Modified Universal Soil Loss Equation Research Articles

Detailed spatial analysis of SWAT-simulated surface runoff and sediment yield in a mountainous watershed in China

In this study, surface runoff and sediment yields, simulated by the Soil and Water Assessment Tool (SWAT) for the Xiangxi catchment, China, are analysed at the spatial level of hydrologic response unit (HRU). This allows for a more precise targeting of best management practices than analysis at the coarser sub-basin level. It also provides the opportunity to validate simulated surface runoff and sediment yield by evaluating the plausibility of their spatial variation within the watershed. The results indicate that satisfactory model performance at a gauge does not guarantee plausible results at HRU level. Both surface runoff and sediment yields were found to vary reasonably with land use and soil types, but not with slope. The credibility of simulated surface runoff was increased by modifying selected SWAT algorithms and parameters. However, these modifications had only a marginal effect on sediment yield, which can be explained by the nonlinear relationship between sediment yield and HRU area in the modified Universal Soil Loss Equation. This study demonstrates that evaluation of model output at HRU level is highly recommended.Editor D. Koutsoyiannis; Guest editor V. Krysanova

Simulation of Sediment Yield Over Un-gauged Stations Using MUSLE and Fuzzy Model

Land and water are two most vital natural resources of the world and hence these resources must be conserved carefully to protect environment to maintain ecological balance. Estimation of runoff and sediment yield is one of the prerequisites for conservation and management of water resources and also for many hydrological applications. The present study has been taken up to predict runoff and sediment yield for a reservoir basin viz. Megadrigedda Reservoir situated in Visakhapatnam District, Andhra Pradesh, India which is having a drainage area of 363 Sq.km. Modified Universal Soil Loss Equation (MUSLE) has been used to estimate the sediment yield. The runoff factors of MUSLE were computed by the measured values of runoff and peak rate of runoff at outlet of the reservoir. Topographic factor (LS) and crop management factor(C) were determined using geographic information system (GIS) and field-based survey of land use/land cover. The conservation practice factor (P) is obtained from the literature. Sediment yield at the outlet of the study reservoir has been simulated for fifteen storm events spread over the period of 2010-2013 and is validated with that of measured values. The resulted coefficient of determination value has been obtained as 0.84 for the study area which indicates that MUSLE model is working satisfactory for the selected basin. Fuzzy logic based model has also been developed to estimate sediment yield. The resulted correlation obtained between Fuzzy logic model and MUSLE model is 0.97 and with that of measured value it is 0.937.

Evaluation of Three Soil Erosion Models for Small Watersheds

The present study aims at evaluating three soil erosion models; Modified Universal Soil Loss Equation (MUSLE); Unit Sediment graph (USG) and Water Erosion Prediction Project (WEPP). The models were tested on small watersheds within the Pamba River basin of Kerala, India, using the data on observed rainfall-runoff-sediment yield events. Three watersheds are selected with varying land use types, topography and drainage density. Three erosion models were applied for the same rainfall events and the results were compared with the observed sediment yield values. It was seen that the USG predicted the rate of sediment yield better than the other two models. Even though WEPP is a physically distributed model, the large and detailed data requirement, which is impractical in studies of this scale, affected its prediction accuracy. Application MUSLE gives the large errors compared to the observed sediment yield. Therefore, it was found from this study that the Unit Sediment Graph (USG) based approach is having better applicability for the prevailing climatic and geographical setup.

Mapping the risk of water erosion in the watershed of the Ningxia-Inner Mongolia reach of the Yellow River, China

Mapping and assessing soil-erosion risk can address the likelihood of occurrence of erosion as well as its consequences. This in turn provides precautionary and relevant suggestions to assist in disaster reduction. Because soil erosion by water in the watershed of the Ningxia-Inner Mongolia reach of the Yellow River is closely related to silting of the upper reaches of the Yellow River, it is necessary to assess erosion risk in this watershed. This study aims to identify the soil-erosion risk caused by water in the watershed of the Ningxia-Inner Mongolia reach of the Yellow River from 2001 to 2010. Empirical models called Chinese Soil Loss Equation (CSLE) and Modified Universal Soil Loss Equation (MUSLE) were used to predict the erosion modulus in slope surfaces and gullies. Then the soil erosion risk in this watershed was assessed according to the classification criteria of soil erosion intensities (SL190-2007). The study results showed that the range of values of the erosion modulus in this watershed was 0–44,733 t/km2/a. More than 20% of the total watershed area was found to present an erosion risk, with the regions at risk mainly located in channels and their upper reaches, and in mountainous areas. To determine the regression coefficients of the erosion factors with respect to erosion modulus, a GWR (geographically weighted regression) was carried out using the ArcGIS software. It was found that the topographic factor has the highest contribution rate to the soil erosion modulus, while the highest contribution rate of the erosion factors to the erosion modulus and the largest values of the factors were not located in the same places. Based on this result, the authors propose that slope management is the most important task in preventing soil loss in this watershed, and the soil-conservation projects should be built according to the contribution rate of the erosion factors.

Simulate Efficacy of Vegetative Filter Strips Based on Coupling Model and its Application

As one of Best Management Practices, Vegetative Filter Strip (VFS) had been widely application and their effects were fine. Planning and design VFS is based on quantitative predicting the purification effect. A mathematical model by coupling Vegetative Filter Strip Model (VFSMOD) with the Modified Universal Soil Loss Equation (MUSLE) was designed to estimate sediments trapping efficiency of VFS under the different conditions. Furthermore, in this paper the applicability of coupling model had been tested well by plot experiments in Chinese northwest, so the coupling model was applied to simulate the efficacy of VFS in Shaanxi Heihe River basin. Result reveals that grassed filter strips with about 10 m width are reasonable in Heihe River basin. Besides that, it is unsuitable to set grassed filter strips under the conditions of 15° above slope in river bank.

Predicting erosion and sediment yield in a mesoscale basin in the semiarid monsoon region Miyun/China

IntroductionChanges in land use and agricultural management have caused a strong increase in sediment and particulate phosphorus input into the Miyun reservoir. The simulation of the relevant runoff and sediment fluxes at the mesoscale needs adequate procedures, adapted to a semiarid monsoon climate and regional land-use pattern.ResultsThe modified Universal Soil Loss Equation (USLE-M) was integrated into the STOFFBILANZ model to calculate daily soil losses in the entire Miyun catchment area. The results are well within the range of monitoring data from Wischmeier plots that are located inside the investigation area. For the reference year 2009, soil erosion was estimated at an average of 952 kg ha−1 year−1. Daily based simulation of sediment input into surface waters was done in the next step, taking into account the likeliness of sediment input and sediment delivery ratio. Average sediment inputs are by 113 kg ha−1 year−1. Critical source areas are located on cropland and are particularly relevant on the former lakebed of the Miyun reservoir which has recently been used for corn cropping.ConclusionsCompared with observation data from the Bai and Chao rivers, the simulation of sediment loads showed a satisfying agreement that underlines the suitability of the selected approach to substitute recently used one-year balances based on the Universal Soil Loss Equation (USLE) approach. Conservation tillage was selected as a possible mitigation option to reduce soil erosion and sediment loads.Owing to the limited availability of spatial and monitoring data, the simulations are approximate and only a first step in contributing to an integrated river basin management that should be improved in future.

A review of the application of the MUSLE model worldwide

The sediment yield model of the MUSLE (modified universal soil loss equation) is applied extensively throughout the world, but different performances have been reported of its success relative to measured data. A review of all the available literature is presented to assess the application of the model under different conditions and, ultimately, make a comprehensive judgement on the different aspects to allow readers to adjust their further research. A review of 49 papers showed the variable accuracy of the model, which depends on the manner of calculation and determination of the input and output, and the study time and space scales. There were differences in land use, in correspondence of the physiographic characteristics with those of the original conditions of model development, and even in the experience of researchers in applying the model. The results also show the need to consider the original application of the model, as proposed by its developers, to achieve comparable results.Editor Z.W. KundzewiczCitation Sadeghi, S.H.R., et al., 2014. A review of the application of the MUSLE model worldwide. Hydrological Sciences Journal, 59 (2), 365–375.

Sensitivity analysis and calibration of the Modified Universal Soil Loss Equation (MUSLE) for the upper Malewa Catchment, Kenya

Simulation models are widely used for studying physical processes such as surface runoff, sediment transport and sediment yield in catchments. Most models need case-specific empirical data for parameterization before being applied especially in regions other than the ones they have been developed. Sensitivity analysis is usually performed to determine the most influential factors of a model so that they can be prioritized for optimization. In this way uncertainties in model outputs can be reduced considerably. This study evaluates the commonly used modified universal soil loss equation (MUSLE) model used for sediment yield simulation for the case of the upper Malewa catchment in Kenya. The conceptual factors of the model are assessed relative to the hydrological factors in the model. Also, the sensitivity of the model to the choice of the objective function in calibration is tested. The Sobol' sensitivity analysis method was used for evaluating the degree of sensitivity of the conceptual and hydrological factors for sediment yield simulations using the MUSLE model. Nash-Sutcliffe Efficiency (NSE) and the modified Nash-Sutcliffe Efficiency (NSEm) are used to test the sensitivity of the model to the choice of the objective function and robustness of model performance with sediment data measured from upper Malewa catchment, Kenya. The results indicate that the conceptual factors are the most sensitive factors of the MUSLE model contributing about 66% of the variability in the output sediment yield. Increased variability of sediment yield output was also observed. This was attributed to interactions of input factors. For the upper Malewa catchment calibration of the MUSLE model indicates that the use of NSEm as an objective function provides stable results, which indicates that the model can satisfactorily be applied for sediment yield simulations.

Suitability of MUSLT for storm sediment yield prediction in Chehelgazi watershed, Iran

The Chehelgazi watershed of Gheshlagh Dam in western Iran was selected to check the capability of the MUSLT (Theoretical Modified Universal Soil Loss Equation) model for estimating sediment yield during storms. The efficiency of MUSLT for sediment yield prediction was assessed using observed sediment data recorded for 11 storm events between October 2006 and April 2007. The results showed that MUSLT overestimated sediment yield with a high coefficient of determination (R2 = 0.636 and p < 0.05), and it was then calibrated by examining regression models. The developed calibrated model (C-MUSLT) performed well, with a coefficient of determination of 0.739 (p < 0.05) and relative estimation and verification errors of 49.36 and 25.18%, respectively. The results of comparison between observed and estimated values, obtained by applying the calibrated model, confirmed that the difference was significant with a t value of 1.453 (p = 0.05). Citation Sadeghi, S.H.R., Gholami, L., and Khaledi Darvishan, A.V., 2013. Suitability of MUSLT for storm sediment yield prediction in Chehelgazi watershed, Iran. Hydrological Sciences Journal, 58 (4), 892–897.

Comparison of sediment transport computations using hydrodynamic versus hydrologic models in the Simiyu River in Tanzania

This paper presents the results of a study that compares the sediment routing of the Simiyu River using the hydrologic model, Soil and Water Assessment Tool (SWAT) and the 1D hydrodynamic simulation software for Rivers and Estuaries (SOBEK-RE) model. Routing in SWAT is completed using the simplified Bagnold’s equation and in the SOBEK-RE model is undertaken using the Saint Venant equation. The upstream boundary conditions for the routing modules were derived from the subcatchments sediment yields that were estimated by SWAT using the Modified Universal Soil Loss Equation (MUSLE). The sediment loads extrapolated or interpolated from the sediment rating curve for the catchment outlet were used for calibration and validation purposes. The SWAT model predicted an erosion rate of 2.09Mt/yr. The total sediment load transported to the main outlet of the catchment simulated by the SWAT and SOBEK-RE models was equal to 2.94 and 2.72Mt/yr, respectively. Thus the models computed a net erosion in the channels of 0.84Mt/yr (SWAT) and 0.63Mt/yr (SOBEK-RE). When comparing the results of the models for the different reaches of the main channel and main tributaries, the models showed different results both in magnitude and in sign (erosion/deposition). However, in a situation where data is scarce (such as grain size, channel geometry), the more complex hydrodynamic model does not necessarily lead to more reliable results.

Stakeholder perspectives: An important component for applying total maximum daily load science

This paper compares stakeholder perceptions of uncertainty of the sediment load predictions from each of two modeling methods. A stochastic approach to sediment load prediction using the Water Erosion Prediction Project (WEPP) model provides statistical data sufficient to develop probability distributions. The other method, a traditional deterministic approach called the Modified Universal Soil Loss Equation (MUSLE), computes a sediment load caused by a selected rainfall frequency and date of event. We explain the sediment load prediction methodologies and present results of each approach in the context of the study of stakeholder perceptions of model uncertainty. Three focus groups of stakeholders (science and technical professionals, environmentalists, and producers) agreed that more information provided by the stochastic method was helpful to them as stakeholders for decision making. With advances in computing technology, stochastic models can now be used beyond the research setting and applied to nonpoint source control planning by state agencies. Connecting the natural resource sciences and the social sciences methodologies provided valuable insights into how to better engage stakeholders in understanding and making decisions about soil erosion control.

산지 소유역에 적합한 MUSLE 유출인자 산정식 개선

MUSLE는 단일 호우사상에 대한 토사유출량을 산정하기 위해 미국 47개 유역의 관측 데이터를 기반으로 Williams(1975)에 의해 개발된 식이다. MUSLE의 여러 인자 중 유출인자는 <TEX>${\alpha}(Q{\cdot}Q_p)^{\beta}$</TEX>로 표현되며, 계수 <TEX>${\alpha}$</TEX>, <TEX>${\beta}$</TEX>는 유역의 특성에 따라 많은 차이를 보인다. 따라서, 미국의 관측 데이터로부터 유도된 MUSLE의 유출인자를 국내에 그대로 적용하는 경우 적절한 결과를 기대하기 어렵다. 본 연구에서는 3개의 국내 산지 소유역에서 관측된 32개의 강우유출 및 토사유출 관측자료를 활용하여 우리나라 실정에 맞는 MUSLE의 유출인자 산정 방법을 제시하고자 한다. Q와 <TEX>$Q_p$</TEX>의 적정 산정방법 제안을 위해 SCS, Nakayasu, Clark 유출모형에 의한 강우유출량을 관측값과 비교하였고, 우리나라 산지특성에 맞는 유출인자의 계수 <TEX>${\alpha}$</TEX>, <TEX>${\beta}$</TEX> 값을 유도하기 위하여 계산된 유출인자와 관측된 자료로부터 유도된 유출인자의 상관관계를 분석하였다. 그 결과, 산지 소유역에서 Q와 <TEX>$Q_p$</TEX> 산정에 가장 적절한 강우유출 모형은 Nakayasu 모형으로 나타났고, 유출인자 <TEX>${\alpha}$</TEX>는 유역별로 0.61~6.87 범위의 값, <TEX>${\beta}$</TEX>는 0.98~1.02 범위의 값을 갖는 것으로 산정되었으며, 우리나라 산지유역에 적절한 유출인자 산정식 <TEX>$5.33(Q{\cdot}Q_p)^{0.91}$</TEX>을 제안하였다. 제안된 유출인자 산정방법을 다른 소유역에 적용하여 관측값과 비교한 결과, MUSLE에서 제시한 값보다 <TEX>${\alpha}$</TEX>는 작게, <TEX>${\beta}$</TEX>는 크게 산정되었고, 상관계수 0.948, 효율성 계수 0.325로 나타나 본 연구에서 제안한 유출인자 산정방법이 MUSLE에서 제시한 식을 적용하는 것보다 양호한 결과를 보여주는 것으로 나타났다. Williams developed the Modified Universal Soil Loss Equation(MUSLE) by replacing the rainfall energy factor in USLE with runoff energy factor, which was expressed in the function of total runoff volume Q and peak discharge <TEX>$Q_p$</TEX> with the form of <TEX>${\alpha}(Q{\cdot}Q_p)^{\beta}$</TEX>. The coefficients <TEX>${\alpha}$</TEX> and <TEX>${\beta}$</TEX> were derived from individual rainfall data of 47 basins and largely depended on the hydrological characteristics of the basins. Therefore, it may occur the inappropriate results when the runoff factor recommended in MUSLE are applied to the basins in Korea without a validation. The purpose of this study is to present the runoff model and the coefficients of the runoff factor which are suitable for mountainous basins in Korea. We used 32 rainfall runoff and sediment yields data measured from 3 small mountainous basins in Korea. In order to achieve our purposes, the total runoff and peak discharge by SCS, Nakayasu, and Clark model were compared with measured data. And the correlation analysis between calculated and measured runoff factor was performed. The results showed that the suitable model for small mountainous basins was Nakayasu model and the range of coefficients <TEX>${\alpha}$</TEX> and <TEX>${\beta}$</TEX> was 0.61~6.87 and 0.98~1.02 respectively. And the equation of <TEX>$5.33(Q{\cdot}Q_p)^{0.91}$</TEX> was suggested as the runoff factor in application of MUSLE to small mountainous basins in Korea. For the purpose of the verification, the runoff factor suggested in this study was applied to another basins to estimate sediment yields, and the results showed that the application of the newly suggested runoff factor was more reasonable than that of the runoff factor suggested by Williams(1975).

Detention Pond Sediment Accumulation Prediction using Monte Carlo Simulation

Problem statement: A study in Malaysia had been carried out to predic t the sediment accumulation in urban detention ponds. Suspended sediment is pollutant of primary concern to the river that results in adverse environmental effect. Detention pond becomes a practical approach to thi s problem. Suspended sediment that settled in stormwater detention pond, can bring effect to the detention pond functions. Questions were raised on how certain were the observed and predicted values of sediment depth and load accumulation esti mations. Secondly the question was what the sediment accumulation be in the next 100 years. The uncertainties of sediments estimation vary greatly due to the hydrological variability and rainfall ra ndom nature obtain the relationship between flow discharge and suspended sediment rate using on-site data collection at UTM and Ledang Heights, Nusajaya. Predict accumulated sediment loads and depth from MUSLE over 10-100 years. Analyze the uncertainties of sediment loads and depth using Monte Carlo Simulation (MCS) combining normal distribution. Obtain the maximum probability of occ urrence of sediment loads and depth in the detention pond. Approach: Modified Universal Soil Loss Equation (MUSLE) and Trap Efficiency (TE) Method was applied to predict sediment accumulation. This uncertainty of sediment loads and depth was carried out using Monte Carlo Simulation (MCS) Method. The water samples were collected for suspended solids data and other water quality parameters at Ledang Heights, Nusajaya, Johor and University Technology Malaysia (UTM), Johor. Sampling station were randomly selected at the inlet and outlet of the detention pond. The hydrological parameters such as flow and velocity were also collected. Results: The simulation results showed the maximum probability of occurrence value for observed sediment loads and sediment dept h from Ledang Heights were 0.0062 tons (16.5%) and 0.0005 mm (17.5%) respectively. The maximum probability of occurrence values for observed sediment loads and sediment depth at UTM showed no obvious differences with Ledang Heights; about 0.015 tons (16.8%) and 0.00037 mm (15.5%) respectively. The maximum occurrence of predicted sediment loads and sediment depth usin g MUSLE method for Ledang Height was 77.8 tons (16.8%) and 7.5 mm (26.8%) respectively. The maximum occurrence for UTM was slightly higher, about 264 tons (15.70%) and 7.0 mm (21.10%) respectively. The higher values for UTM were suspected due to its larger watershed. The sediment loads and depths were also predicted for the next 50-100 years considering no significant watershed l and use changes. Conclusion: The sediment accumulation estimation and forecasting are very important to ensure the effectiveness and proper operation of the detention pond. The continuous eff ort through natural sediment control measures such as proper vegetation and grass inplants are always encourage around the detention pond and surrounding areas throughout its lifespan.

Analyzing the Changes of Soil Erodibility Index (K) in the Soils of Arid Regions and the Effective Factors in Central Iran (Case Study: Yazd-Ardakan Plain)

One of the main factors of water erosion is the natural characteristics of the soil called ordetachability. The present study aims to analyze the variations of soil erodibility factor in different plains and thefactors related to it. Erodibility is one the key factors in some models of erosion and sediment such as Universal SoilLoss Equation (USLE), Revised USLE (RUSLE), and Modified USLE (MUSLE) and is a function of grain sizedistribution, organic matter, structure and infiltration. To this end, the index of soil erodibility was measured throughfield surveys in 37 spots in the faces of bare pediment, coalescing pediment, and concealed pediment plains usingWischmeier and Smith (1987) method. The infiltration of soil profile and the percentage of desert pavement in thefield were measured as well. Soil grain size distribution, percentage of organic matter, soil structure, gravelvolumetric content, lime, salinity, acidity, and sodium absorption rate were also measured in the laboratory. Thestatistical analysis indicated positive correlations of erodibility with silt, very fine sand (VFS), and negativecorrelation of this factor with gravel, sand, infiltration, organic matter, and lime. The results from Analysis ofVariance (ANOVA) test also indicated that three factors of salinity, acidity, and sodium absorption rate are notsignificantly different in bare pediment, coalescing pediment, and concealed pediment plains. The results suggestedthat in natural conditions of soil surface, desert pavement plays its protective role and land use change throughmixing the soil would thwart effect of the pavement. So, the erodibility of the soil in manipulated and mixedconditions increases up to 10 times.

Soil loss estimation through MUSLE using Kirpich and Williams times of concentration using RS and GIS techniques: a case study

Water is one of the most vital requirements for sustenance of life. Water, along with soil, is the most essential natural resource for economic and social development. A study of soil and water dynamics at a watershed level can facilitate a scientific approach toward their conservation and management. The present study is an attempt to apply the Modified Universal Soil Loss Equation (MUSLE) along with the Soil Conservation Service Curve Number (SCS-CN) method for runoff estimation and comparison of soil loss estimates for the catchments of Baindur Hole and Yedamavina Hole in the Udupi District of Karnataka State, India, obtained by times of concentration calculated by the Kirpich equation and the Williams equation. The base map and thematic maps were prepared using Indian Remote Sensing satellite 1C (IRS-1C) LISS-III (Linear Imaging Self-Scanning Sensor) image for land use/land cover and from Survey of India topo sheet in a GIS environment for overlaying and extraction of results. The time of concentration estimated by the Kirpich formula is lower in all cases; hence, the corresponding soil loss is 1.4 times higher than that determined with Williams formula. Catchments 23 and 17 with a lower drainage length show comparatively higher values of soil loss in case of the Williams equation, which can be attributed to the greater importance of drainage length in the equation.

Prediction of storm-related sediment-associated contaminant loads in a watershed scale

Abstract Suspended sediment moving in watersheds provides a pathway for the transport of sediment-associated contaminants. Information about sediment and nutrients exported from catchments as well as related erosive processes are required by catchment managers and decision-makers. Due to lack of adequate data in this respect, the Modified Universal Soil Loss Equation (MUSLE) model has been applied in storm-related sediment yield predictions in the Kojour watershed, Iran, to estimate the phosphorus (P) and organic matter (OM) loads associated with storm-related sediments The results of this study showed that a calibrated MUSLE model could estimate storm-related OM and P losses in the study area within an acceptable estimation error (RE) of 33% and 23%, respectively.

Simulation of Soil and Water Loss in the Upper Huaihe River Basin using the Xinanjiang Model

The Xinanjiang model is coupled with the Modified Universal Soil Loss Equation to simulate the soil and water loss in the upper Huaihe River. The outputs show that xinanjiang model can simulate runoff and sediment well, and the total runoff was generally less than 10% for both model calibration and validation with the Nash-Sutcliffe efficiency larger than 0.78 respectively. The computed sediment graphs were in good agreement with the observed ones, i.e. the relative errors of the computed total sediment yield was generally less than 20% for both model calibration and validation with the Nash-Sutcliffe efficiency larger than 0.62 respectively.

Analyzing variation of sediment yields in wet and drought years

This study presents meteorological and hydrologic drought effects on sediment yield in a small rural basin, Uğrak Watershed in Tokat Region of North Central Anatolia, Turkey. Sediment yield was estimated by using Modified Universal Soil Loss Equation (MUSLE) model for 25 years period. The maximum and minimum sediment yields were estimated in 1980 and 1997 respectively. Historical precipitation and flow data were analyzed to determine meteorological and hydrological drought by Standardized Precipitation Index (SPI) method. Results showed thatthere was 10-year drought vs. 15-year wet for meteorological and 14-year drought vs. 11-year wet for hydrological conditions. In the meteorologically drought and wet years, the sediment yields were estimated as 6920.7 tons and 18068.2 tons, respectively. In the hydrological dry and wet years, the sediment yields were estimated as 7417.8 tons and 21489.2 tons, respectively. Sediment yields were found similar in meteorological and hydrological wet and also similar in meteorological and hydrological dry conditions. Drought reduced the sediment yield in the study area.

MUSLE Evaluation of Soil Loss on a Construction Site by Using Gauging Weirs

During urbanization, large areas of soil are exposed to the risk of soil erosion due to extensive earthworks and construction activities. Runoff from construction sites is known by far the largest source of sediment clogging our waterways. Erosion occurred from the study area due to removal of vegetation, high rainfall intensity, alteration of existing topography, and the covering of previously vegetated surfaces with impervious cover such as roads, driveways and buildings. The main objective of this study is to evaluate the soil loss due to storm rainfall and runoff on a construction site located at Sungai Ara, Penang State of Malaysia. A purpose-built hydraulic structure namely Sharp Crested Rectangular Weir was constructed and installed on site for more reliable estimates of flow during storms. The soil loss was then evaluated by using an empirical modeling known as the Modified Universal Soil Loss Equation (MUSLE). Results showed that large amount of sediment has being eroded from the study area during these activities. The highest soil loss rate was estimated was 64 ton/ha during a storm event.

MUSLE Evaluation of Soil Loss on a Construction Site by Using Gauging Weirs

During urbanization, large areas of soil are exposed to the risk of soil erosion due to extensive earthworks and construction activities. Runoff from construction sites is known by far the largest source of sediment clogging our waterways. Erosion occurred from the study area due to removal of vegetation, high rainfall intensity, alteration of existing topography, and the covering of previously vegetated surfaces with impervious cover such as roads, driveways and buildings. The main objective of this study is to evaluate the soil loss due to storm rainfall and runoff on a construction site located at Sungai Ara, Penang State of Malaysia. A purpose-built hydraulic structure namely Sharp Crested Rectangular Weir was constructed and installed on site for more reliable estimates of flow during storms. The soil loss was then evaluated by using an empirical modeling known as the Modified Universal Soil Loss Equation (MUSLE). Results showed that large amount of sediment has being eroded from the study area during these activities. The highest soil loss rate was estimated was 64 ton/ha during a storm event.