Water is characterised by both its quantity (availability) and its quality. Salinity, which is one of the major water quality parameters limiting use of a wide range of land and water resources, refers to the total dissolved solutes in water. It is influenced by a combination of several soil-water-salt-plant related processes. In order to develop optimum management schemes for environmental control through relevant hydrological modelling techniques, it is important to identify and understand these processes affecting salinity. Therefore, the various sources and processes controlling salt release and transport from the soil surface through the root zone to groundwater and streams as well as reservoirs are extensively reviewed in this project with subsequent exploration of some hydro salinity modelling approaches. The simulation of large and complex hydrological systems, such as these at a catchment scale, requires a flexible and efficient modelling tool to assist in the assessment of the impact of land and water use alternatives on the salt balance. The currently available catchment models offer varying degrees of suitability with respect to modelling hydrological problems, dependent on the model structure and the type of the approach used. The A CR U agrohydrological modelling system, with its physically-conceptually based characteristics as well as being a multi-purpose model that is able to operate both as a lumped and distributed model, was found to be suitable for hydro salinity modelling at a catchment scale through the incorporation of an appropriate hydro salinity module. The main aim of this project was to develop, validate and verify a hydro salinity module for the ACRU model. This module is developed in the object-oriented version of ACRU, viz. ACRU2000, and it inherits the basic structure and objects of the model. The module involves the interaction of the hydrological processes represented in ACRU and salinity related processes. Hence, it is designated as ACRUSalinity. In general, the module is developed through extensive review of ACRU and hydrosalinity models, followed by conceptualisation and design of objects in the module. It is then written in Java object-oriented programming language. The development of ACRUSalinity is based mainly on the interaction between three objects, viz. Components, Data and Processes. Component objects in ACRU2000 represent the physical features in the hydrological system being modelled. Data objects are mainly used to store data or information. The Process objects describe processes that can take place in a conceptual or real world hydrological system. The Process objects in ACRUSalinity are grouped into six packages that conduct: • the initial salt load determination in subsurface components and a reservoir • determination of wet atmospheric deposition and salt input from irrigation water • subsurface salt balance, salt generation and salt movement • surface flow salt balance and salt movement • reservoir salt budgeting and salt routing and • channel-reach salt balancing and, in the case of distributed hydro salinity modelling, salt transfer between sub-catchments. The second aim of the project was the validation and verification of the module. Code validation was undertaken through mass balance computations while verification of the module was through comparison of simulated streamflow salinity against observed values as recorded at gauging weir UIH005 which drains the Upper Mkomazi Catchment in KwaZuluNatal, South Africa. Results from a graphical and statistical analysis of observed and simulated values have shown that the simulated streamflow salinity values mimic the observed values remarkably well. As part of the module development and validation, sensitivity analysis of the major input parameters of ACRUSalinity was also conducted. This is then followed by a case study that demonstrates some potential applications of the module. In general, results from the module evaluation have indicated that ACRUSalinity can be used to provide a reasonable first order approximation in various hydrosalinity studies. Most of the major sources and controlling factors of salinity are accommodated in the ACRUSalinity module which was developed in this project. However, for a more accurate and a better performance of the module in diversified catchments, further research needs to be conducted to account for the impact of salt loading from certain sources and to derive the value of some input parameters to the new module. The research needs include incorporation in the module of the impact of salt loading from fertilizer applications as well as from urban and industrial effluents. Similarly, further research needs to be undertaken to facilitate the module's conducting salt routing at sub-daily time step and to account for the impact of bypass flows in heavy soils on the surface and subsurface salt balances. / Thesis (M.Sc.)-University of Natal, Pietermaritzburg, 2003.

Corrigenda attached to back end paper. / Bibliography: p. 526-559. / xxx, 559 p. : ill. ; 30 cm. / Title page, contents and abstract only. The complete thesis in print form is available from the University Library. / This research analyses the suitability of back-propagation artifical neural networks (ANNs) for modelling multivariate water quality time series. The ANNs are successfully applied to two case studies, the long-term forcasting of salinity and the modelling of blue-green algae, in the River Murray, Australia. / Thesis (Ph.D.)--University of Adelaide, Dept. of Civil and Environmental Engineering, 1996?

Thesis (M.Ing.)--Stellenbosch University, 2000. / ENGLISH ABSTRACT: The objective of this research has been to compare nonpoint sources assessment techniques for simulating phosphorous production in rural catchments which have a variety ofland use types. Four nonpoint source assessment techniques capable of simulating phosphorous production, operating at different spatial and temporal resolutions, were selected after an intensive literature review. The model selection criteria included the capability to simulate phosphorous production, the need for the study to cover a range of spatial and temporal resolutions, model data requirements, model affordability and availability in South Africa. The models selected using these criteria are the Phosphorous Export Model (PEM) (Weddepohl & Meyer, 1992), Impoundment and River Management and Planning Assessment Tool for Water Quality Simulation Model (IMPAQ) (DWAF,1995), the Hydrological Simulation Program Fortran (HSPF) (Bricknell,1993) and the Agricultural Catchments Research Unit Model (ACRU) (Smithers and Caldecott, 1994). Four ofthe study catchments were selected within the Berg River basin in the Western Cape and the remaining four were selected within the Amatole catchments in the Eastern Cape. The four subcatchments in the Berg River basin are the Twenty-Four Rivers, Leeu River, Kompanjies River and Doring River catchments and the four in the Amatole catchments are the Upper Buffalo, Cwencwe, Yellowwoods and Gqunube River catchments. The range of land use/cover types comprises: Western Cape catchments : wheat, grapes, natural vegetation and forestry Eastern Cape catchments : natural vegetation and forestry The PEM and IMPAQ models were applied reasonably successfully to all the catchments to simulate phosphorous production, with the observed flow as the input. The HSPF model could not successfully be applied to the catchments to simulate both the catchment hydrology and phosphorous production. Hence, the investigation into HSPF was abandoned, and in its place, the ACRU daily phosphorous yield model was incorporated at a fairly late stage in the research. ACRU was applied to only the Western Cape catchments. The estimated parameters for different land use types were compared to investigate the potential for parameter transfer in space and time. Both the PEM and IMP AQ models showed promise that land use parameters could be transferred in time for catchments located in the Western Cape catchments, but did not show promise for catchments located in the Eastern Cape. The IMPAQ model showed promise that land use parameters could be transferred in space for catchments located in the Eastern Cape, but did not perform as well in the Western Cape catchments. The PEM model showed promise that land use parameters could be transferred in space for catchments located in the Western Cape, but did not perform as well in the Eastern Cape. Since the ACRU phosphorous yield model was included at a late stage of the research, the potential for land use parameter transfer in space and time could not investigated. The model results were verified at the relevant flow and water quality gauging stations. The ACRU phosphorous model verification results showed promise for catchments located in humid parts of the Berg River basin, but did not perform as well in the catchment located in the semi-arid part. RECOMMENDATIONS FOR FURTHER RESEARCH: I. Intensive research should be undertaken to develop a database ofland use parameters/ export coefficients related to phosphorous production (and other non-conservative constituents) in South African catchments. Availability of these parameters would make phosphorous modelling much easier. HSPF should be configured and calibrated, more especially its water quality component, for catchments with hourly rainfall and rainfall stations located within/on the catchment boundaries, to investigate its performance under South African conditions. Given the complexity of the HSPF algorithms and the time required to familiarise oneself with the model, it is recommended that such an investigation be undertaken which is not inclusive of any other models. The spatial resolution ofPEM is extremely coarse, and should be improved to allow the user to partition the total flow in the catchment according to contributions from the variety ofland use types and to estimate soluble and particulate phosphorous parameters for each land use type. A study should be undertaken to investigate the potential for the ACRU phosphorous yield model parameter transfer in time and space. Sampling frequency of water quality data in South Africa should be improved, because it is difficult to assess the performance of the calibrated water quality models, more especially phosphorous export models, due to a lack of continuous data sets. Rainfall data collection in gauged catchments, more especially Western Cape catchments (e.g. Twenty-Four Rivers, Leeu, Kompanjies and the Doring River catchments), should be improved. There should be at least one rainfall gauging station located within the catchment boundaries. This would contribute towards achieving reasonable hydrological calibration or verification. Since runoff is the driving factor for water quality components, improved hydrological calibration/verification would result in reasonable water quality calibration/verification. / AFRIKAANSE OPSOMMING: Die doel van die navorsing was om die simulering van fosfaat produksie in landelike gebiede, wat 'n verskeidenheid grondgebruike het, met behulp van nie-punt bron evaluerings tegnieke te evulaeer. Vier nie-punt bron evaluerings tegnieke, met die vermoë om fosfaat produksie op verskillende ruimtelike en tyds resolusies te simuleer, is gekies na 'n intensiewe ondersoek van beskikbare literatuur. Die kriteria vir die keuse van die model het ingesluit die vermoë om fosfaat produksie te simuleer, die behoefte vir die studie om 'n reeks van ruimtelike en tyds resolusies te simuleer, model data vereistes, model bekostigbaarheid en beskikbaarheid in Suid Afrika. Die gekose modelle, gebaseer op bogemelde kriteria, was die PEM, IMPAQ, HSPF en ACRU modelle. Vier van die opvanggebiede gebruik in die studie, was in die Bergrivier bekken in die Wes-Kaap en vier was in die Amatole opvanggebiede in die Oos-Kaap. Die vier opvanggebiede in die Bergrivier bekken is die Vier-en- Twentigriviere, Leeurivier, Kompanjiesrivier en die Doringrivier en die vier opvanggebiede in die Amatole opvanggebiede is die Bo-Buffels, Cwencwe, Yellowwoods, en die Gunubierivier opvanggebiede. Grondgebruik beslaan die volgende: Wes-Kaap opvanggebiede : koring, druiwe, natuurlike weiding en plantasies. Oos-Kaap : natuurlike plantegroei en plantasies Die PEM en IMPAQ modelle is met redelike sukses in al die opvanggebiede gebruik vir die simulasie van fosfaat produksie, met die waargenome vloei as invoer. Die HSPF model kan nie met enige sukses gebruik word om beide die opvanggebied hidrologie en fosfaat produksie, te simuleer nie. Die HSPF model is dus uitgeskakel en in 'n redelike laat stadium van die studie met die ACRU daaglikse fosfaat leweringsmodel vervang. Die ACRU model is net op die Wes-Kaap opvanggebiede toegepas. Die beraamde parameters vir die verskillende grondgebruik tipes is vergelyk om die potensiaal vir parameter oordrag in ruimte en tyd te ondersoek. Beide die PEM en IMPAQ modelle het belowend vertoon ten opsigte van die oordrag van grondgebruik parameters in tyd vir opvanggebiede in die Wes- Kaap, maar het geensins belowend vertoon vir die Oos-Kaap opvanggebiede nie. Die IMPAQ model het belowend vertoon ten opsigte van die ruimtelike oordrag van grondgebruik parameters vir die Oos-Kaap opvanggebiede, maar het nie so goed vertoon in die Wes-Kaap opvanggebiede nie. Die PEM model het belowend vertoon ten opsigte van die ruimtelike oordrag dat grondgebruikte parameters in die Wes-Kaap opvanggebiede is, maar het nie so goed in die Oos-Kaap opvanggebiede vertoon nie. Aangesien die ACRU fosfaat leweringsmodel op 'n laat stadium van die navorsing ingesluit is, kan die potensiaal vir die oordrag van grondgebruik parameters in ruimte en tyd nie ondersoek word nie. Die model resultate is by die toepaslike vloei en waterkwaliteit meetstasies geverifiëer Die resultate van die ACRU fosfaat model verifikasie het belowend vertoon vir opvangebiede in die humiede gedeeltes van die Bergrivier bekken, maar het nie so goed vertoon in die semi-droeë deel van die opvangebied nie. AANBEVELINGS VIR VERDERE NAVORSING : Y4 Intensiewe navorsing moet onderneem word ten einde in 'n databasis van grondgebruik parameters/oordrag koëffisiente met betrekking tot fosfaat produksie (en ander niekonserwatiewe bestandelle ) in Suid Afrikaanse opvanggebiede op te bou. Beskikbaarheid van hierdie parameters sal fosfaat modellering vergemaklik. Die HSPF model moet opgestel en gekalibreer word, meer spesifiek ten opsigte van die waterkwaliteit komponent, vir opvanggebiede met uurlikse reënval en reënvalstasies binne of op die opvanggebied grense, om die model se vertoning onder Suid Afrikaanse omstandighede te ondersoek. Gegewe die kompleksiteit van die HSPF algoritmes en tyd benodig om met model vertroud te raak, word dit aanbeveel dat so 'n ondersoek onderneem word met uitsluiting van die ander modelle. Die ruimtelike resolusie van die PEM model is uitermatig grof, en behoort verbeter te word ten einde die gebruiker toe te laat om die totale vloei in die opvanggebied in ooreenstemming met die bydraes van die onderskeie grondgebruik tipes te verdeel en om oplosbare en partikulere fosfaat parameters vir elke grondgebruik tipe te beraam. 'n Studie om die potensiaal vir die ruimtelike en tydsoordrag van die ACRU fosfaat leweringsmodel parameters te ondersoek, moet onderneem word. Die frekwensie van waterkwaliteit monitering in Suid Afrika moet verbeter word, aangesien dit moelik is om, weens 'n gebrek aan deurlopend waargenome data, die vertoning van gekalibreerde waterkwaliteit modelle te ondersoek, meer spesifiek nog fosfaat uitvoer modelle. Reënval inligting versameling in gemete opvanggebied, meer spesifiek die Wes-Kaap opvanggebiede (bv.Vier-en-Twintigriviere, Leeu, Kompanjies en Doringrivier opvanggebiede), behoort verbeter te word. Daar behoort ten minste een reënval stasie binne die opvanggebied grense te wees. Dit sal bydra tot die bereiking van redelike hidrologiese kalibrasie ofverifikasie. Aangesien afloop die dryfveer van die waterkwaliteit komponente is, sal verbeterde hidrologiese kalibrasie/verifikasie lei tot redelike waterkwaliteit kalibrasie/verifikasie.

Hui Wing-chi. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2001. / Includes bibliographical references (leaves 127-141). / Abstracts in English and Chinese. / LIST OF TABLES --- p.xi / LIST OF FIGURES --- p.xiii / LIST OF ACRONYMS --- p.xvii / Chapter CHAPTER ONE- --- INTRODUCTION / Chapter 1.1 --- Background --- p.1 / Chapter 1.2 --- Conceptual Framework and Study Objectives --- p.7 / Chapter 1.3 --- Scope of the Research and Study Area --- p.10 / Chapter 1.3.1 --- Location and Climate --- p.10 / Chapter 1.3.2 --- Geology --- p.12 / Chapter 1.3.3 --- Landuse Characteristics and Status of Water Quality --- p.13 / Chapter 1.4 --- Significance of Study --- p.14 / Chapter 1.5 --- Organization of Thesis --- p.16 / Chapter CHAPTER TWO - --- LITERATURE REVIEW / Chapter 2.1 --- Landuse Alteration --- p.17 / Chapter 2.1.1 --- Urbanization and Landuse Changes --- p.17 / Chapter 2.1.2 --- Detecting Landuse Changes in Urbanizing Region --- p.19 / Chapter 2.2 --- Impact of Landuse Alteration on Water Quality --- p.21 / Chapter 2.2.1 --- Point and Nonpoint Sources of Water Pollution --- p.22 / Chapter 2.2.2 --- Nonpoint Source Pollution as a Worldwide Environmental Problem --- p.23 / Chapter 2.2.3 --- Methods of Assessing Nonpoint Source Pollution --- p.24 / Chapter 2.2.4 --- GIS-based Modeling of Nonpoint Source Pollution --- p.26 / Chapter 2.2.5 --- Application of Remote Sensing on Water Quality Study --- p.27 / Chapter 2.3 --- Landuse Changes and Their Water Quality Impacts in the Pearl River Delta --- p.28 / Chapter 2.3.1 --- Economic Reform and Urbanization --- p.29 / Chapter 2.3.2 --- Urban Redevelopment --- p.31 / Chapter 2.3.3 --- Rural Industrialization --- p.33 / Chapter 2.3.4 --- Water Pollution --- p.34 / Chapter CHAPTER THREE - --- METHODOLOGY / Chapter 3.1 --- Introduction --- p.36 / Chapter 3.2 --- Computation of Areal Nonpoint Source Pollution Loading --- p.38 / Chapter 3.2.1 --- Assumptions --- p.38 / Chapter 3.2.2 --- Soil Conservation Service (SCS) Curve Number Method --- p.39 / Chapter 3.2.3 --- Generation of Nonpoint Source Pollutants --- p.42 / Chapter 3.2.4 --- Model Operation --- p.43 / Chapter 3.3 --- Instream Water Quality Modeling --- p.45 / Chapter 3.3.1 --- Description ofWASP5 --- p.46 / Chapter 3.3.2 --- Hydraulic Parameters --- p.47 / Chapter 3.3.3 --- Model Constants --- p.48 / Chapter 3.4 --- Description of Model Input Data --- p.49 / Chapter 3.4.1 --- Watershed Delineation --- p.49 / Chapter 3.4.2 --- Soil Data --- p.51 / Chapter 3.4.3 --- Rainfall Data --- p.52 / Chapter 3.4.4 --- Detection Landuse Changes --- p.53 / Chapter 3.4.4.1 --- Image Preprocessing --- p.54 / Chapter 3.4.4.2 --- Classification and Post-classification Analysis --- p.57 / Chapter 3.4.4.3 --- Assessment of Accuracy --- p.60 / Chapter 3.5 --- Scenario Modeling --- p.61 / Chapter CHAPTER FOUR - --- INTERFACING ARCVIE W GIS WITH WATER QUALITY MODEL / Chapter 4.1 --- Watershed Parameter Generator --- p.64 / Chapter 4.1.1 --- Topographic Analysis and Stream Network Definition --- p.65 / Chapter 4.1.2 --- Vectorization of Basin Geometries --- p.68 / Chapter 4.1.3 --- Computation of Basin Geometric Characteristics --- p.69 / Chapter 4.2 --- Nonpoint Source Pollution Loading Generator --- p.69 / Chapter 4.3 --- Instream Water Quality Calculator --- p.74 / Chapter CHAPTER FIVE- --- LANDUSE AND LAND COVER CHANGES ANALYSIS / Chapter 5.1 --- Framework for Analysis --- p.78 / Chapter 5.2 --- Landuse Changes During the Study Period --- p.82 / Chapter 5.2.1 --- Areal Landuse Changes --- p.82 / Chapter 5.2.2 --- Inter-category Landuse Changes --- p.86 / Chapter 5.2.2.1 --- Rural-to-urban Changes --- p.86 / Chapter 5.2.2.2 --- Rural-to-rural Changes --- p.87 / Chapter 5.2.3 --- Error matrix --- p.88 / Chapter 5.3 --- Spatial Pattern of Landuse and Land cover --- p.91 / Chapter 5.3.1 --- Urban Land --- p.92 / Chapter 5.3.2 --- Rural Areas --- p.94 / Chapter 5.4 --- Scenario Building --- p.96 / Chapter 5.5 --- Limitation of Landuse Classification based on Satellite Image Interpretation --- p.96 / Chapter 5.6 --- Summary --- p.98 / Chapter CHAPTER SIX - --- IMPACTS OF LANDUSE CHANGES ON NONPOINT SOURCE POLLUTION LOADING AND WATER QUALITY / Chapter 6.1 --- Impact of Landuse Changes on NPS Loading --- p.100 / Chapter 6.1.1 --- Identification of Curve Number --- p.100 / Chapter 6.1.2 --- Runoff and Areal Nonpoint Source Pollution Loadings --- p.101 / Chapter 6.1.3 --- Sensitivity of NPS Pollution Loading to Landuse Changes --- p.107 / Chapter 6.2 --- Instream Water Quality Analysis --- p.110 / Chapter 6.2.1 --- Downstream Variation of Water Quality --- p.111 / Chapter 6.2.2 --- Comparison with NWQC II --- p.114 / Chapter 6.3 --- Strategic Landuse Management --- p.117 / Chapter 6.4 --- Limitation of the Study --- p.118 / Chapter CHAPTER SEVEN - --- CONCLUSION / Chapter 7.1 --- Summary of Findings --- p.122 / Chapter 7.1.1 --- Landuse and Land Cover Changes --- p.122 / Chapter 7.1.2 --- GIS-based Water Quality Modeling --- p.123 / Chapter 7.1.3 --- Pollution Loading and Instream Water Quality --- p.124 / Chapter 7.2 --- Future Study --- p.125 / REFERENCES --- p.127