Browsing by Subject "Groundwater"

Now showing 1 - 2 of 2

Open Access
Centralized and decentralized management of water resources with multiple users
(2011) Saleh, Yahya
In this study, we investigate two water inventory management schemes with multiple users in a dynamic game-theoretic structure over a two-period planning horizon. We first investigate the groundwater inventory management problem (i) under the decentralized management scheme, where each user is allowed to pump water from a common aquifer making usage decisions individually in a noncooperative fashion, and (ii) under the centralized management scheme, where users are allowed to pump water from a common aquifer with the supervision of a social planner. We consider the case of n non-identical users distributed over a common aquifer region. Furthermore, we consider different geometric configurations overlying the aquifer, namely, the strip, ring, double-layer ring, multi-layer ring and grid configurations. In each configuration, general analytical results of the optimal groundwater usage are obtained and numerical examples are discussed. We then consider the surface and groundwater conjunctive use management problem with two non-identical users in a dynamic game-theoretic structure over a planning horizon of two periods. Optimal water allocation and usage policies are obtained for each user in each period under the decentralized and centralized settings. Some pertinent hypothetical numerical examples are also provided.
Open Access
Fast multi-output relevance vector regression for joint groundwater and lake water depth modeling
(Elsevier, 2022-08) Safari, M. J. S.; Rahimzadeh Arashloo, Shervin; Vaheddoost, B.
Fast multi-output relevance vector regression (FMRVR) algorithm is developed for simultaneous estimation of groundwater and lake water depth for the first time in this study. The FMRVR is a multi-output regression analysis technique which can simultaneously predict multiple outputs for a multi-dimensional input. The data used in this study is collected from 34 stations located in the lake Urmia basin over a 40-year time period. The performance of the FMRVR model is examined in contrast to the support vector regression (SVR) and multi-linear regression (MLR) benchmarks. Results reveal that FMRVR is able to generate more accurate estimation for groundwater and lake water depth with coefficient of determination (R2) of 0.856 and 0.992 and root mean square error (RMSE) of 0.857 and 0.083, respectively. The outperformance of FMRVR can be linked to its capability for a joint estimation of multiple relevant outputs by taking into account possible correlations among the outputs.