Study region Changhua, Taiwan Study focus Estuarine wetlands are increasingly recognized as nature-based solutions that complement structural defenses by providing flood-regulation services and co-benefits such as carbon sequestration. Focusing on the Changhua coast at the Jhuoshuei River estuary in Taiwan, designated as a coastal protection zone under the Coastal Zone Management Act, we develop a coupled hydrodynamic and ecosystem-service framework. The framework links two-dimensional storm-surge modelling using SRH-Coast with ecosystem-service assessment using the InVEST Coastal Blue Carbon module to evaluate wetland loss and restoration under sea-level-rise scenarios. New hydrological insights for the region Our results show that sea-level rise and wetland contraction act as compounding drivers of coastal flood risk along the Changhua coast. Under the + 34.5 cm sea-level-rise scenario, intertidal wetland area decreases from 6063 ha to 4619 ha, while storm-surge inundation extent increases by 65%. Wetland restoration produces the strongest hydrodynamic benefit locally, reducing surge levels by up to 37% across coastal cross-sections, whereas the reduction in total inundation area under future conditions is more modest at about 3%. This scale-dependent response indicates that substantial local surge attenuation does not necessarily translate into an equivalent reduction in system-wide inundation. Projected wetland loss also decreases blue-carbon stocks by about 16.4%, while restoration increases storage by about 31.7% relative to present conditions. Together, these results provide region-specific evidence that wetland preservation and restoration can complement existing coastal protection by attenuating local surge propagation while maintaining blue-carbon storage, and offer a transferable framework for evaluating nature-based flood-risk-reduction strategies on other subsiding, wetland-fringed estuarine coasts.
Study region Kunshan, a low-gradient urban river-lake network in the central Taihu Basin (Yangtze River Delta), China. Study Focus Seasonal hydrological variability can reorganize microbial communities in connected river–lake systems, but responses may differ between water and sediment and alter the interpretation of water-quality indicators. We analyzed 94 surface-water and surficial-sediment samples collected in May and August 2024, representing pre-monsoon and summer-monsoon conditions, respectively. Bacterial community composition differed strongly by matrix and sampling period (NMDS stress = 0.0763; PERMANOVA R² = 0.665, p = 0.001), with matrix accounting for the largest share of variation. Water communities showed stronger seasonal displacement and lower evenness in August, whereas sediments maintained higher diversity. Indicator taxa also shifted by matrix and period, including Limnohabitans in May water, Cyanobium in August water, Nitrospira in May sediment, and Dechloromonas in August sediment. New Hydrological Insights for the Region Taxonomic turnover accompanied matrix-specific functional shifts and assembly changes. Water lost aerobic chemoheterotrophic potential in August, while sediment gained anaerobic chemoheterotrophic and nutrient-transformation capacity. Neutral models revealed contrasting effective immigration trajectories between water and sediment. August shifted to higher C:N, lower C:P, tightened coupling, and altered WQI/TLI links to stoichiometric gradients. These demonstrate asymmetric seasonal hydrological effects across the water–sediment interface and that C:N:P provides useful biogeochemical context to refine microbial and eutrophication indicator interpretation for regulated river-lake networks.
Study Region The Oulanka River system is a semi-natural boreal catchment in Northeast Finland draining to the Arctic Ocean. Boreal catchments are undergoing hydrological and biogeochemical shifts from climate and land-use change, but long-term data are scarce. Study Focus This study aims to quantify long-term (1966–2024), seasonal and spatial trends in water quality, combining a 58-year time series with spatial sampling (2020–2022) in the Oulanka catchment. We analysed concentrations of dissolved organic carbon (DOC), total nitrogen (TN), total phosphorus (TP), nitrite-nitrate (NO₂NO₃), ammonium (NH₄) and phosphate (PO₄), along with seasonal loading, concentration-discharge (C-Q) relationships and carbon:nitrogen:phosphorus (C:N:P) stoichiometry. New Hydrological Insights for the Region Despite significant warming, DOC concentrations did not increase over the time series, unlike in many boreal catchments. TN declined significantly, NO₂NO₃ and NH₄ were stable, and PO₄ increased. Shoulder seasons were identified as key transport periods and contributed higher loading than the winter and growing season. DOC showed mild chemodynamic behaviour, TP had a positive C-Q slope across seasons, and PO₄ varied by season. Over time, C-Q slopes changed significantlyfor TN and NH, and coefficient of variation (CV) ratios decreased, particularly for PO₄. C:N:P stoichiometry was carbon-dominated, with nitrogen becoming increasingly limiting over time. It varied little among seasons or sites. The findings highlight the value of site-specific catchment studies for understanding boreal water quality and informing management.
Study region Luolingqiao (326 km²) and Wenjiashi (164 km²), two small-to-medium sub-basins of the Xiang River Basin in Hunan Province, China. Study focus Reliable flash flood forecasting in small-to-medium basins (SMBs) requires both high temporal resolution and physically constrained long-lead prediction. This study develops a dual-constraint physics-informed framework that couples the Xin'anjiang (XAJ) model with an encoder-decoder LSTM to produce 10-minute runoff forecasts at lead times of up to 6 h, forced exclusively by quality-controlled X-band radar quantitative precipitation estimation (QPE). XAJ-derived physical trajectories are supplied to the LSTM decoder, and a dual-constraint loss penalizes deviations from both observed discharge and XAJ-simulated runoff. The framework is evaluated on 28 flood events under blocked chronological cross-validation, in hindcast mode with observed QPE over the forecast horizon. New hydrological insights for the region At the 6-h lead time, the hybrid model significantly outperforms the standalone XAJ model: relative to XAJ, NSE increases by 20%, RMSE decreases by 25%, and peak error decreases by 46%. Continuous evaluation from 1 to 6 h reveals a crossover near 3 h: the LSTM dominates at shorter horizons, whereas the hybrid model becomes optimal beyond 3–4 h, where physical regularization suppresses recursive error accumulation. Coupling process-based constraints with deep learning at 10-minute resolution is therefore feasible and valuable for flash flood early warning in SMBs with concentration times shorter than 3 h.
Study region Tapi River Basin, a 724 km-long tropical river in India. Study focus: Hydrological and sediment connectivity regulate sediment supply and channel morphology, while intensifying hydroclimatic extremes enhance flood-driven sediment mobilisation. Using observations and hydrological modelling, we investigated flood, sediment, and channel responses to extreme events and a 35-year assessment. We also developed a flood connectivity framework to evaluate hydrological connectivity during floods and infer potential sediment disconnectivity when observed sediment data are unavailable. New hydrological insights Flood-wave connectivity varies spatially due to heterogeneous rainfall and anthropogenic regulation. Extreme events increase sediment loads by ~200–300% relative to average conditions. Channel response is governed by spatial variations in unit stream power (USP) and sediment availability, with high upstream USP promoting erosion and a 3–4-fold reduction downstream favouring deposition, potentially reducing channel conveyance and increasing flood risk. Sediment mobilisation is strongly associated with daily rainfall > 50 mm and seasonal discharge, highlighting the role of extreme rainfall and hydrological conditions. Model simulations indicate a ~36% increase in sediment yield alongside ~8% and ~28% increases in annual mean and maximum rainfall, respectively, over 35 years, under constant land use. Although hydroclimatic variability appears to be a major driver, land-use change, channel processes, and longitudinal barriers may also influence sediment dynamics. These findings highlight the need to incorporate hydroclimatic extremes and connectivity into sediment and flood-risk management.
