Abstract

It is widely acknowledged that waterbodies are becoming increasingly affected by a wide range of drivers of change arising from human activity. To illustrate how this can be quantified a linked modelling approach was applied in the Thames river basin in southern UK. Changes to river flows, water temperature, river and reservoir quality were predicted under three contrasting future “storylines”; one an extension of present day rates of economic development, the others representing more extreme and less sustainable visions. Modelling revealed that lower baseflow conditions will arise under all storylines. For the less extreme storyline river water quality is likely to deteriorate but reservoir quality will improve slightly. The two more extreme futures could not be supported by current management strategies to meet water demand. To satisfy these scenarios, transfer of river water from outside the Thames river basin would be necessary. Consequently, some improvement over present day water quality in the river may be seen, and for most indicators conditions would be better than in the less extreme storyline. However, because phosphorus concentrations will rise, the invoked changes in water demand management would not be of a form suitable to prevent a marked deterioration in reservoir water quality.

Highlights

  • The application of the MARS storylines to the Thames river basin has highlighted a number of key messages:

  • Reduction of nutrients in rivers could help reduce the total phytoplankton biomass in reservoirs, but this might be mitigated by an increase in the dominance of that biomass by the toxic cyanobacteria species as the century progresses and becomes warmer

  • Projected climatic changes under the most extreme Representative Concentration Pathways (RCPs) might result in drying of the river for part of the year which could only be mitigated with drastic changes in water management through building a new reservoir or water transfer from outside the catchment

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Summary

Introduction

With the global population continuing to increase, water resources are becoming ever more threatened by drivers of change, such as urbanisation, agricultural intensification or climate change, that can be directly or indirectly attributed to human activity (Vörösmarty et al, 2010; Wen et al, 2017). The nature of these impacts may be highly dependent on local conditions and be time-variant, for example bed sediments potentially act as sources as well as sinks of phosphorus (Withers and Jarvie, 2008). For these reasons, to evaluate impacts on river basin-wide water resources a statistical or deterministic modelling approach that incorporates the effect of climate drivers is essential. The combined impacts of more than two stressors are much harder to identify without the application of modelling techniques (Hipsey et al, 2015)

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