The precipitation recharge coefficient(PRC), representing the amount of groundwater recharge from precipitation, is an important parameter for groundwater resources evaluation and numerical simulation. It was usually ...The precipitation recharge coefficient(PRC), representing the amount of groundwater recharge from precipitation, is an important parameter for groundwater resources evaluation and numerical simulation. It was usually obtained from empirical knowledge and site experiments in the 1980 s. However, the environmental settings have been greatly modified from that time due to land use change and groundwater over-pumping, especially in the Beijing plain area(BPA). This paper aims to estimate and analyze PRC of BPA with the distributed hydrological model and GIS for the year 2011 with similar annual precipitation as long-term mean. It is found that the recharge from vertical(precipitation + irrigation) and precipitation is 291.0 mm/yr and 233.7 mm/yr, respectively, which accounts for 38.6% and 36.6% of corresponding input water. The regional mean PRC is 0.366, which is a little different from the traditional map. However, it has a spatial variation ranging from –7.0% to 17.5% for various sub-regions. Since the vadose zone is now much thicker than the evaporation extinction depth, the land cover is regarded as the major dynamic factor that causes the variation of PRC in this area due to the difference of evapotranspiration rates. It is suggested that the negative impact of reforestation on groundwater quantity within BPA should be well investigated, because the PRC beneath forestland is the smallest among all land cover types.展开更多
This paper introduces the process of development and practical use implementation of an advanced river management system for supporting integrated water resources management practices in Asian river basins under the f...This paper introduces the process of development and practical use implementation of an advanced river management system for supporting integrated water resources management practices in Asian river basins under the framework of GEOSS Asia water cycle initiative （AWCI）. The system is based on integration of data from earth observation satellites and in-situ networks with other types of data, including numerical weather prediction model outputs, climate model outputs, geographical infor- mation, and socio-economic data. The system builds on the water and energy budget distributed hydrological model （WEB-DHM） that was adapted for specific conditions of studied basins, in particular snow and glacier phenomena and equipped with other functions such as dam operation optimization scheme and a set of tools for climate change impact assess- ment to be able to generate relevant information for policy and decision makers. In situ data were archived for 18 selected ba- sins at the Data Integration and Analysis System （DIAS） of Japan and demonstration projects were carded out showing poten- tial of the new system. It included climate change impact assessment on hydrological regimes, which is presently a critical step for sound management decisions. Results of such three case studies in Pakistan, Philippines, and Vietnam are provided here.展开更多
Identifying the underlying mechanisms that influence the spatial patterns in populations improves the forecasts of the alternative management strategies on the spatial dynamics of the populations, which are critical f...Identifying the underlying mechanisms that influence the spatial patterns in populations improves the forecasts of the alternative management strategies on the spatial dynamics of the populations, which are critical for assessing and managing the fisheries and improving the water resource management. This paper described a new approach of the numerical model for the prediction of the aquatic animal distribution in the flows. The model was developed based on the kinetic theory of gases, the mechanism of the aquatic animal movement and the flow hydrodynamic patterns. The model was validated using the available experimental data and an acceptable agreement was obtained. A comprehensive parameter study was then conducted to help understand the impact and the sensitivity of each parameter to the aquatic animal distribution. The promising results of the model reveal the prospect of applying this model to the reliable prediction of the aquatic animal distribution within a relatively large water area.展开更多
基金Under the auspices of Beijing Natural Science Foundation(No.8152012)National Natural Science Foundation of China(No.41101033,41130744,41171335)
文摘The precipitation recharge coefficient(PRC), representing the amount of groundwater recharge from precipitation, is an important parameter for groundwater resources evaluation and numerical simulation. It was usually obtained from empirical knowledge and site experiments in the 1980 s. However, the environmental settings have been greatly modified from that time due to land use change and groundwater over-pumping, especially in the Beijing plain area(BPA). This paper aims to estimate and analyze PRC of BPA with the distributed hydrological model and GIS for the year 2011 with similar annual precipitation as long-term mean. It is found that the recharge from vertical(precipitation + irrigation) and precipitation is 291.0 mm/yr and 233.7 mm/yr, respectively, which accounts for 38.6% and 36.6% of corresponding input water. The regional mean PRC is 0.366, which is a little different from the traditional map. However, it has a spatial variation ranging from –7.0% to 17.5% for various sub-regions. Since the vadose zone is now much thicker than the evaporation extinction depth, the land cover is regarded as the major dynamic factor that causes the variation of PRC in this area due to the difference of evapotranspiration rates. It is suggested that the negative impact of reforestation on groundwater quantity within BPA should be well investigated, because the PRC beneath forestland is the smallest among all land cover types.
基金the Asia Pacific Network for Global Change Research(APN)for financial support of the AWCI activities through several projects funded under the APN programmes
文摘This paper introduces the process of development and practical use implementation of an advanced river management system for supporting integrated water resources management practices in Asian river basins under the framework of GEOSS Asia water cycle initiative （AWCI）. The system is based on integration of data from earth observation satellites and in-situ networks with other types of data, including numerical weather prediction model outputs, climate model outputs, geographical infor- mation, and socio-economic data. The system builds on the water and energy budget distributed hydrological model （WEB-DHM） that was adapted for specific conditions of studied basins, in particular snow and glacier phenomena and equipped with other functions such as dam operation optimization scheme and a set of tools for climate change impact assess- ment to be able to generate relevant information for policy and decision makers. In situ data were archived for 18 selected ba- sins at the Data Integration and Analysis System （DIAS） of Japan and demonstration projects were carded out showing poten- tial of the new system. It included climate change impact assessment on hydrological regimes, which is presently a critical step for sound management decisions. Results of such three case studies in Pakistan, Philippines, and Vietnam are provided here.
基金supported by the National Natural Science Foundation of China(Grant Nos.51139003&11372161)
文摘Identifying the underlying mechanisms that influence the spatial patterns in populations improves the forecasts of the alternative management strategies on the spatial dynamics of the populations, which are critical for assessing and managing the fisheries and improving the water resource management. This paper described a new approach of the numerical model for the prediction of the aquatic animal distribution in the flows. The model was developed based on the kinetic theory of gases, the mechanism of the aquatic animal movement and the flow hydrodynamic patterns. The model was validated using the available experimental data and an acceptable agreement was obtained. A comprehensive parameter study was then conducted to help understand the impact and the sensitivity of each parameter to the aquatic animal distribution. The promising results of the model reveal the prospect of applying this model to the reliable prediction of the aquatic animal distribution within a relatively large water area.
