Assessment Of Sediment Yield Research Articles

Assessment of sediment yield and accumulation in reservoir: The case of Gibe One Reservoir, Southwestern Ethiopia

Soil erosion and sediment buildup are the factors that speed up the decline in capacity and function of reservoirs, agricultural products, and water resources. In order to simulate sediment and runoff and map high sediment-yielding sub-basins in the Gibe Gojeb catchment in southwest Ethiopia, this study used the Soil and Water Assessment Tool (SWAT) model. Using data on sediment and river flow, calibration and validation were carried out. Between 2003 and 2016, the catchment produced an average annual sediment loading of 62.5 tons ha−1 yr−1, with loading fluctuations ranging from 0.2 to 108.4 tons ha−1 yr−1. The acceptable sediment yield threshold value ranges from 12.3 to 108.4 tons ha−1 yr−1 for 56 sub-basins, and from 0.2 to 10 tons ha−1 yr−1 for 5 sub-basins. The most significant sub-basins with very high to extremely severe sediment yields were sub-basins 1 to 30, 32 to 44, 47, 48, 50, 51, and 53 to 61. After thirteen years of operation, the yearly amount of 58,802 tons of sediment transferred from the catchment and deposited into Gibe One reservoir has decreased the capacity by 5.7 %. The accumulation of sediment in a reservoir has an impact on its functionality, power production, and capacity, affecting the safety of dams and the environment. The study's findings enhanced our comprehension of sediment accumulation in reservoirs and furnished us with the necessary information regarding reservoir safety, integrated soil, and water management.

Assessment of sediment yield and surface runoff using the SWAT hydrological model: a case study of the Khazir River basin, northern Iraq

Assessment of sediment yield and surface runoff using the SWAT hydrological model: a case study of the Khazir River basin, northern Iraq

Sediment yield assessment and suggesting mitigation measures—A case study of Deme watershed, Omo‐Gibe Basin, Ethiopia

AbstractSoil erosion is a big challenge of natural resource development in Ethiopia due to the high expansion of agricultural activity and poor land‐use management. Deme watershed is one of the watersheds found in the Omo‐Gibe Basin, Ethiopia with soil erosion problems. It covers 1284.4 km2. The Soil and Water Assessment Tool (SWAT) integrated with ArcGIS was used to assess the sediment yield of the Deme watershed and develop mitigation measures for soil erosion. The purpose of this study was to assess the sediment yield and provide mitigation measures for the Deme watershed. Ground Control Point (GCP) data collection and field observation were conducted for land‐use land cover classification. The performance of the model was evaluated by coefficient of determination (R2), Nash Sutcliffe simulation efficiency (NSE), and percent bias (PBIAS). SWAT adequately reproduced the observed daily flows and sediment loads temporal evolution with R2 and NSE ≥ .7 and PBIAS < 15% both for the calibration and validation periods. The sediment‐rating curve measured an annual average suspended sediment yield of 12.79 tons per hectare per year, whereas the SWAT model predicted an annual average sediment yield of 14.35 tons per hectare per year. The spatial distribution map of sediment showed that 9 out of 17 sub‐watersheds generate a higher amount of sediment yield (15.1–45 tons/h/year) and are found to be erosion‐prone areas. For proper management of watershed terracing, filter strips, contouring, and reforestation scenarios were developed. Each scenario reduces the sediment yield by 74.29%, 58.34%, 47.78%, and 69.76%, respectively. The proper combination of these scenarios resulted in a 90% reduction in sediment yield. Policymakers and land‐use planners of different organization will benefit from this research by implementing soil and water conservation mechanisms and practices that strengthen and mitigate the natural systems of Deme watershed.

RECONSTRUCTION OF SEDIMENT RUNOFF FORMATION FEATURES IN THE LAKE KHORLAKEL (NORTH CAUCASUS) CATCHMENT FOR THE LAST 8 THOUSAND YEARS (ACCORDING TO GEOMORPHOLOGICAL AND LITHOSTRATIGRAPHIC DATA)<a href="#FN2"><sup>2</sup></a>

The change in sediment yield is an important indicator of the natural environment dynamics, depending on the combination of landscape, tectonic and climatic conditions. Assessment of sediment yield often based on the results of studying the bottom sediments of mountain lakes with relatively compact catchments. However, for correct reconstructions, in addition to analyzing lake sediments, it is necessary to study the causes and mechanizm of sediment redistribution in their catchments, to identify sediment delivery pathways to the reservoir and their possible changes over different time windows. The drainless Lake Khorlakel, located at the altitude of 2045.0 m above sea level on the northern macroslope of the Greater Caucasus. It is a suitable testing ground for complex research: on the one hand, the relict reservoir is an ideal sedimentation trap, and on the other, it is located with in an area of intensive exogenous processes and tectonic activity. The two boreholes were drilled in 2017 in the deepest (≈8 m) part of the lake and 17 samples collected taken from the cores for radiocarbon dating, which made it possible to build an age model for the range from 8000 to 500 yr. BP. Complex geological and geomorphological studies were carried out in 2021 to interpret the obtained data. It was found that sedimentation in the lake is associated with runoff and sediment redistribution in the Elbashi creek catchment. A number of episodes of proluvial activation with the formation of an outflow cone, followed by lake accumulation, have been traced for the last 8 kyr. The connection between lake and catchment ceased only in the last 1 kyr. BP. Two main stages of lake sedimentation with a boundary of 3 kyr. BP and 10 episodes, that are characterized by different proportions of mineral and organic components in bottom sediments were established. Some of the lithostratigraphic boundaries correlate with strong earthquakes that occurred in the Elbrus region, and some – with climatic events.

Assessment of sediment yield and deposition in a dry reservoir using field observations, RUSLE and remote sensing: Wadi Assarin, Oman

Soil erosion, sediment yield, and sediment transport associated with flash flooding in arid regions result in reservoir storage losses, decreased infiltration, high evaporation rates, and degradation of downstream channels. However, the lack of observational data from wadi systems and an empirical formula to compute sediment yield has hindered reservoir trapping evaluation, maintenance, and management. Therefore, this research aimed to estimate the annual soil loss in the upstream catchment area of a reservoir based on the Revised Universal Soil Loss Equation (RUSLE) with a remote sensing dataset. The sediment trapped in the Assarin Dam reservoir in Oman was estimated by coupling unmanned aerial vehicle (UAV) surveys with photogrammetry analysis to assess the reservoir siltation. Among the previous sediment trapping events, seven sets of field observation data were collected to investigate the relationship between soil loss at the catchment scale and sediment deposition volumes in the reservoir. The RUSLE method was applied to estimate soil erosion using independent factors such as rainfall erosivity, soil erodibility, topography, cover management and conservation practices. A remote sensing dataset and geographic information system (GIS) environments were used to analyse the quantitative and spatial distribution of the RUSLE parameters. Two drone surveys were conducted over the reservoir before and after a flash flood. The trapped sediment volume was estimated to be approximately 9,075 m3 (11,343 ton) per event, representing approximately 1.26 % of the total reservoir capacity. This computed volume was validated using measurements from monitored sediment scale bars sited throughout the Assarin Dam reservoir, yielding an accuracy of 79 %. From the RUSLE results, the annual soil erosion was estimated to be 196,599 ton/ha yr−1, of which approximately 5.8 % was trapped in the reservoir. Spatial-temporal variability in the rainfall patterns and the corresponding runoff discharges led to high sediment delivery at the outlet of the basin. After analysing available data from previous field surveys in Oman, a new formula for estimating the sediment yield in Wadi Assarin was developed. The results of this research, which represent the first of their type in the Middle East and North Africa (MENA) region, can support reservoir management practices and show that UAV-based photogrammetry is suitable for measuring trapped sediment volumes.

Soil erosion risk and sediment yield assessment with Revised Universal Soil Loss Equation and GIS: The case of Nesha watershed, Southwestern Ethiopia

This research was administered to spatially predict the soil loss rate of the kaffa zone using a model estimate and GIS. Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions was accustomed estimate potential soil losses by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using DSMW soil map, vegetation cover (C) using spot6 images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P) using DEM and satellite images. supported the analysis, the mean and total annual soil loss potential of the study area was 30 tons ha-1 year-1 and 36,264.5tons ha-1 year-1, respectively. The results also showed that about 2.89, 8.02, 15.31 and 73.78% of the study area were classified as slight, moderate, high, and very high with values ranging from 0 to 15,15 to50,50 to 200, and >200 tons ha-1 year-1, respectively. The study demonstrates that the RUSLE using GIS and RS provides a great advantage to spatially analyzing multi-layer of knowledge. The expected amount of soil loss and its spatial distribution could facilitate sustainable land use and management.

Sediment Yield Assessment, Prioritization and Control Practices in Chambal River Basin Employing SYI Model

Abstract Sediment yield is the result of all sediment production and transport processes. Recent technological developments and increasing availability of global environmental datasets, including earth observation data, provide an opportunity to systematically examine the relationship between sediment yield and controlling catchment variables by employing geographic information system (GIS). The Sediment yield index (SYI) method is employed using soil texture, topography, rainfall erosivity, geomorphology and landuse-landcover parameters to compute the spatial distribution of sediment yield rate and plan soil conservation and prioritize watershed in the Chambal river basin. The model does not provide absolute sediment yield value and can be only used for qualitative purposes. The present study estimated the sediment yield rate between 560-2625 ton/ha/yr with an average value of 1608.89 ton/ ha/yr and severe, very high, high, moderate, and low priority zones. The priority levels are determined based on average sediment yield values and conservation approaches are proposed for all the catchments.

Rainfall Induced Soil Erosion and Sediment Yield Assessment in Upper Brahmaputra River Basin

Abstract Riverbank erosion, aggradation, and river bed degradation are significant threats to most Indian watersheds. A quantitative valuation of the spatial distribution of soil erosion at a watershed level is vital for sustainable watershed planning and management practice. Very few studies can be found that focus on soil loss with sediment yield patterns in the upper Brahmaputra river basin due to massive erosion-deposition processes. Therefore, it is intended to study the soil loss and sediment yield pattern in the upper Brahmaputra river basin at the selected outlet of Majuli Island, located in South Asia. The principal objective is to evaluate soil erosion and sediment yield transported downstream of Majuli Island using the revised universal soil loss equation (RUSLE) and sediment delivery ratio (SDR) models, respectively, for 1979-2014. The study is conducted based on data availability and efficient models like RUSLE and SDR to measure soil erosion and sediment yield. Also, sediment yield maps for 36 years are prepared for the whole catchment considering rainfall as a variable. The maximum area contributing to soil erosion is observed around the hilly region having steep slopes. However, the highest sediment deposition is found near Majuli Island. This study would help take preventive measures for the erosion process and watershed management to minimize soil erosion in the watershed.

Assessment of Runoff and Sediment Yield using Routing Model

The assessment of runoff from rainfall and sediment yield is essential for management and conservation of water availability and can also apply for several applications of hydrology. The technique of Sediment routing has been evolve to route the sediment yield from a selected area which was divided into five sub-basins at Anakapalli station. Remote Sensing (RS) and Geographic Information Systems (GIS) technique are used to find the parameters and develop the routing model. The data related to factors of Runoff (R), Soil erodibility (K), Topographic (LS), crop management (C) and conservation practice for development of the model. In order to affirm the overall performance of the routing technique for the take a look at area, the release and sediment yield records from the Anakapalli gauging station has been collected for 28 rainfall days January 2020 to October 2020. locate at the records amassed, to compute the sediment yield from Routing technique. Measured sediment yield from selected point has been validated to the routing sediment yield from the selected basin. The effect of sediment yield has been evaluate herewith of calculated data and it is establish that coefficient of resolve (R2) are 0.96 and Efficiency of Nash Sutcliffe (ENS) of 96.19 for Routing model is performing well for the studied basin, it is effectively used for assessment of sediment yield in the selected place

Soil erosion and sediment yield assessment using RUSLE and GIS based approach in a forest watershed in Kandi region of Punjab

The Revised Universal Soil Loss Equation (RUSLE) integrated with the sediment delivery ratio (SDR) model employed in the GIS environment has been used to quantify the soil erosion and sediment yield for a small reservoir (Takarla dam) located in the Kandi region of Punjab, India. The catchment area of Takarla dam is 72.6 ha. The various layers including rainfall erosivity factor, soil erodibility factor, Slope length and steepness factor and crop management factor were prepared in ArcGIS to estimate the average annual soil loss. The SDR for the dam watershed was obtained by employing different empirical equations. The sedimentation rate and sediments collected in the dam was assessed for the last 20 years. The results of the present study revealed that the average annual soil loss varied from 0 to 12.8 t ha-1 year-1 for Takarla dam. The sediments deposited in the dam over 20 years estimated to be 142603.8 tonnes. The results of the present study may provide an insight for policy makers to design and execute the watershed management practices to reduce erosion hazard and sediment accumulation in the reservoirs.

The Use of Artificial Neural Network and Advanced Statistics to Model Sediment Yield on a Large Scale: Example of Morocco

Morocco ranks among countries with the greatest achievements in the field of dams in Africa but is affected by the sedimentation phenomenon due to soil erosion in upstreams. The assessment of Sediment Yield (SY) and Suspended Sediment Yield (SSY) remains a challenging global issue, especially in Morocco, characterized by a great diversity of morphological, climatic, and vegetation cover. The main objective of this paper was to perform advanced statistics and artificial neural networks (ANN) in order to understand the spatial distribution of sediment yield and the factors most controlling it, including factors of the RUSLE model (Revised Universal Soil Loss Equation). In order to produce a model able to assess SY, we collected and analyzed extensive data of most variables that can be affecting SY using 42 catchments of the biggest and important dams of Morocco. Statistical analysis of the studied watersheds shows that SY is mainly related to the watershed area and the length of the drainage network. On the other hand, the SSY is higher in watersheds where gully erosion is abundant and lower in areas with no soil horizon. The SSY is mainly related to the altitude, aridity index, sand fraction, and drainage network length. In front of the complexity of preserving this phenomenon, the ANN was applied and gave very good satisfactory results in predicting the SSY (NSE=0.93, R2=0.93).

Soil erosion and sediment yield assessment using RUSLE and GIS-based approach in Anjeb watershed, Northwest Ethiopia

Soil erosion is a serious and continuous environmental problem in Ethiopia. Lack of land use planning, environmental protection, over-cultivation, and overgrazing are prominent causes of erosion and sedimentation. This study is conducted in Anjeb watershed located in the Upper Blue Nile Basin, Ethiopia. In this study, the quantity and distribution of soil erosion, sediment delivery ratio (SDR), and sediment yield of the watershed were assessed by employing remote sensing, geographic information system (GIS), and revised universal soil loss equation analysis capabilities. Important data sets of topography, soil, conservations practices, cover management, and rainfall factors were processed and superimposed in GIS analysis, and soil loss rate, SDR, and sediment yield of the watershed were derived. Based on the result found, the watershed was categorized into six classes of erosion: slight (0–5), moderate (5–10), high (10–15), very high (15–30), severe (30–50), and very severe (> 50) t ha−1 yr−1. The estimated average annual soil loss was 17.3 t ha−1 yr−1. The soil loss rate is higher in the steeper and topographically dissected part of the watershed. The average sediment delivery capacity was about 0.122. The result showed that the average sediment yield in the watershed was grouped into classes of low (< 2.5), moderate (2.5–7.5), high (7.5–12.5), very high (12.5–22.5), severe (22.5–40), and very severe (> 40) t ha−1 yr−1. It is found that from a total of 20,125.5 t yr−1 eroded soil over the whole watershed 2254.5 t yr−1 of sediment has been brought and deposited to the channels. Sediment accumulation from the watershed threatens the storage capacity and life span of Anjeb reservoir which is the source of irrigation water downstream. The study provides an insight to planners and resource managers to design and implement practices of watershed management to reduce erosion and enhance land productivity and to minimize the reservoir sediment accumulation.

Soil erosion risk and sediment yield assessment with universal soil loss equation and GIS: in Dijo watershed, Rift valley Basin of Ethiopia

Soil erosion is the main drivers in the world and Ethiopia in particular. This study has been conducted at Dijo watersheds in the Rift valley Basins of Ethiopia to estimate soil erosion rate and identify erosion hotspot areas for proper planning using Geographic Information System and Universal Soil Loss Equation adapted to Ethiopian condition. 64 years mean annual rainfall data for estimating erosivity factor, digital soil map for estimating soil erodibility factor, Digital Elevation Model for estimating topographic (LS) factor, Land use land cover for cover factor detection from Ethiopian ministry of water resources. The result reveals that the soil loss ranges from 0 ton/ha/year in flat slope to 38.09 ton/ha/year from steep slopes. The average soil loss rate is 2.2 tons per hectare per year and has been classified into three erosion severity classes as very low, low and moderate. The result also reveals that most of the watershed erosion severity evaluated under very low and low soil erosion severity classes covering 97.3% of the watershed areas which is due to the effect of mixed plantation of various tree and terraces. However, moderate soil erosion in the upper parts of the watershed could be due to the inherent characteristics of vertisols, lack of vegetation cover and terraces which should be given first priority for conservation interventions. From the gross soil erosion, 43,762 ton/year sediment yields have been estimated at watershed outlet. Policy aim at keeping land productivity will need to focus to reduce low and moderate soil erosion through terracing, inter-cropping, contour farming, strip cropping, conservation tillage, mulching and biological stabilizers based on their slope range, soil type and land use type. The current finding on erosion was evaluated based on the past 10 years land use land cover scenario; therefore, soil erosion might be reduced if the current land use land cover scenario considered. Finally, the integration of USLE and GIS is an effective tool in mapping the spatial distribution of soil erosion from the entire watershed. The moderate and low soil erosion severity areas should be managed through terracing, inter-cropping, contour farming, strip cropping, conservation tillage, mulching and biological stabilizers based on their slope range, soil type and land use type. Free grazing and cultivation of steep slope(Northern parts) contributed for moderate soil erosion in the watershed should be managed by cut–carry system, limiting the number of cattle units to be grazed in the specific plot of land and leaving the marginal steep slope areas with no ground covers for natural regeneration. Finally, the current finding on erosion was evaluated based on the past 10-year land use land cover scenario. Therefore, the soil erosion could be reduced if the current land use land cover scenario is considered.

Modeling the suspended sediment yield in Lesotho rivers

The present work was carried out in the framework of the Lesotho-Italy cooperation project “Renewable Energy Maps for Lesotho,” launched in 2016, with the main purpose to produce a series of maps aimed to support the Government of Lesotho in planning and expanding the exploitation of renewable energy sources (wind, solar and hydro). A multiple regression model specifically developed for sediment yield assessment in Lesotho catchments is here presented with a view to contributing to the follow-up of development projects in the field of hydroelectric energy. The “Lesotho model,” based on observations at 16 gauging stations, takes into account the proportions of agricultural and sedimentary bedrock areas as explanatory variables. Statistical reliability tests proved the model robustness after previous models, developed at continental or sub-continental scale, revealed to be ineffective or hardly applicable. A map of simulated sediment yields at sub-catchment level is provided, as an example of model application.

Assessing sediment yield and sources using fingerprinting method in a representative catchment of the Loess Plateau, China

Quantitative assessment of sediment yield and sources is of great importance for future soil and water conservation and watershed management in erosion-prone areas. This study investigated sediment yield and sources by using a simple fingerprinting method in a dam-controlled watershed on the northern Loess Plateau. The sampling sediment profile exhibited 24 flood couplets corresponding to rainfall storms from 2001 to 2014. A total of 2.05 × 105 t sediment was trapped during the period. The annual sediment yield varied from 0 to 430 t ha−1 year−1, with an average annual sediment yield of 146.1 t ha−1 year−1. Ten sediment properties (i.e., σ13C, σ15N, TOC, TN, C/N, Xlf, Xhf, Xfd, 137Cs, 210Pb) were potentially selected to identify the sediment sources. The multivariate discriminant function analysis (DFA) test suggested that three soil properties (Χhf, TN, and 137Cs) comprised the optimum composite fingerprinting. The results demonstrated that sandstone contributed nearly 90% of sediment in 2012 and 56.1% in 2003. The contribution from arable land varied from 5.2% in 2005 to 44.6% within the period of 2013–2014. On average, approximately 74.06% of sediment originated from the weathered sandstone, followed by 15.67% from arable land, and the remaining 10.27% from uncultivated land. Our finding indicated that bare sandstone was the main sediment source, leading to relatively high sediment yield in the study area. This study provides a method with great potential for sediment yields assessment and sediment source identification in ungauged watersheds on the Loess Plateau.

Sediment Yield Estimation Using RS and GIS for Upper Karha Watershed Maharashtra India

Soil erosion and water conservation are major concerns arising from agricultural acceleration, changing land patterns and uncertain rainfall pattern. Soil erosion within watersheds results in increasing the deposition of sedimentation in the water bodies and thus dropping their carrying capacity and life span. Soil erosion studies are crucial for watershed design and management. The objective of current investigation is to quantify sediment yield of Upper Karha watershed of Pune district, Maharashtra, India, which is a semi-arid zone and rain-shadow region. In the present study, the sediment yield assessment by USLE model and RUSLE model is performed with the help of remote sensing and geographical information system. The average annual sediment yield is observed, i.e. 4.54 tonne/acre/year and 4.14 tonne/acre/year by USLE and RUSLE models, respectively. To address the current issue of sedimentation, suitable sites and suitable types of structures were suggested for soil and water conservation.

Assessment of sediment yield in Thailand using revised universal soil loss equation and geographic information system techniques

AbstractSoil is one of the most important natural resources on Earth. Information on soil loss is important to support agricultural productivity and natural resource management. Therefore, this research aimed to estimate and map mean annual soil erosion and sediment deposition using a geographic information system (GIS). The soil loss in each grid cell was analysed by the revised universal soil loss equation (RUSLE) model. The parameters of the RUSLE including rainfall, soil type, and land use were calculated in each grid cell from a digital elevation model with of 1‐km2 resolution. Furthermore, sediment deposition was derived from the RUSLE model and used in GIS software to generate soil loss capacity maps. The results show that soil erosion occurred over all parts of Thailand, especially in the northern and southern parts due to the topography, geology, and land cover. The sediment was deposited in grid cells where the elevation was low, primarily near rivers. The results of this research support local land development policies that are implemented to control sediment yields during development.

Estimating the sediment trap efficiency of intermittently dry reservoirs: lessons from the Kruger National Park, South Africa

AbstractThe assessment of sediment yield from reservoir siltation requires knowledge of the reservoir's sediment trap efficiency (TE). Widely used approaches for the estimation of the long‐term mean TE rely on the ratio of the reservoir's storage capacity (C) to its catchment size (A) or mean annual inflow (I). These approaches have been developed from a limited number of reservoirs (N ≤ 40), most of them located in temperate climate regions. Their general applicability to reservoirs receiving highly variable runoff such as in semi‐arid areas has been questioned. Here, we examine the effect of ephemeral inflow on the TE of 10 small (≤ 280 × 103 m3), intermittently dry reservoirs located in the Kruger National Park. Fieldwork was conducted to determine the storage capacity of the reservoir basins. The frequency and magnitude of spillage events was simulated with the daily time step Pitman rainfall–runoff model. Different runoff scenarios were established to cope with uncertainties arising from the lack of runoff records and imperfect input data. Scenarios for the relationship between water and sediment discharge were created based on sediment rating curves. Taking into account uncertainties in hydrological modelling, uncertainties of mean TE estimates, calculated from all scenarios (N = 9), are moderate, ranging from ±6 to ±11% at the 95% confidence level. By comparison, estimating TE from the storage capacity to catchment area (C/A) ratio induces high uncertainty (ranges of 35 to 65%), but this uncertainty can be confined (15 to 33%) when the latter approach is combined with hydrological modelling. Established methods relying on the storage capacity to mean annual inflow (C/I) ratio most probably lead to an overestimation of the TE for the investigated reservoirs. The approach presented here may be used instead to estimate the TE of small, intermittently dry reservoirs in semi‐arid climate regions. Copyright © 2017 John Wiley &amp; Sons, Ltd.

Assessment of Sediment Yield according to Observed Dataset

Assessment of Sediment Yield according to Observed Dataset

Assessment of sediment yield using RS and GIS at two sub-basins of Dez Watershed, Iran

Soil erosion is a serious threat to soil and water resources in semi-arid regions. Modified Pacific South-west Inter Agency Committee (MPSIAC) and Erosion Potential Method (EPM), as two well-known models, have shown their performance in many case studies. The goal of present study is to assess the efficiency of these methods for estimating the sediments yield and erosion intensity within short-term and long-term timeframes over two sub-basins of Dez watershed, west of Iran. The results showed that the study area can be categorized into slight, moderate, high and very high erosion zones. Almost half of the study area is highly susceptible to erosion due to the geological formations and land cover. Moreover, the long-term (i.e. 30 years) sediment yield of 387 and 615 (kton)y−1 estimated by MPSIAC and EPM models demonstrated the superiority of EPM. Compared to the measured value of 612 (kton)y−1, the performance of EPM was astonishing. By splitting the dataset into six periods of five years, the sediment yield was predicted in short-term periods by both aforementioned methods. Such segmentation provides the opportunity to evaluate the impact of extreme flooding events on the models performances. The results showed that both models failed in estimation of sediment load during flood conditions. Nevertheless, the correlation coefficients for estimating the sediment yield were found to be R=0.93 and R=0.85 for EPM and MPSIAC models respectively, for short-term simulations.