Hydrological droughts are complex recurring hazards that can cause water shortages in streams or storages such as reservoirs, lakes, groundwater, and snowpacks, resulting in negative impacts to natural and socio-economic systems. Significant advances in hydrological drought reconstructions, monitoring, prediction, and impact mitigation documented in the recent years provide evidence for improved documentation and water management decisions. However, challenges remain in terms of quantifying the drought signal in all the components of the hydrological cycle. Moreover, hydrological droughts are both driven by climate variability and influenced by human activities that can intensify the drought signal. Thus, modeling and prediction of these events needs to consider both natural and anthropogenic factors.
Hydrological modeling and remote sensing are crucial to quantifying the available water resources and the propagation of the drought signal. Though in-situ measurements are mostly available in the major basins, measurements may lack adequate temporal and spatial sampling of groundwater levels, reservoir volumes, wetlands, and snow depths. These tools are needed to distinguish between the human and natural components of hydrological drought and to perform reliable drought prediction on sub-seasonal to multi-annual timescales, which are of critical importance for setting up strategies for reducing the vulnerability to drought and improving drought response. Deficiencies in sub-seasonal to decadal prediction can impact skillful prediction of hydrological drought, calling for an improved knowledge of the relationship between remote teleconnections, local climate variables and hydrological conditions, as well as initial land surface states and land-atmosphere interactions.
To achieve this goal, improved monitoring and refined statistical and dynamical models including bias corrections and downscaling techniques are of paramount importance. Regional climate change and the increasing human intervention on water resources contribute to increased frequency and severity of hydrological droughts, factors that challenge drought prediction due to the non-stationarity in hydroclimatic interactions.
This Research Topic aims to provide new perspectives on hydrological drought reconstruction, monitoring and prediction, highlighting existing challenges and opportunities for the generation of usable information to assist decision making in terms of water management and policy.
We welcome contributions on the state-of-the-art of hydrological drought research in terms of reconstruction, monitoring and prediction, considering regional and global scales. Case studies analyzing the physical processes of extreme drought events are encouraged. Manuscripts focusing on but not limited to the following themes are particularly welcome:
- Hydrological drought monitoring in snow-dominated regions;
- Reconstruction of past hydrological droughts using innovative use of modeling and observational datasets.
- Prediction of hydrological droughts from sub-seasonal to multi-decadal time scales;
- Quantification of hydrological drought environmental impacts;
- Hydrological drought monitoring based on satellite data, re-analyses and model outputs;
- Projections of future hydrological droughts;
- Physical processes underlying hydrological droughts.
Manuscripts focusing on the socioeconomic effects of drought should be directed to our Research Topic
Hydrological Extremes and Society