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Groundwater level trend analysis using the statistical auto-regressive HARTT method
Journal article   Open access   Peer reviewed

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

Guesh Zeru, Tena Alamirew, Haile A. Shishaye, Megersa Olmana, Nata Tadesse and Michael J Reading
Hydrological Research Letters, Vol.14(1), pp.17-22
2020
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Abstract

accumulative residual rainfall groundwater sustainability hydrograph non-climatic variable
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 (K1) was found to be 0.00562 ± 0.0007 mm. This K1 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 (K2) 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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