To assess the impact of climate change on water quality in an impounded river basin, this study estimated future air temperature and rainfall in the years of 2020, 2050 and 2080 by statistically downscaling the simulation results from two GCM models combined with two emission scenarios (A2 and B1). ...
To assess the impact of climate change on water quality in an impounded river basin, this study estimated future air temperature and rainfall in the years of 2020, 2050 and 2080 by statistically downscaling the simulation results from two GCM models combined with two emission scenarios (A2 and B1). Both scenarios were selected from the Special Report on Emission Scenarios (SRES) suggested by IPCC. The A2 scenario represents an extreme condition whereas the B1 scenario represents a clean and energy efficient condition which is similar to that of study basin. Under the consideration of long-term time scale, the change in land use was predicted using the Neural Network model. With the results of estimated climate factors and land use data, the discharge and the concentrations of BOD, TN and TP in the Andong and Hapcheon dam basins were simulated using the SWAT model. In addition, the future inflow and water quality according to the construction of the Youngju multipurpose dam were simulated using the reservoir water quality model, which coupled the EFDC and the WASP models, using the rainfall and water temperature data extracted from this study. The change in water quality (BOD, TN and TP) was analyzed for each climate change scenario before and after the construction of the dam. The estimated monthly mean air temperature was generally increased in both the A2 and B1 scenarios from 2020 to 2080. The increase in annual air temperature was greater in the A2 scenario than the B1 scenario. The change in the estimated rainfall was also greater in the A2 scenario which represents an extreme condition than the B1 scenario. The rainfall was greatly increased in the Hapcheon dam basin. The monthly mean rainfall was decreased in May, June and October regardless of the A2 and B1 scenarios and was increased in the other months. The results from the future land use simulation using the Neural Network model indicated general increase of urbanization and unused land. The simulation of discharge and water quality using the SWAT model coupled with the predicted land use and the estimated air temperature and rainfall showed that monthly discharge in the dam basins was decreased in May and June, whose rainfall is relatively small, and was increased rapidly until September, but the degree of the increase shrank quickly. In February, the rainfall was not much, but the snowmelt contributed the increased discharge. The range of annual discharge increase was elevated from 2020 to 2080. Among water quality components in the dam basins, the concentration of BOD which is greatly affected by air temperature and discharge was increased from 2020 to 2080 due to the increase in water temperature. The monthly mean BOD concentration showed tendency to increase in the concentration and the range of increase during March ? June having relatively smaller rainfall and higher water temperature, to decrease in the concentration in summer months due to higher discharge after rainfall, and to increase in the concentration gradually since October. The change in BOD concentration for the B1 emission scenario was greater than the A2 scenario in the annual increase range and the pollution level. The concentration of TN was decreased during March ? June which is drought period and increased again afterward. After the year 2080, TN was greater in every month than the present regardless of the climate scenarios, except for August and September. In contrast to TN, the concentration of TP was generally decreased. The annual TP concentration indicated a more significant decrease in the drought period in 2080 than 2020, which could be attributed to decreased discharge and algal growth. The monthly TP concentration was increased in flood period and decreased in drought period. The change in TP concentration was greater for the B1 scenario than the A2 scenario. The simulation of water quality change in the reservoir after the construction of the dam in the future exhibited that the concentrations of BOD and TN were somewhat increased and the concentration of TP was decreased from 2020 to 2080. The A2 scenario simulated higher TN and TP concentrations with lower BOD than the B1 scenario. The results from two downscaled GCM models based on the A2 and B1 emission scenarios of the IPCC in a dammed river basin simulated that the air temperature, discharge, TN and TP concentrations and the ranges in increases were greater for the A2 scenario than the B1 scenario. However, the concentration of BOD was higher for the B1 scenario than the A2 scenario. From the year 2020 to 2080, the air temperature, rainfall, discharge, BOD and TN were increased, except for TP concentration. The additional studies about the relationship among the changes in air temperature, discharge and water quality as well as the uncertainty in water quality simulation are requested. It is expected that the results of this study can contribute to the establishment of water resources and water environment policies.
To assess the impact of climate change on water quality in an impounded river basin, this study estimated future air temperature and rainfall in the years of 2020, 2050 and 2080 by statistically downscaling the simulation results from two GCM models combined with two emission scenarios (A2 and B1). Both scenarios were selected from the Special Report on Emission Scenarios (SRES) suggested by IPCC. The A2 scenario represents an extreme condition whereas the B1 scenario represents a clean and energy efficient condition which is similar to that of study basin. Under the consideration of long-term time scale, the change in land use was predicted using the Neural Network model. With the results of estimated climate factors and land use data, the discharge and the concentrations of BOD, TN and TP in the Andong and Hapcheon dam basins were simulated using the SWAT model. In addition, the future inflow and water quality according to the construction of the Youngju multipurpose dam were simulated using the reservoir water quality model, which coupled the EFDC and the WASP models, using the rainfall and water temperature data extracted from this study. The change in water quality (BOD, TN and TP) was analyzed for each climate change scenario before and after the construction of the dam. The estimated monthly mean air temperature was generally increased in both the A2 and B1 scenarios from 2020 to 2080. The increase in annual air temperature was greater in the A2 scenario than the B1 scenario. The change in the estimated rainfall was also greater in the A2 scenario which represents an extreme condition than the B1 scenario. The rainfall was greatly increased in the Hapcheon dam basin. The monthly mean rainfall was decreased in May, June and October regardless of the A2 and B1 scenarios and was increased in the other months. The results from the future land use simulation using the Neural Network model indicated general increase of urbanization and unused land. The simulation of discharge and water quality using the SWAT model coupled with the predicted land use and the estimated air temperature and rainfall showed that monthly discharge in the dam basins was decreased in May and June, whose rainfall is relatively small, and was increased rapidly until September, but the degree of the increase shrank quickly. In February, the rainfall was not much, but the snowmelt contributed the increased discharge. The range of annual discharge increase was elevated from 2020 to 2080. Among water quality components in the dam basins, the concentration of BOD which is greatly affected by air temperature and discharge was increased from 2020 to 2080 due to the increase in water temperature. The monthly mean BOD concentration showed tendency to increase in the concentration and the range of increase during March ? June having relatively smaller rainfall and higher water temperature, to decrease in the concentration in summer months due to higher discharge after rainfall, and to increase in the concentration gradually since October. The change in BOD concentration for the B1 emission scenario was greater than the A2 scenario in the annual increase range and the pollution level. The concentration of TN was decreased during March ? June which is drought period and increased again afterward. After the year 2080, TN was greater in every month than the present regardless of the climate scenarios, except for August and September. In contrast to TN, the concentration of TP was generally decreased. The annual TP concentration indicated a more significant decrease in the drought period in 2080 than 2020, which could be attributed to decreased discharge and algal growth. The monthly TP concentration was increased in flood period and decreased in drought period. The change in TP concentration was greater for the B1 scenario than the A2 scenario. The simulation of water quality change in the reservoir after the construction of the dam in the future exhibited that the concentrations of BOD and TN were somewhat increased and the concentration of TP was decreased from 2020 to 2080. The A2 scenario simulated higher TN and TP concentrations with lower BOD than the B1 scenario. The results from two downscaled GCM models based on the A2 and B1 emission scenarios of the IPCC in a dammed river basin simulated that the air temperature, discharge, TN and TP concentrations and the ranges in increases were greater for the A2 scenario than the B1 scenario. However, the concentration of BOD was higher for the B1 scenario than the A2 scenario. From the year 2020 to 2080, the air temperature, rainfall, discharge, BOD and TN were increased, except for TP concentration. The additional studies about the relationship among the changes in air temperature, discharge and water quality as well as the uncertainty in water quality simulation are requested. It is expected that the results of this study can contribute to the establishment of water resources and water environment policies.
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#기후변화 수질측정 수질변화 수자원영향
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