Ecohydrological Model Research Articles

Prioritizing conservation practice locations for effective water quality improvement using the Agricultural Conservation Planning Framework (ACPF) and the Soil and Water Assessment Tool (SWAT)

Adopting the right agricultural conservation practices (CPs) at the right place is critical to maximizing water quality benefits. The Agricultural Conservation Planning Framework (ACPF) tool identifies all potential CPs and their locations within a target watershed based on the landscape characteristics. The ACPF tool suggests hundreds of CP locations in a watershed, making it challenging to prioritize the CP implementation. We develop and demonstrate an efficient approach using a multicriteria ranking technique for prioritizing the CPs suggested by ACPF, considering pollution hotspots and CP cost and effectiveness to support decision-makers. The pollution hotspots are estimated with simulations from an ecohydrological model, the Soil and Water Assessment Tool (SWAT). The CP cost and effectiveness were estimated from CP installation costs and pollutant reduction efficiencies from the literature. The methodology was demonstrated in the Conewago and Mahantango watersheds in Pennsylvania, US, for grassed waterways (GWWs) and water and sediment control basins (WASCOBs) for sediment load reduction. Multiple CP prioritization scenarios were evaluated with individual and combined criteria for reductions in total sediment load, yield (loading per area), and cost. In single criterion-based prioritization, the cost-based and load-based prioritization indicated cost efficiency and fewer CPs, respectively. The yield-based approach correctly prioritized CPs in sediment loss hotspots in the case study watersheds; however, it needed more CPs to meet the target reductions. The multicriteria approach efficiently prioritized CPs in sediment hotspots to meet target reductions. Although this approach was demonstrated in two case study watersheds and for sediment loss reduction, it is applicable for any location or pollutant for which similar input variables can be provided, thereby providing a means for prioritizing the results of ACPF for implementation in the Mid-Atlantic region of the US.

Improving process-consistency of an ecohydrological model through inclusion of spatial patterns of satellite-derived land surface temperature

Distributed hydrological models can correctly simulate spatial patterns if the model parameters adequately represent the spatial heterogeneity of the basin. However, determining realistic values of these parameters is often difficult. Considering remote sensing-derived land-surface states and fluxes in combination with streamflow observations is a suitable strategy to better constrain parameters and improve process-consistency. For ecohydrological modelling, an accurate representation of vegetation characteristics is important to capture the vegetation response to varying moisture availability. Land surface temperature (Ts) may serve as a valuable diagnostic because it is pivotal to the surface energy and water balance, and conveys information about ecosystem stress and water use. This study aims at assessing the benefits of integrating spatial patterns of Landsat-derived Ts into calibration of a process-based ecohydrological model to improve process representation of catchment-scale energy fluxes and vegetation response to moisture deficits. We explicitly analyze the trade-off between streamflow and Ts performance, and explore the value of adding an increasing number of Ts images in the calibration process. The study is performed in a mixed land cover catchment in Germany using the ecohydrological model EcH2O. Our results demonstrate the value of satellite-derived Ts data for reducing uncertainties of energy-balance related vegetation parameters, which are hardly constrained in streamflow-only calibration. Including satellite-derived Ts for model calibration reduced the mean absolute error of spatial anomalies in simulated Ts patterns by 15 % with negligible deterioration of streamflow performance. Inclusion of spatial Ts patterns improved capturing the differences in Ts between vegetation types, and affected simulated evapotranspiration fluxes. Improvements in simulated Ts could already be achieved by including only few (4–5) images of satellite-derived Ts in calibration. Based on our results, we advocate a wider use of satellite-based Ts data for multivariate calibration to improve model parameter identifiability and process consistency of highly parameterised, process-based distributed ecohydrological models, especially when capturing hydrology-vegetation interactions is crucial.

Characterizing the effect of scaling errors on the spatial downscaling of mountain vegetation gross primary productivity

ABSTRACT High spatial resolution Gross Primary Productivity (GPP) estimation makes it feasible to better understand the spatial heterogeneity of mountain vegetation photosynthesis. Spatial downscaling is a practical approach to obtaining high resolution GPP estimates, whereas there is almost no attention given to the downscaled biases resulted from the widely reported scaling errors in medium or coarse resolution GPP estimates. To fill the above gap, this study adopted an eco-hydrological model to obtain 960 m resolution distributed GPP estimates (not including scaling errors) and lumped GPP estimates (including scaling errors) over four mountainous watersheds. Then, the distributed and lumped estimates were downscaled from 960 m to 30 m, respectively. Finally, the contribution of reducing scaling errors was characterized by the agreement index (d), BIAS and Root-Mean-Square-Error (RMSE) values between downscaled GPP and referenced GPP (directly generated at the spatial resolution of 30 m). Results showed that a large difference existed between lumped and distributed GPP, with d, BIAS, and RMSE of 0.79, 212, and 334 gC m−2 year−1, demonstrating that the scaling errors should be given enough attention to current coarse resolution GPP estimates. Before considering the scaling errors, large uncertainties were observed in the GPP downscaled from lumped values, with d, BIAS, and RMSE of 0.68, 220, and 480 gC m−2 year−1. After considering the scaling errors, a significant improvement was achieved in the GPP downscaled from distributed values, with an increased d value of 0.81, a decreased BIAS value of 10 gC m−2 year−1, and a decreased RMSE value of 388 gC m−2 year−1, indicating that reducing the medium or coarse resolution scaling errors would effectively improve the spatial downscaling of mountain vegetation GPP. Our study highlights the effect of scaling errors on the spatial downscaling of mountain vegetation productivity, which should be given more attention in the future carbon modeling.

Confluence simulations based on dynamic channel parameters in the grasslands lacking historical measurements

Technology has greatly promoted ecohydrological model development, but runoff generation and confluence simulations have fallen behind in ecohydrological model development due to limited innovations. To fully understand ecohydrological processes and accurately describe the coupling between ecological and hydrological processes, a distributed ecohydrological model was constructed by integrating multisource information into distributed dynamic process model (DDPM). We mainly describe runoff generation and convergence modules. Based on the improved HBV model and degree-3 h factor method, runoff generation and snow routines were constructed for semiarid grassland basins. In view of meandering and variable steppe river channels and steep hydrological relief characteristics, a confluence module was constructed; the 1-km bend radius equivalent concept was innovatively proposed to unify river channel bend degrees. The daily runoff simulation validation results obtained using two datasets were R2 = 0.947 and 0.932, NSE = 0.945 and 0.905, KGE = 0.971 and 0.680. In the 3-hour flood simulations, the DDPM could better restore small long-distance water flows than the confluence method that did not consider actual river lengths or bend energy losses; the DDPM more accurately simulated the flood peak arrival time than the confluence method that did not consider overflow. The simulated mainstream overflow frequency increased by 0.84/10 years, and significant interaction periods of 10 to 13 years occurred with local precipitation, ecological status, and global climate change. An approximately 2-year lag occurred in the global climate change response. This study helps us further understand and reveal the ecohydrological processes of steppe rivers in semiarid regions.

Aerodynamic effects cause higher forest evapotranspiration and water yield reductions after wildfires in tall forests.

Wildfires are increasing in frequency, intensity, and extent globally due to climate change and they can alter forest composition, structure, and function. The destruction and subsequent regrowth of young vegetation can modify the ecosystem evapotranspiration and downstream water availability. However, the response of forest recovery on hydrology is not well known with even the sign of evapotranspiration and water yield changes following forest fires being uncertain across the globe. Here, we quantify the effects of forest regrowth after catastrophic wildfires on evapotranspiration and runoff in the world's tallest angiosperm forest (Eucalyptus regnans) in Australia. We combine eddy covariance measurements including pre- and post-fire periods, mechanistic ecohydrological modeling and then extend the analysis spatially to multiple fires in eucalypt-dominated forests in south-eastern Australia by utilizing remote sensing. We find a fast recovery of evapotranspiration which reaches and exceeds pre-fire values within 2 years after the bushfire, a result confirmed by eddy covariance data, remote sensing, and modeling. Such a fast evapotranspiration recovery is likely generalizable to tall eucalypt forests in south-eastern Australia as shown by remote sensing. Once climate variability is discounted, ecohydrological modeling shows evapotranspiration rates from the recovering forest which reach peak values of +20% evapotranspiration 3 years post-fire. As a result, modeled runoff decreases substantially. Contrary to previous research, we find that the increase in modeled evapotranspiration is largely caused by the aerodynamic effects of a much shorter forest height leading to higher surface temperature, higher humidity gradients and therefore increased transpiration. However, increases in evapotranspiration as well as decreases in runoff caused by the young forest are constrained by energy and water limitations. Our result of an increase in evapotranspiration due to aerodynamic warming in a shorter forest after wildfires could occur in many parts of the world experiencing forest disturbances.

Assessment of climate change impacts for two tributary basins of the Irtysh River in Kazakhstan

Information about the climate change impacts on river discharge of 2 tributary basins of the Irtysh River, the Oba and Ulbi, is important for effective management of the water resources of the Shulba reservoir in Kazakhstan. The main aim of the study was to investigate potential changes in water resource availability in the study basins. To assess the projected changes, the process-based eco-hydrological model SWIM was used under 2 Representative Concentration Pathway (RCP) climate scenarios obtained from the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP). Our results show an increase in mean annual temperature of 6.1°C, an increase in average annual precipitation of 7.5 to 14%, an increase in annual average discharge for the Oba (6 to 8%) and smaller discharge changes (below 5%) for the Ulbi at the end of the century under RCP8.5—a scenario of comparatively high greenhouse gas emissions—compared to the reference period (1981-2010). Seasonal variations are marked by the peak discharge occurring up to a month earlier, a decrease in the duration of snow accumulation and a reduction in discharge during the summer months. The peak discharge period is prolonged in time, and a slight increase in river discharge could be expected from October to December. Possible future changes in climate may have serious impacts on water resources, agriculture and economic development in the case study basins. The results of this study can be extrapolated to other neighboring basins in Kazakhstan with similar climatic and geophysical characteristics.

Changes in Blue/Green Water Partitioning Under Severe Drought

AbstractMuch attention has been given to the disproportionate streamflow deficits (relative to rainfall deficits) experienced by many catchments during the Millennium Drought (1998–2009) in southeastern Australia, along with lack of post‐drought streamflow recovery in some cases. However, mechanisms behind the coupled hydrologic and ecosystem dynamics are poorly understood. We applied a process‐based ecohydrologic model (RHESSys) in a Melbourne water supply catchment to examine changes in ecohydrologic behavior during and after the drought. Our simulations suggested that average transpiration (green water) was maintained under drought despite a substantial (12%) decrease in average rainfall, meaning that the entire rainfall deficit translated to reduced streamflow (blue water). Altered spatial patterns of vegetation behavior across the terrain helped the ecosystem maintain this unexpectedly high green water use. Decreased transpiration upland was compensated by increases in the riparian zone, which was less water limited and therefore able to meet higher water demand during drought. In the post‐drought period, we found greater transpiration and reduced subsurface water storage relative to pre‐drought, suggesting a longer‐term persistence in altered water partitioning. The post‐drought outcome was attributed to a combination of warmer climate and the persisting effects of the drought on nutrient availability. Given the importance of shifting ecohydrologic patterns across space, our results raise concerns for applying lumped conceptual hydrologic models under nonstationary or extreme conditions. Additionally, the processes we identified have important implications for water supply in Australia's second largest city under projected drying.

Nocturnal Water Use Partitioning and Its Environmental and Stomatal Control Mechanism in Caragana korshinskii Kom in a Semi-Arid Region of Northern China

As an important aspect of plant water consumption, nocturnal water use (En) behavior provides reliable information on the effect of plantation carbon and water budgets at stand and regional scales. Therefore, quantifying En and its environmental and stomatal controlling mechanisms is urgent to establish adaptation strategies for plantation management in semiarid regions. With the help of the sap flow technique, our study investigated the seasonal variations in canopy transpiration and canopy conductance in a Caragana korshinskii Kom plantation. Environmental variables were measured concurrently during the growing seasons of 2020 and 2021. The results indicated that the average En values were 0.10 mm d−1 and 0.09 mm d−1, which accounted for 14% and 13% of daily water use, respectively, over two years. The proportions of nocturnal transpiration (Tn) to En were approximately 49.76% and 54.44%, while stem refilling (Re) accounted for 50.24% and 45.56% of En in 2020 and 2021, respectively, indicating that C. korshinskii was able to draw on stored stem water to support transpiration. En was predominantly affected by nocturnal canopy conductance (Gc–n), air temperature (Ta–n) and wind speed (u2-n). In contrast, Gc–n and Ta–n explained the highest variation in Tn and nocturnal vapor pressure (VPDn), and u2-n explained the highest variation in Re. Total effects of the five environmental and stomatal variables explained 50%, 36% and 32% of En, Tn and Re variation, respectively. These findings could enable a better understanding of nocturnal water use dynamics and their allocation patterns in C. korshinskii plantations on the Bashang Plateau. Moreover, our results reveal the water use strategies of artificial shrubs and highlight the importance of incorporating nocturnal water use processes into large-scale ecohydrological models in semiarid regions.

Subsurface structure regulates water storage in the alpine critical zone on the Qinghai-Tibet Plateau

The subsurface critical zone (CZ) structure in alpine regions has a profound influence on water storage that is not well understood due to a lack of available accurate spatiotemporal measurements. This work is to reveal that the organic layer (A), leaching-deposit layer (B), saprolite layer (C) and freeze–thaw processes regulate changes in subsurface liquid water storage (CSWS). We performed in situ field surveys, ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) along an elevation gradient (4221–3205 m) in the Qinghai Lake Basin Critical Zone Observatory (QLBCZO) on the Qinghai-Tibet Plateau. The results showed that the saprolite layer (thickness of 0.84–41.85 m) and the liquid water storage (SWS) increased along the decreasing elevation. The saprolite layer was the main subsurface liquid water storage reservoir, with average value of 595.49 ± 729.87 mm, which occupied 76.10 % of the total water storage of layers A, B and C. The SWS of the saprolite layers increased the most, by 39.41 mm and 45.88 mm in the thawing and nonfreezing periods, respectively, and that of layer B decreased maximally by 52.50 mm in the freezing period. The subsurface layer and elevation had the contribution to SWS at 68.07 % during the nonfreezing period. Comparing other climate and environmental factors, the seasonal frozen thickness (SFT) and precipitation contributed most to CSWS during the thawing and freezing period (27.95 % and 19.87 %), respectively. This study contributes to advancing the mechanistic understanding of the interactions between the subsurface CZ structure and water storage processes and provides high-quality data with which coupled ecohydrological models can be developed.

Modeling the effects of plant uptake dynamics on nitrogen removal of a bioretention system

Bioretention systems are widely used to remove nutrients from urban runoff. Plants play a key role in the nitrogen removal performance of bioretention systems; however, few model studies have focused on the effects of plant uptake dynamics on the performance. In this study, we propose an eco-hydrological model of bioretention systems by coupling plant, hydrological, and nitrogen modules. The eco-hydrological model was verified using observed data on biomass, plant nitrogen uptake, hydrological performance, and effluent nitrogen concentrations of a bioretention system planted with Canna indica L. in Shenzhen, China. The validated model was used to evaluate the effects of seasonal or interannual variation of plant nitrogen uptake on nitrogen removal performance of the bioretention system. The results indicated that (i) The model is able to explicitly describe plant dynamics and nitrogen transformation processes of the system, and the Nash Sutcliffe Efficiency coefficients of biomass, monthly plant nitrogen uptake, and effluent nitrogen concentrations were all greater than 0.6; (ii) The plant nitrogen uptake is sensitive to most parameters in the plant module; The effluent nitrogen concentrations are sensitive to decomposition constant of plant residues (kres) during most months of the year and also sensitive to optimal nitrogen content at the germination (bn1) and optimal nitrogen content at the maturity (bn2) during the months with low influent nitrogen concentrations; and (iii) The seasonal and interannual variations in plant nitrogen uptake significantly affect nitrogen removal efficiencies, especially during rainy seasons. Therefore, the model can consider the influence of plant nitrogen uptake on the long-term nitrogen removal performance of bioretention systems.

Combining resilience and resistance with threat‐based approaches for prioritizing management actions in sagebrush ecosystems

AbstractThe sagebrush biome is a dryland region in the western United States experiencing rapid transformations to novel ecological states. Threat‐based approaches for managing anthropogenic and ecosystem threats have recently become prominent, but successfully mitigating threats depends on the ecological resilience of ecosystems. We used a spatially explicit approach for prioritizing management actions that combined a threat‐based model with models of resilience to disturbance and resistance to annual grass invasion. The threat‐based model assessed geographic patterns in sagebrush ecological integrity (SEI) to identify core sagebrush, growth opportunity, and other rangeland areas. The resilience and resistance model identified ecologically relevant climate and soil water availability indicators from process‐based ecohydrological models. The SEI areas and resilience and resistance indicators were consistent—the resilience and resistance indicators showed generally positive relationships with the SEI areas. They also were complementary—SEI areas provided information on intact sagebrush areas and threats, while resilience and resistance provided information on responses to disturbances and management actions. The SEI index and resilience and resistance indicators provide the basis for prioritizing conservation and restoration actions and determining appropriate strategies. The difficulty and time required to conserve or restore SEI areas increase as threats increases and resilience and resistance decrease.

The effects of leaf traits on litter rainfall interception with consequences for runoff and soil conservation

Abstract During rainfall, plant litter interception regulates overland flow with an impact on water runoff generation and sediment displacement. Besides the rainfall characteristics, the effects of litter mass, thickness, storage and drainage properties on rainfall interception are reasonably well understood. In contrast, less is known about the influence of leaf traits, which we hypothesized to affect interception, soil hydrology and conservation via litter structure assembly. We measured the runoff and soil loss generation as determined by litter layer structural and hydraulic properties of 16 coexisting tropical woody species with wide‐range morphological leaf traits in a rainfall simulator experiment. Our results show that litter produced by coexisting species can differ in precipitation interception, thereby influencing runoff and soil loss. This is because there is important interspecific variation in litter water storage and drainage, which are negatively affected by leaf area (LA). Leaf water repellency positively affected litter water storage. Moreover, LA also negatively affected litter layer density. Litter density, in turn, increased runoff, but decreased soil loss, possibly due to protection against splash erosion. These results can be used to predict the effects of plant traits on the soil water balance and soil integrity protection through ecohydrological interception by the litter layer. The next research steps will be to extend our model to multiple‐species litter layers, and to validate and calibrate our model in different field situations in different ecosystems. Synthesis: We revealed the direct and indirect effects of species leaf size and hydraulic traits on litter rainfall interception, runoff and soil loss. We propose a new litter‐soil ecohydrological model, by using structural equation models, which can be used as a tool to predict ecosystem functioning, and guide management and restoration actions with water and soil conservation targets.

A hydrogeophysical framework to assess infiltration during a simulated ecosystem-scale flooding experiment

This study presents a framework to quantify changes in soil saturation in response to flooding caused by extreme hydrologic perturbation on coastal ecosystems at the interfaces and transition between terrestrial and aquatic systems. Subsurface heterogeneity limits the use of in situ measurements to quantify subsurface flow during flooding due to the spatial discontinuity in the measured data. While geophysical methods, including time-lapse electrical resistivity imaging (ERI), are increasingly used to monitor soil hydrological processes, their abilities to parameterize flow models have been underutilized. This study combines background ERI, ground penetrating radar (GPR), time-lapse ERI, soil characterization, and a numerical flow model developed using an Advanced Terrestrial Simulator (ATS) code to quantify the infiltration pathway and describe the hydrological dynamics during a simulated flooding experiment. We assessed the use of two conceptual models developed using [1] ERI and GPR data that described the stratigraphic distribution, and time-lapse ERI that mapped permeability contrast, and [2] information from a national soil database for capturing changes in saturation. Combining the ERI and GPR results with soil core data revealed the stratigraphic heterogeneity at the site with a silty clay layer from 1 to 2 m between an overlying loamy topsoil and an underlying saturated silty sand. This silty clay layer could restrict deep infiltration. The time-lapse ERI showed up to a 35% decrease in resistivity, which correlated with soil moisture data (R2 value > 0.53) and revealed preferential infiltration zones used to inform the flow model. Numerical simulation results from both the geophysics- and soil database-informed models quantified changes in soil saturation with calculated soil moistures that agreed with field data. The geophysics-informed model captured more of the system’s variability, reflective of shallow subsurface heterogeneities. The framework presented will serve as a precursor for a robust ecohydrological model that can describe the impacts of extreme events induced by climate change on coastal ecosystems.

Sap flux and stable isotopes of water show contrasting tree water uptake strategies in two co‐occurring tropical rainforest tree species

AbstractThe short‐term dynamics of tree water use strategies for neighbouring co‐occurring species are poorly understood. Here, we quantify the high frequency changes in water sources and sap flux patterns of two commonly co‐occurring tropical rainforest tree species: Dendrocnide photinophylla (Kunth; Chew) and Argyrodendron peralatum (F.M. Bailey; Edlin ex J.H. Boas). A combination of continuous sap flux measurements and hourly sampling of xylem water stable isotope composition (δD and δ18O) were used to observe water use strategies during a 24‐h transpiration cycle. Sap flux ranged between 2.82 and 28.50 L day−1, with A. peralatum recording a 67% higher rate than D. photinophylla. For both tree species, sap flux increased with tree size and diurnal sap flux increase resulted in more isotopically enriched xylem water. A Bayesian Mixing Model analysis, which used sampled soil water isotopic composition from five soil depths ranging from of 0 to 1 m, revealed that D. photinophylla primarily used water from very shallow depth or soil surface layer (2–60 cm), while A. peralatum sourced its water mostly from deeper layers (60–100 cm). We propose that these differences in species' water consumption patterns are related to plant water storage capacity and wood anatomical features. This research demonstrates that combining xylem isotope composition and sap flux measurements can help reveal species‐specific water use strategies, which can be beneficial for improved process understanding in ecohydrological modelling.

Assessing land use effects on ecohydrological partitioning in the critical zone through isotope‐aided modelling

AbstractStable water isotopes are naturally occurring conservative tracers that can ‘fingerprint’ water sources and track ecohydrological fluxes across the critical zone (CZ). Parsimonious, tracer‐aided models allow effective quantification of the ecohydrological partitioning of rainfall into different water fluxes. We incorporated stable water isotopes into a one‐dimensional, tracer‐aided model (EcoIsoPlot) to follow the pathway of precipitation through the CZ at a lowland catchment—the long‐term experimental Demnitzer Millcreek Catchment (DMC), Germany—with contrasting vegetation covers (forest, agroforestry, grassland and arable). Precipitation (amount and δ2H), potential evapotranspiration (PET), leaf area index (LAI), air temperature and relative humidity were used as input data for modelling the growing season of 2021. The year had relatively average overall wetness, but a dry, cold spring with snowfall, and an exceptionally large summer storm event (~60 mm precipitation). Multi‐criteria calibration of the model was conducted using depth‐specific soil moisture and soil water δ2H measurements as targets. The novel incorporation of isotopes into model calibration constrained process representation of the estimated water balance with reasonable simulations and uncertainty bounds for water partitioning. Throughout the soil profile, soil moisture dynamics and stable water isotope variations were captured reasonably well. Green water fluxes (evapotranspiration) were highest at the forest site and blue water fluxes (groundwater recharge) highest at the grassland. Comparing simulations with estimated potential evapotranspiration (ET) and measured groundwater table fluctuations added further confidence to the modelling result. Overall, these may suggest a slight underestimation of ET and slight overestimation of recharge, though the results are similar to previous findings. Our study demonstrated the potential of stable water isotope data to enhance relatively simple, transferrable approaches to ecohydrological modelling of water fluxes in the CZ and to help improve model consistency. Such low‐parameterised tracer‐aided models have major potential for evidence‐based applications to aid management and help stakeholder communication.

Simulating drip irrigation in large-scale and high-resolution ecohydrological models: From emitters to the basin

Drip irrigation is deemed as a solution to the water conflict between agricultural and ecological needs in arid regions, but assessing hydrological impacts of drip irrigation remains challenging. This study developed a new approach to simulating drip irrigation at a basin scale, with the configuration of irrigation system explicitly represented and the emitter-scale wetted soil volume directly modeled, and incorporated the approach into HEIFLOW, a fully distributed and physically based ecohydrological model. The improved model, named HEIFLOW-drip, was used to study the potential implementation of drip irrigation in the Zhangye basin in Northwest China. Due to the recycling effect of irrigation return flow, the basin-scale water-saving efficiency (WSE) of drip irrigation fully implemented in the irrigated farmlands is 16.8%, less than half of its field-scale WSE (36.5%). This discrepancy indicates that accounting the water saved in fields may lead to notable overestimation of the basin-wide water saving by drip irrigation in basins with strong surface water-groundwater interactions. If fully implemented, drip irrigation would significantly alter the regional water balance, increasing the stream outflow by approximately 30%, while causing a decline in groundwater level. This tradeoff can be alleviated by tuning the management parameters of drip irrigation, which can achieve a synergistic effect of increasing the streamflow while preventing dramatic groundwater depletion. Another effective strategy is to implement drip irrigation in part of the basin. Given the intricate impacts of drip irrigation on hydrological processes, the determination of the scale and location of drip irrigation should be thought through at the basin level. Further analyses indicate the importance of proper management of the water saved by drip irrigation, which is crucial to prevent the paradox of irrigation efficiency. The findings of this study have great implications for addressing the complex water-food-ecosystem nexus in arid endorheic river basins.

Characterizing Errors Using Satellite Metadata for Eco‐Hydrological Model Calibration

AbstractUnderstanding the origins of errors between model predictions and catchment observations is a critical element in hydrologic model calibration and uncertainty estimation. Difficulties arise because there are a variety of error sources but only one measure of the total residual error between model predictions and catchment observations. One promising approach is to collect extra information a priori to characterize the data error before calibration. We implement here a new model calibration strategy for an ecohydrological model, using the satellite metadata information as a means to inform the model priors, to decompose data error from total residual error. This approach, referred to as Bayesian ecohydrological error model (BEEM), is first examined in a synthetic setting to establish its validity, and then applied to three real catchments across Australia. Results show that (a) BEEM is valid in a synthetic setting, as it can perfectly ascertain the true underlying error; (b) in real catchments the model error is reduced when utilizing the observation error variance as added error contributing to total error variance, while the magnitude of total residual error is more robust when utilizing metadata about the data quality proportionality as the basis for assigning total error variance; (c) BEEM improves model calibration by estimating the model error appropriately and estimating the uncertainty interval more precisely. Overall, our work demonstrates a new approach to collect prior error information in satellite metadata and reveals the potential for fully utilizing metadata about error sources in uncertainty estimation.

High‐resolution in situ stable isotope measurements reveal contrasting atmospheric vapour dynamics above different urban vegetation

AbstractWe monitored stable water isotopes in liquid precipitation and atmospheric water vapour (δv) using in situ cavity ring‐down spectroscopy (CRDS) over a 2 month period in an urban green space area in Berlin, Germany. Our aim was to better understand the origins of atmospheric moisture and its link to water partitioning under contrasting urban vegetation. δv was monitored at multiple heights (0.15, 2 and 10 m) in grassland and forest plots. The isotopic composition of δv above both land uses was highly dynamic and positively correlated with that of rainfall indicating the changing sources of atmospheric moisture. Further, the isotopic composition of δv was similar across most heights of the 10 m profiles and between the two plots indicating high aerodynamic mixing. Only at the surface at ~0.15 m height above the grassland δv showed significant differences, with more enrichment in heavy isotopes indicative of evaporative fractionation especially after rainfall events. Further, disequilibrium between δv and precipitation composition was evident during and right after rainfall events with more positive values (i.e., values of vapour higher than precipitation) in summer and negative values in winter, which probably results from higher evapotranspiration and more convective precipitation events in summer. Our work showed that it is technically feasible to produce continuous, longer‐term data on δv isotope composition in urban areas from in situ monitoring using CRDS, providing new insights into water cycling and partitioning across the critical zone of an urban green space in Central Europe. Such data have the potential to better constrain the isotopic interface between the atmosphere and the land surface and to thus, improve ecohydrological models that can resolve evapotranspiration fluxes.

Ecohydrologic model with satellite-based data for predicting streamflow in ungauged basins

Information on water availability in basins can be crucial for making decisions for effective water resource management in basins. As the operation of hydrometric stations in Korea is mainly focused on flood season and large rivers, most basins have lack or no observed data. Consequently, this complicates water resource planning and management. Remote sensing data is emerging as a powerful alternative to hydrological information in ungauged basins. This study investigated the applicability of Satellite-Remote Sensed Data (SRSD) as a source for model calibration in Prediction in Ungauged Basins (PUB) through modeling. Remote sensed leaf area index (LAI), actual evapotranspiration, and soil moisture data were used. Each SRSD was used alone to calibrate a hydrologic model to predict the daily streamflow for 28 basins in Korea. A vegetation module was added to the existing hydrologic model to use LAI. Among the SRSDs tested, the model calibrated with LAI had the most robust performance, predicting streamflow with acceptable accuracy compared to the traditional calibration based on streamflow. In particular, since the model account for vegetation actively interacting with evapotranspiration and soil moisture in the season of low flow, the LAI-calibrated model showed an advantage in improving the flow prediction performance. Although further research is required to utilize evapotranspiration and soil moisture data, the overall results of the LAI-based calibration were promising for predicting streamflow in ungauged basins where observations are scarce or absent, given that the satellite-derived LAI data were used alone without any preprocessing such as a bias correction. However, the prediction performance of the LAI-calibrated model was found to have a statistically significant relationship with local conditions. Therefore, by evaluating and improving the potential of SRSD in different region and climatic conditions, it is expected that the application of the SRSD-only calibration method can be extended to various ungauged basins.

Photosynthetic capacity, canopy size and rooting depth mediate response to heat and water stress of annual and perennial grain crops

Perennial grain crops are promoted as an alternative to annual staple crops to reduce negative environmental effects of agriculture and support a variety of ecosystem services. While perennial grains have undergone extensive testing, their vulnerability to projected future warmer and drier growing conditions remains unclear. To fill this gap, we compared leaf temperature and gas exchange rates of annual wheat and different perennial wheat ideotypes using a multi-layer process-based eco-hydrological model. The model combines leaf-level gas exchange, optimality principles regulating stomatal conductance, energy balance, radiative and momentum transfer inside the canopy, as well as soil water balance. Wheat ideotypes are parameterized based on an extensive review of field data. When compared with annual wheat, perennial wheat ideotypes with high leaf area index had between 12% and 39% higher canopy transpiration and net CO2 assimilation, depending on their photosynthetic capacity and water status. Differences in leaf temperature and instantaneous water use efficiency between annual wheat and the perennial ideotypes were moderate (-0.5 to +0.4 °C and -6 to +2%, respectively). Low soil water availability did not alter the ranking of ideotypes in terms of canopy temperature and gas exchanges. During a prolonged dry down, cumulated water use was higher and canopy temperature lower in perennial than annual ideotypes, thanks to the deeper roots, whereas cumulated net CO2 fixation depended on the specific traits and air temperature. Leaf-specific and whole plant characteristics interacted with hydro-meteorological conditions in defining the perennial's vulnerability envelopes to potential heat and water stress. These findings underline the importance of plant characteristics, and particularly leaf area and rooting depth, in defining the suitability of perennial grain crops under future climates.