Catchment memory explains hydrological drought forecast performance.

Hydrological drought forecasts outperform meteorological ones, which is anticipated coming from catchment memory. Yet, the importance of catchment memory in explaining hydrological drought forecast performance has not been studied. Here, we use the Baseflow Index (BFI) and the groundwater Recession Coefficient (gRC), which through the streamflow, give information on the catchment memory. Performance of streamflow drought forecasts was evaluated using the Brier Score (BS) for rivers across Europe. We found that BS is negatively correlated with BFI, meaning that rivers with high BFI (large memory) yield better drought prediction (low BS). A significant positive correlation between gRC and BS demonstrates that catchments slowly releasing groundwater to streams (low gRC), i.e. large memory, generates higher drought forecast performance. The higher performance of hydrological drought forecasts in catchments with relatively large memory (high BFI and low gRC) implies that Drought Early Warning Systems have more potential to be implemented there and will appear to be more useful.

Characterisation of the dynamics of past droughts.

Drought is a complex natural phenomenon. The description of the way in which drought changes (moves) in space may help to acquire knowledge on its drivers and processes to improve its monitoring and prediction. This research presents the application of an approach to characterise the dynamics of drought. Tracks, severity, duration, as well as localisation (onset and end position), and rotation of droughts were calculated. Results of calculated droughts were compared with documented information. Data from the Standardized Precipitation Evaporation Index (SPEI) Global Drought Monitor was used to identify droughts in India as an example for the period 1901-2013. Results show regions where droughts with considerable coverage tend to occur. Paths, i.e. consecutive spatial tracks, of six of the most severe reported droughts were analysed. In all of them, areas overlap considerably over time, which suggest that drought remains in the same region for a period of time. Results of this research are being used to build a model to predict the spatial drought tracks, incl. India (https://www.researchgate.net/project/STAND-Spatio-Temporal-ANalysis-of-Drought).

Heatwaves, droughts, and fires: Exploring compound and cascading dry hazards at the pan-European scale.

Compound and cascading natural hazards usually cause more severe impacts than any of the single hazard events alone. Despite the significant impacts of compound hazards, many studies have only focused on single hazards. The aim of this paper is to investigate spatio-temporal patterns of compound and cascading hazards using historical data for dry hazards, namely heatwaves, droughts, and fires across Europe. We streamlined a simple methodology to explore the occurrence of such events on a daily basis. Droughts in soil moisture were analyzed using time series of a threshold-based index, obtained from the LISFLOOD hydrological model forced with observations. Heatwave and fire events were analyzed using the ERA5-based temperature and Fire Weather Index datasets. The data used in this study relates to the summer seasons from 1990 to 2018. Our results show that joint dry hazard occurrences were identified in west, central, and east Europe, and with a lower frequency in southern Europe and eastern Scandinavia. Drought plays a substantial role in the occurrence of the compound and cascading events of dry hazards, especially in southern Europe as it drives duration of cascading events. Moreover, drought is the most frequent hazard-precursor in cascading events, followed by compound drought-fire events. Changing the definition of a cascading dry hazard by increasing the number of days without a hazard from 1 to 21 within the event (inter-event criterion), lowers as expected, the maximum number of cascading events from 94 to 42, and extends the maximum average duration of cascading events from 38 to 86 days. We had to use proxy observed data to determine the three selected dry hazards because long time series of reported dry hazards do not exist. A complete and specific database with reported hazards is a prerequisite to obtain a more comprehensive insight into compound and cascading dry hazards.

Evaluating skill and robustness of seasonal meteorological and hydrological drought forecasts at the catchment scale - Case Catalonia (Spain).

Robust sub-seasonal and seasonal drought forecasts are essential for water managers and stakeholders coping with water shortage. Many studies have been conducted to evaluate the performance of hydrological forecasts, that is, streamflow. Nevertheless, only few studies evaluated the performance of hydrological drought forecasts. The objective of this study, therefore, is to analyse the skill and robustness of meteorological and hydrological drought forecasts on a catchment scale (the Ter and Llobregat rivers in Catalonia, Spain), rather than on a continental or global scale. Meteorological droughts were forecasted using downscaled (5 km) probabilistic weather reforecasts (ECMWF-SEAS4). These downscaled data were also used to produce hydrological drought forecasts, derived from time series of streamflow data simulated with a hydrological model (LISFLOOD). This resulted in seasonal hydro-meteorological reforecasts with a lead time up to 7 months, for the time period 2002-2010. These monthly reforecasts were compared to two datasets: (1) droughts derived from a proxy for observed data, including gridded precipitation data and discharge simulated by the LISFLOOD model, fed by these gridded climatological data; and (2) droughts derived from in situ observed precipitation and discharge. Results showed that the skill of hydrological drought forecasts is higher than the climatology, up to 3-4 months lead time. On the contrary, meteorological drought forecasts, analysed using the Standardized Precipitation Index (SPI), do not show added value for short accumulation times (SPI1 and SPI3). The robustness analysis showed that using either a less extreme or a more extreme threshold leads to a large change in forecasting skill, which points at a rather low robustness of the hydrological drought forecasts. Because the skill found in hydrological drought forecasts is higher than the meteorological ones in this case study, the use of hydrological drought forecasts in Catalonia is highly recommended for management of water resources.

Moving from drought hazard to impact forecasts.

Present-day drought early warning systems provide the end-users information on the ongoing and forecasted drought hazard (e.g. river flow deficit). However, information on the forecasted drought impacts, which is a prerequisite for drought management, is still missing. Here we present the first study assessing the feasibility of forecasting drought impacts, using machine-learning to relate forecasted hydro-meteorological drought indices to reported drought impacts. Results show that models, which were built with more than 50 months of reported drought impacts, are able to forecast drought impacts a few months ahead. This study highlights the importance of drought impact databases for developing drought impact functions. Our findings recommend that institutions that provide operational drought early warnings should not only forecast drought hazard, but also impacts after developing an impact database.

Increased fire hazard in human-modified wetlands in Southeast Asia.

Vast areas of wetlands in Southeast Asia are undergoing a transformation process to human-modified ecosystems. Expansion of agricultural cropland and forest plantations changes the landscape of wetlands. Here we present observation-based modelling evidence of increased fire hazard due to canalization in tropical wetland ecosystems. Two wetland conditions were tested in South Sumatra, Indonesia, natural drainage and canal drainage, using a hydrological model and a drought-fire index (modified Keetch-Byram index). Our results show that canalization has amplified fire susceptibility by 4.5 times. Canal drainage triggers the fire season to start earlier than under natural wetland conditions, indicating that the canal water level regime is a key variable controlling fire hazard. Furthermore, the findings derived from the modelling experiment have practical relevance for public and private sectors, as well as for water managers and policy makers, who deal with canalization of tropical wetlands, and suggest that improved water management can reduce fire susceptibility.

Integration of research advances in modelling and monitoring in support of WFD river basin management planning in the context of climate change.

The integration of scientific knowledge about possible climate change impacts on water resources has a direct implication on the way water policies are being implemented and evolving. This is particularly true regarding various technical steps embedded into the EU Water Framework Directive river basin management planning, such as risk characterisation, monitoring, design and implementation of action programmes and evaluation of the "good status" objective achievements (in 2015). The need to incorporate climate change considerations into the implementation of EU water policy is currently discussed with a wide range of experts and stakeholders at EU level. Research trends are also on-going, striving to support policy developments and examining how scientific findings and recommendations could be best taken on board by policy-makers and water managers within the forthcoming years. This paper provides a snapshot of policy discussions about climate change in the context of the WFD river basin management planning and specific advancements of related EU-funded research projects. Perspectives for strengthening links among the scientific and policy-making communities in this area are also highlighted.