Shamim Shirjandi; A Khademalrasoul; Adel Moradi Sabzkuhi; Hadi Amerikhah
Abstract
IntroductionSoil degradation is a phenomenon which destructs the soil structure and mitigates its capacity for production. Among several processes that cause soil degradation, soil erosion as one of the most common forms of soil degradation leads to loss of soil surface and including on-site and off-site ...
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IntroductionSoil degradation is a phenomenon which destructs the soil structure and mitigates its capacity for production. Among several processes that cause soil degradation, soil erosion as one of the most common forms of soil degradation leads to loss of soil surface and including on-site and off-site effects. Although soil erosion is a natural process on the earth, but destructive human activities such as burning agriculture residue, deforestation, overgrazing, and lack of proper soil conservation practices; accelerate the soil erosion and enhance the negative outcomes of erosion. Selecting and implementing of management scenarios requires assessment of soil losses from different management operations. Generally, management practices consist of structural and non-structural methods that used to reduce erosion, prevent nutrient removal, and increase soil infiltration capacity. Application of simulation models is an appropriate technique to evaluate erosional conditions. GeoWEPP is a process-based, distributed parameters and continuous simulation model of water erosion in watersheds with the possibility to simulate hillslopes and hydrographical network. Locating problems in real world usually face with a large amount of information and decision space that need to be optimized using evolutionary algorithms due to the variety of aims considered. Considering diversity of evolutionary algorithms, NSGA-II is one of the most common and a usable multiobjective evolutionary algorithm (MOEA) which is very powerful tool for solving problems with conflicting objectives. Development of simulation models along with optimization algorithms that are capable of analyzing very complex systems, have found to be very efficient in real world problems. Simulation-optimization models are powerful tools for solving problems for least cost and best performance.Methods and materialsTo predict sediment yield and runoff in the studied watershed, the GeoWEPP integrates WEPP model with TOPAZ (Topography Parameterization), CLIGEN (Climate Generation) and GIS tool (ArcGIS). The GeoWEPP model provides the processing of digital data including DEM ASCII file, soil ASCII file and landcover ASCII file. To generate climate file, the CLIGEN module which is a stochastic weather generation model was utilized. Furthermore in TOPAZ part the CSA (critical source area) and MSCL (minimum source channel length) to delineate streams and also the outlet point of studied watershed were defined using GeoWEPP linked to ArcGIS. Using the basic maps including DEM, slope, soil great groups and soil database the GeoWEPP model simulates and generates the hillslopes automatically; therefore this is an important advantage of GeoWEPP compared to WEPP model which is capable of performing the simulation of watershed components spontaneously. In this study in order to optimize the placement of Gabions, 118 channels and 5110 candidate sites for gabion construction were simulated and evaluated. For optimization process; regarding the number of objectives firstly the AHP technique was used to prioritize the effective factors on the placement of Gabions. Analytical hierarchy process is a structured technique for organizing and analyzing complicated decisions based on mathematical calculations. The AHP depicts the accurate approach for quantifying the weights of criteria and estimates the relative magnitudes of factors through pair-wise comparisons. The AHP technique includes creating hierarchical structure, prioritizing and calculating relative weights of the criteria, calculating the final weights and system results compatibility. The main criteria (objectives) for our study were minimum distance from road, minimum distance from residential area, maximum length of main channel, maximum sediment yield, maximum discharge volume and maximum volume structure. Indeed using the AHP technique it was possible to restrict the decision making space and the number of possible options, therefore simplify the optimization process. Then NSGA-II (Non-dominated Sorting Genetic Algorithm) was applied in order to find the best solutions, i.e. the Pareto front, of alternatives for optimal location of structures based on the two objectives with higher priority and distance constraint. Results and discussionThe results of paired comparison matrix and prioritizing showed that the length of main channel in the watershed is the main effective criterion in locating Gabion structures. The first priority is considered as the most critical channel which produces the highest sediment yield; therefore the most expensive structure is established on that channel. After channel length, the volume discharge was the second priority of effective factors for gabion placement. Using the results of AHP, based on channel length and discharge volume the non-dominated sorting genetic algorithm (NSGA-II) was performed and the priority of critical channels and the specific position was determined from 1 to 35 among 5110 candidate sites for Gabion construction. Using the ArcGIS, slope map and the lowest width of the critical channels the place for gabion construction as a point was determined. Moreover the main output of GeoWEPP is the spatial distribution of sediment yield and based on this map the sediment yield was classified in the watershed. Based on this map the red color was the highest amount of sediment yield (more than 4 ton) in the watershed. ConclusionResults confirmed that application of simulation-optimization techniques helps to select the best sites to construct the Gabion as structural best management practice therefore is a cost-effective technique.
