<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>One of the direct economic consequences of dam failure (DF) is that water supply for irrigation is affected and incomes of the agriculture sector (AS) are reduced. The main purpose of this study is to apply a linear programming model (LPM), which, the objective function of the model was set to maximize the income function of the region AS with accessible water sources and function of crops production before and after the DF by using dummy variable (DV) regression models to optimize water supply for irrigation. The results obtained indicate that the consumption of surface water(SW) and groundwaters (GW), before the DF has not been optimized, as there are 15.5 % source loss in SW and 14.5 % in GW. After the DF, the allocation of SW in the best possible situation of access to SW sources is independent of the model input. It has a fixed value equivalent to 86 million cubic meters (MCM), which indicates a 116% decrease in comparison with the optimized value. Total accessible water sources are decreased by 36 % and using GW is 15 % more than an average long period time. A based on the finding from this research and its comparison with previous studies, this model is appropriate for water supply programming after DF and for dry weather Conditions.</p>
</abstract>

One of the direct economic consequences of dam failure (DF) is that water supply for irrigation is affected and incomes of the agriculture sector (AS) are reduced. The main purpose of this study is to apply a linear programming model (LPM), which, the objective function of the model was set to maximize the income function of the region AS with accessible water sources and function of crops production before and after the DF by using dummy variable (DV) regression models to optimize water supply for irrigation. The results obtained indicate that the consumption of surface water(SW) and groundwaters (GW), before the DF has not been optimized, as there are 15.5 % source loss in SW and 14.5 % in GW. After the DF, the allocation of SW in the best possible situation of access to SW sources is independent of the model input. It has a fixed value equivalent to 86 million cubic meters (MCM), which indicates a 116% decrease in comparison with the optimized value. Total accessible water sources are decreased by 36 % and using GW is 15 % more than an average long period time. A based on the finding from this research and its comparison with previous studies, this model is appropriate for water supply programming after DF and for dry weather Conditions.

Optimization in Water Resources At Dry Weather Conditions Before and After the Dam Failure By Using Dummy Variable Regression Approach

Department of Water Engineering, Arak Branch

Department of Civil Engineering, Arak Branch

Department of Chemical Engineering, College of Engineering and Technology

Department of Mathematics, College of Science, Arak Branch

Journal of Applied Engineering Sciences

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

One of the direct economic consequences of dam failure (DF) is that water supply for irrigation is affected and incomes of the agriculture sector (AS) are...

Optimization in Water Resources At Dry Weather Conditions Before and After the Dam Failure By Using Dummy Variable Regression Approach

Publié en ligne: 26 mai 2021

Pages: 61 - 68

Reçu: 14 déc. 2020

Accepté: 04 janv. 2021

DOI: https://doi.org/10.2478/jaes-2021-0009

Mots clés
Dam failure, Dummy variable, linear programming, optimization, water supply

© 2021 H. A. Torabi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Optimization in Water Resources At Dry Weather Conditions Before and After the Dam Failure By Using Dummy Variable Regression Approach

Publié en ligne: 26 mai 2021

Pages: 61 - 68

Reçu: 14 déc. 2020

Accepté: 04 janv. 2021

DOI: https://doi.org/10.2478/jaes-2021-0009

Mots clésDam failure, Dummy variable, linear programming, optimization, water supply

© 2021 H. A. Torabi et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Mots clés
Dam failure, Dummy variable, linear programming, optimization, water supply