Simulation and Optimization for Management of Water Resources in a Canal Command Area

Shirahatti, S. S.; Kaushal, M.P.; Jain, Anil; Khepar, S. D.

doi:10.13031/2013.9704

Cited by 2 publications

(2 citation statements)

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“…Each unit response describes the impact of a brief stress (such as pumping) upon hydraulic heads at selected points of the field. A response matrix is created by assembling all unit responses and is included in the management model, turning pumping rates and/or hydraulic heads into decision variables (Aguado and Remson 1974, Heidari 1982, Gorelick 1983, Karatzas and Pinder 1993, Shirahatti and Khepar 2007.…”

Section: Introductionmentioning

confidence: 99%

A stochastic optimization framework for the restoration of an over-exploited aquifer

Mylopoulos

Sidiropoulos

2016

Hydrological Sciences Journal

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This study investigates the impact of hydraulic conductivity uncertainty on the sustainable management of the aquifer of Lake Karla, Greece, using the stochastic optimization approach. The lack of surface water resources in combination with the sharp increase in irrigation needs in the basin over the last 30 years have led to an unprecedented degradation of the aquifer. In addition, the lack of data regarding hydraulic conductivity in a heterogeneous aquifer leads to hydrogeologic uncertainty. This uncertainty has to be taken into consideration when developing the optimization procedure in order to achieve the aquifer's sustainable management. Multiple Monte Carlo realizations of this spatially-distributed parameter are generated and groundwater flow is simulated for each one of them. The main goal of the sustainable management of the 'depleted' aquifer of Lake Karla is twofold: to determine the optimum volume of renewable groundwater that can be extracted, while, at the same time, restoring its water table to a historic high level. A stochastic optimization problem is therefore formulated, based on the application of the optimization method for each of the aquifer's multiple stochastic realizations in a future period. In order to carry out this stochastic optimization procedure, a modelling system consisting of a series of interlinked models was developed. The results show that the proposed stochastic optimization framework can be a very useful tool for estimating the impact of hydraulic conductivity uncertainty on the management strategies of a depleted aquifer restoration. They also prove that the optimization process is affected more by hydraulic conductivity uncertainty than the simulation process.

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Section: Introductionmentioning

confidence: 99%

A stochastic optimization framework for the restoration of an over-exploited aquifer

Mylopoulos

Sidiropoulos

2016

Hydrological Sciences Journal

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“…With the advent of digital computers in the late 1970s numerical solutions of (D-F) equation were developed using finite difference schemes (Singh and Jacob, 1976;Wachyan and Rushton, 1987;Ahmad et al, 1993;Shirahatti, 1997). Numerical solutions are also available for one-dimensional Saint Venant equation for a rigid open channel (Strelkoff, 1970).…”

Section: Introductionmentioning

confidence: 99%

Studies on groundwater recharge through surface drains

Singh¹,

Kaushal²,

Khepar³

et al. 2007

WSA

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A mathematical model is developed for the estimation of groundwater recharge through surface drains for both free flow as well as detained flow conditions. The Dupuit-Forchheimmer equation is solved using the Crank-Nicolson central finite difference scheme, to obtain the mound height matrix. The Gaussian elimination method was used to solve the matrix, to obtain the mound height at different radial distances across the drain. Various hydrogeological parameters like hydraulic conductivity, specific yield, etc. are determined by field investigations. Surface runoff available due to a particular rainfall event is correlated with recharge rate available in the drain. The model gives volume of water recharged for various rainfall events under different antecedent moisture conditions for both free flow and detained flow conditions. The value of recharge rate computed by using the model for a particular depth of flow in the drain is matched with the observed values. The model is more sensitive to change in the value of specific yield than hydraulic conductivity.

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Simulation and Optimization for Management of Water Resources in a Canal Command Area

Cited by 2 publications

References 0 publications

A stochastic optimization framework for the restoration of an over-exploited aquifer

A stochastic optimization framework for the restoration of an over-exploited aquifer

Studies on groundwater recharge through surface drains

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