Arid
DOI10.1080/15567036.2018.1476934
Integration of time series forecasting in a dynamic decision support system for multiple reservoir management to conserve water sources
Sabzi, Hamed Zamani1; Abudu, Shalamu2; Alizadeh, Reza3; Soltanisehat, Leili4; Dilekli, Naci1; King, James Phillip5
通讯作者Sabzi, Hamed Zamani
来源期刊ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS
ISSN1556-7036
EISSN1556-7230
出版年2018
卷号40期号:11页码:1398-1416
英文摘要

In most of arid and semi-arid regions, there are limited sources of available fresh water for different domestic and environmental demands. Strategic and parsimonious fresh water-use in water-scarce areas such as Southern New Mexico is crucially important. Elephant Butte and Caballo reservoirs are two integrated reservoirs in this region that provide water supply for many water users in downstream areas. Since Elephant Butte Reservoir is in a semi-arid region, it would be rational to utilize other energy sources such as wind energy to produce electricity and use the water supply to other critical demands in terms of time and availability. This study develops a strategy of optimal management of two integrated reservoirs to quantify the savable volume of water sources through optimal operation management. To optimize operations for the Elephant Butte and Caballo reservoirs as an integrated reservoir operation in New Mexico, the authors in this case study utilized two autoregressive integrated moving average models, one non-seasonal (daily, ARIMA model) and one seasonal (monthly, SARIMA model), to predict daily and monthly inflows to the Elephant Butte Reservoir. The coefficient of determination between predicted and observed daily values and the normalized mean of absolute error (NMAE) were 0.97 and 0.09, respectively, indicating that the daily ARIMA prediction model was significantly reliable and accurate for a univariate based streamflow forecast model. The developed time series prediction models were incorporated in a decision support system, which utilizes the predicted values for a day and a month ahead and leads to save significant amount of water volume by providing the optimal release schedule from Elephant Butte into the Caballo Reservoir. The predicted daily and monthly values from the developed ARIMA prediction models were integrated successfully with the dynamic operation model, which provides the optimal operation plans. The optimal operation plan significantly minimizes the total evaporation loss from both reservoirs by providing the optimal storage levels in both reservoirs. The saved volume of the water would be considered as a significant water supply for environmental conservation actions in downstream of the Caballo Reservoir. Providing an integrated optimal management plan for two reservoirs led to save significant water sources in a region that water shortage has led to significant environmental consequences. Finally, since the models are univariate, they demonstrate an approach for reliable inflow prediction when information is limited to only streamflow values. We find that hydroelectric power generation forces the region to lose significant amount of water to evaporation and therefore hinder the optimal use of freshwater. Based on these findings, we conclude that a water scarce region like Southern New Mexico should gain independence from hydroelectric power and save the freshwater for supporting ecosystem services and environmental purposes.


英文关键词ARIMA Decision support systems dynamic systems reservoir management sarima time series analysis
类型Article
语种英语
国家USA
收录类别SCI-E
WOS记录号WOS:000434399800013
WOS关键词OPTIMIZATION ; OPERATION ; MODELS ; PERFORMANCE ; UNCERTAINTY ; STREAMFLOW ; ENERGY
WOS类目Energy & Fuels ; Engineering, Chemical ; Environmental Sciences
WOS研究方向Energy & Fuels ; Engineering ; Environmental Sciences & Ecology
来源机构New Mexico State University
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/208928
作者单位1.Univ Oklahoma, Dept Geog & Environm Sustainabil, Norman, OK 73019 USA;
2.New Mexico Interstate Stream Commiss, Albuquerque, NM USA;
3.Univ Oklahoma, Syst Realizat Lab, Norman, OK 73019 USA;
4.Old Dominion Univ, Dept Engn Management & Syst Engn, Norfolk, VA 23529 USA;
5.New Mexico State Univ, Dept Civil Engn, Las Cruces, NM 88003 USA
推荐引用方式
GB/T 7714
Sabzi, Hamed Zamani,Abudu, Shalamu,Alizadeh, Reza,et al. Integration of time series forecasting in a dynamic decision support system for multiple reservoir management to conserve water sources[J]. New Mexico State University,2018,40(11):1398-1416.
APA Sabzi, Hamed Zamani,Abudu, Shalamu,Alizadeh, Reza,Soltanisehat, Leili,Dilekli, Naci,&King, James Phillip.(2018).Integration of time series forecasting in a dynamic decision support system for multiple reservoir management to conserve water sources.ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS,40(11),1398-1416.
MLA Sabzi, Hamed Zamani,et al."Integration of time series forecasting in a dynamic decision support system for multiple reservoir management to conserve water sources".ENERGY SOURCES PART A-RECOVERY UTILIZATION AND ENVIRONMENTAL EFFECTS 40.11(2018):1398-1416.
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