The connection between water and human wellbeing is increasingly causing concern about the implications of water scarcity on poverty. The primary fear is that water scarcity may not only worsen poverty, but may also undermine efforts to alleviate poverty and food insecurity. A review of literature revealed that the relationship between water scarcity and poverty is a complex one, with water scarcity being both a cause and consequence of poverty. Furthermore, water scarcity is multidimensional, which makes it difficult to define, while it can also vary considerably, both temporally and spatially. Finally, the relationship between water scarcity and poverty is a difficult one to quantify. Within the context of water scarcity, indicators are viewed by many development analysts as appropriate tools for informing and orienting policy-making, for comparing situations and for measuring performance. However, simplistic traditional indicators cannot capture the complexity of the water-poverty link; hence a proliferation of more sophisticated indicators and indices since the early 1990s. The Water Poverty Index (WPI), one of these new indices, assesses water scarcity holistically. Water poverty derives from the conceptualisation of this index which relates dimensions of poverty to access to water for domestic and productive use. However, the WPI has not been applied extensively at meso-catchment scale, the scale at which water resources managers operate. In South Africa, the Thukela Catchment -in the province of KwaZulu-Natal presents a unique opportunity to assess the WPI at this scale. The Thukela is a diverse catchment with respect to physiography, climate and (by extension) natural vegetation, land use, demography, culture and economy. While parts of the catchment are suitable for intensive agricultural production and others are thriving economic centres, a large percentage of the population in the catchment lives in poverty in high risk ecosystems, with their vulnerability exacerbated by policies of the erstwhile apartheid government. Many rural communities, a high percentage of which occupy these naturally harsh areas, have low skills levels, with a high proportion of unemployed people, low or no income and low services delivery. Infrastructural development, which relates to municipal service delivery, is often made prohibitively expensive by the rugged terrain in which many people live. As in other catchments in South Africa, the Thukela is affected by policies and initiatives aimed at accomplishing the objectives of post-1994 legislation such as the South Africa Constitution and the National Water Act. The potential of the WPI to assess the impacts of these initiatives on human wellbeing and to inform decision .making in the Thukela catchment was investigated. An analysis of a 46 year long series of monthly summations of daily values of streamflows output by the ACRU agrohydrological simulation model has shown that the Thukela, in its entirety , is a water-rich catchment. The reliability of the streamflows, which has implications for communities who collect water directly from 1 streams, is high along main channels but can be considerably less along low order tributaries of the main streams. The flow reliability along the small tributaries is less in winter than in summer. A high percentage of the catchment's population, in addition to being poor and not having access to municipal services, live near, and rely on, the small tributaries for their water supplies. Admittedly, this analysis addresses only one dimension of water poverty, viz. physical water shortage. Nevertheless, the study revealed that despite the Thukela's being a water-rich catchment, many communities are still water stressed. A more holistic characterisation of the water scarcity situation in the Thukela catchment was achieved using the WPI. A review of possible information sources for computing the WPI in South Africa found that many monitoring programmes, information systems and databases are either in existence and are active, or being restructured, or are under different stages of development. If and when they are all fully functional , they should be able to support national assessments of the WPI at meso-scale without the need to collect additional information. A combination of information from some of the active databases and secondary data from other local studies was used to compute the WPI in the Thukela catchment. The assessment uncovered the following: • There is an apparent association between water poverty and socio-economic disadvantage in the Thukela catchment. • There was an improvement in the water poverty situation in most parts of the Thukela catchment between 1996 and 2001, although the degree of improvement varied from subcatchment to subcatchment. Climate change, if it manifests itself by higher temperatures and reduced rainfall, will most likely worsen water poverty throughout the Thukela catchment, with the subcatchments in which many of the poor communities are located being more likely to experience the most severe impacts as the coping capacities of those communities are already strained under current climatic conditions. The findings of this study illustrate the potential of WPI as a tool for informing decision making and policy evaluation at the meso-catchment scale at which many water-related decisions are made. / Thesis (Ph.D.)-University of KwaZulu-Natal, Pietermaritzburg, 2006.

As is the case in many other regions in the world, sugarcane production in southern Africa is affected by a wide range of climatic conditions, which can vary considerably from location to location and from year to year. As a result, the season length and growth cycles of sugarcane in southern Africa differ greatly. Such conditions include the hot and dry regions of northern KwaZulu-Natal, Swaziland and Mpumalanga, where sugarcane is mostly irrigated, to the humid sub-tropical coastal belt extending from the far north coast of KwaZulu-Natal to areas in the Eastern Cape, as well as the cool frost prone midlands regions of KwaZulu-Natal. Owing to the wide range of climatic conditions in which sugarcane is grown in southern Africa, there are many different external factors that affect sugarcane production, including a range of pests and diseases, frost occurrences and variations in soil water. The objective of this research was to (1) identify a number of important variables that affect cane production in southern Africa, (2) employ suitable models to reflect these variables, and (3) simulate and map the extent and severity of these variables at a high spatial resolution over southern Africa. Such variables include the Eldana saccharina and Chilo sacchariphagus stalk borers, sugarcane rust fungus, heat units with selected base temperatures, frost, soil water content, soil compaction, irrigation water demand, conducive and non-conducive growing conditions, flowering proficiencies for sugarcane, sugarcane yields and yield increments per unit of irrigation. The distribution patterns of the above-mentioned variables relied greatly upon the various models employed to represent them, as well as the accuracy of the temperature and rainfall databases to which the various models were applied. Although not definitive, the models used to reflect the variables which had been identified were considered to be generally satisfactory. The resolution at which the variables which had been identified in this study were mapped, was also found to be adequate. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2008.

Many techniques have been developed over the years in first world countries for the estimation of flood hydrographs from small catchments for application in design, management and operations of water related issues. However, relatively little attention has been directed towards the transfer and adaptation of such techniques to developing countries in which major hydrological decisions are crucially needed, but in which a scarcity of quality hydrological data often occurs. As a result, hydrologists and engineers in developing countries are frequently unable to alleviate the problems that extreme rainfall events can create through destructive flood flows or, alternatively, they do not possess the appropriate tools with which to design economically viable hydraulic structures. Eritrea is a typical example of a developing country which faces difficulties in regard to the adaptation of an appropriate design flood estimation technique for application on small catchments. As a result, the need has arisen to adapt a relatively simple and robust design flood model that can aid hydrologists and engineers in making economic and safe designs of hydraulic structures in small catchments. One objective of this study was, therefore, to review approaches to hydrological modelling and design flood estimation techniques on small catchments, in order to identify the barriers regarding their adaptation, as well as to assist in the selection of an appropriate technique for application, in Eritrea. The southern African adaptation of the SCS (i.e. Soil Conservation Service) design hydrograph technique, which has become a standard method for design flood estimation from small catchments in that region, was selected for application on small catchments in Eritrea for several reasons. It relies on the determination of a simple catchment response index in the form of an initial Curve Number (CN), which reflects both the abstraction characteristics and the non-linear stormflow responses of the catchment from a discrete rainfall event. Many studies on the use of SCS-based hydrological models have identified that adjustment of the initial CN to a catchment's antecedent soil moisture (ASM) to be crucial, as the ASM has been found to be one of the most sensitive parameters for accurate estimates of design flood volumes and peak discharges. In hydrologically heterogeneous regions like Eritrea, the hypothesis was postulated that simulations using a suitable soil water budgeting procedure for CN adjustment would lead to improved estimates of design flood volumes and peak discharges when compared with adjustments using the conventional SCS antecedent moisture conditions (SCS-AMC) method. The primary objective of this dissertation was to develop a surrogate methodology for the soil water budgeting procedure of CN adjustment, because any direct applications of soil water budgeting techniques are impractical in most parts of Eritrea owing to a scarcity of adequate and quality controlled hydrological information. It was furthermore hypothesised that within reasonably similar climatic regions, median changes in soil moisture storage from the socalled "initial" catchment soil moisture conditions, i.e. LIS, were likely to be similar, while between different climatic regions median LISs were likely to be different. Additionally, it was postulated that climatic regions may be represented by a standard climate classification system. Based on the above hypotheses, the Koppen climate classification, which can be derived from mean monthly rainfall and temperature information, was first applied to the 712 relatively homogeneous hydrological response zones which had previously been identified in southern Africa. A high degree of homogeneity of median values of LIS, derived by the daily time step ACRU soil moisture budgeting model, was observed for zones occurring within each individual Koppen climate class (KCC) - this after a homogeneity test had been performed to check if zones falling in a specific KCC had similar values of median LIS. Further assessment within each KCC found in southern Africa then showed that a strong relationship existed between LIS and Mean Annual Precipitation (MAP). This relationship was, however, different between KCCs. By developing regression equations, good simulations of median LIS from MAP were observed in each KCC, illustrating the potential application of the Koppen climate classification system as an indicator of regional median LIS, when only very basic monthly climatological information is available. The next critical task undertaken was to test whether the estimate of median LIS from MAP by regression equation for a specific Koppen climate class identified in southern Africa would remain similar for an identical Koppen climatic region in Eritrea. As already mentioned, LIS may be determined from daily time step hydrological soil moisture budget models such as ACRU model. The performance of the ACRU stormflow modelling approach was, therefore, first verified on an Eritrean gauged research catchment, viz. the Afdeyu, in order to have confidence in the use of values of LIS generated by it. A SCS-ACRU stormflow modelling approach was then tested on the same catchment by using the new approach of CN adjustment, termed the ACRU-Koppen method, and results were compared against stormflow volumes obtained using the SCS-AMC classes and the Hawkins' soil water budgeting procedures for CN adjustment, as well as when CNs remain unadjusted. Despite the relatively limited level of information on climate, soils and land use for the Afdeyu research catchment, the ACRU model simulated both daily and monthly flows well. By comparing the outputs generated from the SCS model when using the different methods of CN adjustment, the ACRU-Koppen method displayed better levels of performances than either of the other two SCS-based methods. A further statistical comparison was made among the ACRU, the SCS adjusted by ACRU-Koppen, the SCS adjusted by AMC classes and the unadjusted SCS models for the five highest stormflows produced from the five highest daily rainfall amounts of each year on the Afdeyu catchment. The ACRU model produced highly acceptable statistics from stormflow simulations on the Afdeyu catchment when compared to the SCS-based estimates. In comparing results from the ACRU-Koppen method to those from the SCS-AMC and unadjusted CN methods it was found that, statistically, the ACRU-Koppen performed much better than either of the other two SCS based methods. On the strength of these results the following conclusions were drawn: • Changes in soil moisture storage from so-called "initial" catchment soil moisture conditions, i.e. L1S, are similar in similar climatic regions; and • Using the ACRU-Koppen method ofCN adjustment, the SCS-SA model can, therefore, be adapted for application in Eritrea, for which Koppen climates can be produced from monthly rainfall and temperature maps. Finally, future research needs for improvements in the SCS-ACRU-Koppen (SAK) approach in light of data availability and the estimation ofL1S were identified. From the findings of this research and South African experiences, a first version of a "SCSEritrea" user manual based on the SAK modelling approach has been produced to facilitate its use throughout Eritrea. This user manual, although not an integral part of this dissertation, is presented in its entirety as an Appendix. A first Version of the SCS-Eritrea software is also included. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2004.

Identifying areas of the hillslope that are most sensitive to soil erosion and contribute significantly to sediment yield is a primary concern in environmental protection and conservation. Therefore the ability to predict the magnitude and variability of soil erosion and sediment yield is important to catchment managers in order to select the appropriate conservation practices that keep soil erosion and sediment yield within the tolerable limits. A number of models have been developed for simulating soil erosion and sediment yield from a catchment. However, none of them are universally applicable and most of them require extensive data which are extremely costly, time consuming and sometimes not available except in research catchments. Hence it was concluded that the combined use of an empirically based soil loss model, RUSLE, Geographic Information Systems (GIS) techniques, and a Sediment Delivery Ratio (SDR) concept would be a candidate modelling tool, which would be a compromise between the advantages of simplicity, data availability, the complex spatial variability of hydrological and geomorphological characteristics of a catchment and the economic limitation of field data measurements in sediment yield studies. Such a modelling tool was developed in this research and was able to identify sediment source areas and predict annual sediment yield from catchments. Data from the Henley catchment, South Africa have been used for demonstrating the potential use of the model in soil erosion and sediment yield studies. Arcview GIS grid functions were used to define the flow direction, accumulation, pathways, and velocity in a catchment as a function of topography and land use and to describe spatially variable input and output information. In addition the Arcview GIS grid function was used to discretise the catchment into hydrologically homogeneous grid cells to capture the catchment heterogeneity. The gross soil erosion in each cell was calculated using the soil loss model RUSLE while a distributed topography based SDR parameter was used to determine the mass of eroded sediment that would be transported to the nearest stream and ultimately to the catchment outlet. The average annual soil loss and sediment yield values were 26 t. ha-1.yr -1 and 1.6 t. ha-1.yr -1 respectively. High soil erosion and sediment yield rates are evident in the residential and agricultural areas, which are characterised by degradation due to overgrazing and traditional and peri-urban settlements with mixed crops. The average annual SDR value was 0.19 for the Henley catchment and large SDR values are associated with areas adjacent to the channel system. This can be explained by recognizing that the SDR is significantly influenced by characteristics of the drainage system. Comparison of event based simulations of sediment yields to those estimated from measurements demonstrated that the proposed model predictions ranged between 13 % and 60 % of the measured estimates, consistently over predicting. This is because the SDR component of the model is developed as a mean annual parameter, assuming that over a long period a stream system must intimately transport all the sediments delivered to it. Hence the channel network sediment delivery parameters would have to be considered at short temporal scales. Comparing the results of the model prediction against other sediment modelling techniques in South Africa demonstrated the usefulness of the model as an effective catchment management tool. The model has advantages over these other techniques since it includes a distributed grid based component, which enables the identification of sediment source areas in the catchment. The sensitivity analysis shows that the model was highly sensitive to parameters derived from topography and land use of the catchment. Future research with the model should include further testing and analysis of its components on different catchments. The topography based SDR concept which is a key component in sediment routing for prediction of either long term average sediment yield or isolated storm event simulation from a catchment warrants specific attention. Effort in future should focus on identifying parameters which affect the sediment delivery within a catchment. This may be achieved by incorporating processes describing the movement of sediments in the channel network of the catchment. / Thesis (M.Sc.)-University of KwaZulu-Natal, Pietermaritzburg, 2004.