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| Type: | Resource | |
| Storage: | The size of this resource is 1.5 KB | |
| Created: | Feb 08, 2023 at 3:31 p.m. | |
| Last updated: | Mar 23, 2023 at 6:30 p.m. | |
| Citation: | See how to cite this resource |
| Sharing Status: | Public |
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| Views: | 731 |
| Downloads: | 226 |
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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 solutionstochastic groundwater flow model considering recharge as uncertain parameter. The groundwater flow model was developed and simulated using MODFLOW 20 0 0 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. (C) 2020 The Author(s). Published by Elsevier B.V.
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Additional Metadata
| Name | Value |
|---|---|
| DOI | 10.1016/j.mex.2020.100907 |
| Depth | 60 |
| Scale | 10 001 - 100 000 km² |
| Layers | 1 |
| Purpose | Scientific investigation (not related to applied problem) |
| GroMoPo_ID | 313 |
| IsVerified | True |
| Model Code | MODFLOW |
| Model Link | https://doi.org/10.1016/j.mex.2020.100907 |
| Model Time | SS |
| Model Year | 2020 |
| Model Authors | Rwanga, S; Ndambuki, J |
| Model Country | South Africa |
| Data Available | Report/paper only |
| Developer Email | sophia.rwanga@yahoo.com; jmndambuki@yahoo.co.uk |
| Dominant Geology | Unsure |
| Developer Country | South Africa |
| Publication Title | Dataset of development of stochastic groundwater flow under uncertain recharge |
| Original Developer | No |
| Additional Information | |
| Integration or Coupling | None of the above |
| Evaluation or Calibration | |
| Geologic Data Availability | No |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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