Hydrology and Earth System Sciences

Hydrology and Earth System Sciences

Published by Copernicus Publications on behalf of European Geosciences Union

Online ISSN: 1607-7938

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Print ISSN: 1027-5606

Disciplines: Geosciences, Multidisciplinary; Water Resources

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Schematic of the proposed cross-site synthesis. Obs, Db, M, and UPH indicate observatories, database, models, and Unsolved Problems in Hydrology, respectively.
Graphical illustration of a hydrological observatory (HO) network in the European Union (EU) in scenario 1. Each sub-catchment is equipped with basic instrumentation: a weather station, a runoff gauging station, a cosmic-ray neutron sensor (CRNS) with a wireless sensor network controlling soil profile sensors, and a streamflow sensor at the catchment's outlet. Satellite products are available anywhere in the world. The soil profile cross-section illustrates the soil profile sensor unit and the stationary CRNS.
Graphical illustration of a hydrological observatory (HO) network in the European Union (EU) in scenario 2. Each sub-catchment established along an ideal transect is equipped with a high-density network of sampling and monitoring units for soil hydrology research. Frequent uncrewed aerial system (UAS) and aircraft surveys are organized over the experimental area. Satellite products are available anywhere in the world. Frequent campaigns of geophysical (electromagnetic induction, EMI technique) and tracing (stable isotopes in water, such as δ2H and δ18O) measurements are carried out across the HO. Flow monitoring and water sampling are carried out along the stream. The soil profile cross-section shows the monitoring and sampling activities in the groundwater–soil–plant–atmosphere continuum in a position of the dense point grid (purple circles).
Possible configurations of hydrological observatory (HO) networks are illustrated, spanning a range from a few (color-coded in red) to numerous (color-coded in blue) HOs. The thickness of the arrows indicates the quantity of instruments present in each HO. The data obtained from the HO network and remote sensing platforms are used to inform hydrological models of different complexities, enabling us to address specific scientific questions across disparate spatial scales.
HESS Opinions: Towards a common vision for the future of hydrological observatories

January 2025

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236 Reads

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Günter Blöschl

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Interactive Public Peer Review · Community driven · Not for profit

Hydrology and Earth System Sciences (HESS) is a not-for-profit international two-stage open-access journal for the publication of original research in hydrology. HESS encourages and supports fundamental and applied research that advances the understanding of hydrological systems, their role in providing water for ecosystems and society, and the role of the water cycle in the functioning of the Earth system. A multi-disciplinary approach is encouraged that broadens the hydrological perspective and the advancement of hydrological science through integration with other cognate sciences and cross-fertilization across disciplinary boundaries.

Recent articles


Expected annual minima from an idealized moving-average drought index
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February 2025

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3 Reads

Numerous drought indices originate from the Standardized Precipitation Index (SPI) and use a moving-average structure to quantify drought severity by measuring normalized anomalies in hydroclimate variables. This study examines the theoretical probability of annual minima based on such a process. To accomplish this, we derive a stochastic model and use it to simulate 10 ×106 years of daily or monthly SPI values in order to determine the distribution of annual exceedance probabilities. We believe this is the first explicit quantification of annual extreme exceedances from a moving-average process where the moving-average window is proportionally large (5 %–200 %) relative to the year, as is the case for many moving-window drought indices. The resulting distribution of annual minima follows a generalized normal distribution rather than the generalized extreme-value (GEV) distribution, as would be expected from extreme-value theory. From a more applied perspective, this study provides the expected annual return periods for the SPI or related drought indices with common accumulation periods (moving-window length), ranging from 1 to 24 months. We show that the annual return period differs depending on both the accumulation period and the temporal resolution (daily or monthly). The likelihood of exceeding an SPI threshold in a given year decreases as the accumulation period increases. This study provides clarification and a caution for the use of annual return period terminology (e.g. the 100-year drought) with the SPI and a further caution for comparing annual exceedances across indices with different accumulation periods or resolutions. The study also distinguishes between theoretical values, as calculated here, and real-world exceedance probabilities, where there may be climatological autocorrelation beyond that created by the moving average.


Assessing national exposure to and impact of glacial lake outburst floods considering uncertainty under data sparsity

February 2025

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62 Reads

Glacial lake outburst floods (GLOFs) are widely recognised as one of the most devastating natural hazards in the Himalayas, with catastrophic consequences, including substantial loss of life. To effectively mitigate these risks and enhance regional resilience, it is imperative to conduct an objective and holistic assessment of GLOF hazards and their potential impacts over a large spatial scale. However, this is challenged by the limited availability of data and the inaccessibility to most of the glacial lakes in high-altitude areas. The data challenge is exacerbated when dealing with multiple lakes across an expansive spatial area. This study aims to exploit remote sensing techniques, well-established Bayesian regression models for estimating glacial lake conditions, cutting-edge flood modelling technology, and open data from various sources to innovate a framework for assessing the national exposure and impact of GLOFs. In the innovative framework, multi-temporal imagery is utilised with a random forest model to extract glacial lake water surfaces. Bayesian models are employed to estimate a plausible range of glacial lake water volumes and the associated GLOF peak discharges while accounting for the uncertainty stemming from the limited sizes of the available data and outliers within the data. A significant number of GLOF scenarios is subsequently generated based on this estimated plausible range of peak discharges. A graphics processing unit (GPU)-based hydrodynamic model is then adopted to simulate the resulting flood hydrodynamics in different GLOF scenarios. Necessary socio-economic information is collected and processed from multiple sources, including OpenStreetMap, Google Earth, local archives, and global data products, to support exposure analysis. Established depth–damage curves are used to assess the GLOF damage extents for different exposures. The evaluation framework is applied to 21 glacial lakes identified as potentially dangerous in the Nepalese Himalayas. The results indicate that, in the scenario of a complete breach of dam height across 21 lakes, Tsho Rolpa Lake, Thulagi Lake, and Lower Barun Lake bear the most serious impacts of GLOFs on buildings, roads, and agricultural areas, while Thulagi Lake could influence existing hydropower facilities. One unnamed lake in the Trishuli River basin, two unnamed lakes in the Tamor River basin, and three unnamed lakes in the Dudh River basin have the potential to impact more than 200 buildings. Moreover, the unnamed lake in the Trishuli River basin has the potential to inundate existing hydropower facilities.


Simulating the Tone River eastward diversion project in Japan carried out 4 centuries ago

February 2025

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6 Reads

The Tone River is the largest river in Japan, flowing from the Kanto Plain westward to the Pacific Ocean. The river originally flowed southward, entering Tokyo Bay, but the Tone River eastward diversion project (TREDP) in the 17th century and many later projects changed the flow route to that of today. The gradual process of eastward diversion has been extensively studied from the historical viewpoint, revealing that the initial project in the 17th century was principally intended to establish a stable navigation route. However, no scholars have yet proven this hypothesis via hydrological modeling. We used the H08 global hydrological model to reconstruct historical flow direction maps at a 60 arcsec spatial resolution with a 1 d temporal resolution. We hypothesized that the historical claims could be numerically verified using a relatively simple simulation. First, we confirmed that our modeling framework reasonably reproduced the present river flows by adding two present-day bifurcation functions. Next, using the reconstructed historical maps, we quantified low flows (20th percentile) in the 17th century and confirmed that the Tone River diversion aided navigation because it connected areas that increased low flows. Finally, the validity of our historical simulation was proven by contrasting the distribution of simulated low flow rates with the flows at the historical river ports that lie furthest upstream. We show that it is possible to bridge two different disciplines, history, and numerical hydrological modeling to obtain a better understanding of human–water interactions. One limitation is that we only reconstructed historical land maps in the present study; the meteorological forcing inputs employed were identical to those of the 20th century. The historical inputs are not known.


Lack of robustness of hydrological models: a large-sample diagnosis and an attempt to identify hydrological and climatic drivers

February 2025

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12 Reads

The transferability of hydrological models over contrasting climate conditions, also identified as model robustness, has been the subject of much research in recent decades. The occasional lack of robustness identified in such models is not only an operational challenge – since it affects the confidence that can be placed in projections of climate change impact – it also hints at possible deficiencies in the structures of these models. This paper presents a large-scale application of the robustness assessment test (RAT) for three hydrological models with different levels of complexity: GR6J, HYPE and MIKE SHE. The dataset comprises 352 catchments located in Denmark, France and Sweden. Our aim is to evaluate how robustness varies over the dataset and between models and whether the lack of robustness can be linked to some hydrological and/or climate characteristics of the catchments (thus providing a clue as to where to focus model improvement efforts). We show that, although the tested models are very different, they encounter similar robustness issues over the dataset. However, models do not necessarily lack robustness in the same catchments and are not sensitive to the same hydrological characteristics. This work highlights the applicability of the RAT regardless of model type and its ability to provide a detailed diagnostic evaluation of model robustness issues.


Canopy structure modulates the sensitivity of subalpine forest stands to interannual snowpack and precipitation variability

February 2025

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35 Reads

A declining spring snowpack is expected to have widespread effects on montane and subalpine forests in western North America and across the globe. The way that tree water demands respond to this change will have important impacts on forest health and downstream water subsidies. Here, we present data from a network of sap velocity sensors and xylem water isotope measurements from three common tree species (Picea engelmannii, Abies lasiocarpa and Populus tremuloides) across a hillslope transect in a subalpine watershed in the Upper Colorado River basin. We use these data to compare tree- and stand-level responses to the historically high spring snowpack but low summer rainfall of 2019 against the low spring snowpack but high summer rainfall amounts of 2021 and 2022. From the sap velocity data, we found that only 40 % of the trees showed an increase in cumulative transpiration in response to the large snowpack year (2019), illustrating the absence of a common response to interannual spring snowpack variability. The trees that increased water use during the year with the large spring snowpack were all found in dense canopy stands – irrespective of species – while trees in open-canopy stands were more reliant on summer rains and, thus, more active during the years with modest snow and higher summer rain amounts. Using the sap velocity data along with supporting measurements of soil moisture and snow depth, we propose three mechanisms that lead to stand density modulating the tree-level response to changing seasonality of precipitation: Topographically mediated convergence zones have consistent access to recharge from snowmelt which supports denser stands with high water demands that are more reliant and sensitive to changing snow. Interception of summer rain in dense stands reduces the throughfall of summer rain to surface soils, limiting the sensitivity of the dense stands to changes in summer rain. Shading in dense stands allows the snowpack to persist deeper into the growing season, providing high local reliance on snow during the fore-summer (early-summer) drought period. Combining data generated from natural gradients in stand density, like this experiment, with results from controlled forest-thinning experiments can be used to develop a better understanding of the responses of forested ecosystems to futures with reduced spring snowpack.


Modeling Lake Titicaca's water balance: the dominant roles of precipitation and evaporation

February 2025

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43 Reads

In the face of climate change and increasing anthropogenic pressures, a reliable water balance is crucial for understanding the drivers of water level fluctuations in large lakes. However, in poorly gauged hydrosystems such as Lake Titicaca, most components of the water balance are not measured directly. Previous estimates for this lake have relied on scaling factors to close the water balance, which introduces additional uncertainty. This study presents an integrated modeling framework based on conceptual models to quantify natural hydrological processes and net irrigation consumption. It was implemented in the Water Evaluation and Planning System (WEAP) platform at a daily time step for the period 1982–2016, considering the following terms of the water balance: upstream inflows, direct precipitation and evaporation over the lake, and downstream outflows. To estimate upstream inflows, we evaluated the impact of snow and ice processes and net irrigation withdrawals on predicted streamflow and lake water levels. We also evaluated the role of heat storage change in evaporation from the lake. The results showed that the proposed modeling framework makes it possible to simulate lake water levels ranging from 3808 to 3812 m a.s.l. with good accuracy (RMSE = 0.32 m d⁻¹) over a wide range of long-term hydroclimatic conditions. The estimated water balance of Lake Titicaca shows that upstream inflows account for 56 % (958 mm yr⁻¹) and direct precipitation over the lake for 44 % (744 mm yr⁻¹) of the total inflows, while 93 % (1616 mm yr⁻¹) of the total outflows are due to evaporation and the remaining 7 % (121 mm yr⁻¹) to downstream outflows. The water balance closure has an error of -15 mm yr⁻¹ without applying scaling factors. Snow and ice processes, together with net irrigation withdrawals, had a minimal impact on variations in the lake water level. Thus, Lake Titicaca is primarily driven by variations in precipitation and high evaporation rates. These results will be useful for supporting decision-making in water resource management. We demonstrate that a simple representation of hydrological processes and irrigation enables accurate simulation of water levels. The proposed modeling framework could be replicated in other poorly gauged large lakes because it is relatively easy to implement, requires few data, and is computationally inexpensive.


Achieving water budget closure through physical hydrological process modelling: insights from a large-sample study

February 2025

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13 Reads

Modern hydrology is embracing a data-intensive new era, with information from diverse sources currently providing support for hydrological inferences at broader scales. This results in a plethora of data-reliability-related challenges that remain unsolved. The water budget non-closure is a widely reported phenomenon in hydrological and atmospheric systems. Many existing methods aim to enforce water budget closure constraints through data fusion and bias correction approaches, often neglecting the physical interconnections between water budget components. To solve this problem, this study proposes a Multisource Dataset Correction Framework grounded in Physical Hydrological Process Modelling to enhance water budget closure, termed the PHPM-MDCF. The concept of decomposing the total water budget residuals into inconsistency and omission residuals is embedded in this framework to account for different residual sources. We examined the efficiency of the PHPM-MDCF and the distribution of residuals across 475 contiguous United States (CONUS) basins selected by hydrological simulation reliability. The results indicate that the inconsistency residuals dominate the total water budget residuals, exhibiting highly consistent spatiotemporal patterns. This portion of residuals can be significantly reduced through PHPM-MDCF correction and achieved satisfactory efficiency. The total water budget residuals decreased by 49 %, on average, across all basins, with reductions exceeding 80 % in certain basins. The credibility of the correction framework was further verified through noise experiments and comparisons with existing methods. In the end, we explored the potential factors influencing the distribution of residuals and found notable scale effects, along with the key role of hydro-meteorological conditions. This emphasizes the importance of carefully evaluating the water balance assumption when employing multisource datasets for hydrological inference in small and humid basins.


Assessing recovery time of ecosystems in China: insights into flash drought impacts on gross primary productivity

February 2025

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14 Reads

Recovery time, referring to the duration that an ecosystem needs to return to its pre-drought condition, is a fundamental indicator of ecological resilience. Recently, flash droughts – characterised by rapid onset and development – have gained increasing attention. Nevertheless, the spatiotemporal patterns in gross primary productivity (GPP) recovery time and the factors influencing it remain largely unknown. In this study, we investigate the recovery time patterns in a terrestrial ecosystem in China based on GPP using a random forest regression model and the SHapley Additive exPlanations (SHAP) method. A random forest regression model was developed to analyse the factors influencing recovery time and establish response functions through partial correlation for typical flash drought recovery periods. The dominant driving factors of recovery time were determined using the SHAP method. The results reveal that the average recovery time across China is approximately 37.5 d, with central and southern regions experiencing the longest durations. Post-flash-drought radiation emerges as the primary environmental factor, followed by the aridity index and post-flash-drought temperature, particularly in semi-arid and sub-humid areas. Temperature exhibits a non-monotonic relationship with recovery time, where both excessively cold and hot conditions lead to longer recovery periods. Herbaceous vegetation recovers more rapidly than woody forests, with deciduous broadleaf forests demonstrating the shortest recovery time. This study provides valuable insights for comprehensive water resource and ecosystem management and contributes to large-scale drought monitoring efforts.


Evaluation of high-resolution snowpack simulations from global datasets and comparison with Sentinel-1 snow depth retrievals in the Sierra Nevada, USA

February 2025

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33 Reads

The spatial distribution of mountain snow water equivalent (SWE) is key information for water management. We implement a tool to simulate snowpack properties at high resolution (100 m) by using only global datasets of meteorology, land cover and elevation. The meteorological data are obtained from ERA5, which makes the method applicable in near real time (5 d latency). We evaluate the output using 49 SWE maps derived from airborne lidar surveys in the Sierra Nevada. We find very good agreement at the catchment scale using uncalibrated lapse rates. Larger biases at the model grid scale are especially evident at high elevation but do not alter the catchment-scale snow mass accuracy. We additionally compare the simulated snow depth to Sentinel-1 retrievals and find a similar accuracy with respect to synchronous airborne lidar surveys. However, Sentinel-1 snow depth products are sparse and often masked during the melt season, whereas ERA5–SnowModel provides a spatially and temporally continuous SWE.


The benefits and trade-offs of multi-variable calibration of the WaterGAP global hydrological model (WGHM) in the Ganges and Brahmaputra basins

January 2025

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54 Reads

While global hydrological models (GHMs) are affected by large uncertainties regarding model structure, forcing and calibration data, and parameters, observations of model output variables are rarely used to calibrate the model. Pareto-dominance-based multi-objective calibration, often referred to as Pareto-optimal calibration (POC), may serve to estimate model parameter sets and analyse trade-offs among different objectives during calibration. Within a POC framework, we determined optimal parameter sets for the WaterGAP global hydrological model (WGHM) in the two largest basins of the Indian subcontinent – the Ganges and the Brahmaputra, collectively supporting nearly 580 million inhabitants. The selected model parameters, determined through a multi-variable, multi-signature sensitivity analysis, were estimated using up to four types of observations: in situ streamflow (Q), GRACE and GRACE Follow-On terrestrial water storage anomaly (TWSA), LandFlux evapotranspiration (ET), and surface water storage anomaly (SWSA) derived from multi-satellite observations. While our sensitivity analysis ensured that the model parameters that are most influential for the four variables were identified in a transparent and comprehensive way, the rather large number of calibration parameters, 10 for the Ganges and 16 for the Brahmaputra, had a negative impact on parameter identifiability during the calibration process. Calibration against observed Q was crucial for reasonable streamflow simulations, while additional calibration against TWSA was crucial for the Ganges basin and helpful for the Brahmaputra basin to obtain a reasonable simulation of both Q and TWSA. Additionally calibrating against ET and SWSA enhanced the overall model performance slightly. We identified several trade-offs among the calibration objectives, with the nature of these trade-offs closely tied to the physiographic and hydrologic characteristics of the study basins. The trade-offs were particularly pronounced in the Ganges basin, in particular between Q and SWSA, as well as between Q and ET. When considering the observational uncertainty of the calibration data, model performance decreases in most cases. This indicates an overfitting to the singular observation time series by the calibration algorithm. We therefore propose a transparent algorithm to identify high-performing Pareto solutions under consideration of observational uncertainties of the calibration data.


Do land models miss key soil hydrological processes controlling soil moisture memory?

January 2025

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65 Reads

Soil moisture memory (SMM), which refers to how long a perturbation in soil moisture (SM) can last, is critical for understanding climatic, hydrological, and ecosystem interactions. Most land surface models (LSMs) tend to overestimate surface soil moisture and its persistency (or SMM), sustaining spuriously large soil surface evaporation during dry-down periods. We attempt to answer a question: do LSMs miss or misrepresent key hydrological processes controlling SMM? We use a version of Noah-MP with advanced hydrology that explicitly represents preferential flow and surface ponding and provides optional schemes of soil hydraulics. We test the effects of these processes, which are generally missed by most LSMs in SMM. We compare SMMs computed from various Noah-MP configurations against that derived from the Soil Moisture Active Passive (SMAP) L3 soil moisture and in situ measurements from the International Soil Moisture Network (ISMN) from the years 2015 to 2019 over the contiguous United States (CONUS). The results suggest that (1) soil hydraulics plays a dominant role and the Van Genuchten hydraulic scheme reduces the overestimation of the long-term surface SMM produced by the Brooks–Corey scheme, which is commonly used in LSMs; (2) explicitly representing surface ponding enhances SMM for both the surface layer and the root zone; and (3) representing preferential flow improves the overall representation of soil moisture dynamics. The combination of these missing schemes can significantly improve the long-term memory overestimation and short-term memory underestimation issues in LSMs. We suggest that LSMs for use in seasonal-to-subseasonal climate prediction should, at least, adopt the Van Genuchten hydraulic scheme.


Effect of floodplain trees on apparent friction coefficient in straight compound channels

January 2025

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33 Reads

The interaction of water streams in channels with a complex cross section, involving the exchange of water mass and momentum between slowly flowing water in the floodplains and fast water in the main channel, significantly depends on the diversification of the surface roughness between the main channel and floodplains. Additionally, trees increase flow resistance strongly in floodplains and significantly in the main channel by intensifying the interaction process. As a result, the water velocity and the discharge capacity of both parts of the channel decrease and, at the same time, affect the flow conditions in the main channel. The results of laboratory experiments were used to determine the effect of floodplain trees on the discharge capacity of the channel with diversified roughness. The reduction in the velocity of the main channel caused by the stream interactions is described with the apparent friction coefficients introduced at the boundary between the main channel and the floodplain. The values of resistance coefficients and their changes as a result of the significant influence of trees on the interaction process were determined for different surface roughnesses of the main-channel bottom.


Technical note: A fast and reproducible autosampler for direct vapor equilibration isotope measurements

January 2025

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35 Reads

To investigate water movement in environmental systems, stable isotope (²H and ¹⁸O) ratios of water are commonly used tracers. Analyzing the isotopic ratios of water in or adsorbed to substances like soil or plant tissue necessitates the extraction or equilibration of water prior to analysis. One such method, direct vapor equilibration, is popular due to its cost-effectiveness and straightforward sample processing. However, sample analysis requires significant manual labor, thereby limiting the number of samples that can be analyzed. This limitation is compounded by the fact that stored samples undergo evaporative isotopic changes over time. Moreover, manual measurements require many laborious procedural steps that can easily compromise reproducibility. The operator has to subjectively decide if the measurements are stable and then record the analyzer readings. To address these challenges, we have developed a system that automates the analysis process. Our autosampler for vapor samples, named VapAuSa, features a modular design that allows for up to 350 ports for direct vapor equilibration samples. These ports sequentially connect the prepared samples to a laser isotope analyzer, enabling continuous automated measurements. Within the accompanying software, measurement criteria can be specified, facilitating reproducible analysis. The developed system was tested by co-measuring 90 soil samples and 21 liquid water samples with known δ values. VapAuSa measurements have a negligible measurement bias (<1×10-13 ‰ for both δ2H and δ18O) and similar measurement repeatability compared to manual analysis of identical samples (δ2H=±4.5 ‰ and δ18O=±0.58 ‰ for VapAuSa measurements vs. δ2H=±5.7 ‰ and δ18O=±0.37 ‰ for manual analysis). However, the increased sample throughput minimizes storage-induced isotopic changes. Moreover, VapAuSa triples sample throughput per week while also reducing the direct labor time to just 10 % of that required for manual processing.


Spatially explicit assessment of water stress and potential mitigating solutions in a large water-limited basin: the Yellow River basin in China

January 2025

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37 Reads

Comprehensive assessment of the long-term evolution of water stress and its driving factors is essential for designing effective water resource management strategies. However, the roles of water withdrawal and water availability components in determining water stress and potential mitigating measures in large water-scarce basins are poorly understood. Here, an integrated analytical framework was applied to the Yellow River basin (YRB), where the water crisis has been a core issue for sustainable development. The analysis suggests that the YRB has experienced unfavorable changes in critical water stress indicators over the past 56 years. Compared to the period from 1965 to 1980, the regional water stress index (WSI) and the frequency and duration of water scarcity increased by 76 %, 100 %, and 92 %, respectively, over the most recent 2 decades. Water withdrawal was the primary driver of the increased WSI before 2000; however, it has since contributed as much as water availability. Meanwhile, local water management and climate change adaptation were shown to be important in determining total water availability at the sub-basin scale. Water demand in the 2030s is predicted to be 6.5 % higher than during 2001–2020 (34.2 km³) based on the trajectory of historical irrigation water use and corrected socio-economic data under different Shared Socioeconomic Pathways (SSPs). To meet all sectoral water needs, a surface water deficit of 8.36 km³ is projected. Potential improvements in irrigation efficiency could address 25 % of this deficit, thereby alleviating the pressure on external water transfer projects. Such efficiency gains would enable the WSI of the YRB in the 2030s to be maintained at the current level (0.95), which would worsen conditions for 44.9 % of the total population while easing them for 10.7 % compared to in the 2000s. Our results have vital implications for water resource management in basins facing similar water crises to that in the YRB.


Schematic of the proposed cross-site synthesis. Obs, Db, M, and UPH indicate observatories, database, models, and Unsolved Problems in Hydrology, respectively.
Graphical illustration of a hydrological observatory (HO) network in the European Union (EU) in scenario 1. Each sub-catchment is equipped with basic instrumentation: a weather station, a runoff gauging station, a cosmic-ray neutron sensor (CRNS) with a wireless sensor network controlling soil profile sensors, and a streamflow sensor at the catchment's outlet. Satellite products are available anywhere in the world. The soil profile cross-section illustrates the soil profile sensor unit and the stationary CRNS.
Graphical illustration of a hydrological observatory (HO) network in the European Union (EU) in scenario 2. Each sub-catchment established along an ideal transect is equipped with a high-density network of sampling and monitoring units for soil hydrology research. Frequent uncrewed aerial system (UAS) and aircraft surveys are organized over the experimental area. Satellite products are available anywhere in the world. Frequent campaigns of geophysical (electromagnetic induction, EMI technique) and tracing (stable isotopes in water, such as δ2H and δ18O) measurements are carried out across the HO. Flow monitoring and water sampling are carried out along the stream. The soil profile cross-section shows the monitoring and sampling activities in the groundwater–soil–plant–atmosphere continuum in a position of the dense point grid (purple circles).
Possible configurations of hydrological observatory (HO) networks are illustrated, spanning a range from a few (color-coded in red) to numerous (color-coded in blue) HOs. The thickness of the arrows indicates the quantity of instruments present in each HO. The data obtained from the HO network and remote sensing platforms are used to inform hydrological models of different complexities, enabling us to address specific scientific questions across disparate spatial scales.
HESS Opinions: Towards a common vision for the future of hydrological observatories

January 2025

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236 Reads

The Unsolved Problems in Hydrology (UPH) initiative has emphasized the need to establish networks of multi-decadal hydrological observatories to gain a deep understanding of the complex hydrologic processes occurring within diverse environmental conditions. The already existing monitoring infrastructures have provided an enormous amount of hydrometeorological data, facilitating detailed insights into the causal mechanisms of hydrological processes, the testing of scientific theories and hypotheses, and the revelation of the physical laws governing catchment behavior. Yet, hydrological monitoring programs have often produced limited outcomes due to the intermittent availability of financial resources and the substantial efforts required to operate observatories and conduct comparative studies to advance previous findings. Recently, some initiatives have emerged that aim to coordinate data acquisition and hypothesis testing to facilitate an efficient cross-site synthesis of findings. To this end, a common vision and practical data management solutions need to be developed. This opinion paper provocatively discusses two potential endmembers of a future hydrological observatory (HO) network based on a given hypothesized community budget: a comprehensive set of moderately instrumented observatories or, alternatively, a small number of highly instrumented supersites. A network of moderately instrumented monitoring sites would provide a broad spatial coverage across the major pedoclimatic regions by supporting cross-site synthesis of the lumped hydrological response (e.g., rainfall–runoff relationship, Budyko analysis) across diverse continental landscapes. However, the moderate instrumentation at each site may hamper an in-depth understanding of complex hydrological processes. In contrast, a small number of extensively instrumented research sites would enable community-based experiments in an unprecedented manner, thereby facilitating a deeper understanding of complex, non-linear processes modulated by scale-dependent feedback and multiscale spatiotemporal heterogeneity. Lumping resources has proven to be an effective strategy in other geosciences, e.g., research vessels in oceanography and drilling programs in geology. On the downside, a potential limitation of this approach is that a few catchments will not be representative of all pedoclimatic regions, necessitating the consideration of generalization issues. A discussion on the relative merits and limitations of these two visions regarding HOs is presented to build consensus on the optimal path for the hydrological community to address the UPH in the coming decades. A final synthesis proposes the potential for integrating the two endmembers into a flexible management strategy. Keywords: hydrological observatory network, experimental catchments, cross-site synthesis, hypothesis testing vs. exploratory science, unsolved problems in hydrology, societal needs, technology advancements.


Heavy-tailed flood peak distributions: what is the effect of the spatial variability of rainfall and runoff generation?

January 2025

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25 Reads

The statistical distributions of observed flood peaks often show heavy-tailed behaviour, meaning that extreme floods are more likely to occur than for distributions with an exponentially receding tail. Falsely assuming light-tailed behaviour can lead to an underestimation of extreme floods. Robust estimation of the tail is often hindered due to the limited length of time series. Therefore, a better understanding of the processes controlling the tail behaviour is required. Here, we analyse how the spatial variability of rainfall and runoff generation affects the flood peak tail behaviour in catchments of various sizes. This is done using a model chain consisting of a stochastic weather generator, a conceptual rainfall-runoff model, and a river routing routine. For a large synthetic catchment, long time series of daily rainfall with varying tail behaviours and varying degrees of spatial variability are generated and used as input for the rainfall-runoff model. In this model, the spatial variability and mean depth of a sub-surface storage capacity are varied, affecting how locally or widely saturation excess runoff is triggered. Tail behaviour is characterized by the shape parameter of the generalized extreme value (GEV) distribution. Our analysis shows that smaller catchments tend to have heavier tails than larger catchments. For large catchments especially, the GEV shape parameter of flood peak distributions was found to decrease with increasing spatial rainfall variability. This is most likely linked to attenuating effects in large catchments. No clear effect of the spatial variability of the runoff generation on the tail behaviour was found.


How much water vapour does the Tibetan Plateau release into the atmosphere?

January 2025

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34 Reads

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1 Citation

Water vapour flux, expressed as evapotranspiration (ET), is critical for understanding the earth climate system and the complex heat–water exchange mechanisms between the land surface and the atmosphere in the high-altitude Tibetan Plateau (TP) region. However, the performance of ET products over the TP has not been adequately assessed, and there is still considerable uncertainty in the magnitude and spatial variability in the water vapour released from the TP into the atmosphere. In this study, we evaluated 22 ET products in the TP against in situ observations and basin-scale water balance estimations. This study also evaluated the spatiotemporal variability of the total vapour flux and of its components to clarify the vapour flux magnitude and variability in the TP. The results showed that the remote sensing high-resolution global ET data from ETMonitor and PMLV2 had a high accuracy, with overall better accuracy than other global and regional ET data with fine spatial resolution (∼ 1 km), when comparing with in situ observations. When compared with water balance estimates of ET at the basin scale, ETMonitor and PMLV2 at finer spatial resolution and GLEAM and TerraClimate at coarse spatial resolution showed good agreement. Different products showed different patterns of spatiotemporal variability, with large differences in the central to western TP. The multi-year and multi-product mean ET in the TP was 333.1 mmyr-1, with a standard deviation of 38.3 mmyr-1. The ET components (i.e. plant transpiration, soil evaporation, canopy rainfall interception evaporation, open-water evaporation, and snow/ice sublimation) available from some products were also compared, and the contribution of these components to total ET varied considerably, even in cases where the total ET from different products was similar. Soil evaporation accounts for most of the total ET in the TP, followed by plant transpiration and canopy rainfall interception evaporation, while the contributions from open-water evaporation and snow/ice sublimation cannot be negligible.


Potential of long-term satellite observations and reanalysis products for characterising soil drying: trends and drought events

January 2025

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73 Reads

Soil drying has multiple adverse impacts on the environment, society, and economy. Thus, it is crucial to monitor and characterise related drought events and to understand how underlying geophysical trends may affect them. Here, we compare the ability of long-term satellite observations and state-of-the-art reanalysis products to characterise soil drying. We consider the European Space Agency Climate Change Initiative (ESA CCI) remote-sensing surface soil moisture products (encompassing an ACTIVE, a PASSIVE, and a COMBINED product) as well as surface and root zone soil moisture from the ERA5, ERA5-Land, and MERRA-2 reanalysis products. In addition, we use a new root zone soil moisture dataset derived from the ESA CCI COMBINED product. We analyse global surface and root zone soil moisture trends in these products over the 2000–2022 period. Furthermore, we investigate the impact of the products' trend representation on their ability to capture major seasonal soil moisture (or agroecological) drought events as a use case. The latter is based on the analysis of 17 selected drought events documented in the scientific literature; these events are characterised by their severity (the time-accumulated standardised soil moisture anomalies), magnitude (the minimum of the standardised anomalies over time), duration, and spatial extent. The soil moisture trends are globally diverse and partly contradictory between products. ERA5, ERA5-Land, and ESA CCI COMBINED show larger fractions of drying trends, whereas ESA CCI ACTIVE and MERRA-2 display more widespread wetting trends. The differences between reanalysis products are related to a positive mean bias in the precipitation trends and regionally negative biases in surface air temperature trends in MERRA-2 compared with ground observational products, suggesting that this reanalysis underestimates drying trends. Given these biases in the MERRA-2 precipitation and temperature trends and considering available validation studies, the ESA CCI COMBINED-based products and ERA5-Land are considered more reliable and are consecutively used for a synthesis of global surface and root zone soil moisture trends. This synthesis suggests a consistent tendency towards soil drying during the last 2 decades in these products in 49.3 % of the surface and 44.5 % of the root zone layers of the covered global land area. The respective fractions of wetting trends amount to 21.1 % and 20.6 % for the surface and root zone, respectively, while areas with no trend direction consensus amount to 29.6 % and 35.0 %, respectively, reflecting the considerable uncertainties associated with global soil moisture trends. Geographically, drying is localised to parts of Europe and the Mediterranean; the Black Sea–Caspian Sea and Central Asian region; Siberia; parts of the western USA and the Canadian Prairies; and larger parts of South America, parts of southern and northern Africa, and parts of northwestern Australia. All investigated products mostly capture the considered drought events. Overall, the events tend to be least pronounced in the ACTIVE remote-sensing product across all drought metrics, particularly with respect to the magnitudes. Furthermore, MERRA-2 shows lower drought magnitudes than the other products, in both the surface layer and the root zone. The COMBINED remote-sensing products (surface and root zone soil moisture dataset) display partly stronger drought severities than the other products. In the root zone, the droughts are dampened with respect to the magnitude and smaller with respect to the spatial extent than in the surface layer, but they show a tendency toward prolonged durations and stronger severities. The product differences in the magnitude and severity of the drought events are consistent with the differences in soil moisture trends, which demonstrates that the representation of soil moisture trends plays a fundamental role in the drought-detection capacity of the different products.


Combined impacts of climate change and human activities on blue and green water resources in a high-intensity development watershed

January 2025

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48 Reads

Sustainable management of blue and green water resources is vital for the stability and sustainability of watershed ecosystems. Although there has been extensive attention paid to blue water (BW), which is closely related to human beings, the relevance of green water (GW) to ecosystem security is typically disregarded in water resource evaluations. Specifically, comprehensive studies are scarce on the detection and attribution of variations of blue and green water in the Dongjiang River basin (DRB), an important source of regional water supply in the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) of China. Here we assess the variations of BW and GW scarcity and quantify the impacts of climate change and land use change on BW and GW in DRB using the multi-water-flux calibrated Soil and Water Assessment Tool (SWAT). Results show that BW and green water storage (GWS) in DRB increased slowly at rates of 0.14 and 0.015 mm a⁻¹, respectively, while green water flow (GWF) decreased significantly at a rate of -0.21 mm a⁻¹. The degree of BW and GW scarcity in DRB is low, and the per capita water resources in more than 80 % of DRB exceed 1700 m³ per capita per year. Attribution results show that 88.0 %, 88.5 %, and 39.4 % of changes in BW, GWF, and GWS result from climate change. Both climate change and land use change have decreased BW, while climate change (land use change) has decreased (increased) GWF in DRB. These findings can guide the optimization of the allocation of blue and green water resources between upper and lower reach areas in DRB and further improve the understanding of blue and green water evolution patterns in humid regions.


Ecohydrological responses to solar radiation changes

January 2025

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36 Reads

The implementation of future geoengineering projects to counteract global warming trends or more generally changes in aerosol loads alter solar radiation reaching the Earth's surface. These changes could have effects on ecohydrological systems with impacts which are still poorly quantified. Here, we compute how changes in solar radiation affect global and local near-surface meteorological variables by using CMIP6 model results. Using climate model outputs, we compute climate sensitivities to solar radiation alterations. These sensitivities are then applied to local observations and used to construct two sets of numerical experiments: the first focuses on solar radiation changes only, and the second systematically modifies precipitation, air temperature, specific humidity, and wind speed using the CMIP6-derived sensitivities to radiation changes, i.e., including its land–atmosphere feedback. We use those scenarios as input to a mechanistic ecohydrological model to quantify the local responses of the energy and water budgets as well as vegetation productivity spanning different biomes and climates. In the absence of land–atmosphere feedback, changes in solar radiation tend to reflect mostly in sensible heat changes, with minor effects on the hydrological cycle, and vegetation productivity correlates linearly with changes in solar radiation. When land–atmosphere feedback is included, changes in latent heat and hydrological variables are much more pronounced, mostly because of the temperature and vapor pressure deficit changes associated with solar radiation changes. Vegetation productivity tends to have an asymmetric response with a considerable decrease in gross primary production to a radiation reduction not accompanied by a similar increase at higher radiation. These results provide important insights into how ecosystems could respond to potential future changes in shortwave radiation including solar geoengineering programs.


Revealing joint evolutions and causal interactions in complex ecohydrological systems by a network-based framework

January 2025

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35 Reads

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1 Citation

There is evidence that climate change and human activities are changing ecohydrological systems, yet the complex relationships among ecological (normalized difference vegetation index, gross primary productivity, and water use efficiency) and hydrological variables (runoff, soil water storage, groundwater storage, etc.) remain understudied. This study develops a novel framework based on network analysis alongside satellite data and in situ observations to delineate the joint evolutions (phenomena) and causal interactions (mechanisms) in complex systems. The former employs correlations, and the latter uses physically constrained causality analysis to construct network relationships. This framework is applied to the Yellow River basin, a region undergoing profound ecohydrological changes. Results suggest that joint evolutions are controlled by compound drivers and direct causality. Different types of network relationships are found – namely, joint evolution with weak causality, joint evolution with high causality, and asynchronous evolution with high causality. The upstream alpine subregions, for example, where the ecological subsystem is more influenced by temperature, while the hydrological one is more driven by precipitation, show relatively high synchronization but with weak and lagged causality between two subsystems. On the other hand, ecohydrological causality can be masked by intensive human activities (revegetation, water withdrawals, and reservoir regulation), leading to distinct evolution trends. Other mechanisms can also be deduced. Reductions in water use efficiency in the growing season are directly caused by the control of evapotranspiration, and the strength of control decreases with the greening land surface in some subregions. Overall, the proposed framework provides useful insight into the complex interactions within the ecohydrological systems for the Yellow River basin and has applicability to broader geographical contexts.


State updating of the Xin'anjiang model: joint assimilating streamflow and multi-source soil moisture data via the asynchronous ensemble Kalman filter with enhanced error models

January 2025

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34 Reads

Assimilating either soil moisture or streamflow individually has been well demonstrated to enhance the simulation performance of hydrological models. However, the runoff routing process may introduce a lag between soil moisture and outlet discharge, presenting challenges in simultaneously assimilating the two types of observations into a hydrological model. The asynchronous ensemble Kalman filter (AEnKF), an adaptation of the ensemble Kalman filter (EnKF), is capable of utilizing observations from both the assimilation moment and the preceding periods, thus holding potential to address this challenge. Our study first merges soil moisture data collected from field soil moisture monitoring sites with China Meteorological Administration Land Data Assimilation System (CLDAS) soil moisture data. We then employ the AEnKF, equipped with improved error models, to assimilate both the observed outlet discharge and the merged soil moisture data into the Xin'anjiang model. This process updates the state variables of the model, aiming to enhance real-time flood forecasting performance. Tests involving both synthetic and real-world cases demonstrates that assimilation of these two types of observations simultaneously substantially reduces the accumulation of past errors in the initial conditions at the start of the forecast, thereby aiding in elevating the accuracy of flood forecasting. Moreover, the AEnKF with the enhanced error model consistently yields greater forecasting accuracy across various lead times compared to the standard EnKF.


Effects of different climatic conditions on soil water storage patterns

January 2025

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85 Reads

The soil water storage (SWS) defines the crop productivity of a soil and varies under different climatic conditions. Pattern identification and quantification of these variations in SWS remain difficult due to the non-linear behaviour of SWS changes over time. Wavelet analysis (WA) provides a tool to efficiently visualize and quantify these patterns by transferring the time series from the time domain into the frequency domain. We applied WA to an 8-year time series of SWS, precipitation (P), and actual evapotranspiration (ETa) in similar soils of lysimeters in a colder and drier location and in a warmer and wetter location within Germany. Correlations between SWS, P, and ETa at these sites might reveal the influence of altered climatic conditions but also of subsequent wet and dry years on SWS changes. We found that wet and dry years exerted an influence over SWS changes by leading to faster or slower response times of SWS changes in relation to precipitation with respect to normal years. The observed disruption of annual patterns in the wavelet spectra of both sites was possibly caused by extreme events. Extreme precipitation events were visible in SWS and P wavelet spectra. Time shifts in correlations between ETa and SWS became smaller at the wetter and warmer site over time in comparison to at the cooler and drier site, where they stayed constant. This could be attributed to an earlier onset of the vegetation period over the years and, thus, to an earlier ETa peak every year. This reflects the impact of different climatic conditions on soil water budget parameters.


The effect of climate change on the simulated streamflow of six Canadian rivers based on the CanRCM4 regional climate model

January 2025

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57 Reads

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1 Citation

The effect of climate change on the hydro-climatology, particularly the streamflow, of six major Canadian rivers (Mackenzie, Yukon, Columbia, Fraser, Nelson, and St. Lawrence) is investigated by analyzing results from the historical and future simulations (RCP 4.5 and 8.5 scenarios) performed with the Canadian regional climate model (CanRCM4). Streamflow is obtained by routing runoff using river networks at 0.5° resolution. Of these six rivers, the Nelson and St. Lawrence are the most regulated. As a result, the streamflow at the mouth of these rivers shows very little seasonality. Additionally, the Great Lakes significantly dampen the seasonality of streamflow for the St. Lawrence River. Mean annual precipitation (P), evaporation (E), runoff (R), and temperature increase for all six river basins in both future scenarios considered here, and the increases are higher for the more fossil-fuel-intensive RCP 8.5 scenario. The only exception is the Nelson River basin, for which the simulated runoff increases are extremely small. The hydrological response of these rivers to climate warming is characterized by their existing climate states. The northerly Mackenzie and Yukon River basins show a decrease in the evaporation ratio (E/P) and an increase in the runoff ratio (R/P) since the increase in precipitation is more than enough to offset the increase in evaporation associated with increasing temperature. For the southerly Fraser and Columbia River basins, the E/P ratio increases despite an increase in precipitation, and the R/P ratio decreases due to an already milder climate in the northwestern Pacific region. The seasonality of simulated monthly streamflow is also more affected for the southerly Fraser and Columbia rivers than for the northerly Mackenzie and Yukon rivers as snow amounts decrease and snowmelt occurs earlier. The streamflow seasonality for the Mackenzie and Yukon rivers is still dominated by snowmelt at the end of the century, even in the RCP 8.5 scenario. The simulated streamflow regime for the Fraser and Columbia rivers shifts from a snow-dominated to a hybrid or rainfall-dominated regime towards the end of this century in the RCP 8.5 scenario. While we expect the climate change signal from CanRCM4 to be higher than that from other climate models, owing to the higher-than-average climate sensitivity of its parent global climate model, the results presented here provide a consistent overview of hydrological changes across six major Canadian river basins in response to a warmer climate.


Synchronization frequency analysis and stochastic simulation of multi-site flood flows based on the complicated vine copula structure

January 2025

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56 Reads

Accurately modeling and predicting flood flows across multiple sites within a watershed presents significant challenges due to potential issues of insufficient accuracy and excessive computational demands in existing methodologies. In response to these challenges, this study introduces a novel approach centered around the use of vine copula models, termed RDV-Copula (reduced-dimension vine copula construction approach). The core of this methodology lies in its ability to integrate and extract complex data before constructing the copula function, thus preserving the intricate spatial–temporal connections among multiple sites while substantially reducing the vine copula's complexity. This study performs a synchronization frequency analysis using the devised copula models, offering valuable insights into flood encounter probabilities. Additionally, the innovative approach undergoes validation by comparison with three benchmark models which vary in dimensions and nature of variable interactions. Furthermore, the study conducts stochastic simulations, exploring both unconditional and conditional scenarios across different vine copula models. Applied in the Shifeng Creek watershed, China, the findings reveal that vine copula models are superior in capturing complex variable relationships, demonstrating significant spatial interconnectivity crucial for flood risk prediction in heavy-rainfall events. Interestingly, the study observes that expanding the model's dimensions does not inherently enhance simulation precision. The RDV-Copula method not only captures comprehensive information effectively but also simplifies the vine copula model by reducing its dimensionality and complexity. This study contributes to the field of hydrology by offering a refined method for analyzing and simulating multi-site flood flows.


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5.7 (2023)

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10.1 (2023)

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1.415 (2023)

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