In this study,SRTM DEM data and ASTER GDEM data were used as the basic topographic data,and Arc Hydro Tools was utilized for extension module so as to study on extracting digital drainage network of watershed based on...In this study,SRTM DEM data and ASTER GDEM data were used as the basic topographic data,and Arc Hydro Tools was utilized for extension module so as to study on extracting digital drainage network of watershed based on surface runoff model,as well as to compare the two extracted results.The result showed that through the introduction of drainage density parameter to determine the river drainage area threshold,the both extracted drainages showed the goodness-of-fit with the factual drainage network on 1∶250 000 scale topographic map,and the extracted digital river could be used in practical operation of the risk assessment model of mountain torrents disaster in Liaohe basin.展开更多
Catchments health assessment is fundamental to effective catchments management. Generally, an assessment method should be selected to reflect both the purpose of assessment and local characteristics. A trial in Shangh...Catchments health assessment is fundamental to effective catchments management. Generally, an assessment method should be selected to reflect both the purpose of assessment and local characteristics. A trial in Shanghai was conducted to test the method for catchments health assessment in urbanized fiver network area. Seven indicators that described four dimensions of river, river network, land use and function, and local feature were used to assess catchments values; while possible change rate of urbanization and industrialization in the next 3 years were chosen for catchments pressure assessment in the value-pressure model. Factors related to catchments classification, indicators measurement and protection priority have been considered in the development strategies for catchments health management. The results showed that value-pressure assessment was applicable in urbanized catchments health management, particularly when both human and catchments had multiple demands. As a result of over 30-year rapid urbanization, more than 70% of Shanghai fiver network area was still in a healthy condition with high catchments values, among them, 39.3% was under high pressure. Poor water quality, simplified river system and weakened local feature of fiver pattern had largely affected catchments health in Shanghai. Lack of long-term monitoring data would seriously restrict the development and validity of catchments health assessment.展开更多
The paper describes the application of SDSM （statistical downscaling model） and ANNs （artificial neural networks） models for prediction of the hydrological trend due to the climate-change. The SDSM has been calibr...The paper describes the application of SDSM （statistical downscaling model） and ANNs （artificial neural networks） models for prediction of the hydrological trend due to the climate-change. The SDSM has been calibrated and generated for the possible future scenarios of meteorological variables, which are temperature and rainfall by using GCMs （global climate models）. The GCM used is SRES A2. The downscaled meteorological variables corresponding to SDSM were then used as input to the ANNs model calibrated with observed station data to simulate the corresponding future streamflow changes in the sub-catchment of Kurau River. This study has discovered the hydrological trend over the catchment. The projected monthly streamflow has shown a decreasing trend due to the increase in the, mean of temperature for overall months, except the month of August and November.展开更多
基金Supported by National Science and Technology Support Project(2008BAK49B07)~~
文摘In this study,SRTM DEM data and ASTER GDEM data were used as the basic topographic data,and Arc Hydro Tools was utilized for extension module so as to study on extracting digital drainage network of watershed based on surface runoff model,as well as to compare the two extracted results.The result showed that through the introduction of drainage density parameter to determine the river drainage area threshold,the both extracted drainages showed the goodness-of-fit with the factual drainage network on 1∶250 000 scale topographic map,and the extracted digital river could be used in practical operation of the risk assessment model of mountain torrents disaster in Liaohe basin.
基金Under the auspices of Shanghai Natural Science Foundation (No. 09ZR1409100)National Natural Science Foundation of China (No. 40871016)Key Program of National Natural Science Foundation of China (No. 40730526)
文摘Catchments health assessment is fundamental to effective catchments management. Generally, an assessment method should be selected to reflect both the purpose of assessment and local characteristics. A trial in Shanghai was conducted to test the method for catchments health assessment in urbanized fiver network area. Seven indicators that described four dimensions of river, river network, land use and function, and local feature were used to assess catchments values; while possible change rate of urbanization and industrialization in the next 3 years were chosen for catchments pressure assessment in the value-pressure model. Factors related to catchments classification, indicators measurement and protection priority have been considered in the development strategies for catchments health management. The results showed that value-pressure assessment was applicable in urbanized catchments health management, particularly when both human and catchments had multiple demands. As a result of over 30-year rapid urbanization, more than 70% of Shanghai fiver network area was still in a healthy condition with high catchments values, among them, 39.3% was under high pressure. Poor water quality, simplified river system and weakened local feature of fiver pattern had largely affected catchments health in Shanghai. Lack of long-term monitoring data would seriously restrict the development and validity of catchments health assessment.
文摘The paper describes the application of SDSM （statistical downscaling model） and ANNs （artificial neural networks） models for prediction of the hydrological trend due to the climate-change. The SDSM has been calibrated and generated for the possible future scenarios of meteorological variables, which are temperature and rainfall by using GCMs （global climate models）. The GCM used is SRES A2. The downscaled meteorological variables corresponding to SDSM were then used as input to the ANNs model calibrated with observed station data to simulate the corresponding future streamflow changes in the sub-catchment of Kurau River. This study has discovered the hydrological trend over the catchment. The projected monthly streamflow has shown a decreasing trend due to the increase in the, mean of temperature for overall months, except the month of August and November.
