A review of the application of the MUSLE model worldwide

Sadeghi, Seyed Hamidreza; Gholami, Leila; Darvishan, Abdulvahed Khaledi; Pari, Saeidi

doi:10.1080/02626667.2013.866239

Cited by 98 publications

(69 citation statements)

References 28 publications

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“…The RUSLE2 framework is a computer interface to handle more complex field situations, including an updated database of 25 factors (Foster et al, 2003). These three variations of R/USLE measure soil loss at an annual time scale, but the MUSLE uses runoff and peak flow rate to estimate event-based soil loss (Sadeghi et al, 2014). None of these approaches originally include seasonal soil loss, but this paper points to improvements in seasonal soil loss estimation as a future direction for R/USLE studies.…”

Section: Equation Version 2 (Rusle2) and The Modified Universal Soilmentioning

confidence: 99%

“…R/USLE applications usually estimate soil loss at the annual timescale, and the MUSLE estimates soil loss from a single storm event (Renard et al, 1997;Sadeghi et al, 2014). As seen in the review of methods to calculate rainfall erosivity, many 20 different studies have attempted to estimate the R-factor, underscoring its importance to soil erosion research.…”

Section: Seasonal Erosion Vulnerabilitymentioning

confidence: 99%

“…This review addresses the complexity of the different factors, and things for 10 researchers to consider before applying R/USLE to their study area. The MUSLE is not included in this review because an extensive review of the model has already been done by Sadeghi et al (2014) and event-scale estimates are beyond the scope of this paper.…”

Section: Equation Version 2 (Rusle2) and The Modified Universal Soilmentioning

confidence: 99%

See 2 more Smart Citations

A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

Benavidez¹,

Jackson²,

Maxwell³

et al. 2018

Preprint

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Abstract. Soil erosion is a major problem around the world because of its effects on soil productivity, nutrient loss, siltation in water bodies, and degradation of water quality. By understanding the driving forces behind soil erosion, we can more easily identify erosion-prone areas within a landscape and use land management and other strategies to effectively manage the problem. Soil erosion models have been used to assist in this task. One of the most commonly used soil erosion models is 10 the Universal Soil Loss Equation (USLE) and its family of models: the Revised Universal Soil Loss Equation (RUSLE), the Revised Universal Soil Loss Equation version 2 (RUSLE2), and the Modified Universal Soil Loss Equation (MUSLE). This paper reviewed the different components of USLE and RUSLE etc., and analysed how different studies around the world have adapted the equations to local conditions. We compiled these studies and equations to serve as a reference for other researchers working with R/USLE and related approaches. We investigate some of the limitations of R/USLE, such as issues 15 in data-sparse regions, its inability to account for soil loss from gully erosion or mass wasting events, and that it does not predict sediment pathways from hillslopes to water bodies. These limitations point to several future directions for R/USLE studies: incorporating soil loss from other types of soil erosion, estimating soil loss at sub-annual temporal scales, and using consistent units for future literature. These recommendations help to improve the applicability of the R/USLE in a range of geoclimatic regions with varying data availability, and at finer spatial and temporal scales for scenario analysis. 20

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Section: Equation Version 2 (Rusle2) and The Modified Universal Soilmentioning

confidence: 99%

Section: Seasonal Erosion Vulnerabilitymentioning

confidence: 99%

Section: Equation Version 2 (Rusle2) and The Modified Universal Soilmentioning

confidence: 99%

See 1 more Smart Citation

A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

Benavidez¹,

Jackson²,

Maxwell³

et al. 2018

Preprint

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“…It is also reasonable to consider current conditions of a particular catchment instead of employing the one-size-fits-all approach to modeling [61,62].…”

Section: Model Descriptionmentioning

confidence: 99%

Streamflow and Sediment Yield Prediction for Watershed Prioritization in the Upper Blue Nile River Basin, Ethiopia

Ayele

Teshale

et al. 2017

Water

127

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Inappropriate use of land and poor ecosystem management have accelerated land degradation and reduced the storage capacity of reservoirs. To mitigate the effect of the increased sediment yield, it is important to identify erosion-prone areas in a 287 km 2 catchment in Ethiopia. The objectives of this study were to: (1) assess the spatial variability of sediment yield; (2) quantify the amount of sediment delivered into the reservoir; and (3) prioritize sub-catchments for watershed management using the Soil and Water Assessment Tool (SWAT). The SWAT model was calibrated and validated using SUFI-2, GLUE, ParaSol, and PSO SWAT-CUP optimization algorithms. For most of the SWAT-CUP simulations, the observed and simulated river discharge were not significantly different at the 95% level of confidence (95PPU), and sources of uncertainties were captured by bracketing more than 70% of the observed data. This catchment prioritization study indicated that more than 85% of the sediment was sourced from lowland areas (slope range: 0-8%) and the variation in sediment yield was more sensitive to the land use and soil type prevailing in the area regardless of the terrain slope. Contrary to the perception of the upland as an important source of sediment, the lowland in fact was the most important source of sediment and should be the focus area for improved land management practice to reduce sediment delivery into storage reservoirs. The research also showed that lowland erosion-prone areas are typified by extensive agriculture, which causes significant modification of the landscape. Tillage practice changes the infiltration and runoff characteristics of the land surface and interaction of shallow groundwater table and saturation excess runoff, which in turn affects the delivery of water and sediment to the reservoir and catchment evapotranspiration.

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“…Sediment load measurements are useful to calibrate soil erosion models (Tazioli et al 2005;Khaledi Darvishan et al 2010;Tazioli, 2009;Spalevic, 2011;Sadeghi et al 2013Sadeghi et al , 2014. Modelling, in fact, is a good, often necessary and proven tool useful to evaluate the amount of discharge and erosion in a watershed, especially when hydrometric and discharge data are not available (Behzadfar et al 2014).…”

Section: Introductionmentioning

confidence: 99%

Calculation of Sediment Yield in the S2-1 Watershed of the Shirindareh River Basin, Iran

Darvishan¹,

Behzadfar²,

Spalević³

et al. 2017

AgricultForest

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SUMMARYSoil erosion by water as a natural process can occur in all climates and zones and change all landforms. As the measuring of soil erosion is costly and time consuming process, dozens of erosion prediction models have been developed and the aim of the majority of all of them is to predict average rates (often an annual average rate) of soil loss from an area such as a plot, a field or a catchment/watershed under various land management techniques. On the other hand, outflow is the most important element of the hydrological cycle and that is why it is important to determine it as accurately as possible by measuring and predicting. Therefore, the IntErO (Intensity of Erossion and Outflow) model based on the EPM (Erosion Potential Method) method was used for calculation of outflow and sediment yield in the S2-1 watershed of Shirindareh River Basin in the Northeast Iran with the area of 46.77 km2. According to the results, the predicted peak discharge was 101 m3 s-1 for the incidence of 100 years and the specific sediment yield was 267 m3 km-2 year-1. According to the previous studies and topographic characteristics, the river basin watershed belongs to the V category and has very weak erosion. The results of the present study and previous experiences of the other researchers revealed that the IntErO model can be used to estimate soil loss in the other regions similar to Shirindareh River Basin.

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A review of the application of the MUSLE model worldwide

Cited by 98 publications

References 28 publications

A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

A review of the (Revised) Universal Soil Loss Equation (R/USLE): with a view to increasing its global applicability and improving soil loss estimates

Streamflow and Sediment Yield Prediction for Watershed Prioritization in the Upper Blue Nile River Basin, Ethiopia

Calculation of Sediment Yield in the S2-1 Watershed of the Shirindareh River Basin, Iran

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