4.3 Article

Climate Change Impact on Reservoir Performance Indexes in Agricultural Water Supply

Journal

JOURNAL OF IRRIGATION AND DRAINAGE ENGINEERING
Volume 139, Issue 2, Pages 85-97

Publisher

ASCE-AMER SOC CIVIL ENGINEERS
DOI: 10.1061/(ASCE)IR.1943-4774.0000496

Keywords

Climate change; Operation management of reservoir; Reservoir performance indicators; Simulation; Optimization

Ask authors/readers for more resources

This paper addresses the impact of climate change on the volume of inflow to a reservoir and the volume of downstream water demand by considering three climate change scenarios in an East Azerbaijan river basin. The HadCM3 model was used to estimate possible scenarios of temperature and rainfall for the period 2026-2039 under an emission scenario (A2). A hydrological model (IHACRES) was first calibrated for the basin; and then, a monthly time series of future temperatures and rainfall were entered into IHACRES. In addition, a 14-year time series of monthly runoff was simulated for 2026-2039. Modeling results indicated that the average long-term annual runoff volume decreased by 0.7% relative to the base period (1987-2000). However, by assuming a nonchanging cultivation area, the average long-term annual water demand volume for crops increased by 16%. Both simulation and optimization models of reservoir operation were used. The simulation of reservoir performance in the delivery of water demand was implemented according to the standard operating policy (SOP) and by using the water evaluation and planning (WEAP) model. The three aforementioned climate change scenarios were then introduced to the WEAP, and the reservoir performance indexes (reliability, vulnerability, and resiliency) were calculated. Results showed that indexes would change in the future relative to the base. Next, for the optimal operation of the reservoir with a water supply for agricultural and environmental purposes, the minimization of total squared deficiencies in the allocation to these purposes was determined for each month and climate change scenario by the using LINGO Version 11.0 software [nonlinear programming (NLP)] algorithm. Results showed that the indexes would change. DOI: 10.1061/(ASCE)IR.1943-4774.0000496. (C) 2013 American Society of Civil Engineers.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available