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Hydrology 2017, 4(2), 25;

Groundwater Resources Assessment and Impact Analysis Using a Conceptual Water Balance Model and Time Series Data Analysis: Case of Decision Making Tool

Snowy Mountains Engineering Corporation (SMEC), Sydney, NSW 2060, Australia
Department of Civil Engineering, University of Engineering and Technology, Peshawar 25120, Pakistan
Author to whom correspondence should be addressed.
Academic Editors: Abdon Atangana and Luca Brocca
Received: 16 February 2017 / Revised: 5 April 2017 / Accepted: 6 April 2017 / Published: 14 April 2017
(This article belongs to the Special Issue Groundwater Flow)
Full-Text   |   PDF [2069 KB, uploaded 17 April 2017]   |  


The allocation of groundwater resources has been a challenge for many years due to its unforeseen side effect and lag time issues, which are often overlooked. The full impact of groundwater utilization/abstraction takes time to realize its effect at its full. In this paper, long-term effects and groundwater dynamics were assessed using a water balance model and a time series analysis, respectively. Undeveloped groundwater systems are commonly found in a state of equilibrium, where, on average, equal amounts of water are recharged and discharged. A water budget is a static accounting of the state of the system at a given time, often before the system is developed. Water balance analysis was carried out together with the groundwater through flow, hydrograph, and surface-groundwater interaction analysis (base flow index) to develop a conceptual water balance model, which is a very basic representation of a complex natural aquifer system and is instrumental to constrain and build a robust numerical model that can be readily justified and updated. A noble approach was employed to assess and constrain the discharge coming out of the model area to sustain the lake level, located to the north of the study area, using the whole lake catchment and lake water balance analysis. Based on the lake water balance, there is a deficit between input and output computation, and hence there should be a groundwater input to sustain the historical lake area. The analysis showed that the model area contributes 40% of the lake catchment, and hence the portion of the groundwater inflow feeding the lake was computed. This is one of the means to constrain the discharge, which adds more confidence to the recharge estimation. This is very important because the size of a sustainable groundwater development usually depends on how much of the discharge from the system can be captured by the development. Capture is independent of the recharge. Instead, it depends on the dynamic response of the aquifer system to the development. The idea that knowing the recharge is important in determining the size of a sustainable groundwater development is a myth and has no basis. The important entity in determining how a groundwater system reaches a new equilibrium is capture. How capture occurs in an aquifer system is a dynamic process. Following this study, lake water balance assessment was indirectly considered as prior information for the numerical model calibration of the discharge from the model area using a conductance parameter. Conductance is a key parameter to estimate the discharge volume together with the change in the simulated hydraulic head between time steps. The water balance error highlights which one is more sensitive, and this could help to assist in planning for future data collection/field work and where to invest the money. The water balance computation helps to figure out the degree of surface-groundwater interaction, uncertainty, sensitive parameter, helps in the decision to invest time and money, and operates as a cross check with other analytical or numerical modelling. View Full-Text
Keywords: Hydrogeology; recharge; discharge; basin; sustainability; long term yield; catchment; Hydrology Hydrogeology; recharge; discharge; basin; sustainability; long term yield; catchment; Hydrology

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Yihdego, Y.; Khalil, A. Groundwater Resources Assessment and Impact Analysis Using a Conceptual Water Balance Model and Time Series Data Analysis: Case of Decision Making Tool. Hydrology 2017, 4, 25.

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