Modelling the Influence of Groundwater Abstractions on the Water Level of Lake Naivasha, Kenya Under Data-Scarce Conditions

被引:14
|
作者
Hogeboom, Rick H. J. [1 ]
van Oel, Pieter R. [2 ]
Krol, Maarten S. [1 ]
Booij, Martijn J. [1 ]
机构
[1] Univ Twente, Twente Water Ctr, NL-7500 AE Enschede, Netherlands
[2] Wageningen Univ, Water Resources Management Grp, NL-6700 AA Wageningen, Netherlands
关键词
Lake Naivasha; Groundwater model; Groundwater; Data scarcity; Irrigation; Water use; RIFT-VALLEY; FLOW MODEL; CATCHMENT; MANAGEMENT; SIMULATION; AQUIFER;
D O I
10.1007/s11269-015-1069-9
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This study presents the state-of-the-art understanding of the data-scarce and hydrogeologically complex groundwater system of Lake Naivasha, Kenya, with the particular aim of exploring the influence groundwater abstractions have on Lake Naivasha's water level. We developed multiple alternative but plausible parameterizations for a MODFLOW groundwater model, based on literature, existing models and available data, while trying not to over-complicate the model. In doing so, we illustrate a possible strategy of going about data-scarce regions in modelling in general. Processes encountered in the calibrated parameterizations show groundwater flows laterally from the escarpments to the valley floor and axially from the lake along the Rift, with a larger portion flowing out southward than northward. Extraction of groundwater interrupts the flow from the northwestern highlands to the lake, leading to a lake stage reduction of 0.7-7.5 cm due to abstractions at our target farm (Flower Business Park) or an implied 7-75 cm due to total groundwater abstractions in the area. Although this study demonstrates our understanding of Naivasha's groundwater system remains fragile and the current model cannot be embedded in operational water management yet, it (i) reflects the contemporary understanding of the local groundwater system, (ii) illustrates how to go about modelling in data-scarce environments and (iii) provides a means to assess focal areas for future data collection and model improvements.
引用
收藏
页码:4447 / 4463
页数:17
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