Browsing by Author "Gao, Hongkai"

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Conceptualization of groundwater-surface water interaction with evidence from environmental isotopes and hydrogeochemistry in lake Babati Basin in Northern Tanzania
(Elsevier, 2023-05) Okwir, Gustavio; Kumar, Sudhir; Pramod, Kumar; Gao, Hongkai; Njau, Karoli
The holistic management of water resources is attainable with evidence-based planning constructed on reliable hydrological information. However, data paucity, especially in sub-Saharan Africa, leads to a significant knowledge gap regarding surface water and groundwater interactions, leaving considerable uncertainty to support relevant decisions. This study combined hydrogeochemistry and environmental isotopes to explore the connections between the surface water and groundwater in the data scarce catchment of Lake Babati Basin in northern Tanzania. The results showed that: i) Lake Babati receives groundwater influx from recently recharged aquifers endowed in the pyroclastic formation in the lake basin; ii) the lake is not well mixed as presented by the heterogenous hydrogeochemistry and confirmed by the differences in the isotopic composition of deuterium and oxygen – 18 at different locations within it; iii) the deep wells located near the lake abstract a mixture of recently recharged water, deep aquifer waters and lake water with enriched isotopic compositions; and iv) the hydrogeochemistry and isotopic data reveal the presence of a hydraulic connection between the lake and deep wells. The findings of this study demonstrate that the catchment, the groundwater system, and Lake Babati are interlinked and, therefore, require the implementation of integrated water resources management to enhance sustainable development.
Mapping groundwater in ungauged lake basin in Tanzania: A comparison between two topography based methods
(Elsevier Ltd., 2022-02) Okwir, Gustavio; Komakech, Hans; Kumar, Sharma; Gao, Hongkai; Njau, Karoli
Groundwater is one of the most critical water resources for Sub Saharan Africa. However, the understanding of the groundwater system in the region is still lacking due to sparse groundwater observations. The influence of topography on the groundwater table is still mostly not evaluated in Sub Saharan Africa. This study applied the analytical hierarchical process to explore and compare the suitability of two secondary topography indices, the Height Above Nearest Drainage (HAND) and Topographic Wetness Index (TWI), to predict groundwater potential. We used shallow and deep wells to validate the groundwater potential zones. The results showed that both HAND and TWI are useful parameters to identify groundwater spatial variability. The water levels and wells depths varied and deepened with reduction in the groundwater potential. The study also showed that both methods are similar in groundwater potential classifications, with an overall accuracy (or similarity) of 70.56% and an overall kappa coefficient of 0.61. The HAND based method, however, showed superiority over the TWI based method. Nevertheless, both methods seemed suitable for preliminary groundwater prospecting with a high potential to minimize prospecting efforts and associated costs and provide insight into locations for future exploitation and optimization of wells drilling success in the study area.
Multi-variate regression analysis of lake level variability: A case of semi-closed, shallow rift valley lake in Northern Tanzania
(Elsevier, 2022) Okwi, Gustavio; Kumar, Sharma; Gao, Hongkai; Selemani, Juma; Njau, Karoli
Lakes are very important for domestic use, commercial purposes, and ecosystem sustenance; nevertheless, studies on how different stressors influence water resources are limited, posing challenges in the planning and managing of water resources. Lake Babati is one of the important lakes in the East African rift valley as a source of fish, drinking water, and hippopotamus habitat. The lake level has consistently declined, threatening the life of organ- isms depending on the lake. Nevertheless, no study postulated the reasons for its decline. Therefore, this study used statistical methods, regression analysis and HEC-HMS hydrological model to investigate the association and sensitivity of the hydrological components driving the lake level variability. Results showed that the Lake Ba- bati level was significantly declining (p < 0.01) at a rate of 0.025 m yearly. The lake level variability was most sensitive to inflow, while outflow and evaporation had almost equivalent magnitude in driving the lake level variability and direct rainfall had the least influence. Although the lake level variability corresponded to changes in the basin supply components, the declining lake level trend was neither directly related to lake evaporation nor inflow as both parameters showed no significant trends. Furthermore, groundwater abstraction within the lakeshore is smaller than lake evaporation and is unlikely the main driver of the decline in lake level. Therefore, the declining lake level seemed related to the spillway outflow, which had been improved to avoid lake flooding resulting in large outflow during the peak seasons and probably the reason for the significant decline in the lake levels even in the rainy seasons. This study benchmarked the most sensitive hydrological drivers influencing lake level whose accurate monitoring and management could rescue the situation