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Lack of access to safe or improved water supply in developing countries is a major global concern, since water is a basic need for sustenance. Programmes aimed at improving access to safe water have been implemented in several sub-Saharan countries. In Botswana, only gazetted settlements have access to water and other basic services provided by the government. This paper examined the level of access to safe water, effort required, and problems encountered in collecting water by households in ungazetted settlements. The paper also investigated whether households in these settlements were willing to pay for improving access to water. The study has been undertaken on settlements located along the Boteti River in the North West District of Botswana. The majority of households in ungazetted settlements satisfy their domestic water requirements through abstracting untreated water from river flows and hand-dug wells when the river is not flowing. Men dominate in collecting water in ungazetted settlements, with the most dominant mode of transporting water being the use of donkey carts. The dominance of men in water collection and use of donkey carts is due to water sources being too distant from homesteads. This has resulted in low water consumption levels, with the per capita water consumption being less than 20 l/capita/ day for most households. Such low levels of water consumption adversely affect attainment of desirable personal hygiene and food preparation. The opportunity cost of time for water collection has been estimated at 1.80 Botswana Pula (P) and the price of water is estimated to be P18/m 3 (1.00 P = 0.1755 USD on 18 November 2005). This is higher than the price paid by households residing in rural

This paper examines effects of three dams on flow characteristics of Insiza River on which they are located. The storage capacities of these dams varies from an equivalent of 48–456% of the mean annual runoff. Mean annual runoff and annual maximum flood flows have not been modified by the presence of these dams. The average number of days per year without runoff had decreased downstream of two dams. A comparison was made of flow duration curves at sites upstream and downstream of the selected dams. Significant differences were detected between the flow duration curves of upstream and downstream sites. Exceedance frequencies of low flows had decreased downstream of two dams, while these had increased downstream of the other dam. The study recommends development of operating rules for these dams that will ensure that changes detected in low flows do not adversely affect instream flow requirements.

The purpose of this study was to identify and assess long-term impacts of land use change on catchment runoff in semi-arid Zimbabwe, based on analyses of long hydrological time series (25–50 years) from six medium-sized (200–1000 km2) non-experimental rural catchments. A methodology combining common statistical methods with hydrological modelling was adopted in order to distinguish between the effects of climate variability and the effects of land use change. The hydrological model (NAM) was in general able to simulate the observed hydrographs very well during the reference period, thus providing a means to account for the effects of climate variability and hence strengthening the power of the subsequent statistical tests. In the test period the validated model was used to provide the runoff record which would have occurred in the absence of land use change. The analyses indicated a decrease in the annual runoff for most of the six catchments, with the largest changes occurring for catchments located within communal land, where large increases in population and agricultural intensity have taken place. However, the decrease was only statistically significant at the 5% level for one of the catchments.

This chapter presents the outcome of research conducted in Otjozondjupa region, central Namibia on the effects of water transfers from two storage dams (Swakoppoort and Omatako Dams) to augment water volume in a third dam (Von Bach Dam) which is located closer to a purification plant. The transfers are strategically made to bring water closer to the purification plant and more important to limit evaporation losses from the wider and shallower dams; Von Bach Dam is much narrower and deeper than the other two dams which together, constitute the source of water for the expansive residential area and industrial hub located in the capital city of Windhoek and its environs. The study investigates water quality in the three dams and analyses the effects of water transferred and possible effects on water treatment costs. Research findings are discussed and analyzed using relevant models for predicting water quality changes. The results from the secchi disk depth measurements and the analysis of turbidity, dissolved oxygen; iron, total phosphorus, ammonia (NH4–N) and chlorophyll a indicate that there were significant negative effects resulting from the water transfers. Other parameters tested indicate that there were no statistically significant differences in the three dams.

The selection of basin characteristics that explain spatial variation of river flows is important for hydrological regionalization as this enables estimation of flow statistics of ungauged basins. A direct gradient analysis method, redundancy analysis, is used to identify basin characteristics, which explain the variation of river flows among 52 selected basins in Zimbabwe. Flow statistics considered are mean annual runoff, coefficient of variation of annual runoff, average number of days per year without flow and selected percentile flows. Basin characteristics investigated are those likely to reflect climatological, topographical and hydrogeological influences including that of land cover on river flows. The first ordination axis of flow statistics is strongly correlated with mean annual precipitation, mean annual potential evaporation and median slope. This ordination axis explains 64% of the variation of selected flow statistics among the selected drainage basins. The proportions of a basin under cultivation, and that with grasslands are correlated with the second ordination axis, which explains 6% of the variation of selected flow statistics. Mean annual precipitation is the most important basin characteristic, and this alone explains 50% of the variation of flow statistics. Median slope is the second most important basin characteristic. Proportions of a basin underlain by different lithological types had no effect on flow characteristics of selected basins. The paper has demonstrated the ability of redundancy analysis to identify basin characteristics that explain the variation of river flows among basins, including estimating the relative importance of these basin characteristics.

The feasibility of predicting flow characteristics from basin descriptors using multiple regression and neural networks has been investigated on 52 basins in Zimbabwe. Flow characteristics considered were average annual runoff, base flow index, flow duration curve, and average monthly runoff . Mean annual runoff is predicted using linear equations from mean annual precipitation, basin slope, and proportion of a basin underlain by granite and gneiss. A multiple regression equation is derived to predict the base flow index from mean annual precipitation, slope, and proportion of a basin with grasslands. Findings indicate that a neural network predicts the base flow index with comparable accuracy to multiple regression. Differences in lithology and land cover type were not significant in explaining the base flow index. An exponential model was able to describe flow duration curves, and coefficients of this model could be predicted from the base flow index. Best predictions of flow duration curves were made by a neural network from base flow index, slope, and proportion of a basin with grasslands. The distribution of mean annual runoff into monthly flows was predicted by a neural network from base flow index, slope, and proportion of a basin with grasslands. The study found the base flow index to be important for predicting flow characteristics, and recommends studies aimed at improving prediction of the base flow index.

Abstract Base flows make up the flows of most rivers in Zimbabwe during the dry season. Prediction of base flows from basin characteristics is necessary for water resources planning of ungauged basins. Linear regression and artificial neural networks were used to predict the base flow index (BFI) from basin characteristics for 52 basins in Zimbabwe. Base flow index was positively related to mean annual precipitation (r = 0.71), basin slope (r = 0.76), and drainage density (r = 0.29), and negatively related to mean annual evapotranspiration (r = –0.74), and proportion of a basin with grasslands and wooded grasslands (r = –0.53). Differences in lithology did not significantly affect BFI. Linear regression and artificial neural networks were both suitable for predicting BFI values. The predicted BFI was used in turn to derive flow duration curves of the 52 basins and with R 2 being 0.89–0.99.