The main goal of this study was to evaluate the performance of AnnAGNPS(Annualized AGricultural NonPoint Source)pollution model,in calculating runoff,sediment loading and nutrient loadings for Funiu Mountain area.Most...The main goal of this study was to evaluate the performance of AnnAGNPS(Annualized AGricultural NonPoint Source)pollution model,in calculating runoff,sediment loading and nutrient loadings for Funiu Mountain area.Most of the model input parameters were sourced from Luanchuan Forest Ecology Station(LFES)in Funiu Mountain area.The data on 23 storms in 2018 was used to calibrate the model and the data on 33 storms in 2019 for validation.The whole evaluation consisted of determining the coefficient of determination(R^(2)),Nash-Sutcliffe coefficient of efficiency(E),and the percentage volume error(VE).Results showed that the runoff volumes were underpredicted by 5.0%with R^(2) of 0.93(P<0.05)during calibration and underpredicted by 5.3%with R^(2) of 0.90(P<0.05)during validation.But sediment loading was able to produce a moderate result.The model underpredicted the daily sediment loading by 15.1%with R^(2) of 0.63(P<0.05)during calibration and 13.5%with R^(2) of 0.66(P<0.05)during validation.Nitrogen loading was overpredicted by 20.3%with R^(2)=0.68(P<0.05),and phosphorus loading performance was slightly poor with R^(2)=0.65(P<0.05)during validation.In general,the model performed well in simulating runoff compared to sediment loading and nutrient loadings.展开更多
[Objectives]By testing applicability of SOC depth distribution model in geographical and climatic conditions of Funiu Mountain area,SOC depth distribution model in the region was established and applied. The construct...[Objectives]By testing applicability of SOC depth distribution model in geographical and climatic conditions of Funiu Mountain area,SOC depth distribution model in the region was established and applied. The constructed model was used to estimate SOC mass density in other regions,thereby obtaining SOC abundance distribution chart at different depths.[Methods]165 soil sampling sites were selected from Quercus variabilis forest,Pinus tabulaeformis forest,mixed forest,and shrub forest in Taowan basin of Funiu Mountain area,to determine SOC content at different depths,study SOC depth distribution pattern of forest in Taowan basin of Funiu Mountain area,and assess SOC reserve at different depths.[Results]Average SOC density of Q. variabilis forest,P. tabulaeformis forest,mixed forest,and shrub forest at the depth of 0-20 cm was 7. 92,8. 42,8. 14 and 9. 67 kg/m^2,and there was significant difference in SOC density between shrub forest and Q. variabilis forest,P. tabulaeformis forest,mixed forest( P < 0. 05),and SOC density of four kinds of vegetation all abruptly declined with soil depth increased. At the depth of 0-20 cm,correlation between SOC density and vegetation type,canopy density,clay content and sand content was significant,and the correlation with altitude was insignificant. When carbon density at the depth of 0-100 cm was used to describe regional SOC reserve,the estimated value was lower. The established space model could predict SOC density of forest.[Conclusions]The estimation of deep-layer SOC by the established model needed further consideration,and estimation method for special areas needed to be further demonstrated.展开更多
基金the National Natural Science Foundation of China(32271848).
文摘The main goal of this study was to evaluate the performance of AnnAGNPS(Annualized AGricultural NonPoint Source)pollution model,in calculating runoff,sediment loading and nutrient loadings for Funiu Mountain area.Most of the model input parameters were sourced from Luanchuan Forest Ecology Station(LFES)in Funiu Mountain area.The data on 23 storms in 2018 was used to calibrate the model and the data on 33 storms in 2019 for validation.The whole evaluation consisted of determining the coefficient of determination(R^(2)),Nash-Sutcliffe coefficient of efficiency(E),and the percentage volume error(VE).Results showed that the runoff volumes were underpredicted by 5.0%with R^(2) of 0.93(P<0.05)during calibration and underpredicted by 5.3%with R^(2) of 0.90(P<0.05)during validation.But sediment loading was able to produce a moderate result.The model underpredicted the daily sediment loading by 15.1%with R^(2) of 0.63(P<0.05)during calibration and 13.5%with R^(2) of 0.66(P<0.05)during validation.Nitrogen loading was overpredicted by 20.3%with R^(2)=0.68(P<0.05),and phosphorus loading performance was slightly poor with R^(2)=0.65(P<0.05)during validation.In general,the model performed well in simulating runoff compared to sediment loading and nutrient loadings.
基金Supported by the National Natural Science Foundation of China(31670616)
文摘[Objectives]By testing applicability of SOC depth distribution model in geographical and climatic conditions of Funiu Mountain area,SOC depth distribution model in the region was established and applied. The constructed model was used to estimate SOC mass density in other regions,thereby obtaining SOC abundance distribution chart at different depths.[Methods]165 soil sampling sites were selected from Quercus variabilis forest,Pinus tabulaeformis forest,mixed forest,and shrub forest in Taowan basin of Funiu Mountain area,to determine SOC content at different depths,study SOC depth distribution pattern of forest in Taowan basin of Funiu Mountain area,and assess SOC reserve at different depths.[Results]Average SOC density of Q. variabilis forest,P. tabulaeformis forest,mixed forest,and shrub forest at the depth of 0-20 cm was 7. 92,8. 42,8. 14 and 9. 67 kg/m^2,and there was significant difference in SOC density between shrub forest and Q. variabilis forest,P. tabulaeformis forest,mixed forest( P < 0. 05),and SOC density of four kinds of vegetation all abruptly declined with soil depth increased. At the depth of 0-20 cm,correlation between SOC density and vegetation type,canopy density,clay content and sand content was significant,and the correlation with altitude was insignificant. When carbon density at the depth of 0-100 cm was used to describe regional SOC reserve,the estimated value was lower. The established space model could predict SOC density of forest.[Conclusions]The estimation of deep-layer SOC by the established model needed further consideration,and estimation method for special areas needed to be further demonstrated.
