Seasonal Hydrological Forecasting and Climate Prediction

Seasonal hydrological forecasting integrates climate predictions with hydrological models to estimate river flows, groundwater levels and drought or flood risk several months in advance. Such forecasts draw on large-scale climate precursors, land‐surface initial conditions and ensemble approaches to capture uncertainty. They inform water resource management, disaster risk reduction, agricultural planning and hydropower operations by providing probabilistic outlooks of streamflow extremes and water availability. Advances in coupled atmosphere–land modelling, bias correction of seasonal climate forecasts and data assimilation have substantially improved forecast skill. At the same time, understanding of catchment memory and hydrological regimes has clarified why predictability varies geographically and seasonally. Globally, skillful seasonal forecasts support early warning systems, guide reservoir operations and underpin climate adaptation strategies.

Research from Nature Portfolio

Recent studies have demonstrated the capacity to forecast hydrological drought using only precipitation data, revealing that standardised indices of meteorological drought hold predictive power for both streamflow and groundwater deficits. By analysing multiple lag times and accumulation periods, researchers have shown that catchment properties—such as storage capacity and land-surface characteristics—critically modulate forecast performance. These findings highlight the feasibility of a globally scalable hydrological drought early warning system that meets international disaster risk reduction objectives and extends early warnings for all regions.

Seasonal Hydrological Forecasting and Climate Prediction publication trend

The graph below shows the total number of articles in seasonal hydrological forecasting and climate prediction across all publications each year (not limited to Nature Index journals).

Technical terms

Hydrological drought: A condition of below-normal streamflow or groundwater levels resulting from prolonged precipitation deficits moderated by catchment storage.

Standardized Precipitation Index (SPI): A statistical measure that quantifies precipitation anomalies over fixed accumulation periods to characterise meteorological drought severity.

Ensemble streamflow prediction (ESP): A method generating multiple streamflow forecasts by forcing hydrological models with historical meteorological sequences and current catchment states.

Initial hydrologic conditions (IHCs): The state of catchment storage variables (e.g., soil moisture, groundwater, snow) at the time of forecast initialization, contributing substantially to short-lead-time skill.

Hydrological regime: The characteristic response of a river system to meteorological inputs, determined by catchment morphology and storage dynamics, influencing forecast predictability.

References

1. Hydrological drought forecasts using precipitation data depend on catchment properties and human activities. Communications Earth & Environment (2024).
2. High resolution monitoring and probabilistic prediction of meteorological drought in a Mediterranean environment. Weather and Climate Extremes (2023).
3. Hydrological regimes explain the seasonal predictability of streamflow extremes. Environmental Research Letters (2023).
4. The suitability of a seasonal ensemble hybrid framework including data-driven approaches for hydrological forecasting. Hydrology and Earth System Sciences (2023).
5. Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts. Hydrology and Earth System Sciences (2016).
6. A review on climate‐model‐based seasonal hydrologic forecasting: physical understanding and system development. Wiley Interdisciplinary Reviews Water (2015).
7. Seasonal hydrologic prediction in the United States: understanding the role of initial hydrologic conditions and seasonal climate forecast skill. Hydrology and Earth System Sciences (2011).
8. On the sources of global land surface hydrologic predictability. Hydrology and Earth System Sciences (2013).