In the face of global warming and increasing impervious surfaces,quantifying the change of climate potential productivity(CPP)is of great significance for the food production planning.Targeting the Dongting Lake Basin...In the face of global warming and increasing impervious surfaces,quantifying the change of climate potential productivity(CPP)is of great significance for the food production planning.Targeting the Dongting Lake Basin,which is a key area for food production in China,this paper uses meteorological data,as well as Climate Change Initiative Land Cover,and Shuttle Radar Topography Mission digital elevation model to investigate the CPP and its changes from 2000 to 2020.The suitability of land for cultivation(SLC),and the land use/land cover change(LUCC)are also considered.The results showed that the CPP varied from 9,825 to 20,895 kg ha^(-1).Even though the newly added impervious surfaces indirectly resulted in the decrease of CPP by of 9.81×10~8 kg,overall,the CPP increased at an average rate of 83.7 kg ha^(-1)a^(-1).Global warming is the strongest driver behind CPP increase,and CPP has played an important role in the conversions between cultivated land and other land types.The structure of land types tends to be optimized against this challenge.展开更多
This study developed a hierarchical Bayesian(HB)model for local and regional flood frequency analysis in the Dongting Lake Basin,in China.The annual maximum daily flows from 15 streamflow-gauged sites in the study are...This study developed a hierarchical Bayesian(HB)model for local and regional flood frequency analysis in the Dongting Lake Basin,in China.The annual maximum daily flows from 15 streamflow-gauged sites in the study area were analyzed with the HB model.The generalized extreme value(GEV)distribution was selected as the extreme flood distribution,and the GEV distribution location and scale parameters were spatially modeled through a regression approach with the drainage area as a covariate.The Markov chain Monte Carlo(MCMC)method with Gibbs sampling was employed to calculate the posterior distribution in the HB model.The results showed that the proposed HB model provided satisfactory Bayesian credible intervals for flood quantiles,while the traditional delta method could not provide reliable uncertainty estimations for large flood quantiles,due to the fact that the lower confidence bounds tended to decrease as the return periods increased.Furthermore,the HB model for regional analysis allowed for a reduction in the value of some restrictive assumptions in the traditional index flood method,such as the homogeneity region assumption and the scale invariance assumption.The HB model can also provide an uncertainty band of flood quantile prediction at a poorly gauged or ungauged site,but the index flood method with L-moments does not demonstrate this uncertainty directly.Therefore,the HB model is an effective method of implementing the flexible local and regional frequency analysis scheme,and of quantifying the associated predictive uncertainty.展开更多
To improve soil carbon sequestration capacity,the full soil carbon cycle process needs to be understood and quantified.It is essential to evaluate whether water erosion acts as a net source or sink of atmospheric CO_(...To improve soil carbon sequestration capacity,the full soil carbon cycle process needs to be understood and quantified.It is essential to evaluate whether water erosion acts as a net source or sink of atmospheric CO_(2)at the basin scale,which encompasses the entire hydrological process.This study introduced an approach that combined a spatially distributed sediment delivery model and biogeochemical model to estimate the lateral and vertical carbon fluxes by water erosion at the basin scale.Applying this coupling model to the Dongting Lake Basin,the results showed that the annual average amount of soil erosion during 1980-2020 was 1.33×10^(8)t,displaying a decreasing trend followed by a slight increase.Only 12% of the soil organic carbon displacement was ultimately lost in the riverine systems,and the rest was deposited downhill within the basin.The average lateral soil organic carbon loss induced by erosion was 8.86×10^(11)g C in 1980 and 1.50×10^(11)g C in 2020,with a decline rate of 83%.A net land sink for atmospheric CO_(2)of 5.54×1011g C a^(-1)occurred during erosion,primarily through sediment burial and dynamic replacement.However,ecological restoration projects and tillage practice policies are still significant in reducing erosion,which could improve the capacity of the carbon sink for recovery beyond the rate of horizontal carbon removal.Moreover,our model enables the spatial explicit simulation of erosion-induced carbon fluxes using costeffective and easily accessible input data across large spatial scales and long timeframes.Consequently,it offers a valuable tool for predicting the interactions between carbon dynamics,land use changes,and future climate.展开更多
基金funded by the National Natural Science Foundation of China(Grant No.72174211)the Natural Science Foundation of Hunan Province(Grant No.2023JJ30693)。
文摘In the face of global warming and increasing impervious surfaces,quantifying the change of climate potential productivity(CPP)is of great significance for the food production planning.Targeting the Dongting Lake Basin,which is a key area for food production in China,this paper uses meteorological data,as well as Climate Change Initiative Land Cover,and Shuttle Radar Topography Mission digital elevation model to investigate the CPP and its changes from 2000 to 2020.The suitability of land for cultivation(SLC),and the land use/land cover change(LUCC)are also considered.The results showed that the CPP varied from 9,825 to 20,895 kg ha^(-1).Even though the newly added impervious surfaces indirectly resulted in the decrease of CPP by of 9.81×10~8 kg,overall,the CPP increased at an average rate of 83.7 kg ha^(-1)a^(-1).Global warming is the strongest driver behind CPP increase,and CPP has played an important role in the conversions between cultivated land and other land types.The structure of land types tends to be optimized against this challenge.
基金supported by the National Natural Science Foundation of China(Grants No.51779074 and 41371052)the Special Fund for the Public Welfare Industry of the Ministry of Water Resources of China(Grant No.201501059)+3 种基金the National Key Research and Development Program of China(Grant No.2017YFC0404304)the Jiangsu Water Conservancy Science and Technology Project(Grant No.2017027)the Program for Outstanding Young Talents in Colleges and Universities of Anhui Province(Grant No.gxyq2018143)the Natural Science Foundation of Wanjiang University of Technology(Grant No.WG18030)
文摘This study developed a hierarchical Bayesian(HB)model for local and regional flood frequency analysis in the Dongting Lake Basin,in China.The annual maximum daily flows from 15 streamflow-gauged sites in the study area were analyzed with the HB model.The generalized extreme value(GEV)distribution was selected as the extreme flood distribution,and the GEV distribution location and scale parameters were spatially modeled through a regression approach with the drainage area as a covariate.The Markov chain Monte Carlo(MCMC)method with Gibbs sampling was employed to calculate the posterior distribution in the HB model.The results showed that the proposed HB model provided satisfactory Bayesian credible intervals for flood quantiles,while the traditional delta method could not provide reliable uncertainty estimations for large flood quantiles,due to the fact that the lower confidence bounds tended to decrease as the return periods increased.Furthermore,the HB model for regional analysis allowed for a reduction in the value of some restrictive assumptions in the traditional index flood method,such as the homogeneity region assumption and the scale invariance assumption.The HB model can also provide an uncertainty band of flood quantile prediction at a poorly gauged or ungauged site,but the index flood method with L-moments does not demonstrate this uncertainty directly.Therefore,the HB model is an effective method of implementing the flexible local and regional frequency analysis scheme,and of quantifying the associated predictive uncertainty.
基金supported by the National Natural Science Foundation of China(Grant No.U19A2047)the Natural Science Foundation of Hunan Province(Grant No.2023JJ20030)。
文摘To improve soil carbon sequestration capacity,the full soil carbon cycle process needs to be understood and quantified.It is essential to evaluate whether water erosion acts as a net source or sink of atmospheric CO_(2)at the basin scale,which encompasses the entire hydrological process.This study introduced an approach that combined a spatially distributed sediment delivery model and biogeochemical model to estimate the lateral and vertical carbon fluxes by water erosion at the basin scale.Applying this coupling model to the Dongting Lake Basin,the results showed that the annual average amount of soil erosion during 1980-2020 was 1.33×10^(8)t,displaying a decreasing trend followed by a slight increase.Only 12% of the soil organic carbon displacement was ultimately lost in the riverine systems,and the rest was deposited downhill within the basin.The average lateral soil organic carbon loss induced by erosion was 8.86×10^(11)g C in 1980 and 1.50×10^(11)g C in 2020,with a decline rate of 83%.A net land sink for atmospheric CO_(2)of 5.54×1011g C a^(-1)occurred during erosion,primarily through sediment burial and dynamic replacement.However,ecological restoration projects and tillage practice policies are still significant in reducing erosion,which could improve the capacity of the carbon sink for recovery beyond the rate of horizontal carbon removal.Moreover,our model enables the spatial explicit simulation of erosion-induced carbon fluxes using costeffective and easily accessible input data across large spatial scales and long timeframes.Consequently,it offers a valuable tool for predicting the interactions between carbon dynamics,land use changes,and future climate.