Fluvial sediment transport data is a very important data for effective water resource management.However,acquiring this data is expensive and tedious hence sediment yield modeling has become an alternative approach in...Fluvial sediment transport data is a very important data for effective water resource management.However,acquiring this data is expensive and tedious hence sediment yield modeling has become an alternative approach in estimating river sediment yields.In Ghana,several sediment yield predicting models have been developed to estimate the sediment yields of ungauged rivers including the Pra River Basin.In this paper,10 months sediment yield data of the Pra River Basin was used to evaluate the existing sediment yield predicting models of Ghana.A regression analysis between predicted sediment yield data derived from the models and the observed suspended sediment yields of the Pra Basin was done to determine the extent of estimation of observed sediment yields.The prediction of suspended sediment yield was done for 4 out of 5 existing sediment yield predicting models in Ghana.There were variations in sediment yield between observed and predicted suspended sediments.All predicted sediment yields were lower than observed data except for equation 3 where the results were mixed.All models were found to be good estimators of fluvial sediments with the best model being equation 4.Sediment yield tends to increase with drainage basin area.展开更多
The main objective of this paper is to report on preliminary validation results of the newly applied sediment yields estimation model in Tanzania, the Pacific Southwest Inter-Agency Committee (PSIAC). This is a follow...The main objective of this paper is to report on preliminary validation results of the newly applied sediment yields estimation model in Tanzania, the Pacific Southwest Inter-Agency Committee (PSIAC). This is a follow-up research on the call to customize simple and/or multi-processes sediment yields estimation models such as PSIAC in the region. The PSIAC approach is based on a sediment yield classification scheme employing individual drainage basin characteristics: surface geology, soils, climate, runoff, topography, ground cover, land use, upland erosion, channel erosion, and sediment transport. In this study, PSIAC model is built from readily available environmental variables sourced from Government ministries/agencies and public domain global spatial data. The sediment classification exercise was verified with field observations. The set up model was then validated by 31 small dams’ siltation surveys and previous sedimentation study findings. PSIAC model performance for major part of central Tanzania was good during calibration (BIAS = 7.88%) and validation (BIAS = 18.12%). Another observation was that uncalibrated model performs fairly well, though performance improves with calibration. The extension of the uncalibrated PSIAC model to 3 selected large basins of Tanzania, with drainage areas size up to 223,000 km2, registered a satisfactory performance in one of them with fair performance in the rest. For large basins, the performance seems to correlate with general ground slope. The higher the slope, the better the performance. It is, however, not apparent from this study on the threshold drainage area and slope requirements for better performance of the model. Notwithstanding, the PSIAC model has improved previous sediment yields estimates based on simple regressive models. Finally, the paper proposes two main further research works: use of high resolution geospatial data and additional validation dams siltation data even beyond the central part of Tanzania, and carries out rigorous study on spatial scale model application limitations.展开更多
Climate change predictions for the Pacific Northwest region of the United States of America include increasing temperatures, intensification of winter precipitation, and a shift from mixed snow/rain to rain-dominant e...Climate change predictions for the Pacific Northwest region of the United States of America include increasing temperatures, intensification of winter precipitation, and a shift from mixed snow/rain to rain-dominant events, all of which may increase the risk of soil erosion and threaten agricultural and ecological productivity. Here we used the agricultural/environmental model SWAT with climate predictions from the Coupled Model Intercomparison Project 5 (CMIP5) “high CO2 emissions” scenario (RCP8.5) to study the impact of altered temperature and precipitation patterns on soil erosion and crop productivity in the Willamette River Basin of western Oregon. An ensemble of 10 climate models representing the full range in temperature and precipitation predictions of CIMP5 produced substantial increases in sediment yield, with differences between yearly averages for the final (2090-2099) and first (2010-2019) decades ranging from 3.9 to 15.2 MT·ha-1 among models. Sediment yield in the worst case model (CanESM2) corresponded to loss of 1.5 - 2.7 mm·soil·y-1, equivalent to potentially stripping productive topsoil from the landscape in under two centuries. Most climate models predicted only small increases in precipitation (an average of 5.8% by the end of the 21st century) combined with large increases in temperature (an average of 0.05°C·y-1). We found a strong correlation between predicted temperature increases and sediment yield, with a regression model combining both temperature and precipitation effects describing 79% of the total variation in annual sediment yield. A critical component of response to increased temperature was reduced snowfall during high precipitation events in the wintertime. SWAT characterized years with less than basin-wide averages of 20 mm of precipitation falling as snow as likely to experience severe sediment loss for multiple crops/land uses. Mid-elevation sub-basins that are projected to shift from rain-snow transition to rain-dominant appear particularly vulnerable to sediment loss. Analyses of predicted crop yields indicated declining productivity for many commonly grown grass seed and cereal crops, along with increasing productivity for certain other crops. Adaptation by agriculture and forestry to warmer, more erosive conditions may include changes in selection of crop kinds and in production management practices.展开更多
Flint River watershed is located in northern Alabama and southern Tennessee, USA and is home to several species of rare, threatened, or endangered plants and animals in a rapidly urbanizing area. Dominant land uses ar...Flint River watershed is located in northern Alabama and southern Tennessee, USA and is home to several species of rare, threatened, or endangered plants and animals in a rapidly urbanizing area. Dominant land uses are forest and agricultural, with row crops and livestock production as major farm enterprises. Soil and Water Assessment Tool (SWAT), a deterministic hydrologic model that can predict hydrologic conditions over various temporal and spatial scales, was used to simulate the hydrologic response of the watershed to land-use/land cover (LULC) change. Analysis between observed and predicted stream flow demonstrated that the initial SWAT model run requires calibration of stream parameters in order to give a more accurate output from the model. The calibration was performed with sequential uncertainty fitting, ver. 2 (SUFI-2) in the SWAT Calibration Uncertainty Program. After calibration, stream sediment yield values were compared by sub-basin between a current (2001) and three future (2030) land use scenarios, in order to identify areas in the watershed that were the most susceptible to increased sediment yield in the future. The future growth scenarios (smart, plan and sprawl) were created using the ArcGIS extension, Prescott Spatial Growth Model. Sub-basins with the greatest sensitivity for larger sediment yields were identified and prioritized for conservation efforts.展开更多
A constitutive model for methane hydrate-bearing sediment(MHBS)is essential for the analysis of mechanical response of MHBS to the change of hydrate saturation caused by gas extraction. A new elasto-plastic constituti...A constitutive model for methane hydrate-bearing sediment(MHBS)is essential for the analysis of mechanical response of MHBS to the change of hydrate saturation caused by gas extraction. A new elasto-plastic constitutive model is built in order to simulate the mechanical behavior of MHBS in this paper. This model represents more significant mechanical properties of MHBS such as bonding, higher stiffness, softening and stress-strain nonlinear relationship. The bonding behavior can be described by use of a parameter related to mechanical hydrate saturation. Higher stiffness can be modeled by the introduction of hydrate saturation into traditional expression of soil stiffness. Softening can be controlled by a function describing the relationship between cohesion and bonding structure factor. Dilatancy can be estimated by establishing the relationship between the lateral strain and axial strain. Meanwhile, the hypothesis of isotropic expanding is applied to the calculation of the volumetric strain. The stress-strain curves under different hydrate saturation conditions predicted by the proposed model are in good agreement with the test data. All the coefficients can be easily obtained by the triaxial test of MHBS.展开更多
The potential future increase in corn-based biofuel may be expected to have a negative impact on water quality in streams and lakes of the Midwestern US due to increased agricultural chemicals usage. This study used t...The potential future increase in corn-based biofuel may be expected to have a negative impact on water quality in streams and lakes of the Midwestern US due to increased agricultural chemicals usage. This study used the SWAT model to assess the impact of continuous-corn farming on sediment and phosphorus loading in Upper Rock River watershed in Wisconsin. It was assumed that farmers in the area where corn was rotated with soybean would progressively skip soybean for continuous corn as corn became more profitable. Simulations using SWAT indicated that conversion of corn-soybean to corn-corn-soybean would cause 11% and 2% increase in sediment yield and TP loss, respectively. The conversion of corn-soybean to continuous corn caused 55% and 35% increase in sediment yield and TP loss, respectively. However, this increase could be mitigated by applying various BMPs and/or conservation practices such as conservation tillage, fertilizer management and vegetative buffer strips. The conversion to continuous corn tilled with conservation tillage reduced sediment yield by 2% and did not change TP loss. Increase in P fertilizer amount was roughly proportional to increase in TP loss and 11% more TP was lost when fertilizer was applied four months before planting. Vegetative buffer strips, 15 to 30 m wide, around corn farms reduced sediment yield by 51 to 70% and TP loss by 41 to 63%.展开更多
Developing regional models using physiographic, climatic, and hydrologic variables is an approach to estimating suspended load yield(SLY)in ungauged watersheds. However, using all the variables might reduce the applic...Developing regional models using physiographic, climatic, and hydrologic variables is an approach to estimating suspended load yield(SLY)in ungauged watersheds. However, using all the variables might reduce the applicability of these models. Therefore, data reduction techniques(DRTs), e.g., principal component analysis(PCA), Gamma test(GT), and stepwise regression(SR), have been used to select the most effective variables. The artificial neural network(ANN) and multiple linear regression(MLR) are also common tools for SLY modeling. We conducted this study(1) to obtain the most effective variables influencing SLY through DRTs including PCA, GT, and SR, and then, to use them as input data for ANN and MLR; and(2) to provide the best SLY models. Accordingly, we used 14 physiographic, climatic, and hydrologic parameters from 42 watersheds in the Hyrcanian forest region(in northern Iran). The most effective variables as determined through DRTs as well as the original data sets were used as the input data for ANN and MLR in order to provide an SLY model. The results indicated that the SLY models provided by ANN performed much better than the MLR models, and the GT-ANN model was the best. The determination of coefficient,relative error, root mean square error, and bias were 99.9%, 26%, 323 t/year, and 6 t/year in the calibration period, and 70%, 43%, 456 t/year, and 407 t/year in the validation period, respectively. Overall, selecting the main factors that influence SLY and using artificial intelligence tools can be useful for water resources managers to quickly determine the behavior of SLY in ungauged watersheds.展开更多
Based on meteorologic data in Xixi Watershed from 1972 to 1979, the SWAT model was applied to simulate the response of runoff and sediment yield in Xixi Watershed to climate change under 24 kinds of climate change sce...Based on meteorologic data in Xixi Watershed from 1972 to 1979, the SWAT model was applied to simulate the response of runoff and sediment yield in Xixi Watershed to climate change under 24 kinds of climate change scenarios, and then the spatial and temporal distribution of change rates of the runoff and sediment were analyzed. The results showed that the runoff yield would increase with the increase of precipitation or decrease of temperature, and the sediment yield would increase with the increase of precipitation or increase of temperature; the runoff would be more sensitive to variations in precipitation than to variations in temperature, and precipitation change would lead to more obvious change in the run- off yield; the temporal distribution of change rates of the runoff and sediment yield would be uneven in the 12 months, and the variation trends of the two change rates in the 12 months would be accordant; the spatial distribution of change rates of the runoff and sediment yield would be uneven in the sub-watersheds, and the change rate of the runoff yield would be bigger in the sub-watersheds where the runoff yield in the basic period would be smaller. This study can provide decision-making basis for sustainable development of Jinjiang Basin.展开更多
Soil erosion is an important economic and environmental concern throughout the world. In order to assess soil erosion risk and conserve soil and water resources, soil erosion modeling at the watershed scale is imperat...Soil erosion is an important economic and environmental concern throughout the world. In order to assess soil erosion risk and conserve soil and water resources, soil erosion modeling at the watershed scale is imperative. The Guelph model for evaluating effects of Agricultural Management System on Erosion and Sedimentation (GAMES) is tailor-made for such applications;it, however, requires a significant amount of spatial information which needs to be pre-processed using a Geographic Information System (GIS). The GAMES model currently lacks any such automated tools. As such, the GAMES was loosely coupled to a GIS interface to manage the large spatial input data and to produce efficient cartographic representations of model output results. The developed interface tool was tested to simulate the Kettle Creek paired watershed in Southern Ontario, Canada. Result demonstrated that the GIS-assisted procedure increased the ability of the GAMES model in simulating such a spatially varied watershed and made the process more efficient and user-friendly. Furthermore, the quality of reporting and displaying resultant spatial output was also significantly improved. The developed GAMES interface could be applied to any watershed, and the enhancement could be used to assess soil erosion risk and conserve soil and water resources in an effective way.展开更多
The Yellow River is well known as a sediment-laden river, which is the main reason that it cannot be controlled as easily as other rivers. Many researchers, such as Qian Ning et al., have found that the sediment load ...The Yellow River is well known as a sediment-laden river, which is the main reason that it cannot be controlled as easily as other rivers. Many researchers, such as Qian Ning et al., have found that the sediment load of the Yellow River comes mainly from the sandy and gritty area of the Loess Plateau. Therefore, it is very important to simulate the sediment yield in this area. This paper proposes a method to compute the sediment production in the sandy and gritty area based on the digital watershed model. The suggested model is calibrated and validated in the Chabagou basin, which is a small catchment in the study area. Finally, the model simulates the sediment yield of the sandy and gritty area in 1967, 1978, 1983, 1994 and 1997, which represents a high water and high sediment year, a mean water and mean sediment year, a high water and low sediment year, a low water and high sediment year, and a low water and low sediment year separately. The simulation results, including the runoff depth and erosion modulus, can well explain the "low water and high sediment" phenomena in the Yellow River basin. The total amount of the sediment production and its distribution generated by the model is very useful for water and soil conservation in the sandy and gritty area of the Loess Plateau.展开更多
文摘Fluvial sediment transport data is a very important data for effective water resource management.However,acquiring this data is expensive and tedious hence sediment yield modeling has become an alternative approach in estimating river sediment yields.In Ghana,several sediment yield predicting models have been developed to estimate the sediment yields of ungauged rivers including the Pra River Basin.In this paper,10 months sediment yield data of the Pra River Basin was used to evaluate the existing sediment yield predicting models of Ghana.A regression analysis between predicted sediment yield data derived from the models and the observed suspended sediment yields of the Pra Basin was done to determine the extent of estimation of observed sediment yields.The prediction of suspended sediment yield was done for 4 out of 5 existing sediment yield predicting models in Ghana.There were variations in sediment yield between observed and predicted suspended sediments.All predicted sediment yields were lower than observed data except for equation 3 where the results were mixed.All models were found to be good estimators of fluvial sediments with the best model being equation 4.Sediment yield tends to increase with drainage basin area.
文摘The main objective of this paper is to report on preliminary validation results of the newly applied sediment yields estimation model in Tanzania, the Pacific Southwest Inter-Agency Committee (PSIAC). This is a follow-up research on the call to customize simple and/or multi-processes sediment yields estimation models such as PSIAC in the region. The PSIAC approach is based on a sediment yield classification scheme employing individual drainage basin characteristics: surface geology, soils, climate, runoff, topography, ground cover, land use, upland erosion, channel erosion, and sediment transport. In this study, PSIAC model is built from readily available environmental variables sourced from Government ministries/agencies and public domain global spatial data. The sediment classification exercise was verified with field observations. The set up model was then validated by 31 small dams’ siltation surveys and previous sedimentation study findings. PSIAC model performance for major part of central Tanzania was good during calibration (BIAS = 7.88%) and validation (BIAS = 18.12%). Another observation was that uncalibrated model performs fairly well, though performance improves with calibration. The extension of the uncalibrated PSIAC model to 3 selected large basins of Tanzania, with drainage areas size up to 223,000 km2, registered a satisfactory performance in one of them with fair performance in the rest. For large basins, the performance seems to correlate with general ground slope. The higher the slope, the better the performance. It is, however, not apparent from this study on the threshold drainage area and slope requirements for better performance of the model. Notwithstanding, the PSIAC model has improved previous sediment yields estimates based on simple regressive models. Finally, the paper proposes two main further research works: use of high resolution geospatial data and additional validation dams siltation data even beyond the central part of Tanzania, and carries out rigorous study on spatial scale model application limitations.
文摘Climate change predictions for the Pacific Northwest region of the United States of America include increasing temperatures, intensification of winter precipitation, and a shift from mixed snow/rain to rain-dominant events, all of which may increase the risk of soil erosion and threaten agricultural and ecological productivity. Here we used the agricultural/environmental model SWAT with climate predictions from the Coupled Model Intercomparison Project 5 (CMIP5) “high CO2 emissions” scenario (RCP8.5) to study the impact of altered temperature and precipitation patterns on soil erosion and crop productivity in the Willamette River Basin of western Oregon. An ensemble of 10 climate models representing the full range in temperature and precipitation predictions of CIMP5 produced substantial increases in sediment yield, with differences between yearly averages for the final (2090-2099) and first (2010-2019) decades ranging from 3.9 to 15.2 MT·ha-1 among models. Sediment yield in the worst case model (CanESM2) corresponded to loss of 1.5 - 2.7 mm·soil·y-1, equivalent to potentially stripping productive topsoil from the landscape in under two centuries. Most climate models predicted only small increases in precipitation (an average of 5.8% by the end of the 21st century) combined with large increases in temperature (an average of 0.05°C·y-1). We found a strong correlation between predicted temperature increases and sediment yield, with a regression model combining both temperature and precipitation effects describing 79% of the total variation in annual sediment yield. A critical component of response to increased temperature was reduced snowfall during high precipitation events in the wintertime. SWAT characterized years with less than basin-wide averages of 20 mm of precipitation falling as snow as likely to experience severe sediment loss for multiple crops/land uses. Mid-elevation sub-basins that are projected to shift from rain-snow transition to rain-dominant appear particularly vulnerable to sediment loss. Analyses of predicted crop yields indicated declining productivity for many commonly grown grass seed and cereal crops, along with increasing productivity for certain other crops. Adaptation by agriculture and forestry to warmer, more erosive conditions may include changes in selection of crop kinds and in production management practices.
文摘Flint River watershed is located in northern Alabama and southern Tennessee, USA and is home to several species of rare, threatened, or endangered plants and animals in a rapidly urbanizing area. Dominant land uses are forest and agricultural, with row crops and livestock production as major farm enterprises. Soil and Water Assessment Tool (SWAT), a deterministic hydrologic model that can predict hydrologic conditions over various temporal and spatial scales, was used to simulate the hydrologic response of the watershed to land-use/land cover (LULC) change. Analysis between observed and predicted stream flow demonstrated that the initial SWAT model run requires calibration of stream parameters in order to give a more accurate output from the model. The calibration was performed with sequential uncertainty fitting, ver. 2 (SUFI-2) in the SWAT Calibration Uncertainty Program. After calibration, stream sediment yield values were compared by sub-basin between a current (2001) and three future (2030) land use scenarios, in order to identify areas in the watershed that were the most susceptible to increased sediment yield in the future. The future growth scenarios (smart, plan and sprawl) were created using the ArcGIS extension, Prescott Spatial Growth Model. Sub-basins with the greatest sensitivity for larger sediment yields were identified and prioritized for conservation efforts.
基金Supported by the National Science and Technology Major Project of China(No.2011ZX05026-004)the National Natural Science Foundation of China(No.51309047 and No.51509032)
文摘A constitutive model for methane hydrate-bearing sediment(MHBS)is essential for the analysis of mechanical response of MHBS to the change of hydrate saturation caused by gas extraction. A new elasto-plastic constitutive model is built in order to simulate the mechanical behavior of MHBS in this paper. This model represents more significant mechanical properties of MHBS such as bonding, higher stiffness, softening and stress-strain nonlinear relationship. The bonding behavior can be described by use of a parameter related to mechanical hydrate saturation. Higher stiffness can be modeled by the introduction of hydrate saturation into traditional expression of soil stiffness. Softening can be controlled by a function describing the relationship between cohesion and bonding structure factor. Dilatancy can be estimated by establishing the relationship between the lateral strain and axial strain. Meanwhile, the hypothesis of isotropic expanding is applied to the calculation of the volumetric strain. The stress-strain curves under different hydrate saturation conditions predicted by the proposed model are in good agreement with the test data. All the coefficients can be easily obtained by the triaxial test of MHBS.
文摘The potential future increase in corn-based biofuel may be expected to have a negative impact on water quality in streams and lakes of the Midwestern US due to increased agricultural chemicals usage. This study used the SWAT model to assess the impact of continuous-corn farming on sediment and phosphorus loading in Upper Rock River watershed in Wisconsin. It was assumed that farmers in the area where corn was rotated with soybean would progressively skip soybean for continuous corn as corn became more profitable. Simulations using SWAT indicated that conversion of corn-soybean to corn-corn-soybean would cause 11% and 2% increase in sediment yield and TP loss, respectively. The conversion of corn-soybean to continuous corn caused 55% and 35% increase in sediment yield and TP loss, respectively. However, this increase could be mitigated by applying various BMPs and/or conservation practices such as conservation tillage, fertilizer management and vegetative buffer strips. The conversion to continuous corn tilled with conservation tillage reduced sediment yield by 2% and did not change TP loss. Increase in P fertilizer amount was roughly proportional to increase in TP loss and 11% more TP was lost when fertilizer was applied four months before planting. Vegetative buffer strips, 15 to 30 m wide, around corn farms reduced sediment yield by 51 to 70% and TP loss by 41 to 63%.
基金supported by the Department of Environmental Science,Urmia Lake Research Institute,Urmia University
文摘Developing regional models using physiographic, climatic, and hydrologic variables is an approach to estimating suspended load yield(SLY)in ungauged watersheds. However, using all the variables might reduce the applicability of these models. Therefore, data reduction techniques(DRTs), e.g., principal component analysis(PCA), Gamma test(GT), and stepwise regression(SR), have been used to select the most effective variables. The artificial neural network(ANN) and multiple linear regression(MLR) are also common tools for SLY modeling. We conducted this study(1) to obtain the most effective variables influencing SLY through DRTs including PCA, GT, and SR, and then, to use them as input data for ANN and MLR; and(2) to provide the best SLY models. Accordingly, we used 14 physiographic, climatic, and hydrologic parameters from 42 watersheds in the Hyrcanian forest region(in northern Iran). The most effective variables as determined through DRTs as well as the original data sets were used as the input data for ANN and MLR in order to provide an SLY model. The results indicated that the SLY models provided by ANN performed much better than the MLR models, and the GT-ANN model was the best. The determination of coefficient,relative error, root mean square error, and bias were 99.9%, 26%, 323 t/year, and 6 t/year in the calibration period, and 70%, 43%, 456 t/year, and 407 t/year in the validation period, respectively. Overall, selecting the main factors that influence SLY and using artificial intelligence tools can be useful for water resources managers to quickly determine the behavior of SLY in ungauged watersheds.
基金Supported by the Science and Technology Development Plan Project of Binzhou City(Policy Guidance)(2013ZC1001)Scientific Research Foundation of Binzhou University(BZXYG1414)+1 种基金Key Science and Technology Project for the Control of Major Safety Production Accidents in 2015 of State Administration of Work Safety(Shandong-0052-2015AQ)Project for Experimental Techniques of Binzhou University(BZXYSYXM201207)
文摘Based on meteorologic data in Xixi Watershed from 1972 to 1979, the SWAT model was applied to simulate the response of runoff and sediment yield in Xixi Watershed to climate change under 24 kinds of climate change scenarios, and then the spatial and temporal distribution of change rates of the runoff and sediment were analyzed. The results showed that the runoff yield would increase with the increase of precipitation or decrease of temperature, and the sediment yield would increase with the increase of precipitation or increase of temperature; the runoff would be more sensitive to variations in precipitation than to variations in temperature, and precipitation change would lead to more obvious change in the run- off yield; the temporal distribution of change rates of the runoff and sediment yield would be uneven in the 12 months, and the variation trends of the two change rates in the 12 months would be accordant; the spatial distribution of change rates of the runoff and sediment yield would be uneven in the sub-watersheds, and the change rate of the runoff yield would be bigger in the sub-watersheds where the runoff yield in the basic period would be smaller. This study can provide decision-making basis for sustainable development of Jinjiang Basin.
文摘Soil erosion is an important economic and environmental concern throughout the world. In order to assess soil erosion risk and conserve soil and water resources, soil erosion modeling at the watershed scale is imperative. The Guelph model for evaluating effects of Agricultural Management System on Erosion and Sedimentation (GAMES) is tailor-made for such applications;it, however, requires a significant amount of spatial information which needs to be pre-processed using a Geographic Information System (GIS). The GAMES model currently lacks any such automated tools. As such, the GAMES was loosely coupled to a GIS interface to manage the large spatial input data and to produce efficient cartographic representations of model output results. The developed interface tool was tested to simulate the Kettle Creek paired watershed in Southern Ontario, Canada. Result demonstrated that the GIS-assisted procedure increased the ability of the GAMES model in simulating such a spatially varied watershed and made the process more efficient and user-friendly. Furthermore, the quality of reporting and displaying resultant spatial output was also significantly improved. The developed GAMES interface could be applied to any watershed, and the enhancement could be used to assess soil erosion risk and conserve soil and water resources in an effective way.
基金supported by the National Natural Science Foundation of China(Grant No.50221903).
文摘The Yellow River is well known as a sediment-laden river, which is the main reason that it cannot be controlled as easily as other rivers. Many researchers, such as Qian Ning et al., have found that the sediment load of the Yellow River comes mainly from the sandy and gritty area of the Loess Plateau. Therefore, it is very important to simulate the sediment yield in this area. This paper proposes a method to compute the sediment production in the sandy and gritty area based on the digital watershed model. The suggested model is calibrated and validated in the Chabagou basin, which is a small catchment in the study area. Finally, the model simulates the sediment yield of the sandy and gritty area in 1967, 1978, 1983, 1994 and 1997, which represents a high water and high sediment year, a mean water and mean sediment year, a high water and low sediment year, a low water and high sediment year, and a low water and low sediment year separately. The simulation results, including the runoff depth and erosion modulus, can well explain the "low water and high sediment" phenomena in the Yellow River basin. The total amount of the sediment production and its distribution generated by the model is very useful for water and soil conservation in the sandy and gritty area of the Loess Plateau.
