Predicting shallow groundwater tables for sloping highland aquifers
2019
Alemie, Tilashwork C. | Tilahun, Seifu A. | Ochoa-Tocachi, Boris F. | Schmitter, Petra S. | Buytaert, Wouter | Parlange, Jean-Yves | Steenhuis, Tammo S.
While hydrological science has made great strides forward during the last 50 years with the advance of computing power and availability of satellite images, much is unknown about the sustainable development of water for irrigation, domestic use, and livestock consumption for millions of households in the developing world. Specifically, quantification of shallow underground water resources for irrigation in highland regions remains challenging. The objective is to better understand the hydrology of highland watersheds with sloping hillside aquifers. Therefore, we present a subsurface flow model for hillside aquifers with recharge that varied from day to day. Recharge to the aquifer was estimated by the Thornthwaite Mather procedure. A characteristic time was identified for travel time of water flowing from the upper part of the hillside to the river or well. Using the method of characteristics, we found that the height of shallow groundwater level can be predicted by determining the total recharge over the characteristic time divided by drainable porosity. We apply the model to farmer-dug wells in the Ethiopian highlands using observed rainfall, potential evaporation, and a fitted travel time. We find that the model performs well with maximum water table heights being determined by the soil surface and minimum heights by the presence or absence of volcanic dikes downhill. Our application shows that unless the water is ponded behind a natural or artificial barrier, hillslope aquifers are unable to provide a continuous source of water during the long, dry season. This clearly limits any irrigation development in the highlands from shallow sloping groundwater.
اظهر المزيد [+] اقل [-]الكلمات المفتاحية الخاصة بالمكنز الزراعي (أجروفوك)
المعلومات البيبليوغرافية
تم تزويد هذا السجل من قبل International Livestock Research Institute