Dataset of development of stochastic groundwater flow under uncertain recharge

Sophia Rwanga; Julius Ndambuki

doi:10.1016/j.mex.2020.100907

Dataset of development of stochastic groundwater flow under uncertain recharge

MethodsX. 2020 Apr 30:7:100907. doi: 10.1016/j.mex.2020.100907. eCollection 2020.

Authors

Sophia Rwanga¹, Julius Ndambuki²

Affiliations

¹ Vaal University of Technology, Department of Civil Engineering, South Africa.
² Department of Civil Engineering, Tshwane University of Technology, South Africa.

Abstract

Groundwater is a valuable resource of limited extent both in quantity and in space. In order to ensure its careful use, proper evaluation of its availability is required. The majority of groundwater flow numerical models still provide only deterministic predictions with no supplementary information on uncertainty predictions. Stochastic groundwater management aims at treating uncertainty within decision oriented models in a logical and systematic manner which cannot be experienced in deterministic modelling approach. This paper presents a detailed methodology followed in the development of a stochastic groundwater model under uncertain recharge. The methodology is comprised of two steps (1) The development of a groundwater flow model and (2) the development of a stochastic solution- stochastic groundwater flow model considering recharge as uncertain parameter.•The groundwater flow model was developed and simulated using MODFLOW 2000 software and calibrated using Parameter Estimation Program (PEST). Validated model compared well with calibrated model.•The uncertainty in recharge was propagated to the flow model through Monte Carlo (MC) sampling technique.•The methodology demonstrated the importance of developing groundwater flow models that acknowledge the existence of recharge uncertainty and hence consider it in the development of groundwater management solutions.

Keywords: Development; Groundwater flow; MODFLOW Software; Recharge; Stochastic; Uncertain.