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Prediction of Land Use Management Scenarios Impact on Water Erosion Risk in Kashidar Watershed, Azadshahr, Golestan Province

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Prediction of Land Use Management Scenarios Impact on Water Erosion Risk in Kashidar Watershed, Azadshahr, Golestan Province SimpoJournal PDF of MergeRangeland and Science, Split 201 Unregistered3, Vol. 3, No. 2 Version - http://www.simpopdf.com Akhzari et al. / 165 Contents available at ISC and SID Journal homepage: www.rangeland.ir Full Length Article: Prediction of Land Use Management Scenarios Impact on Water Erosion Risk in Kashidar Watershed, Azadshahr, Golestan Province Davoud AkhzariA, Samaneh Eftekhari AhandaniB, Behnaz AttaeianA, Alireza IldoromiC AAssistant Professor, Department of Watershed and Rangeland Management, Malayer University, Iran. (Corresponding Author). Email: [email protected] BPost Graduated Student of Desert Area Management, Department of Rangeland and Watershed Management, Gorgan University of Agricultural and Natural Resources Sciences, Iran. CAssociate Professor, Department of Watershed and Rangeland Management, Malayer University, Iran. Received on: 27/05/2013 Accepted on: 12/09/2013 Abstract. Soil erosion is a serious problem especially in northern parts of Iran. One the most important side effects on soil erosion may be the decline in qualities of soil refers to agricultural productivity. So it is very important to assess the soil erosion risk for the sustainable development of agriculture. This study outlines ways undertaken to provide a new tool to manage water erosion from physical and economical perspectives. Kashidar Watershed in north of Iran is used as a case study. The focus of this study is on exploring the economic and physical impacts of eight land use-based scenarios for water erosion management as well as conducting a trade-off analysis using the Multi-Criteria Decision Making (MCDM) technique. This involves developing a modeling system to assist decision makers in formulating scenarios, analyzing the impacts of these scenarios on water erosion, interpreting and suggesting appropriate scenarios for implementation in the area. This study was conducted with object of modeling and assessing soil erosion risk in Kashidar Watershed with the application of IMAGE\LDM. Rainfall erosivity index, relief index, soil erosivity index and land cover index were four basic factors used in IMAGE\LDM. Soil erosion risk can be divided into six groups. Furthermore, the spatial distribution characteristics were also analyzed with the application of GIS in the view of elevation, land use types. Among 8 scenarios for water erosion management, most appropriate ones that have minimum proportion of high water erosion hazard classes, maximum gross margin and minimum establishment cost were chosen as best scenarios. Key words: Land use, Water erosion, Trade-off analysis, MCDM, Kashidar Watershed Simpo J.PDF of Range. Merge Sci., and 2013 Split, Vol. 3Unregistered, No. 2 Version - http://www.simpopdf.com Prediction of …/ 166 1. Introduction characteristics. Therefore, a scenario Economic development and human planning is required to achieve optimum welfare largely depend on optimum sustainable farming systems (Nikkami, utilization of natural resources 2009). (Karunakaran, 2012). Successive crops Severe erosion usually causes a planting cause cropland economic decrease in producing agricultural efficiency reduction. Continuing this products, which demonstrates the strong process will lead to a big reduction in impact of usage on the amount of erosion farmerʼs income (Singh, 2008). Improper (Martha, 2004). Suitable land use selection and cultivation of traditional selection reduces soil erosion (Martha, crops will exacerbate the problem 2004). Soil erosion in Kashidar (Maroyi, 2012). Appropriate land use Watershed is higher than normal amount selection in the agricultural field increase (Golestan Natural Resources Bureau, farmerʼs income (Karunakaran, 2012). 2009). Land use management scenarios Thus revision of agricultural land use is for reducing phosphorous leak to lower very useful for agricultural area unites, Green Bay in the State of Michigan using income increment, and land use the SWAT were used. This research result application improvement. Kashidar showed the best land use management watershed ecosystem has a vital role for scenarios to reduce the phosphorous leak economy of the region. Golestan Natural (Baumgart and Fermanich, 2008). The Resources bureau, (2009) recommended Unit Stream Power based an integrated management with these Erosion/Deposition model was applied to goals; 1) to increment community predict land use management scenarios awareness and skills in order to impact on water erosion. Results showed implement the conservation and that the whole erosion from urban areas rehabilitation of land in agricultural scenarios was higher than other land use systems, and 2) to establish agricultural scenarios (Leh et al., 2011). Revised land use system based on the ability of Universal Soil Loss Equation (RUSLE) land to support sustainable land use. Land model and Geographic Information use conflicts in Kashidar Watershed area Systems (GIS) with geo-statistical are associated with the preservation of techniques were adopted to study ecosystem where erosion and different land use management scenarios sedimentation rate is very high and they impact on water erosion risk. Results will improve farmersˈ welfare and showed that the RUSLE model was a income, to attain food security, poverty good method to estimate soil erosion risk spread prevention and to provide jobs in different scenarios because it was (Hengki et al., 2012). simple, fast and economical to use More than 80% of native people in (Ferreira and Panagopoulos, 2012). Kashidar Watershed live below the A model used for regional soil poverty line. Kashidar Watershed erosion evaluation is semi-quantitative farmlands are mainly rain fedcultivation. methods. The Integrated Model to Assess Income obtained from this type of the Global Environment (IMAGE) is a farming is not enough for farmers living dynamic integrated assessment modeling costs. One of the best ways to increase framework for global change. Land farmersˈ income, is land use management degraded model is one of the basic of these lands. The appropriate land use models of IMAGE (Tingting, 2008). The selection due to farmers' income aim of this study was to use the Integrated increases. Land use change requires Model to Assess the Global Environment compliance consideration with the (IMAGE)- Land Degrade Model (LDM) technical, economical and social SimpoJournal PDF of MergeRangeland and Science, Split 201 Unregistered3, Vol. 3, No. 2 Version - http://www.simpopdf.com Akhzari et al. / 167 to evaluate the soil erosion risk in 37°5'N, the altitude of area is 950-2500 Kashidar Watershed. m above sea level with an area of 15017 ha. The study area accommodates 6 2. Materials and Methods villages (Golestan Natural Resources The study area is located in Southern East Bureau, 2009). Map of the study area in of Golestan Province, Iran. Iran and Golestan Province showed in Geographically the study area lies (Fig. 1). between 55°27' to 55°40' E and 36°56' to Fig. 1. Map of the study area in Iran and Golestan Province The Integrated Model to Assess the factor. According to IMAGE-LDM, the Global Environment (IMAGE)- Land monthly average intensity of rainfall Degrade Model (LDM) was used to (mm/day) was selected as the indication evaluate the soil erosion risk in the study of rainfall intensity. If the maximum area. The (IMAGE)- Land Degrade monthly average of rainfall intension of Model (LDM) input map layers include three months exceeds 2mm/day, the R- rainfall erosivity index (R-factor), relief factor is assigned 1. If the maximum index, soil erodibility index and land monthly average of rainfall intension of cover index (Tingting, 2008). three months belongs to 0 to 2mm per Among the four major factors day, the R-factor is assigned 0. If the affecting the soil erosion, rain is the main value between these two extremes a agent for erosion, which reflects the linear relation is assumed (Tingting, potential rate of soil erosion. Not all 2008). rainfalls can induce soil erosion except Based on these factors LDM those showers of high intensity. So the model provides a map that shows the erosivity of rainfall is mainly determined susceptibility and potential sensitivity to by the intensity of rainfall events. water erosion in Kashidar Watershed. Rainfall in Kashidar Watershed is very Potential susceptibility and sensitivity to unevenly distributed, which mainly water erosion is ranged from E1 to E6. concentrates in spring season, so the From E1 to E6, the potential rainfall data from March to June was susceptibility and sensitivity to water used to calculate R- erosion gradually increased (Tingting, 2008). Simpo J.PDF of Range. Merge Sci., and 2013 ,Split Vol. 3Unregistered, No. 2 Version - http://www.simpopdf.com Prediction of …/ 168 These maps were prepared and considered. The feasible management superimposed using the ArcGIS software actions for the southern parts of Kashidar to estimate the water erosion severity over Watershed are enclosure, Forage the study area. The Spearman rank cultivation and orchard planting. correlation coefficient was calculated to Assuming the present condition as a base evaluate the accuracy of hazard zonation case scenario, the number of new (Mesdaghi, 2004). To develop scenarios will be 2n – 1, in which n is the management scenarios, all feasible number of management actions. The base management actions were listed and all of case scenario is regarded as scenario one the possible combinations of those actions and the other scenarios are compared with were considered. In order to determine
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