Optimizing the Conjunctive Use of Surface Water and Groundwater in Water Stressed River Basins: Case of Olifants River Basin, South Africa
| dc.contributor.author | Kifanyi, Gislar Edgar | |
| dc.date.accessioned | 2023-09-21T12:33:39Z | |
| dc.date.available | 2023-09-21T12:33:39Z | |
| dc.date.issued | 2017 | |
| dc.description | This thesis was published in the year 2017 | |
| dc.description.abstract | One of the new techniques currently used to address water shortage problems in the developed countries is the optimum conjunctive water use. Optimum conjunctive water use demands that the surface and subsurface reservoirs are fully characterized if deterministic methods are to give reliable results. However, in real world phenomena, full characterization of surface – groundwater reservoirs is neither practically nor economically feasible. This research, therefore, aimed at developing a combined simulation-optimization quantitative conjunctive water use management model which can sustainably manage water resources taking into account input parameter uncertainty. Response matrix technique was used to combine simulation model with optimization model (procedure). The novelty of this research work is that determination of optimum conjunctive water use was determined under scanty data and uncertain condition. Surface water and groundwater conceptual models were developed, and integrated to form a conjunctive water use conceptual model which was converted into numerical simulation model for both deterministic and stochastic simulations. MODFLOW 2000 and RIVER Package (RIV) (together referred to as conjunctive water use simulation model) supported in Visual MODFLOW 2014.2 Classical Interface was used to determine aquifer system responses (drawdowns). These drawdowns were assembled as response matrices and then incorporated into an optimization management model as drawdowns constraints coefficients. The simulation optimization problems were solved and analysed through “Active-Set” (Sequential Quadratic Programming (SQP) optimizer (algorithm)) implemented under the MATLAB 2014a environment. The Retrospective Optimization Approximation (ROA) method was used for solving the stochastic optimization problem and to v investigate the impact of uncertainty on optimal management strategies. ROA procedure solves and evaluates a sequence of optimization sub-problems in an increasing number of realizations. Results indicated that the study area aquifer has potential groundwater resource which is undeveloped. Deterministic approach underestimates the water withdrawal rates. The optimal withdrawal rates designed based on ROA approach were relatively higher than those designed based on deterministic approach. Moreover, the overall percentages of contribution of surface water and groundwater sources to the total water demand obtained through ROA approach was about 58% and 42%, respectively while the overall percentages contribution obtained through deterministic approach was about 85% and 15%, respectively. This is about ±27 % variation (i.e., Differences between the approaches realized) of percentages of contribution of the two water sources to the total water demand. Furthermore, findings indicated that ROA conjunctive water use management technique has potential to ensure sustainability of limited water resources of river basins. Through ROA approach the expected total optimal objective function value converged to its maximum value within a relatively few iterations (6 to 8 iterations) in about 2.30 Hrs computational time. In conclusion, results demonstrated that the ROA approach is a promising technique for use in managing conjunctive water use under uncertainty conditions. It is recommended that guidelines for determination of the sequence of sample sizes for use in ROA method framework should be established. The use of parallel computer processors to enhance computational time efficiency for large optimization problems should be explored. Quantitative methods for determination of weights for estimating values of objective functions should be investigated. The application of the ROA approach to multi-objectives optimization problems should be explored. | |
| dc.description.sponsorship | TUT | |
| dc.identifier.uri | http://repository.must.ac.tz/handle/123456789/100 | |
| dc.language.iso | en | |
| dc.publisher | Tshwane University Of Technology | |
| dc.title | Optimizing the Conjunctive Use of Surface Water and Groundwater in Water Stressed River Basins: Case of Olifants River Basin, South Africa | |
| dc.type | Thesis |