The feasibility of rooftop rainwater harvesting （RRWH） as an alternative source of water to meet the outdoor water demand in nine states of the U.S. was evaluated using a system dynamics model developed in Systems T...The feasibility of rooftop rainwater harvesting （RRWH） as an alternative source of water to meet the outdoor water demand in nine states of the U.S. was evaluated using a system dynamics model developed in Systems Thinking, Experimental Learning Laboratory with Animation. The state of Arizona was selected to evaluate the effects of the selected model parameters on the efficacy of RRWH since among the nine states the arid region of Arizona showed the least potential of meeting the outdoor water demand with rain harvested water. The analyses were conducted on a monthly basis across a 10-year projected period from 2015 to 2024. The results showed that RRWH as a potential source of water was highly sensitive to certain model parameters such as the outdoor water demand, the use of desert landscaping, and the percentage of existing houses with RRWH. A significant difference （as high as 37.5%） in rainwater potential was observed between the projected wet and dry climate conditions in Arizona. The analysis of the dynamics of the storage tanks suggested that a 1.0-2.0 m3 rainwater barrel, on an average, can store approximately 80% of the monthly rainwater generated from the rooftops in Arizona, even across the high seasonal variation. This interactive model can be used as a quick estimator of the amount of water that could be generated, stored, and utilized through RRWH systems in the U.S. under different climate conditions. The findings of such comprehensive analyses may help regional policymakers, especially in arid regions, to develop a sustainable water management infrastructure.展开更多
Long-range precipitation forecasts are useful when managing water supplies.Oceanicatmospheric oscillations have been shown to influence precipitation.Due to a longer cycle of some of the oscillations,a short instrumen...Long-range precipitation forecasts are useful when managing water supplies.Oceanicatmospheric oscillations have been shown to influence precipitation.Due to a longer cycle of some of the oscillations,a short instrumental record is a limitation in using them for long-range precipitation forecasts.The influence of oscillations over precipitation is observable within paleoclimate reconstructions;however,there have been no attempts to utilize these reconstructions in precipitation forecasting.A data-driven model,KStar,is used for obtaining long-range precipitation forecasts by extending the period of record through the use of reconstructions of oscillations.KStar is a nearest neighbor algorithm with an entropy-based distance function.Oceanic-atmospheric oscillation reconstructions include the El Nino-Southern Oscillation(ENSO),the Pacific Decadal Oscillation(PDO),the North Atlantic Oscillation(NAO),and the Atlantic Multi-decadal Oscillation(AMO).Precipitation is forecasted for 20 climate divisions in the western United States.A 10-year moving average is applied to aid in the identification of oscillation phases.A lead time approach is used to simulate a one-year forecast,with a 10-fold cross-validation technique to test the models.Reconstructions are used from 1658-1899,while the observed record is used from 1900-2007.The model is evaluated using mean absolute error(MAE),root mean squared error(RMSE),RMSE-observations standard deviation ratio(RSR),Pearson's correlation coefficient(R),NashSutcliffe coefficient of efficiency(NSE),and linear error in probability space(LEPS) skill score(SK).The role of individual and coupled oscillations is evaluated by dropping oscillations in the model.The results indicate 'good' precipitation estimates using the KStar model.This modeling technique is expected to be useful for long-term water resources planning and management.展开更多
Hydrologic analysis in watersheds lacking rain gauge stations has been a challenge and even those with stations that do not contain the required amount of data create problems in model verification.So,the study integr...Hydrologic analysis in watersheds lacking rain gauge stations has been a challenge and even those with stations that do not contain the required amount of data create problems in model verification.So,the study integrates the Next Generation Weather RadarIII precipitation data and the Personal Computer Storm Water Management Model(PCSWMM)for evaluating the model's effectiveness.The study further integrates 100-year return period precipitation intensity and PCSWMM to generate a one-dimensionalflood risk zone map,which shows the major sub-catchments under risk zones.Based on the identification of risk zones from PCSWMM,three different low-impact developments(LIDs),street plants,infiltration trenches,and green roofs are applied independently and uniformly to compare the decrease inflow.Thereafter,the prioritized list of critical sub-catchments from hydraulic modeling is compared with the compromise programming method,an approach for studying the decrement inflow by increasing LID application(infiltration trench)in thefirstfive critical sub-catchments,suggesting planners and researchers identify the most critical sub-catchments and develop future potential strategies.展开更多
文摘The feasibility of rooftop rainwater harvesting （RRWH） as an alternative source of water to meet the outdoor water demand in nine states of the U.S. was evaluated using a system dynamics model developed in Systems Thinking, Experimental Learning Laboratory with Animation. The state of Arizona was selected to evaluate the effects of the selected model parameters on the efficacy of RRWH since among the nine states the arid region of Arizona showed the least potential of meeting the outdoor water demand with rain harvested water. The analyses were conducted on a monthly basis across a 10-year projected period from 2015 to 2024. The results showed that RRWH as a potential source of water was highly sensitive to certain model parameters such as the outdoor water demand, the use of desert landscaping, and the percentage of existing houses with RRWH. A significant difference （as high as 37.5%） in rainwater potential was observed between the projected wet and dry climate conditions in Arizona. The analysis of the dynamics of the storage tanks suggested that a 1.0-2.0 m3 rainwater barrel, on an average, can store approximately 80% of the monthly rainwater generated from the rooftops in Arizona, even across the high seasonal variation. This interactive model can be used as a quick estimator of the amount of water that could be generated, stored, and utilized through RRWH systems in the U.S. under different climate conditions. The findings of such comprehensive analyses may help regional policymakers, especially in arid regions, to develop a sustainable water management infrastructure.
文摘Long-range precipitation forecasts are useful when managing water supplies.Oceanicatmospheric oscillations have been shown to influence precipitation.Due to a longer cycle of some of the oscillations,a short instrumental record is a limitation in using them for long-range precipitation forecasts.The influence of oscillations over precipitation is observable within paleoclimate reconstructions;however,there have been no attempts to utilize these reconstructions in precipitation forecasting.A data-driven model,KStar,is used for obtaining long-range precipitation forecasts by extending the period of record through the use of reconstructions of oscillations.KStar is a nearest neighbor algorithm with an entropy-based distance function.Oceanic-atmospheric oscillation reconstructions include the El Nino-Southern Oscillation(ENSO),the Pacific Decadal Oscillation(PDO),the North Atlantic Oscillation(NAO),and the Atlantic Multi-decadal Oscillation(AMO).Precipitation is forecasted for 20 climate divisions in the western United States.A 10-year moving average is applied to aid in the identification of oscillation phases.A lead time approach is used to simulate a one-year forecast,with a 10-fold cross-validation technique to test the models.Reconstructions are used from 1658-1899,while the observed record is used from 1900-2007.The model is evaluated using mean absolute error(MAE),root mean squared error(RMSE),RMSE-observations standard deviation ratio(RSR),Pearson's correlation coefficient(R),NashSutcliffe coefficient of efficiency(NSE),and linear error in probability space(LEPS) skill score(SK).The role of individual and coupled oscillations is evaluated by dropping oscillations in the model.The results indicate 'good' precipitation estimates using the KStar model.This modeling technique is expected to be useful for long-term water resources planning and management.
基金University of Illinois System,Grant/Award Number:#107688。
文摘Hydrologic analysis in watersheds lacking rain gauge stations has been a challenge and even those with stations that do not contain the required amount of data create problems in model verification.So,the study integrates the Next Generation Weather RadarIII precipitation data and the Personal Computer Storm Water Management Model(PCSWMM)for evaluating the model's effectiveness.The study further integrates 100-year return period precipitation intensity and PCSWMM to generate a one-dimensionalflood risk zone map,which shows the major sub-catchments under risk zones.Based on the identification of risk zones from PCSWMM,three different low-impact developments(LIDs),street plants,infiltration trenches,and green roofs are applied independently and uniformly to compare the decrease inflow.Thereafter,the prioritized list of critical sub-catchments from hydraulic modeling is compared with the compromise programming method,an approach for studying the decrement inflow by increasing LID application(infiltration trench)in thefirstfive critical sub-catchments,suggesting planners and researchers identify the most critical sub-catchments and develop future potential strategies.
