Prediction of soil erosion and sediment delivery ratio using RUSLE at Sanganeh soil conservation research station

Document Type : Research/Original/Regular Article

Authors

1 Assistant Professor/ Soil Conservation and Watershed Management Department, Khorasan Agricultural and Natural Resources Research Centre, Mashhad, Iran

2 Professor/ Soil Conservation and Watershed Management Research Institute, Agricultural Research, Education and Extension Organization, Tehran, Iran

Abstract

Introduction
Soil erosion by water is one of the most common environmental problems worldwide and is considered a serious risk for sustainability in developing countries. Water erosion on a global scale is one of the most critical types of soil and environmental degradation due to its geographical extent and ecological effects. In this regard, effectively controlling sediment load is an important component in watershed management. In the formulation of a watershed management strategy, the estimation of sediment delivery ratio (SDR) plays a significant role. SDR is defined as the sediment yield from an area divided by the gross erosion of that same area. SDR is expressed as a percentage and represents the efficiency of the watershed in moving soil particles from areas of erosion to the point where sediment yield is measured. One of the problems in estimating the SDR in watersheds is the lack of proper information on the amount of soil erosion and sediment yield. In this context, the Sanganeh soil conservation research station, having measured soil erosion and sediment yield of small watersheds, is a suitable place to evaluate the accuracy of the RUSLE model and estimate the ratio of sediment delivery on the scale of small watersheds. The current research aims to achieve two goals: a) determining the accuracy of the RUSLE model in estimating soil erosion based on the measurements in the erosion plots, and b) estimating the SDR using the estimated soil erosion values as well as the sediment yield measured at the outlet small watershed are planned.
 
Materials and Methods
Considering the importance of soil erosion and the study of sediment processes in semi-arid rangeland ecosystems, the Khorasan Razavi Agricultural and Natural Resources Research Center (KANRRC) assessed some micro-watersheds for the collection of storm-wise runoff and associated sediment. The Sanganeh research micro-watershed, located 100 km from Mashhad City (northeast Iran), is one of the watersheds selected for this study. The watershed area, the longest waterways, and the mean slope of the watershed are 1.2 ha, 145.0 m, and 31.2%, respectively. The study watershed consists of semi-arid rangeland dominated by Bromus tectorum and Artemisia diffusa, with a coverage of 50%. The soil is Entisol and Aridosol, young, with a maximum depth of 30 cm. The mean electrical soil conductivity (EC), soil organic matter (OM), clay, sand, silt, and surface rock fragments of soils are 1.81, 1.57, 10.6, 54.7, 34.7, and 5%, respectively. In this research, three experimental small watersheds with areas between 4300-12000 m2 were selected along with the erosion plots in them. Then, 24 rainfall events related to two periods of 2006-2009 and 2016-2018 were recorded along with the corresponding data of runoff and sediment in watersheds and plots. In this study, water flow and sediment yield were monitored at the main outlet of the micro-watersheds and plots. The runoff volume was calculated after each storm event by multiplying the depth of collected water, measured using an iron ruler at five points in the tank (corners and central), by the surface area of the collector. The collected runoff and sediment were then mixed thoroughly and one sample was taken to determine sediment concentration and sediment yield. Then, by collecting the required information (includeing rainfall erosivity, topography, conservation practice, soil erodibility, and cover-crop management factors), the RUSLE model was run and compared with the observation data of the plots. The storm-wise soil erosion predictions were compared with observed data based on the criteria of the coefficient of determination (R2) and relative estimation error (RE). In the following, by modifying the RUSLE model and observing the sedimentation data of the studied watersheds, the value of the SDR was estimated.
 
Results and Discussion
After collecting the required information, the RUSLE model was implemented at the plot scale. The accuracy of the model was evaluated using erosion plot data, which was not confirmed due to huge overestimations of RUSLE. Next, to achieve more accurate results, regression types (linear, exponential, power, etc.) were used between the observed and estimated values of soil erosion (RUSLE). After applying the correction coefficient, this model was able to estimate the average erosion rate of the whole period are 12, 17, and 2% for E1, E4, and E6 watersheds, respectively, which is within the acceptable range of soil erosion modeling. Therefore, it can be said that the accuracy of the modified RUSLE model (by regression model) in estimating the average soil erosion during the period is higher than the event-based scale. Also, the prediction of maximum event estimation error for E1, E4, and E6 watersheds was 25.7, 35.8, and 21.6%, respectively. After evaluating the accuracy of the RUSLE model at the plot scale and in order to know the amount of soil erosion at the watershed scale, the values ​​of L, S, K, and C factors for the watersheds were calculated based on a weighted average and entered into the modified model. Therefore, the results of the RUSLE model were generalized to the watershed scale. In the final stage, by dividing the amount of erosion by the corresponding amounts of sediment yield measured at the outlet of watersheds, the ratio of sediment delivery was calculated. The average SDR of the entire period in the E1, E4, and E6 watersheds are 42.2, 41.5, and 39.7%, respectively, and in the maximum events, it is one or two percent higher.
 
Conclusion
Overall, the results of this research showed that using the modified RUSLE model, it is possible to estimate the average soil erosion in the Sangane soil conservation station and also estimate the SDR. Therefore, this approach can be used in executive programs in similar areas. According to the obtained results, the classification of rainfall data based on the rain erosive factor and then the evaluation of the RUSLE model can provide more accurate results. In addition, in this research, due to the small area of the watersheds, waterway processes did not play a role in the deposition and transfer of eroded soils. It is also suggested that similar research could be done in larger watersheds. Finally, considering the determination of the SDR in this area, it is recommended to evaluate the accuracy of the experimental methods for determining the SDR.

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Main Subjects


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