Development of an objective‐oriented groundwater model for conjunctive‐use planning of surface water and groundwater

In this paper we construct an objective‐oriented model for conjunctive‐use planning of surface water and groundwater for the Warren groundwater basin in southern California. The goal of conjunctive‐use planning is to decrease high‐nitrate concentration while maintaining groundwater levels at desired...

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Bibliographic Details
Published in:Water resources research 2009-12, Vol.45 (12), p.n/a
Main Authors: Chiu, Yung-Chia, Sun, Ne-Zheng, Nishikawa, Tracy, Yeh, William W.G
Format: Article
Language:English
Subjects:
basins
case studies
groundwater
groundwater contamination
hydrologic models
inverse problem
model calibration
nitrates
parameter structure identification
planning
simulation models
surface water
water management
water table
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Summary:In this paper we construct an objective‐oriented model for conjunctive‐use planning of surface water and groundwater for the Warren groundwater basin in southern California. The goal of conjunctive‐use planning is to decrease high‐nitrate concentration while maintaining groundwater levels at desired elevations and meeting water demand. We formulate a management problem that minimizes the total cost over the proper choices of the time‐varying pumping and recharge rates at prespecified wells and surface ponds. To make the solution of the management problem reliable, we must have an accurate simulation model to predict groundwater level and nitrate concentration distributions under different management alternatives. The objective‐oriented model construction approach seeks a representative parameter that has the simplest structure and requires the minimum data for identification but can produce reliable results for a given model application. With the data from the Warren groundwater basin, we show how to incorporate management objectives into the construction of an objective‐oriented model, identify the parameter structure and its corresponding parameter values, solve the generalized inverse problem effectively by finding the worst‐case parameter (WCP), evaluate the sufficiency of existing data, and find a robust experiment design when the existing data are insufficient. Results of this case study show that the presented methodology is useful in practice because (1) data sufficiency can be judged before conducting actual field experiments and (2) the identified WCP drastically reduces the computation time for constructing an objective‐oriented model.
ISSN:0043-1397
1944-7973
DOI:10.1029/2007WR006662