Optimal Long-term Operation of Reservoir-river Systems under Hydrologic Uncertainties: Application of Interval Programming

Long-term basin-wide reservoir-river operation optimization problems are usually complex and nonlinear especially when the water quality issues and hydrologic uncertainties are incorporated. It is due to non-convex functions in water quality modeling and a large number of computational iterations re...

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Vydané v:Water resources management Ročník 27; číslo 11; s. 3865 - 3883
Hlavní autori: Nikoo, Mohammad Reza, Karimi, Akbar, Kerachian, Reza
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Dordrecht Springer Netherlands 01.09.2013
Springer
Springer Nature B.V
Predmet:
Algorithms
Atmospheric Sciences
Civil Engineering
Earth and Environmental Science
Earth Sciences
Earth, ocean, space
Environment
Exact sciences and technology
Freshwater
Geotechnical Engineering & Applied Earth Sciences
Groundwater
Hydrogeology
hydrologic models
Hydrology
Hydrology. Hydrogeology
Hydrology/Water Resources
Intervals
Linear programming
Long term planning
Mathematical analysis
Mathematical models
model uncertainty
Nonlinear programming
Nonlinearity
Optimization techniques
Programming
Quality management
Reservoirs
River basins
River systems
Rivers
Stream flow
Studies
Surface water
Total dissolved solids
Uncertainty
Water allocation
Water demand
Water pollution
Water quality
Water resources
Water resources management
Water supply
watersheds
wetlands
Middle East
Iran
Asia
Conjunctive use
Interval parameter optimization
Zayandehrood river basin
Nonlinear programming
Water quality
rivers
models
reservoirs
water supply
concentration
linear programming
pollution
surface water
currents
planning
wetlands
water resources
water quality
solution
optimization
water resource management
uncertainties
methodology
ISSN:0920-4741, 1573-1650
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Popis
Shrnutí:Long-term basin-wide reservoir-river operation optimization problems are usually complex and nonlinear especially when the water quality issues and hydrologic uncertainties are incorporated. It is due to non-convex functions in water quality modeling and a large number of computational iterations required by most of stochastic programming methods. The computational burden of uncertainty modeling can be reduced by a special combination of uncertainty modeling and interval programming, though the problem solution is still a challenge due to model nonlinearity. In this paper, an integrated water quantity-quality model is developed for optimal water allocation at river-basin scale. It considers water supply and quality targets as well as hydrologic, water quality and water demand uncertainties within the nonlinear interval programming (NIP) framework to minimize the slacks in water supply and quality targets during a long-term planning horizon. A fast iterative linear programming (ILP) method is developed to convert the NIP into a linear interval programming (LIP). The ILP resolves two challenges in NIP, first converting the large non-linear programming (NLP) into a linear programming (LP) with minimum approximation and second reducing the iterations needed in interval programming for NLP into just two iterations for the upper and lower limits of decision variables. This modeling approach is applied to the Zayandehrood river basin in Iran that has serious water supply and pollution problems. The results show that in this river basin at dry conditions when available surface water resources are below 85 % of normal hydrologic state and water demands are 115 % of current water demands, the total dissolved solids (TDS) concentration can be reduced by 50 % at the inlet of the Gavkhuni wetland located downstream of the river basin.
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ISSN:0920-4741
1573-1650
DOI:10.1007/s11269-013-0384-2