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Rainfall-induced progressive soil erosion of compacted surface layer (SL) impedes the functioning of cover system (CS) of landfills with high expected design life (≈ 100 years). The existing soil erosion models are not tested extensively for compacted soil with cracks and vegetation. This study evaluated the efficacy of three popular soil erosion models for estimating the soil loss of compacted SL of CS, which is useful for annual maintenance. The interactive effect of rainfall, vegetation and desiccation cracks on erosion of compacted surface layer was investigated under the influence of both natural and simulated rainfall events for one year. Among all, the Morgan, Morgan and Finney (MMF) model was found to be effective in predicting soil erosion of compacted SL. However, the MMF model overestimated soil erosion when the vegetation cover exceeded 60%. The soil loss estimated from Revised Universal Soil Loss Equation (RUSLE) and Water Erosion Prediction Project (WEPP) models was poor for high rainfall intensity (100 mm/h). The RUSLE and WEPP model overestimated the soil erosion for low vegetation cover (≤ 3%) and underestimated for vegetation area > 3%. The mechanism of root reinforcement, strength due to root water uptake-induced soil suction and its effect on soil loss mitigation could not be adequately captured by the existing models for compacted SL. Further studies are needed to improve the existing erosion models for incorporating the effects of desiccation and vegetation on soil loss from the compacted SL.

Soil erosion is one of the most critical hazards adversely affecting both environment and economy. Assessment of the annual soil erosion rate provides information on soil erosion risk zones indicating the areas with high, severe and low risks. Modelling and prediction of soil erosion has a long history of more than seven decades. It becomes imperative to be familiar with the quantum of studies conducted and methods employed across the world to assess vulnerability of ecosystems to soil erosion to plan strategies for their conservation. There are several methods based on various factors like land use, soil quality, topography etc. available to assess the susceptibility of a region to soil loss. With time the gap in understanding of such models and their use around the world has increased. Numerous models for assessing soil erosion exist but there is a lack of knowledge on spatial distribution of the methods being used. Academic papers related to assessment of soil erosion vulnerability published during the past three decades (1991–2019) were reviewed. Total 160 studies were reviewed to understand advances in the methods used to assess soil erosion vulnerability worldwide, identification of the most popular methods and proportion of studies conducted in the fragile region of Himalayas. The results show that 18 different methods have mainly been used to assess soil erosion risk in different regions. These methods include statistical, physical, process based and empirical models. The use of few physical methods like ANSWERS and SHE has decreased with time while that of physical and process methods like RUSLE, SWAT, WEPP and PESERA has increased with time. The review highlighted that various models being used worldwide are based on their suitability to the region. It also brings to attention that few models like PESERA, EUROSEM and WEPP are mostly being used concentrated in a particular region. Models like PESERA and EPM are mostly used in European region and may be encouraged to estimate soil erosion in Himalayan region. The review also highlights lack of studies with inclusion of water quality as an important parameter while assessing soil erosion vulnerability in the region. The review suggests that in case of lack of data, various statistical methods like PCA, CF, FUZZY etc. can be preferred for qualitative assessment over quantitative assessment. Considering availability of accurate input, researchers need to attempt more methods and perform comparative studies to attain accurate results for assessing soil erosion vulnerability leading to strategizing soil conservation in fragile regions.

The stochastic weather generator CLIGEN can simulate long-term weather sequences as input to WEPP for erosion predictions. Its use, however, has been somewhat restricted by limited observations at high spatial–temporal resolutions. Long-term daily temperature, daily, and hourly precipitation data from 2405 stations and daily solar radiation from 130 stations distributed across mainland China were collected to develop the most critical set of site-specific parameter values for CLIGEN. Ordinary kriging (OK) and universal kriging (UK) with auxiliary covariables, i.e., longitude, latitude, elevation, and the mean annual rainfall, were used to interpolate parameter values into a 10 km×10 km grid, and the interpolation accuracy was evaluated based on the leave-one-out cross-validation. Results showed that UK generally outperformed OK. The root mean square error between UK-interpolated and observed temperature-related parameters was ≤0.88 ∘C (1.58 ∘F). The Nash–Sutcliffe efficiency coefficient for precipitation- and solar-radiation-related parameters was ≥0.87, except for the skewness coefficient of daily precipitation, which was 0.78. In addition, CLIGEN-simulated daily weather sequences using UK-interpolated and observed parameters showed consistent statistics and frequency distributions. The mean absolute discrepancy between the two sequences for temperature was ∘C, and the mean absolute relative discrepancy for solar radiation, precipitation amount, duration, and maximum 30 min intensity was % in terms of the mean and standard deviation. These CLIGEN parameter values at 10 km resolution would meet the minimum data requirements for WEPP application throughout mainland China. The dataset is available at http://clicia.bnu.edu.cn/data/cligen.html (last access: 20 May 2021) and https://doi.org/10.12275/bnu.clicia.CLIGEN.CN.gridinput.001 (Wang et al., 2020).

The main objective of this study is to predict soil erosion in the Lattakia Governorate (W Syria) using the Water Erosion Prediction Project model (WEPP) and to compare the result with that of the RUSLE. Field survey and data collection were carried out, and 44 soil samples were analyzed. In addition, all the necessary input files were prepared for use in the WEPP model and RUSLE. Results show that more than of 80% of the locations studied experience slight to moderate erosion (less than 5 t/ha/y), whereas the rest of the locations experience severe soil erosion hazard. Moreover, the volume of runoff estimated by the WEPP model is in the range of 51–321 mm, and the R2 between the simulated soil erosion and the predicted runoff reached 0.68. Interestingly, the R2 between the WEPP model and RUSLE is 0.56, which indicates a good correlation between the two models.

Effective watershed management and protection of water resources from non-point source pollution require identification, prioritization, and targeting of pollutant source areas. Process-based hydrology and water quality models are powerful heuristic tools for land and water resources managers. However, because of their complexity, such models are often under-utilized as management prioritization and planning tools. In this paper, we present a prioritization, interactive visualization, and analysis tool (Pi-VAT) that is programmed to synthesize multi-scenario, multi-watershed outputs from process-based geospatial models. We demonstrate the utility of Pi VAT to examine simulated hydrologic, sediment, and water quality response at the hillslope/hydrologic response unit (HRU) scale. We apply Pi-VAT to output from multiple watersheds and for multiple management scenarios and treatments from two geospatial models for watershed management: Water Erosion Prediction Project (WEPP) and Soil & Water Assessment Tool (SWAT). Pi-VAT was developed using the Shiny web application framework for the R programming language. In a matter of minutes, Pi-VAT can synthesize overwhelming amounts of output from process-based models into information useful for land and water resources managers. We illustrate the use of Pi-VAT to interactively identify, quantify, and visualize areas that are most susceptible to disturbance under different scenarios and provide a synthesis approach based on land use, soil type, and slope steepness. This approach guides land and water resources managers in prioritizing the areas of the watershed that provide the maximum reduction in pollutant loads while treating the least amount of area. Pi-VAT provides a flexible reactive platform for the development of decision support tools based on process-based models intended for watershed management and research applications. AFRI program [1009827]; USDA National Institute of Food and Agriculture Published version This work was supported by the AFRI program [grant no201667020-25320/project accession no. 1009827] from the USDA National Institute of Food and Agriculture. Public domain – authored by a U.S. government employee

Evaluation of prediction models is crucial to achieving valid information on erosion processes and their management choices. WEPP model efficiency in predicting ephemeral gully (EG) erosion was recently tested and compared with both EGEM and empirical models. The models abilities to predict EG erosion were validated using measured estimates at the 6 eroding locations around Mubi area in Northeast Nigeria between April 2008 and October 2009. Each location consisted of 3 watersheds where data on soils, climate, slope, management practices, EG shapes and dimensions were collected. Data on relevant soil properties were collected in the field and then analyzed in laboratory. The mass of soil loss (MSL) predicted by empirical, EGEM and WEPP models were compared with the measured using paired T-test, regression graphs (r2-values), error analysis, and analysis of variance (ANOVA) in a completely randomized design. The EG erosion losses varied significantly (P ≤ 0.05) between sites and years. No significant (P ≤ 0.05) differences were observed between measured and the empirically predicted aggregate MSL. The measured aggregate MSL strongly correlated with those predicted by empirical (r2 = 0.67), than with EGEM (r2 = 0.57), and WEPP (r2 = 0.53) models. Slight over and under-prediction instances against the measured erosion were noted with all the models. The WEPP model was found to slightly over-predict MSL when compared to either the empirical or EGEM model. The prediction quality of the models was generally impressive. Future works should focus more on local inputs such as climate, plants, management, and tillage data for use with WEPP.

Model inputs for prediction of runoff and soil erosion commonly require precipitation intensity information. Intensity is often estimated if precipitation data with high temporal resolution are unavailable. However, when intensity is time-averaged for fixed measurement intervals, estimates become increasingly underestimated with longer intervals due to the assumption that event durations begin and end at specified measurement intervals. In this study, adjustment factors were determined for downscaling the temporal resolution of intensity values derived from selected resolutions within the range of 10 to 1,440 min for Koppen-Geiger climate regions in the United States. In this case, monthly mean maximum 30 min intensity (MX.5P) was downscaled, which is a parameter used to generate stochastic meteorological inputs for models that include the Rangeland Hydrology and Erosion Model (RHEM) and the Water Erosion Prediction Project model (WEPP). The adjustment factors were given by regressions of reference MX.5P values derived from data with 5 min resolution against MX.5P values derived from data with lower temporal resolutions (≥10 min). In addition to using a slope coefficient for intensity in the regression equation, permutations of the equation included use of an elevation coefficient and constants, resulting in four total permutations. For the 143 stations and 17 climate regions analyzed, the four regression equations had roughly equal performance, and all gave statistically significant results. Regressions for adjusting hourly data using only an intensity coefficient in the equation had standard error of the estimate ranging from 1.01 to 2.96 mm h–1 with an average of 2.04 mm h–1. When downscaling daily values, the error range was 2.50 to 10.20 mm h–1 with an average of 5.63 mm h–1. Average time-to-peak intensity probability distributions for each climate region were also determined. Finally, a stochastic weather generator, CLIGEN, was used to test the effectiveness of applying the climate-based factors as an alternative to using subhourly data.

A strong need exists for tools to assess the efficacy of conservation practices across large regions supporting informed policy decisions that may lead to better soil and water conservation while optimizing agricultural production options. Perennial warm‐season grasses (WSGs) such as switchgrass (Panicum virgatum), can be grown on marginally productive and/or environmentally sensitive lands to meet growing bioenergy demands while reducing water runoff and soil erosion compared to current row crop systems. Quantifying the soil and water conservation effects of WSG when strategically placed on the landscape would help support decisions favoring both economic and environmental benefits. We used the Daily Erosion Project (DEP) to simulate the effects of WSGs on hillslope water runoff and soil loss for 2008–2016 across eight major land resource areas (MLRA) in the Midwest United States. Four different scenarios (baseline or existing conditions and switchgrass grown on slopes ≥3%, ≥6%, and ≥10%) were modeled. Across all hillslope groups replacing row crops with switchgrass reduced yearly water runoff and soil loss by 3.2%–12.1% and 43.7%–95.5% compared with the baseline levels, respectively. Water and soil conservation efficiency (water runoff reductions or soil loss reductions associated with 1% increase in switchgrass coverage) increased with slope as 10% > 6% > 3% for all MLRAs. Switchgrass replacement on slopes ≥10% reduced average soil loss estimates as much as 22.6 Mg ha−1 year−1 for the most erosive MLRA (baseline soil erosion rate of 28.6 Mg ha−1 year−1) and resulted in all MLRA erosion estimates ≤6.0 Mg ha−1 year−1. For soil loss, an apparent interaction existed between slope group and total annual precipitation; as annual precipitation increased, the difference in soil loss between slope groups increased. Soil loss was more sensitive to these factors than was water runoff. Policy supporting a renewable energy industry while strategically improving soil and water resources seems globally advantageous.

Effective treatment of persistent agricultural erosion with limited conservation funds requires the identification of critical source areas (CSA) at the subfield scale for watershed scale planning. Publicly available data, physically-based modeling frameworks, and strong conservation district initiatives are now all in place to more directly connect conservation implementation with the underlying physical hydrology. The overall objective of this dissertation was to operationalize physical modeling simulations to identify CSA and inform strategic conservation prioritization. I developed a method for spatially distributing a simplified framework of the Water Erosion Prediction Project (WEPP) model that simulates the physical mechanisms of hillslope hydrology and erosion. A land type characterization of representative WEPP profiles was defined for spatial slope, soil, climate, and management data. Profile simulations mapped to individual flow paths in a regional watershed. This method preserved a higher resolution than the WEPP hillslope approach at 95.6% less computational cost. Simulating multiple conservation practice scenarios identified CSA at the subfield scale as well as conservation practice effectiveness. Erosion decreased by 58% for a change from uniform conventional tillage (CT) to mulch tillage (MT) and by 98% for CT to no-tillage (NT). Treatment of 25% of agricultural area effectively accounted for almost all of this reduction in erosion. Ten-meter conservation buffers were highly effective at reducing sediment delivery to the stream where erosion rates were large., With a voluntary conservation paradigm, identifying CSA is insufficient to promote good conservation. Historically, social and financial drivers of conservation adoption have buffered implementation. A system dynamics model simulated the physical, social, and financial incentive interactions to understand conservation adoption and erosion rates under possible conservation targeting scenarios. Targeting CSA with conservation funding for land retirement with the conservation reserve program and for reduced tillage decreased the total average erosion rate by more than 50%. The most effective use of conservation funds, however, occurs when the diffusion of innovation mechanism is reinforced by broad-scale payments for tillage reduction. By identifying positive feedback, our simulations suggest large potential gains in erosion reduction and conservation fund efficiency are possible. Findings from this work can greatly enhance soil and water conservation planning.

The WEPP watershed model was applied for simulation of storm-wise runoff and sediment yield from two forest watersheds (WS-I and WS-II) having an area of 1.85 and 21.3 ha, respectively, situated in Shivalik foot-hills of North-West, India. The WS-I was divided into 29 hillslopes and 18 channels, while WS-II was divided into 35 hillslopes and 25 channels. CLIGEN software was used to create the climate file, which was based on the observed meteorological data. The soil, slope, and land-use management files were created for each hillslope and channel. The model was calibrated on WS-I and then applied to WS-II to ascertain whether the model must be calibrated every time it is applied to a new watershed in the region. The WEPP model was calibrated and validated by using the hydrological data of 22 storms (1982–2004) for WS-I and 13 storms (2001–4) for WS-II. The statistics showed that calibrated model for WS-I, simulated storm-wise runoff, and sediment yield for WS-II with advisable precision as substantiated by the lower values of RMSE (5.43 mm and 0.31 Mg/ha) and average error (2.09 mm and 0.09 Mg/ha) and high values of correlation coefficient (0.93 and 0.86) and model efficiency (83.90% and 69.50%). It is evident from this study that once the WEPP model has been calibrated on a representative watershed, it can be effectively applied to uncalibrated/ungauged watersheds in Shivalik foot-hills for watersheds with similar characteristics.

Soil erosion is a major environmental problem in many parts of the world and represents a serious problem for sustainable agriculture and the environment, with direct and indirect impacts on soil quality and fertility. This study aimed to use the Water Erosion Prediction Project (WEPP) model to estimate rill erosion and determine soil physical and hydraulic properties, which are essential to investigate its performance. To this end, an experiment was carried out in the Exu Creek watershed, in Serra Talhada, semi -arid region of Pernambuco State (Brazil), under increasing flow rates: T1: 5.87 L min-1; T2: 12.10 L min-1; T3: 20.33 L min1; and T4: 27.57 L min-1. Liquid and solid discharges were sampled for determination and characterization of hydraulic parameters in preformed rill flows. Reynolds numbers between 2,019 and 6,929 and Froude numbers below 1 found in this study attest to occurrence of erosive rills. Soil losses due to rill erosion increased as flow rates increased. Rill erodibility was 0.0011 kg N-1 s-1, and critical shear stress (tc) was 1.91 Pa, collapsing rill sidewalls and increasing local uplift, wet perimeter, and rill hydraulic radius. RESUMO A erosão do solo é um dos maiores problemas em muitas partes do mundo com impactos diretos e indiretos representando um problema muito sério na agricultura e sustentabilidade ambiental, afetando a fertilidade e qualidade do solo. Elevada erosão do solo e altas cargas de sedimentos são problemas sérios em várias regiões semiáridas no Brasil. No intuito de aplicar procedimentos de mitigação, são necessários uma estimação precisa da erosão do solo e produção de sedimentos. Este trabalho visa a abordagem do Water Erosion Prediction Project (WEPP) na quantificação da erosão em sulcos e avaliação das relações físicas e hidráulicas, essenciais para investigar o desempenho do modelo. Com este objetivo, o experimento foi desenvolvido na região semiárida da bacia hidrográfica do Exu, Serra Talhada - Pernambuco (Brasil), através de aplicações crescentes de diferentes vazões: T1: 5,87 L min-1; T2: 12,10 L min-1; T3: 20,33 L min-1 e T4: 27,57 L min-1. Amostras de descargas líquidas e sólidas foram coletadas para determinação e caracterização dos parâmetros hidráulicos da vazão nos sulcos pré-estabelecidos. Os números de Reynolds entre 2.019 e 6.929 e de Froude abaixo de 1, atestaram a ocorrência de sulcos erosivos. As perdas de solo devido à erosão nos sulcos foram elevadas após os crescentes fluxos aplicados e o valor da erodibilidade do sulco obtido foi de 0,0011 kg N-1 s-1 e a tensão crítica de cisalhamento (tc) de 1,91 Pa causando o colapso das paredes laterais, elevação da área, perímetro molhado e o raio hidráulico dos sulcos experimentais.

In this study, the Water Erosion Prediction Project (WEPP) was used to model the soil sediment yield in four monocropping systems in Claveria, Misamis Oriental in Southern Philippines, as influenced by rainfall. The rainfall data were analyzed and inputted into the WEPP model, together with the soil, climate, and other relevant data in Claveria. The sensitivity analysis was performed using four corn monocropping systems (CMS), including no-till (NT), light till (LT), medium till (MT), and heavy till (HT), considering rill cover, effective hydraulic conductivities of the soil, increasing annual rainfall, and rainfall-runoff factors. The WEPP model indicated that soil sediment yield is highly sensitive to the type of tillage practice and the increased rainfall in Claveria. Claveria’s average annual rainfall is over 3000 mm with nine rainy months and three dry months. During the 13 years, the annual rainfall increased by 28%, which is equivalent to 68 mm/year. The average annual erosion rates increased by 114%, 85%, and 54% in LT, MT, and HT CMS, respectively. One management option to keep sediment yields to an acceptable level is to shift from HT or MT systems to NT or LT systems, which maintain high levels of residue cover on the soil.

Optical fiber phase optical time domain reflectometry (phase-OTDR) has been applied on the West-East Gas Pipeline Project (WEPP) of China for vibration monitoring. In order to improve the accuracy ...

In the current study, WEPP and EPM models were used to estimate the amount of soil erosion and sediment in the basin of Kangir. The required data for implementation of the WEPP model were prepared in six categories including soil, climate, management, slope, drainage and reservoir based on which we took the information needed to build soil and management files. Some information such as texture, cation exchange capacity, organic matter, sand content, effective hydraulic flow and critical shear stress was used. After production of all the layers, the WEPP model was implemented using the GEOWEPP software. In this software, erosion and sediment amounts were estimated by three methods: domain, watershed and flow path methods. In the Kangir River watershed, the sediment content was 7.64 t/ha/year, 6.13 t/ha/year and 11.87 t/ha/year. Thus, the two methods of domain 7.64 t/ha/year and flow path 11.83 t/ha/year were closer to the observed sediment 10.5. Based on the EPM model, the sedimentation coefficient of the Kangir basin was 0.81. The results of the research indicate the high erodibility rate of the watershed basin. The erosion-sensitive units were located in the western and southwestern regions of the basin. In the EPM model, the erosion rate (Z) was 0.6 indicating moderate to high erodibility rate in the watershed. Furthermore, the highest erosion rate was in the western and southwestern parts of the watershed. Finally, the results of estimating soil erosion and sediment production in the watershed of Kangir illustrated that the WEPP model has a more accurate estimation of soil erosion and sediment production, and in this model, the flow path method used to estimate the amount of soil erosion and sediment production was close to the observed sediment at the hydrometric station.

Aim of study: Main objective of this research was to predict some of the processes (soil loss, runoff and sediment yield) related to soil erosion with the help of WEPP (Water Erosion Prediction Project) model. Area of study: The WEPP model was applied to the Düz Creek Watershed (1059 ha in size). It is a sub-watershed flowing into the greater Çoruh River Basin near the district of Borçka, Artvin. Material and methods: As required by the WEPP model, four large-data files of soil, climate, slope and plant cover/management were created for the watershed using the data gathered from in-field samplings (soil), laboratory analyses and GIS (Geographical Information Systems) assessments. For easier run and detailed investigation of soil erosion process of the research area, the studied watershed was divided into eight small hydrological units (SHUs) and the program was run on these SHUs. Main results: At the end of GeoWEPP’s run, the results revealed that a total of about 735 mm annual precipitation was fell within the study area. The model also predicted that there was approximately 207 mm as runoff out of this amount of precipitation, which, in turn, generated an annual total soil loss and sediment amounts as 2815.2 t and 2720.9 t, respectively. In addition, the sediment yield per unit area was estimated to be around 2.57 ton/ha/yr while the sediment delivery ratio (SDR) was found to be as 0.977. Lastly, the model predicted that the particle distribution of eroded sediment were 20%, 25% and 55% of clay, silt and sand, respectively, while the mean organic matter (OM) amount of the lost sediment was about 5% for the studied watershed. Highlights: Soil loss and sediment yield can be calculated for large areas in a short time and with little cost.

Accurate soil loss prediction at the regional scale is necessary for a better understanding of the soil erosion processes and conservation practices. This study aimed to calibrate the WEPP model for predicting soil loss under semi-arid region conditions in the northwest of Iran. Inter-rill and rill erosion were simulated at 59 points with three replications. Therefore, the ability of the regression equation in WEPP model and the derived regression and artificial neural network (ANN) models by Mirzaee et al. (2017) for predicting baseline soil erodibility parameters were evaluated to estimate soil loss. The results of the present study showed that the WEPP model that applied soil baseline erodibility predicted data by the regression equation in the WEPP model performed poorly in comparison to the derived aspatial models by Mirzaee et al. (2017). Additionally, the WEPP model that used soil baseline erodibility predicted data by the developed ANNs by Mirzaee et al. (2017) yielded the best results with the highest R2 (0.681) and the lowest RMSE (5.1 Mg ha−1) values for predicting soil loss rate. In general, the prediction map of soil erosion showed that soil erosion varied from 1.0 to 26.5 Mg ha−1.

Soil erosion has long been recognised as a significant process of soil destruction, affecting millions of hectares of land worldwide, resulting in loss of fertility and biodiversity, decreased stability of marine and terrestrial ecosystems and enhanced exposure to climate change. In semi-arid zones, the highest rate of deforestation occurred in wooded grassland, bushland and shrubland systems, while the lowest rate occurred in woodland. Satellite remote sensing technology for tracking and modelling soil erosion has exploded in popularity worldwide over the last decade. More precisely, renewed emphasis has been placed on recent advances in remote sensing technologies and the availability of these data at various resolutions, as well as on the critical need for up-to-date knowledge on soil loss levels, soil erosion monitoring and modelling, in particular, to ensure that viable agricultural fields are available to ensure food security. GIS research delivers adequate results when developing erosion surveys and risk maps using GIS data layers such as DEM, slope, aspect and land use. The Revised Universal Soil Loss Equation (RUSLE), the Water Erosion Prediction Project (WEPP) and Environmental Information Coordination are the most widely used scientific erosion prediction models that are combined with remote sensing and GIS (CORINE). Remote sensing techniques and the universal soil loss equation were established as the primary tools for mapping and tracking soil erosion in this chapter. It consists of four components: baseline sheet and rill erosion mapping, real-time rill and gully erosion monitoring, future sheet and rill erosion change forecast and long-term pattern determination.

This paper presents the development and verification of an improved and cost-effective flume apparatus and corresponding testing methodology. A rigorous analysis of the flow conditions during testing was considered and an interpretation of test results was carried out following the premises of the Water Erosion Prediction Project (WEPP) rill erosion model. The apparatus and methodology were verified using statically compacted specimens of a latosol from the central region of Brazil. Tests were performed on samples with void ratios of 1.0 and 1.5 and under variable hydraulic conditions to verify the repeatability and ideal analysis time for the soil loss curves. The soil loss curves presented hyperbolic behavior, with a maximum value that appeared to be randomly behaved, which can be attributed to the complex nature of the erosion processes at later stages. The equipment and testing methodology produced erosion curves with repeatability that were superior with respect to their initial linear and transition portions. Recommendations are made regarding the adequate interpretation of the testing data and the selection of the ideal elapsed time for soil loss analysis.

The formation of scientific research in the fields of physiology, biology and ecology in Ukraine is studied. It is proved that the development of information technology and software for research and improvement of natural and artificial biological objects began in the middle of the 20th century with the widespread use of computer technology. It is established that in the 1990s, Ukrainian scientists from research institutions of the NAAS system using economic-mathematical modeling developed computer programs that optimized the functioning of biological objects by using large amounts of data in plant growth optimization models. It is established that at the beginning of the 21st century the researches of Ukrainian scientists A.B. Achasov, S.A. Baliuk, S.Yu. Bulygin, M.M. Kotova, R.V. Ternova, D.O. Timchenko in the field of biomedical engineering developed in collaboration with foreign scientists. In particular, the effectiveness of economic and mathematical models created by American scientists in the form of computer applications to establish the ecological role of plants, they theoretically confirmed in the soil and climatic conditions of Ukraine and China. The value of the WEPP (Water Erosion Prediction Project) computer simulation model, which is used to calculate the processes of water erosion in the soil, has been established. Dynamic computer model WEPS (Wind Erosion Prediction System), which is used to plan soil protection technologies against wind erosion. The dynamic computer model EuroSEM (European Soil Erosion Model), which was developed to better describe erosion phenomena in agroecosystems. It is proved that the priority direction of research of Ukrainian scientists in establishing the efficiency of biological objects is the use of space imaging technologies, which contributed to the stabilization and increase of efficiency of agroecosystems.

Process-based erosion models are efficient tools that can be used to predict where and when erosion occurs. On unpaved roads that have been recognized as important sediment sources, soil loss along road segments should be precisely predicted. This study was performed using the hillslope version of the Water Erosion Prediction Project (WEPP) to estimate soil loss from 20 typical road segments in the red soil region of South China. Terrestrial laser scanning (TLS)-measured soil losses were used to validate the model simulations. The results showed that the WEPP model could reasonably predict the total soil loss in relatively short (less than 100 m) and gentle (slope gradient lower than 10%) road segments. In contrast, the WEPP-simulated soil loss was underestimated for long or steep road segments. Detailed outputs along roads revealed that most of the peak soil loss rates could not be adequately calculated. The linear critical shear stress and the sediment equilibrium theory in the WEPP model for soil detachment simulation might be responsible for the underestimation. Additionally, the lack of upslope flow and the curved road tortuosity were found to be connected to the relatively low efficiency of the model outputs. Nevertheless, the WEPP simulation could accurately fit the trend of soil loss variation along road segments despite underestimation. Furthermore, the simulated results could provide a reliable prediction of the maximum soil loss positions. Therefore, the WEPP model could be adopted to evaluate the erosion risk of unpaved roads in the red soil region of South China.

Storm events and soil erosion can adversely impact flood control, soil conservation, water quality, the recreation economy, and ecosystem biodiversity in urban systems. Urban Low Impact Development practices (LIDs) can manage stormwater runoff, control soil losses, and improve water quality. The Water Erosion Prediction Project (WEPP) model has been widely applied to assess the responses of hydrology and soil losses to conservation practices in agricultural and forested areas. This research study is the first to calibrate the WEPP model to simulate streamflow discharge in the Brentwood watershed in Austin, Texas and apply the calibrated WEPP model to assess the impacts of LIDs. The costs and impacts of various LID scenarios on annual water balance, and monthly average, and daily runoff volumes, and sediment losses at hillslopes and at the watershed outlet were quantified and compared. The LID scenarios identified that native planting in Critically Eroding Areas (CEAs), native planting in all suitable areas, native planting in CEAs with detention ponds, and native planting in all suitable areas with detention ponds could reduce the predicted average annual stormwater runoff by 20–24% and sediment losses by 86–94% at the watershed outlet, and reduce the average annual soil loss rates on hillslope profiles in sub-watersheds by 86–87% with the lowest costs (USD 2991/yr–USD 5257/yr). Watershed/field characteristics, locations, areas, costs, and the effectiveness of the LID practices were essential in choosing the LID scenarios. These research results can help guide decision-making on the selection and implementation of the most economical and suitable LID practices to strengthen the climate resilience and environmental sustainability of urban systems.

Unpaved road erosion have been recognized as important sediment sources in a watershed. To evaluate where and when road erosion occurs, the soil loss along road segments should be precisely predicted with process-based erosion models. Methods: The hillslope version of the Water Erosion Prediction Project (WEPP) was used to estimate soil loss from 20 typical road segments in the red soil region of South China. Terrestrial laser scanning (TLS)-measured soil losses were used to validate the model simulations. The results showed that the WEPP model could reasonably predict the total soil loss in relatively short (less than 100 m) and gentle (slope gradient lower than 10%) road segments. In contrast, soil loss would be underestimated for long or steep road segments. Detailed outputs along roads revealed that most of the peak soil loss rates were underestimated. It might due to the linear critical shear stress theory in the WEPP model. Additionally, the lack of upstream flow was found to be connected to the relatively low model efficiency. Nevertheless, the WEPP simulation could accurately fit erosion trend and predict the peak soil loss positions along road segments. Conclusions: The WEPP model could be adopted to evaluate the erosion risk of unpaved roads in the red soil region of South China.

Soil erosion is one of the main threats facing the agriculture and natural resources sector all over the world, and the same is true for Syria. Several empirical and physically based tools have been proposed to assess erosion induced soil losses and runoff driving the processes, from plot to regional spatial scales. The main goal of this research is to evaluate the performance of the Water Erosion Prediction Project (WEPP) model in predicting runoff in comparison with field experiments in the Al-Sabahia region of Western Syria in three ecosystems: agricultural lands (AG), burned forest (BF) and forest (FO). To achieve this, field experimental plots (2∗1.65∗0.5 m) were prepared to obtain runoff observation data between September 2012 and December 2013. In addition, the input data (atmospheric forcing, soil, slope, land management) were prepared to run the WEPP model to estimate the runoff. The results indicate that the average observed runoffs in the AG, BF and FO were 12.54 ± 1.17, 4.81 ± 0.97 and 1.72 ± 0.16 mm/event, respectively, while the simulated runoffs in the AG, BF and FO were 15.15 ± 0.89, 9.23 ± 1.48 and 2.61 ± 0.47mm/event, respectively. The statistical evaluation of the model's performance showed an unsatisfactory performance of the WEPP model for predicting the run-offs in the study area. This may be caused by the structural flaws in the model, and/or the insufficient site-specific input parameters. So, to achieve good performance and reliable results of the WEPP model, more observation data is required from different ecosystems in Syria. These findings can provide guidance to planners and environmental engineers for proposing environmental protection and water resources management plans in the Coastal Region in Syria., Soil Erosion; WEPP model; Runoff prediction; Ecosystem; Statistical analysis

To give soils and soil degradation, which are among the most crucial threats to ecosystem stability, social and political visibility, small and large scale modelling and mapping of soil erosion is inevitable. The most widely used approaches during an 80year history of erosion modelling are Universal Soil Loss Equation (USLE)-type based algorithms which have been applied in 109 countries. Addressing soil erosion by water (excluding gully erosion and land sliding), we start this review with a statistical evaluation of nearly 2,000 publications). We discuss model developments which use USLE-type equations as basis or side modules, but we also address recent development of the single USLE parameters (R, K, LS, C, P). Importance, aim and limitations of model validation as well as a comparison of USLE-type models with other erosion assessment tools are discussed. Model comparisons demonstrate that the application of process-based physical models (e.g., WEPP or PESERA) does not necessarily result in lower uncertainties compared to more simple structured empirical models such as USLE-type algorithms. We identified four key areas for future research: (i) overcoming the principally different nature of modelled (gross) versus measured (net) erosion rates, in coupling on-site erosion risk to runoff patterns, and depositional regime, (ii) using the recent increase in spatial resolution of remote sensing data to develop process based models for large scale applications, (iii) strengthen and extend measurement and monitoring programs to build up validation data sets, and (iv) rigorous uncertainty assessment and the application of objective evaluation criteria to soil erosion modelling. Keywords: Universal soil loss equation, RUSLE, CSLE, Soil redistribution, Soil degradation, Water erosion, Model, Review

In this paper, we evaluated the Water Erosion Prediction Project (WEPP) model using 5-yr monitored runoff and sediment data from three different lands cover treatments in the Loess Plateau of China. The results showed that the WEPP model was able to predict 22 out of 37 recorded runoff producing events, and 20 out of 34 recorded sediment producing events. Prediction of annual runoff is more accurate than the prediction of sediment. The correlation coefficients between the annual monitored and simulated runoff ranged from 0.69 to 0.91, and 0.11 to 0.90 for sediment; for the three treatments (bare, corn and grass), the prediction for the grass plot is better than the other two. Soil moisture and storm intensity appeared to have greater effect on both predictability and accuracy of runoff events and sediment yields. For grass plot, Nash-Sutcliffe coefficient was 0.76 in runoff and 0.56 in sediment. WEPP predictions for the grass plot were in agreement with measured values, but no better than using the averaged measured values for the other two treatments (bare and corn plots). Application of the WEPP model should be decided with precautions in the Loess Plateau area

Rigorous validation of the first-order detachment-transport coupling concept using different sediment sizes is nonexistent in the literature. We hypothesized that particle sizes in a sediment-laden flow can affect soil detachment. The objectives of this study were to investigate the relationship between detachment rates by rill flows and hydraulic parameters under low flow discharges, and to quantify the responses of soil detachment rates to sediment loads and median sizes. A concentrated flow flume test was conducted under three low flow discharges (0.00033, 0.00067 and 0.00100 m2·s−1) and three sediment concentrations (50, 100 and 200 kg·m−3) with five median sizes (0.233, 0.204, 0.169, 0.115 and 0.078 mm). The results showed that the relationship between soil detachment capacity and shear stress fits the Water Erosion Prediction Project (WEPP) model well (R2 = 0.89). Stream power, compared with shear stress, is a better hydraulic parameter in simulating soil detachment rates under different sediment concentrations. The soil detachment rates by sediment-laden rill flows were negatively related to both sediment loads and sediment median sizes, validating the first-order sediment feedback relationships used in the WEPP model. The overall responses of soil detachment rates to sediment loads and sediment median sizes followed multivariate linear relationships, further demonstrating the negative feedbacks of sediment load and size on soil detachment by rill flow.

© 2017 China University of Geosciences (Beijing) and Peking University The devastating effect of soil erosion is one of the major sources of land degradation that affects human lives in many ways which occur mainly due to deforestation, poor agricultural practices, overgrazing, wildfire and urbanization. Soil erosion often leads to soil truncation, loss of fertility, slope instability, etc. which causes irreversible effects on the poorly renewable soil resource. In view of this, a study was conducted in Kelantan River basin to predict soil loss as influenced by long-term land use/land-cover (LULC) changes in the area. The study was conducted with the aim of predicting and assessing soil erosion as it is influenced by long-term LULC changes. The 13,100 km 2 watershed was delineated into four sub-catchments Galas, Pergau, Lebir and Nenggiri for precise result estimation and ease of execution. GIS-based Universal Soil Loss Equation (USLE) model was used to predict soil loss in this study. The model inputs used for the temporal and spatial calculation of soil erosion include rainfall erosivity factor, topographic factor, land cover and management factor as well as erodibility factor. The results showed that 67.54% of soil loss is located under low erosion potential (reversible soil loss) or 0–1 t ha −1 yr −1 soil loss in Galas, 59.17% in Pergau, 53.32% in Lebir and 56.76% in Nenggiri all under the 2013 LULC condition. Results from the correlation of soil erosion rates with LULC changes indicated that cleared land in all the four catchments and under all LULC conditions (1984–2013) appears to be the dominant with the highest erosion losses. Similarly, grassland and forest were also observed to regulate erosion rates in the area. This is because the vegetation cover provided by these LULC types protects the soil from direct impact of rain drops which invariably reduce soil loss to the barest minimum. Overall, it was concluded that the results have shown the significance of LULC in the control of erosion. Maps generated from the study may be useful to planners and land use managers to take appropriate decisions for soil conservation.

Soil loss models are useful tools for making land management decisions to prevent soil and water quality problems. Several soil loss models have been developed, including the process-based Water Erosion Prediction Project (WEPP) model and the empirical Revised Universal Soil Loss Equation (RUSLE). Although process-based models provide accurate soil loss estimates, they are infrequently used for conservation planning because of their complexity and data need. On the other hand, models such as RUSLE cannot predict the soil loss nor the sediment composition associated with individual events, both of which are critical for designing accurate soil and water conservation practices. Therefore, the objective of this study was to develop a model for estimating sediment delivery on an event scale while predicting its clay, silt and sand fractions. For this purpose, the WEPP model was implemented using measured soil and climate data from Central Chile to generate a soil loss database for many hillslope configurations and management practices. More than 200,000 erosion events were generated using data from 83 sites. Using multiple regression analysis, the main variables controlling soil loss were identified, which included rainfall erosivity, soil erodibility, hillslope geometry, antecedent soil moisture and total precipitation. These variables were incorporated into a soil loss model, which was calibrated using data from 32 sites (R2 = 0.81–0.83) and validated for the remaining 51 sites (R2 = 0.66–0.89). The model provided accurate estimates for the clay and silt fractions (R2 = 0.86 and 0.78, respectively) but showed difficulties for predicting the sand fraction (R2 = 0.31). Contour plowing and vegetative filter strip routines were also incorporated into the soil loss model, providing reliable soil loss (R2 = 0.51–0.78), clay (R2 = 0.54–0.75), and silt (R2 = 0.57–0.68) estimates. The developed model is remarkably easy to use and, due to its simplicity, allows incorporating other soil conservation routines, providing a flexible tool for soil conservation planning. This study provides a detailed description and methodology for building such a model and discusses its advantages and limitations.

RUSLE2 is a rainfall erosion model that, in its standard mode, predicts long term soil losses as an aid to making decisions related to soil conservation in the USA. In recent times, RUSLE2 has developed a capacity to predict event soil losses using user entered data for event rain and EI30. WEPP is a more process based model which uses a stochastic weather generator, CLIGEN, to generate events that are stochastically distributed in time. CLIGEN does not estimate event EI30 values for the rainfall events it generates but it is possible to do so through use of erosivity densities (EI30 per unit quantity of rainfall) data available in RUSLE2. This enables CLIGEN to be used as a climate generator for RUSLE2 and provides the capacity to use RUSLE2 in roles similar to the ones where WEPP is being applied.

CLImate GENerator (CLIGEN) (v5.3), a stochastic weather generator, is widely used in conjunction with the Water Erosion Prediction Project (WEPP) model for runoff and soil loss predictions. CLIGEN generates daily estimates of weather based on long-term observed weather station data statistics. For the United States, the original CLIGEN database released with WEPP in 1995 was derived using inconsistent periods of climate records through 1992 that could lead to significant variations in runoff and soil loss predictions on spatial and temporal scales. To achieve more reliable estimates of runoff and soil loss, an updated climate database was derived from a consistent 40 years of recent climate records of 1974 to 2013 in the United States. The objectives of this study were to (1) examine the spatial patterns in trends of differences in precipitation and maximum and minimum temperatures between the two databases, and (2) evaluate the impacts on WEPP-predicted mean annual runoff and soil loss, from the original to the updated databases. For runoff and soil loss estimates, WEPP simulations were conducted under a tilled fallow condition for 1,600 CLIGEN locations in the contiguous United States for a slope profile of 22.1 m length, 9% slope gradient, and silt loam soil. Comparison of precipitation and maximum and minimum temperatures between the original and updated databases showed variations in spatial patterns both annually and seasonally. Annual precipitation and minimum temperature generally increased across most of the country while maximum temperature increased in the western half of the United States and parts of the Northeast. Seasonally, increases in precipitation are evident in the Midwest in spring, fall, and winter, the Northwest in spring, and the Southeast in fall. Maximum daily temperature has increased in the western half of United States and parts of the Northeast in the winter, fall, and spring, whereas minimum daily temperature has increased in all seasons across the United States. Changes in WEPP-simulated mean annual runoff and soil loss from the use of the original to the updated CLIGEN database showed increases in runoff and soil loss in most of the United States. However, some stations showed either increases or decreases in runoff and/or soil loss with the updated database primarily because of differences in monthly precipitation and intensity values in the two databases. Understanding the impacts of the use of the updated database on runoff and soil loss from this study will help in making informed decisions for conservation planning and management when utilizing the WEPP erosion model.

Tokat is one of the developing provinces in terms of urbanism. Therefore, the land use changes city-wide which closely affects soil erosion. Numerical estimation of soil erosion is very important to prevent soil losses. In this study, USLE and WEPP Hillslope model were used to estimate the long-term soil losses in a slope area which used to be a pasture land and then turned into a fruit orchard in Büyükbeybağı area of Tokat province. Erosion sensitivity of the soil in the slope area was detected to be very low. Erosivity value of the area is low, soil is resistant to erosion due to pasture land use type and fruit orchard use type does not require intense soil cultivation practices. For all these reasons, both estimation technologies estimated soil losses of the land to be low. Tokat, şehircilik bakımından gelişmekte olan illerden birisidir. Bundan dolayı il genelinde arazi kullanımı değişmekte ve bu durum toprak erozyonunu çok yakından etkilemektedir. Toprak erozyon miktarının sayısal olarak tahmin edilmesi, toprak kayıplarının engellenmesinde çok önemlidir. Bu çalışmada, Tokat ili Büyükbeybağı mevkiinde yer alan önceden mera arazi kullanım türünde olup, daha sonra meyve bahçesine dönüştürülmüş bir yamaç arazide meydana gelen, uzun yıllık toprak kayıpları USLE ve WEPP Hillslope modeli ile tahmin edilmiştir. Yamaç arazisinde yer alan toprakların aşınıma duyarlılığı oldukça düşük olarak belirlenmiştir. Yörenin erosivite değerinin düşük, mera kullanım türünden dolayı toprakların erozyona dayanıklı olması ve meyve bahçesi kullanım türünün yoğun toprak işleme uygulamalarını gerektirmemesine bağlı olarak, her iki tahmin teknolojisi de arazinin toprak kayıplarını düşük olarak tahmin etmiştir.

The need to estimate event soil loss better than the USLE and the RUSLE has led to the development of WEPP and the USLE-M, a modification of the USLE that estimates event soil loss for bare fallow runoff and soil loss plots in the USLE database better than the USLE/RUSLE when runoff is known or predicted well. Although the erosivity indices in the USLE-M and the USLE/RUSLE focus on raindrop driven erosion, the calibration of the erodibility index on plots where rilling occurs enables the USLE-M and the USLE/RUSLE to be applied on areas where sheet and rill erosion occur. This paper presents results from the application of both WEPP and the USLE-M to modelling event soil loss from 6 runoff and soil plots at the Ansai Research Station of Soil and Water Conservation, Chinese Academy of Sciences (36°56′N, 109°16′E) produced from steep slopes (8.7%–53.2%) where rills frequently developed under natural rainfall during 1985–1992. WEPP was calibrated to minimize the mean squared error (MSE) between measured runoff and predicted runoff for the events where WEPP predicted runoff and soil loss to occur. The number of events where WEPP predicted runoff and soil loss to occur varied from 25% to 41% of events that actually produced soil loss. In the comparison with WEPP, the USLE-M erodibility factor was calibrated by dividing the total observed soil loss where WEPP predicted runoff and soil loss to occur by the total of the USLE-M erosivity factor for the same set of events. Consequently, the total amount of soil lost estimated for these events by both models were the same. This enabled the ability of the models to predict event soil loses to be examined using the Nash-Sutcliffe model efficiency index. In every case, the efficiency index values for the USLE-M were higher than for WEPP irrespective of whether the values of USLE-M erosivity index were determined using observed or WEPP predicted runoff. As a model of rainfall erosion, focusing on a process based approach has not resulted in WEPP performing as well as or better than the USLE-M on the steep bare fallow plots of loessal soil at the Ansai Research Station in China.

The largest and practically non-renewable losses of erosion in all sectors of the economy undergoes agrarian sphere. The area of land damaged by water erosion in Ukraine reaches 33.3% or 13.3 million hectares, of which 4.5 million hectares are medium and strongly ground, of which 68 thousand hectares completely lost the humus horizon. The reasons for the acceleration of erosion processes in Ukraine are the mass ignoring of the simplest agrotechnical anti-erosion measures, the imperfection of the land management organization of the territory to provide elementary anti-erosion protection, underestimation of the role of wild forest belts, ineffective use of funds aimed at preventing erosion, resulting in degradation processes lately unprecedented. High degree of cultivation of agricultural land and excessive saturation of crop rotation with crop rotation against the background of non-compliance with the basic provisions of a set of measures to increase and maintain soil fertility is a direct way to the destruction of soil cover as a basis for the existence of life on our planet. The quantitative estimation of water erosion involves two systems of evaluation criteria: the actual soil erosion and the potential danger of erosion at a certain level of probability of the effects of erosion factors (the world experience in the organization of anti-erosion protection indicates that it is sufficient to calculate 10% security). To update the outdated data on soil erosion in Ukraine, it is necessary to conduct a repeated continuous survey of soil cover on a modern methodological basis, which requires significant financial costs. However, it is possible to assess the erosion hazard using mathematical models of erosion, in particular the Water Erosion Prediction Project (WEPP) model, which provides information on the intensity and tension of erosion processes and the determination of the magnitude of possible erosion losses in the soil. WEPP is a physically grounded model that allows the modeling of erosion processes of agricultural lands located on small water catchments (up to 250 hectares). The model is based on mathematical equations describing physical processes of soil erosion and hydrology of erosion runoff. In this case, the catchment area, according to its relief, is divided into elementary units - slopes and watercourses. The model allows you to trace the routes of drainage and flushing along the elements of the relief up to the exit of the catchment. Simulation can be carried out in two modes: in the mode of long-term modeling and in mode of modeling of a single shower. The input data for the model are data on the terrain, the characteristics of the catchment soil, types of cultivating soil and agricultural vegetation on its fields, parameters characterizing the climatic conditions of the terrain. Two series of forecast calculations were conducted: the first one was for the conditions of the existing land placement, the second one for the case of implementation of the project of soil protection of the territory. For this purpose, in both cases, the preferred lines of the drain lines were determined, for each runoff line, soil erosion loss calculation using the WEPP model was performed, after which regularization and interpolation of the obtained data were performed and erosion hazard maps for each case were constructed. Quantitative estimation of two series of forecast calculations for the conditions of existing land placement and in the case of implementation of the project of soil protection of the territory using WEPP erosion model and specialized software showed that in the event of a 10% rainstorming of equipment, the territory of forest bands and drainage facilities significantly reduces erosion danger, even in the black pair.

Soil or sediment redistribution prediction along hillslopes and within small watersheds is considered to be a great challenge for the application of watershed erosion models in predicting the impact of soil and water conservation measures as well as for the redistribution of pollution such as radioactive fallout. In this study, long-term soil loss and deposition were estimated for two nested semi-arid watersheds within the Walnut Gulch Experimental Watershed in Southeastern Arizona using the process-based Geo-spatial interface of WEPP (GeoWEPP). While soil parameters were previously parametrized and validated through watershed outlet runoff and sediment yields, the channel parameters were adjusted and validated based on reference values of soil redistribution generated from fallout radionuclide 137Cs samples within the watersheds. Two methods were applied for the soil redistribution analysis by comparing observed and simulated soil loss/deposition rates (a) at single pixels and reference values at the specific location of each 137Cs sample site; and (b) for average values of a 5 m radius around each 137Cs sample site to compensate for measurement and model uncertainties. Surprisingly, soil redistribution predictions improved as topographic data resolution increased from 5 m to 3 m and were best at 1 m without changing key model parameters that were originally derived at the watershed scale.

Soil erosion affects agricultural landscapes worldwide, threatening food security and ecosystem viability. In arable environments, soil loss is primarily caused by short, intense rainstorms, typically characterized by high spatiotemporal variability. The complexity of erosive events challenges modeling efforts and explicit inclusion of extreme events in long-term risk assessment is missing. This study is intended to bridge this gap by quantifying the discrete and cumulative impacts of rainstorms on plot-scale soil erosion and providing storm-scale erosion risk analyses for a cropland region in northern Israel. Central to our analyses is the coupling of (1) a stochastic rainfall generator able to reproduce extremes down to 5-minute temporal resolutions; (2) a processes-based event-scale cropland erosion model (Dynamic WEPP, DWEPP); and, (3) a state-of-the-art frequency analysis method that explicitly accounts for rainstorms occurrence and properties. To our knowledge, this is the first study in which DWEPP runoff and soil loss are calibrated at the plot-scale on cropland (NSE is 0.82 and 0.79 for event runoff and sediment, respectively). We generated 300-year stochastic simulations of event runoff and sediment yield based on synthetic precipitation time series. Based on this data, the mean annual soil erosion in the study site is 0.1 kg m-2 [1.1 t ha-1]. Results of the risk analysis indicate that individual extreme rainstorms (>50 return period), characterized by high rainfall intensities (30-minute maximal intensity > ~60 mm h-1) and high rainfall depth (>~200 mm), can trigger soil losses even one order of magnitude higher than the annual mean. The erosion efficiency of these rainstorms is mainly controlled by the short-duration (≤30 min) maximal intensities. The results demonstrate the importance of incorporating the impact of extreme events into soil conservation and management tools. We expect our methodology to be valuable for investigating future changes in soil erosion with changing climate.

The variation of soil erosion across scales remains a controversial issue. A theoretical framework, coupling the normalized Green-Ampt equation for infiltration, 1D kinematic wave model for overland flow, and WEPP erosion modeling approaches for soil erosion, was used to explain and quantify the direct effect of scale on the soil erosion process. The results show that the relation between interrill erosion and slope length accords with a power-law decreasing trend, while the relation of rill erosion versus slope length shows a power-law increasing trend. Moreover, the power-law scaling of interrill erosion becomes more prominent with an increase of rainfall duration and intensity but is nearly independent of the interrill erodibility factor. The rainfall duration, soil type, soil critical shear stress, sediment transport coefficient, and rill erodibility factor substantially influence the magnitude of scale effect on rill erosion, while rainfall intensity, slope gradient, and Manning's roughness have minor effects. It suggests that the scale effect on soil erosion is variable and dynamic for different erosion types, rainfall and soil characteristics, which can explain why the controversial scaling relationships of soil erosion exist in previous studies. The physically based soil erosion model WEPP is compared to the empirical models USLE and RUSLE at various scales. Only when rill erosion plays a dominant role in soil loss do all these models exhibit consistent scale effect on erosion. These results provide insights into the essence of scaling in the hillslope soil erosion process, which are expected to benefit the development of upscaling techniques for the large-scale hydrological, geomorphological, and ecological processes.

The Water Erosion Prediction Project (WEPP) model has been widely used to assess the impacts of management practices and climate change on runoff and soil loss at both hillslope and watershed scales. However, the representation of channel erosion processes in WEPP has not been changed significantly since it was released. The current (WEPP v2012.8) and previous WEPP versions assume that channel input erodibility parameters are constant through time, which may lead to erroneous channel detachment predictions, especially for cropland with substantial tillage operations. In this research, the temporally constant values of channel erodibility and critical shear stress were replaced by daily updated values, using the same temporal erodibility and critical shear stress adjustments that are applied in hillslope profile simulations for rill detachment. Observed watershed-scale runoff and soil erosion data from six agricultural watersheds were used to calibrate and compare the WEPP model performance in simulating channel runoff volumes and soil losses before and after the modification. The research showed both WEPP v2012.8 and the modified WEPP model (WEPP_CE) could satisfactorily simulate event-based hydrology and soil erosion at the watershed outlets after calibration. The WEPP_CE model with temporally varying channel erodibility and critical shear stress values demonstrated improved representation of the physical processes in channel soil detachment. Continued improvement in the representation of channel erosion processes in WEPP and other process-based models is needed. The improved WEPP model can be used to evaluate the effectiveness of soil conservation practices on hydrology and erosion in further research.

Different surveying methods were used to assess and illustrate road profile changes and sediment displacement over a six-month period at four sites on a sand road at Cooloola, Queensland, Australia. Total monthly traffic and total monthly rainfall (two-way ANOVA without replication, p < 0.05) had an effect on the mean centre dumpy level depths and sediment displacement at one site (correlation 0.81 for total monthly traffic/mean centre dumpy level depths), but not at the other three sites. Traditional road-surface field measurements showed large changes in volume and weight of sediment movement and Water Erosion Prediction Project (WEPP) modelling predicted an annual sediment yield (i.e., sand displacement from road) of 115.37 kg with a total sediment loss of 7,551.36 kg for each 120 m by 6 m site over the next 80 years. The methodology used can be applied to other national parks and protected areas and for the effective and sustainable management of sand road networks. Subscribe to JPRA

The sediment transport capacity must be considered because it provides a theoretical basis for accurate prediction of soil erosion. Existing studies tended to study sediment transport capacity using a particular soil, but the models derived from one kind of soil cannot be applicable to other soil types. To obtain a prediction model for a variety of soils and evaluate its applicability, sandy loess and loess soil (d50=0.095 mm and d50’=0.04 mm) were chosen in the indoor artificial simulated sediment transport experiments. The experimental slopes ranged from 7% to 38.4% and the unit discharges were adjusted from 0.00014 to 0.00526m2/s. Moreover, this study combined the experimental data with cohesive soil and cohesionless sand from four scholars so as to analyze the response relationship between sediment transport capacity and each flow intensity parameter through dimensionless processing. Results showed that the dimensionless sediment transport capacity varied with its power function relationship with the flow intensity parameters. Through analysis, the effective stream power could be seen as an optimum indicator (R2=0.9692). After considering the effective stream power and volume sediment concentration, this study derived a formula for calculating the sediment transport capacity. It was better than the ANSWERS (Areal Nonpoint Source Watershed Environment Response Simulation) model, improved WEPP (Water Erosion Prediction Project) model, Zhang’s formula and Ali’s model due to its superior applicability to cohesive soil and cohesionless sand. These findings lay a basis for establishing prediction models of soil erosion.

Whereas current erosion models are successful in quantitative estimates of soil erosion by water flow, modeling the coevolution of geomorphological features, particularly rill network properties and soil erosion on hillslopes, is still a major challenge. In this study, we propose a rill evolution modeling approach, and combine it with a rainfall-runoff and soil erosion model to simulate the feedback loop of hillslope geomorphic development and soil erosion processes. Rill evolution is mainly characterized by three rill network attributes, comprised of rill density, orientation angle, and rill width, all modeled with physical equations. The entire rainfall-runoff-erosion and rill evolution model is tested against a set of rill network evolution and soil erosion data from an experimental hillslope subjected to successive rainfall events. The simulated spatial and temporal variations of rill network characteristics and soil erosion agree well with the measured data. The results demonstrate that the three rill network characteristics continually alter the partitioning of interrill and rill flows and affect the interrill and rill flow erosivity and soil erosion, which in turn modify the rill geometry and rill network planform. Comparatively, existing approaches such as WEPP that ignore the rill evolution processes largely underestimate the hillslope soil erosion when using time independent model parameters. Moreover, a sensitivity analysis indicates that both the rill evolution and soil erosion processes are sensitive to the rill evolution parameters, rainfall intensity, and slope angle. These results can inform the development of general geomorphic evolution and soil erosion models on evolving rilled hillslopes.

Sedimentation has been causing both onsite and offsite damages around the world. In this context, watershed prioritization allows decision-makers to implement management strategies for reducing sediment yield. So, this study aimed to determine the subwatersheds that produce the maximum amount of sediment for reducing sedimentation in a watershed. We used GeoWEPP, Geo-spatial interface for Water Erosion Prediction Project (WEPP) model, to predict sediment yield in the watershed. In order to run GeoWEPP easily and reliably, the watershed was divided into 85 subwatersheds. Sediment yield was found to be 5.13 tons ha− year−for the whole watershed. In order to produce a sediment risk map in ArcGIS, values from 0 to 1 were assigned to the sediment yield values of each subwatershed by using min-max normalization method. The obtained values were divided into 5 risk classes. According to this map, 42% of the study area was subject to very low sediment risk, while 28%, 12%, 7%, and 11% of it were subject to low, moderate, high, and very high sediment risk. When the sediment yield amount of the risk classes was investigated, very high sediment risk class accounted for 54% of total sediment yield in the watershed. These results revealed that a small part of the watershed contributed a disproportionate amount of the total sediment yield. Consequently, the GeoWEPP-based prioritization approach can help decision-makers design and implement effective soil and water conservation practices to reduce sediment yield in the regions where human and financial resources are limited.

Submitted by Ana Paula Oliveira Aranha (ana-paula.aranha@unesp.br) on 2020-11-23T12:59:51Z No. of bitstreams: 1 D. FINAL Ana P. O. Aranha.pdf: 1214953 bytes, checksum: 9280514cddd1f5d68d77e073b1f2dae2 (MD5) Approved for entry into archive by Laudicélia Martins Arantes (lm.arantes@unesp.br) on 2020-11-23T13:12:31Z (GMT) No. of bitstreams: 1 aranha_apo_me_jabo.pdf: 1214953 bytes, checksum: 9280514cddd1f5d68d77e073b1f2dae2 (MD5) Made available in DSpace on 2020-11-23T13:12:31Z (GMT). No. of bitstreams: 1 aranha_apo_me_jabo.pdf: 1214953 bytes, checksum: 9280514cddd1f5d68d77e073b1f2dae2 (MD5) Previous issue date: 2020-07-31 Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) Um componente crítico para o uso bem-sucedido do WEPP, em regiões com solos tropicais, refere-se à carência de valores da erodibilidade em entressulcos (Ki). Deste modo, objetivou-se: i) determinar Ki de latossolos argilosos; ii) estimar Ki a partir de atributos do solo; iii) acessar a variabilidade espacial dos valores preditos de Ki. Parcelas experimentais de 0,38 m2, com declividades médias de 0,10 m m-1, foram submetidas a chuva simulada, com intensidade de 65 mm h-1 e duração de 65 minutos, para determinar Ki. Amostras de enxurrada foram coletadas e, posteriormente, a concentração de sedimentos e o fluxo de enxurrada foram determinados. Os solos testados foram: 1) LV1 - Latossolo Vermelho distrófico; LV2 - Latossolo Vermelho distrófico; LV3 - Latossolo Vermelho eutroférrico. Os teores de argila e Fe2O3 apresentaram correlações negativas e significativas com Ki (r=-0,94 e r=-0,86, nesta ordem). A razão caulinita/(caulinita+gibbsita) apresentou correlação positiva e significativa com Ki. As equações do modelo WEPP foram insatisfatórias para estimar Ki, pois a eficiência do modelo (EF) foi negativa (EF=-90.07). Uma equação para estimar Ki foi proposta: Ki = 0,8445+0,0013 × Areia (R2=0,87**). Ela foi validada, cujo desempenho foi muito bom (EF = 0,90). Uma análise geoestatística foi conduzida, o que permitiu a confecção de mapas. A variabilidade espacial dos atributos foi observada, com nítida contribuição da textura e mineralogia do solo em definir zonas específicas para Ki. Tais resultados podem servir de apoio para estudos futuros da erosão hídrica em ambientes tropicais, utilizando a variabilidade espacial no seu processo de modelagem. A critical component for the successful use of WEPP, in regions with climatic soils, refers to the lack of erodibility values in off-season (Ki). Thus, the objective was to: i) determine Ki of clayey oxisols; ii) estimate Ki from soil attributes; iii) access a spatial variability of the predicted Ki values. Experimental plots of 0.38m2, with media slope of 0.10 m m-1, were subjected to simulated rain, with an intensity of 65 mm h-1 and duration of 65 minutes, to determine Ki. Flood samples were collected and, subsequently, a concentration of sediments and flood flow were selected. The following were tested: 1) LV1 - Dystrophic Red Latosol; LV2 - Dystrophic Red Latosol; LV3 - Eutropheric Red Latosol. The clay and Fe2O3 contents reported negative and calculated correlations with Ki (r = 0.94 and r =-0.86, in that order). The kaolinite/(kaolinite+gibbsite) ratio shows a positive and significant correlation with Ki. As the equations of the WEPP model were unsatisfactory for the Ki estimate, the efficiency of the model (EF) was negative (EF = -90.07). An equation for the Ki estimate was proposed: Ki=0.8445+ 0.0013 × Sand (R2 = 0.87 **). It was validated, whose performance was very good (EF = 0.90). A geostatistical analysis was conducted, or allowed the making of maps. A spatial variability of the attributes was observed, with the contribution of soil texture and mineralogy in specific areas defined for Ki. These results may serve as support for future studies of water erosion in climatic environments, using a spatial variation in its modeling process. 135408/2018-0

WEPP is a process-based model that estimates runoff and water erosion at slope level, maintaining a soil water balance at daily pace. The objective of this work is to adjust and validate the water balance component of the WEPP model in two watershed management situations (afforestation and natural grassland field) to obtain an adjusted tool that determines runoff and erosion. Soil water content data measured with neutron probe 4 times in the year down to 1.3 m depth during 10 years were used, and were compared with WEPP estimates. The results indicate that the WEPP estimations were not good (Efficiency coefficient (E) = 0.03, -1.29, -0.01, -1.74, 0.17 and -0.08 for the profiles) in high slope (C), average slope (D) and low slope (F), in the Grassland and afforested watershed, respectively, with an E considered insufficient and with periods of over and underestimation water content for both management situations. A better fit was obtained by eliminating the data outside of the calibration line in the profile C, with no improvement for the D and F profiles in both management situations. The results indicate that parameters such as evapotranspiration and WEPP equations must be adjusted to achieve better performance. Resumen: El modelo WEPP se basa en procesos que estiman escurrimiento y erosión hídrica a nivel de ladera, manteniendo un balance hídrico del suelo en forma diaria. El objetivo de este trabajo es ajustar y validar el componente balance hídrico del modelo WEPP en dos situaciones de manejo de cuencas (forestada y pastura natural) para obtener una herramienta ajustada que permita estimar escurrimiento y erosión. Se utilizaron datos de agua en el suelo medidos con sonda de neutrones cuatro veces por año hasta 1,3 m de profundidad durante diez años, y se los comparó con los datos simulados con el modelo WEPP. Los resultados indican que la estimación del modelo en los perfiles situados en ladera alta (C), ladera media (D) y ladera baja (F) para ambas cuencas no fue buena (Coeficiente de eficiencia (E) = 0,03, -1,29, -0,01, -1,74, 0,17 y -0,08 para los perfiles C, D y F en la cuenca de pastura natural y forestada, respectivamente), con E considerado como insuficiente y con períodos de sobre y subestimación del contenido de agua en el suelo para ambas situaciones de manejo. Al eliminar los datos de contenido de agua registrados por fuera de la recta de calibración de la sonda de neutrones, los resultados presentaron un mejor ajuste para el perfil C, no registrándose igual mejora para los perfiles D y F en ambas situaciones de manejo. Los resultados indican que se deben ajustar parámetros como la evapotranspiración y las ecuaciones del modelo WEPP para lograr su mejor performance. Resumo: O modelo WEPP é baseado em processos que estimam o escoamento superficial e a erosão hídrica no nível da encosta, mantendo um balanço hídrico do solo diariamente. O objetivo deste trabalho é ajustar e validar o componente de balanço hídrico do modelo WEPP em duas situações de manejo da bacia (pastagens florestadas e naturais) para obter uma ferramenta ajustada que permita estimar o escoamento superficial e a erosão. Os dados de água no solo medidos pela sonda de nêutrons foram usados quatro vezes por ano, com profundidade de 1,3 m por dez anos e comparados com dados simulados usando o modelo WEPP. Os resultados indicam que a estimativa do modelo nos perfis localizados nos declives alto (C), médio (D) e baixo (F para ambas as bacias) não foi boa (coeficiente de eficiência (E) = 0,03, -1,29, -0,01, -1,74, 0,17 e -0,08 para os perfis C, D e F na bacia de pastagem natural e florestal, respectivamente) com E considerado insuficiente e com períodos de super e subestimação do teor de água no solo para ambos Situações de gerenciamento: Ao eliminar os dados de conteúdo de água registrados fora da linha de calibração da sonda de nêutrons, os resultados mostraram uma melhor adequação ao perfil C, não registrando a mesma melhoria para o D e F em ambas as situações de gerenciamento. Os resultados indicam que parâmetros como evapotranspiração e equações do modelo WEPP devem ser ajustados para alcançar seu melhor desempenho.

Almost 20 years of observed 1-minute weather data from the most complete and longest operational NOAA Automated Surface Observation Station (ASOS) network station were used to prepare seven climate inputs (the raw, unadjusted, quality checked, and gap-filled gauge data and six temporal aggregations of the same data) to the Water Erosion Prediction Project (WEPP) model. The nearest stations from both the old (1995) and new (2015) CLIGEN databases were also used to compare climate inputs and corresponding soil loss predictions from WEPP as it would typically be applied in the field for research or soil conservation planning. The results showed that WEPP simulations driven by CLIGEN closely approximated the vigor (erosivity) of breakpoint quality climate inputs despite using only 15-minute precipitation data for CLIGEN input file parameterization. Erosion prediction models and corresponding theory were developed initially based on breakpoint rainfall data, so climate inputs that more closely approximate that kind of data should be considered ideal for soil erosion modeling efforts. These results call into question the use of coarser resolution climate inputs such as 15-minute precipitation data, which are most common, without applying sufficient adjustments and/or corrections to better approximate breakpoint data. Our findings also suggest that intensity corrections of 4% used by Hollinger et al. (2002), USDA-ARS (2008, 2013), and McGehee and Srivastava (2018) for the Revised Universal Soil Loss Equation (RUSLE2) erosivity inputs may not be sufficient for at least the climate near these stations in the Northeastern United States. A national study of precipitation intensity and erosivity based on high resolution climate inputs like those available from the ASOS network may be warranted.

Soil erosion is identified as the primary cause of soil degradatgion due to the unsustainable agricultural practices, leading to severe threat worldwide for soil health and water quality problems. Therefore, quantifying soil erosion under various conservation practices is important for watershed management and a framework that can accurately estimate the spatio-temporal dynamics of soil erosion is required. In this paper, a modeling framework that coupled physically based models, Water Erosion Prediction Project (WEPP) and MIKE SHE/MIKE 11, was presented. Daily soil loss in field scale was determined using WEPP and the transport processes of the eroded soil were simulated using an advection-dispersion equation in MIKE SHE/MIKE 11 models. The framework facilitated the physical simulation of sediment production at the field scale and transport processes across the watershed. The coupled model was tested in an intensively managed agricultural watershed in Illinois. The impacts of no-till practice on both sediment production and sediment yield were evaluated using scenario-based simulations with different fractions of no-till and conventional tillage combinations. The results indicated that if no-till were implemented for all fields throughout the watershed, 76% and 72% reductions in total soil loss and sediment yield, respectively, can be achieved. In addition, if no-till practice were implemented in the most vulnerable areas to sediment production across the watershed, a 40% no-till implementation can achieve almost the same reduction as 100% no-till implementation. Based on the simulation results, the impacts of no-till practice are more prominent if implemented where it is most needed.

Indonesia government has nominated Surabaya city as one of the Indonesia pilot projects of waste to energy power plants (WEPP). The WEPP in Surabaya will start to operate in November 2019. However, to ensure this facility operates according to the regulation, the WEPP should be supported by good policy from the stakeholder. This research aims to review the policy implementation of WEPP in Surabaya pilot project based on Van Meter and Van Horn theory. The theory has several indicators that indicate good policy implementation. This research used a descriptive qualitative approach by interviewing fifteen respondents who involved in WEPP pilot project. The results suggest that the policy implementation of WEPP needs further regulation from local government about the management procedure of waste material, which converts to the tipping fee. The solution suggested from this issue is the contract refinement and the fundamental improvement of the communication system to the better WEPP.

Severe fire greatly increases soil erosion rates and overland-flow in forest land. Soil erosion prediction models are essential for estimating fire impacts and planning post-fire emergency responses. We evaluated the performance of a) the Revised Universal Soil Loss Equation (RUSLE), modified by inclusion of an alternative equation for the soil erodibility factor, and b) the Disturbed WEPP model, by comparing the soil loss predicted by the models and the soil loss measured in the first year after wildfire in 44 experimental field plots in NW Spain. The Disturbed WEPP has not previously been validated with field data for use in NW Spain; validation studies are also very scarce in other areas. We found that both models underestimated the erosion rates. The accuracy of the RUSLE model was low, even after inclusion of a modified soil erodibility factor accounting for high contents of soil organic matter. We conclude that neither model is suitable for predicting soil erosion in the first year after fire in NW Spain and suggest that soil burn severity should be given greater weighting in post-fire soil erosion modelling.

Landuse change significantly alters the hydrologic characteristics of the land surface within a watershed. In the present study, the impact of landuse change (2006-2016) on runoff and sediment yield has been assessed in Patiala-Ki-Rao watershed (5140 ha) located in Shivalik foot-hills, using remote sensing, geographical information system (GIS), and Water Erosion Prediction Project (WEPP) watershed model. The watershed has seven major landuse classes, namely agriculture, built-up, fallow land, forest, grass land, streams, and water bodies. The landuse change analysis indicated that the area under all the landuses decreased except built-up that increased by 372.27 ha (112.04%). Forest is the most affected landuse among all watershed landuses that shrinked by 194.90 ha followed by agriculture (64.57 ha), grass land (50.81 ha), streams (30.42 ha), fallow land (21.86 ha), and water bodies (9.72 ha). Runoff and sediment yield for the landuse of the years 2006 and 2016 were simulated by the WEPP model using two climate scenarios (2006 and 2016). The simulated runoff, sediment yield, and sediment delivery ratio increased by 18.62%, 48.04%, and 32.23% under Climate-2006 and 26.78%, 30.23%, and 16.09% under Climate-2016 due to change in landuse during a period of 10 years. This clearly indicates that landuse change in 10 years has greatly influenced the hydrology of the watershed and requires urgent land allocation policy in place for sustainable development in the area.