Climate change impact on flood events of Pungwe river basin
Year: 2022
Type: conference-abstract
Abstract: Using the Mann-Kendal test, this study sought to analyse historical trends in hydro-meteorological variables and to establish future trends in selected variables. The study also sought to establish how climate change affects flood inundation extent for the Pungwe River Basin. The historical data was analysed to detect change-point using Pettitt, Standard Normal Homogeneity (SNH), Buishand range and Von Neumann tests. Climate ensembles of 10 Regional Climate Models (RCM’s) from the CORDEX project with RCP 2.6 and RCP 8.5 pathways were selected based on their documented performance on simulating temperature and rainfall in African basins. The historical rainfall and temperature time series and the downscaled climate data were input into the HBV model to generate streamflow for the period of 2022 to 2099. Flood extent for 50-, 100-and 1000-year return periods were predicted using the HEC-RAS hydraulic model. At the annual time-step, a change-point was detected in 2000 and 2012 for Metuchira and Catandica rainfall stations respectively. The results of the Mann Kendall test for 1982 to 2020 indicated a statistically significant and increasing annual trend for 5 of the 9 stations, namely Pungwe Sul, Nhazonia, Catandica, Metuchira, and Pungwe Fronteira. By 2070, annual rainfall at all the 9 studied meteorological stations is predicted to reduce by a maximum of 68 % (22.04 mm/day), with increasing inter-annual variability across all the RCM’s. Temperature is expected to increase by up to 15 % (4.5 oC) over the same period. The HBV model shows good performance for the Gorongosa Ponte station during calibration and validation with Nash Sutcliffe model efficiency 89 and 83 %, respectively. By the 2040s, simulations from HBV revealed that the peak flows for the Pungwe River Basin will vary from a maximum of about 120 % to a minimum of 57 % from the RCM’s. The analyses also show that by 2070 climate change may cause a minimum of 2784.4 km2 and a maximum of 8235.6 km2 in inundated areas for CanESM2 and CNRM-CM5 RCM’s, respectively. These results are essential for decision making on flood hazard mapping and early warning systems, prompting a pathway for sustainable development.
DOI: 10.5194/iahs2022-745
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4296700652