Multi-metric flood hazard characterization using daily rainfall runoff dynamics: a comparative analysis of Rufiji and Mirongo Catchments, Tanzania
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Date
2026-06-15
Journal Title
Journal ISSN
Volume Title
Publisher
MDPI
Abstract
Flood hazards are intensifying across Africa due to rapid urban expansion and hydro-
climatic variability. This study develops a multi-metric geospatial framework combining
extreme value analysis, hydrograph-based metrics, and dependence modelling to quan-
tify flood magnitude, frequency, timing, and joint risk dynamics. Daily precipitation
and streamflow reanalysis data (1985–2025) were analyzed for two contrasting Tanzanian
catchments: the large Rufiji basin (RU) and the smaller Mirongo catchment (MW). An-
nual maxima were modelled using the Generalized Extreme Value (GEV) distribution,
complemented by flow duration curves, peak-over-threshold detection, and regression-
copula dependence analysis. Results reveal strong hydrological contrasts. RU exhibits
amplified rare-event growth (design floods from ~2850 to 11,770 m3/s), extended recession
persistence (>100 days), low flashiness, and long rainfall-runoff lags (~15 days), indicating
storage-dominated behavior. MW shows smaller design floods (~80 to 370 m3/s), higher
flashiness, and short lags (~4 days), reflecting rapid, rainfall-driven response. Gaussian
copula parameters indicate moderate dependence in both basins (0.32 and 0.34), suggesting
that joint dependence alone does not distinguish flood mechanisms without complementary
metrics. The proposed framework improves basin-specific flood risk profiling and supports
geospatial early-warning system design in data-scarce Sub-Saharan environments.
Description
International Journal of Geo-Information
Keywords
Flood hazard characterization, Extreme value analysis, Rainfall-runoff dependence, Hydrological response dynamics, Geospatial flood risk profiling, Flow regime analysis, Peak-over-threshold modelling, Tanzania
Citation
https://www.mdpi.com/2220-9964/15/6/268