‌ـ 2014 در ایستگاه بندر ماهشهر با مقدار 39/20 در سال 2010 اتفاق افتاده است. درضمن بیشترین مقدار ترسالی بر اساس شاخص PNPI در ایستگاه اهواز با مقدار 33/216 و در سال 1997 اتفاق افتاده است. همچنین براساس شاخص RAI شدیدترین خشکسالی طی دورۀ زمانی 1990ـ 2014 در ایستگاه بندر ماهشهر با مقدار 26/6- و در سال 2010 اتفاق افتاده است. نیز براساس شاخص RAI بیشترین مقدار ترسالی در ایستگاه اهواز با مقدار 6/8 و در سال 1997 به وقوع پیوسته است.     1 Over the past few decades, the frequency and number of drought occurrence has been more than other natural disasters influencing human societies. Drought is a kind of natural disaster formed and extended smoothly and in a crawling way in comparison with other natural hazards like heavy precipitations and floodwaters. There are different and numerous indicators for quantitative expression of drought. Percentage Indicators of normal precipitation (PNPI) and precipitation abnormality (RAI) status and continuation of drought in 8 stations of Abadan, Ahvaz, Bandar-e Mahshahr, Bostan, Masjed Soleyman, Omidieh, Ramhormoz and Safi Abad in Khuzestan province during the statistical period (1990-2014) have been considered in this research. As the obtained results show, based on PNPI indicator, the most severe drought happened during period 1990-2014 in Bandar- e Mahshahr station with the amount of 20.39 in 2010. Also, the most severe wet period happened in Ahvaz station with the amount of 216.33 in 1997, based on PNPI indicator. Also, based on RAI indicator, the most severe drought happened in Bandar- e Mahshahr with the amount of 6.26 in 2010 during the period 1990-2014. Based on RAI indicator, the most severe wet period occurred in Ahvaz station with the amount of 8.6 in 1997. 923 930 محمدحسین جهانگیر Mohammad Hossein Jahangir استادیار گروه انرژی‏ های نو و محیط زیست، دانشکدۀ علوم و فنون نوین، دانشگاه تهران Iran mh.jahangir@ut.ac.ir اقبال نوروزی Eghbal Norozi دانشجوی کارشناسی ارشد، دانشکدۀ علوم و فنون نوین، دانشگاه تهران Iran eghbalnorozi@ut.ac.ir Drought PNPI indicator RAI indicator Khuzestan Province zoning منابع##[1] Movedat E, Maleki S, Classification and Spatial Measurement of Social - Physical damages of the Cities Against Earthquakes by Using VIKOR Technique and GIS, Case Study: Yazd City. Jornal of Management System. 2014; 4(11): 85-103. (In Prsian).## [2] Mosavi S H, AbasAli V, Maeiri M.Study of Drought severity and its severity in Semnan using DI index. Second National Conference on Drought Effects and Management Tools. Isfahan Agricultural and Natural Resources Research Center. 2009.(In Prsian).## [3] Heidari, H. Plantand.Drought, Reserch institute of forest and Regeland publications, 2006.## [4] Khosravi Y, Mozafari Kh. Error Analysis in the Evaluation of the SPI Drought Index Using Geostatistical Methods, Case Study of Bushehr Province. Jornal of Geography. 2015; 14(48): 189-212.(In Prsian).## [5] Evazi M, Masaedi A. Monitoring and Spatial Analysis of Meteorological Drought in Golestan Province using Geostatistical Methods. Jornal of Range and Watershed Management, Iranian jornal of Natural Resources. 2011; 64(1): 65-78.(In Persian).##[6] Ansari H, Davari K. Zoning drought using standard precipitation index(SPI) in GIS Environment, Case study of khorasan province. Jornal of Geogrohi.2007; Res. 60:97-108. 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0 منابع آب و نقش آن در جذب گردشگران، مطالعه موردی قنات های شهر تهران Water resources and their role in attracting tourists (Case Study: Tehran’s Qanats) https://ije.ut.ac.ir/article_62651.html 10.22059/ije.2017.62651 0 قنات پس از ابداع در کشور ایران، به‌علت کارایی مناسب و مطلوب در دیگر نقاط کرۀ زمین گسترش یافت و آب زیرزمینی را در دسترس استفاده‏کنندگان آن قرار داد. مطالعات نشان‌دهندۀ 10 هزار کیلومتر قنات و 300 هزار چاه دسترسی به قنات‏ها در بستر شهرهای ایران است. به‌منظور بهره‏برداری از قنوات برای اهداف گردشگری باید به توسعۀ پایدار توجه شود. این مسئله به‌معنای بهره‏برداری مسئولانه، بابرنامه و معقول از این منابع آبی است. گردشگری مزایای بسیاری از جمله تبادل فرهنگی، رونق کسب‌و‌کار‏های بومی، اشتغال‏‏زایی برای ساکنان و نزدیکی بیشتر جوامع با یکدیگر دارد. بررسی پیشینه و ساختار قنات‏ها در ایران و سایر نقاط جهان نشان‌دهندۀ دانش فنی زیاد، ظرافت و نگهداری مناسب از این منابع آبرسانی است. تغییرات اقلیمی، عدم نگهداری و مدیریت نامناسب قنات‏ها و گسترش روش‏های نوین آبرسانی به خشک‌شدن بسیاری از قنات‏ها در کشور ایران منجر شده است. تجربه‏های پیشین در احیای قنوات و تبدیل آنها به مراکز گردشگری در بخش‏هایی از ایران و جهان با موفقیت روبه‌رو بوده است. پیش‏بینی می‏شود ظرفیت گردشگری زیادی برای معرفی قنات‏ها و جذب سرمایۀ ناشی از حضور گردشگران در قنات‏های هستۀ تاریخی‌ـ مرکزی تهران وجود داشته باشد.   1 Since Iranians introduced Qanat to the world, it has been widely spread around the world due to its usefulness providing people with groundwater. According to studies conducted in Iran, it is estimated that about 10,000 km qanats with 300,000 wells lie under Iranian urban areas. In order to utilize these water resources, sustainable development should be taken into account, which is exploitation of these resources with responsibility, reasonable and proper planning. Tourism is associated with many advantages including cultural exchange, flourished native businesses, increased rate of employment, and familiarity of  communities with each other. Studying the history and structure of Qanats in Iran and other regions reveals the high technical knowledge of our ancestors. Many reasons contribute to the decline of Qanats in Iran including new methods of irrigation, climate changes and inappropriate management knowledge. However, based on previous successful experiences in reviving Qanats and turning them into tourist attractions in different parts of the world and also Iran, the high potential of this structure to attract a huge number of tourists is revealed; therefore, reviving and improving these structures in historical parts of Tehran is recommended. 931 941 نصرالله آبادیان Nasrollah Abadian دانشجوی دکتری گروه شهرسازی، واحد امارات، دانشگاه آزاد اسلامی، دبی، امارات Iran nasrollah.abadian@yahoo.com ناصر اقبالی Naser Eghbali دانشیار گروه جغرافیا، واحد تهران مرکز، دانشگاه آزاد اسلامی، تهران، ایران Iran naser.eqbali@yahoo.com نسیم خانلو Nasim Khanlou استادیار گروه شهرسازی، تهران شرق، دانشگاه آزاد اسلامی، تهران، ایران Iran hevak.valkyr@gmail.com Qanat Tourism Tehran resuscitation of water resources منابع##1.  Stiros SC. Accurate measurements with primitive instruments: the “paradox” in the qanat design. Journal of Archaeological Science. 2006;33(8):1058-64.##2.  Maleki A, Khorsandi A. 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