Author(s): Abbey Buehler; Yunus Salami

Linked Author(s):

Keywords: Catchment classification; Transboundary Niger river basin; Hydrological model

Abstract: Transboundary rivers that run through separate water management jurisdictions with distinct hydrological characteristics sometimes experience competitive water usage. A system of classification of catchments along such river basins could help ease hydrological modelling on subbasin scales and hopefully refine the spatial and temporal resolution of information about adjacent catchments especially under changing natural and anthropogenic influences. However, there exists no universally accepted basis for hydrological classification of catchments. Some studies have applied hydrological models to catchment classification based upon criteria like streamflow regimes, hydrologic similarity, and hydroclimatic factors. But some constraints have included geographic or situational limitations of models, and large numbers of model parameters and data involved. The latter is counterproductive because the main purpose of catchment classification is to decrease the complexity of water systems by grouping them into several like categories. This study performed catchment classification in four different ways (quasi-runoff coefficients, empirical runoff equations, Muskingum-Cunge routing, and exceedance probabilities) in a major transboundary river whose basins sometimes experience water security issues. Using predefined catchment classification criteria and thirteen initial hydrological zones, the results across all four methods revealed five distinct catchment areas and suggest that a combination of different methodology may be needed for reliably classifying catchments. The methodology and information gathered could be used by stakeholders for applications in irrigation planning, river discharge modelling, navigation, flood risk management, improving dam storage and release policies, and optimizing food-water-energy nexus in the region.

DOI: https://doi.org/10.1080/15715124.2019.1628033

Year: 2020