Ecohydrological Model Research Articles

Spatiotemporal green water dynamics and their responses to variations of climatic and underlying surface factors: A case study in the Sanjiang Plain, China

Study regionThe Sanjiang Plain (SJP), located at the confluence reaches of the Heilong, Songhua, and Wusuli Rivers in Northeast China. Study focusThis study aimed to quantify the effects of varying climate and land-use/land-cover (LULC) dynamics on green water (GW) over the SJP during two distinctive periods (i.e., pre-2000 and post-2000), when synergetic effects of increased precipitation and temperature and rapid development of agriculture occurred. This assessment used the distributed eco-hydrological model ESSI-3. Multivariable and multi-objective calibration approaches (i.e., discharge, evapotranspiration, and terrestrial water storage anomaly) were used to ensure the high accuracies of the model outputs. New hydrological insights for the regionThis research concluded that GW flow and GW storage in the SJP evidently increased after 2000 compared with before. Across the SJP, GW flow and GW storage responded differently to climate changes and LULC dynamics during pre-2000 and post-2000 period. Our results demonstrated that GW storage changes were predominately affected by climatic changes, especially variations in precipitation, whose contribution accounted for more than 56% after 2000. However, GW flow changes were mainly governed by LULC changes, especially the influence of cropland transformation, whose contribution increased over 20% in the post-2000 period. This study posed a deep insight regarding impacts of regional climatic and LULC changes on GW dynamics, which may benefit decision-making for planting structure optimization and adjustment over the region.

Development of a process-based eco-hydrology model for evaluating the spatio-temporal dynamics of macro- and micro-plastics for the whole of Japan

Plastic contamination has been receiving considerable attention during the last few decades. Although some models could simulate transport and fate of plastic debris in freshwater systems, complete model for the whole picture of plastic dynamics on basin scale has yet to be established. In the present study, the authors extended process-based eco-hydrology models, NICE (National Integrated Catchment-based Eco-hydrology) and NICE-BGC (BioGeochemical Cycle), to link them with plastic debris model, and applied to all of the 109 first-class (class A) river basins throughout Japan. New model included advection, dispersion, diffusion, settling, dissolution and deterioration due to light and temperature. These processes could help to evaluate effect of mismanaged plastic waste (MPW) and point sources (tyres, personal care products, dust, and laundry) on spatio-temporal dynamics of macro- and micro-plastics there. The model showed simulated hydrologic cycle was generally in good agreement with observed one. In contrast, simulated value of annual-averaged nutrient transports was overestimated in comparison with observed value averaged over non-flood periods. Sensitivity analysis of micro-plastic transport to various factors also implied effects of degradation would not be negligible under some conditions. Generally, large amounts of plastic flowed out of some limited rivers (Tone, Kiso, Yodo, and Ara Rivers) with a large proportion of macro-plastic flux in comparison with micro-plastic flux. Further, scenario analysis quantified the total plastic flux varied according to efficiency of micro-plastic removal in wastewater treatment plants (WWTP) and density of plastic, and was estimated as within the range 1,100 – 3,500 ton/yr, relatively similar to that of existing values. It was also clarified only a limited proportion of plastics discharged onto land flow out into the ocean intensively during rainfall seasons. These results help to quantify impacts of plastic waste on biosphere, and may aid development of solutions and measures to reduce plastic input to the ocean.

Effects of elevated temperature and abnormal precipitation on soil carbon and nitrogen dynamics in a Pinus densiflora forest

Forests have the largest terrestrial nutrient pools. The loss of soil carbon and nitrogen in forests under ongoing climate warming is subject to severe environmental degradation. To mitigate the negative effects of global warming on soil carbon and nitrogen in forest, it is important to obtain a better understanding of how elevated temperature and altered precipitation variability impact soil nutrient dynamics. To explore such interactions, we coupled an eco-hydrological model (Multi-Layer Canopy model, MLCan) with a biogeochemical model and applied the combined model to Pinus densiflora forest in Gwangneung Experimental Forest, South Korea, from 2004 to 2020. Our results showed that there was a time lag of 4 years to trigger soil organic carbon losses under the elevated temperature of +1.11°C during 2014–2020 compared to 2010–2013. A temperature rise over a prolonged period increased microbial biomass and activity, stimulating soil organic carbon decomposition. The combination of soil nitrate accumulation and exceptional but expected delay in heavy precipitation seasons of 2 months led to nitrate leaching four times higher than the average at 1 m depth in 2010. Reduced evapotranspiration and heavy precipitation during early fall caused intense subsurface water flux, resulting in a great increase in the risk of nitrate leaching. Our results highlight that the impacts of global warming on soil carbon decompositions has a time lag of 4 years and changes in precipitation characteristics will lead to excessive nitrate loss in P. densiflora forests under climate change.

Subsurface Lateral Flows Buffer Riparian Water Stress Against Snow Drought

AbstractIn the Sierra Nevada, CA, the Mediterranean climate exposes montane forests to water stress during the summer drought. Normally, spring snowmelt alleviates summer water stress, especially in riparian ecosystems that receive subsurface lateral inputs from groundwater. However, snow drought could potentially eliminate these beneficial effects. This research investigates how subsurface lateral redistribution mediates hillslope‐scale vegetation responses to snow drought. We apply a spatially‐distributed ecohydrologic model (Regional Hydro‐Ecologic Simulation System (RHESSys)) to a snow‐dominated watershed in the Sierra Nevada. We incorporate observed sap flow data along a hillslope to estimate relative differences in water stress for upslope and riparian sites, and constrain RHESSys drainage parameter uncertainty. Our model results show that subsurface lateral inputs buffer riparian water stress against snow drought. For all drought types, both upslope and riparian sites experience substantial losses of net primary productivity (NPP), and on average upslope sites are more adversely affected (upslope loss of NPP = 45% vs. riparian = 28%). Dry droughts from a lack of rain or snow induce substantial loss of biomass for upslope and riparian trees because of low annual precipitation, but a small snowpack retained during cold, dry years slightly alleviates these effects and delays water stress by 2 weeks in riparian areas and 3 weeks upslope. While riparian forests are often buffered against drought stress, our study also shows that riparian forests can suffer from water stress. We found 21% of drought scenarios where riparian trees experience greater water stress than upslope trees that were mostly associated with wet and warm snow droughts.

Multisource remote sensing data facilitate ecohydrological simulations without runoff calibration

AbstractObserved runoff is typically the only variable applied to calibrate ecohydrological models, which can simulate runoff well but cannot guarantee reliable reproduction of other hydrological components (e.g., evapotranspiration (ET) and total terrestrial water storage change (TWSC)). This study explores the potential of estimating hydrological components (runoff, ET, TWSC, groundwater, and root‐zone water storage.) using a conceptual model driven and calibrated by multisource remote sensing data only. The performances of the model were evaluated in 13 catchments with different geological, climatic and vegetation conditions. Results show that the model was encouraging in simulating monthly runoff (median KGE, 0.71; RMSE, 19.4 mm/mon), ET (median KGE, 0.86; RMSE, 9.0 mm/mon), and TWSC (median KGE, 0.58; RMSE, 26.6 mm/mon). The good positive correlation between root‐zone water storage and gross primary productivity also indicates the effectiveness of the model in simulating root‐zone water storage. This study offers new prospects for estimating key ecohydrological components precisely, especially in catchments that are difficult to monitor (e.g., karst regions) and catchments with limited observation data (e.g., ungauged regions).

Do Model Results Vary under Different Routing Algorithms Based on a Distributed Ecohydrological Model?

Abstract Although several flow routing (FR) algorithms are developed for hydrological modeling, it is still uncertain how the selection of algorithms may affect model results. This study aims to explore the similarity and dissimilarity in model results among different FR algorithms characterized by single flow direction (SD) and multiple flow direction (MD). The Coupled Hydro-Ecological Simulation System (CHESS) was incorporated with six different FR algorithms (D8, D∞, MD∞, MD8, MFD-md, and RMD∞) and then applied for modeling ecohydrological processes for a semiarid mountainous watershed in the western United States during 1991–2012. Comparisons were made between the model results at the catchment and the grid scale. After slightly adjusting one of the most sensitive soil parameters, all algorithms behave similarly in simulating stream hydrographs. When averaged for the watershed, the modeled ecohydrological variables mostly do not differ significantly (<5%) among the six FR algorithms. Nevertheless, the simulated ecohydrological variables are spatially more autocorrelated under the more dispersive MD algorithms. In addition, there exist significant (>5%) cell-level differences in modeled soil moisture among different FR algorithms, with propagated influences on the simulated evapotranspiration and vegetation growth variables. In hillslopes, the cell-level differences in model results tend to increase significantly as the flows move to the streams. Overall, this study proves that the watershed-level differences in model results among FR algorithms are low after model calibration, while significant differences still occur at the cell level. Thus, observational data are essential for testing which routing algorithm captures better the reality of local ecohydrological processes. Significance Statement The consideration of flow routing is essential for accurately simulating land surface ecohydrological processes. However, less is known about how the selection of flow routing algorithms may affect the model results. Based on model experiments, we found that the model results under different algorithms do not significantly differ from each other when averaged for the watershed. However, significant differences in model results exist at the individual cell level. These findings are useful for guiding future modeling-related research and also suggest the importance of field studies for testing which routing algorithm can better represent local ecohydrological processes.

A fine spatial resolution estimation scheme for large-scale gross primary productivity (GPP) in mountain ecosystems by integrating an eco-hydrological model with the combination of linear and non-linear downscaling processes

Accurate estimation of mountain vegetation gross primary productivity (GPP) at fine spatial resolutions offers opportunities to better understand mountain ecosystems’ feedback to the global climate system. Eco-hydrological models have great advantages in simulating mountain vegetation photosynthesis, but their large-scale applications remain challenging at fine spatial resolutions due to the computing resources. In this work, a scheme by integrating an eco-hydrological model called Boreal Ecosystem Productivity Simulator-TerrainLab (BTL) with the linear and non-linear downscaling processes, was developed to obtain large-scale mountain vegetation GPP at the 30 m resolution over four watersheds. Firstly, two coarse spatial resolution GPP were simulated by BTL at 480 m and 120 m. Then, the 30 m resolution GPP was estimated by a linear downscaling process modelled at 120 m and a non-linear downscaling process modelled from 480 m to 120 m. The 30 m resolution BTL-simulated GPP was served as reference for evaluation. Results showed that the Root-Mean-Square-Error (RMSE) after downscaling was decreased by 110 gCm-2year−1 compared to the 120 m resolution BTL-simulated GPP (500 gCm−2 year−1) at the 30 m resolution, highlighting the effectiveness of the proposed scheme in recovering the topographic variations of mountain vegetation GPP at fine spatial resolutions. Compared to the 120 m resolution BTL-simulated GPP (351 gCm−2 year−1), RMSE after downscaling was decreased by 156 gCm−2 year−1 at the 120 m resolution, indicating that the proposed scheme is feasible in correcting GPP errors at coarse spatial resolutions. More specifically, the non-linear downscaling process was observed to effectively improve GPP estimates after linear downscaling, suggesting that the spatial scaling errors in coarse estimates should be considered in the downscaling process. Our study indicates that the scheme that runs eco-hydrological models at coarse resolutions and then downscales them by surface heterogeneity is a practical approach for obtaining large-scale mountain vegetation GPP at fine spatial resolutions.

Climate and management impacts on the spatiotemporal dynamics of water-carbon fluxes in the North China Plain

Evapotranspiration (ET) and gross primary production (GPP) over agroecosystems could be noticeably altered by climate change and human activities. A better understanding of the impacts on water-carbon interactions and the underlying mechanisms, are crucial to improve water use efficiency (WUE). Comparing to 23 site-years of observations, regional ET dataset and statistical yields, the Remote Sensing-based cropland Ecohydrological Model (ReSEM) was validated to estimate the spatiotemporal dynamics of ET, GPP and WUE for dryland agroecosystems in the North China Plain (NCP) from 2001 to 2018. Spatially, the distributions of mean annual ET, GPP and WUE were comparable which changed obviously in different climatic conditions while varied slightly between various irrigation areas. The significantly increased WUE occurred in 38.6 % cropland, mainly located in the humid south regions with less irrigation requirement and the central sub-humid areas along the Yellow River with access to surface irrigation. The averaged increasing trend of WUE in the heavily irrigated semi-arid areas was relatively low. The temporal dynamic of regional mean WUE indicated a significantly increased rate of 0.026 gC kg−1H2O per year during 2001–2018. The spatiotemporal trends of WUE were mainly resulted from the significantly increased GPP rather than ET. The experimental simulations demonstrated that agricultural management dominated the interannual trend of WUE, whose relative contribution (79.5 %) was obviously larger than that of air CO2 concentration (40.2 %) and climate variable change (−19.7 %). Besides, the effects of agricultural management on WUE were further divided based on the classified six cropping systems, 82.4 % of which was attributed to the management of winter wheat-summer maize rotation system. This study sheds light on the improvement of WUE for dryland agroecosystem under changing environments and highlights the dominant impact of agricultural management.

A guideline for spatio‐temporal consistency in water quality modelling in rural areas

A guideline for spatio‐temporal consistency in water quality modelling in rural areas

Eco-hydrological modelling of channel network dynamics-part 2: application to metapopulation dynamics.

Temporal variations in the configuration of the flowing portion of stream networks are observed in the large majority of rivers worldwide. However, the ecological implications of river network expansions/retractions remain poorly understood, owing to the lack of computationally efficient modelling tools conceived for the long-term simulation of river network dynamics. Here, we couple a stochastic approach for the simulation of channel network expansion and retraction (described in a companion paper) with a dynamic version of a stochastic occupancy metapopulation model. The coupled eco-hydrological model is used to analyse the impact of pulsing river networks on species persistence under different hydroclimatic scenarios. Our results unveil the existence of a climate-dependent detrimental effect of network dynamics on species spread and persistence. This effect is enhanced by dry climates, where flashy expansions and retractions of the flowing channels induce metapopulation extinction. Survival probabilities are particularly reduced in settings where the spatial heterogeneity of network connectivity is pronounced. The analysis indicates that accounting for the temporal variability of the flowing river network and its connectivity is a fundamental prerequisite for analysing in-stream metapopulation dynamics.

Eco-hydrological modelling of channel network dynamics-part 1: stochastic simulation of active stream expansion and retraction.

Dynamic changes in the active portion of stream networks represent a phenomenon common to diverse climates and geologic settings. However, mechanistically describing these processes at the relevant spatiotemporal scales without huge computational burdens remains challenging. Here, we present a novel stochastic framework for the effective simulation of channel network dynamics capitalizing on the concept of 'hierarchical structuring of temporary streams'-a general principle to identify the activation/deactivation order of network nodes. The framework allows the long-term description of event-based changes of the river network configuration starting from widely available climatic data (mainly rainfall and evapotranspiration). Our results indicate that climate strongly controls temporal variations of the active length, influencing not only the preferential configuration of the active channels but also the speed of network retraction during drying. Moreover, we observed that-while the statistics of wet length are mainly dictated by the underlying climatic conditions-the spatial patterns of active reaches and the size of the largest connected patch of the network are strongly controlled by the spatial correlation of local persistency. The proposed framework provides a robust mathematical set-up for analysing the multi-faceted ecological legacies of channel network dynamics, as discussed in a companion paper.

Linking Critical Zone With Watershed Science: The Example of the Heihe River Basin

AbstractWatersheds are the basic unit of Earth's terrestrial systems and are therefore ideal units for the study of critical zones (CZs). However, grand challenges remain regarding the observation, modeling, and management of CZs and watershed systems. We synthesize the progress and breakthroughs associated with watershed science and CZ research in the Heihe River basin (HRB), a large‐scale endorheic river basin with unique mountain cryosphere‐oasis‐desert landscapes and prominent human‐nature competition for water resources. The HRB observation system consists of mountain cryosphere, agricultural oasis, and natural oasis observatories and is promoted by large‐scale comprehensive experiments to achieve multiscale observations. A watershed system model that couples ecohydrological models with socioeconomic models is developed to investigate the complex interactions among water, ecology, and socioeconomics in the HRB. The model is embedded in a decision support system to bridge science and decision‐making and to better serve river basin sustainability. Significant progress and breakthroughs have been made in CZ and watershed process research (e.g., cryospheric hydrological processes, ecological and hydrological interactions, and surface‐groundwater interactions) in the HRB. Nevertheless, observation and modeling of geochemical and geomorphological processes in the CZ have not been well addressed in integrated watershed studies of the HRB. In the future, new observation technologies, agent‐based models, machine learning, and data assimilation will benefit both watershed science and CZ science and help to address complexity and dynamics in the CZ at the river basin scale. Overall, the HRB has successfully demonstrated how an experimental river basin can link CZ science with watershed science.

Evolution of Wet and Dry Spells Based on Original and Corrected Precipitation Data in Southwest China, 1961–2019

Gauge-measured precipitation data have long been recognized to underestimate actual precipitation due to wind-induced error, trace precipitation, and wetting loss, which affects the spatial and temporal characteristics of precipitation. In this study, we examined spatial and temporal differences in wet and dry spell indices based on original (Po) and corrected (Pc) precipitation data and their correlations with large-scale circulation indices (LSCIs) in Southwest China during 1961–2019. The main conclusions were: (1) Pc-based trends in wet/dry spell indices were generally more pronounced than Po-based. Specifically, when Pc-based, more stations had significant changes in the MWS, MLWS, MPWS, PWS95, FWW, FDW, MDS, MLDS, NLDS, and DDS95 indices, while fewer had significant changes in the NWS, NDS, FDD, and FWD indices. (2) Spearman’s results showed that more LSCIs were significantly related to the Pc-based wet/dry spell indices than Po-based. Po-based and Pc-based MWS, Po-based MDS, and Pc-based NLDS were significantly related to the most LSCIs. Therefore, taking them as examples, wavelet transform coherence (WTC) and partial wavelet coherence (PWC) were used to explore the coherence with LSCIs. WTC results showed South Asian Summer Monsoon Index (SASMI) + Po-based MWS, Arctic Oscillation (AO) + Po-based MDS, SASMI + Pc-based MWS, Asia Polar Vortex Intensity Index (APVI) + Pc-based NLDS exhibited the most obvious periodic resonance with main resonance periods of 2.13~7.8 year, 2.19~10.41 year, 2.13~12.13 year, 2.75~18.56 year, respectively. Since WTC may arbitrarily ignore the interaction between LSCIs, PWC is adopted for further analysis. PWC results showed the coherence of AO +Po-based MDS significantly increased after eliminating the Nino Eastern Pacific index (NEP) influence, with the main resonance period of 6.56~18.56 year. This study clearly demonstrated that corrected precipitation data should be used to improve the accuracy of drought assessments, climate models, eco-hydrological models, etc.

Spatial Variation in Catchment Response to Climate Change Depends on Lateral Moisture Transport and Nutrient Dynamics

AbstractFuture shifts in rainfall, temperature and carbon dioxide (CO2) will impact hydrologic and ecosystem behavior. These changes are expected to vary in space because water and nutrient availability vary with terrain and soil properties, with feedbacks on vegetation and canopy adjustment. However, within‐basin patterns and spatial dependencies of ecohydrologic dynamics have often been ignored in future scenario modeling. We used a distributed process‐based ecohydrologic model, the Regional Hydro‐Ecological Simulation System, as a virtual catchment to examine spatial and temporal variability in climate change response. We found spatial heterogeneity in Leaf Area Index, transpiration and soil saturation trends, with some scenarios even showing opposite trends in different locations. For example, in a drying scenario, decreased vegetation productivity in water‐limited upslope areas enhanced downslope nutrient subsidies so that productivity increased in the nutrient‐limited riparian zone. In scenarios with both warming and rising CO2, amplifying feedbacks between mineralization, vegetation water use efficiency and litter fall led to large increases in growth that were often strongest in the riparian area (depending on the coincident rainfall change). Modeled transpiration trends were determined by the competing effects of vegetation growth and changing water use efficiency. Overall, the riparian zone experienced substantially different (and even opposing) ecohydrologic trends compared to the rest of the catchment, which is important because productive riparian areas often contribute a disproportionate amount of vegetation growth, transpiration and nutrient consumption to catchment totals. Models that are spatially lumped, lack key ecosystem‐driving dynamics, or ignore lateral transport could misrepresent the complex ecohydrologic changes catchments could experience in the future.

Evolution of the freshwater provisioning services under climate change and vegetation restoration influences

• Freshwater provisioning decreased in the Yellow river basin during last 57 years. • Increased annual precipitation significantly improved the freshwater provisioning. • Freshwater provisioning decreased impacting by vegetation restoration after 1999. • Freshwater provisioning service negatively impacted by the raised slope. The freshwater provisioning ecosystem services are important and complicatedly affected by climate change and human activities. The well-known Grain for Green Program (GGP) implemented in the Yellow River Basin (YRB) of China, greatly modify the flow patterns and result cascading effects on the freshwater provisioning services of watershed ecosystem. Studies about the impacts of climate and land use changes on streamflow increased rapidly in recent years; however, the evolution characteristic of the freshwater provisioning services under climate change and vegetation restoration is poorly understood. Based on an index-based ecosystem service approach, the annual freshwater provisioning index (FWPI) was calculated and evolution of the freshwater provisioning services were analyzed from 1958 to 2014 for nine watersheds in the YRB. According to a coupled ecohydrological model (CLM-GBHM) developed in the YRB, two vegetation scenarios consisting of fixed leaf area index (LAI) in 1982 and remote-sensed LAI among 1982–2014were established and the annual FWPI under both scenarios were simulated. The respective influence of vegetation restoration and climate on the freshwater provisioning services were finally quantitatively analyzed. The results show that the annual FWPI had a general decrease in most of watersheds in the past 57 years. The increased precipitation during 2000–2014 significantly improved the freshwater provisioning services by 0.8 %–21.3 % among 9 watersheds in comparison with those during 1980–1999, considering the respective impact of climate change. The restored vegetation after the GGP carried out since 1999 had a negative influence on the freshwater provisioning services in the YRB. The mean annual FWPI obviously reduced by −11.9 % and −3.6 % in the upper YRB and the entire basin, respectively, and it reduced by −2.4 %∼−5.8 % in five tributary watersheds during 2000–2014. A significant positive correlation between the mean annual FWPI(S1-S2) which denoting the difference between FWPI under two vegetation scenarios (S1, S2), and the average slope was observed (R 2 = 0.52 and p < 0.05), indicating the negative effect of the raised slope on the freshwater provisioning services. Above results suggest that the precipitation is one critical climate factor of enhancing the freshwater provisioning services, whereas the negative influence of the vegetation restoration and slope changes on the freshwater provisioning should be considered when implementing the GGP for enhancing other hydrological services such as soil erosion control and the flood regulation in different river basins. Results from this study would provide scientific insights in enhancing ecology protection and sustainable utilization of water resources of watershed ecosystems..

Exacerbated drought accelerates catastrophic transitions of groundwater-dependent ecosystems in arid endorheic basins

• Two Haloxylon species exhibited distinct water use strategies but analogous bistable transitions. • Drought accelerates catastrophic shifts in both Haloxylon ecosystems by reducing resilience. • Natural and anthropogenic forcings are aggravating drought in groundwater-dependent ecosystems. • Drought adaptation strategies for such ecosystems must account for maintaining resilience. Drought has become a major threat to regional sustainable development in drylands. Ecological drought, emphasizing the process of drought impacts on ecosystems in coupled human-natural systems, has been posing large risks to the stability of groundwater-dependent ecosystems (GDEs) in drylands. Yet, the interconnected avenues via which ecological drought drives vegetation transition, ecological resilience and ecosystem services in GDEs with species-specific traits remain elusive, especially in arid endorheic basins. Here, we combine comprehensive field measurements derived from representative groundwater depth transects in Central Asia and simulations obtained from the stochastic eco-hydrological models and the Langevin approach, we find that two groundwater-dependent species, the salt-tolerant Haloxylon ammodendron and salt-sensitive Haloxylon persicum , exhibit contrasting water use strategies being driven by variations in eco-physiological traits and environmental regimes. Nonetheless, both the low-resilient H. ammodendron and high-resilient H. persicum vegetation tend to show bistable transition corresponding to vegetated and bare soils under drought stress with stochastic noises and time delays. Alarmingly, ecological drought is accelerating catastrophic transitions in both Haloxylon ecosystems induced by diminishing ecological flows, depleting soil moisture, and aggravating salinization, together with climate forcing. In particular, exacerbated drought stress reduces ecological resilience, enhances the likelihood of catastrophic shifts, and reduces ecosystem services of GDEs in arid endorheic basins. Our results highlight that ecological drought adaptation strategies must account for resilience maintenance by balancing water scarcity, water overuse, and water/soil quality to avoid accelerating regime shifts in dryland ecosystems.

Climate Change Impacts on the Water Resources and Vegetation Dynamics of a Forested Sardinian Basin through a Distributed Ecohydrological Model

Climate change is impacting Mediterranean basins, bringing warmer climate conditions. The Marganai forest is a natural forest protected under the European Site of Community Importance (Natura 2000), located in Sardinia, an island in the western Mediterranean basin, which is part of the Fluminimaggiore basin. Recent droughts have strained the forest′s resilience. A long-term hydrological database collected from 1922 to 2021 shows that the Sardinian forested basin has been affected by climate change since the middle of the last century, associated with a decrease in winter precipitation and annual runoff, reduced by half in the last century, and an increase of ~1 °C in the mean annual air temperature. A simplified model that couples a hydrological model and a vegetation dynamics model for long-term ecohydrological predictions in water-limited basins is proposed. The model well predicted almost one century of runoff observations. Trees have suffered from the recent warmer climate conditions, with a tree leaf area index (LAI) decreasing systematically due to the air temperature and a vapor pressure deficit (VPD) rise at a rate of 0.1 hPa per decade. Future climate scenarios of the HadGEM2-AO climate model are predicting even warmer conditions in the Sardinian forested basin, with less annual precipitation and higher air temperatures and VPD. Using these climate scenarios, we predicted a further decrease in runoff and tree transpiration and LAI in the basin, with a reduction of tree LAI by half in the next century. Although the annual runoff decreases drastically in the worst scenarios (up to 26%), runoff extremes will increase in severity, outlining future scenarios that are drier and warmer but, at the same time, with an increased flood frequency. The future climate conditions undermine the forest’s sustainability and need to be properly considered in water resources and forest management plans.

Evaluating satellite-derived soil moisture data for improving the internal consistency of process-based ecohydrological modelling

Soil moisture is a key variable controlling the energy and water balance at the land surface and satellite-derived soil moisture (SDSM) products can therefore be helpful to constrain parameters of (eco)hydrological models. Due to coarse resolution of many SDSM products (>25 km), previous studies mostly focused on large catchments (>500 km2). However, recent developments in soil moisture remote sensing resulted in SDSM products with improved spatio-temporal resolution, which are potentially better suited for model calibration in small to meso-scale catchments. This study therefore aims at assessing the value of three recent SDSM products (SMAPL3E, SCATSAR and ASCAT DIREX SWI) with high spatio-temporal resolution (spatial sampling 0.5–9 km; temporal resolution 1–3 d) for the calibration of the process-based ecohydrological model EcH2O in a 66-km2 catchment in NE Germany.Satellite-derived soil water index (SWI) data agreed well with in-situ soil moisture observations (Pearson correlation coefficient: 0.67–0.86), with a slightly better performance for SMAPL3E than for the other two products (SCATSAR, ASCAT DIREX SWI). Calibrating the ecohydrological model EcH2O to SWI data based on SMAPL3E improved the dynamics of simulated soil moisture (increase of Pearson correlation coefficient by 0.03), while model performance for streamflow slightly deteriorated (decrease of Nash-Sutcliffe efficiency by 0.02). Including volumetric soil moisture data based on in-situ data or SDSM scaled to in-situ data in the model calibration was necessary to further improve the model with respect to absolute soil moisture levels (increase of Nash-Sutcliffe efficiency for scaled soil moisture from 0.23–0.25 to 0.56–0.59). Comparing spatial patterns of simulated soil moisture and SDSM revealed shortcomings of the simulated and the SDSM data. Simulated soil moisture spatial patterns are influenced by artefacts of the interpolated precipitation patterns, while spatial patterns of SDSM seem too strongly damped. Based on this study, the following recommendations may be derived for practitioners who consider including soil moisture data for model calibration: 1) integrating SDSM in model calibration is beneficial for improving model internal consistency; 2) where available, in-situ soil moisture data should be included in order to better constrain simulated absolute soil moisture levels; 3) at the scale of small to meso-scale catchments (∼100 km2), the temporal dynamics of the SDSM products evaluated in this study are likely more helpful for model calibration than their spatial patterns.

Snow-melt water: An important water source for Picea crassifolia in Qilian Mountains

The tall mountains on the mainland are not only important for ecological barriers but also important for water-source bases. Forests play a key role in maintaining tall mountains' ecological and hydrological functions. Therefore, it is important to study the water sources to ensure the existence and growth of forests. We sampled precipitation, snow-melt water, soil, and Picea crassifolia at different altitudes in the Qilian Mountain and analyzed hydrogen and oxygen stable isotopes. The study showed that the snow-melt water contribution to Picea crassifolia water persisted throughout the growing season, and was detectable even in the late growing season, with snow-melt water accounting for 33% of Picea crassifolia water sources. The hydrogen and oxygen stable isotopes of Picea crassifolia xylem water showed that the plants mainly used snow-melt water in the dry season and rainfall in the rainy season. The snow-melt water greatly reduces the impact of spring and summer droughts on forests in the high mountain system in the mainland. Our findings mean that the recent rainfall changes reconstructed by hydrogen and oxygen stable isotopes of Picea crassifolia tree ring can not accurately reflect the water sources in the plant growing season. At the same time, the eco-hydrological model needs to be reconsidered based on the assumption of the rapid transformation of precipitation-soil water-plant water.

Improvement of evapotranspiration simulation in a physically based ecohydrological model for the groundwater–soil–plant–atmosphere continuum

Accurate quantification of terrestrial evapotranspiration (ET) is essential to understanding the interaction between land and atmosphere, as well as the feedback response of vegetation dynamics. In our previous work, a physically based ecohydrological model called the simple terrestrial hydrosphere (SiTH) model was developed to estimate ET and the other ET-related variables based on the groundwater–soil–plant–atmosphere continuum (GSPAC). However, the SiTH model (SiTHv1) still has some deficiencies in the model structure and parameters, which can result in potential uncertainty in the estimation of terrestrial ET. In this study, we aimed to address these limitations by developing a new version of the SiTH model (SiTHv2). The main modifications of the SiTHv2 model include: (1) the vegetation moisture constraint module is updated with vegetation optical depth observations; (2) the critical model parameters associated with root distribution are constrained using flux observations; (3) the soil module is extended to a three-layer module with 5 m of total depth; (4) an irrigation input water strategy is applied in the cropland areas; and (5) the latest ERA5-Land reanalysis data with a finer spatial resolution are used as the meteorological forcing data. The estimated ET of the SiTHv2 model was validated/compared at multiple scales (i.e., site/plot, basin, and global) with flux data, basin water balance data, and other mainstream global ET products, respectively. The results demonstrate that the SiTHv2 model performs better than the SiTHv1 model, with an improvement in the overall model root-mean-square error of 0.66 mm day−1 (plot scale) and 98.58 mm year−1 (basin scale), representing 27% and 22% improvements over the SiTHv1 model in the same circumstances, respectively. In addition, the performance of the SiTHv2 model ranks well when compared to the existing terrestrial ET models and products. The improvements to the SiTH model should allow improved estimation of terrestrial ET and provide support to potential studies in water transfer within the GSPAC.