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Assessing water availability using remote sensing in South Rukuru and North Rumphi River Basin

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dc.contributor.author Gondwe, Gomi Thomas
dc.date.accessioned 2024-08-12T09:50:56Z
dc.date.available 2024-08-12T09:50:56Z
dc.date.issued 2024-07
dc.identifier.citation en_US
dc.identifier.uri http://repository.mzuni.ac.mw/handle/123456789/542
dc.description.abstract To effectively and efficiently assess water availability there is a need for good quality hydrological time series data. Globally there is a dense decline in hydrological data, which makes it difficult to assess water availability. Remotely acquired data can be an alternative data source. This study was conducted to assess water availability using remote sensing in South Rukuru and North Rumphi River Basin. To assess the water availability, a rainfall-runoff (soil moisture method) hydrological model was developed using the Water Evaluation and Planning (WEAP) modelling software. The WEAP inputs included the Global Land Data Assimilation System (GLDAS) climate datasets, Elevation data, and the Land Use Land Cover. The observed stream flow data was used for calibrating and validating the WEAP model. A hydrological data availability assessment was performed to check for gaps or missing data in the streamflow time series data. Although there were missing data, but with the threshold set, all stations under study had a good allowable overall data availability. The performance of the WEAP model simulation was assessed and the monthly measured and simulated streamflow statistics showed a positive strong relationship (R2 = 0.81, NSE = 0.81, IA = 0.95, KGE = 0.89 and PBIAS of -3.8) at station 7G18. Similarly, there was a very good agreement between the monthly measured and simulated streamflow at station 7H3 (R2 = 0.94, NSE = 0.93, IA = 0.98, KGE = 0.85 and PBIAS of -9.3). The hydrological response showed that in months at which the precipitation was at its peak in all the sub-basins, the water availability was also at peak. In general, The WEAP model has demonstrated the capability of GLDAS datasets to be used to assess water availability when there is insufficient, inconsistent or fragmented observed hydrological data. en_US
dc.language.iso en en_US
dc.publisher en_US
dc.title Assessing water availability using remote sensing in South Rukuru and North Rumphi River Basin en_US
dc.type Thesis en_US


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