Your search found 8 records
1 Gumindoga, W.; Rientjes, T.; Shekede, M. D.; Rwasoka, D. T.; Nhapi, I.; Haile, Alemseged Tamiru. 2014. Hydrological impacts of urbanization of two catchments in Harare, Zimbabwe. Remote Sensing, 6(12):12544-12574. [doi: https://doi.org/10.3390/rs61212544]
Hydrological factors ; Urbanization ; Impact assessment ; Catchment areas ; Water management ; Water resources ; Water table ; Land cover change ; Remote sensing ; Satellite imagery ; Rain ; Runoff ; Models ; Woodlands ; Deforestation ; Stream flow ; Soils ; Infiltration / Zimbabwe / Harare / Mukuvisi Catchment / Marimba Catchment
(Location: IWMI HQ Call no: e-copy only Record No: H046874)
(9.22 MB)
By increased rural-urban migration in many African countries, the assessment of changes in catchment hydrologic responses due to urbanization is critical for water resource planning and management. This paper assesses hydrological impacts of urbanization on two medium-sized Zimbabwean catchments (Mukuvisi and Marimba) for which changes in land cover by urbanization were determined through Landsat Thematic Mapper (TM) images for the years 1986, 1994 and 2008. Impact assessments were done through hydrological modeling by a topographically driven rainfall-runoff model (TOPMODEL). A satellite remote sensing based ASTER 30 metre Digital Elevation Model (DEM) was used to compute the Topographic Index distribution, which is a key input to the model. Results of land cover classification indicated that urban areas increased by more than 600 % in the Mukuvisi catchment and by more than 200 % in the Marimba catchment between 1986 and 2008. Woodlands decreased by more than 40% with a greater decrease in Marimba than Mukuvisi catchment. Simulations using TOPMODEL in Marimba and Mukuvisi catchments indicated streamflow increases of 84.8 % and 73.6 %, respectively, from 1980 to 2010. These increases coincided with decreases in woodlands and increases in urban areas for the same period. The use of satellite remote sensing data to observe urbanization trends in semi-arid catchments and to represent catchment land surface characteristics proved to be effective for rainfall-runoff modeling. Findings of this study are of relevance for many African cities, which are experiencing rapid urbanization but often lack planning and design.
2 Misi, A.; Gumindoga, W.; Hoko, Z. 2018. An assessment of groundwater potential and vulnerability in the upper manyame sub-catchment of Zimbabwe. Physics and Chemistry of the Earth, 105:72-83. [doi: https://doi.org/10.1016/j.pce.2018.03.003]
Groundwater assessment ; Groundwater pollution ; Water quality ; Drinking water ; Groundwater recharge ; Aquifers ; Mapping ; Geographical information systems ; Rain ; Catchment areas ; Principal component analysis ; Models / Zimbabwe / Upper Manyame Sub-Catchment
(Location: IWMI HQ Call no: e-copy only Record No: H049298)
(2.75 MB)
Severe depletion and pollution of groundwater resources are of rising concern in the Upper Manyame Sub-Catchment (UMSC); Zimbabwe's most urbanised sub-catchment. Despite groundwater playing a pivotal role in the provision of potable water in the sub-catchment, it is under serious threat from anthropogenic stressors which include sewage effluents and leachates from landfills, among others. Inadequate scientific knowledge pertaining to the spatio-temporal variability of groundwater storage and vulnerability in the UMSC is further compromising its sustainability. Therefore, comprehensive assessments of UMSC's Groundwater Potential (GP) and vulnerability are crucial for its effective management. This study assessed GP and vulnerability in the UMSC using Geographic Information Systems and Remote Sensing techniques. Groundwater conditioning factors: geology, slope, land-use, drainage density, topographic index, altitude, recharge and rainfall were used to develop GP zones. Validation of the GP map was done by correlating estimated GP with historical borehole yields. An assessment of groundwater vulnerability was done at micro-catchment level (Marimba) using the GOD model; a three parameter Index Overlay Model. Marimba is the most urbanised and has the second highest borehole density. It also exhibits similar landuse characteristics as the UMSC. Furthermore, groundwater quality in Marimba was assessed from 15 sampling sites. Fifteen drinking water parameters were analysed based on the standard methods for Water and Wastewater Examination. The potability of groundwater was then assessed by comparing the measured water quality parameters with the Standards Association of Zimbabwe (SAZ) drinking water standards and/or WHO guidelines for drinking water. Repeated Measures ANOVA and Principal Component Analysis (PCA) were used to assess the spatio-temporal variations in groundwater quality and to identify key parameters, respectively. About 72% (2725.9 km2) of the UMSC was found to be of moderate GP, while 19% and 9% accounted for high and low GP, respectively. Marimba vulnerability status was dominantly moderate (77.3%). Parameters: EC, pH, coliforms, TDS, total hardness, Fe, NH4+ and turbidity exceeded SAZ and/or WHO drinking water limits on most sampling sites with DO, total and faecal coliforms showing significant variations (p < 0.05). Four Principal Components representing 84% of the cumulative variance were extracted; with PC1, PC2, PC3 and PC4 contributing 38%, 19.1%, 14.3% and 12.85%, respectively. PC1 was characterized by pH, TDS, EC and total hardness. PC2's variance was associated with elevated levels of Cl-, Zn and Cu. PC3 had high loadings of total and faecal coliforms, Fl- and turbidity while PC4 was characterized by high loadings of Pb, Fe, ammonia and turbidity. The variation in the nature of the parameters across PCs explains the complexity of pollutants within the micro-catchment. PC2 and PC4 were largely characterized by metallic compounds, suggesting pollution from mineral dissolution into the aquifers e.g. from industrial areas and dumpsites. PC3 indicate the contribution of domestic waste e.g. faecal waste from waste pipe leakages and poorly constructed pit latrines. The findings of this study are useful decision-making tools on groundwater utilisation and groundwater protection.
3 Gumindoga, W.; Rientjes, T. H. M.; Haile, Alemseged Tamiru; Makurira, H.; Reggiani, P. 2019. Performance of bias-correction schemes for CMORPH rainfall estimates in the Zambezi River Basin. Hydrology and Earth System Sciences, 23(7):2915-2938. [doi: https://doi.org/10.5194/hess-23-2915-2019]
Rainfall patterns ; Precipitation ; Estimation ; Satellite observation ; Performance evaluation ; River basins ; Water resources ; Weather forecasting ; Meteorological stations ; Rain gauges / Botswana / Malawi / Mozambique / Zambia / Zimbabwe / Zambezi River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H049387)
https://www.hydrol-earth-syst-sci.net/23/2915/2019/hess-23-2915-2019.pdf
https://vlibrary.iwmi.org/pdf/H049387.pdf
https://vlibrary.iwmi.org/pdf/H049387.pdf
(4.60 MB) (4.60 MB)
Satellite rainfall estimates (SREs) are prone to bias as they are indirect derivatives of the visible, infrared, and/or microwave cloud properties, and hence SREs need correction. We evaluate the influence of elevation and distance from large-scale open water bodies on bias for Climate Prediction Center-MORPHing (CMORPH) rainfall estimates in the Zambezi basin. The effectiveness of five linear/non-linear and time–space-variant/-invariant bias-correction schemes was evaluated for daily rainfall estimates and climatic seasonality. The schemes used are spatio-temporal bias (STB), elevation zone bias (EZ), power transform (PT), distribution transformation (DT), and quantile mapping based on an empirical distribution (QME). We used daily time series (1998–2013) from 60 gauge stations and CMORPH SREs for the Zambezi basin. To evaluate the effectiveness of the bias-correction schemes spatial and temporal crossvalidation was applied based on eight stations and on the 1998–1999 CMORPH time series, respectively. For correction, STB and EZ schemes proved to be more effective in removing bias. STB improved the correlation coefficient and Nash–Sutcliffe efficiency by 50 % and 53 %, respectively, and reduced the root mean squared difference and relative bias by 25 % and 33 %, respectively. Paired t tests showed that there is no significant difference (p- q) plots. The spatial cross-validation approach revealed that most bias-correction schemes removed bias by >28 %. The temporal cross-validation approach showed effectiveness of the bias-correction schemes. Taylor diagrams show that station elevation has an influence on CMORPH performance. Effects of distance >10 km from large-scale open water bodies are minimal, whereas effects at shorter distances are indicated but are not conclusive for a lack of rain gauges. Findings of this study show the importance of applying bias correction to SREs.
4 Gumindoga, W.; Rientjes, T. H. M.; Haile, Alemseged Tamiru; Makurira, H.; Reggiani, P. 2019. Performance evaluation of CMORPH satellite precipitation product in the Zambezi Basin. International Journal of Remote Sensing, 40(20):7730-7749. [doi: https://doi.org/10.1080/01431161.2019.1602791]
Rain ; Precipitation ; Satellites ; Weather forecasting ; Performance evaluation ; River basins ; Meteorological stations ; Observation ; Hydrology ; Deltas / Botswana / Mozambique / Malawi / Zimbabwe / Zambia / Zambezi River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H049388)
(2.28 MB)
For evaluation of the Climate Prediction Center-MORPHing (CMORPH) satellite rainfall product in the Zambezi Basin, daily time series (1998–2013) of 60 rain gauge stations are used. Evaluations for occurrence and rain rate are at sub-basin scale and at daily, weekly, and seasonal timescale by means of probability of detection (POD), false alarm ratio (FAR), critical success index (CSI) and frequency bias (FBS). CMORPH predicts 60% of the rainfall occurrences. Rainfall detection is better for the wet season than for the dry season. Best detection is shown for rainfall rates smaller than 2.5 mm/day. Findings on error decomposition revealed sources of Hit, Missed and False rainfall bias. CMORPH performance (detection of rainfall occurrences and estimations for rainfall depth) at sub-basin scale increases when daily estimates are accumulated to weekly estimates. Findings suggest that for the Zambezi Basin, errors in CMORPH rainfall should be corrected before the product can serve applications such as in hydrological modelling that largely rely on reliable and accurate rainfall inputs.
5 Muhoyi, H.; Gumindoga, W.; Mhizha, A.; Misi, S. N.; Nondo, N. 2022. Water quality monitoring using remote sensing, lower Manyame Sub-Catchment, Zimbabwe. Water Practice and Technology, 17(6):1347-1357. [doi: https://doi.org/10.2166/wpt.2022.061]
Water quality ; Monitoring ; Remote sensing ; Catchment areas ; Chemical oxygen demand ; Total nitrogen ; Total phosphorus ; Surface water ; Satellite imagery ; Lakes / Zimbabwe / Lower Manyame Sub-Catchment / Manyame River
(Location: IWMI HQ Call no: e-copy only Record No: H051218)
https://iwaponline.com/wpt/article-pdf/17/6/1347/1067109/wpt0171347.pdf
https://vlibrary.iwmi.org/pdf/H051218.pdf
https://vlibrary.iwmi.org/pdf/H051218.pdf
(0.67 MB) (688 KB)
The Lower Manyame Sub-catchment (LMS) is one of the most heavily polluted in Zimbabwe. Its waters are valuable for irrigation, domestic and industrial purposes. LMS has serious eutrophication problems emanating from human activities within it, and lakes Manyame and Chivero upstream. Data collected from October 2018 to April 2019 were used to test an integrated methodology based on field measurements and remote sensing. This study illustrates the production of multitemporal spatialised maps of total suspended solids (TSS), chemical oxygen demand (COD), total nitrogen (TN) and total phosphorus (TP) concentrations from satellite data acquired from Sentinel-2. The analysis confirmed the pollution (eutrophic and organic matter) status of LMS water, for the period considered by this research. As a result, careful land planning must be done through the joint operation of local authorities, regional agencies and regional institutions, since Manyame River is a tributary of the Zambezi River (a transboundary river).
6 Chisadza, B.; Mashakani, B.-L.; Gwate, O.; Chiwara, P.; Choruma, D.; Gumindoga, W.. 2022. Determination of groundwater potential zones using geographic information systems and remote sensing in Lupane District, Zimbabwe. Irrigation and Drainage, 13p. (Online first) [doi: https://doi.org/10.1002/ird.2741]
Groundwater potential ; Geographical information systems ; Remote sensing ; Groundwater recharge ; Boreholes ; Energy ; Foods ; Nexus approaches ; Land cover ; Land use ; Soil types ; Slope ; Drainage ; Geology ; Models / Zimbabwe / Lupane
(Location: IWMI HQ Call no: e-copy only Record No: H051288)
(3.02 MB)
Groundwater is a vital natural resource for agricultural, domestic and industrial uses. Understanding the spatial distribution of groundwater resources is critical to improving the relationship between water, food and energy. This article uses GIS and remote sensing and the analytical hierarchy process (AHP) technique to map the potential groundwater zones in the Lupane district. Lineaments, drainage density, slope, soil type, geology and land use land cover (LULC) were used to create thematic maps in ArcMap. The thematic maps were weighted and ranked according to their influence on the movement and occurrence of groundwater. To validate the groundwater potential zones (GWPZs) model, we used LULC and 675 perennial and seasonal boreholes in the Lupane district. The LULC and borehole maps were overlaid on the modelled GWPZ map to highlight their distribution. The GWPZ results show that areas with good potential make up the majority of the district (41%), followed by areas with moderate potential (30%), poor potential (14%), very good potential (13%) and very poor potential (2%). The results showed that 74% (499) of perennial boreholes overlapped the zones with good, moderate and/or very good groundwater potential. The GWPZ map can therefore be used as a preliminary reference when selecting suitable sites for the exploitation of groundwater resources. Further testing of the model using both seasonal and year-round yields and depths from boreholes is recommended.
7 Mokhesuoe, F.; Gumindoga, W.; Molete, S. F. 2023. Wetland water balance assessment: a case study of the Sosa Wetland, Maseru, Lesotho. Water Practice and Technology, 18(3):738-752. [doi: https://doi.org/10.2166/wpt.2023.013]
Wetlands ; Water balance ; Assessment ; Land use ; Land cover ; Evapotranspiration ; Vegetation ; Precipitation ; Grasslands ; Cultivation ; Stream flow ; Models ; Case studies / South Africa / Lesotho / Maseru / Sosa Wetland
(Location: IWMI HQ Call no: e-copy only Record No: H051915)
https://iwaponline.com/wpt/article-pdf/18/3/738/1198007/wpt0180738.pdf
https://vlibrary.iwmi.org/pdf/H051915.pdf
https://vlibrary.iwmi.org/pdf/H051915.pdf
(0.91 MB) (928 KB)
The Sosa wetland is a sensitive wetland, situated at the headwaters of the Jordan catchment in Maseru. Due to unregulated land use activities in the past decades (2010–2020), the Sosa wetland nearly dried up. Therefore, this study performed a wetland water balance of the Sosa wetland in Lesotho for the period of 1975–2020 using GIS and remote sensing. Landsat imageries of 1975–2020 were used for land use and land cover while the Penman -Monteith and Thornthwaite methods were used to estimate evapotranspiration. Results show that water/marsh, cultivation, settlements and bare-land increased by 2.04, 4.1, 5.82 and 28.71%, respectively, from 1975 to 2020. Forest and shrubs as well as grasslands decreased by 38.83 and 1.76%, respectively, from 1975 to 2020. Evapotranspiration estimates for the period 1984–2020 were in the range of 900 -1,071 mm/year which is substantially greater than the annual mean rainfall of the catchment which ranges from 550 to 850 mm/year. The most sensitive wetlands are found in the middle reach of the catchment and at the headwaters occupying about 16.03% of the catchment, whereas moderately sensitive wetlands occupy 39.75%. The water balance closure as a ratio of rainfall received ranged from -3.13 to -3.5.
8 Magidi, J.; Nhamo, L.; Kurwakumire, E.; Gumindoga, W.; Mpandeli, S.; Liphadzi, S.; Mabhaudhi, Tafadzwanashe. 2024. Catalysing cleaner production systems: benchmarking with the COVID-19 lockdowns in South Africa. In Nhamo, L.; Mpandeli, S.; Liphadzi, S.; Mabhaudhi, Tafadzwanashe. (Eds.). Circular and transformative economy: advances towards sustainable socio-economic transformation. Boca Raton, FL, USA: CRC Press. pp.242-259. (Africa Circular Economy Series) [doi: https://doi.org/10.1201/9781003327615-13]
(Location: IWMI HQ Call no: e-copy only Record No: H052580)
https://www.taylorfrancis.com/chapters/oa-edit/10.1201/9781003327615-13/catalysing-cleaner-production-systems-james-magidi-luxon-nhamo-edward-kurwakumire-webster-gumindoga-sylvester-mpandeli-stanley-liphadzi-tafadzwanashe-mabhaudhi
https://vlibrary.iwmi.org/pdf/H052580.pdf
https://vlibrary.iwmi.org/pdf/H052580.pdf
(1.45 MB) (1.45 MB)
Industrial and vehicular emissions are among the major contributors to greenhouse gas (GHG) atmospheric concentration, causing ozone depletion, climate change, and health risks. Reducing air pollution to permissible levels fosters human and environmental health through reduced radiation, stabilised temperatures, and improved air quality. This chapter quantifies the spatio-temporal atmospheric pollution in South Africa using remotely sensed satellite data acquired between April 2019 and April 2020, just before and during the coronavirus disease 2019 (COVID-19) pandemic lockdown. Remotely sensed data are essential for quantifying and monitoring air quality over time by assessing the change in pollution indicators such as fine particulate matter (PM2.5) and nitrogen dioxide (NO2) content. An analysis of results reveals that NO2 levels in South Africa reduced by 20.5% during the COVID-19 lockdown period compared to normal economic activity. The findings were used to develop a framework to guide policy and support decision-making to formulate coherent strategies for reducing pollution and alignment towards a low-carbon economy. Developing controlling and monitoring systems that capture episodic pollution events and enhance cleaner production mechanisms is critical for ensuring low carbon emissions and reducing environmental and human health risks. Although most NO2 emissions are generated in urban environments, the effects are felt far beyond, with detrimental effects on the environment and human health.
Powered by DB/Text WebPublisher, from
