This study applied a new methodology (complex network), instead of using classic methods, to establish the relationships between rainfall events in large East Asian cities. The relationships show that western China and Southeast Asia have a lot of influence on each other. Moreover, it is confirmed that the relationships arise from the effect of the East Asian monsoon. In future, complex network may be able to be applied to analyze the concurrent relationships between extreme rainfall events.

Terrain indices constitute a good candidate for modelling the spatial variation of soil moisture conditions in many landscapes. In this study, we evaluate nine terrain indices on varying DEM resolution and user-defined thresholds with validation using an extensive field soil moisture class inventory. We demonstrate the importance of field validation for selecting the appropriate DEM resolution and user-defined thresholds and that failing to do so can result in ambiguous and incorrect results.

Most of the literature has focused on the runoff response to climate change, while neglecting the impacts of the potential variation in the active catchment water storage capacity (ACWSC) that plays an essential role in the transfer of climate inputs to the catchment runoff. This study aims to systematically identify the response of the ACWSC to a long-term meteorological drought and asymptotic climate change.

The study assessed changes in total nitrogen (TN) and total phosphorus (TP) loads in response to eastern Pacific (EP) and central Pacific (CP) El Niño events over the Corn Belt, USA, using the SWAT model. Results showed that EP (CP) El Niño events improved (exacerbated) water quality in the region. Furthermore, EP El Niño had a much broader and longer impact on water quality at the outlets, but CP El Niño could lead to similar increases in TN/TP loads as EP El Niño at the specific watersheds.

Equitable sharing of benefits is key to successful cooperation in transboundary water resource management. However, external changes can shift the split of benefits and shifts in the preferences regarding how an actor’s benefits compare to the other’s benefits. To understand how these changes can impact the robustness of cooperative agreements, we develop a socio-hydrological system dynamics model of the benefit sharing provision of the Columbia River Treaty and assess a series of scenarios.

This study aims to further evaluate the relative importance of antecedent soil moisture and rainfall on flood generation and the controlling factors. The relative importance of antecedent soil moisture and daily rainfall present a significant correlation with drainage area; the larger the watershed, and the more essential the antecedent soil saturation rate is in flood generation, the less important daily rainfall will be.

Stable isotope ratios (isotope values) of surface water reflect hydrological pathways, mixing processes, and atmospheric exchange within catchments. We used a water-balance-based mapping method, which represents patterns of surface flow and mixing, and added a regression-based correction step using catchment environmental characteristics to map water isotope ratios across all the rivers of New Zealand.

Analyzing the impact of soil age and rainfall intensity on vertical subsurface flow paths in calcareous soils, with a special focus on preferential flow occurrence, shows how water flow paths are linked to the organization of evolving landscapes. The observed increase in preferential flow occurrence with increasing moraine age provides important but rare data for a proper representation of hydrological processes within the feedback cycle of the hydro-pedo-geomorphological system.

The relationship between atmospheric intraseasonal signals and precipitation is highly uncertain and depends on the region and lead time. In this study, we develop a spatiotemporal projection, based on a Bayesian hierarchical model (STP-BHM), to address the above challenge. The results suggest that the STP-BHM model is skillful and reliable for probabilistic subseasonal precipitation forecasts over China during the boreal summer monsoon season.

Whether rainwater-recharged soil water (RRS) uptake can increase plant transpiration after rainfall pulses requires investigation. Our results indicate a differential response of plant transpiration to RRS uptake. Mixed afforestation enhances these water relationships and decreases soil water source competition in deep soil. Our results suggest that plant species or plantation types that can enhance RRS uptake and reduce water competition should be considered for use in water-limited regions.

There is serious concern that river floods are increasing. Starting from explanations discussed in public, the article addresses three hypotheses: land-use change, hydraulic structures, and climate change increase floods. This review finds that all three changes have the potential to not only increase floods, but also to reduce them. It is crucial to consider all three factors of change in flood risk management and communicate them to the general public in a nuanced way.

This work aims to develop the Transit Time index (TTi) as a natural tracer of karst groundwater transit time, usable in the 0–6-month range. Based on the fluorescence of organic matter, TTi shows its relevance to detect a small proportion of fast infiltration water within a mix, while other natural transit time tracers provide no or less sensitive information. Comparison of the average TTi of different karst springs also provides consistent results with the expected relative transit times.

We assessed the effect of catchment topographic slopes on the nitrate export dynamics in terms of the nitrogen mass fluxes and concentration level using a coupled surface–subsurface model. We found that flatter landscapes tend to retain more nitrogen mass in the soil and export less nitrogen mass to the stream, explained by the reduced leaching and increased potential of degradation in flat landscapes. We emphasized that stream water quality is potentially less vulnerable in flatter landscapes.

Spatially explicit quantification of design storms is essential for flood risk assessment and planning. However, available datasets are mainly based on spatially interpolated station-based design storms. Since the spatial interpolation of the data inherits a large potential for uncertainty, we develop an approach to be able to derive spatially explicit design storms on the basis of weather radar data. We find that our approach leads to an improved spatial representation of design storms.

Neural ODEs fuse physics-based models with deep learning: neural networks substitute terms in differential equations that represent the mechanistic structure of the system. The approach combines the flexibility of machine learning with physical constraints for inter- and extrapolation. We demonstrate that neural ODE models achieve state-of-the-art predictive performance while keeping full interpretability of model states and processes in hydrologic modelling over multiple catchments.

This article examines how a hydrological model exploring the causes of a lake desiccation was turned into a 5-step participatory process to better adjust the model to address questions that were causing suspicions and conflicts in the community. Although the process was key in finding a combination of strategies that were of moderate impact and higher local acceptability, we address the challenges of such collaboration in modeling when conflict is deeply embedded in the context.

Soil hydraulic and hydrodispersive properties are necessary for modeling water and solute fluxes in agricultural and environmental systems. Despite the major efforts in developing methods (e.g., lab-based, pedotransfer functions), their characterization at applicative scales remains an imperative requirement. Thus, this paper proposes a noninvasive in situ method integrating electromagnetic induction and hydrological modeling to estimate soil hydraulic and transport properties at the plot scale.

In this paper, we deliver an evaluation of the second generation operational German drought monitor (https://www.ufz.de/duerremonitor) with a state-of-the-art compilation of observed soil moisture data from 40 locations and four different measurement methods in Germany. We show that the expressed stakeholder needs for higher resolution drought information at the one-kilometer scale can be met and that the agreement of simulated and observed soil moisture dynamics can be moderately improved.

High-resolution river modeling is of great interest to local governments and stakeholders for flood-hazard mitigation. This work presents a physics-guided, machine learning (ML) framework for combining the strengths of high-resolution process-based river network models with a graph-based ML model capable of modeling spatiotemporal processes. Results show that the ML model can approximate the dynamics of the process model with high fidelity, and data fusion further improves the forecasting skill.

The objective of the paper is to highlight the seasonal and singular shift of the transfer time distributions of two catchments (≅10 km²). Based on 2 years of rainfall and discharge observations, we compare variations in the properties of TTDs with the physiographic characteristics of catchment areas and the eco-hydrological cycle. The paper eventually aims to deduce several factors conducive to particularly rapid and concentrated water transfers, which leads to flash floods.