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Representative pumping wells network to estimate groundwater withdrawal from aquifers: Lessons from a developing country, Iran

Parizi, E ; Sharif University of Technology | 2019

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  1. Type of Document: Article
  2. DOI: 10.1016/j.jhydrol.2019.124090
  3. Publisher: Elsevier B.V , 2019
  4. Abstract:
  5. In this study a review of the developed methods to estimate groundwater withdrawal (GWW) from aquifers by pumping wells is provided. Then, a method adopted by Iran's Basic Studies Bureau of Water Resources Management Company for estimation of GWW through 536 aquifers across Iran is presented and modified. This so-called “representative pumping wells network” (RPWN) approach is a combination of statistical and rate-and-time methods which has been implemented for all aquifers in Iran since 2007. The RPWN approach is based on the overlaying of 10 important features in a GIS environment and classified in a number of zones in which their withdrawals are statistically different. The representative pumping wells in each zone are sampled for RPWN based on a multi-objective optimization. Three aquifers of Tehran, Arak, and Qazvin in Iran are selected as real cases studies to demonstrate the efficiency of the modified RPWN approach. Metered pumpage of the all active wells obtained from the last official inventory in 2007 is considered as true GWW values to evaluate the current and modified RPWNs. Based on modified approach, 50 representative pumping wells (RPWs) are selected for each aquifer of Tehran, Arak, and Qazvin, respectively 58%, 11%, and 50% less than number of wells considered in the current RPWN. Whereas the computational errors of GWW by the current RPWN are between 19.9% and 26.2%, the modified RPWN shows much smaller errors in the range of 0.2% to 1.41%. Moreover, the modified RPWN reduces the cost of data compilation to 10.6% to 58.0% of the current RPWN. The results of this study demonstrate that the modified RPWN approach is a robust, efficient, effective and consistent tool and particularly suited to the aquifers that pumping wells provides a dense observation network in which data compilation of GWW impose a great deal of financial burden. © 2019
  6. Keywords:
  7. Groundwater withdrawal ; Pumping wells ; Rate-and-time method ; Representative pumping wells network ; Aquifers ; Developing countries ; Hydrogeology ; Multiobjective optimization ; Well pumps ; Computational error ; Data compilation ; Important features ; Observation networks ; Pumping well ; Statistical approach ; Water resources management ; Groundwater resources ; Aquifer ; GIS ; Groundwater ; Network analysis ; Statistical analysis ; Well ; well water ; Arak ; Iran ; Markazi ; Qazvin [Iran] ; Tehran [Iran]
  8. Source: Journal of Hydrology ; Volume 578 , 2019 ; 00221694 (ISSN)
  9. URL: https://www.sciencedirect.com/science/article/pii/S002216941930825X