Browsing by Author "Barnard, Johannes Jacobus"

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    A bi-objective model for water allocation and scheme water scheduling
    (Stellenbosch : Stellenbosch University, 2019-04) Barnard, Johannes Jacobus; Lotter, Daniel; Stellenbosch University. Faculty of Engineering. Dept. of Industrial Engineering.
    ENGLISH ABSTRACT: "Water is life" | this common expression is often referred to as a cliche, but Earth's inhabitants can truly bear witness to the accuracy of this statement. As a result of global warming, the El Nin~o phenomenon, a growing population and expanding economies, water has globally become a cherished commodity. In the Western Cape, South Africa, a devastating drought experienced over the two-year period 2017/2018 has propelled the innovation of more e ective and e cient water management strategies to the forefront, especially in the farming sector, where farmers are currently compelled to produce agricultural crops with less water. An irrigation and scheme water supply schedule may, for example, be employed with the aim of proposing how crops should be irrigated during their various growth stages, if natural water supply is insufficient, and how additional scheme water supply should be scheduled to enhance efficient water use. An open-air irrigation reservoir typically serves as a water storage facility for the purpose of irrigating agricultural crops. Evaporation (the process of transforming water vapour into the atmosphere) from such a reservoir water surface may, however, result in a reduced reservoir capacity of up to 20%. In this thesis, two novel mathematical models are proposed which form the basis of a decision support system for farmers aimed at providing bene cial agricultural crop irrigation strategies. The first is a single-objective optimisation model which proposes an irrigation schedule in conjunction with a scheme water supply schedule in which the goal is to maximise the total profit obtainable from crop yield. This maximisation process is subject to a user-specified reservoir water capacity that should be left over in an open-air reservoir at the end of a speci ed scheduling horizon. If possible, additional water resources may be obtained from scheme water supply in order to aid with the irrigation of crops. These additional water resources, however, usually come at a cost, which is also included in the total profit calculation. The second model is a bi-objective optimisation model which aims to maximise the total profit from crop yield while simultaneously maximising the reservoir water contents at the end of the last scheduling period. When plotted in objective space, the solutions to the model form a Pareto front that is presented as the basis of decision support to the decision maker (farmer), providing him with an overview of numerous implementable irrigation and scheme water supply schedules for a variety of end-period reservoir water levels. Both the single-objective and bi-objective optimisation models are validated in three ways, namely by face validation, by random benchmark validation and by consulting an expert in the field of crop irrigation and farming. Embedded in the decision support system, these models enable the decision maker to develop a course of action in terms of crop irrigation for a tailored farming scenario.
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    Prosopis invasion in the Northern Cape: remote sensing analysis of management action effectiveness
    (Stellenbosch : Stellenbosch University, 2021-12) Barnard, Johannes Jacobus; De Klerk, Helen Margaret; Van Wilgen, Brian W.; Eckert, Sandra; Stellenbosch University. Faculty of Arts and Social Sciences. Dept. of Geography and Environmental Studies.
    ENGLISH ABSTRACT: Large-scale land acquisitions (LSLAs) for agricultural sector have grown significantly in the past decade, and are mostly prevalent in developing countries. Because LSLAs are not without negative effects on the environment and local communities, and because information about them is scarce and difficult to obtain, systems allowing LSLAs detection, characterization and monitoring in space and time are needed. With the increasing availability of global satellite data products, technological development in cloud computing, image and data mining analysis, remote sensing has evolved to an interesting tool for the detection and characterization of changes in land use systems. This study presents a novel approach to generically detect and characterize LSLAs at regional spatial extents. In order to capture and analyse the full range of land use spectral and spatial signatures related to agricultural LSLAs, this study is based on a 2-level data driven approach (Self-Organizing Maps followed by a clustering algorithm), consisting of two phases: 1) land use/land cover change detection at regional scale within dense temporal stacks of vegetation indices (MODIS-NDVI, 250m) and 2), discrimination of different land use/land cover classes using a set of spectral vegetation indices, textural features and shape metrics computed from landscape-extracted objects (Landsat-8, 30m). Evaluation of the methodology is performed against a ground truth database on LSLAs in Senegal. Results obtained during this exploratory research, are promising and provide some insights in agricultural LSLAs in the northern half of Senegal. With a very limited number of discriminative features (consisting of two Vegetation Indices and two textural features), detection of agricultural LSLAs is possible. Recommendations are given for enhancement of the generalization performance of the unsupervised classifier.