Hydropower Variability and Droughts from Stalagmite Analysis
Drought is Ireland’s forgotten hazard. With drier summers projected due to climate change, any future droughts will have major impacts on Ireland’s major water systems, including hydroelectric generation. The need to realise vulnerabilities to drought and quantify risk are hampered by a poor understanding of natural drought variability at event and decadal scale.
HYDROSTAL will reconstruct past drought variability in NW Ireland using stalagmite geochemistry and employ the results to model both changing hydrological conditions and hydroelectric generation in the River Erne catchment under varying rainfall and drought scenarios using a custom built AI hydrological model.
HYDROSTAL is a Sustainable Energy Authority of Ireland funded project to Dr. Nick Scroxton at the Irish Climate and Analysis Research Units, Department of Geography, Maynooth University.
HYDROSTAL will reconstruct past drought variability using stalagmite geochemistry
Speleothems will be used as high-resolution, precisely dated, paleoclimate archives to produce a 20th Century and Holocene records of past rainfall variability from in and around the River Erne catchment. Utilising state-of-the-art mixed dating and proxy methods, HYDROSTAL will combine stable isotope and trace element concentrations to deconvolve local rainfall amount and the climate drivers that underly any changes. Analytical work will be carried out at Maynooth University and the National Centre for Isotope Geochemistry at University College Dublin.
“We have little understanding of drought frequency, duration or severity beyond the last 200 years, including under both changing climates and abrupt climate events such as slowdowns in the Atlantic Meridional Overturning Circulation, a key climate tipping point for Ireland. To safeguard reliable hydroelectric generation there is a need to understand historical drought variability.”
HYDROSTAL will investigate the impacts of rainfall variability and drought on the hydrology of the River Erne using a custom built AI hydrological model
During HYDROSTAL we will build AI hydrological model that uses modern rainfall and streamflow observational data to predict the impact of drought events on the Erne catchment. Combining the AI hydrological model with an enhanced history of drought events will provide a stress test of future streamflow in the Erne to known historical and future potential droughts, ultimately with the aim of stress testing hydroelectric generation at Cliff and Cathleen's Falls.