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The sediment transport, involving the movement of the bedload and suspended sediment in the basins, is a critical environmental concern that worsens water scarcity and leads to degradation of land and its ecosystems. Machine learning (ML) algorithms have emerged as powerful tools for predicting sediment yield. However, their use by decision-makers can be attributed to concerns regarding their consistency with the involved physical processes. In light of this issue, this study aims to develop a physics-informed ML approach for predicting sediment yield. To achieve this objective, Gaussian, Center, Regular, and Direct Copulas were employed to generate virtual combinations of physical of the sub-basins and hydrological datasets. These datasets were then utilized to train deep neural network (DNN), conventional neural network (CNN), Extra Tree, and XGBoost (XGB) models. The performance of these models was compared with the modified universal soil loss equation (MUSLE), which serves as a process-based model. The results demonstrated that the ML models outperformed the MUSLE model, exhibiting improvements in Nash–Sutcliffe efficiency (NSE) of approximately 10%, 18%, 32%, and 41% for the DNN, CNN, Extra Tree, and XGB models, respectively. Furthermore, through Sobol sensitivity and Shapley additive explanation–based interpretability analyses, it was revealed that the Extra Tree model displayed greater consistency with the physical processes underlying sediment transport as modeled by MUSLE. The proposed framework provides new insights into enhancing the accuracy and applicability of ML models in forecasting sediment yield while maintaining consistency with natural processes. Consequently, it can prove valuable in simulating process-related strategies aimed at mitigating sediment transport at watershed scales, such as the implementation of best management practices. [ABSTRACT FROM AUTHOR]

The study utilized the Modified Universal Soil Loss Equation (MUSLE) to predict sediment loss and evaluate the model's performance in the Agewmariam experimental watershed in order to support the planning, management, and appropriate use of the soil and water resources in the watershed. The natural resources conservation service (NRCS) curve number method was used to model runoff energy factor. By overlaying maps of runoff energy, soil erodibility, slope length and steepness, cover management, and support practice factors with assigned values, the cumulative effect of these parameters for the suspended sediment yield was calculated using the ArcGIS raster calculator. The runoff energy factor was the most sensitive parameter, followed by slope length and steepness factor. To improve the model's fit to the local conditions, the initial abstraction to storage ratio (λ) of the runoff energy factor was reduced to 0.023, and the MUSLE model coefficient and exponent were adjusted to 1 and 0.59, respectively. During calibration, the mean observed and estimated suspended sediment yields were 0.2 and 0.23 ton/ha, respectively, while during validation, they were 0.7 and 0.53 ton/ha, respectively. The model evaluation showed that the MUSLE model, without calibration, was not appropriate for estimating runoff and sediment yield. However, with appropriate calibration, the model showed good performance with a coefficient of determination (R2), coefficient of efficiency (E), and index of agreement (d) of 0.85, 0.85, and 0.96 respectively, during calibration and 0.84, 0.65, and 0.83 respectively, during validation. Based on these findings, this study suggests that the calibrated MUSLE model can be used to prioritize soil and water conservation interventions within the watershed or can be extrapolated to neighboring similar watersheds. Further refinement of model input parameters using more data from the watershed is recommended to increase the prediction accuracy of the model.

Predicting and estimating sediment yield from the catchment is crucial for the effective management of water resources and controlling soil erosion. Until now, Universal Soil Loss Equations (USLE) and their modifications are appreciated and commonly applied among many methods. The idea of this work is to use the ESDAC database (a web platform hosting a series of pan-European and global datasets on soil erosion) to build the modified form of the USLE for the Zagożdzonka catchment, a small agricultural area located in central Poland. The calculated sediment yield is compared with the one determined based on the reservoir survey. Conducted analyses show that the average annual suspended sediment yield from the study catchment estimated using the MUSLE equation accounts for 201 Mg and is close to that determined based on the reservoir survey, i.e., 248 Mg. However, MUSLE, with the initially proposed parameters, will overpredict sediment transport at the study site. The ESDAC database may support local studies concerning soil erosion and sediment transport. The research is helpful for policymakers, planners, and engineers.

Predicting and estimating sediment yield from the catchment is crucial for the effective management of water resources and controlling soil erosion. Universal Soil Loss Equations (USLE) and their modifications have been appreciated and commonly applied among many methods. The idea of this work is to use the ESDAC database (a web platform hosting a series of pan-European and global datasets on soil erosion) to build the modified form of the USLE for the Zagożdzonka catchment, a small agricultural area located in central Poland. The calculated sediment yield is compared with the one determined based on the reservoir survey. The conducted analyses show that the average annual suspended sediment yield from the study catchment estimated using the MUSLE equation accounts for 201 Mg and is close to that determined based on the reservoir survey, i.e., 248 Mg. However, MUSLE, with the initially proposed parameters, will overpredict sediment transport at the study site. The ESDAC database may support local studies concerning soil erosion and sediment transport. The research is helpful for policymakers, planners, and engineers. [ABSTRACT FROM AUTHOR]

Sediment accumulation is a major factor in reducing irrigation reservoir useful life as well as reducing the reservoir capacity. Therefore, the goal of this study was to estimate the volume of sediment accumulated in the reservoir using a bathymetric survey and to assess the watershed sediment yield to reservoirs using the Modified Universal Soil Loss Equation (MUSLE) model. The bathymetric survey method involves subtracting the two-period capacities, one before dam construction and one after dam construction. On the other hand, the sediment inflow calculated by the MUSLE model over the last six years is estimated after determining the physical parameters (K, LS, C, and P factors) and runoff index (VQ and QP) from the watershed using ArcGIS 10.8 and Excel software. The bathymetric survey showed that 297,000m3 (362,340 tons) of sediment had accumulated in the reservoir over six years of operation, whereas the Modified Universal Soil Loss Equation estimated 256,262.86 tons of sediment yield at the outlet of the watershed (inflow to the reservoir). This means that the reservoir's total capacity has been reduced by 7.52 percent and 5.4 percent, respectively, over the last six years of operation, using a bathymetric survey and the Modified Universal Soil Loss Equation. According to the bathymetric survey results, the reservoir will not be functional for more than 15 years if the sediment rate remains the same as in the previous six years. Using the bathymetry method, the sedimentation rates of the dead storage and live storage zones were 31,666.67 m3/year and 48,333.33 m3/year, respectively. The watershed's sediment yield and specific sediment yield were determined using bathymetry survey results to be 61,371.95 tons/year and 45.46 tons/ha/year, respectively, whereas the sediment yield using the MUSLE model was 31.64 tons/ha/year. Since the watershed generated large amount of sediment, so to protect the filling of reservoir, the stake holders should have to apply watershed management techniques as well as should have to avoid farming near to the reservoir area. [ABSTRACT FROM AUTHOR]

Sediment yield estimation along with identification of soil erosion mechanisms is essential for developing sophisticated management approaches, assessing, and balancing different management scenarios and prioritizing better soil and water conservation planning and management. At the watershed scale, land management practices are commonly utilized to minimize sediment loads. The goal of this research was to estimate sediment yield and prioritize the spatial dispersion of sediment-producing hotspot areas in the Nashe catchment using the Soil and Water Assessment Tool (SWAT). Moreover, to reduce catchment sediment output, this study also aims to assess the effectiveness of certain management practices. For calibration and validation of the model, monthly stream flow and sediment data were utilized. The model performance indicators show good agreement between measured and simulated stream flow and sediment yields. The study examined four best management practice (BMP) scenarios for the catchment's designated sub-watersheds: S0 (baseline scenario), S1 (filter strip), S2 (stone/soil bunds), S3 (contouring), and S4 (terracing). According to the SWAT model result, the watershed's mean yearly sediment output was 25.96 t/ha. yr. under baseline circumstances. The model also revealed areas producing the maximum sediment quantities indicating the model's effectiveness for implementing and evaluating the sensitivity of sediment yield to various management strategies. At the watershed scale, treating the watershed with various management scenarios S1, S2, S3, and S4 decreased average annual sediment yield by 34.88%, 57.98%, 39.55%, and 54.77%, respectively. The implementations of the soil/stone bund and terracing scenarios resulted in the maximum sediment yield reduction. The findings of this study will help policymakers to make better and well-informed decisions regarding suitable land use activities and best management strategies. [ABSTRACT FROM AUTHOR]

Authors propose a beneficial methodology for hydrological planning in their study. Prospective evaluations of the basins’ net capacity can be done using the technique presented. The HEC-HMS (Hydrologic Modelling System) software can be used to estimate in a basin, the sediment emitted. For a certain precipitation, this methodology allows estimating, within a certain range, the gradual blockage of a reservoir, and even a projected date for total blockage. This has some applications to adopt corrective measures that prevent or delay the planned blockage deadlines. The model is of the semi-distributed type, estimating the generation and emission of sediments by sub-basins. The integration of different return periods in HEC-HMS with a semi-distributed model by sub-basins and the application of a mathematical model are the differentiating element of this research. The novelty of this work is to allow prognosing the reservoir sedimentation rate of basins in a local and regional scale with a medium and large temporary framework. The developed methodology allows public institutions to take decisions concerning hydrological planning. It has been applied to the case of “Charco Redondo” reservoir, in Cádiz, Andalusia, in southern Spain. Applying the methodology to this case, an average soil degradation of the reservoir basin has been estimated. Therefore, it is verified that in 50 years the reservoir is expected to lose 8.4% of its capacity.

Sediment accumulation is a major factor in reducing a reservoir's useful life. As a result, information on any changes in storage capacity is required to reduce the reservoir's risk. Therefore, the goal of this study was to determine the amount of sediment entering the reservoir using the Modified Universal Soil Loss Equation (MUSLE). The sediment entering into the reservoir was calculated by the MUSLE model over the last six years and is estimated after determining the physical parameters (K, LS, C, and P factors) and runoff index (VQ and QP) from the watershed using ArcGIS 10.8 and Excel software. The single event sediment (daily sediment) using MUSLE was a product of physical parameters (K, LS, C, and P factors) and runoff index (VQ and QP). The Modified Universal Soil Loss Equation estimated 256,262.86 tons of sediment yield at the outlet of the watershed (inflow to the reservoir in the last six years). The reservoir's total capacity has been reduced by 5.4 percent over the last six years of operation. The average rate of sedimentation was estimated at 42,710.48 tons/year or 31.64 tons/ha/year. Hence; the annual capacity reduction of the reservoir was 0.9 percent.

The study aims to estimate annual sediment yields of Mayurakshi River Basin using SWAT tool of ArcGIS. Climatic aspects, soil, land use and slope maps were integrated within SWAT tool to predict sediment yield capacity using MUSLE method. Alongside, the study attempts to identify spatial distribution of major gully erosion prone sites using ANN and RF models. Twelve Gully Erosion Conditioning Factors namely, elevation, curvature, aspect, runoff, TWI, slope, geology, stream frequency, rainfall erosivity, NDVI, LS-factor and LULC were selected. A gully erosion inventory map was prepared using 128 gully sites and divided into training (70%) and testing (30%) classes. Results obtained from the study shows that sediment yield capacity is very high in north-western and south-western parts of the basin due to high probability of gully erosion. Both ANN (ROC 0.96, Kappa 0.92) and RF (ROC 0.97, Kappa 0.94) models have high prediction accuracy and strong interrater reliability with MUSLE (0.60 and 0.75). [ABSTRACT FROM AUTHOR]

Managing water resources requires consideration of both environmental and socio-economic benefits to effectively balance the benefits and costs. This includes identifying ecosystem services (ES) of concern and how to evaluate the project or proposed changes effect on these ES. The purpose of this effort is to describe methods to evaluate ecosystem services to provide expanded irrigation to existing agricultural lands in Alabama and the potential application to other areas. A case study has been undertaken on the Middle Alabama watershed in central Alabama and methods have been developed and applied to evaluate ES in terms of how irrigated versus rainfed fields will affect sediment retention, fertilizer usage and the effect of the subsequent discharges of sediment and nitrogen from fertilizer on water quality. The results of case studies in the Middle Alabama watershed indicate positive ES benefits from sustainable agricultural practices and the irrigation of agricultural lands versus rainfed fields. We anticipate these methods will be applicable to other watersheds outside the southeast region too. [ABSTRACT FROM AUTHOR]

A remote sensing and GIS-based watershed scale model has been developed that simulates event-based runoff and sediment yield at each grid of the DEM. The model estimates the runoff and sediment yield in each grid using the natural resources conservation service (NRCS) curve number method and modified universal soil loss equation (MUSLE), respectively, and routes these hydrological parameters using the Muskingum method of routing. The model requires four input files, viz., rainfall, DEM, soil map, and land use map. The model takes the DEM as the primary input which is processed for the determination of various watershed characteristics. The model code for DEM processing, estimation of runoff, and sediment yield and routing is written in Python language and the graphical user interface is written in HTML + JavaScript language. The developed model has been evaluated for its performance on a gauged forest watershed (40.3 ha) located in Shivaliks of North-West India. The test statistics of the developed model indicates reasonably accurate simulation of runoff and sediment yield as is evident from lower values of percent bias (6.40% and − 3.95%), mean bias error (2.52 mm and 0.18 Mg ha−1), mean absolute percent error (1.39 and 0.24) and root mean square error (4.02 mm and 0.29 Mg ha−1), and high values of correlation coefficient (0.936 and 0.974) and Nash–Sutcliffe model efficiency (88.42% and 82.74%). Hence, the developed model can be applied for the simulation of event-based runoff and sediment yield from the watersheds. [ABSTRACT FROM AUTHOR]

AbstractLanduse changes and rainfall intensity from natural vegetation to cultivated fields both impact on river streamflows and sediment dynamics. Assessing the magnitude of these flow and sediment changes is important to water management. However, many rivers are still under-studied/monitored and data sparse. Fully distributed rainfall-runoff models, such as JAMS/J2000, allow for simulation of streamflow, its flow components and potential sediment yield given landuse and hydrological changes. This study demonstrates the use of this method in the Bot River, a data-scarce catchment in South Africa. A hydrological model was implemented, and sediment yield was estimated under three landuse and two hydrological flow component scenarios. The model reported Nash-Sutcliffe efficiencies (E2) of 0.64 and 0.32 (for streamflow) for model calibration and validation periods, respectively. Modelled mean annual sediment yield increased from 423 t/km2/yr in 1990 to 490 t/km2/yr in 2018, attributable to landuse changes. [ABSTRACT FROM AUTHOR]

En el ámbito de la llanura pampeana tienen lugar procesos degradativos que condicionan la actividad agrícola ganadera, vinculados con la erosión de tipo hídrica superficial. El presente trabajo busca modelar la emisión de sedimentos en una cuenca hidrográfica con forestaciones del Noreste Pampeano. La metodología implementada consiste en aplicar un modelo cartográfico cuantitativo desarrollado en base geoespacial con Sistema de Información Geográfica, apoyado en la Ecuación Universal de Pérdida de Suelo Modificada (MUSLE). Se realizó un análisis de validación estadística con ensayos de microsimulador de lluvias a campo, para una lluvia de 30 mm.h-1 de dos años de retorno. Los resultados obtenidos fueron mapas georreferenciados de cada factor de la MUSLE valorizados por color-intensidad, que alcanzan un valor de 33,77 Mg de sedimentos emitidos a la salida de la cuenca, con un coeficiente de correlación de 0,94 y un grado de ajuste de Nash-Sutcliffe de 0,82. Se concluye que el modelo cartográfico generó información espacial precisa de los componentes de la MUSLE para un evento de lluvia concreto. La aplicación del microsimulador de lluvias permitió la obtención de valores reales de emisión de sedimentos, lográndose un alto grado de ajuste. La emisión de sedimentos en la cuenca resultó ser leve a nula.

The study utilized the Modified Universal Soil Loss Equation (MUSLE) to predict sediment loss and evaluate the model's performance in the Agewmariam experimental watershed in order to support the planning, management, and appropriate use of the soil and water resources in the watershed. The natural resources conservation service (NRCS) curve number method was used to model runoff energy factor. By overlaying maps of runoff energy, soil erodibility, slope length and steepness, cover management, and support practice factors with assigned values, the cumulative effect of these parameters for the suspended sediment yield was calculated using the ArcGIS raster calculator. The runoff energy factor was the most sensitive parameter, followed by slope length and steepness factor. To improve the model's fit to the local conditions, the initial abstraction to storage ratio (λ) of the runoff energy factor was reduced to 0.023, and the MUSLE model coefficient and exponent were adjusted to 1 and 0.59, respectively. During calibration, the mean observed and estimated suspended sediment yields were 0.2 and 0.23 ton/ha, respectively, while during validation, they were 0.7 and 0.53 ton/ha, respectively. The model evaluation showed that the MUSLE model, without calibration, was not appropriate for estimating runoff and sediment yield. However, with appropriate calibration, the model showed good performance with a coefficient of determination (R 2 ), coefficient of efficiency (E), and index of agreement (d) of 0.85, 0.85, and 0.96 respectively, during calibration and 0.84, 0.65, and 0.83 respectively, during validation. Based on these findings, this study suggests that the calibrated MUSLE model can be used to prioritize soil and water conservation interventions within the watershed or can be extrapolated to neighboring similar watersheds. Further refinement of model input parameters using more data from the watershed is recommended to increase the prediction accuracy of the model., Competing Interests: The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Yonas Reda reports financial support was provided by Sekota Dryland Agricultural Research Centre (SDARC). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2024 The Authors.)

Flash floods, among the most destructive natural hazards, are commonly studied as to their catastrophic power in terms of fatalities, infrastructure damages and economic losses. A devastating aftermath of flash floods, which has not received much‐deserved attention in the literature, is the sizeable and permanent soil loss due to soil erosion and sediment yields. This study aims at forecasting soil erosion and sediment yields due to the disastrous storm event that occurred in Mandra town (western Attica, Greece) on 15 November 2017. Gridded hydrometeorological forecasts were conducted at 5‐min and 1‐h time steps by means of the chemical hydrological atmospheric ocean wave system (CHAOS). The forecasts of soil erosion and sediment yields were achieved by a high‐resolution geographic information system (GIS) application of the modified universal soil loss equation (MUSLE) on the basis of the forecasted surface runoff hydrographs. The entire event lasted from the afternoon of 14 November until noon of 15 November, but the bulk of the disastrous storm occurred in the morning of 15 November 2017, flooding two torrent basins. As a result of the extreme flash flood, 2195 tons and 1435 tons of sediment were forecasted to be detached from the body of the soil's surface and transported to the stream networks of the Soures and Agia Aikaterini Torrent basins which cross Mandra. Soil erosion maps were constructed for every hour and the spatial and temporal evolution of soil erosion was shown throughout the event. This study provides concrete insights on the erosion‐prone areas of the study basins, which can inform actions against erosion. [ABSTRACT FROM AUTHOR]

The effect of the topographic factor of the Modified Universal Soil Equation (MUSLE) on soil erosion and sediment yield is not clear. Except for the coefficient, soil erodibility, cover, and conservation practice factors of the MUSLE, an individual effect of the exponents and topographic factors of the MUSLE on soil erosion and sediment yield can be seen by applying the model at different watersheds. A primary objective of this paper is to estimate the best exponents and topographic factors of the MUSLE under the hydro-climatic conditions of Ethiopia. For the sake of the calibration procedure, the main factors of the MUSLE that directly affect the soil erosion process, such as cover, conservation practice, soil erodibility, and topographic factors, are estimated based on past experiences from the literature and comparative approaches, whereas the parameters that do not directly affect the erosion process or that have no direct physical meaning (i.e., coefficient a and exponent b) are estimated through calibration. We verified that the best exponent of the MUSLE is 1 irrespective of the topographic factor, which results in the maximum performance of the MUSLE (i.e., approximately 100%). The best exponent that corresponds to the best equation of the topographic factor is 0.57; in this case, the performance of the model is greater than or equal to 80% for all watersheds under our consideration. We expect the same for other watersheds of Ethiopia, while for other exponents and topographic factors, the performance of the model decreases. Therefore, for the conditions of Ethiopia, the original exponent of the MUSLE is changed from 0.56 to 0.57, and the best equations of the topographic factor are provided in this paper. [ABSTRACT FROM AUTHOR]

A primary objective of this paper is to change the input data requirement of the Modified Universal Soil Loss Equation (MUSLE) for the calculation of its runoff factor for possible application in data-scarce areas. Basically, the MUSLE was developed for a small agricultural watershed, where the extent of erosion is from sheet to rill erosion, but we cannot exactly tell whether it considers gully erosion or not. The underlying physical assumption to improve the MUSLE is that the amount of potential energy of runoff is proportional to the shear stress for sediment transport from a slope field and the kinetic energy of the runoff at the bottom of the slope field for gully formation. The improved MUSLE was tested at four watersheds in Ethiopia, and it showed better performance (i.e., the minimum performance is 84%) over the original MUSLE (i.e., the minimum performance was 80%), for all four watersheds under our consideration. We expect the same to be true for other watersheds of Ethiopia. [ABSTRACT FROM AUTHOR]

Brahmaputra River Basin (BRB), the largest contributor of sediment load in Ganges–Brahmaputra–Meghna delta, is highly vulnerable to future climate change. Several studies assessed the effects of climate change of BRB on river flow but an assessment on sediment load has not been conducted. Changes in sediment load in the future need to be assessed to control and manage sediment flows in large catchments properly. The present study focuses on developing a hydrological and sediment routing model of BRB using the HEC-HMS model to estimate future sediment load together with the flow for the RCP 8.5 climate scenario. Modified Universal Soil Loss Equation and Engelund Hansen method of HEC-HMS have been applied for the sediment transport of BRB. The model has been calibrated using daily runoff for the period 1983–1996 and validated for the period 1997–2010, respectively. The uncertainty in the percentage change in seasonal sediment load during the pre-monsoon season is higher than that of the monsoon season. However, the contribution of the sediment load of pre-monsoon is very much lower than the monsoon season. The percentage changes in mean annual sediment load compared to the baseline period for the 2020s, 2050s and 2080s are 34, 67 and 115%, respectively. HIGHLIGHTS This is the first attempt to assess the future changes in the sediment load of the Brahmaputra River Basin (BRB).; Soil Moisture Accounting (SMA) method was used for simulating continuous rainfall–runoff processes.; The hydrological model was developed using a high-resolution bias-corrected multi-model ensemble RCM.; The percent changes in mean annual sediment load for the years of 2010–2039 (2020s), 2040–2069 (2050s) and 2070–2099 (2080s) are 34, 67 and 115%, respectively.; The uncertainties associated with the projected sediment loads of BRB increase with time in the future.;

From 26th August 2022 to 20th August 2023, an exhibition of shells of Mediterranean gastropods and bivalves from the collection of Mr. Dimitris Iakovidis and his daughter Niki Iakovidou was on display in the Regional Museum in Olomouc. In addition to the aesthetic experience, visitors could learn about the biology of the species on display and the ways in which humans can use them. The exhibition also included a zone for children, who could choose a seashell to take home. From the entries in the visitors‘ book, it was clear that the exhibition had fulfilled its aim of both showing the beauty of shells and encouraging an ecological sensitivity to marine life. [ABSTRACT FROM AUTHOR]

The Keeler Dunes Complex is an active dunefield located adjacent to Owens (dry) Lake, California. The source of sediment to the Keeler Dunes area is often assumed to be from the Owens Lake playa; however, the dunes lie at the toe of the Slate Canyon alluvial fan (the Fan). Here hydrologic and hydraulic modeling was conducted for the Fan to assess the contribution of fan sediment to the Keeler Dunes. Assessment of the potential for sediment deposition was conducted for two scenarios based on the relocation of State Highway 136 from the Owens Lake playa upgradient on the Fan and the subsequent construction of flow diversion berms. The berm construction (1954 and 1967) coincided with observations of the destabilization and migration of the Keeler Dunes. Runoff from Slate Canyon watershed was estimated using a Hydrological Simulation Program–Fortran (HSPF) model based on hourly precipitation records. The resulting hydrology output served as inputs to FLO-2D models of the Fan. With the model of hydraulic output, it was estimated that approximately one million tons of sediment were moved from the Fan hydrographic apex toward the Keeler Dunes area during the peak streamflow event of record. This represents a significant volume with respect to the total volume of the Keeler Dunes. Our modeling of the peak flow event indicates the construction of the highway diversion berms resulted in the partial redirection of fan flows and therefore sediment deposition in relation to the Keeler Dunes. This localized change in sediment availability and spatial distribution is a likely factor in the subsequent morphogenesis of the dunes.

The proposed site for the construction of a new dam (Laleni Dam) on the Tsitsa River in the Eastern Cape, South Africa falls within a high soil erosion zone, which is expected to affect the lifespan of the dam. Estimating the sediment yield of the catchment is important from a management perspective, and thus we designed this study to assess the applicability of the Modified Universal Soil Loss Equation (MUSLE). The original MUSLE was applied to the Inxu River sub catchment, upstream of a proposed dam, over a summer rainfall period extending from October 2016 to April 2017. A modified version of the MUSLE, incorporating a storage module, was later applied over the same period. Model calibration of the MUSLE with and without a storage model was tested against 7 months of recorded daily suspended sediment discharge data. With a storage model, we achieved a percentage bias, coefficient of efficiency and R2 of 2%, 0.83 and 0.83, respectively, while without storage the performance statistics were markedly lower. These results suggest that a calibrated MUSLE can provide estimates of sediment yield that are valuable for regional planning, and that the inclusion of a storage component further improves the MUSLE application. Given the complexity of sediment generation and transport processes, a relatively simple empirical MUSLE model is a useful tool for initial sediment yield estimation for planning purposes.

This study compares different methods to calculate erosion and sedimentation processes in the Aviar Basin, a natural peri-urban basin located in Comúd'Encamp (Andorra). The basin area is small, covering less than one square kilometer. Currently, increased densities of houses and buildings under natural basins can cause drainage problems. This is due to the heavy accumulation of eroded solid material in the sewer systems. Therefore, for a given basin condition, accurate estimation of erosion and sedimentation amounts is important. The development of erosion models aims to facilitate the estimation of eroded solid material and the design of possible protective measures to prevent soil losses. Both empirical and physically based erosion models were used to study the Aviar Basin for these purposes. Empirical models include USLE (Universal Soil Loss Equation), RUSLE (Revised USLE) and MUSLE (Modified USLE), while one physically based model, KINEROS 2, was used. The volumes of solid materials produced in the Aviar Basin during the year 2012 were determined using these four different erosion models and then compared between them. The results of this study show that the estimation of soil loss using KINEROS 2 is useful in practice because the results obtained are close to those obtained from the empirical models. [ABSTRACT FROM AUTHOR]

Managing water resources requires consideration of both environmental and socio-economic benefits to effectively balance the benefits and costs. This includes identifying ecosystem services (ES) of concern and how to evaluate the project or proposed changes effect on these ES. The purpose of this effort is to describe methods to evaluate ecosystem services to provide expanded irrigation to existing agricultural lands in Alabama and the potential application to other areas. A case study has been undertaken on the Middle Alabama watershed in central Alabama and methods have been developed and applied to evaluate ES in terms of how irrigated versus rainfed fields will affect sediment retention, fertilizer usage and the effect of the subsequent discharges of sediment and nitrogen from fertilizer on water quality. The results of case studies in the Middle Alabama watershed indicate positive ES benefits from sustainable agricultural practices and the irrigation of agricultural lands versus rainfed fields. We anticipate these methods will be applicable to other watersheds outside the southeast region too.

Water erosion is a major cause of soil degradation worldwide. This natural phenomenon has been continually accelerated by anthropogenic activities, with constants increase of soil losses. The main objective of this study was to apply the Modified Universal Soil Loss Equation (MUSLE) model to estimate soil loss in rainy events during one year period. The total study was conducted between August 2017 and July 2019 in coffee growing areas located in the Serra da Mantiqueira, Southern Minas Gerais, Brazil. Most of the factors used for the MUSLE equation were determined from Geographic Information Systems. The results showed that soil losses ranged from 53.40 to 28.37 Mg in both areas depending on the land use and 33.12 and 23.82 Mg related to the soil classes. The largest soil losses were estimated to exposed soils in eucalyptus without conservationist practices, in the highest slopes and in Haplic Cambisol (CX). It was concluded that the conservation management practices correlated to anthropic activities adopted in the coffee crop contributed to the reduction of soil losses and maintenance of edaphic conditions. [ABSTRACT FROM AUTHOR]

A primary objective of this paper is to change the input data requirement of the Modified Universal Soil Loss Equation (MUSLE) for the calculation of its runoff factor for possible application in data-scarce areas. Basically, the MUSLE was developed for a small agricultural watershed, where the extent of erosion is from sheet to rill erosion, but we cannot exactly tell whether it considers gully erosion or not. The underlying physical assumption to improve the MUSLE is that the amount of potential energy of runoff is proportional to the shear stress for sediment transport from a slope field and the kinetic energy of the runoff at the bottom of the slope field for gully formation. The improved MUSLE was tested at four watersheds in Ethiopia, and it showed better performance (i.e., the minimum performance is 84%) over the original MUSLE (i.e., the minimum performance was 80%), for all four watersheds under our consideration. We expect the same to be true for other watersheds of Ethiopia.

The effect of the topographic factor of the Modified Universal Soil Equation (MUSLE) on soil erosion and sediment yield is not clear. Except for the coefficient, soil erodibility, cover, and conservation practice factors of the MUSLE, an individual effect of the exponents and topographic factors of the MUSLE on soil erosion and sediment yield can be seen by applying the model at different watersheds. A primary objective of this paper is to estimate the best exponents and topographic factors of the MUSLE under the hydro-climatic conditions of Ethiopia. For the sake of the calibration procedure, the main factors of the MUSLE that directly affect the soil erosion process, such as cover, conservation practice, soil erodibility, and topographic factors, are estimated based on past experiences from the literature and comparative approaches, whereas the parameters that do not directly affect the erosion process or that have no direct physical meaning (i.e., coefficient a and exponent b) are estimated through calibration. We verified that the best exponent of the MUSLE is 1 irrespective of the topographic factor, which results in the maximum performance of the MUSLE (i.e., approximately 100%). The best exponent that corresponds to the best equation of the topographic factor is 0.57; in this case, the performance of the model is greater than or equal to 80% for all watersheds under our consideration. We expect the same for other watersheds of Ethiopia, while for other exponents and topographic factors, the performance of the model decreases. Therefore, for the conditions of Ethiopia, the original exponent of the MUSLE is changed from 0.56 to 0.57, and the best equations of the topographic factor are provided in this paper.

Suspended sediments (SSs) contribute to the maintenance of several ecosystems. However, intense soil erosion can lead to environmental, social, and economic impacts. South America (SA) has very high erosion and sediment transport rates. Here, we present a detailed description of the spatio‐temporal dynamics of natural SS flows in SA using the continental sediment model MGB‐SED AS. We evaluate the model with daily in situ data from 595 stations, information from regional studies and a global model. The model performance analysis showed that, in general, there was a better agreement between simulated and observed data than with the information found in regional studies and of the global model. The use of the hydrodynamic propagation method has allowed a better representation of sediment flows in rivers and floodplains. Based in the calibrated model results, SA delivers 1.00 × 109 t/year of SS to the oceans, in which the Amazon (4.36 × 108 t/year), Orinoco (1.37 × 108 t/year), La Plata (1.11 × 108 t/year), and Magdalena (3.26 × 107) rivers are the main suppliers. The floodplains play an essential role, retaining about 12% (2.40 × 108 t/year) of the SS loads reaching the rivers. In this study, data sets related to SS flows in SA were generated and can be used to support other large‐scale researches or policymakers and stakeholders for adequate management of continental land use. Key Points: First assessment of natural spatio‐temporal sediment dynamics in South America from physically based modelFloodplains anticipate the peak of suspended sediment discharge, and retain almost 12% of sedimentsSouth America exports 2.76 Mt/day of suspended sediments to the oceans; 44%, 14%, and 11% come from Amazon, Orinoco, and La Plata rivers, respectively [ABSTRACT FROM AUTHOR]

Water erosion is an important agronomic, economic and environmental concern in the semi-arid Mediterranean environment. Characterization of the process and choice of a method for estimating it depends on available data and characteristics of the study area. This article aims at quantifying and spatializing water erosion using the Modified (MUSLE) and Revised (RUSLE) Universal Soil Loss Equation coupled with a Geographic Information System (GIS): MUSLE-SIG and RUSLE-SIG. Erosion was modeled in two watersheds located in central Tunisia, Fidh Ali and Fidh Ben Naceur. Field data from 1994 to 2000 were used to calibrate RUSLE-GIS and MUSLE-GIS. Results showed a faithful modeling of reality in terms of landscape degradation. Both models gave relatively similar results. While RUSLE-GIS, more recent, is widely used by researchers in Tunisia, the calibrated version of MUSLE-GIS also gave satisfaction in simulating water erosion. Consequently, both models could be used in Tunisia by development agencies aiming at reducing soil erosion, the choice of one or the other depending on the available data. [ABSTRACT FROM AUTHOR]

Depth to wet front is generally considered as the amount of water that penetrates into soil and wets the internal soil layer. This is an important variable especially in applications such as runoff generation and sediment yield estimation. This variable in some cases is used in the hydrological science, in the form of a proxy for infiltration as an important factor in soil erosion processes. This work deals with estimating event-based suspended sediment yield in relation to depth to wet front to capture the significance of the depth to wet front in Modified Universal Soil Loss Equation (MUSLE). In this field study, a rainfall simulator equipped with drip systems installed over an experimental hillslope plot was used to generate rainfall with intensities of 45, 60, and 70 mm/h over three slopes 10, 20, and 30% with three repetitions. The coefficient of determination (R2) and the Nash–Sutcliffe efficiency (ECNS) were applied as performance metrics for the model. The results revealed that storm rainfall energy or Erosivity Index (EI30) itself was not suitable for estimating the sediment yield. On the other hand, incorporating both EI30 and rainfall-runoff resulted in higher model efficiency. Upon addition of the depth to wet factor into MUSLE model, a greater efficiency was obtained. Further, the results of event-based simulated and observed sediment indicated that they closely corresponded to a straight line (푅2 = 0.94 and NSE = 0.93). Thus, the depth to wet front was a useful variable in sediment yield simulation. The Nash efficiency coefficient and correlation factor for the estimation total sediment yield were obtained (R2 = 0.93; NSE : 0.92) for both calibration and (R2 = 0.93; NSE : 0.86) validation stages. The result suggests that consideration of the depth to wet front in MUSLE model may lead to improved hydrological and sediment applications. [ABSTRACT FROM AUTHOR]

This study compares different methods to calculate erosion and sedimentation processes in the Aviar Basin, a natural peri-urban basin located in Comúd’Encamp (Andorra). The basin area is small, covering less than one square kilometer. Currently, increased densities of houses and buildings under natural basins can cause drainage problems. This is due to the heavy accumulation of eroded solid material in the sewer systems. Therefore, for a given basin condition, accurate estimation of erosion and sedimentation amounts is important. The development of erosion models aims to facilitate the estimation of eroded solid material and the design of possible protective measures to prevent soil losses. Both empirical and physically based erosion models were used to study the Aviar Basin for these purposes. Empirical models include USLE (Universal Soil Loss Equation), RUSLE (Revised USLE) and MUSLE (Modified USLE), while one physically based model, KINEROS 2, was used. The volumes of solid materials produced in the Aviar Basin during the year 2012 were determined using these four different erosion models and then compared between them. The results of this study show that the estimation of soil loss using KINEROS 2 is useful in practice because the results obtained are close to those obtained from the empirical models.

The evaluation of sediment yield by water erosion taking into consideration the possible impact of climate change is the object of this work, concerning the use of the Modified Universal Soil Loss Equation (MUSLE) in an Italian case study. This empirical model was implemented in a Geographical Information System, taking into account Alpine hydrology and geomorphological and climate parameters, which are crucial in the analysis of the intensity and variability of sediment yield production processes. The case study is the Guerna Creek basin, a small-sized mountain watershed placed in Lombardy, in the South-Central Alps (Northern Italy). In recent decades it has been hit at the same time by floods and erosive phenomena, showing its hydraulic-hydrological weakness. Three future climate change scenarios from 2041 to 2060, around the middle of this century, were built according to CORDEX data referring to three different Representative Concentration Pathways (RCP 2.6, RCP 4.5, RCP 8.5). The findings showed that in the future climate, the sediment yield at the basin scale might change by 24–44% for a single heavy storm in the middle of the current century.

Vegetation cover is an important factor controlling erosion and sediment yield. Therefore, its effect is accounted for in both experimental and modelling studies of erosion and sediment yield. Numerous studies have been conducted to account for the effects of vegetation cover on erosion across spatial scales; however, little has been conducted across temporal scales. This study investigates changes in vegetation cover across multiple temporal scales in Eastern Cape, South Africa and how this affects erosion and sediment yield modelling in the Tsitsa River catchment. Earth observation analysis and sediment yield modelling are integrated within this study. Landsat 8 imagery was processed, and Normalised Difference Vegetation Index (NDVI) values were extracted and applied to parameterise the Modified Universal Soil Loss Equation (MUSLE) vegetation (C) factor. Imagery data from 2013–2018 were analysed for an inter-annual trend based on reference summer (March) images, while monthly imagery for the years 2016–2017 was analysed for intra-annual trends. The results indicate that the C exhibits more variation across the monthly timescale than the yearly timescale. Therefore, using a single month to represent the annual C factor increases uncertainty. The modelling shows that accounting for temporal variations in vegetation cover reduces cumulative simulated sediment by up to 85% across the inter-annual and 30% for the intra-annual scale. Validation with observed data confirmed that accounting for temporal variations brought cumulative sediment outputs closer to observations. Over-simulations are high in late autumn and early summer, when estimated C values are high. Accordingly, uncertainties are high in winter when low NDVI leads to high C, whereas dry organic matter provides some protection from erosion. The results of this study highlight the need to account for temporal variations in vegetation cover in sediment yield estimation but indicate the uncertainties associated with using NDVI to estimate C factor.

This study has evaluated the runoff and erosion rates in torrents of Southern Italy, two forested headwaters with very similar climatic, hydrological and geomorphological characteristics; in one headwater, 15 check dams were installed in the mid-1950s, while the other is not regulated with engineering works. To this aim, the hydrological variables have been modeled over 15 years after check dam installation using the HEC-HMS (Hydrologic Engineering Center-Hydrologic Modeling System) model coupled to the MUSLE (Modified Universal Soil Loss Equation) equation. The model simulations have shown that check dams have not played a significant role in reducing the surface runoff compared to the unregulated torrent; in both catchments, the well-developed forest cover determined very low runoff coefficients (lower than 0.3%) with a scarce runoff generation capacity. Additionally, the reduction in peak flow due to the check dams was not significant, on average −7.4% compared to the unregulated headwater. Check dams have retained sediments for about 8–10 years after their installation, reducing erosion by about 35%, although soil loss was much lower than the tolerance limit in both catchments. After the sediment retention capacity of the dam sediment wedge was depleted, the sediment yield in the regulated torrent was even higher (by about 20%) compared to the unregulated catchment. Overall, the study has shown that the use of check dams as a catchment management strategy of forested headwaters under semi-arid Mediterranean conditions should be considered with caution, since the structures could be ineffective to reduce water and sediment flows during floods or, in some cases, check dams may increase erosion rates.

Soil erosion is one of the principal causes of soil degradation in Sandakan, Sabah, Malaysia. The natural phenomenon of erosion is now accelerated by human activities that alter the natural mechanisms. This acceleration is caused by destruction of plant cover, the growing of wrong cultivations, unsuitable farming techniques etc., all of which may be prevented with correct management and land planning. Soil erosion has been identified as one of the important environmental issues and therefore, detail assessment on prediction of soil loss and its impacts has been carried out using the application of the Modified Soil Loss Equation (MUSLE) and Geographical Information System (GIS). ARCINFO was used for the storage of the data layer on each factor controlling soil erosion. Identification of potential high-risk erosion areas was made using a thematic data layering approach to analyze risk areas. The quantitative soil loss (t ha-1 yr-1) ranges estimates by MUSLE model by a spatial information analisis approach (GIS) were computed: (a) Very High risk (>150 tons/ha/year); (b) High risk (100-150 tons/ha/year); (c) Moderate risk (50- 100 tons/ha/year); (d) Low risk (10-50 tons/ha/year); and (e) Very low risk (

ABSTRACT Calibration and validation are two important steps in the application of sediment models requiring observed data. This study aims to investigate the potential use of suspended sediment concentration (SSC), water quality and remote sensing data to calibrate and validate a large-scale sediment model. Observed data from across 108 stations located in the Doce River basin was used for the period between 1997-2010. Ten calibration and validation experiments using the MOCOM-UA optimization algorithm coupled with the MGB-SED model were carried out, which, over the same period of time, resulted in 37 calibration and 111 validation tests. The experiments were performed by modifying metrics, spatial discretization, observed data and parameters of the MOCOM-UA algorithm. Results generally demonstrated that the values of correlation presented slight variations and were superior in the calibration step. Additionally, increasing spatial discretization or establishing a background concentration for the model allowed for improved results. In a station with high quantity of SSC data, calibration improved the ENS coefficient from -0.44 to 0.44. The experiments showed that the spectral surface reflectance, total suspended solids and turbidity data have the potential to enhance the performance of sediment models.

The misapplication of empirical hydrologic models with regard to the spatial context of their development and application is rife. The Modified Universal Soil Loss Equation (MUSLE) model was calibrated and validated for Ofuloko Watershed (612 ha) in North-Central Nigeria. Hydro-meteorological data for 20 rainfall events (occurring from 2nd June to 14th July 2017) were obtained from a station installed adjacent the watershed. The control points of the Ofuloko Watershed were obtained at 10 m intervals from a survey conducted with a hand-held GPS receiver to delineate the watershed and generate the Digital Elevation Model (DEM) in Surfers 10 environment. Sediment yield was measured at the watershed outlet and soil samples obtained from the watershed was analysed in a laboratory. The Curve Number method was used to estimate the runoff volume, peak runoff for the watershed was estimated using the Rational Method and the time of concentration was computed using the method developed by Kirpich. The slope length and steepness factors were obtained using the McCool equations. Correction factors were applied to the soil erodibility factor to obtain the actual values for tropical soils. Data from the first 10 storm events were used to calibrate the MUSLE while data from the remaining 10 storm events were used to test and validate the model. A comparison of the measured (observed) sediment yield and the predicted sediment yield using the Chi-square goodness-of-fit test showed that they are not significantly different at 5% significance level. The Nash-Sutcliffe Efficiency Coefficient value of 0.8805, which is acceptable for most hydrologic applications was also obtained after the comparison. Strict adherence to the application requirements of MUSLE as documented in this research has demonstrated its utility as a watershed management tool in the derived ecological zone of Nigeria. [ABSTRACT FROM AUTHOR]