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Climate change, caused by an increase in anthropogenic emissions of greenhouse gasses, is having an increasingly noticeable effect on the Netherlands. Over the past years, we have seen periods of extreme droughts and high temperatures, but also periods of heavy rainfall. It is expected that these extreme events will continue to increase in the future. In addition to global mitigation efforts, it is necessary to take measures to adapt to the negative consequences of climate change. Many ongoing and large-scale spatial redevelopment initiatives, including the Nationaal Programma Landelijk Gebied (NPLG), the Programmatische Aanpak Grote Wateren (PAGW), the Programma NOVEX, Provinciale Bossenstrategieën and the Programma Waterveiligheid en Ruimte Limburg (WRL), consider climate-adaptive planning as a major theme in their planning. However, these policies do not consider the more direct way in which land use and spatial planning can influence the climate: through alternating land-atmosphere interactions and the so-called small water cycle. Yet, the exact role of how this mechanism affect the local climate remains uncertain. Therefore, a coalition of Limburg-based parties (including the Natuur en Milieufederatie Limburg, Waterschap Limburg, RVO, Provincie Limburg and the Limburgse Voedselbosbrigade) argues that there is an urgent need for more research into these land-atmosphere interactions on a regional scale. In this research, a first step has been taken in the form of an overview of the current state of knowledge on land-atmosphere interaction in the Netherlands and North-western Europe, including the possibility to influence these interactions on a regional or local scale through choices in land use, land cover, water management and planning. Based on this, we can provide well-founded advice on the scientific and societal relevance of further (model) research on these interactions in the context of climate adaptation. Based on a bibliographic database of relevant sc, Klimaatverandering, veroorzaakt door een toename in door de mens uitgestoten broeikasgassen, krijgt ook in Nederland steeds meer een voelbare impact. Zo hebben we in de afgelopen jaren periodes van extreme droogte en hoge temperaturen gezien, maar ook periodes van extreme neerslag. Verwacht wordt dat deze extremen ook in de toekomst verder zullen toenemen. Naast wereldwijde mitigatie, is het nodig om maatregelen te nemen die de negatieve gevolgen van klimaatverandering beperken. Een groot aantal actuele en grootschalige herontwikkelingen van de ruimtelijke indeling, waaronder het Nationaal Programma Landelijk Gebied (NPLG), de Programmatische Aanpak Grote Wateren (PAGW), het Programma NOVEX, provinciale Bossenstrategieën en het Programma Waterveiligheid en Ruimte Limburg (WRL), nemen klimaatadaptief inrichten dan ook als majeur thema mee in de planning. In dit beleid wordt echter geen rekening gehouden met het feit dat landgebruik en ruimtelijke inrichting het klimaat op een meer directe manier kunnen beïnvloeden via land-atmosfeerinteracties en de zogenoemde kleine waterkringloop. Wat deze rol van landgebruiksveranderingen op het lokale klimaat precies is, lijkt echter onzeker. Een coalitie van Limburgse partijen (bestaande uit Natuur en Milieufederatie Limburg, Waterschap Limburg, RVO, Provincie Limburg en de Limburgse Voedselbosbrigade) vindt daarom dat er snel meer onderzoek nodig is naar deze land-atmosfeer interacties op euregionale schaal. In dit onderzoek is een eerste stap gemaakt, in de vorm van een overzicht van de huidige stand van kennis over land-atmosfeerinteracties in Nederland en Noordwest-Europa, en over de mogelijkheid om deze interacties op regionale of lokale schaal te beïnvloeden met keuzes in grondgebruik, bedekkingsgraad, waterhuishouding en inrichting. Aan de hand hiervan kunnen we een goed onderbouwd advies geven over de vraag of het wetenschappelijk en maatschappelijk relevant is nader (model)onderzoek te doen naar deze interacties in d

The relation between drought severity and drought impacts is complex and relatively unexplored in the African continent. This study assesses the relation between reported drought impacts, drought indices, water scarcity and aridity across several counties in Kenya. The monthly bulletins of the National Drought Management Authority in Kenya provided drought impact data. A random forest (RF) model was used to explore which set of drought indices (standardized precipitation index, standardized precipitation evapotranspiration index, standardized soil moisture index and standardized streamflow index) best explains drought impacts on pasture, livestock deaths, milk production, crop losses, food insecurity, trekking distance for water and malnutrition. The findings of this study suggest a relation between drought severity and the frequency of drought impacts, whereby the latter also showed a positive relation with aridity. A relation between water scarcity and aridity was not found. The RF model revealed that every region, aggregated by aridity, had their own set of predictors for every impact category. Longer timescales (≥12 months) and the standardized streamflow index were strongly represented in the list of predictors, indicating the importance of hydrological drought to predict drought impact occurrences. This study highlights the potential of linking drought indices with text-based impact reports while acknowledging that the findings strongly depend on the availability of drought impact data. Moreover, it emphasizes the importance of considering spatial differences in aridity, water scarcity and socio-economic conditions within a region when exploring the relationships between drought impacts and indices.

Ground-based datasets of observed snow water equivalent (SWE) are scarce, while gridded SWE estimates from remote-sensing and climate reanalysis are unable to resolve the high spatial variability of snow on the ground. Long-term ground observations of snow depth, in combination with models that can accurately convert snow depth to SWE, can fill this observational gap. Here, we provide a new SWE dataset (NH-SWE) that encompasses 11 071 stations in the Northern Hemisphere (NH) and is available at 10.5281/zenodo.7515603 . This new dataset provides daily time series of SWE, varying in length between 1 and 73 years, spanning the period 1950-2022, and covering a wide range of snow climates including many mountainous regions. At each station, observed snow depth was converted to SWE using an established snow-depth-to-SWE conversion model, with excellent model performance using regionalised parameters based on climate variables. The accuracy of the model after parameter regionalisation is comparable to that of the calibrated model. The key advantages and strengths of the regionalised model presented here are its transferability across climates and the high performance in modelling daily SWE dynamics in terms of peak SWE, total snowmelt and duration of the melt season, as assessed here against a comparison model. This dataset is particularly useful for studies that require accurate time series of SWE dynamics, timing of snowmelt onset, and snowmelt totals and duration. It can, for example, be used for climate change impact analyses, water resources assessment and management, validation of remote sensing of snow, hydrological modelling, and snow data assimilation into climate models.

Rivers play an important role in the macroplastics transport and retention dynamics in the environment. Therefore, gaining an understanding of these processes is vital in order to help determine the fate of macroplastic in the environment. During flood events the transport of floating macroplastic is known to increase. We compared plastic accumulation and flushing on sixteen riverbanks along the Dutch Meuse river during the period that includes the July 2021 extreme flood to plastic accumulation on the same riverbanks as during normal discharge conditions between 2018 and 2021. Here we show that following the flood small macroplastic categories ($\lt\!2.5$ cm) were flushed from the riverbanks, while larger soft plastic fragments (2.5–50 cm) and wet tissues were deposited. We found that for all plastic categories and for all riverbanks averaged, the plastic accumulation rate during the July 2021 flood was higher than that which would be expected for that time of year. However, the average accumulation rate for all locations during the period that included the flood was lower than the average accumulation rate over the Dutch winter (Oct/Nov–Feb/Mar). Our results show that litter category composition following the July 2021 flood differed from normal conditions. This indicates that plastic deposition and remobilization processes on riverbanks differ between extreme flood and annually average conditions. These observations contribute to a better understanding of the fate of macroplastic in the environment in terms of the drivers of both its transport and deposition.

The accuracy of soil moisture estimated from synthetic aperture radar (SAR) backscatter data at high resolutions is limited by speckle. A common practice to mitigate speckle is to multilook the data prior to retrieving soil moisture. While multilooking indeed reduces speckle, it also decreases the spatial resolution and removes possibly useful high resolution information from the data. We, therefore, hypothesized that using higher resolution backscatter data for soil moisture retrieval would lead to higher retrieval accuracies. A high resolution field study combined with a synthetic experiment showed that calculating soil moisture prior to multilooking to the final target resolution calculate-then-average (CtA) has substantial advantages over the average-then-calculate (AtC) approach. Currently, the AtC strategy is most often applied in soil moisture studies, mainly due to its computational advantage compared to the CtA approach. We show that by making use of a higher source resolution backscatter data than the target resolution, we could improve soil moisture retrieval over an agricultural field.

Correction to: Nature Climate Change. Published online 4 July 2022. In the initially published version of this article, the calculation of the ecosystem limitation index (ELI; see “Methods”) had a programming error: the surface net radiation Rn, which should have been computed as the difference between incoming and outgoing shortwave and longwave radiation (SWin – SWout) + (LWin – LWout), was actually calculated as SWin + SWout. Despite the calculated variable not having any direct physical meaning, it has a spatiotemporal signature similar to that of the shortwave incoming radiation SWin alone, as SWin in vegetated areas is typically much larger than SWout. Further, shortwave incoming radiation is a widely used energy proxy1 and in light use efficiency models for gross primary productivity, as it is directly used by vegetation for photosynthesis and can therefore be closely associated with transpiration2. Hence, we introduce SWin as a new energy proxy in our analysis in order to correct for the described programming error. Given that the previous wrongly calculated energy proxy was similar to SWin, new results of our study are very similar to the published version. This led to changes in the text where instances of “(surface) net radiation” were replaced by “incoming shortwave radiation,” and some minor changes were made to Figures 1–4 and Supplementary Figures 1–20. For comparison, the original, uncorrected article is linked to this notice as Supplementary Information, and revised scripts and figures and data are available in refs. 3,4. Using SWin allows the calculation of ELI independent of temperature, which is used as a predictor in the attribution analysis. While net radiation relies on outgoing longwave radiation and therefore incorporates a temperature signal, SWin does not. The implementation of SWin as an energy proxy variable was also suggested under review. Supplementary information is available in the online version of this notice.

This paper shares an early-career perspective on potential themes for the upcoming International Association of Hydrological Sciences (IAHS) Scientific Decade (SD). This opinion paper synthesizes six discussion sessions in western Europe identifying three themes that all offer a different perspective on the hydrological threats the world faces and could serve to direct the broader hydrological community: “Tipping points and thresholds in hydrology,” “Intensification of the water cycle,” and “Water services under pressure.” Additionally, four trends were distinguished concerning the way in which hydrological research is conducted: big data, bridging science and practice, open science, and inter- and multidisciplinarity. These themes and trends will provide valuable input for future discussions on the theme for the next IAHS SD. We encourage other early-career scientists to voice their opinion by organizing their own discussion sessions and commenting on this paper to make this initiative grow from a regional initiative to a global movement.

The filling of the Grand Ethiopian Renaissance Dam (GERD) started in 2020, posing additional challenges for downstream water management in the Blue Nile River in the Republic of the Sudan, which is already struggling to cope with the effects of climate change. This is also the case for many transboundary rivers that are affected by a lack of cooperation and transparency during the filling and operation of new dams. Without information about water supply from neighboring countries, it is risky to manage downstream dams as usual, but operational information is needed to apply modifications. This study aims to develop a novel approach/framework that utilizes hydrological modeling in conjunction with remote-sensing data to retrieve reservoir filling strategies under limited-data-availability conditions. Firstly, five rainfall products (i.e., ARC2, CHIRPS, ERA5, GPCC, and PERSIANN-CDR; see Sect. 2.3 for more information) were evaluated against historical measured rainfall at 10 stations. Secondly, to account for input uncertainty, the three best-performing rainfall products were forced in the conceptual hydrological model HBV-light with potential evapotranspiration and temperature data from ERA5. The model was calibrated during the period from 2006 to 2019 and validated during the period from 1991 to 1996. Thirdly, the parameter sets that obtained very good performance (Nash-Sutcliffe efficiency, NSE, greater than 0.75) were utilized to predict the inflow of GERD during the operation period (2020-2022). Then, from the water balance of GERD, the daily storage was estimated and compared with the storage derived from Landsat and Sentinel imageries to evaluate the performance of the selected rainfall products and the reliability of the framework. Finally, 3 years of GERD filling strategies was retrieved using the best-performing simulation of CHIRPS with an RMSE of 1.7 ×109 and 1.52 ×109m3 and an NSE of 0.77 and 0.86 when compared with Landsat- and Sentinel-derived reservoir

Tree restoration is an effective way to store atmospheric carbon and mitigate climate change. However, large-scale tree-cover expansion has long been known to increase evaporation, leading to reduced local water availability and streamflow. More recent studies suggest that increased precipitation, through enhanced atmospheric moisture recycling, can offset this effect. Here we calculate how 900 million hectares of global tree restoration would impact evaporation and precipitation using an ensemble of data-driven Budyko models and the UTrack moisture recycling dataset. We show that the combined effects of directly enhanced evaporation and indirectly enhanced precipitation create complex patterns of shifting water availability. Large-scale tree-cover expansion can increase water availability by up to 6% in some regions, while decreasing it by up to 38% in others. There is a divergent impact on large river basins: some rivers could lose 6% of their streamflow due to enhanced evaporation, while for other rivers, the greater evaporation is counterbalanced by more moisture recycling. Several so-called hot spots for forest restoration could lose water, including regions that are already facing water scarcity today. Tree restoration significantly shifts terrestrial water fluxes, and we emphasize that future tree-restoration strategies should consider these hydrological effects.

We study the controls on open water evaporation of a large lowland reservoir in the Netherlands. To this end, we analyse the dynamics of open water evaporation at two locations, Stavoren and Trintelhaven, at the border of Lake IJssel (1100ĝ€¯km2); eddy covariance systems were installed at these locations during the summer seasons of 2019 and 2020. These measurements were used to develop data-driven models for both locations. Such a statistical model is a clean and simple approach that can provide a direct indication of (and insight into) the most relevant input parameters involved in explaining the variance in open water evaporation, without making a priori assumptions regarding the process itself. We found that a combination of wind speed and the vertical vapour pressure gradient can explain most of the variability in observed hourly open water evaporation. This is in agreement with Dalton's model, which is a well-established model often used in oceanographic studies for calculating open water evaporation. Validation of the data-driven models demonstrates that a simple model using only two variables yields satisfactory results at Stavoren, with R2 values of 0.84 and 0.78 for hourly and daily data respectively. However, the validation results for Trintelhaven fall short, with R2 values of 0.67 and 0.65 for hourly and daily data respectively. Validation of the simple models that only use routinely measured meteorological variables shows adequate performance at hourly (R2Combining double low line0.78 at Stavoren and R2Combining double low line0.51 at Trintelhaven) and daily (R2Combining double low line0.82 at Stavoren and R2Combining double low line0.87 at Trintelhaven) timescales. These results for the summer periods show that open water evaporation is not directly coupled to global radiation at the hourly or daily timescale. Rather a combination of wind speed and vertical gradient of vapour pressure is the main driver at these timescales. We would like to stress, Water Resources

Tree restoration is an effective way to store atmospheric carbon and mitigate climate change. However, large-scale tree-cover expansion has long been known to increase evaporation, leading to reduced local water availability and streamflow. More recent studies suggest that increased precipitation, through enhanced atmospheric moisture recycling, can offset this effect. Here we calculate how 900 million hectares of global tree restoration would impact evaporation and precipitation using an ensemble of data-driven Budyko models and the UTrack moisture recycling dataset. We show that the combined effects of directly enhanced evaporation and indirectly enhanced precipitation create complex patterns of shifting water availability. Large-scale tree-cover expansion can increase water availability by up to 6% in some regions, while decreasing it by up to 38% in others. There is a divergent impact on large river basins: some rivers could lose 6% of their streamflow due to enhanced evaporation, while for other rivers, the greater evaporation is counterbalanced by more moisture recycling. Several so-called hot spots for forest restoration could lose water, including regions that are already facing water scarcity today. Tree restoration significantly shifts terrestrial water fluxes, and we emphasize that future tree-restoration strategies should consider these hydrological effects.

The term "flash drought"describes a type of drought with rapid onset and strong intensity, which is co-affected by both water-limited and energy-limited conditions. It has aroused widespread attention in related research communities due to its devastating impacts on agricultural production and natural systems. Based on a global reanalysis dataset, we identify flash droughts across China during 1979-2016 by focusing on the depletion rate of weekly soil moisture percentile. The relationship between the rate of intensification (RI) and nine related climate variables is constructed using three machine learning (ML) technologies, namely, multiple linear regression (MLR), long short-term memory (LSTM), and random forest (RF) models. On this basis, the capabilities of these algorithms in estimating RI and detecting droughts (flash droughts and traditional slowly evolving droughts) were analyzed. Results showed that the RF model achieved the highest skill in terms of RI estimation and flash drought identification among the three approaches. Spatially, the RF-based RI performed best in southeastern China, with an average CC of 0.90 and average RMSE of the 2.6 percentile per week, while poor performances were found in the Xinjiang region. For drought detection, all three ML technologies presented a better performance in monitoring flash droughts than in conventional slowly evolving droughts. Particularly, the probability of detection (POD), false alarm ratio (FAR), and critical success index (CSI) of flash drought derived from RF were 0.93, 0.15, and 0.80, respectively, indicating that RF technology is preferable in estimating the RI and monitoring flash droughts by considering multiple meteorological variable anomalies in adjacent weeks to drought onset. In terms of the meteorological driving mechanism of flash drought, the negative precipitation (P) anomalies and positive potential evapotranspiration (PET) anomalies exhibited a stronger synergistic effect on flash droughts

Terrestrial ecosystems are essential for food and water security and CO2 uptake. Ecosystem function is dependent on the availability of soil moisture, yet it is unclear how climate change will alter soil moisture limitation on vegetation. Here we use an ecosystem index that distinguishes energy and water limitations in Earth system model simulations to show a widespread regime shift from energy to water limitation between 1980 and 2100. This shift is found in both space and time. While this is mainly related to a reduction in energy-limited regions associated with increasing surface net radiation, the largest shift towards water limitation is found in regions where net radiation increases are accompanied by soil moisture decreases. We therefore demonstrate a widespread regime shift in ecosystem function that is stronger than implied by individual trends in net radiation, soil moisture and terrestrial evaporation, with important implications for future ecosystem services.

We study the controls on open water evaporation of a large lowland reservoir in the Netherlands. To this end, we analyse the dynamics of open water evaporation at two locations, Stavoren and Trintelhaven, at the border of Lake IJssel (1100ĝ€¯km2); eddy covariance systems were installed at these locations during the summer seasons of 2019 and 2020. These measurements were used to develop data-driven models for both locations. Such a statistical model is a clean and simple approach that can provide a direct indication of (and insight into) the most relevant input parameters involved in explaining the variance in open water evaporation, without making a priori assumptions regarding the process itself. We found that a combination of wind speed and the vertical vapour pressure gradient can explain most of the variability in observed hourly open water evaporation. This is in agreement with Dalton's model, which is a well-established model often used in oceanographic studies for calculating open water evaporation. Validation of the data-driven models demonstrates that a simple model using only two variables yields satisfactory results at Stavoren, with R2 values of 0.84 and 0.78 for hourly and daily data respectively. However, the validation results for Trintelhaven fall short, with R2 values of 0.67 and 0.65 for hourly and daily data respectively. Validation of the simple models that only use routinely measured meteorological variables shows adequate performance at hourly (R2Combining double low line0.78 at Stavoren and R2Combining double low line0.51 at Trintelhaven) and daily (R2Combining double low line0.82 at Stavoren and R2Combining double low line0.87 at Trintelhaven) timescales. These results for the summer periods show that open water evaporation is not directly coupled to global radiation at the hourly or daily timescale. Rather a combination of wind speed and vertical gradient of vapour pressure is the main driver at these timescales. We would like to stress the

Given the diverse physico-chemical properties of elements, we hypothesize that their incoherent distribution across the leaf tissues, combined with the distinct resistance to degradation that each tissue exhibits, leads to different turnover rates among elements. Moreover, litter layers of varying ages produce diverse chemical signatures in solution during the wet degradation. To verify our hypothesis, Na, K, Mg, Mn, Ca, Pb, Al and Fe were analysed together with the rare earth elements (REE) in the solid fractions and in the respective leachates of fresh leaves and different litter layers of two forested soils developed under Pseudotsuga menziesii and Fagus sylvatica L. trees. The results from the leaching experiment were also compared with the in situ REE composition of the soil solutions to clarify the impact that the litter degradation processes may have on soil solution chemical composition. Both tree species showed similar biogeochemical processes dominating the element dynamics during litter degradation. REE, Al, Fe and Pb were preferentially retained in the solid litter material, in comparison with the other cations, and their concentrations increased over time during the degradation. Accordingly, different litter fractions produced different yields of elements and REE patterns in the leachates, indicating that the tree species and the age of the litter play a role in the chemical release during degradation. In particular, the evolution of the REE patterns, relative to the age of the litter layers, allowed us to deliver new findings on REE fractionation and mobilization during litter decay. Specifically, the degradation of the litter was characterized by a decrease in the Y/Ho ratio and an increase in the LaN/YbN ratio. The relationship between these ratios provided information on the litter species-specific resistance to degradation, with Douglas-fir litter material showing a lower resistance. During the litter degradation of the two tree species, two main d