scholarly journals A case study: the approach to the integrated and cooperative management of the water resources of the Maputo River Basin by Moçambique, Swaziland and South Africa

2008 ◽  
Author(s):  
A. Tanner ◽  
D. Mndzebele ◽  
J. Ilomäki
Keyword(s):  
South Africa ◽  
Water Resources ◽  
River Basin ◽  
Cooperative Management

Sharing the Incomati waters: cooperation and competition in the balance

Water Policy ◽  
2003 ◽  
Vol 5 (4) ◽  
pp. 349-368 ◽  
Author(s):  
Pieter van der Zaag ◽  
Álvaro Carmo Vaz
Keyword(s):  
South Africa ◽  
Water Resources ◽  
River Basin ◽  
Water Use ◽  
Political History ◽  
Cooperation And Competition ◽  
Water Developments ◽  
Natural Characteristics ◽  
Water Uses

The water resources of the Incomati river basin, shared between South Africa, Swaziland and Mozambique, are intensively used. Moreover, the basin is situated in a part of Africa that over the last 40 years has experienced a dynamic, sometimes turbulent and volatile, political history. Both ingredients might have been sufficient for the emergence of confrontations over water. Tensions between Mozambique, South Africa and Swaziland over Incomati waters existed but never escalated. This case study attempts to explain why cooperation prevailed, by presenting information about the natural characteristics of the basin, its political history, water developments and the negotiations that took place during the period 1967–2002. The paper provides four explanations why tensions did not escalate and cooperation prevailed. It is concluded that the developments in the Incomati basin support the hypothesis that water drives peoples and countries towards cooperation. Increased water use has indeed led to rising cooperation. When the next drought comes and Mozambique, South Africa and Swaziland enforce their recently concluded agreement, and voluntarily decrease those water uses deemed less essential, then the hypothesis has to be accepted.

scholarly journals Modelling streamflow response to hydro-climatic variables in the Upper Mkomazi River, South Africa

2014 ◽  
Author(s):  
◽  
Oluwaseun Kunle Oyebode
Keyword(s):  
South Africa ◽  
Water Resources ◽  
Genetic Programming ◽  
Predictive Models ◽  
Model Development ◽  
De Algorithm ◽  
Planning And Management ◽  
Ann Models ◽  
Artificial Neural

Streamflow modelling remains crucial to decision-making especially when it concerns planning and management of water resources systems in water-stressed regions. This study proposes a suitable method for streamflow modelling irrespective of the limited availability of historical datasets. Two data-driven modelling techniques were applied comparatively so as to achieve this aim. Genetic programming (GP), an evolutionary algorithm approach and a differential evolution (DE)-trained artificial neural network (ANN) were used for streamflow prediction in the upper Mkomazi River, South Africa. Historical records of streamflow and meteorological variables for a 19-year period (1994- 2012) were used for model development and also in the selection of predictor variables into the input vector space of the models. In both approaches, individual monthly predictive models were developed for each month of the year using a 1-year lead time. Two case studies were considered in development of the ANN models. Case study 1 involved the use of correlation analysis in selecting input variables as employed during GP model development, while the DE algorithm was used for training and optimizing the model parameters. However in case study 2, genetic programming was incorporated as a screening tool for determining the dimensionality of the ANN models, while the learning process was further fine-tuned by subjecting the DE algorithm to sensitivity analysis. Altogether, the performance of the three sets of predictive models were evaluated comparatively using three statistical measures namely, Mean Absolute Percent Error (MAPE), Root Mean-Squared Error (RMSE) and coefficient of determination (R2). Results showed better predictive performance by the GP models both during the training and validation phases when compared with the ANNs. Although the ANN models developed in case study 1 gave satisfactory results during the training phase, they were unable to extensively replicate those results during the validation phase. It was found that results from case study 1 were considerably influenced by the problems of overfitting and memorization, which are typical of ANNs when subjected to small amount of datasets. However, results from case study 2 showed great improvement across the three evaluation criteria, as the overfitting and memorization problems were significantly minimized, thus leading to improved accuracy in the predictions of the ANN models. It was concluded that the conjunctive use of the two evolutionary computation methods (GP and DE) can be used to improve the performance of artificial neural networks models, especially when availability of datasets is limited. In addition, the GP models can be deployed as predictive tools for the purpose of planning and management of water resources within the Mkomazi region and KwaZulu-Natal province as a whole.

Interdependent effects of climate variability and forest cover change on streamflow dynamics: a case study in the Upper Umvoti River Basin, South Africa

2019 ◽  
Vol 19 (7) ◽  
pp. 1963-1971
Author(s):  
Karen Lebek ◽  
Cornelius Senf ◽  
David Frantz ◽  
José A. F. Monteiro ◽  
Tobias Krueger
Keyword(s):  
South Africa ◽  
Climate Variability ◽  
River Basin ◽  
Forest Cover ◽  
Forest Cover Change

IMPLEMENTING ENVIRONMENTAL FLOWS IN COMPLEX WATER RESOURCES SYSTEMS - CASE STUDY: THE DUERO RIVER BASIN, SPAIN

2011 ◽  
Vol 29 (4) ◽  
pp. 451-468 ◽  
Author(s):  
J. Paredes-Arquiola ◽  
F. Martinez-Capel ◽  
A. Solera ◽  
V. Aguilella
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Environmental Flows ◽  
Water Resources Systems

scholarly journals Supplemental irrigation potential and impact on downstream flow of Karkheh River basin in Iran

2016 ◽  
Vol 20 (5) ◽  
pp. 1903-1910 ◽  
Author(s):  
Behzad Hessari ◽  
Adriana Bruggeman ◽  
Ali Mohammad Akhoond-Ali ◽  
Theib Oweis ◽  
Fariborz Abbasi
Keyword(s):  
Water Resources ◽  
River Basin ◽  
Water Productivity ◽  
Environmental Flow ◽  
Supplemental Irrigation ◽  
Irrigation Potential ◽  
Winter Crops ◽  
Downstream Flow ◽  
Karkheh River Basin

Abstract. Supplemental irrigation of rainfed winter crops improves and stabilises crop yield and water productivity. Although yield increases by supplemental irrigation are well established at the field level, its potential extent and impact on water resources at the basin level are less researched. This work presents a Geographic Information Systems (GIS)-based methodology for identifying areas that are potentially suitable for supplemental irrigation and a computer routine for allocating streamflow for supplemental irrigation in different sub-basins. A case study is presented for the 42 908 km2 upper Karkheh River basin (KRB) in Iran, which has 15 840 km2 of rainfed crop areas. Rainfed crop areas within 1 km from the streams, with slope classes 0–5, 0–8, 0–12, and 0–20 %, were assumed to be suitable for supplemental irrigation. Four streamflow conditions (normal, normal with environmental flow requirements, drought and drought with environmental flow) were considered for the allocation of water resources. Thirty-seven percent (5801 km2) of the rainfed croplands had slopes less than 5 %; 61 % (3559 km2) of this land was suitable for supplemental irrigation, but only 22 % (1278 km2) could be served with irrigation in both autumn (75 mm) and spring (100 mm), under normal flow conditions. If irrigation would be allocated to all suitable land with slopes up to 20 %, 2057 km2 could be irrigated. This would reduce the average annual outflow of the upper KRB by 9 %. If environmental flow requirements are considered, a maximum (0–20 % slopes) of 1444 km2 could receive supplemental irrigation. Under drought conditions a maximum of 1013 km2 could be irrigated, while the outflow would again be reduced by 9 %. Thus, the withdrawal of streamflow for supplemental irrigation has relatively little effect on the outflow of the upper KRB. However, if the main policy goal would be to improve rainfed areas throughout the upper KRB, options for storing surface water need to be developed.

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