A drought index is developed that quantifies drought on an annual scale, making it applicable to monitoring clay shrinkage damage to buildings. A comparison with the number of insurance claims for subsidence shows that the presence of trees near individual houses must be taken into account. Significant soil moisture droughts occurred in France in 2003, 2018, 2019, 2020, and 2022. Particularly high index values are observed in 2022. It is found that droughts will become more severe in the future.

Stream networks expand and contract, affecting the amount and quality of water in perennial streams. This study presents measurements of changes in water chemistry and the flowing portion of the drainage network during rainfall events in two neighboring catchments. Despite the proximity and similar size, soil, and bedrock, water chemistry and stream network dynamics differed substantially in the two catchments. These differences are attributed to the differences in the slope and channel network.

Hydrologic models are needed to provide simulations of water availability, floods, and droughts. The accuracy of these simulations is often quantified with so-called performance scores. A common thought is that different models are more or less applicable to different landscapes, depending on how the model works. We show that performance scores are not helpful in distinguishing between different models and thus cannot easily be used to select an appropriate model for a specific place.

The release of carbon from landscapes into streams is one important component within the global carbon cycle. We measured the concentrations of dissolved organic carbon (DOC), one of the forms in which carbon can be present, in the streams of three nested forested subcatchments over 12 months. The export of DOC is closely linked to water flow processes within the subcatchments, but the interplay of soils, vegetation, topography, and microclimate results in distinct seasonal DOC release patterns.

Seasonal streamflow forecasts are an important component of flood risk management. Here, we train and test a machine learning model to predict the monthly maximum daily streamflow up to 4 months ahead. We train the model on precipitation and temperature forecasts to produce probabilistic hindcasts for 579 stations across the UK for the period 2004–2016. We show skilful results up to 4 months ahead in many locations, although, in general, the skill declines with increasing lead time.

The Hybrid Ensemble and Variational Data Assimilation framework for Environmental Systems (HEAVEN) enhances flood predictions by refining hydrologic models through improved data integration and uncertainty management. Tested in three southeastern US watersheds during hurricanes, HEAVEN assimilates real-time United States Geological Survey (USGS) streamflow data, boosting forecast accuracy.

The classic logistic function characterizes the stationary relationship between drought loss and intensity. This paper accounts for time in the magnitude, shape and location parameters of the logistic function and derives nonstationary intensity loss functions. A case study is designed to test the functions for drought-affected populations by province in mainland China from 2006 to 2023. Overall, the nonstationary intensity loss functions are shown to be a useful tool for drought management.

Accurately estimating groundwater recharge using numerical models is particularly difficult in cold regions with snow and soil freezing. This study evaluated a physics-based model against high-resolution field measurements. Our findings highlight a need for a better representation of soil-freezing processes, offering a roadmap for future model development. This leads to more accurate models to aid in water resource management decisions in cold climates.

Stream chemistry in permafrost watersheds is highly seasonal due to ground thaw and declining streamflow after spring melt, reducing hydrologic connectivity with organic-rich flow paths in fall. We quantified the magnitude of stream chemistry seasonality (driven by processes other than seasonal streamflow) across 10 watersheds. Watersheds with steeper slopes saw a more rapid decline in DOC (dissolved organic carbon) concentrations, while greater permafrost extent led to a greater relative increase in ion concentrations.

During geological carbon sequestration, the injected supercritical CO₂, being less dense, floats above the brine. The dissolution of CO₂ into brine helps mitigate the risk of CO₂ leakage. As CO₂ dissolves into the brine, it increases the density of brine in the upper layer, initiating gravity-driven convection (GDC), which significantly enhances the rate of CO₂ dissolution. We derived two empirical formulas to predict the asymptotic dissolution rate driven by GDC in heterogeneous fields.

The simultaneous or sequential occurrence of different flood processes, including extreme storm surges and heavy precipitation, tends to trigger compound floods, which are often destructive. We develop a land–river–ocean coupled model for the prediction of compound floods in a big river delta region. The coupled model is shown to perform well in simulating the combined effect of heavy precipitation, river flood routing, storm surges, and inundation for events induced by tropical cyclones.