Informations et ressources scientifiques
sur le développement des zones arides et semi-arides

Accueil du site → Master → Afrique du Sud → 2022 → An assessment of the use of remote sensing to estimate catchment rainfall for use in hydrological modelling and design flood estimation

University of KwaZulu-Natal (2022)

An assessment of the use of remote sensing to estimate catchment rainfall for use in hydrological modelling and design flood estimation

Khakhu, Khodani.

Titre : An assessment of the use of remote sensing to estimate catchment rainfall for use in hydrological modelling and design flood estimation

Auteur : Khakhu, Khodani.

Université de soutenance : University of KwaZulu-Natal

Grade : Master of Science in Hydrology 2022

Résumé partiel
The accurate estimation of catchment rainfall is crucial, especially in hydrological modelling and flood hydrology which is used for the planning and design of hydrological infrastructures such as dams and bridges. Traditionally, catchment rainfall is estimated by making use of ground-based point rainfall measurements from rain gauges. The literature review conducted in this study supports that there is evidence of a decrease in the number of operational groundbased rainfall stations in South Africa which presents a challenge when estimating catchment rainfall for use in hydrological modelling and design flood estimation. Thus, innovative ways are required to estimate catchment rainfall and to improve the estimation of catchment design rainfall. This study investigated the use of remote sensing as an alternative way to estimate catchment design rainfall. To do this, a pilot study was first used to develop and test the methodology using a quaternary catchment that was selected based on the raingauge density. This was followed by the application of a refined methodology in another quaternary catchment which was used to verify the results that were obtained in the pilot study. After a comprehensive review of the literature, the remote sensing product selected for this study was the CHIRPS rainfall product. The methodology adopted first validated the remotely sensed rainfall data using the observed rainfall data and the estimated remotely sensed rainfall values were bias corrected using the observed rainfall data. The statistics that were used for validating are MAE, MBE, RMSE and D. The method that was used for bias correction was empirical quantile mapping Issues encountered, and as documented in the literature, include the unavailability of long periods of observed quality rainfall data and the limited and uneven spatial distribution of rainfall stations. Catchment rainfalls were estimated using observed rainfall, and this was assumed as the best estimate and was compared to the catchment rainfalls that were estimated using the biascorrected remotely sensed rainfalls.

Présentation

Version intégrale (3,7 Mb)

Page publiée le 4 janvier 2023