With realizing the importance of ecosystem services to society, the efforts to evaluate the ecosystem services have increased. As the largest tributary of the Yellow River, the Weihe River has been endowed with many e...With realizing the importance of ecosystem services to society, the efforts to evaluate the ecosystem services have increased. As the largest tributary of the Yellow River, the Weihe River has been endowed with many ecological service functions. Among which, water yield can be a measure of local availability of water and an index for evaluating the conservation function of the region. This study aimed to explore the temporal and spatial variation of water yield and its influencing factors in the Weihe River Basin(WRB), and provide basis for formulating reasonable water resources utilization schemes. Based on the InVEST(integrated valuation of ecosystem services and tradeoffs) model, this study simulated the water yield in the WRB from 1985 to 2019, and discussed the impacts of climatic factors and land use change on water yield by spatial autocorrelation analysis and scenario analysis methods. The results showed that there was a slight increasing trend in water yield in the WRB over the study period with the increasing rate of 4.84 mm/10a and an average depth of 83.14 mm. The main water-producing areas were concentrated along the mainstream of the Weihe River and in the southern basin. Changes in water yield were comprehensively affected by climate and underlying surface factors. Precipitation was the main factor affecting water yield, which was consistent with water yield in time. And there existed significant spatial agglomeration between water yield and precipitation. Land use had little impact on the amount of water yield, but had an impact on its spatial distribution. Water yield was higher in areas with wide distribution of construction land and grassland. Water yield of different land use types were different. Unused land showed the largest water yield capacity, whereas grassland and farmland contributed most to the total water yield. The increasing water yield in the basin indicates an enhanced water supply service function of the ecosystem. These results are of great significance to the water resources management of the WRB.展开更多
Extreme precipitation events bring considerable risks to the natural ecosystem and human life.Investigating the spatial-temporal characteristics of extreme precipitation and predicting it quantitatively are critical f...Extreme precipitation events bring considerable risks to the natural ecosystem and human life.Investigating the spatial-temporal characteristics of extreme precipitation and predicting it quantitatively are critical for the flood prevention and water resources planning and management.In this study,daily precipitation data(1957–2019)were collected from 24 meteorological stations in the Weihe River Basin(WRB),Northwest China and its surrounding areas.We first analyzed the spatial-temporal change of precipitation extremes in the WRB based on space-time cube(STC),and then predicted precipitation extremes using long short-term memory(LSTM)network,auto-regressive integrated moving average(ARIMA),and hybrid ensemble empirical mode decomposition(EEMD)-LSTM-ARIMA models.The precipitation extremes increased as the spatial variation from northwest to southeast of the WRB.There were two clusters for each extreme precipitation index,which were distributed in the northwestern and southeastern or northern and southern of the WRB.The precipitation extremes in the WRB present a strong clustering pattern.Spatially,the pattern of only high-high cluster and only low-low cluster were primarily located in lower reaches and upper reaches of the WRB,respectively.Hot spots(25.00%–50.00%)were more than cold spots(4.17%–25.00%)in the WRB.Cold spots were mainly concentrated in the northwestern part,while hot spots were mostly located in the eastern and southern parts.For different extreme precipitation indices,the performances of the different models were different.The accuracy ranking was EEMD-LSTM-ARIMA>LSTM>ARIMA in predicting simple daily intensity index(SDII)and consecutive wet days(CWD),while the accuracy ranking was LSTM>EEMD-LSTM-ARIMA>ARIMA in predicting very wet days(R95 P).The hybrid EEMD-LSTM-ARIMA model proposed was generally superior to single models in the prediction of precipitation extremes.展开更多
Exploring the current runoff characteristics after the large-scale implementation of the Grain for Green(GFG)project and investigating its sensitivities to potential drivers are crucial for water resource prediction a...Exploring the current runoff characteristics after the large-scale implementation of the Grain for Green(GFG)project and investigating its sensitivities to potential drivers are crucial for water resource prediction and management.Based on the measured runoff data of 62 hydrological stations in the Weihe River Basin(WRB)from 2006 to 2018,we analyzed the temporal and spatial runoff characteristics in this study.Correlation analysis was used to investigate the relationships between different runoff indicators and climate-related factors.Additionally,an improved Budyko framework was applied to assess the sensitivities of annual runoff to precipitation,potential evaporation,and other factors.The results showed that the daily runoff flow duration curves(FDCs)of all selected hydrological stations fall in three narrow ranges,with the corresponding mean annual runoff spanning approximately 1.50 orders of magnitude,indicating that the runoff of different hydrological stations in the WRB varied greatly.The trend analysis of runoff under different exceedance frequencies showed that the runoff from the south bank of the Weihe River was more affluent and stable than that from the north bank.The runoff was unevenly distributed throughout the year,mainly in the flood season,accounting for more than 50.00%of the annual runoff.However,the trend of annual runoff change was not obvious in most areas.Correlation analysis showed that rare-frequency runoff events were more susceptible to climate factors.In this study,daily runoff under 10%-20%exceeding frequencies,consecutive maximum daily runoff,and low-runoff variability rate had strong correlations with precipitation,aridity index,and average runoff depth on rainy days.In comparison,daily runoff under 50%-99%exceeding frequencies,consecutive minimum daily runoff,and high-runoff variability rate had weak correlations with all selected impact factors.The sensitivity analysis results suggested that the sensitivity of annual runoff to precipitation was always higher than that to potential evaporation.The runoff about 87.10%of the selected hydrological stations were most sensitive to precipitation changes,and 12.90%were most sensitive to other factors.The spatial pattern of the sensitivity analysis indicated that in relatively humid southern areas,runoff was more sensitive to potential evaporation and other factors,and less sensitive to precipitation.展开更多
基金funded by the National Natural Science Foundation of China(U2243211)。
文摘With realizing the importance of ecosystem services to society, the efforts to evaluate the ecosystem services have increased. As the largest tributary of the Yellow River, the Weihe River has been endowed with many ecological service functions. Among which, water yield can be a measure of local availability of water and an index for evaluating the conservation function of the region. This study aimed to explore the temporal and spatial variation of water yield and its influencing factors in the Weihe River Basin(WRB), and provide basis for formulating reasonable water resources utilization schemes. Based on the InVEST(integrated valuation of ecosystem services and tradeoffs) model, this study simulated the water yield in the WRB from 1985 to 2019, and discussed the impacts of climatic factors and land use change on water yield by spatial autocorrelation analysis and scenario analysis methods. The results showed that there was a slight increasing trend in water yield in the WRB over the study period with the increasing rate of 4.84 mm/10a and an average depth of 83.14 mm. The main water-producing areas were concentrated along the mainstream of the Weihe River and in the southern basin. Changes in water yield were comprehensively affected by climate and underlying surface factors. Precipitation was the main factor affecting water yield, which was consistent with water yield in time. And there existed significant spatial agglomeration between water yield and precipitation. Land use had little impact on the amount of water yield, but had an impact on its spatial distribution. Water yield was higher in areas with wide distribution of construction land and grassland. Water yield of different land use types were different. Unused land showed the largest water yield capacity, whereas grassland and farmland contributed most to the total water yield. The increasing water yield in the basin indicates an enhanced water supply service function of the ecosystem. These results are of great significance to the water resources management of the WRB.
基金Under the auspices of National Key Research and Development Program of China(No.2017YFE0118100-1)。
文摘Extreme precipitation events bring considerable risks to the natural ecosystem and human life.Investigating the spatial-temporal characteristics of extreme precipitation and predicting it quantitatively are critical for the flood prevention and water resources planning and management.In this study,daily precipitation data(1957–2019)were collected from 24 meteorological stations in the Weihe River Basin(WRB),Northwest China and its surrounding areas.We first analyzed the spatial-temporal change of precipitation extremes in the WRB based on space-time cube(STC),and then predicted precipitation extremes using long short-term memory(LSTM)network,auto-regressive integrated moving average(ARIMA),and hybrid ensemble empirical mode decomposition(EEMD)-LSTM-ARIMA models.The precipitation extremes increased as the spatial variation from northwest to southeast of the WRB.There were two clusters for each extreme precipitation index,which were distributed in the northwestern and southeastern or northern and southern of the WRB.The precipitation extremes in the WRB present a strong clustering pattern.Spatially,the pattern of only high-high cluster and only low-low cluster were primarily located in lower reaches and upper reaches of the WRB,respectively.Hot spots(25.00%–50.00%)were more than cold spots(4.17%–25.00%)in the WRB.Cold spots were mainly concentrated in the northwestern part,while hot spots were mostly located in the eastern and southern parts.For different extreme precipitation indices,the performances of the different models were different.The accuracy ranking was EEMD-LSTM-ARIMA>LSTM>ARIMA in predicting simple daily intensity index(SDII)and consecutive wet days(CWD),while the accuracy ranking was LSTM>EEMD-LSTM-ARIMA>ARIMA in predicting very wet days(R95 P).The hybrid EEMD-LSTM-ARIMA model proposed was generally superior to single models in the prediction of precipitation extremes.
基金funded by the National Natural Science Foundation of China(U2243211).
文摘Exploring the current runoff characteristics after the large-scale implementation of the Grain for Green(GFG)project and investigating its sensitivities to potential drivers are crucial for water resource prediction and management.Based on the measured runoff data of 62 hydrological stations in the Weihe River Basin(WRB)from 2006 to 2018,we analyzed the temporal and spatial runoff characteristics in this study.Correlation analysis was used to investigate the relationships between different runoff indicators and climate-related factors.Additionally,an improved Budyko framework was applied to assess the sensitivities of annual runoff to precipitation,potential evaporation,and other factors.The results showed that the daily runoff flow duration curves(FDCs)of all selected hydrological stations fall in three narrow ranges,with the corresponding mean annual runoff spanning approximately 1.50 orders of magnitude,indicating that the runoff of different hydrological stations in the WRB varied greatly.The trend analysis of runoff under different exceedance frequencies showed that the runoff from the south bank of the Weihe River was more affluent and stable than that from the north bank.The runoff was unevenly distributed throughout the year,mainly in the flood season,accounting for more than 50.00%of the annual runoff.However,the trend of annual runoff change was not obvious in most areas.Correlation analysis showed that rare-frequency runoff events were more susceptible to climate factors.In this study,daily runoff under 10%-20%exceeding frequencies,consecutive maximum daily runoff,and low-runoff variability rate had strong correlations with precipitation,aridity index,and average runoff depth on rainy days.In comparison,daily runoff under 50%-99%exceeding frequencies,consecutive minimum daily runoff,and high-runoff variability rate had weak correlations with all selected impact factors.The sensitivity analysis results suggested that the sensitivity of annual runoff to precipitation was always higher than that to potential evaporation.The runoff about 87.10%of the selected hydrological stations were most sensitive to precipitation changes,and 12.90%were most sensitive to other factors.The spatial pattern of the sensitivity analysis indicated that in relatively humid southern areas,runoff was more sensitive to potential evaporation and other factors,and less sensitive to precipitation.
