In recent years, research on spatial scale and scale transformation of eroded sediment transport has become a forefront field in current soil erosion research, but there are very few studies on the scale effect proble...In recent years, research on spatial scale and scale transformation of eroded sediment transport has become a forefront field in current soil erosion research, but there are very few studies on the scale effect problem in Karst regions of China. Here we quantitatively extracted five main factors influencing soil erosion, namely rainfall erosivity, soil erodibility, vegetative cover and management, soil and water conservation, and slope length and steepness. Regression relations were built between these factors and also the sediment transport modulus and drainage area, so as to initially analyze and discuss scale effects on sediment transport in the Wujiang River Basin(WRB). The size and extent of soil erosion influencing factors in the WRB were gauged from: Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model(ASTER GDEM), precipitation data, land use, soil type and Normalized Difference Vegetation Index(NDVI) data from Global Inventory Modeling and Mapping Studies(GIMMS) or Advanced Very High Resolution Radiometer(AVHRR), and observed data from hydrometric stations. We find that scaling effects exist between the sediment transport modulus and the drainage area. Scaling effects are expressed after logarithmic transformation by a quadratic function regression relationship where the sediment transport modulus increases before decreasing, alongside changes in the drainage area. Among the five factors influencing soil erosion, slope length and steepness increases first and then decreases, alongside changes in the drainage area, and are the main factors determining the relationship between sediment transport modulus and drainage area. To eliminate the influence of scale effects on our results, we mapped the sediment yield modulus of the entire WRB, adopting a 1 000 km^2 standard area with a smaller fitting error for all sub-basins, and using the common Kriging interpolation method.展开更多
为了更深入地研究气候变化和土地利用变化对乌江流域蓝绿水时空分布的影响,该研究采用SWAT(soil and water assessment tool)模型,利用1985—2019年逐日气象数据以及1990年、2000年和2010年土地利用数据,设定多种变化情景,定量分析了蓝...为了更深入地研究气候变化和土地利用变化对乌江流域蓝绿水时空分布的影响,该研究采用SWAT(soil and water assessment tool)模型,利用1985—2019年逐日气象数据以及1990年、2000年和2010年土地利用数据,设定多种变化情景,定量分析了蓝水绿水对乌江流域气候和土地利用变化的响应。同时,还利用5个CMIP6(coupled model intercomparison project phase 6)模式集合平均(multi-modal ensemble,MME)以及FLUS(future land-use simulation)模型,预估了乌江流域在2015—2100年间蓝绿水的时空变化。结果表明:1)SWAT模型在乌江流域的校准期和验证期的决定系数(coefficient of determination,R^(2))分别为0.94、0.87,纳什系数(Nash-Sutcliffe coefficient,NSE)分别为0.94、0.77,FLUS模型的Kappa系数为0.764,证明其在流域水文模拟和未来土地利用预估方面的可靠性。2)在1985—2014年间,乌江流域的蓝水、绿水都呈现出先增加后减少的趋势。蓝水、绿水均先分别增加了137.3、7.9 mm/a,然后分别减少了127.5、12.7 mm/a。气候变化对蓝水变化的影响贡献占比为99%,对绿水变化的影响贡献占比平均为88%,表明气候变化在蓝水和绿水变化中的主导地位。3)到2040年,城镇用地面积几乎比2010年扩张了近1.5倍。在2015—2100年,无论是在SSP2-4.5还是SSP5-8.5情景下,蓝水、绿水都呈增加趋势。因此未来需要合理规划乌江流域的土地利用,控制城镇化速度。研究结果可为乌江流域合理规划土地利用、实现水资源综合管理提供支持和参考。展开更多
蓝绿水评价可为流域水资源的全面管理提供科学参考,以地形复杂的乌江流域为例,基于SWAT(Soil and Water Assessment Tool)水文模型,通过年径流距平百分率法确定不同降水年型,利用曼-肯德尔M-K检验法(Mann-Kendall Trend Method)和线性...蓝绿水评价可为流域水资源的全面管理提供科学参考,以地形复杂的乌江流域为例,基于SWAT(Soil and Water Assessment Tool)水文模型,通过年径流距平百分率法确定不同降水年型,利用曼-肯德尔M-K检验法(Mann-Kendall Trend Method)和线性回归趋势分析法分析评估乌江流域1992-2019年蓝绿水资源量时空特征和不同降水年型蓝绿水年内分配和空间分布差异。结果表明:(1)SWAT模型模拟效果较好,可以准确描述乌江流域水循环过程;(2)流域多年平均降水量、蓝水资源量和绿水资源量分别为1126mm、549mm和589mm,降水量和蓝水资源量总体呈下降趋势,绿水资源量总体呈上升趋势;(3)丰水年、平水年和枯水年绿水系数分别为46%、52%和58%,绿水资源量有所变化,对生态系统维持起重要作用;(4)从流域上游到下游,降水量和蓝水资源量均呈现出先增加再减少的趋势,绿水资源量呈现出先增加再减少最后增加的趋势;(5)蓝水资源量时空分布差异主要受降水量变化影响,绿水资源量时空分布受到降水量、气温和土地利用覆被变化的影响。展开更多
基金generously supported by Project of National Natural Science Foundation of China (41641011)National Geology and Mineral Resources Survey and Assessment Program (DDT0160087)
文摘In recent years, research on spatial scale and scale transformation of eroded sediment transport has become a forefront field in current soil erosion research, but there are very few studies on the scale effect problem in Karst regions of China. Here we quantitatively extracted five main factors influencing soil erosion, namely rainfall erosivity, soil erodibility, vegetative cover and management, soil and water conservation, and slope length and steepness. Regression relations were built between these factors and also the sediment transport modulus and drainage area, so as to initially analyze and discuss scale effects on sediment transport in the Wujiang River Basin(WRB). The size and extent of soil erosion influencing factors in the WRB were gauged from: Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model(ASTER GDEM), precipitation data, land use, soil type and Normalized Difference Vegetation Index(NDVI) data from Global Inventory Modeling and Mapping Studies(GIMMS) or Advanced Very High Resolution Radiometer(AVHRR), and observed data from hydrometric stations. We find that scaling effects exist between the sediment transport modulus and the drainage area. Scaling effects are expressed after logarithmic transformation by a quadratic function regression relationship where the sediment transport modulus increases before decreasing, alongside changes in the drainage area. Among the five factors influencing soil erosion, slope length and steepness increases first and then decreases, alongside changes in the drainage area, and are the main factors determining the relationship between sediment transport modulus and drainage area. To eliminate the influence of scale effects on our results, we mapped the sediment yield modulus of the entire WRB, adopting a 1 000 km^2 standard area with a smaller fitting error for all sub-basins, and using the common Kriging interpolation method.
文摘为了更深入地研究气候变化和土地利用变化对乌江流域蓝绿水时空分布的影响,该研究采用SWAT(soil and water assessment tool)模型,利用1985—2019年逐日气象数据以及1990年、2000年和2010年土地利用数据,设定多种变化情景,定量分析了蓝水绿水对乌江流域气候和土地利用变化的响应。同时,还利用5个CMIP6(coupled model intercomparison project phase 6)模式集合平均(multi-modal ensemble,MME)以及FLUS(future land-use simulation)模型,预估了乌江流域在2015—2100年间蓝绿水的时空变化。结果表明:1)SWAT模型在乌江流域的校准期和验证期的决定系数(coefficient of determination,R^(2))分别为0.94、0.87,纳什系数(Nash-Sutcliffe coefficient,NSE)分别为0.94、0.77,FLUS模型的Kappa系数为0.764,证明其在流域水文模拟和未来土地利用预估方面的可靠性。2)在1985—2014年间,乌江流域的蓝水、绿水都呈现出先增加后减少的趋势。蓝水、绿水均先分别增加了137.3、7.9 mm/a,然后分别减少了127.5、12.7 mm/a。气候变化对蓝水变化的影响贡献占比为99%,对绿水变化的影响贡献占比平均为88%,表明气候变化在蓝水和绿水变化中的主导地位。3)到2040年,城镇用地面积几乎比2010年扩张了近1.5倍。在2015—2100年,无论是在SSP2-4.5还是SSP5-8.5情景下,蓝水、绿水都呈增加趋势。因此未来需要合理规划乌江流域的土地利用,控制城镇化速度。研究结果可为乌江流域合理规划土地利用、实现水资源综合管理提供支持和参考。
文摘蓝绿水评价可为流域水资源的全面管理提供科学参考,以地形复杂的乌江流域为例,基于SWAT(Soil and Water Assessment Tool)水文模型,通过年径流距平百分率法确定不同降水年型,利用曼-肯德尔M-K检验法(Mann-Kendall Trend Method)和线性回归趋势分析法分析评估乌江流域1992-2019年蓝绿水资源量时空特征和不同降水年型蓝绿水年内分配和空间分布差异。结果表明:(1)SWAT模型模拟效果较好,可以准确描述乌江流域水循环过程;(2)流域多年平均降水量、蓝水资源量和绿水资源量分别为1126mm、549mm和589mm,降水量和蓝水资源量总体呈下降趋势,绿水资源量总体呈上升趋势;(3)丰水年、平水年和枯水年绿水系数分别为46%、52%和58%,绿水资源量有所变化,对生态系统维持起重要作用;(4)从流域上游到下游,降水量和蓝水资源量均呈现出先增加再减少的趋势,绿水资源量呈现出先增加再减少最后增加的趋势;(5)蓝水资源量时空分布差异主要受降水量变化影响,绿水资源量时空分布受到降水量、气温和土地利用覆被变化的影响。
