Abstract
Clean water is essential for supporting human livelihoods and maintaining ecosystem health. However, our knowledge of water quality is severely impaired by a lack of quantitative information. Being under-monitored and often imperceptible to the human eye, water pollution has been branded an “invisible crisis”. Protecting and improving the quality of
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surface waters globally is contingent upon an improved understanding of the problem and its drivers. Process-based models are tools that can supplement our knowledge of water quality beyond what is possible using in situ measurements alone.
This thesis introduces and applies the Dynamical Surface Water Quality (DynQual) model, a high-resolution global surface water quality model for simulating water temperature and concentrations of salinity (total dissolved solids; TDS), organic (biological oxygen demand; BOD) and pathogen (fecal coliform; FC) pollution. DynQual was used to provide a global assessment of past and current surface water quality. Modelled results demonstrate that surface water quality issues are globally relevant, with exceedances of key concentration thresholds for TDS, BOD and FC pollution occurring across all world regions albeit with different frequencies and magnitudes. Current year-round and multi-pollutant hotspots are located across northern India and eastern China, whereas trends towards surface water quality deterioration in the last ~40 years are most profound in Sub-Saharan Africa and southern Asia.
Process-based models provide unique opportunities to quantitatively assess the impact of future change on the availability and quality of water resources. This includes exploring the effectiveness of management strategies for improving water quality. In this thesis, DynQual was applied to assess the effectiveness of halving the proportion of untreated wastewater entering the environment by 2030 for improving ambient surface water quality. While substantial reductions in organic (BOD) and pathogen (FC) pollution are achieved, changes to the frequency and magnitude of water quality threshold exceedances drastically vary across world regions. Particularly in the developing world, reductions in pollutant loadings are locally effective but the transmission of pollution from upstream areas still leads to water quality issues downstream.
This thesis also presents the first assessment of the impact of global change on water quality, based on state-of-the-art projections of societal change and trajectories of climate change. Results indicate that the proportion of the global population exposed to salinity, organic and pathogen pollution by the end of the century ranges from 17 - 27%, 20 - 37% and 22 - 44%, respectively, with poor surface water quality disproportionately affecting people living in developing countries. Exhibiting the largest increases in both the absolute and relative number of people exposed to polluted surface water, irrespective of climate change and socioeconomic development scenario, this thesis concludes that Sub-Saharan Africa will increasingly become the key hotspot of surface water pollution.
Inability to meet our clean water demands is considered one of the major risks to humankind both in terms of likelihood and potential impacts. This thesis highlights the need to better understand and account for water quality aspects, in addition to water availability aspects, in order to achieve sustainable management of water resources globally.
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