Investigating groundwater recharge and dynamics at continental scales using comparative hydrology

Abstract

Groundwater is an essential resource for natural and human systems throughout the world and the rates at which aquifers are recharged constrain sustainable levels of consumption. However, we still lack a clear understanding of how groundwater recharge varies across continental scales, especially in data sparse regions where there may only be a few ground-based estimates across entire continents. In these regions, a lot of our understanding about groundwater recharge across continental scales is in instead derived from global-scale models, which often disagree and are seldom evaluated against ground-based estimates of recharge. Even in more data-rich environments, our understanding of groundwater dynamics across continental scales is mostly derived from continental to global-scale models.

In this thesis I try to improve our understanding of groundwater recharge and dynamics across continental scales, with the aim of directing the future development of continental to global-scale models. I initially focus on data sparse regions, namely Africa, and try to understand what is controlling the spatial variability of ground-based estimates of annual recharge and recharge ratio (annual recharge / annual precipitation) across the continent. I synthesize information about reported groundwater recharge controls from studies in Africa
and use this to guide the development of a classification, which I find can explain differences in ground-based recharge estimates. Following this, I evaluate recharge estimates from eight global-scale models that are part of the ISIMIP model inter-comparison project. By comparing global model recharge outputs to one another and to ground-based estimates, I find that model uncertainty is greatest in tropical and subtropical parts of Africa. I then focus on a more data rich region, i.e., the USA, to investigate the spatial patterns in observed groundwater dynamics across continental scales. This allows me to take a data-based approach when investigating the controls and drivers of groundwater behaviour at climatic, inter-annual and seasonal timescales.

Date of Award	2 Dec 2021
Original language	English
Awarding Institution	University of Bristol
Supervisor	Ross A Woods (Supervisor) & Rafael Rosolem (Supervisor)