Groundwater Potential Mapping using Shannon's Entropy and Random Forest Models in the Bojnourd Township

Document Type : Research Article

Authors

1 PhD student in Range Sciences and Engineering, Islamic Azad University, Bojnourd, Iran

2 Natural Resources and Environmental Engineering, College of Agriculture, Shiraz University, Shiraz, Iran

3 Planning and Management Organization of North-Khorasan Province

Abstract

Nowadays, water supply for sustainable development is one of the most important concerns and challenges in most countries of the world. Due to determination of groundwater potential zones are one of the important tools in the conservation, management and utilization of water resources. Thus, the present study aimed to prioritize the effective factors on groundwater potential and its susceptibility zonation using Shannon’s entropy and Random Forest in Bojnourd Township. So, layers of slope angle, slope aspect, plan curvature, profile curvature, slope length, altitude, topographic wetness index, distance from fault, fault density, distance from river, drainage density, lithology and land use are known as affecting factors on Groundwater potential and were digitized in ArcGIS software environment. Subsequently, using Shannon’s entropy and Random Forest models, weight of affective factors was calculated in R statistical package and finally groundwater potential maps were prepared for the study area. The accuracy of groundwater potential zoning has been evaluated using relative operating curve (ROC), and according to the results, the accuracy of the Shannon’s entropy model was (85.55%), which is more acceptable than the accuracy of the Random Forest model (76.95 percent). Also, layers of land use, lithology, distance from river and altitude layers had the most effect on Groundwater potential in the study area based on the Shannon’s entropy model.

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[1].       ابراهیم‌خانی، سمیه؛ افضلی، مهدی؛ شکوهی، علی، 1390، پیش­بینی و بررسی عوامل تصادفات جاده‌ای با استفاده از الگوریتم‌های داده‌کاوی، فصلنامۀ دانش انتظامی زنجان، شمارۀ 1، سال اول: 127-111.
[2].       پورقاسمی، حمیدرضا؛ مرادی، حمیدرضا؛ فاطمی عقدا، سیدمحمود، 1392، تهیۀ نقشۀ حساسیت زمین‌لغزش با استفاده از سیستم استنتاج عصبی-فازی تطبیقی در شمال شهر تهران، مجلۀ پژوهش‌های دانش زمین، شمارۀ 10: 78-63.
[3].       ذبیحی، محسن؛ شاهدی، کاکا؛ دارابی، حمید؛ صفری، عطا، 1392، مطالعۀ خشکسالی هواشناسی دشت بجنورد با استفاده از شاخص‏های SPI، PNPI، NITZCHE، ZSI و DI، پنجمین کنفرانس مدیریت منابع آب ایران، بهمن ماه، تهران، ایران
[4].       فرشاد، محمد؛ ساده، جواد، 1392، مکان‌یابی خطای اتصال کوتاه در خطوط انتقال جریان مستقیم ولتاژ بالا با استفاده از شبکۀ عصبی، رگرسیون تعمیم‌یافته و الگوریتم جنگل تصادفی، سیستم‌های هوشمند در مهندسی برق، سال چهارم، شمارۀ 2: 14-1.
[5].       فضل‌اولی، رامین؛ شریفی، فرود؛ بهنیا، عبدالکریم، 1385، بررسی تأثیر پخش سیلاب در تغذیۀ مصنوعی سفرۀ آب زیرزمینی دشت موسیان (استان ایلام)، مجلۀ منابع طبیعی ایران، جلد 59، شمارۀ 1: 74-54.
[6].       محمدی، حسین‌مراد؛ شمسی‏پور، علی‌اکبر، 1382، تأثیر خشکسالی‏های اخیر در افت منابع آب زیرزمینی دشت‎های شمال همدان، مجلۀ پژوهش‏های جغرافیایی، شمارۀ 45: 130-115.
[7]. Bednarik, Martin. Magulova, Barbora, Matys. Mirko, and Marschalko, Marian, 2010, Landslide susceptibility assessment of the Kralovany–Liptovsky Mikulaš railway case study, Physics and Chemistry of the Earth, vol 35, pp162–171.
[8]. Chenini, Ismail. Ben Mammou, Abdallah, and May, Moufida El, 2010, Groundwater recharge zone mapping using GIS-based multi-criteria analysis: a case study in Central Tunisia (Maknassy Basin), Water Resources Management, vol 24 (5), pp 921–939.
[9]. Chowdhury, Alivia. Jha, Madan, Chowdary, Vuy, and Mal, Bimal C,  2009, Integrated remote sensing and GIS-based approach for assessing groundwater potential in West Medinipur district, West Bengal, India, International Journal of Remote Sensing, vol 30, pp 231–250.
[10].            Constantin, Mihaela. Bednarik, Martin, Jurchescu, Marta, and Vlaicu, Marius, 2011, Landslide susceptibility assessment using the bivariate statistical analysis and the index of entropy in the Sibiciu Basin (Romania), Environmental Earth Science, vol 63, pp 397–406.
[11].            Corsini, Alessandro . Cervi, Federico, and Ronchetti, Francesco, 2009, Weight of evidence and artificial neural networks for potential groundwater spring mapping: an application to the Mt. Modino area (Northern Apennines, Italy), Geomorphology, vol 111, pp 79–87.
[12].            Dar, Imran. Sankar, Kristian, and Dar, Mithas, 2010, Remote sensing technology and geographic information system modeling: an integrated approach towards the mapping of groundwater potential zones in Hardrock terrain, Mamundiyar basin, Journal of Hydrology, vol 394, pp 285–295.
[13].            DavoodiMoghaddam, Davood. Rezaei, Mojtaba, Pourghasemi, Hamid Reza, Pourtaghi, Zohre Sadat, and Pradhan, Biswajeet, 2013, Groundwater spring potential mapping using bivariate statistical model and GIS in the Taleghan watershed, Iran, Arabian Journal of Geoscience, vol 8, pp 913–929.
[14].            Fitts, Charles, Groundwater Science, Academic Press (Elsevier), 2002, pp 450.
[15].            Ganapuram, Sreedhar. Vijaya Kumar, Ganiga T, Murali, Krishna, Kahya, Ercan, and Demirel, Cuneyd, 2009, Mapping of groundwater potential zones in the Musi basin using remote sensing data and GIS, Advance Engineering Software, vol 40, pp 506–518.
 
[16].            Gaur, Shishir. Chahar, Bhagu R, and Graillot, Didier, 2011, Combined use of groundwater modeling and potential zone analysis for management of groundwater, International Journal of Applied Earth Observation and Geoinformation, vol 13, pp 127–139.
[17].            Ghayoumian, Jafar. Mohseni, Seyed Mohsen, Feiznia, Sadat, Nouri, Behzad, and Malekian, Arash, 2007, Application of GIS techniques to determine areas most suitable for artificial groundwater recharge in a coastal aquifer in southern Iran, Journal of Asian Earth Sciences, vol 30, pp 364–374.
[18].            Gupta, Manika, and Srivastava, Prashant, 2010, Integrating GIS and remote sensing for identification of groundwater potential zones in the hilly terrain of Pavagarh, Gujarat, India, Water International vol 35, pp 233–245.
[19].            Jain, Pradeep. 1998, Remote sensing techniques to locate ground water potential zones in upper Urmil River basin, district Chatarpur-central India, Journal of the Indian Society of Remote Sensing, vol 26, pp 135–147.
[20].            Jha, Madan. Chowdhury, Alivia, Chowdary, Vuy, and Peiffer, Stefan, 2007, Groundwater management and development by integrated remote sensing and geographic information systems: prospects and constraints, Water Resources Management, vol 21, pp 427–467.
[21].            Krishnamurthy, Jayasree. Srinivas, Rao G, 1995, Role of geological and geomorphological factors in groundwater exploration: a study using IRS LISS data, International Journal of Remote Sensing, vol 16(14), pp 2595–2618.
[22].            Manap, Mohamad Abd. Nampak, Haleh, Pradhan, Biswajeet, Lee, Saro, Soleiman, Wan Nor Azmin, and Ramli, Mohammad Firuz, 2012, Application of probabilistic-based frequency ratio model in groundwater potential mapping using remote sensing data and GIS, Arabian Journal of Geosciences, vol 7, pp 711-724.
[23].            Mukherjee, Soumyajit. 1996, Targeting saline aquifer by remote sensing and geophysical methods in a part of Hamirpur_Kanpur, India, Hydrogeology Journal, vol 19, pp 1867–1884.
[24].            Murthy, K Sri Rama. 2000, Groundwater potential in a semi-arid region of Andhra Pradesh- a geographical information system approach, International Journal of Remote Sensing, vol 21(9), pp 1867–1884.
[25].            Murthy, K Sri Rama. and Mamo, Abiy Gatachew, 2009, Multi-criteria decision evaluation in groundwater zones identification in Moyale-Teltelesubbasin, South Ethiopia, International Journal of Remote Sensing, vol 30, pp 2729–2740.
[26].            Naghibi, Seyed Amir. Pourghasemi, Hamid Reza, Pourtaghi Zohre Sadat, and Rezaei, Ashkan, 2014, Groundwater qanat potential mapping using frequency ratio and Shannon’s entropy models in the Moghan watershed, Iran, Journal of Earth Science, , vol 8 (1), pp 171-186.
[27].            Nefeslioglu, Hakan. Duman, Tamar, and Durmaz, Serap, 2008, Landslide susceptibility mapping for a part of tectonic Kelkit Valley (Easten Black Sea Region of Turkey), Geomorphology, vol 94, pp 401-418.
[28].            Nicodemus, Kristin K. 2011, Letter to the Editor: On the stability and ranking of predictors from random forest variable importance measures predictors from random forest variable importance measures, Brief Bio-inform, vol 12 (4), pp 369–373.
[29].            Oh, Hyun-Joo. Kim, Yong-Sung, Choi, Jong-Kuk, Park, Eungyu, and Lee, Saro, 2011, GIS mapping of regional probabilistic groundwater potential in the area of Pohang City, Korea, Journal of Hydrology, vol 399, pp 158–172.
[30].            Ozdemir, Adnan. 2011, GIS-based groundwater spring potential mapping in the Sultan Mountains (Konya, Turkey) using frequency ratio, weights of evidence and logistic regression methods and their comparison, Journal of Hydrology, vol 41, pp 290–308.
[31].            Pourghasemi, Hamid Reza. GoliJirandeh, Abbas, Pradhan, Biswajeet,  Xu, Chong, and Gokceoglu, Candan, 2013, Landslide susceptibility mapping using support vector machine and GIS, Journal of Earth System Science, vol 122 (2), pp 349-369.
[32].            Pourghasemi, Hamid Reza. Mohammady, Majid, and Pradhan, Biswajeet, 2012, Landslide susceptibility mapping using index of entropy and conditional probability models in GIS: Safarood Basin, Iran, Catena, vol 97, pp 71–84.
[33].            Pourghasemi, Hamid Reza. Moradi, Hamid Reza, FatemiAghda, Seyed Mahmood, Gokceoglu, Candan, and Pradhan, Biswajeet, 2014, GIS-based landslide susceptibility mapping with probabilistic likelihood ratio and spatial multi criteria evaluation models (North of Tehran, Iran), Arabian Journal of Geoscience, vol 7, pp 1857-1878.
[34].            Pourtaghi, Zohre Sadat. and Pourghasemi, Hamid Reza, 2014, GIS-based groundwater spring potential assessment and mapping in the Birjand Township, southern Khorasan Province. Iran, Hydrogeology Journal, vol 22, pp 643-662.
[35].            Pradhan, Biswajeet. 2009, Groundwater potential zonation for basaltic watersheds using satellite remote sensing data and GIS techniques, Central European Journal of Geosciences, vol 1(1), pp 120–129.
[36].            Pradhan, Biswajeet. and Lee, Saro, 2010, Landslide susceptibility assessment and factor effect analysis: back propagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modeling, Environmental Modeling and Software, vol 25 (6), pp 747–759.
[37].            Rao, Subba, 2006. Groundwater potential index in a crystalline terrain using remote sensing data: Environmental Geology, vol 50 (7), pp 1067–1076.
[38].            Sener, Erhan. Davraz, Aysen, and Ozcelik, Mehmet, 2005, An integration of GIS and remote sensing in groundwater investigations: a case study in Burdur, Turkey, Hydrogeology Journal, vol 13, pp 826–834.
[39].            Shannon, Claude. 1948, A mathematical theory of communication, Bulletin System, Technology Journal, vol 27, pp 379–423.