Climate Change and Hydrological Extremes: Predicting and Preparing for the Impact on Water Resources

Understanding hydrological flow variability and quantification of groundwater recharge rates have been two of the cornerstones of sustainable water management for decades. The cause-and-effect relationship between flow variability and groundwater recharge is mainly dependent on climate type, for example Mediterranean climates vs tropical climates. Each climate type, has historically been predictable, for example mean annual temperature, temperature amplitude, mean annual precipitation and precipitation seasonality, implying that the system could be modelled so long as there were sufficient data records. However, two of the most commonly cited consequences of climate change are extreme weather events and hydroclimatic instability. Both processes break down the “predictable” component of hydro-climatic modelling and require a re-evaluation of both how models are set up for simulation of the hydrological system in any given location as well as the data needed to support these simulations. In short, are our current models ready for a dynamic climate and the associated hydrological system change? Adapting to this changed climate reality requires a multifaceted approach that integrates environmental parameters (temperature, evaporation, precipitation), hydrological tracers (e.g., water isotopes), hydro-climatic indices but also incorporates anthropogenic impacts (e.g., water impoundments). Often these parameters/tracers are governed by data constraints at the spatial (e.g., point data) and temporal scale (data continuity). In this contribution we examine the results of rainfall-runoff modelling in southern Africa where soil-moisture-deficit-index was used to show that headwater drought is a key indicator of severe oncoming dry conditions. In particular, changes in precipitation seasonality required the recalibration of model parameters for ‘wet’ and ‘dry’ periods in order to make the model adaptable to unpredictable climate variability. In spite of multiple calibration efforts, the temporal uncertainty remained significant due to anthropogenic changes in the system being modelled, for example water diversions into dams and abstractions for irrigation, changes that are likely to increase in the future. Stable water isotopes are sensitive tracers of the impact of climate change on hydrological flow because they are natural constitutes of water and their partitioning is strongly dependent on temperature. The integration of temperature sensitive hydrological tracers like water isotopes and along with other hydro-climatic indices within hydrological modelling systems can advance the development of flexible modelling tools that better accommodate climate variability. Doing so however, requires an assessment of what data records will be needed in the future, and taking steps to ensure that the collections of these datasets are prioritized.