Soil erosion on cropland is a major source of environmental problems in China ranging from the losses of a non-renewable resource and of nutrients at the source to contamination of downstream areas. Regional soil loss...Soil erosion on cropland is a major source of environmental problems in China ranging from the losses of a non-renewable resource and of nutrients at the source to contamination of downstream areas. Regional soil loss assessments using the Universal Soil Loss Equation (USLE) would supply a scientiifc basis for soil conservation planning. However, a lack of in-formation on the cover and management (C) factor for cropland, one of the most important factors in the USLE, has limited accurate regional assessments in China due to the large number of crops grown and their complicated rotation systems. In this study, single crop soil loss ratios (SLRs) were col ected and quantiifed for 10 primary crops from past studies or re-ports. The mean annual C values for 88 crop rotation systems in 12 cropping system regions were estimated based on the combined effects of single crop SLRs and the percentage of annual rainfal erosivity (R) during the corresponding periods for each system. The C values in different cropping system regions were compared and discussed. The results indicated that the SLRs of the 10 primary crops ranged from 0.15 to 0.74. The mean annual C value for al 88 crop rotation systems was 0.34, with a standard deviation of 0.12. The mean C values in the single, double and triple cropping zones were 0.37, 0.36 and 0.28, respectively, and the C value in the triple zone was signiifcantly different from those in single and double zones. The C values of dryland crop systems exhibited signiifcant differences in the single and triple cropping system regions but the differences in the double regions were not signiifcant. This study is the ifrst report of the C values of crop rotation systems in China at the national scale. It wil provide necessary and practical parameters for accurately assessing regional soil losses from cropland to guide soil conservation plans and to optimize crop rotation systems.展开更多
Anthropogenic activities have altered land cover in Lake Baringo Catchment contributing to increased erosion and sediment transport into water bodies. The study aims at analyzing the spatial and temporal Land Use and ...Anthropogenic activities have altered land cover in Lake Baringo Catchment contributing to increased erosion and sediment transport into water bodies. The study aims at analyzing the spatial and temporal Land Use and Land Cover Changes (LULCC) changes from 1988 to 2018 and to identify the main driving forces. GIS and Remote Sensing techniques, interviews and field observations were used to analyze the changes and drivers of LULCC from 1988-2018. The satellite imagery was selected from SPOT Image for the years 1988, 1998, 2008 and 2018. Environment for Visualizing Images (ENVI 5.3) was used to perform image analysis and classification. The catchment was classified into six major LULC classes which are water bodies, settlement, rangeland, vegetation, farmland and bare land. The results revealed that, between the years 1988-1998, and 1998-2008, water bodies decreased by 2.77% and 0.76% respectively. However, during the years 2008-2018, water body coverage increased by 1.87%. Forest cover steadily increased from 1988-2018. From 1988-1998, 1998-2008 and 2008-2018, farmland was increased by 21.11%, 3.21% and 1.7% while rangeland decreased continuously between the years 1988-1998, 1998-2008 and 2008-2018 in the order 15.14%, 4.13% and 3.74% respectively. Similarly, bare land also reduced by 1.75%, 1.04% and 0.99% between the years 1988-1998, 1998-2008 and 2008-2018 respectively. The findings attributed LULCC to rapid population growth, deforestation, poor farming practices and overstocking. The results will provide valuable information to the relevant stakeholders to formulate evidence-based land use management strategies in order to achieve ecological integrity.展开更多
We present a new approach for calculating the C-factor of RUSLE considering the effect of low-reflectance vegetation cover areas on the reduction of the effects on erosion caused by rainfall seasonality.For this,we pr...We present a new approach for calculating the C-factor of RUSLE considering the effect of low-reflectance vegetation cover areas on the reduction of the effects on erosion caused by rainfall seasonality.For this,we propose the coefficients Cr2(rescaled 2)and C-PC(Precipitation Correction),which represent the Cfactor,and an adaptation in NDVI calculation,according to the seasonality of precipitation(NDVI-PC).The Cr2 factor is used when there is no seasonal effect of rainfall on vegetation,while the C-PC factor is calculated for localities under the influence of seasonality,from NDVI-PC.The proposed approaches were tested using different satellites images in the Palmares-Ribeir~ao do Saco watershed,Rio de Janeiro,Brazil.The values of Cr2 and C-PC factors were compared to the Cr factor(rescaled)and to mean values from the literature for different land covers.Our results indicated that the Cr2 factor represents an improvement in accuracy in relation to Cr by considering specific values of the studied area to normalize the data without generalizations.Furthermore,the C-PC factor is able to simulate the effect of seasonality,providing more realistics values of soil loss by the RUSLE as a function of the proportion of area affected by the rainfall seasonality obtained from NDVI-PC.We conclude that both Cr2 and C-PC factors generate values similar of the C-factor observed in the literature,and therefore are able to provide better soil loss estimation than that using the Cr factor.展开更多
The prevalence of unwholesome land use practices and population pressure exacerbates soil loss which is worsening the problem of sedimentation of the Kubanni dam. This study was conducted at the Kubanni drainage basin...The prevalence of unwholesome land use practices and population pressure exacerbates soil loss which is worsening the problem of sedimentation of the Kubanni dam. This study was conducted at the Kubanni drainage basin covering a spatial area of 56.7 Km2 in Samaru, Zaria, Nigeria to estimate annual soil loss using the RUSLE model. Satellite images of Landsat OLI for December 2014, 2016, 2018, February, July and November 2022;soil data, rainfall data from 2010 to 2022, and DEM of 30-meter resolution were utilized for the study. All factors of the RUSLE model were calculated for the basin using assembled data. The erosivity (R-factor) was discovered to be 553.437 MJ∙mm∙ha−1∙h−1∙yr−1. The average erodibility (K-factor) value was 0.1 Mg∙h∙h∙ha−1∙MJ−1∙mm−1∙yr−1. The Slope Length and Steepness factor (LS-factor) in the basin ranged between 0% and 13.47%. The Crop Management Factor (C-factor) values were obtained from a rescaling of the NDVI values derived for the study area and ranged from 0.26 to 0.55. Support practice (P-factors) were computed from the prevalent tillage practice in the basin and ranged from 0.27 to 0.40. The soil loss amount for the Kubanni basin was found to be 28441.482 tons∙ha−1∙yr−1, while the annual soil loss for the entire Kubanni drainage basin was found to be 49780.257 tons∙yr−1. The study has demonstrated the viability of coupling RUSLE model and Remote Sensing and Geographic Information System (GIS) techniques for the estimation of soil loss in the Kubanni drainage basin.展开更多
Rainfall erosivity is an important climatic factor for predicting soil loss. Through the application of high-resolution pluviograph data at 5 stations in Huangshan City, Anhui Prov- ince, China, we analyzed the perfor...Rainfall erosivity is an important climatic factor for predicting soil loss. Through the application of high-resolution pluviograph data at 5 stations in Huangshan City, Anhui Prov- ince, China, we analyzed the performance of a modified Richardson model that incorporated the seasonal variations in parameters α andβ. The results showed that （1） moderate to high seasonality was presented in the distribution of erosive rainfall, and the seasonality of rainfall erosivity was even stronger; （2） seasonal variations were demonstrated in both parameters α and β of the Richardson model; and （3） incorporating and coordinating the seasonality of parameters αandβgreatly improved the predictions at the monthly scale. This newly modi- fied model is therefore highly recommended when monthly rainfall erosivity is required, such as, in planning soil and water conservation practices and calculating the cover-management factor in the Universal Soil Loss Equation （USLE） and Revised Universal Soil Loss Equation （RUSLE）.展开更多
基金financially supported by the Fund for Creative Research Groups of National Natural Science Foundation of China (41321001)
文摘Soil erosion on cropland is a major source of environmental problems in China ranging from the losses of a non-renewable resource and of nutrients at the source to contamination of downstream areas. Regional soil loss assessments using the Universal Soil Loss Equation (USLE) would supply a scientiifc basis for soil conservation planning. However, a lack of in-formation on the cover and management (C) factor for cropland, one of the most important factors in the USLE, has limited accurate regional assessments in China due to the large number of crops grown and their complicated rotation systems. In this study, single crop soil loss ratios (SLRs) were col ected and quantiifed for 10 primary crops from past studies or re-ports. The mean annual C values for 88 crop rotation systems in 12 cropping system regions were estimated based on the combined effects of single crop SLRs and the percentage of annual rainfal erosivity (R) during the corresponding periods for each system. The C values in different cropping system regions were compared and discussed. The results indicated that the SLRs of the 10 primary crops ranged from 0.15 to 0.74. The mean annual C value for al 88 crop rotation systems was 0.34, with a standard deviation of 0.12. The mean C values in the single, double and triple cropping zones were 0.37, 0.36 and 0.28, respectively, and the C value in the triple zone was signiifcantly different from those in single and double zones. The C values of dryland crop systems exhibited signiifcant differences in the single and triple cropping system regions but the differences in the double regions were not signiifcant. This study is the ifrst report of the C values of crop rotation systems in China at the national scale. It wil provide necessary and practical parameters for accurately assessing regional soil losses from cropland to guide soil conservation plans and to optimize crop rotation systems.
文摘Anthropogenic activities have altered land cover in Lake Baringo Catchment contributing to increased erosion and sediment transport into water bodies. The study aims at analyzing the spatial and temporal Land Use and Land Cover Changes (LULCC) changes from 1988 to 2018 and to identify the main driving forces. GIS and Remote Sensing techniques, interviews and field observations were used to analyze the changes and drivers of LULCC from 1988-2018. The satellite imagery was selected from SPOT Image for the years 1988, 1998, 2008 and 2018. Environment for Visualizing Images (ENVI 5.3) was used to perform image analysis and classification. The catchment was classified into six major LULC classes which are water bodies, settlement, rangeland, vegetation, farmland and bare land. The results revealed that, between the years 1988-1998, and 1998-2008, water bodies decreased by 2.77% and 0.76% respectively. However, during the years 2008-2018, water body coverage increased by 1.87%. Forest cover steadily increased from 1988-2018. From 1988-1998, 1998-2008 and 2008-2018, farmland was increased by 21.11%, 3.21% and 1.7% while rangeland decreased continuously between the years 1988-1998, 1998-2008 and 2008-2018 in the order 15.14%, 4.13% and 3.74% respectively. Similarly, bare land also reduced by 1.75%, 1.04% and 0.99% between the years 1988-1998, 1998-2008 and 2008-2018 respectively. The findings attributed LULCC to rapid population growth, deforestation, poor farming practices and overstocking. The results will provide valuable information to the relevant stakeholders to formulate evidence-based land use management strategies in order to achieve ecological integrity.
基金Paulo Tarso S.Oliveira was supported by the Brazilian National Council for Scientific and Technological Development(CNPq)(grants 441289/2017e7 and 306830/2017e5)the Coordination of Superior Level Staff Improvement-Brazil(CAPES)(Finance Code 001).
文摘We present a new approach for calculating the C-factor of RUSLE considering the effect of low-reflectance vegetation cover areas on the reduction of the effects on erosion caused by rainfall seasonality.For this,we propose the coefficients Cr2(rescaled 2)and C-PC(Precipitation Correction),which represent the Cfactor,and an adaptation in NDVI calculation,according to the seasonality of precipitation(NDVI-PC).The Cr2 factor is used when there is no seasonal effect of rainfall on vegetation,while the C-PC factor is calculated for localities under the influence of seasonality,from NDVI-PC.The proposed approaches were tested using different satellites images in the Palmares-Ribeir~ao do Saco watershed,Rio de Janeiro,Brazil.The values of Cr2 and C-PC factors were compared to the Cr factor(rescaled)and to mean values from the literature for different land covers.Our results indicated that the Cr2 factor represents an improvement in accuracy in relation to Cr by considering specific values of the studied area to normalize the data without generalizations.Furthermore,the C-PC factor is able to simulate the effect of seasonality,providing more realistics values of soil loss by the RUSLE as a function of the proportion of area affected by the rainfall seasonality obtained from NDVI-PC.We conclude that both Cr2 and C-PC factors generate values similar of the C-factor observed in the literature,and therefore are able to provide better soil loss estimation than that using the Cr factor.
文摘The prevalence of unwholesome land use practices and population pressure exacerbates soil loss which is worsening the problem of sedimentation of the Kubanni dam. This study was conducted at the Kubanni drainage basin covering a spatial area of 56.7 Km2 in Samaru, Zaria, Nigeria to estimate annual soil loss using the RUSLE model. Satellite images of Landsat OLI for December 2014, 2016, 2018, February, July and November 2022;soil data, rainfall data from 2010 to 2022, and DEM of 30-meter resolution were utilized for the study. All factors of the RUSLE model were calculated for the basin using assembled data. The erosivity (R-factor) was discovered to be 553.437 MJ∙mm∙ha−1∙h−1∙yr−1. The average erodibility (K-factor) value was 0.1 Mg∙h∙h∙ha−1∙MJ−1∙mm−1∙yr−1. The Slope Length and Steepness factor (LS-factor) in the basin ranged between 0% and 13.47%. The Crop Management Factor (C-factor) values were obtained from a rescaling of the NDVI values derived for the study area and ranged from 0.26 to 0.55. Support practice (P-factors) were computed from the prevalent tillage practice in the basin and ranged from 0.27 to 0.40. The soil loss amount for the Kubanni basin was found to be 28441.482 tons∙ha−1∙yr−1, while the annual soil loss for the entire Kubanni drainage basin was found to be 49780.257 tons∙yr−1. The study has demonstrated the viability of coupling RUSLE model and Remote Sensing and Geographic Information System (GIS) techniques for the estimation of soil loss in the Kubanni drainage basin.
基金Fund for Creative Research Groups of National Natural Science Foundation of China, No.41321001 the National Natural Science Foundation of China, No.51379008 the Open Research Fund of the State Key Lab of Simulation and Regulation of Water Cycle in River Basin, No.2014QN04.
文摘Rainfall erosivity is an important climatic factor for predicting soil loss. Through the application of high-resolution pluviograph data at 5 stations in Huangshan City, Anhui Prov- ince, China, we analyzed the performance of a modified Richardson model that incorporated the seasonal variations in parameters α andβ. The results showed that （1） moderate to high seasonality was presented in the distribution of erosive rainfall, and the seasonality of rainfall erosivity was even stronger; （2） seasonal variations were demonstrated in both parameters α and β of the Richardson model; and （3） incorporating and coordinating the seasonality of parameters αandβgreatly improved the predictions at the monthly scale. This newly modi- fied model is therefore highly recommended when monthly rainfall erosivity is required, such as, in planning soil and water conservation practices and calculating the cover-management factor in the Universal Soil Loss Equation （USLE） and Revised Universal Soil Loss Equation （RUSLE）.
