Impact of the spatial variability of daily precipitation on hydrological projections: A comparison of GCM‐ and RCM‐driven cases in the Han River basin,Korea

In this study, we investigate the impact of the spatial variability of daily precipitation on hydrological projections based on a comparative assessment of streamflow simulations driven by a global climate model (GCM) and two regional climate models (RCMs). A total of 12 different climate input datasets, that is, the raw and bias‐corrected GCM and raw and bias‐corrected two RCMs for the reference and future periods, are fed to a semidistributed hydrological model to assess whether the bias correction using quantile mapping and dynamical downscaling using RCMs can improve streamflow simulation in the Han River basin, Korea. A statistical analysis of the daily precipitation demonstrates that the precipitation simulated by the GCM fails to capture the large variability of the observed daily precipitation, in which the spatial autocorrelation decreases sharply within a relatively short distance. However, the spatial variability of precipitation simulated by the two RCMs shows better agreement with the observations. After applying bias correction to the raw GCM and raw RCMs outputs, only a slight change is observed in the spatial variability, whereas an improvement is observed in the precipitation intensity. Intensified precipitation but with the same spatial variability of the raw output from the bias‐corrected GCM does not improve the heterogeneous runoff distributions, which in turn regulate unrealistically high peak downstream streamflow. GCM‐simulated precipitation with a large bias correction that is necessary to compensate for the poor performance in present climate simulation appears to distort streamflow patterns in the future projection, which leads to misleading projections of climate change impacts on hydrological extremes.     

Delineating coastal groundwater discharge processes in a wetland area by means of electrical resistivity imaging, 224Ra and 222Rn

Coastal groundwater discharge (CGD) plays an important role in coastal hydrogeological systems as they are a water resource that needs to be managed, particularly in wetland areas. Despite its importance, identifying and monitoring CGD often presents physical and logistical constraints, restraining the application of more traditional submarine groundwater discharge surveying techniques. Here we investigate the capability of electrical resistivity imaging (ERI) in the Peníscola wetland (Mediterranean coast, Spain). ERI surveying made it possible to identify and delineate an ascending regional groundwater flow of thermal and Ra‐enriched groundwater converging with local flows and seawater intrusion. The continuous inputs of Ra‐rich groundwater have induced high activities of Ra isotopes and ²²²Rn into the marsh area, becoming among the highest previously reported in wetlands and coastal lagoons. Geoelectrical imaging enabled inferring focused upward discharging areas, leaking from the aquifer roof through a confining unit and culminating as spring pools nourishing the wetland system. Forward modelling over idealized subsurface configurations, borehole datasets, potentiometric records from standpipe piezometers, petrophysical analysis, and four natural and independent tracers (²²⁴Ra, ²²²Rn, temperature and salinity) permitted assessing the geoelectrical model and a derived hydrogeological pattern. The research highlights the potential of ERI to improve hydrogeological characterization of subsurface processes in complex contexts, with different converging flows. Additionally, a hydrogeological conceptual model for a groundwater‐fed coastal wetland was proposed, based on the integration of surveying datasets. Copyright © 2013 John Wiley & Sons, Ltd.