Hydrology and Climate Change Article Summaries

This study investigated the effects of sprinkler irrigation intensity on soil water-salt transport and winter wheat yield under brackish-water irrigation using field experiments and HYDRUS-1D simulations. It identified optimal irrigation intensities (1.33 × 10⁻⁶ m s⁻¹ for 3 kg m⁻³ salinity; 1.33 × 10⁻⁶ m s⁻¹ and 1.81 × 10⁻⁶ m s⁻¹ for 5 kg m⁻³ salinity) that balanced water-salt dynamics and minimized yield reduction.

This study analyzed spectral scaling across 671 U.S. watersheds to distinguish the relative contributions of hydrological inputs and watershed filtering to streamflow persistence, identifying three distinct watershed regimes based on their scaling exponents.

This study quantifies the differential climate sensitivity of irrigated and rainfed rice yields at the provincial level in the Philippines and projects the impact of irrigation conversion on future rice self-sufficiency under various climate change scenarios. It finds that while irrigation conversion can substantially offset negative climate impacts on yields, it is insufficient as a standalone solution to achieve high rice self-sufficiency targets, with the ratio projected to remain below 87% even with full irrigation.

This study develops an uncertainty-aware framework combining hydrological modeling, machine learning, and dendrohydrological validation to reconstruct 74 years of natural streamflow in the regulated Abitibi River watershed. The reconstructed ensemble reveals statistically significant increases in annual and spring streamflow, with estimated trends of 1.91 m³/s/year and 2.67 m³/s/year, respectively.

This study developed explainable artificial intelligence models to identify hydroclimatic controls on cotton yield and project mid-century yields across Texas. It found that climate impacts on Texas cotton are highly region- and production-system-specific, with some areas experiencing significant yield declines (e.g., High Plains) and others modest increases (e.g., Low Rolling Plains) by 2030–2050.

This study analyzed 150 years (1862–2011) of climate variability and water balance components in the Adige River basin, confirming a significant temperature increase (over 2 °C in the last 50 years) and increasing evapotranspiration and water deficit, while precipitation showed no significant long-term change and external forcings had a weak influence.

This study evaluated ECMWF SEAS5 seasonal forecasts for drought monitoring and early warning in Portugal, finding they offer potential for early warning despite limitations like coarse resolution and a warm-season wet bias, with performance varying by lead time and season.

This study introduces HydroSPI-ARX, an autoregressive and explainable machine-learning framework for leakage-controlled drought early warning over Türkiye, demonstrating significant skill gains over baseline models, particularly at a six-month lead time, by leveraging the multi-scale memory of the Standardized Precipitation Index (SPI).

This study used high-resolution numerical simulations to investigate the multi-scale dynamics and mesoscale drivers of the catastrophic September 2022 Marche flood in central Italy, revealing the critical role of Apennine orography in anchoring the storm and the extreme sensitivity of rainfall patterns to initial and boundary conditions.

This study investigates global patterns and drivers of multi-year groundwater droughts using a hyper-resolution dataset (1960-2019), revealing that 35% of global groundwater grid cells experience multi-year droughts, predominantly extended by subsurface processes. The research defines three global groundwater response types to understand the interplay between meteorological and groundwater drought duration.

This study reconstructs 343 years of combined Selenga and Angara River streamflow using a tree-ring network to establish a multi-century hydroclimatic baseline for Lake Baikal, revealing a significant decline throughout the 20th century followed by a sharp and sustained recovery in the last decade.

This study formalizes a five-stage decision logic for Flood-Managed Aquifer Recharge (Flood-MAR) planning, applying it retrospectively to four sites in Kazakhstan to link available evidence with screening conclusions and identify subsequent investigation requirements, particularly for source verification.

This study provides a daily global compound dry–hot index (SSTCI) and a ready-to-use CDHE (Compound Dry-Hot Extreme) catalogue for 1961–2023 at 0.1° resolution. Built on soil moisture memory and surface air temperature, the findings indicate that CDHEs have become more frequent and longer lasting in many regions in recent decades.

This study identifies four distinct conditional weather regimes responsible for persistent summer rainfall over the southeastern United States (SEUS) from 1979 to 2023. It reveals that similar regional wet conditions can arise from fundamentally different large-scale atmospheric circulation and moisture transport configurations.

This study examines contrasting temperature and precipitation responses to climate change at Split–Marjan, Croatia, revealing pronounced warming, an increase in warm-dry days, and heterogeneous precipitation changes despite no significant trend in annual totals.

This study quantifies the impact of 223 reservoirs on India's streamflow extremes using a national hydrologic modeling system, revealing significant attenuation of monsoon high flows and augmentation of pre-monsoon low flows, but also highlighting a high vulnerability due to rapid reservoir saturation.

This study evaluates Snow Water Equivalent (SWE) estimates from three large-scale land-surface products (ERA5-Land, CERRA-Land, VHR-REA_IT) across Italy against the IT-SNOW reference dataset. It reveals significant regional differences in product performance, with forcing biases explaining a substantial portion of the observed SWE discrepancies, offering guidance for long-term hydro-climatological assessments.

This study introduces the Streamflow Alteration Index (SAI), a parsimonious, network-based screening metric, to map and quantify potential streamflow alteration across Ontario, Canada. The resulting SAI v1.0 database provides a practical and reproducible baseline for large-domain hydrologic and ecological applications by estimating the percentage of upstream drainage area exposed to alteration sources.

This study investigates the hydrometeorological and catchment-scale drivers of flood generation in India's Godavari River basin, revealing how temporal precipitation properties and specific catchment areas contribute to flood events across different aridity regimes. It differentiates between short-duration, single-event floods in semi-arid regions and long-duration, multi-event floods in semi-humid areas, identifying key flood-dominant sub-basins.

This study investigates the benefits of Bayesian estimation for quantifying parametric uncertainty within a large hydrological model ensemble. It finds that Bayesian parameter estimation significantly improves individual model performance, especially for complex models, thereby influencing the interpretation of model structural comparisons. However, it offers only marginal improvements to multi-model ensemble hydrological predictions, suggesting that the high computational cost of Bayesian methods is often not justified for practical forecasting when structural diversity is present.