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The partitioning of precipitation water input on land between green (evapotranspiration) and blue (runoff) water fluxes distributes the annually renewable freshwater resource among sectors and ecosystems. The patterns and main drivers of this partitioning are not fully understood around the global land area. We decipher the worldwide patterns and key determinants of this water flux partitioning and investigate its predictability based on a global machine learning model. Available data for 3,614 hydrological catchments and model application to the global land area agree in showing mostly larger green than blue water flux. Possible expansion/intensification of irrigated and/or rainfed agriculture to feed a growing human population, along with climate warming, will tend to increase this flux partitioning asymmetry, jeopardizing blue water security. The developed machine learning model presents a promising predictive tool for future blue and green water availability under various forthcoming climate and land-use change scenarios around the world.

Hydrology plays a crucial role in understanding Earth's intricate water system and addressing water‐related problems, including against the backdrop of ongoing climate change. A retrospective review of the evolution of hydrology up to the current state of research is of great importance for understanding this role. While there have been some quantitative reviews of large numbers of hydrological publications, there still remains a lack of overarching hydrological research assessment, particularly with the focus on hydrological basins as fundamental spatial‐geographic units of hydrological analysis. Large language models, represented by OpenAI's ChatGPT, have demonstrated powerful textual understanding capabilities, making it possible to extract such overarching and basin information from hydrological publications. Here, we considered publications related to hydrology from Web of Science spanning January 1980 to October 2023, and parsed the information from this extensive body of literature by integrating a large language model and geocoding. These techniques enable quantitative analysis of research characteristics across different spatio‐temporal scales, focusing on hotspot topics, collaboration networks, and various basins worldwide. Our study revealed an increase in hydrological research since the 1990 s, with shifts in research priorities from groundwater and nutrients to climate change and ecohydrology. Some basins in North America and Europe have consistently been hotspots for hydrological research. Since the 2010s, there has been a noteworthy increase in interest toward basins in China and South Asia, but attention to many regions with frequent extreme rainfall remains insufficient. Geographical patterns show different preferred research topics for different basins, but climate change has emerged as the most prominent topic across all regions in the last decade. In conclusion, our study provides an effective approach to quantitative analysis of research trends, offering a fresh view on the evolution of hydrology as a research field, its focus on various hydrological basins around the world, and the emergence of overarching and basin‐specific hot topics over time. We explore the literature review capability of a large language model combined with geocoding over the whole field of hydrological researchWe quantify the evolution of hydrological research, hotspot topics, collaboration networks, and basins in focus, worldwide over timeHydrological research publication exhibits major and accelerating growth with WRR emerging as the top influential journal over time We explore the literature review capability of a large language model combined with geocoding over the whole field of hydrological research We quantify the evolution of hydrological research, hotspot topics, collaboration networks, and basins in focus, worldwide over time Hydrological research publication exhibits major and accelerating growth with WRR emerging as the top influential journal over time

Increasing incidences of eutrophication and groundwater quality impairment from agricultural nitrogen pollution are threatening humans and ecosystem health. Minimal improvements in water quality have been achieved despite billions of dollars invested in conservation measures worldwide. Such apparent failures can be attributed in part to legacy nitrogen that has accumulated over decades of agricultural intensification and that can lead to time lags in water quality improvement. Here, we identify the key knowledge gaps related to landscape nitrogen legacies and propose approaches to manage and improve water quality, given the presence of these legacies.

This study develops a general quantification framework for consistent intermodel and intercatchment comparison of the nutrient and pollutant mass loading from multiple sources in a catchment area to downstream surface and coastal waters. The framework accounts for the wide spectrum of different transport pathways and travel times through the subsurface (soil, groundwater, sediment) and the linked surface (streams, lakes, wetlands) water systems of a catchment. The account is based on key flow partitioning and mass delivery fractions, which can be quantified differently by different flow and transport and reaction models. The framework application is exemplified for two Swedish catchment cases with regard to the transport of phosphorus and of a generic attenuating solute. The results show essential differences in model quantifications of transport pathways and temporal spreading, with important implications for our understanding of cause and effect in the catchment-scale nutrient and pollutant loading to downstream waters.

Offsetting residual emissions of greenhouse gases will be critical in our aims to limit global warming. Nature-based solutions (NbS) have been proposed as an opportunity to mitigate climate change while protecting and restoring the world’s natural capital. This Voices asks: what is the mitigation potential of NbS and the main needs for their succesful implementation?

Population increases and environmental degradation are challenges for urban sustainability. Planning support systems are available to assist local authorities in developing strategies toward sustainability and resilience of urban areas, but are not always used in practice. We adapted an open-source planning support system to the case of Stockholm County, Sweden, where there is a productive working relationship between researchers, city planners, and regional planners. We employed a collaborative approach in extending and updating the planning support system and analyzed the outcomes, in order to both improve the planning support system and to investigate the process of planner engagement in planning support system development. The approach involved systematic interactions with local planning authorities and e.g. additional data processing, integrating scientific knowledge, policy, and engagement by planners in the complex process of planning for sustainable urban development. This made the planning support system more user-friendly for local planners, facilitating adoption by planning authorities through overcoming common quality and acceptance barriers to the use of planning support system in practice. Involving planners in planning support system development thus increases (i) planning support system quality, producing relevant and up-to-date outputs, and (ii) acceptance for planning support system by regional planners. Further assessment is required to determine whether planners can operate the adapted planning support system unaided.

Translational research (TR) represents a promising systematic process for going from scientific discoveries to practical applications. Through conversations with academics, practitioners, decision‐makers and users, there has emerged a broad level of water science community support for including TR in Water Resources Research (WRR) publications. Based on this, we now open a continuing special collection of TR papers in WRR. The aim is to facilitate a community within hydrology and water science that seeks to provide actionable knowledge for societal benefit across disciplines, scales and contexts, with a focus on water as a key societal resource or a risk (e.g., of floods, droughts, or as pollutant carrier). This Editorial discusses what the multi‐faceted nature of TR may include in the context of WRR, why it is important to encourage TR papers in WRR, and how the opening of a continuing special collection of translational water research papers initiates a process to include such articles in the journal. Opening a continuing special collection for translational research (TR) papers in the context of Water Resources Research (WRR)Explaining the multi‐faceted nature of TR and Initiating a process to encourage and include such papers in WRRAiming to facilitate a community within hydrology and water science that seeks to provide actionable knowledge for societal benefit Opening a continuing special collection for translational research (TR) papers in the context of Water Resources Research (WRR) Explaining the multi‐faceted nature of TR and Initiating a process to encourage and include such papers in WRR Aiming to facilitate a community within hydrology and water science that seeks to provide actionable knowledge for societal benefit

The emergence of large language models (LLMs), such as ChatGPT, has garnered significant attention, particularly in academic and scientific circles. Researchers, scientists, and instructors hold varying perspectives on the advantages and disadvantages of using ChatGPT for research and teaching purposes. ChatGPT will be used by many scientists going forward for creating content and driving scientific progress. This commentary offers a brief explanation of the fundamental principles behind ChatGPT and how it can be applied in the fields of hydrology and other Earth sciences. The article examines the primary applications of this open artificial intelligence tool within these fields, specifically its ability to assist with writing and coding tasks, and highlights both the advantages and concerns associated with using such a model. Moreover, the study brings up some other limitations of the model, and the dangers of potential miss‐uses. Finally, we suggest that the academic community adapts its regulations and policies to harness the potential benefits of LLMs while mitigating its pitfalls, including establishing a structure for utilizing LLMs and presenting clear regulations for their implementation. We also outline some specific steps on how to accomplish this structure. Large language models (LLMs) such as ChatGPT, are new technological tools that might fundamentally change academiaChatGPT can assist in academic writing but should not be relied on as the only source of information in hydrology and Earth Science studiesAuthors should exhibit transparency in their utilization of LLMs and uphold ethical responsibility Large language models (LLMs) such as ChatGPT, are new technological tools that might fundamentally change academia ChatGPT can assist in academic writing but should not be relied on as the only source of information in hydrology and Earth Science studies Authors should exhibit transparency in their utilization of LLMs and uphold ethical responsibility

This study investigates nutrient‐related water quality conditions and change trends in the first management periods of the EU Water Framework Directive (WFD; since 2009) and Baltic Sea Action Plan (BASP; since 2007). With mitigation of nutrients in inland waters and their discharges to the Baltic Sea being a common WFD and BSAP target, we use Sweden as a case study of observable effects, by compiling and analyzing all openly available water and nutrient monitoring data across Sweden since 2003. The data compilation reveals that nutrient monitoring covers only around 1% (down to 0.2% for nutrient loads) of the total number of WFD‐classified stream and lake water bodies in Sweden. The data analysis further shows that the hydro‐climatically driven water discharge dominates the determination of waterborne loads of both total phosphorus and total nitrogen across Sweden. Both water discharge and the related nutrient loads are in turn well correlated with the ecosystem status classification of Swedish water bodies. Nutrient concentrations do not exhibit such correlation and their changes over the study period are on average small, but concentration increases are found for moderate‐to‐bad status waters, for which both the WFD and the BSAP have instead targeted concentration decreases. In general, these results indicate insufficient distinction and mitigation of human‐driven nutrient components in inland waters and their discharges to the sea by the internationally harmonized applications of the WFD and the BSAP. The results call for further comparative investigations of observable large‐scale effects of such regulatory/management frameworks in different parts of the world. Nutrient loads correlate well with classified ecosystem status in monitored waters; nutrient concentrations do notWater discharge determines nutrient loads and underlies their correlation with ecosystem status classNutrient concentration increases—not expected decreases—are found after first management period

The separate and combined effects of different drivers of change to water fluxes and resources on land (CWOL) remain difficult to distinguish and largely unknown, particularly at a global scale. Our study analyzes CWOL during the period 1901–2008, based on available hydroclimatic data for up to 859 hydrological basins. We develop a worldwide spectrum of change magnitudes and directions in Budyko space, from which we distinguish climate and landscape drivers of CWOL. We find that landscape drivers (e.g., changes in land and water use, water storage or water phase) are needed to explain CWOL in at least 74% of the basins studied. The water change effects of such landscape drivers are mostly opposite to those of atmospheric climate change. The change spectrum approach we developed provides a useful tool for quantifying and visualizing CWOL and for distinguishing the effects of climate and landscape drivers across regions and scales. Global historic changes of water on land are quantified and visualizedIn 74% of the basins water change explanation requires landscape driversLandscape‐driven effects are mostly in opposite direction to climate‐driven effects

On behalf of the editorial board of Water Resources Research (WRR)and the entire water science community, we want to express our most heartfelt gratitude to all who reviewed manuscripts for the journal in 2021. Your great efforts have ensured and improved the high quality and impact of the WRR papers and generally of research in our field. In 2021, the 2,960 individuals listed below have contributed 4,788 peer reviews with the 432 people indicated in italics, reviewing three or more papers for the journal. The editors, associate editors, and authors of WRR sincerely thank all our reviewers and look forward to the exciting advances that will be published in WRR in 2022.

Hydrological change is a central part of global change. Its drivers in the past need to be understood and quantified for accurate projection of disruptive future changes. Here we analyse past hydro-climatic, agricultural and hydropower changes from twentieth century data for nine major Swedish drainage basins, and synthesize and compare these results with other regional and global assessments of hydrological change by irrigation and deforestation. Cross-regional comparison shows similar increases of evapotranspiration by non-irrigated agriculture and hydropower as for irrigated agriculture. In the Swedish basins, non-irrigated agriculture has also increased, whereas hydropower has decreased temporal runoff variability. A global indication of the regional results is a net total increase of evapotranspiration that is larger than a proposed associated planetary boundary. This emphasizes the need for climate and Earth system models to account for different human uses of water as anthropogenic drivers of hydro-climatic change. The present study shows how these drivers and their effects can be distinguished and quantified for hydrological basins on different scales and in different world regions. This should encourage further exploration of greater basin variety for better understanding of anthropogenic hydro-climatic change.

Editors‐in‐chief of AGU journals stress urgent need for greening economyCross‐sector solutions‐based science must supplement basic researchAGU is adding solutions‐based community science journal to portfolio Editors‐in‐chief of AGU journals stress urgent need for greening economy Cross‐sector solutions‐based science must supplement basic research AGU is adding solutions‐based community science journal to portfolio

Large‐scale covariations of freshwater fluxes and storages on land can critically regulate the balance of green (evapotranspiration) and blue (runoff) water fluxes, and related land‐atmosphere interactions and hydroclimatic hazards. Such large‐scale covariation patterns are not evident from smaller‐scale hydrological studies that have been most common so far, and remain largely unknown for various regions and climates around the world. To contribute to bridging the large‐scale knowledge gaps, we synthesize and decipher hydroclimatic data time series over the period 1980–2010 for 6,405 catchments around the world. From observation‐based data, we identify dominant large‐scale linear covariation patterns between monthly freshwater fluxes and soil moisture (SM) for different world parts and climates. These covariation patterns are also compared with those obtained from reanalysis products and Earth System Models (ESMs). The observation‐based data sets robustly show the strongest large‐scale hydrological relationship to be that between SM and runoff (R), consistently across the study catchments and their different climate characteristics. This predominantly strongest covariation between monthly SM and R is also the most misrepresented by ESMs and reanalysis products, followed by that between monthly precipitation and R. Comparison of observation‐based and ESM results also shows that an ESM may perform well for individual monthly variables, but fail in representing the patterns of large‐scale linear covariations between them. Observation‐based quantification of these patterns, and ESM and reanalysis improvements for their representation are essential for fundamental understanding, and more accurate and reliable modeling and projection of large‐scale hydrological conditions and changes under ongoing global and regional change. The closest large‐scale monthly covariations across different regions and worldwide are between soil moisture and runoffMonthly covariations in blue‐water precipitation‐runoff and green‐water precipitation‐evapotranspiration are mostly weakerSoil moisture‐runoff and precipitation‐runoff relationships are the most misrepresented by studied reanalysis products and Earth System Models The closest large‐scale monthly covariations across different regions and worldwide are between soil moisture and runoff Monthly covariations in blue‐water precipitation‐runoff and green‐water precipitation‐evapotranspiration are mostly weaker Soil moisture‐runoff and precipitation‐runoff relationships are the most misrepresented by studied reanalysis products and Earth System Models

This study develops a theoretical tool for investigating the impact on cost effective coastal water management from explicit treatment of: coastal pollutant transports, stochastic pollutant transports in the catchment areas, and wetlands as a pollutant abatement option. It is applied to a relatively well investigated estuary, Himmerfjärden, south of the Swedish capital, Stockholm. The theoretical results indicate that all three factors influence cost effective allocation of measures and associated design of economic instruments. The consideration of stochastic pollutant transports will increase costs, but the direction of influence of the other two factors cannot be determined without empirical support. The application to nitrogen transport in Himmerfjärden shows that, for target nitrogen reductions given in terms of a percentage of pre-abatement loads, the inclusion of coastal transports in the cost calculations lowers the estimated total costs for targets interpreted in terms of nitrogen loads to the marine water. The alternative investigated target interpretation was in terms of nitrogen loads to coastal waters. Depending on the ability of wetlands to abate nitrogen and to change the variance in pollutant load to the coastal recipients, costs are either increased or decreased as compared to when wetlands are excluded as nitrogen abatement options.

The editors thank the 2020 peer reviewers The editors thank the 2020 peer reviewers

In coastal aquifers the dynamic mixing zone between intruding seawater and fresh groundwater constitutes a zone of salinity transition that may supply brackish groundwater along with chemical tracers and nutrients to coastal waters. Tidal influence has been proposed as a possible mechanism for enhancement of recirculated seawater, total submarine groundwater discharge (SGD), and associated tracer loading through salinity transition zones into coastal waters. We show that tidal oscillation may, for relatively low SGD cases, considerably increase the average recirculated seawater component of total SGD relative to nontidal conditions. High SGD cases, however, are dominated by and require large fresh groundwater flow components also under tidal conditions; this result is obtained from a wide range of different groundwater simulation scenarios and is supported by direct comparison with field data from different reported high‐SGD sites in the world. For cases with hydrologically limited fresh groundwater flow directly into the sea we propose that observed excessive coastal loading of groundwater‐derived tracers may be the result of large groundwater flow and transport into unmonitored coastal stream reaches, in addition to SGD.