An integrated approach for aquifer characterization and groundwater productivity evaluation in the Lake Haramaya watershed, Ethiopia

Shishaye, Haile Arefayne; Tait, Douglas R.; Befus, K. M.; Maher, Damien T.

doi:10.1007/s10040-019-01956-7

Cited by 17 publications

(22 citation statements)

References 37 publications

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“…The Haramaya watershed aquifer system is recharged predominantly from precipitation (Shishaye et al, 2019). Therefore, any significant long-term trend in water-level may not only be due to human interventions but may also be associated with a long-term change in climate variables.…”

Section: Model Resultsmentioning

confidence: 99%

“…Usually, the relative coefficient of determination between the simulated and observed water-levels is a function of input data ranges, model accuracy, data quality, site characteristics, time period and other factors that are difficult to measure (Ferdowsian et al, 2001a). However, it is also important to note that all the wells drilled in the area (Figure 1) are in a similar geologic formation, alluvial deposit (Shishaye et al, 2019). Therefore, it can be con-cluded that the model results (Table I) represent the cumulative effects of residual rainfall and the underlying timetrend ( Figure 2), while other factors (human-induced) are shared by the time-trend (non-climatic variable).…”

Section: Model Resultsmentioning

confidence: 99%

“…The area has a subtropical agro-climatic condition with an average annual rainfall of 776 mm and an average temperature of 18°C. The watershed is part of the Harar Plateau, in the upper Wabi-Shebele Basin and is characterized by three major stratigraphic units including the Precambrian crystalline basement, Mesozoic sedimentary rocks and Quaternary sediments (Shishaye et al, 2019). The aquifer system in the area is a single unconfined unit with an average thickness of 55 m (Shishaye et al, 2019).…”

Section: Methodsmentioning

confidence: 99%

“…Groundwater has been the only source of water supply in the Lake Haramaya watershed in Ethiopia since the desiccation of Lake Haramaya in 2006 (Shishaye and Abdi, 2016;Shishaye et al, 2019). Despite the development of many private and public wells for domestic and agricultural purposes, the water supply is still inadequate to meet the needs of the region.…”

Section: Introductionmentioning

confidence: 99%

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Groundwater level trend analysis using the statistical auto-regressive HARTT method

Zeru

Alamirew

Shishaye

et al. 2020

Hydrological Research Letters

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In this study, the Hydrograph Analysis: Rainfall and Time-Trends (HARTT) model was used to determine the contribution of climatic and non-climatic stresses on groundwater levels in the Lake Haramaya well-field, Ethiopia. Monthly precipitation and monitored water-level data were used as explanatory variables of the method. Variability in rainfall explained 81.3% of groundwater levels using 2-month average time-delay. The coefficient of the impact of rainfall on groundwater level (K 1) was found to be 0.00562 ± 0.0007 mm. This K 1 value indicates that a 1 mm increase in rainfall from the annual average rainfall raises the groundwater-level by 0.00562 ± 0.0007 mm, while 1 mm decrease in rainfall causes a 0.00562 ± 0.0007 mm drop in groundwater-level in the area. However, the average falling trend of the groundwater level (K 2) was 1.51 ± 0.133 m/year, even with rainfall causing water-levels to rise between 1.01 to 3.29 m/year. With decreased rainfall, rainfall accounted for about 19.5% of the total-drawdown, while 80.5% was due to cumulative effects of non-climatic variables. This shows that rainfall inputs are negated by cumulative non-climatic stresses leading to the long-term net decline in groundwater level. Projected water-level results show that groundwater levels will be below pumping positions in <24 years which may have dire consequences for local landowners.

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Section: Model Resultsmentioning

confidence: 99%

Section: Model Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Groundwater level trend analysis using the statistical auto-regressive HARTT method

Zeru

Alamirew

Shishaye

et al. 2020

Hydrological Research Letters

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“…Groundwater resource assessment, management and over-exploitation issues have been extensively and successfully addressed using numerical modeling, and specifically using Modflow. Case studies can be found worldwide, including in countries like India [17][18][19], Pakistan [20], Iran [21], Greece [22], China [23], Taiwan [24], Ethiopia [25], and the USA [26]. In Ethiopia, for example, Shishaye et al [25] developed groundwater resources sustainability analysis.…”

Section: Introductionmentioning

confidence: 99%

Water Resource Assessment of a Complex Volcanic System Under Semi-Arid Climate Using Numerical Modeling: The Borena Basin in Southern Ethiopia

Razack

Furi

Fanta

et al. 2020

Water

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The Borena basin is located in southern Ethiopia, in a semi-arid climate, on the eastern shoulder of the south Main Ethiopian Rift (MER). The study area covers 18,000 km2 and is characterized by a lack of perennial surface waters that can be used for domestic and agricultural purpose. As a result, groundwater, which occurs in complex volcanic settings, is the only source for water supply in the study area. This work is focused on the basaltic aquifers, which are intensely fractured, resulting in strong connectivity within the system. All available data (geology, hydraulic head, hydraulic parameters, well inventory and discharge, etc.) were compiled in a GIS database. The overall objective of this work is the assessment of groundwater potential, its spatial distribution and factors controlling its movement using numerical groundwater modeling to enhance groundwater management and use in the Borena basin. The modeling task was conducted at two scales: (i) regional scale; (ii) wellfields scale. The regional steady state model was calibrated using the Pilot points approach, highlighting a strongly heterogeneous system. A significant result of the regional model consisted of estimating the water balance of the whole system. The total inflow to the basin amounts to 542 × 106 m3/year, of which 367 × 106 m3/year are provided by superficial recharge. Groundwater resources are exploited with 7 wellfields. Exploitation of the wellfields was optimized based on the Sustainable Yield concept, which reserves a fraction of natural recharge for the benefit of the environment (surface waters, ecosystems). Each wellfield was extracted from the regional model, refined and used to simulate and optimize pumping scenarios, with the objective of maximizing discharge rates and avoiding over-exploitation of the groundwater. The optimized abstraction at all wellfields amounts to 121 × 106 m3/year, which represents 33% of the natural recharge and fully agrees with the sustainable yield concept.

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Delineation of groundwater quality locations suitable for target end‐use purposes through deep neural network models

et al. 2021

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Groundwater is the main source of water for beverages, and its quality varies depending on extraction location; this is particularly the case in regions with complex geology, topography, and multiple forms of land use. Thus, it is important to determine a suitable groundwater extraction location based on intended water use and the related water quality standards. In this study, deep neural network (DNN) models and GIS data relating to groundwater quality were applied to estimate potential maps of Gangwon Province in South Korea, where groundwater is frequently extracted for drinking purposes. These maps specify areas where the groundwater quality is conducive for being used as mineral water and water for brewing coffee (hereafter referred as "coffee water"). Sensitivity analysis identified how inputs were sensitive to model estimation and showed that land-use variables were the most sensitive. The importance of each variable quantified how good or bad its region is for the desired groundwater. The overall features of importance were similar between mineral water and coffee water. However, with differences in hydrogeological units, carbonate rock was a variable of high positive importance for mineral water; metamorphic rock was its equivalent for coffee water. Our results offer a potential map of desired groundwater quality in the absence of a detailed understanding of the underlying hydrochemical processes governing groundwater quality. Additionally, the development of such a potential mapping model can help to determine the appropriate development area of groundwater for their respective purposes. Abbreviations: DNN, deep neural network. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

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An integrated approach for aquifer characterization and groundwater productivity evaluation in the Lake Haramaya watershed, Ethiopia

Cited by 17 publications

References 37 publications

Groundwater level trend analysis using the statistical auto-regressive HARTT method

Groundwater level trend analysis using the statistical auto-regressive HARTT method

Water Resource Assessment of a Complex Volcanic System Under Semi-Arid Climate Using Numerical Modeling: The Borena Basin in Southern Ethiopia

Delineation of groundwater quality locations suitable for target end‐use purposes through deep neural network models

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