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W. Gumindoga

Researcher at University of Zimbabwe

Publications -  61
Citations -  986

W. Gumindoga is an academic researcher from University of Zimbabwe. The author has contributed to research in topics: Environmental science & Drainage basin. The author has an hindex of 14, co-authored 44 publications receiving 733 citations. Previous affiliations of W. Gumindoga include University of Twente.

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Assessing the relationship between water quality parameters and changes in landuse patterns in the Upper Manyame River, Zimbabwe

TL;DR: In this article, the impacts of landuse activities on the water quality of the Upper Manyame River was assessed through analyses of historical concentrations and pollution loads for TP, DO, COD, NH 3 -N, SS, Pb, NO 3, BOD 5, EC, PO 4 -P and TN at the Environmental Management Agency (EMA) gauging station CR21 sampling point for 1996, 2000/1 and 2008/9.
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Potential of weight of evidence modelling for gully erosion hazard assessment in Mbire District – Zimbabwe

TL;DR: In this paper, the potential of gully erosion could be successfully modelled as a function of seven environmental factors (landcover, soil type, distance from river and distance from road, Sediment Transport Index (STI), Stream Power Index (SPI), and Wetness Index (WI)) using a GIS-based Weight of Evidence Modelling (WEM) in the Mbire District of Zimbabwe.
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Estimation of actual evapotranspiration using the Surface Energy Balance System (SEBS) algorithm in the Upper Manyame catchment in Zimbabwe

TL;DR: In this paper, the Surface Energy Balance System for turbulent heat fluxes (SEBS) algorithm was applied to determine actual evapotranspiration in the Upper Manyame catchment in Zimbabwe.
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Ungauged runoff simulation in Upper Manyame Catchment, Zimbabwe: Application of the HEC-HMS model

TL;DR: In this article, the hydrologic Engineering Center Hydrologic Modelling System (HEC-HMS) model was applied to simulate runoff in the ten gauged and ungauged Upper Manyame subcatchments in Zimbabwe.
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Detection of land cover changes around Lake Mutirikwi, Zimbabwe, based on traditional remote sensing image classification techniques

TL;DR: In this paper, the authors mapped the land cover changes around Lake Mutirikwi in 1984-2011 using Landsat images using traditional image classification methods including the maximum likelihood classifier algorithm and tested the possibility of mapping the coverage and abundance of surface floating aquatic weeds.