Evaluation of drought propagation in an ensemble mean of large-scale hydrological models

Abstract

Abstract. Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological drought? To answer this question, we evaluated the simulation of drought propagation in an ensemble mean of ten large-scale models, both landsurface models and global hydrological models, that participated in the model intercomparison project of WATCH (WaterMIP). For a selection of case study areas, we studied drought characteristics (number of droughts, duration, severity), drought propagation features (pooling, attenuation, lag, lengthening), and hydrological drought typology (classical rainfall deficit drought, rain-to-snow-season drought, wet-todry- season drought, cold snow season drought, warm snow season drought, composite drought).Drought characteristics simulated by large-scale models clearly reflected drought propagation; i.e. drought events became fewer and longer when moving through the hydrological cycle. However, more differentiation was expected between fast and slowly responding systems, with slowly responding systems having fewer and longer droughts in runoff than fast responding systems. This was not found using largescale models. Drought propagation features were poorly reproduced by the large-scale models, because runoff reacted immediately to precipitation, in all case study areas. This fast reaction to precipitation, even in cold climates in winter and in semi-arid climates in summer, also greatly influenced the hydrological drought typology as identified by the largescale models. In general, the large-scale models had the correct representation of drought types, but the percentages of occurrence had some important mismatches, e.g. an overestimation of classical rainfall deficit droughts, and an underestimation of wet-to-dry-season droughts and snow-related droughts. Furthermore, almost no composite droughts were simulated for slowly responding areas, while many multiyear drought events were expected in these systems.We conclude that most drought propagation processes are reasonably well reproduced by the ensemble mean of largescale models in contrasting catchments in Europe. Challenges, however, remain in catchments with cold and semiarid climates and catchments with large storage in aquifers or lakes. This leads to a high uncertainty in hydrological drought simulation at large scales. Improvement of drought simulation in large-scale models should focus on a better representation of hydrological processes that are important for drought development, such as evapotranspiration, snow accumulation and melt, and especially storage. Besides the more explicit inclusion of storage in largescale models, also parametrisation of storage processes requires attention, for example through a global-scale dataset on aquifer characteristics, improved large-scale datasets on other land characteristics...

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

“…We note that the approach chosen here is consistent with that commonly used in previous groundwater studies (e.g., Bloomfield and Marchant, 2013;Li and Rodell, 2015). On the other hand, the grid-scale analysis was carried out using the monthly estimates of drought indices gridded at a 0.5 • spatial resolution -the scale that is commonly used in regional-and global-scale drought studies (e.g., Sheffield et al, 2004;Andreadis et al, 2005;Gudmundsson et al, 2012;Seneviratne et al, 2012;Van Loon et al, 2012;Tallaksen and Stahl, 2014;Wanders et al, 2015). The gridded fields of drought indices were estimated using a procedure similar to the ones employed in creating multi-model drought indices (see, e.g., Mo and Lettenmaier, 2013;Nijssen et al, 2014).…”

“…An extensive multi-model study (Prudhomme et al, 2014), for example, projected increases in hydrological drought severity in many areas around the world. This approach also has limitations in its application to local-to regional-scale hydrological drought monitoring because of scale mismatches and some issues in the correct representation of storage in models (Gudmundsson et al, 2012;Van Loon et al, 2012;Tallaksen and Stahl, 2014). The importance of spatial variation in groundwater drought conditions resulting from complexity in subsurface conditions is increasingly recognized (Peters et al, 2006;Bloomfield and Marchant, 2013;Stoelzle et al, 2014).…”

The response of agricultural drought to meteorological drought and the influencing factors: A case study in the Wei River Basin, China

“…However, few studies (e.g., Pandey and Ramasastri 2001;Wang et al, 2011;Van Loon et al, 2012) were performed toward this purpose. Most of previous studies were conducted with the aid of hydrological models.…”

“…Wang et al (2011) used a hydro-agronomic model to study the propagation from meteorological drought to agricultural and hydrological droughts in central Illinois. Van Loon et al (2012) applied an ensemble mean of large-scale hydrological models to evaluate drought propagations. Although these models are effective tools for investigating drought propagation or the lag time of agricultural drought response to meteorological drought, they are data demanding and intensive computation.…”

Reconstruction of droughts in India using multiple land surface models (1951–2015)

“…S2a). These results indicate 10 that the root-zone soil moisture from the VIC model responds faster to the monsoon season precipitation than the other two LSMs, which can be associated with soil moisture persistence and model parameterization (Van Loon et al, 2012;Wang et al, 2009;Xia et al, 2012). However, we notice that the correlation between 4-month SPI at the end of the monsoon season and 4-month SSI declines rapidly after October (ONDJ, NDJF and so on) for the VIC and the Noah models (Fig.…”