Progress in rainfall-runoff modelling – contribution of remote sensing

Abstract

Surface runoff modelling is crucial, particularly in regions with inadequate hydrometric networks such as southern Africa. In southern Africa, rainfall patterns are erratic with frequent droughts being common. Yet due to population growth, water consumption has increased, posing significant challenges to water resources management to meet demand. It is also anticipated that climate change will increase rainfall variability and drought and this is likely to create challenges for water resources management. In this regard, understanding different water balance components is thus critical to conserve and improve water management strategies. In this paper we present progress and challenges in the modelling of surface runoff, which is one of the key components of water balance, affecting surface water availability. For decades, ground-based measurements and hydrological models have been used to understand surface runoff. Nevertheless, the emergences and advances in remote sensing provide a new horizon to model different water balance components. Specifically, the aim of this work is to provide a detailed overview of the different approaches for modelling surface runoff, which include the use of empirical models and remotely sensed data, in southern Africa. Further, the strengths and weaknesses of the highlighted approaches in understanding the variations in surface runoff are also discussed. The paper also recommends possible directions in which future studies may fill existing gaps in rainfall-runoff literature.

Keywords:

• climate variability
• empirical methods
• multispectral data
• remote sensing
• surface runoff
• water balance
• water scarcity
• water resource management

ORCID

Terence Mushore http://orcid.org/0000-0003-4279-8877