Estimating runoff from ungauged catchments for reservoir water balance in the Lower Middle Zambezi Basin

The Lower Middle Zambezi Basin is sandwiched between three hydropower dams; Kariba, Kafue (Itezhi-tezhi) and Cahora Bassa. The operation of the upstream dams impacts on the inflows into the downstream Cahora Bassa Dam which, in turn, affects the area inundated upstream of the Cahora Bassa Dam. This study applied a rainfall-runoff model (HEC-HMS) and GIS techniques to estimate both the gauged and ungauged runoff contribution to the water balance of Cahora Bassa. The rivers considered in the study are the Zambezi, Kafue, Luangwa, Chongwe, Musengezi and Manyame. Missing data were generated using the mean value infilling method. The DEM hydro-processing technique was used to determine the spatial extent of the ungauged area. A hydrological model, HEC- HMS, was used to simulate runoff from the ungauged catchments. Results from the study show that the ungauged catchment contributes about 12% of the total estimated inflows into the Cahora Bassa Dam. Averaged results over 30 years show total inflows of 71.73 x 109 m3/yr, total outflows of 52.25 x 109 m3/ yr and a residual storage of 20 x 109 m3/yr. The study successfully estimated the water balance of the Middle Zambezi Basin which, in turn, may help to inform the operation of the Cahora Bassa Dam and management of artificial floods in the basin.Keywords: Cahora Bassa, DEM hydroprocessing, HEC-HMS, remote sensing, reservoir operation, runoff simulatio

Effect of landcover/land-use changes on water availability in and around Ruti Dam in Nyazvidzi catchment, Zimbabwe

The aim of this study was to quantify the upstream land-use and landcover changes and assess their effect on Ruti Dam levels and water availability in Nyazvidzi catchment. Remote-sensing techniques, hydrologic modelling and statistical inference were applied. Spatial landcover dynamics were derived from Landsat satellite data for the years 1984, 1990, 1993, 1996, 2003, 2008, and 2013 using the maximum likelihood classification technique. Results showed that forests and shrubs decreased by 36% between 1984 and 2013 whilst cultivated areas increased by 13% over the same period. The HEC-HMS rainfall-runoff model was used to simulate steamflow for the Nyazvidzi catchment, Zimbabwe. For the calibration period (2000–2001), a satisfactory Nash–Sutcliffe efficiency (NSE) model peformance of 0.71 and relative volume error (RVE) of 10% were obtained. Model validation (1995—1997) gave a NSE of 0.61 and RVE of 12%. We applied the Mann-Kendall trend test to assess for monotonic trends in runoff over the study period and the results showed that there were significant decreases in observed runoff at Station E140 (monthly time scale) and at Stations E62 and E140 (seasonal time scale). Results showed that the wet season (Nov–Feb) had higher mean water balance values with an excess runoff of 8.12 mm/month. The dry season (April— Sept) had lower mean water balance values, with the lowest at 0.04 mm/month. Strong positive relationships (r2) between dam levels and land-use changes were obtained as follows: bare (0.95), cultivation (0.76) and forests (0.98). The relationship between runoff generated and land-use changes was found to be relatively weaker (0.54 for forests, 0.51 for bare and 0.14 for cultivation). Findings of this study underscore the relevance of applying hydrological models, remote sensing and statistical inference in quantifying and detecting environmental changes, as well as how they affect the availability and the quality of water resources in space and time

The spatio-temporal variation of the 2014 Tokwe-Mukosi floods: a GIS and remote sensing based approach

Floods are natural hazards that have always created an unexpected threat to human life and property. When severe floods occur in areas occupied by humans, they can create natural disasters that involve the loss of human life, loss of property and may result in serious disruption to the ongoing activities of urban and rural communities. The unanticipated and incessant heavy rains in 2014 that pounded theTokwe-Mukosidam catchment from late January and March led to flooding of the dam basin affecting villagers in the area. The affected villages were mainly those that had not headed to the call by government to relocate to identified land. This created an emergency situation due to increase in volume of water in the dam reservoir. The increase in volume contributed to flooding of the dam basin, marooning the houses and fields in the upstream and destroying infrastructure. Earth observation techniques and GIS can contribute towards more accurate flood hazard mapping that can be used to assess damage to residential properties, infrastructure and agricultural crops as well as provide information for emergency relief work. The objective of this study was to use remote sensing and Geographic Information Systems to determine the spatial variation of flood hazard in the Tokwe-Mukosi Dam area during and after the 2014 flooding using the (recent launched 2013) 30m Landsat 8 OLI based images via GloVis website (http://glovis.usgs.gov/).A segment map digitizing technique in ILWIS was used to separate the water and non-water areas. Areas occupied by water in the different dates were also determined through histogram analysis. The digitized segment maps was exported as a shapefile in ArcGIS and then over-layed with other important data such as soil type and land cover maps. The land surface characteristics (such as elevation, land cover, and distance from stream network, rivers and road network) were also related with the presence and absence data (flood condition) using a spatial logistic regression in SPSS v17.0. Results indicate that the water inundated area increased by more than 40% from January 2013 (just before the floods) to February 2014 (During the floods) and April 2014 (after the floods). Factors such as elevation, distance from river network had a signification relationship (p<0.05) with flood hazard. Thus the use of remote sensing and statistical techniques can be a valuable tool for flood plain zoning and disaster preparedness for the settlements in the Tokwe-Mukosi Dam area. It can also help to prevent undesirable side effects of the developments and can assist in implementing effective mitigation measures.,Zimbabwe Institution of Engineer

Evaluation of sub daily satellite rainfall estimates through flash flood modelling in the Lower Middle Zambezi Basin

Flash floods are experienced almost annually in the ungauged Mbire District of the Middle Zambezi Basin. Studies related to hydrological modelling (rainfall-runoff) and flood forecasting require major inputs such as precipitation which, due to shortage of observed data, are increasingly using indirect methods for estimating precipitation. This study therefore evaluated performance of CMORPH and TRMM satellite rainfall estimates (SREs) for 30 min, 1 h, 3 h and daily intensities through hydrologic and flash flood modelling in the Lower Middle Zambezi Basin for the period 2013–2016. On a daily timestep, uncorrected CMORPH and TRMM show Probability of Detection (POD) of 61 and 59 %, respectively, when compared to rain gauge observations. The best performance using Correlation Coefficient (CC) was 70 and 60 % on daily timesteps for CMORPH and TRMM, respectively. The best RMSE for CMORPH was 0.81 % for 30 min timestep and for TRMM was 2, 11 % on 3 h timestep. For the year 2014 to 2015, the HEC-HMS (Hydrological Engineering Centre-Hydrological Modelling System) daily model calibration Nash Sutcliffe efficiency (NSE) for Musengezi sub catchment was 59 % whilst for Angwa it was 55 %. Angwa sub-catchment daily NSE results for the period 2015–2016 was 61 %. HEC-RAS flash flood modeling at 100, 50 and 25 year return periods for Angwa sub catchment, inundated 811 and 867 ha for TRMM rainfall simulated discharge at 3 h and daily timesteps, respectively. For CMORPH generated rainfall, the inundation was 818, 876, 890 and 891 ha at daily, 3 h, 1 h and 30 min timesteps. The 30 min time step for CMORPH effectively captures flash floods with the measure of agreement between simulated flood extent and ground control points of 69 %. For TRMM, the 3 h timestep effectively captures flash floods with coefficient of 67 %. The study therefore concludes that satellite products are most effective in capturing localized hydrological processes such as flash floods for sub-daily rainfall, because of improved spatial and temporal resolution

A GIS-based approach for identifying suitable sites for rainwater harvesting technologies in Kasungu District, Malawi

A GIS-based approach for identifying suitable sites for rainwater harvesting (RWH) technologies was developed and applied in Kasungu District, Malawi. Data were obtained from reports, socio-economic survey documents of the area and maps. Field surveys were conducted in the villages of Chipala Extension Planning Area (EPA), in order to identify and evaluate the performance of existing RWH interventions, and determine factors for locating suitable areas for RWH. Observed soil moisture content was used to assess the water retention performance of the prevalent RWH technologies: contour tied ridging and soil mulching. A GIS-based Soil Conservation Service Curve Number (SCS-CN) method was used to map runoff potential for areas with RWH technologies, using physical factors of rainfall, land use, soil type and slope to estimate runoff potential. This was then integrated in a GIS database, with social-economic factors in the form of household income level and environmental factors, including impacts of implementing RWH, to determine the suitability of land areas for RWH in Kasungu District. One way analysis of variance (ANOVA) was used to test the impact of identified technologies by comparing the moisture content measurements for each of the identified technologies at 5% level of significance. The ANOVA results showed a statistically significant difference in the moisture measurements for the three technologies identified (P &lt; 0.05). The RWH suitability map for the study area showed that 0.2% of the area considered had very high potential, 33.5% high, 55.9% moderate, 10.1% marginal and 0.3% not suitable for in-field RWH. The model was verified by locating the existing RWH on the suitability map obtained from GIS: 81% of RWH were located in the highly and moderately suitable areas whilst only 13% were located in areas of low suitability. Hence the developed model can reliably be used to predict potential areas for RWH

Predicting streamflow for land cover changes in the Upper Gilgel Abay River Basin, Ethiopia : A TOPMODEL based approach

Hydrological effects of land cover changes and runoff contributions from respective land cover types are analysed for the Upper Gilgel Abay basin in Ethiopia. Runoff production and streamflow are simulated by the TOPMODEL approach. For impact assessment of land cover changes, satellite based land covers for the years 1973, 1986 and 2001 are considered. Catchment topography as well as land cover and vegetation characteristics are derived from satellite images and serve to estimate model parameters. Land cover in TOPMODEL has been implemented by spatial units based on the actual size of each land cover type. The topographic index distribution function, which is an important input to the TOPMODEL, is prepared for each land cover type. Simulations are also performed for specific land cover types to allow inter comparison of hydrological responses. Results showed that the highest peak flow as well as the annual streamflow volume varied among the land cover types agriculture, forest and grassland which dominate land cover in the catchment. Results of this study show that in data poor basins, satellite images provide suitable land surface data for rainfall–runoff modelling and land surface parameterization. Findings are of relevance for many African rural catchments which experience rapid population increases and resource scarcity