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An assessment of groundwater recharge estimation techniques for sustainable resource management
Date
2019Author
Singh, A.
Panda, S.N.
Uzokwe, V.N.E.
Krause, P.
Type
Target Audience
Scientists
Metadata
Show full item recordAbstract/Description
Groundwater resources are limited and they are declining in quality and quantity due to contamination and climate change impacts. Under the environment of the increasing water demand for domestic, agricultural, and industrial uses and dwindling resources, the management of groundwater resources is a challenging task worldwide. Precise evaluation of groundwater recharge is vital for its sustainable management and efficient use for various sectors of the economy. An overview of different groundwater recharge estimation techniques is presented in this paper. The techniques covered in this study include numerical approach, tracer method, hydrologic budget method, and multiple methods. The norms of recharge estimation through rainfall, canal seepage, and field percolation are also covered in this study. The literature analysis revealed that the tracer techniques are extensively used in water-scarce areas for estimating groundwater recharge. And the use of watertable fluctuations is a valuable means for shaping the size of both long and short-term alterations in recharge. The analysis also revealed that groundwater recharge can be estimated by using the numerical models. Because each approach is associated with some limitations, the use of multiple approaches was recommended to estimate the groundwater recharge. In many cases, diverse approaches balance every other and aid improve the conceptual model of recharge processes. This literature analysis provides the basis for the selection of an appropriate recharge estimation technique under a specific set of conditions.
http://dx.doi.org/10.1016/j.gsd.2019.100218
Multi standard citation
Permanent link to this item
https://hdl.handle.net/20.500.12478/5800Non-IITA Authors ORCID
Veronica N.E Uzokwehttps://orcid.org/0000-0002-5563-9210
Digital Object Identifier (DOI)
http://dx.doi.org/10.1016/j.gsd.2019.100218