Application of satellite-derived rainfall estimates to extend water resource simulation modelling in South Africa

Spatially interpolated rainfall estimates from rain-gauges are widely used as input to hydrological models, but deriving accurate estimates at appropriate space and time scales remain a major problem. In South Africa there has been a gradual decrease in the number of active rain-gauges over time. Satellite-based estimates of spatial rainfall are becoming more readily available and offer a viable substitute. The paper presents the potential of using Climate Prediction Center African daily precipitation climatology (CPCAPC) satellite-based datasets (2001-2006) to drive a Pitman hydrological model which has been calibrated using gauge-based rainfall data (1920-1990). However, if two sources of rainfall data are to be used together, it is necessary to ensure that they are compatible in terms of their statistical properties. A non-linear frequency of exceedance transformation technique was used to correct the satellite data to be more consistent with historical spatial rainfall estimates. The technique generated simulation results for the 2001 to 2006 period that were greatly improved compared to the direct use of the untransformed satellite data. While there remain some further questions about the use of satellite-derived rainfall data in different parts of the country, they do seem to have the potential to contribute to extending water resource modelling into the future.Keywords: satellite-based rainfall, hydrological model, water resources, South Afric

Application of satellite-derived rainfall estimates to extend water resource simulation modelling in South Africa

Spatially interpolated rainfall estimates from rain-gauges are widely used as input to hydrological models, but deriving accurate estimates at appropriate space and time scales remain a major problem. In South Africa there has been a gradual decrease in the number of active rain-gauges over time. Satellite-based estimates of spatial rainfall are becoming more readily available and offer a viable substitute. The paper presents the potential of using Climate Prediction Center African daily precipitation climatology (CPCAPC) satellite-based datasets (2001-2006) to drive a Pitman hydrological model which has been calibrated using gauge-based rainfall data (1920-1990). However, if two sources of rainfall data are to be used together, it is necessary to ensure that they are compatible in terms of their statistical properties. A non-linear frequency of exceedance transformation technique was used to correct the satellite data to be more consistent with historical spatial rainfall estimates. The technique generated simulation results for the 2001 to 2006 period that were greatly improved compared to the direct use of the untransformed satellite data. While there remain some further questions about the use of satellite-derived rainfall data in different parts of the country, they do seem to have the potential to contribute to extending water resource modelling into the future

Estimation of small reservoir storage capacities in Limpopo River Basin using geographical information systems (GIS) and remotely sensed surface areas: case of Mzingwane catchment

The current interest in small reservoirs stems mainly from their utilization for domestic use, livestock watering, fishing and irrigation. Rarely were small reservoirs considered in the water resources system even though they are important in water resource planning and management. The main limitation being lack of knowledge on small reservoir capacities, for the methodologies used to quantify physical parameters of reservoirs are costly, time consuming and laborious. To address this challenge an attempt has been made in this study to estimate small reservoir storage capacities using remotely sensed surface areas. A field study on 12 small reservoirs was carried out in Mzingwane catchment in Limpopo River Basin; Zimbabwe. The depths of water accompanied with their coordinates were measured; from which area and capacity were calculated for each reservoir using geographical information system based on data acquired from the field and that from satellite images. The output data was compared and a linear regression analysis was carried out to establish a power relationship between surface area and storage capacity of small reservoirs. The Pearson correlation analysis at 95% confidence interval indicated that the variances of the two surface areas (field area and image area) were not significantly different (p < 0.05). The findings from linear regression analysis (log capacity–log area) show that there exist a power relationship between remotely sensed surface areas (m^2) and storage capacities of reservoirs (m^3), with 95% variation of the storage capacity being explained by surface areas. The relationship can be used as a tool in decision-making processes in integrated water resources planning and management in the river basin. The applicability of the relationship to other catchments requires further research as well as investigating the impacts of small reservoirs in water resources available in the river basin by carrying out a hydrological modelling of the catchment

Evaluating uncertainty in water resources estimation in Southern Africa : a case study of South Africa

Hydrological models are widely used tools in water resources estimation, but they are simple representations of reality and are frequently based on inadequate input data and uncertainties in parameter values. Data observation networks are expensive to establish and maintain and often beyond the resources of most developing countries. Consequently, measurements are difficult to obtain and observation networks in many countries are shrinking, hence obtaining representative observations in space and time remains a challenge. This study presents some guidelines on the identification, quantification and reduction of sources of uncertainty in water resources estimation in southern Africa, a data scarce region. The analyses are based on example sub-basins drawn from South Africa and the application of the Pitman hydrological model. While it has always been recognised that estimates of water resources availability for the region are subject to possible errors, the quantification of these uncertainties has never been explicitly incorporated into the methods used in the region. The motivation for this study was therefore to contribute to the future development of a revised framework for water resources estimation that does include uncertainty. The focus was on uncertainties associated with climate input data, parameter estimation (and recognizing the uncertainty due model structure deficiencies) methods and water use data. In addition to variance based measures of uncertainty, this study also used a reservoir yield based statistic to evaluate model output uncertainty, which represents an integrated measure of flow regime variations and one that can be more easily understood by water resources managers. Through a sensitivity analysis approach, the results of the individual contribution of each source of uncertainty suggest regional differences and that clear statements about which source of uncertainty is likely to dominate are not generally possible. Parameter sensitivity analysis was used in identifying parameters which are important withinspecific sub-basins and therefore those to focus on in uncertainty analysis. The study used a simple framework for evaluating the combined contribution of uncertainty sources to model outputs that is consistent with the model limitations and data available, and that allows direct quantitative comparison between model outputs obtained by using different sources of information and methods within Spatial and Time Series Information Modelling (SPATSIM) software. The results from combining the sources of uncertainties showed that parameter uncertainty dominates the contribution to model output uncertainty. However, in some parts of the country especially those with complex topography, which tend to experience high rainfall spatial variability, rainfall uncertainty is equally dominant, while the contributions of evaporation and water use data uncertainty are relatively small. While the results of this study are encouraging, the weaknesses of the methods used to quantify uncertainty (especially subjectivity involved in evaluating parameter uncertainty) should not be neglected and require further evaluations. An effort to reduce data and parameter uncertainty shows that this can only be achieved if data access at appropriate scale and quality improves. Perhaps the focus should be on maintaining existing networks and concentrating research efforts on making the most out of the emerging data products derived from remote sensing platforms. While this study presents some initial guidelines for evaluating uncertainty in South Africa, there is need to overcome several constraints which are related to data availability and accuracy, the models used and the capacity or willingness to adopt new methods that incorporate uncertainty. The study has provided a starting point for the development of new approaches to modelling water resources in the region that include uncertain estimates

COMPLIANCE TO ENVIRONMENTAL IMPACT ASSESSMENT REGULATIONS BY A GOLD MINING COMPANY IN ZAKA DISTRICT, ZIMBABWE - A TRAVESTY OR TRIBUTE TO ENVIRONMENTAL DEMOCRACY AND JUSTICE

Zimbabwe’s Environmental Management Act has provisions promoting the conduct of environmental impact assessment (EIA) prior to project implementation to protect the environment and environmental rights. Using data collection methods inspired by phenomenological study, this paper discusses if EIA processes by a gold mining company had mainstreamed or marooned ‘access rights’ which are the cornerstone of environmental democracy. While the Zimbabwe’s EIA policy is applauded for covertly mainstreaming environmental democracy, research findings suggest that there exist gaps in the policy framework, policy and practice in promoting comprehensive environmental democracy. EIA processes are done to fulfil legal obligations but with little motivation to protect community interests as participation is symbolic. It is recommended to redesign EIA policy and embed broader attributes of environmental democracy such as locals’ participation in all EIA stages and inclusion of experts on community issues in the EIA review panel to promote fairness, inclusivity, transparency during EIA. Article visualizations

Photocatalytic evidence of the rutile-to-anatase electron transfer in titania

Layered anatase-rutile titania thin-films were synthesized via atmospheric-pressure chemical vapor deposition and characterized using X-ray diffraction, Raman spectroscopy and electron microscopy. The interposition of an amorphous TiO2-based interlayer allowed direct vapor deposition of anatase on a rutile substrate, which is otherwise hindered by templating. This resourceful approach and the subsequent crystallization of the amorphous layer after annealing of the films allowed investigation on the impact of an efficient interface of the two anatase-rutile phases in the photodegradation of a model organic pollutant. Clear evidence is presented on the synergy between the two polymorphs and more importantly, on the charge flow across the interface, which, against much conventional understanding, it involves electron transfer from rutile to anatase and is in agreement with a recent theoretical model and electron paramagnetic resonance data. Here, an increasing density of trapped electrons on the anatase surface of the A/R film is confirmed by photoreduction of silver. This observation is attributed to a defect-free efficient contact between the two phases and the presence of small rutile particles that promote rapid electron transfer at the A-R interface of the films