scholarly journals Storm-wise sediment yield prediction using hillslope erosion model in semi-arid abundant lands

2013 ◽  
Vol 8 (No. 1) ◽  
pp. 42-48 ◽  
Author(s):  
S. Fazli ◽  
H. Noor
Keyword(s):  
Soil Erosion ◽  
Sediment Yield ◽  
Land Surface ◽  
Soil Conservation ◽  
Soil Erodibility ◽  
Storm Events ◽  
Erosion Model ◽  
Sediment Yields ◽  
Slope Steepness ◽  
Erosion Models

Evaluation of soil erosion by existing models is needed as an important tool for managerial purposes in designation of proper water and soil conservation techniques. The present study aimed to assess the applicability of hillslope erosion model (HEM) as one of the newest erosion models for prediction of storm-wise sediment yield in Khosbijan rangeland with 20% slope steepness by using soil erosion standard plots. In order to run the model, runoff depth, land surface cover, soil texture, slope steepness and length were determined for 16 storm events. The results showed that the uncalibrated HEM did not simulate the observed sediment yields properly. Calibration of soil erodibility parameter and developing regression between observed and estimated data indicated that the model was capable of predicting sediment yield in plots by applying soil erodibility parameter of 0.15 with determination coefficient of 0.64 and estimate error of 40%. 

Application of a physically based soil erosion model, GUEST, in the absence of data on runoff rates I. Theory and methodology

Soil Research ◽  
1999 ◽  
Vol 37 (1) ◽  
pp. 1 ◽  
Author(s):  
B. Yu ◽  
C. W. Rose
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Soil Erodibility ◽  
Erosion Model ◽  
Erosion Models ◽  
Loss Data ◽  
Physically Based ◽  
Set Up ◽  
Data Requirements

When physically based erosion models such as GUEST are used to determine soil erodibility parameters or to predict the rate of soil loss, data on runoff rates, as distinct from event runoff amount, are often needed. Data on runoff rates, however, are not widely available. This paper describes methods that can be used to overcome this lack of data on runoff rates. These methods require only rainfall rates and runoff amounts, which are usually available for sites set up primarily to test and validate the USLE technology. In addition, the paper summarises the data requirements for the erosion model GUEST and application procedures. In the accompanying paper, these methods are applied to 4 experimental sites in the ASIALAND Network.

scholarly journals Prioritization of Sub-Watersheds to Sediment Yield and Evaluation of Best Management Practices in Highland Ethiopia, Finchaa Catchment

Land ◽  
2021 ◽  
Vol 10 (6) ◽  
pp. 650
Author(s):  
Wakjira Takala Dibaba ◽  
Tamene Adugna Demissie ◽  
Konrad Miegel
Keyword(s):  
Soil Erosion ◽  
Best Management Practices ◽  
Sediment Yield ◽  
Soil Loss ◽  
Crop Production ◽  
Management Practices ◽  
Assessment Tool ◽  
Swat Model ◽  
Sediment Yields ◽  
Soil And Water

Excessive soil loss and sediment yield in the highlands of Ethiopia are the primary factors that accelerate the decline of land productivity, water resources, operation and function of existing water infrastructure, as well as soil and water management practices. This study was conducted at Finchaa catchment in the Upper Blue Nile basin of Ethiopia to estimate the rate of soil erosion and sediment loss and prioritize the most sensitive sub-watersheds using the Soil and Water Assessment Tool (SWAT) model. The SWAT model was calibrated and validated using the observed streamflow and sediment data. The average annual sediment yield (SY) in Finchaa catchment for the period 1990–2015 was 36.47 ton ha−1 yr−1 with the annual yield varying from negligible to about 107.2 ton ha−1 yr−1. Five sub-basins which account for about 24.83% of the area were predicted to suffer severely from soil erosion risks, with SY in excess of 50 ton ha−1 yr−1. Only 15.05% of the area within the tolerable rate of loss (below 11 ton ha−1yr−1) was considered as the least prioritized areas for maintenance of crop production. Despite the reasonable reduction of sediment yields by the management scenarios, the reduction by contour farming, slope terracing, zero free grazing and reforestation were still above the tolerable soil loss. Vegetative contour strips and soil bund were significant in reducing SY below the tolerable soil loss, which is equivalent to 63.9% and 64.8% reduction, respectively. In general, effective and sustainable soil erosion management requires not only prioritizations of the erosion hotspots but also prioritizations of the most effective management practices. We believe that the results provided new and updated insights that enable a proactive approach to preserve the soil and reduce land degradation risks that could allow resource regeneration.

scholarly journals Assessing the large-scale impacts of environmental change using a coupled hydrology and soil erosion model

2018 ◽  
Vol 6 (3) ◽  
pp. 687-703 ◽  
Author(s):  
Joris P. C. Eekhout ◽  
Wilco Terink ◽  
Joris de Vente
Keyword(s):  
Soil Erosion ◽  
Environmental Change ◽  
Sediment Yield ◽  
Large Scale ◽  
Catchment Scale ◽  
Time Step ◽  
Vegetation Development ◽  
Erosion Model ◽  
Complete Representation ◽  
Large Catchment

Abstract. Assessing the impacts of environmental change on soil erosion and sediment yield at the large catchment scale remains one of the main challenges in soil erosion modelling studies. Here, we present a process-based soil erosion model, based on the integration of the Morgan–Morgan–Finney erosion model in a daily based hydrological model. The model overcomes many of the limitations of previous large-scale soil erosion models, as it includes a more complete representation of crucial processes like surface runoff generation, dynamic vegetation development, and sediment deposition, and runs at the catchment scale with a daily time step. This makes the model especially suited for the evaluation of the impacts of environmental change on soil erosion and sediment yield at regional scales and over decadal periods. The model was successfully applied in a large catchment in southeastern Spain. We demonstrate the model's capacity to perform impact assessments of environmental change scenarios, specifically simulating the scenario impacts of intra- and inter-annual variations in climate, land management, and vegetation development on soil erosion and sediment yield.

Approaches to modelling land erodibility by wind

2009 ◽  
Vol 33 (5) ◽  
pp. 587-613 ◽  
Author(s):  
Nicholas P. Webb ◽  
Hamish A. McGowan
Keyword(s):  
Spatial Data ◽  
Land Surface ◽  
Wind Erosion ◽  
Model Development ◽  
Soil Erodibility ◽  
Roughness Effects ◽  
Research Attention ◽  
Spatial And Temporal Scales ◽  
Erosion Models ◽  
Erosion Modelling

Land susceptibility to wind erosion is governed by complex multiscale interactions between soil erodibility and non-erodible roughness elements populating the land surface. Numerous wind erosion modelling systems have been developed to quantify soil loss and dust emissions at the field, regional and global scales. All of these models require some component that defines the susceptibility of the land surface to erosion, ie, land erodibility. The approaches taken to characterizing land erodibility have advanced through time, following developments in empirical and process-based research into erosion mechanics, and the growing availability of moderate to high-resolution spatial data that can be used as model inputs. Most importantly, the performance of individual models is highly dependent on the means by which soil erodibility and surface roughness effects are represented in their land erodibility characterizations. This paper presents a systematic review of a selection of wind erosion models developed over the last 50 years. The review evaluates how land erodibility has been modelled at different spatial and temporal scales, and in doing this the paper identifies concepts behind parameterizations of land erodibility, trends in model development, and recent progress in the representation of soil, vegetation and land management effects on the susceptibility of landscapes to wind erosion. The paper provides a synthesis of the capabilities of the models in assessing dynamic patterns of land erodibility change, and concludes by identifying key areas that require research attention to enhance our capacity to achieve this task.

scholarly journals Sediment Yield in Dam-Controlled Watersheds in the Pisha Sandstone Region on the Northern Loess Plateau, China

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1264
Author(s):  
Fabing Xie ◽  
Guangju Zhao ◽  
Xingmin Mu ◽  
Peng Tian ◽  
Peng Gao ◽  
...  
Keyword(s):  
Soil Erosion ◽  
Loess Plateau ◽  
Sediment Yield ◽  
Water Conservation ◽  
The Loess Plateau ◽  
Sediment Yields ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Check Dams ◽  
Loss Control

Soil erosion has become the dominant environmental issue endangering sustainable development in agriculture and the ecosystem on the Loess Plateau. Determination of watershed soil erosion rates and sediment yields is essential for reasonable utilization of water resources and soil loss control. In this study, we employed unmanned aerial vehicles (UAVs) and structure-from-motion (SfM) photogrammetry to determine the sediment yields in 24 dam-controlled watersheds in the Pisha sandstone region of the northern Loess Plateau. High differences in total sediment were trapped before the check dams due to their running periods and sediment yields. The estimated specific sediment yield ranged from 34.32 t/(ha∙a) to 123.80 t/(ha∙a) with an average of 63.55 t/(ha∙a), which indicated that the Pisha sandstone region had an intense soil erosion rate. Furthermore, the modified Sediment Distributed Delivery (SEDD) model was applied to identify the erosion-prone areas in the watersheds, and the sediment retained in the check dams were used for model calibration. The performance of the model was acceptable, and the modeling results indicated that the steep Pisha sandstone was the major sediment source for the watersheds, accounting for approximately 87.37% of the sediment yield. Catchment area, erosive precipitation, and badland proportion were the key factors for sediment yield in the dam-controlled watersheds of the Pisha sandstone region, according to multiple regression analyses. These findings indicated that the modified SEDD model is very efficient in identifying spatial heterogeneities of sediment yield in the watershed but requires comprehensive calibration and validation with long-term observations. The Pisha sandstone region is still the key area of soil erosion control in the Loess Plateau, which needs more attention for soil and water conservation due to high sediment yield.

scholarly journals A New Indicator to Better Represent the Impact of Landscape Pattern Change on Basin Soil Erosion and Sediment Yield in the Upper Reach of Ganjiang, China

Land ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 990
Author(s):  
Yongfen Zhang ◽  
Nong Wang ◽  
Chongjun Tang ◽  
Shiqiang Zhang ◽  
Yuejun Song ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
River Basin ◽  
Landscape Metrics ◽  
Landscape Pattern ◽  
Sediment Yield ◽  
River Basins ◽  
Landscape Patterns ◽  
Soil Erodibility ◽  
Land Use Pattern

Landscape patterns are a result of the combined action of natural and social factors. Quantifying the relationships between landscape pattern changes, soil erosion, and sediment yield in river basins can provide regulators with a foundation for decision-making. Many studies have investigated how land-use changes and the resulting landscape patterns affect soil erosion in river basins. However, studies examining the effects of terrain, rainfall, soil erodibility, and vegetation cover factors on soil erosion and sediment yield from a landscape pattern perspective remain limited. In this paper, the upper Ganjiang Basin was used as the study area, and the amount of soil erosion and the amount of sediment yield in this basin were first simulated using a hydrological model. The simulated values were then validated. On this basis, new landscape metrics were established through the addition of factors from the revised universal soil loss equation to the land-use pattern. Five combinations of landscape metrics were chosen, and the interactions between the landscape metrics in each combination and their effects on soil erosion and sediment yield in the river basin were examined. The results showed that there were highly similar correlations between the area metrics, between the fragmentation metrics, between the spatial structure metrics, and between the evenness metrics across all the combinations, while the correlations between the shape metrics in Combination 1 (only land use in each year) differed notably from those in the other combinations. The new landscape indicator established based on Combination 4, which integrated the land-use pattern and the terrain, soil erodibility, and rainfall erosivity factors, were the most significantly correlated with the soil erosion and sediment yield of the river basin. Finally, partial least-squares regression models for the soil erosion and sediment yield of the river basin were established based on the five landscape metrics with the highest variable importance in projection scores selected from Combination 4. The results of this study provide a simple approach for quantitatively assessing soil erosion in other river basins for which detailed observation data are lacking.

scholarly journals Climate Change Impacts on Soil Erosion and Sediment Yield in a Watershed

Water ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 2247
Author(s):  
Ching-Nuo Chen ◽  
Samkele S. Tfwala ◽  
Chih-Heng Tsai
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Sediment Yield ◽  
Climate Change Scenario ◽  
Climate Change Impacts ◽  
Change Scenario ◽  
Erosion And Deposition ◽  
Sediment Yields ◽  
Southern Taiwan ◽  
Total Sediment

This study analyzed the influence of climate change on sediment yield variation, sediment transport and erosion deposition distribution at the watershed scale. The study was based on Gaoping River basin, which is among the largest basins in southern Taiwan. To carry out this analysis, the Physiographic Soil Erosion Deposition (PSED) model was utilized. Model results showed a general increase in soil erosion and deposition volume under the A1B-S climate change scenario. The situation is even worsened with increasing return periods. Total erosion volume and total sediment yield in the watershed were increased by 4–25% and 8–65%, respectively, and deposition volumes increased by 2–23%. The study showed how climate change variability would influence the watershed through increased sediment yields, which might even worsen the impacts of natural disasters. It has further illustrated the importance of incorporating climate change into river management projects.

A process-based soil erosion model ensemble to reduce model uncertainty in climate change impact assessments

2021 ◽  
Author(s):  
Joris Eekhout ◽  
Agustín Millares-Valenzuela ◽  
Alberto Martínez-Salvador ◽  
Rafael García-Lorenzo ◽  
Pedro Pérez-Cutillas ◽  
...  
Keyword(s):  
Climate Change ◽  
Soil Erosion ◽  
Model Uncertainty ◽  
Extreme Precipitation ◽  
Climate Change Impact ◽  
Soil Loss ◽  
Model Ensemble ◽  
Erosion Model ◽  
Erosion Models ◽  
Change Impact

<p>The impact of climate change on future soil loss is commonly assessed with soil erosion models, which are potentially an important source of uncertainty. Here we propose a soil erosion model ensemble, with the aim to reduce the model uncertainty in climate change impact assessments. The model ensemble consisted of five continuous process-based soil erosion models that run at a daily time step, i.e. DHSVM, HSPF, INCA, MMF and SHETRAN. All models simulate detachment by raindrop impact (interrill erosion), detachment by runoff (rill erosion) and immediate deposition of sediment within the cell of its origin. The models were implemented in the SPHY hydrological model. The soil erosion model ensemble was applied in a semi-arid catchment in the southeast of Spain. We applied three future climate scenarios based on global mean temperature rise (+1.5, +2 and +3 ºC). Data from two contrasting regional climate models were used to assess how an increase and a decrease in extreme precipitation affect model uncertainty. Soil loss is projected to increase and decrease under climate change, mostly reflecting the change in extreme precipitation. Model uncertainty is found to increase with increasing slope, extreme precipitation and runoff, which reveals some inherent differences in model assumptions among the five models. Moreover, the model uncertainty increases in all climate change scenarios, independent on the projected change in annual precipitation and extreme precipitation. This supports the importance to consider model uncertainty through model ensembles of climate, hydrology, and soil erosion in climate change impact assessments.</p><p>This research was funded by ERDF/Spanish Ministry of Science, Innovation and Universities - State Research Agency (AEI) /Project CGL2017-84625-C2-1-R; State Program for Research, Development and Innovation Focused on the Challenges of Society.</p>

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