Exploring the link between meteorological drought and streamflow: Effects of climate‐catchment interaction

Abstract

In this paper, we perform a detailed regional analysis of the link between meteorological drought indices and streamflow for a comprehensive Austrian data set of 47 small to medium-size catchments in humid-temperate climate. Four drought indices considering different components of the catchment water balance are tested. We assess the quality of the link using rank correlation analysis, and the probability of detecting low-flow events by hit-scores. Overall, correlations range between 0.4 and 0.8 and differ significantly between regions. A stratified analysis shows that the link is much stronger (i) for summer low flows and droughts than for anomalies in general, and (ii) for more humid than more arid conditions. Under more humid conditions streamflow droughts of small to medium-size catchments are to a large extent generated by climate forcing and therefore well represented by a simple meteorological index. Under increasingly dry conditions, the climate signal gets less predictive, and storage properties of the underground become more important. A simple soil moisture accounting scheme (such as those of the Palmer index) can considerably improve the correlations. Overall, we conclude there is a significant link between meteorological drought and streamflow drought, except for catchments where groundwater storage and snow processes are important. The results are encouraging and provide a wealth of information which can profitably be used to set up statistical prediction models to estimate low flows from meteorological time series.

Multiscale evaluation of the Standardized Precipitation Index as a groundwater drought indicator

“…The best scores for H and F are 1 and 0, respectively, and the worst values are 0 and 1, respectively. More recently, Haslinger et al (2014) used a similar approach to assess the link between the SPI and other atmospheric indices (e.g., SPEI and PDSI) to detect low-flow events in the Austrian catchments based on hit rates (H ).…”

“…It is however noted that such analysis would require a good quality of impact variable data sets and, for many regions for which we need reliable and accurate data sets (e.g., on groundwater drought information), these observations are often not readily available. Nevertheless, the issue of analyzing an appropriate drought timescale is not only specific for the groundwater system, but is also relevant for several other hydrological and ecological systems (e.g., Pasho et al, 2010;Vicente-Serrano et al, 2011López-Moreno et al, 2013;VicenteSerrano et al, 2013;Haslinger et al, 2014;Bachmair et al, 2015;Van Loon, 2015). Figure 5 shows the exemplary time series of the SGI and SPI at 6 and 12 months of the accumulation periods for all wells and grid cells and their respective spatial averages for an overlapping period of 1995-2006.…”

“…The propagation of precipitation signals to groundwater droughts is largely controlled by both catchment and climatic characteristics such as terrain, soil and geological properties, and precipitation seasonality, snowmelt timing, and atmospheric water supply and evaporative demand. This results in a pronounced spatial variation of hydrologic (groundwater) drought characteristics (see, e.g., Peters et al, 2006;Bloomfield and Marchant, 2013;Haslinger et al, 2014;VicenteSerrano et al, 2012;Teuling et al, 2013;Van Loon et al, 2014;Stoelzle et al, 2014;Van Loon, 2015). On the aspect of climatic variables, the SPI that fully accounts for the atmospheric water supply side does not include the effects of the evaporative water demand that could be a determining factor in a hydrologic (groundwater) drought analysis (VicenteSerrano et al, 2010;Teuling et al, 2013).…”

“…Although the SPI is recognized as an effective meteorological drought index (Hayes et al, 2010) due to its relative ease of computation and comparability across climates, some studies have questioned its application for groundwater drought monitoring because the translation of precipitation deficits into hydrologic (groundwater) droughts is nonlinear (Bloomfield and Marchant, 2013;Teuling et al, 2013;Van Loon et al, 2014). Both catchment and climate characteristics such as the differences in underlying soil, terrain, vegetation and geological properties, precipitation seasonality, snowmelt timing, and the availability of atmospheric water supply and demand (evapotranspiration) control the development of hydrologic droughts and the resulting drought characteristics (Bloomfield and Marchant, 2013;Haslinger et al, 2014;Van Loon et al, 2014;Stoelzle et al, 2014;Van Loon, 2015). Recently, Vicente-Serrano et al (2010) introduced the Standardized Precipitation Evapotranspiration Index (SPEI) with a similar multitemporal characteristic to the SPI, but accounting for both the atmospheric water supply (precipitation) and evaporative demand (potential evapotranspiration).…”

“…While there are many studies that have focused on analyzing the propagation of meteorological droughts through the hydrologic systems for improved process understanding of the evolution of hydrologic (groundwater) droughts (e.g., Eltahir and Yeh, 1999;Peters et al, 2003Peters et al, , 2005Peters et al, , 2006Tallaksen et al, 2006Tallaksen et al, , 2009Weider and Boutt, 2010;Vicente-Serrano et al, 2012;Bloomfield and Marchant, 2013;Haslinger et al, 2014;López-Moreno et al, 2013;Van Loon et al, 2014), there is still a lack of comprehensive observation-based studies to verify whether hydrological drought proxies, like precipitation-based indices (SPI) and gridded data products, are suitable for groundwater drought monitoring at regional to local scales relevant for water management. In recent years there have been some efforts to analyze the relationship between meteorological and groundwater-based drought indices (Bloomfield and Marchant, 2013;Folland et al, 2015;Bachmair et al, 2015).…”