The Application of RUSLE Model in Spatial DistributionDetermination of Soil loss Hazard

Document Type : Research Article

Authors

Abstract

The modeling can provide a quantitative approach and consistency in the estimationsoil erosion and sediment yield by a wide range of conditions. In this study, the integration method of revised universal soil loss equation model, geographic information system and remote sensing techniques were used in order to identify the spatial distribution of soil erosion and sediment yield in the Talar watershed. Parameters of rainfall erosivity, soil erodibility, slope length and slope gradient and vegetation cover were calculated in order to provision RUSLE map. The amount of soil loss was calculated from 0 to 9201 tons per hectare per year for the total basin and classification of erosion areas showed that erosion class of low, medium, high and very high with value of 33.12, 27.62, 21.13 and 18.13 percent respectivelycovered the total watershed. The linear regression analysis showed that in the between parameters of RUSLE model, the slope length and slope gradient parameter with value of 0.93 have the most correlation with the soil loss map. Also sw3 sub-watershed with value of 5580.33 tons per hectare per year and the sw4 sub-watershed with value of 19.59 percent have the highest and lowest Erosion hazard and Sediment yield respectively in the between sub-watersheds. The results showed that conservation and management measures can be useful to control and also reduce soil erosion and sediment yield in the Talar watershed.
 
 
 



 
 
 

Keywords

Main Subjects

References

منابع
[1]. Eswaran H, Lal R, Reich P. Land degradation: an overview. In: Bridges EM, Hannam ID, Oldeman LR, Penning de Vries FWT, Scherr SJ, Sombatpanit S (eds) Response to land degradation. Science, Enfield, 2001. P. 20-35.
[2]. Turner B, Clark W, Kates R, Richards J, Matthews J, Meyer W. The earth as transformed by human action. Cambridge: Cambridge Univ. Press.1990.
[3]. Lal R. Soil erosion impact on agronomic productivity and environment quality: critical reviews. Plant Sci. 1998;17:319-464.
[4]. Grepperud S. Soil conservation and government policies in tropical area: does aid worsen the incentives for arresting erosion. Agric econ. 2012;12:120-140.
[5]. Ganasri B, Ramesh H.Assessment of soil erosion by RUSLE model using remote sensing and GIS - A case study of Nethravathi Basin. Geoscience Frontiers. 2015;1-9.
[6]. Prasannakumar V, Shiny R, Geetha N, Vijith H. Spatial prediction of soil erosion risk by remote sensing, GIS and RUSLE approach: a case study of Siruvani river watershed in Attapady valley, Kerala, India. Environ Earth Sci. 2011;64:965–972.
[7]. Nearing M, Foster G,Lane L. A process-based soil erosion model for USDA water erosion prediction project. Transactions of ASAE. 1989;32(5):1587–1593.
[8]. Knisel W. A field scale model for chemicals, runoff, and erosion from agricultural management systems. us department of agriculture research service : US Department of Agriculture Research Service. 2010.
[9]. Morgan R, Quinton J, Rickson R. Structure of the soil erosion prediction model for the European community. Proceedings of International Symposium Water Erosion, Sedimentation and Resource Conservation, 9–13 October, 1990 Dehradun, India. Central Soil andWater Conservation Research and T. CSWCRTI, Dehradun, India. 1990; p.49-59.
[10]. Arnold J, Srinivasan R, Muttiah R, Williams J. Large area hydrologic modeling and assessment part I: Model development1. J Am Water Res Assoc. 1998;34(1):73-89.
[11]. Lazzari M, Gioia D, Piccarreta M, Danese M, Danese A. Sediment yield and erosion rate estimation in the mountain catchments of the Camastra artificial reservoir (Southern Italy): a comparison between different empirical methods. Catena. 2015;127:323e339.
[12]. Renard K, Foster G, Weesies G, McCool D, Yoder D. Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss EquationRUSLE). US Department of Agriculture (Ed.), Agricultural Handbook. US Department of Agriculture, Washington. 1997;703:1–251.
[13]. Wischmeier W, Smith D. Predicting rainfall erosion losses-a guide to conservation planning. Agriculture Handbook No. 537. US Department of Agriculture Science and Education Administration, Washington, DC, USA, 1978. p. 163.
[14]. Vipul Shinde K, Tiwari S, Manjushree S. Prioritization of micro watersheds on the basis of soil erosion hazard using remote sensing and geographic information system. International Journal of Water Resources a Environmental Engineering. 2010;2(3):130-136.
[15]. Pandey A., Chowdary V, Mal B. Identification of critical erosion prone areas in the small agricultural watershed using USLE, GIS and remote sensing. Water Resources Management. 2007;21(4):742-746.
[16]. kouli M, Soupios P, Vallianatos F. Soil erosion prediction using the revised universal soil loss equation (RUSLE) in a GIS framework, Chania, Northwestern Crete, Greece. Environ Geol. 2009;57(3):483-497.
[17]. Kefi M, Yoshino K. Evaluation of the economic effects of soil erosion risk on agricultural productivity using remote sensing: case of watershed in Tunis. International Archives of the Photogrammetry, Remote Sensing Spatial Information Sci. 2010.
[18]. Chen T, Niu R, Wang Y, Li P, Zhang L, Du B. Assessment of spatial distribution of soil loss over the upper basin of Miyun reservoir in China based on RS and GIS techniques. Environ MonitoringAssess. 2011;179:605-617.
[19]. Prasannakumar V, Vijith H, Abinod S, Geetha N. Estimation of soil erosion risk within a small mountainous sub-watershed in Kerala, India, using Revised Universal Soil Loss Equation (RUSLE) and geo-information technology. Geoscience Frontiers. 2012;3(2):209-215.
[20]. Farhan Y, Nawaiseh S. Spatial assessment of soil erosion risk using RUSLE and GIS techniques. Environ Earth Sci. 2015;74(6):4649-4669.
[21]. Zandi J, Soleimani K, Habibnejad Roshan M. Prioritizing of areas of soil erosion control using techniques of multi-criteria evaluation and GIS. Geography and Development. 2013;31:93-105.(In Persian).
[22]. Rahimi K, Mazbani M. Assess of erosion changes Sivand watershed during 1988 and 2009 using of the model RUSLE. Environmental Erosion Researchs. 2013;9:1-18. (In Persian).
[23]. Rakhbin M, Nohegar A, Kamali A, Habib Ellahian M. Estimates of erosion and sediment yield in the watershed Lavrfyn (Hormozgan eparchy) using remote sensing (RS), Geographic Information System (GIS) and experimental models RUSLE. Geographical Research. 2014;3(114):89-104.(In Persian).
[24]. Jahad Engineering services. Comprehensive study of Haraz Watershed. Compilation Reports., Studies office and evaluations watersheds.2001. (In Persian).
[25]. Vaezi A, Bahrami H, Sadeghi S, Mahdian M. Spatial variability of soil erodibility factor (K) of the USLE in North West of Iran. J Agric Sci Tech. 2010;12:241-252.
[26]. Pradhan B, Chaudhari A, Adinarayana J, Buchroithner M. Soil erosion assessment and its correlation with landslid events using remote sensing data and GIS. Environ Monitoring Assess. 2011;171:153-161.
[27]. Hichey R. Slope Angle and Slope Length Solutions for GIS. Cartogeraphy. 2002;29: 582-591.
[28]. Van Remortel R, Maichle R, Hickey R. Computing the LS factor for the revised universal soil oss equation through array-based slope processing of digital elevation data using C++ executable. Computers and Geosciences. 2004;30:1043-1053.
[29]. Wischmeier W, Smith D. Predicting rainfall erosion losses-a guide to conservation planning. Agriculture Handbook No. 537. US Department of Agriculture Science and Education Administration, Washington, DC, USA, 1978. p. 163.
[30]. De Jong S. Aplication of Reflective Remote Sensing for Land Degradation Studies.  University of Utrecht. 1994.
[31]. De Jeng S. Regional assessment of soil erosion using the distributed model SEMMED and remotely sensed data. catena. 1999;37:291-308.
[32]. Kigira F, Gathenya J, Home P. Modeling the influence of land use/land cover changes on sediment yield and hydrology in thika river catchment Kenya, Using Swat Model. Nile Basin Water Sci Eng J. 2012;3(3):56-72.
[33]. Lin C, Lin W, Chou W. Soil erosion prediction and sediment yield estimation: the Taiwan experience. Soil Till Res. 2002;68:143-152.
[34]. Fallah suraki M, Kavian A, Omidvar E. Zoning of soil erosion hazard in the Haraz watershed model RUSLE. 2 National Conference on climate change and engineering sustainable agriculture and natural Resources,, Tehran- September 17.2015. (In Persian).
[35]. Renard K, Foster G, Weesies G, McCool D, Yoder D. Predicting soil erosion by water: a guide to conservation planning with the Revised Universal Soil Loss EquationRUSLE). US Department of Agriculture (Ed.), Agricultural Handbook. US Department of Agriculture, Washington. 1997;703:1–251.
[36]. Khatiby M, Karami F, Rajabi M, Nikju M. Assessment of the soil erosion hazard in the sararkandr chay watersheds, the Sahand east hillsides using of USLE and GIS. Journal of Geography and Urban Planning. 2012;40(16):1-23.(In Persian).
 [37]. Rezai P, Faridy P, Ghorbani M, Kazemi M. Estimate of soil erosion using of RUSLE model and identify the most effective factor in watershed Gabric-southeast Hormozgan province. Quantitative geomorphology researchs 2014;1:97-113.(In Persian).
[38]. Dabral P, Baithuri N, Pandey A. Soil erosion assessment in a hilly catchment of North Eastern India using USLE, GIS and remote sensing. Water Res Manag. 2011;22(12):1783-1798.
[39]. Kamaludin K, Lihan T, Ali Rahman Z, Mustapha M, Idris W, Rahim S. Integration of remote sensing, RUSLE and GIS to model potential soil loss and sediment yield (SY). Hydrol Earth System Sci. 2013;10:4567–4596.
[40]. Getachew H, Melesse A. Effects of Land Use Change on Sediment and Water Yields in Yang Ming Shan National Park, Taiwan. Environments. 2015;2:32-42.
[41]. Huang T, Lo K. Effects of land use change on sediment and water yields in yang ming shan national park, Taiwan. Environments. 2012;2:32-42.
[42]. Khoi D, Suetsugi T. Impact of climate and land-use changes on hydrological processes and sediment yield—a case study of the Be River catchment, Vietnam. Hydrol Sci J. 2014;59(5):1097-1108.
Iranian journal of Ecohydrology
Volume 3, Issue 4
January 2017
Pages 645-658

Files

History

  • Receive Date: 21 November 2016
  • Revise Date: 02 January 2017
  • Accept Date: 21 December 2016
  • First Publish Date: 21 December 2016
  • Publish Date: 21 December 2016

Share

How to cite

Statistics