Sub-Seasonal to Seasonal (S2S) Hydrological Forecasting: Bridging Climate Variability and Water Management.

Extreme events such as heatwaves, floods, cyclones, and droughts have severe impacts across many sectors, including agriculture, energy, and transportation. Most importantly, such events can be detrimental to human health and other living things in nature, causing severe environmental consequences. Accurate prediction of extreme climate events is important for improving their foreseeability and taking precautions against their socio-economic effects on humans, societies and the environment. Sub-seasonal-to-seasonal (S2S) forecasts of extreme events such as heatwaves, cold spells, tropical cyclones, droughts, and floods complement weather and climate services and products by providing information at lead times from two weeks to a season. The predictability of extreme events varies by process due to their deterministic and stochastic characteristics; however, it remains open to improvement. In this sense, applying S2S predictions across different event types is important for assessing their reliability and transferability.Analyzing the effects of climate variability on hydrological regimes is crucial for efficient water resources management. S2S predictions have been the focus of intense scientific investigation and development to improve the predictability of extreme events in a time scale critical for many crucial applications. Furthermore, mapping changes in climate variables into variability in hydrological regimes remains a significant research focus. In this research topic, it is expected that the climate variables, including temperature, precipitation and evapotranspiration, predicted by S2S, will be used in rainfall-runoff simulation using different model approaches, as described in the following section. Runoff, soil moisture, and groundwater storage simulations from relevant modelling approaches can be analyzed for flood and drought events and compared with observed events. This approach can provide a clear idea of whether S2S prediction outputs can reliably be transformed into key hydrological variables to guide decision making process, and how climate variability affects the hydrological regimes and, in turn, water management strategies.This research topic aims to integrate S2S prediction outputs into rainfall-runoff modelling under different climate and hydrological conditions. Process-based models, data-driven models, physics-informed machine learning applications and hybrid models integrating different structures are highly encouraged to be used for the transformation process of hydroclimatic variables, including precipitation, temperature and evapotranspiration, as predicted by S2S, into runoff, soil moisture, and groundwater storage. In this regard, analyzing runoff simulations from the aforementioned models for flooding and drought events and comparing them with observed counterparts can provide a comprehensive outlook on how the variability in climate variables, as revealed by S2S, affects the runoff regime. This will be critical to developing water management strategies for the changing climate conditions. Topic editors: Veber Costa, Cenk Sezen, Priscilla Moura, Dirceu S. Reis Jr. Source: https://www.frontiersin.org/research-topics/86237/sub-seasonal-to-seasonal-s2s-hydrological-forecasting-bridging-climate-variability-and-water-management