Low flow analysis of ungauged river catchments in Ireland

Low flows in rivers can present a significant amount of issues including problems in relation to the assimilation capacity of the river, the ecosystem within the river, as well as the availability of the catchment’s water as... [ view full abstract ]

Low flows in rivers can present a significant amount of issues including problems in relation to the assimilation capacity of the river, the ecosystem within the river, as well as the availability of the catchment’s water as a resource for water supply. The development of the OPW Flood Studies Update (FSU) web-portal has meant that catchment data for the entire country is now readily available. In addition, there is significant body of freely available flow data from river gauging stations in place around the country. As a result of this, the development of predictor equations for various low flow indices is now considered possible for individual ungauged catchments. These equations can be validated on gauged catchments using existing river-flow data.
This paper presents the development of predictor equations for a 1 in 10 year low-flow event for the 7-Day sustained low flow (7-Day SLF), the annual minimum mean daily flow (Amin) and the 7-Day 10 year flow (7Q10) low flow indices. The method of stepwise regression is used to determine the most statistically significant catchment characteristics, of which twenty-one are considered.
The final models developed for the 7-Day SLF and 7Q10 indices contain five variables and have R squared values of 0.8248 and 0.7860 respectively. The Amin model contains six variables and has an R squared value of 0.7619. The most significant catchment characteristics for the development of low-flow regression analysis have also been identified.