Articles | Volume 25, issue 11
https://doi.org/10.5194/hess-25-6041-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-6041-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A deep learning hybrid predictive modeling (HPM) approach for estimating evapotranspiration and ecosystem respiration
Jiancong Chen
CORRESPONDING AUTHOR
Department of Civil and Environmental Engineering, University of
California, Berkeley, CA, USA,
Baptiste Dafflon
Earth and Environmental Sciences Area,
Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Anh Phuong Tran
Earth and Environmental Sciences Area,
Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Department of
Water Resources Engineering and Technology, Water Resources Institute, 8,
Phao Dai Lang, Dong Da, Hanoi, Vietnam
Nicola Falco
Earth and Environmental Sciences Area,
Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Susan S. Hubbard
Earth and Environmental Sciences Area,
Lawrence Berkeley National Laboratory, Berkeley, CA, USA
Related authors
Jiancong Chen, Bhavna Arora, Alberto Bellin, and Yoram Rubin
Hydrol. Earth Syst. Sci., 25, 4127–4146, https://doi.org/10.5194/hess-25-4127-2021, https://doi.org/10.5194/hess-25-4127-2021, 2021
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We developed a stochastic framework with indicator random variables to characterize the spatiotemporal distribution of environmental hot spots and hot moments (HSHMs) that represent rare locations and events exerting a disproportionate influence over the environment. HSHMs are characterized by static and dynamic indicators. This framework is advantageous as it allows us to calculate the uncertainty associated with HSHMs based on uncertainty associated with its contributors.
Yoram Rubin, Ching-Fu Chang, Jiancong Chen, Karina Cucchi, Bradley Harken, Falk Heße, and Heather Savoy
Hydrol. Earth Syst. Sci., 22, 5675–5695, https://doi.org/10.5194/hess-22-5675-2018, https://doi.org/10.5194/hess-22-5675-2018, 2018
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This paper addresses questions related to the adoption of stochastic methods in hydrogeology, looking at factors such as environmental regulations, financial incentives, higher education, and the collective feedback loop involving these factors. We show that stochastic hydrogeology's blind spot is in focusing on risk while ignoring uncertainty, to the detriment of its potential clients. The imbalance between the treatments of risk and uncertainty is shown to be common to multiple disciplines.
Claire L. Bachand, Chen Wang, Baptiste Dafflon, Lauren Thomas, Ian Shirley, Sarah Maebius, Colleen M. Iversen, and Katrina E. Bennett
EGUsphere, https://doi.org/10.5194/egusphere-2024-2249, https://doi.org/10.5194/egusphere-2024-2249, 2024
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Temporally continuous snow depth estimates are vital for understanding changing snow patterns and impacts on permafrost in the Arctic. In this work, we develop an approach to predict snow depth from variability in snow-ground interface temperature using small temperature sensors that are cheap and easy-to-deploy. This new technique enables spatially distributed and temporally continuous snowpack monitoring that was not previously possible.
Ian Shirley, Sebastian Uhlemann, John Peterson, Katrina Bennett, Susan S. Hubbard, and Baptiste Dafflon
EGUsphere, https://doi.org/10.5194/egusphere-2023-968, https://doi.org/10.5194/egusphere-2023-968, 2023
Preprint archived
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Snow depth has a strong impact on soil temperatures and carbon cycling in the arctic. Because of this, we want to understand why snow is deeper in some places than others. Using cameras mounted on a drone, we mapped snow depth, vegetation height, and elevation across a watershed in Alaska. In this paper, we develop novel techniques using image processing and machine learning to characterize the influence of topography and shrubs on snow depth in the watershed.
Katrina E. Bennett, Greta Miller, Robert Busey, Min Chen, Emma R. Lathrop, Julian B. Dann, Mara Nutt, Ryan Crumley, Shannon L. Dillard, Baptiste Dafflon, Jitendra Kumar, W. Robert Bolton, Cathy J. Wilson, Colleen M. Iversen, and Stan D. Wullschleger
The Cryosphere, 16, 3269–3293, https://doi.org/10.5194/tc-16-3269-2022, https://doi.org/10.5194/tc-16-3269-2022, 2022
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In the Arctic and sub-Arctic, climate shifts are changing ecosystems, resulting in alterations in snow, shrubs, and permafrost. Thicker snow under shrubs can lead to warmer permafrost because deeper snow will insulate the ground from the cold winter. In this paper, we use modeling to characterize snow to better understand the drivers of snow distribution. Eventually, this work will be used to improve models used to study future changes in Arctic and sub-Arctic snow patterns.
Carlotta Brunetti, John Lamb, Stijn Wielandt, Sebastian Uhlemann, Ian Shirley, Patrick McClure, and Baptiste Dafflon
Earth Surf. Dynam., 10, 687–704, https://doi.org/10.5194/esurf-10-687-2022, https://doi.org/10.5194/esurf-10-687-2022, 2022
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This paper proposes a method to estimate thermal diffusivity and its uncertainty over time, at numerous locations and at an unprecedented vertical spatial resolution from soil temperature time series. We validate and apply this method to synthetic and field case studies. The improved quantification of soil thermal properties is a cornerstone for advancing the indirect estimation of the fraction of soil components needed to predict subsurface storage and fluxes of water, carbon, and nutrients.
Baptiste Dafflon, Stijn Wielandt, John Lamb, Patrick McClure, Ian Shirley, Sebastian Uhlemann, Chen Wang, Sylvain Fiolleau, Carlotta Brunetti, Franklin H. Akins, John Fitzpatrick, Samuel Pullman, Robert Busey, Craig Ulrich, John Peterson, and Susan S. Hubbard
The Cryosphere, 16, 719–736, https://doi.org/10.5194/tc-16-719-2022, https://doi.org/10.5194/tc-16-719-2022, 2022
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This study presents the development and validation of a novel acquisition system for measuring finely resolved depth profiles of soil and snow temperature at multiple locations. Results indicate that the system reliably captures the dynamics in snow thickness, as well as soil freezing and thawing depth, enabling advances in understanding the intensity and timing in surface processes and their impact on subsurface thermohydrological regimes.
Haruko M. Wainwright, Sebastian Uhlemann, Maya Franklin, Nicola Falco, Nicholas J. Bouskill, Michelle E. Newcomer, Baptiste Dafflon, Erica R. Siirila-Woodburn, Burke J. Minsley, Kenneth H. Williams, and Susan S. Hubbard
Hydrol. Earth Syst. Sci., 26, 429–444, https://doi.org/10.5194/hess-26-429-2022, https://doi.org/10.5194/hess-26-429-2022, 2022
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This paper has developed a tractable approach for characterizing watershed heterogeneity and its relationship with key functions such as ecosystem sensitivity to droughts and nitrogen export. We have applied clustering methods to classify hillslopes into
watershed zonesthat have distinct distributions of bedrock-to-canopy properties as well as key functions. This is a powerful approach for guiding watershed experiments and sampling as well as informing hydrological and biogeochemical models.
Qina Yan, Haruko Wainwright, Baptiste Dafflon, Sebastian Uhlemann, Carl I. Steefel, Nicola Falco, Jeffrey Kwang, and Susan S. Hubbard
Earth Surf. Dynam., 9, 1347–1361, https://doi.org/10.5194/esurf-9-1347-2021, https://doi.org/10.5194/esurf-9-1347-2021, 2021
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We develop a hybrid model to estimate the spatial distribution of the thickness of the soil layer, which also provides estimations of soil transport and soil production rates. We apply this model to two examples of hillslopes in the East River watershed in Colorado and validate the model. The results show that the north-facing (NF) hillslope has a deeper soil layer than the south-facing (SF) hillslope and that the hybrid model provides better accuracy than a machine-learning model.
Jiancong Chen, Bhavna Arora, Alberto Bellin, and Yoram Rubin
Hydrol. Earth Syst. Sci., 25, 4127–4146, https://doi.org/10.5194/hess-25-4127-2021, https://doi.org/10.5194/hess-25-4127-2021, 2021
Short summary
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We developed a stochastic framework with indicator random variables to characterize the spatiotemporal distribution of environmental hot spots and hot moments (HSHMs) that represent rare locations and events exerting a disproportionate influence over the environment. HSHMs are characterized by static and dynamic indicators. This framework is advantageous as it allows us to calculate the uncertainty associated with HSHMs based on uncertainty associated with its contributors.
Nathan A. Wales, Jesus D. Gomez-Velez, Brent D. Newman, Cathy J. Wilson, Baptiste Dafflon, Timothy J. Kneafsey, Florian Soom, and Stan D. Wullschleger
Hydrol. Earth Syst. Sci., 24, 1109–1129, https://doi.org/10.5194/hess-24-1109-2020, https://doi.org/10.5194/hess-24-1109-2020, 2020
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Rapid warming in the Arctic is causing increased permafrost temperatures and ground ice degradation. To study the effects of ice degradation on water distribution, tracer was applied to two end members of ice-wedge polygons – a ubiquitous landform in the Arctic. End member type was found to significantly affect water distribution as lower flux was observed with ice-wedge degradation. Results suggest ice degradation can influence partitioning of sequestered carbon as carbon dioxide or methane.
Benjamin Mary, Luca Peruzzo, Jacopo Boaga, Nicola Cenni, Myriam Schmutz, Yuxin Wu, Susan S. Hubbard, and Giorgio Cassiani
SOIL, 6, 95–114, https://doi.org/10.5194/soil-6-95-2020, https://doi.org/10.5194/soil-6-95-2020, 2020
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The use of non-invasive geophysical imaging of root system processes is of increasing interest to study soil–plant interactions. The experiment focused on the behaviour of grapevine plants during a controlled infiltration experiment. The combination of the mise-à-la-masse (MALM) method, a variation of the classical electrical tomography map (ERT), for which the current is transmitted directly into the stem, holds the promise of being able to image root distribution.
Elchin E. Jafarov, Dylan R. Harp, Ethan T. Coon, Baptiste Dafflon, Anh Phuong Tran, Adam L. Atchley, Youzuo Lin, and Cathy J. Wilson
The Cryosphere, 14, 77–91, https://doi.org/10.5194/tc-14-77-2020, https://doi.org/10.5194/tc-14-77-2020, 2020
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Improved subsurface parameterization and benchmarking data are needed to reduce current uncertainty in predicting permafrost response to a warming climate. We developed a subsurface parameter estimation framework that can be used to estimate soil properties where subsurface data are available. We utilize diverse geophysical datasets such as electrical resistance data, soil moisture data, and soil temperature data to recover soil porosity and soil thermal conductivity.
Emmanuel Léger, Baptiste Dafflon, Yves Robert, Craig Ulrich, John E. Peterson, Sébastien C. Biraud, Vladimir E. Romanovsky, and Susan S. Hubbard
The Cryosphere, 13, 2853–2867, https://doi.org/10.5194/tc-13-2853-2019, https://doi.org/10.5194/tc-13-2853-2019, 2019
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We propose a new strategy called distributed temperature profiling (DTP) for improving the estimation of soil thermal properties through the use of an unprecedented number of laterally and vertically distributed temperature measurements. We tested a DTP system prototype by moving it sequentially across a discontinuous permafrost environment. The DTP enabled high-resolution identification of near-surface permafrost location and covariability with topography, vegetation, and soil properties.
Yoram Rubin, Ching-Fu Chang, Jiancong Chen, Karina Cucchi, Bradley Harken, Falk Heße, and Heather Savoy
Hydrol. Earth Syst. Sci., 22, 5675–5695, https://doi.org/10.5194/hess-22-5675-2018, https://doi.org/10.5194/hess-22-5675-2018, 2018
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This paper addresses questions related to the adoption of stochastic methods in hydrogeology, looking at factors such as environmental regulations, financial incentives, higher education, and the collective feedback loop involving these factors. We show that stochastic hydrogeology's blind spot is in focusing on risk while ignoring uncertainty, to the detriment of its potential clients. The imbalance between the treatments of risk and uncertainty is shown to be common to multiple disciplines.
Benjamin Mary, Luca Peruzzo, Jacopo Boaga, Myriam Schmutz, Yuxin Wu, Susan S. Hubbard, and Giorgio Cassiani
Hydrol. Earth Syst. Sci., 22, 5427–5444, https://doi.org/10.5194/hess-22-5427-2018, https://doi.org/10.5194/hess-22-5427-2018, 2018
Gautam Bisht, William J. Riley, Haruko M. Wainwright, Baptiste Dafflon, Fengming Yuan, and Vladimir E. Romanovsky
Geosci. Model Dev., 11, 61–76, https://doi.org/10.5194/gmd-11-61-2018, https://doi.org/10.5194/gmd-11-61-2018, 2018
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The land model integrated into the Energy Exascale Earth System Model was extended to include snow redistribution (SR) and lateral subsurface hydrologic and thermal processes. Simulation results at a polygonal tundra site near Barrow, Alaska, showed that inclusion of SR resulted in a better agreement with observations. Excluding lateral subsurface processes had a small impact on mean states but caused a large overestimation of spatial variability in soil moisture and temperature.
Anh Phuong Tran, Baptiste Dafflon, and Susan S. Hubbard
The Cryosphere, 11, 2089–2109, https://doi.org/10.5194/tc-11-2089-2017, https://doi.org/10.5194/tc-11-2089-2017, 2017
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Soil organics carbon (SOC) and its influence on terrestrial ecosystem feedbacks to global warming in permafrost regions are particularly important for the prediction of future climate variation. Our study proposes a new surface–subsurface, joint deterministic–stochastic hydrological–thermal–geophysical inversion approach and documents the benefit of including multiple types of data to estimate the vertical profile of SOC content and its influence on hydrological–thermal dynamics.
Haruko M. Wainwright, Anna K. Liljedahl, Baptiste Dafflon, Craig Ulrich, John E. Peterson, Alessio Gusmeroli, and Susan S. Hubbard
The Cryosphere, 11, 857–875, https://doi.org/10.5194/tc-11-857-2017, https://doi.org/10.5194/tc-11-857-2017, 2017
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Snow has a profound impact on permafrost and ecosystem functioning in the Arctic tundra. This paper aims to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. In addition, we develop a Bayesian geostatistical method to integrate multiscale observational platforms (a snow probe, ground penetrating radar, unmanned aerial system and airborne lidar) for estimating snow depth in high resolution over a large area.
Anh Phuong Tran, Baptiste Dafflon, Susan S. Hubbard, Michael B. Kowalsky, Philip Long, Tetsu K. Tokunaga, and Kenneth H. Williams
Hydrol. Earth Syst. Sci., 20, 3477–3491, https://doi.org/10.5194/hess-20-3477-2016, https://doi.org/10.5194/hess-20-3477-2016, 2016
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Quantifying water and heat fluxes in the shallow subsurface is particularly important due to their strong control on recharge, evaporation and biogeochemical processes. This study developed and tested a new inversion scheme to estimate subsurface hydro-thermal parameters by joint using different hydrological, thermal and geophysical data. It is especially useful for the increasing number of studies that are taking advantage of autonomously collected measurements to explore ecosystem dynamics.
Related subject area
Subject: Ecohydrology | Techniques and Approaches: Modelling approaches
Regional patterns and drivers of modelled water flows along environmental, functional, and stand structure gradients in Spanish forests
Machine learning and global vegetation: random forests for downscaling and gap filling
Unraveling phenological and stomatal responses to flash drought and implications for water and carbon budgets
Ecohydrological responses to solar radiation changes
Bias-blind and bias-aware assimilation of leaf area index into the Noah-MP land surface model over Europe
Technical assessment combined with extended cost-benefit analysis for groundwater ecosystem services restoration – An application for Grand Bahama
Technical note: Seamless extraction and analysis of river networks in R
Advancing stream classification and hydrologic modeling of ungaged basins for environmental flow management in coastal southern California
Improving regional climate simulations based on a hybrid data assimilation and machine learning method
A comprehensive assessment of in situ and remote sensing soil moisture data assimilation in the APSIM model for improving agricultural forecasting across the US Midwest
Does non-stationarity induced by multiyear drought invalidate the paired-catchment method?
Is the reputation of Eucalyptus plantations for using more water than Pinus plantations justified?
Attributing trend in naturalized streamflow to temporally explicit vegetation change and climate variation in the Yellow River basin of China
Impacts of different types of El Niño events on water quality over the Corn Belt, United States
Leveraging sap flow data in a catchment-scale hybrid model to improve soil moisture and transpiration estimates
Coupled modelling of hydrological processes and grassland production in two contrasting climates
Does maximization of net carbon profit enable the prediction of vegetation behaviour in savanna sites along a precipitation gradient?
Modelling the artificial forest (Robinia pseudoacacia L.) root–soil water interactions in the Loess Plateau, China
Vegetation greening weakened the capacity of water supply to China's South-to-North Water Diversion Project
Structural changes to forests during regeneration affect water flux partitioning, water ages and hydrological connectivity: Insights from tracer-aided ecohydrological modelling
How does water yield respond to mountain pine beetle infestation in a semiarid forest?
Daily soil temperature modeling improved by integrating observed snow cover and estimated soil moisture in the USA Great Plains
Plant hydraulic transport controls transpiration sensitivity to soil water stress
Drought onset and propagation into soil moisture and grassland vegetation responses during the 2012–2019 major drought in Southern California
Quantifying the effects of urban green space on water partitioning and ages using an isotope-based ecohydrological model
Low and contrasting impacts of vegetation CO2 fertilization on global terrestrial runoff over 1982–2010: accounting for aboveground and belowground vegetation–CO2 effects
Global ecosystem-scale plant hydraulic traits retrieved using model–data fusion
Quantifying the effects of land use and model scale on water partitioning and water ages using tracer-aided ecohydrological models
Quantification of ecohydrological sensitivities and their influencing factors at the seasonal scale
Canopy temperature and heat stress are increased by compound high air temperature and water stress and reduced by irrigation – a modeling analysis
Evaluating a landscape-scale daily water balance model to support spatially continuous representation of flow intermittency throughout stream networks
Testing water fluxes and storage from two hydrology configurations within the ORCHIDEE land surface model across US semi-arid sites
Novel Keeling-plot-based methods to estimate the isotopic composition of ambient water vapor
Disentangling temporal and population variability in plant root water uptake from stable isotopic analysis: when rooting depth matters in labeling studies
Calibration of hydrological models for ecologically relevant streamflow predictions: a trade-off between fitting well to data and estimating consistent parameter sets?
Spatial variability of mean daily estimates of actual evaporation from remotely sensed imagery and surface reference data
Quantification of soil water balance components based on continuous soil moisture measurement and the Richards equation in an irrigated agricultural field of a desert oasis
Mapping the suitability of groundwater-dependent vegetation in a semi-arid Mediterranean area
Modeling boreal forest evapotranspiration and water balance at stand and catchment scales: a spatial approach
The 18O ecohydrology of a grassland ecosystem – predictions and observations
A comprehensive sensitivity and uncertainty analysis for discharge and nitrate-nitrogen loads involving multiple discrete model inputs under future changing conditions
Dynamic responses of DOC and DIC transport to different flow regimes in a subtropical small mountainous river
Evaluation of ORCHIDEE-MICT-simulated soil moisture over China and impacts of different atmospheric forcing data
Testing an optimality-based model of rooting zone water storage capacity in temperate forests
A regional-scale ecological risk framework for environmental flow evaluations
Climate-driven disturbances in the San Juan River sub-basin of the Colorado River
Dominant effect of increasing forest biomass on evapotranspiration: interpretations of movement in Budyko space
Modeling the potential impacts of climate change on the water table level of selected forested wetlands in the southeastern United States
Calibration of a parsimonious distributed ecohydrological daily model in a data-scarce basin by exclusively using the spatio-temporal variation of NDVI
Importance of considering riparian vegetation requirements for the long-term efficiency of environmental flows in aquatic microhabitats
Jesús Sánchez-Dávila, Miquel De Cáceres, Jordi Vayreda, and Javier Retana
Hydrol. Earth Syst. Sci., 28, 3037–3050, https://doi.org/10.5194/hess-28-3037-2024, https://doi.org/10.5194/hess-28-3037-2024, 2024
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Forest blue water is determined by the climate, functional traits, and stand structure variables. The leaf area index (LAI) is the main driver of the trade-off between the blue and green water. Blue water is concentrated in the autumn–winter season, and deciduous trees can increase the relative blue water. The leaf phenology and seasonal distribution are determinants for the relative blue water.
Barry van Jaarsveld, Sandra M. Hauswirth, and Niko Wanders
Hydrol. Earth Syst. Sci., 28, 2357–2374, https://doi.org/10.5194/hess-28-2357-2024, https://doi.org/10.5194/hess-28-2357-2024, 2024
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Drought often manifests itself in vegetation; however, obtaining high-resolution remote-sensing products that are spatially and temporally consistent is difficult. In this study, we show that machine learning (ML) can fill data gaps in existing products. We also demonstrate that ML can be used as a downscaling tool. By relying on ML for gap filling and downscaling, we can obtain a more holistic view of the impacts of drought on vegetation.
Nicholas K. Corak, Jason A. Otkin, Trent W. Ford, and Lauren E. L. Lowman
Hydrol. Earth Syst. Sci., 28, 1827–1851, https://doi.org/10.5194/hess-28-1827-2024, https://doi.org/10.5194/hess-28-1827-2024, 2024
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We simulate how dynamic vegetation interacts with the atmosphere during extreme drought events known as flash droughts. We find that plants nearly halt water and carbon exchanges and limit their growth during flash drought. This work has implications for how to account for changes in vegetation state during extreme drought events when making predictions under future climate scenarios.
Yiran Wang, Naika Meili, and Simone Fatichi
EGUsphere, https://doi.org/10.5194/egusphere-2024-768, https://doi.org/10.5194/egusphere-2024-768, 2024
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Our study uses climate model simulations and process-based ecohydrological modeling to assess the direct and climate feedback induced effects of solar radiation changes on hydrological variables. Results show that solar radiation without climate feedback primarily affects sensible heat with limited effects on hydrology and vegetation. However, climate feedback exacerbates the effects of radiation changes on evapotranspiration and affects vegetation productivity.
Samuel Scherrer, Gabriëlle De Lannoy, Zdenko Heyvaert, Michel Bechtold, Clement Albergel, Tarek S. El-Madany, and Wouter Dorigo
Hydrol. Earth Syst. Sci., 27, 4087–4114, https://doi.org/10.5194/hess-27-4087-2023, https://doi.org/10.5194/hess-27-4087-2023, 2023
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We explored different options for data assimilation (DA) of the remotely sensed leaf area index (LAI). We found strong biases between LAI predicted by Noah-MP and observations. LAI DA that does not take these biases into account can induce unphysical patterns in the resulting LAI and flux estimates and leads to large changes in the climatology of root zone soil moisture. We tested two bias-correction approaches and explored alternative solutions to treating bias in LAI DA.
Anne Imig, Francesca Perosa, Carolina Iwane Hotta, Sophia Klausner, Kristen Welsh, and Arno Rein
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2023-236, https://doi.org/10.5194/hess-2023-236, 2023
Revised manuscript accepted for HESS
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In 2019, Hurricane Dorian led to salinization of groundwater resources on the island of Grand Bahama. We assessed the feasibility of managed aquifer recharge (MAR) for restoring fresh groundwater. Furthermore, we applied a financial and an extended cost-benefit analysis for assessing ecosystem services supported by MAR and reforestation. As a first estimate, MAR could only provide a small contribution to the water demand. Reforestation measures were assessed as financially profitable.
Luca Carraro
Hydrol. Earth Syst. Sci., 27, 3733–3742, https://doi.org/10.5194/hess-27-3733-2023, https://doi.org/10.5194/hess-27-3733-2023, 2023
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Mathematical models are key to the study of environmental processes in rivers. Such models often require information on river morphology from geographic information system (GIS) software, which hinders the use of replicable workflows. Here I present rivnet, an R package for simple, robust, GIS-free extraction and analysis of river networks. The package is designed so as to require minimal user input and is oriented towards ecohydrological, ecological and biogeochemical modeling.
Stephen K. Adams, Brian P. Bledsoe, and Eric D. Stein
Hydrol. Earth Syst. Sci., 27, 3021–3039, https://doi.org/10.5194/hess-27-3021-2023, https://doi.org/10.5194/hess-27-3021-2023, 2023
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Managing streams for environmental flows involves prioritizing healthy stream ecosystems while distributing water resources. Classifying streams of similar types is a useful step in developing environmental flows. Environmental flows are often developed on data-poor streams that must be modeled. This paper has developed a new method of classification that prioritizes model accuracy. The new method advances environmental streamflow management and modeling of data-poor watersheds.
Xinlei He, Yanping Li, Shaomin Liu, Tongren Xu, Fei Chen, Zhenhua Li, Zhe Zhang, Rui Liu, Lisheng Song, Ziwei Xu, Zhixing Peng, and Chen Zheng
Hydrol. Earth Syst. Sci., 27, 1583–1606, https://doi.org/10.5194/hess-27-1583-2023, https://doi.org/10.5194/hess-27-1583-2023, 2023
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This study highlights the role of integrating vegetation and multi-source soil moisture observations in regional climate models via a hybrid data assimilation and machine learning method. In particular, we show that this approach can improve land surface fluxes, near-surface atmospheric conditions, and land–atmosphere interactions by implementing detailed land characterization information in basins with complex underlying surfaces.
Marissa Kivi, Noemi Vergopolan, and Hamze Dokoohaki
Hydrol. Earth Syst. Sci., 27, 1173–1199, https://doi.org/10.5194/hess-27-1173-2023, https://doi.org/10.5194/hess-27-1173-2023, 2023
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This study attempts to provide a framework for direct integration of soil moisture observations collected from soil sensors and satellite imagery into process-based crop models for improving the representation of agricultural systems. The performance of this framework was evaluated across 19 sites times years for crop yield, normalized difference vegetation index (NDVI), soil moisture, tile flow drainage, and nitrate leaching.
Yunfan Zhang, Lei Cheng, Lu Zhang, Shujing Qin, Liu Liu, Pan Liu, and Yanghe Liu
Hydrol. Earth Syst. Sci., 26, 6379–6397, https://doi.org/10.5194/hess-26-6379-2022, https://doi.org/10.5194/hess-26-6379-2022, 2022
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Multiyear drought has been demonstrated to cause non-stationary rainfall–runoff relationship. But whether changes can invalidate the most fundamental method (i.e., paired-catchment method (PCM)) for separating vegetation change impacts is still unknown. Using paired-catchment data with 10-year drought, PCM is shown to still be reliable even in catchments with non-stationarity. A new framework is further proposed to separate impacts of two non-stationary drivers, using paired-catchment data.
Don A. White, Shiqi Ren, Daniel S. Mendham, Francisco Balocchi-Contreras, Richard P. Silberstein, Dean Meason, Andrés Iroumé, and Pablo Ramirez de Arellano
Hydrol. Earth Syst. Sci., 26, 5357–5371, https://doi.org/10.5194/hess-26-5357-2022, https://doi.org/10.5194/hess-26-5357-2022, 2022
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Of all the planting options for wood production and carbon storage, Eucalyptus species provoke the greatest concern about their effect on water resources. We compared Eucalyptus and Pinus species (the two most widely planted genera) by fitting a simple model to the published estimates of their annual water use. There was no significant difference between the two genera. This has important implications for the global debate around Eucalyptus and is an option for carbon forests.
Zhihui Wang, Qiuhong Tang, Daoxi Wang, Peiqing Xiao, Runliang Xia, Pengcheng Sun, and Feng Feng
Hydrol. Earth Syst. Sci., 26, 5291–5314, https://doi.org/10.5194/hess-26-5291-2022, https://doi.org/10.5194/hess-26-5291-2022, 2022
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Variable infiltration capacity simulation considering dynamic vegetation types and structural parameters is able to better capture the effect of temporally explicit vegetation change and climate variation in hydrological regimes. Vegetation greening including interannual LAI and intra-annual LAI temporal pattern change induced by large-scale ecological restoration and non-vegetation underlying surface change played dominant roles in the natural streamflow reduction of the Yellow River basin.
Pan Chen, Wenhong Li, and Keqi He
Hydrol. Earth Syst. Sci., 26, 4875–4892, https://doi.org/10.5194/hess-26-4875-2022, https://doi.org/10.5194/hess-26-4875-2022, 2022
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The study assessed changes in total nitrogen (TN) and total phosphorus (TP) loads in response to eastern Pacific (EP) and central Pacific (CP) El Niño events over the Corn Belt, USA, using the SWAT model. Results showed that EP (CP) El Niño events improved (exacerbated) water quality in the region. Furthermore, EP El Niño had a much broader and longer impact on water quality at the outlets, but CP El Niño could lead to similar increases in TN/TP loads as EP El Niño at the specific watersheds.
Ralf Loritz, Maoya Bassiouni, Anke Hildebrandt, Sibylle K. Hassler, and Erwin Zehe
Hydrol. Earth Syst. Sci., 26, 4757–4771, https://doi.org/10.5194/hess-26-4757-2022, https://doi.org/10.5194/hess-26-4757-2022, 2022
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In this study, we combine a deep-learning approach that predicts sap flow with a hydrological model to improve soil moisture and transpiration estimates at the catchment scale. Our results highlight that hybrid-model approaches, combining machine learning with physically based models, are a promising way to improve our ability to make hydrological predictions.
Nicholas Jarvis, Jannis Groh, Elisabet Lewan, Katharina H. E. Meurer, Walter Durka, Cornelia Baessler, Thomas Pütz, Elvin Rufullayev, and Harry Vereecken
Hydrol. Earth Syst. Sci., 26, 2277–2299, https://doi.org/10.5194/hess-26-2277-2022, https://doi.org/10.5194/hess-26-2277-2022, 2022
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We apply an eco-hydrological model to data on soil water balance and grassland growth obtained at two sites with contrasting climates. Our results show that the grassland in the drier climate had adapted by developing deeper roots, which maintained water supply to the plants in the face of severe drought. Our study emphasizes the importance of considering such plastic responses of plant traits to environmental stress in the modelling of soil water balance and plant growth under climate change.
Remko C. Nijzink, Jason Beringer, Lindsay B. Hutley, and Stanislaus J. Schymanski
Hydrol. Earth Syst. Sci., 26, 525–550, https://doi.org/10.5194/hess-26-525-2022, https://doi.org/10.5194/hess-26-525-2022, 2022
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Most models that simulate water and carbon exchanges with the atmosphere rely on information about vegetation, but optimality models predict vegetation properties based on general principles. Here, we use the Vegetation Optimality Model (VOM) to predict vegetation behaviour at five savanna sites. The VOM overpredicted vegetation cover and carbon uptake during the wet seasons but also performed similarly to conventional models, showing that vegetation optimality is a promising approach.
Hongyu Li, Yi Luo, Lin Sun, Xiangdong Li, Changkun Ma, Xiaolei Wang, Ting Jiang, and Haoyang Zhu
Hydrol. Earth Syst. Sci., 26, 17–34, https://doi.org/10.5194/hess-26-17-2022, https://doi.org/10.5194/hess-26-17-2022, 2022
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Drying soil layers (DSLs) have been extensively reported in artificial forestland in the Loess Plateau, China, which has limited water resources and deep loess. To address this issue relating to plant root–soil water interactions, this study developed a root growth model that simulates both the dynamic rooting depth and fine-root distribution. Evaluation vs. field data proved a positive performance. Long-term simulation reproduced the evolution process of the DSLs and revealed their mechanisms.
Jiehao Zhang, Yulong Zhang, Ge Sun, Conghe Song, Matthew P. Dannenberg, Jiangfeng Li, Ning Liu, Kerong Zhang, Quanfa Zhang, and Lu Hao
Hydrol. Earth Syst. Sci., 25, 5623–5640, https://doi.org/10.5194/hess-25-5623-2021, https://doi.org/10.5194/hess-25-5623-2021, 2021
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To quantify how vegetation greening impacts the capacity of water supply, we built a hybrid model and conducted a case study using the upper Han River basin (UHRB) that serves as the water source area to the world’s largest water diversion project. Vegetation greening in the UHRB during 2001–2018 induced annual water yield (WY) greatly decreased. Vegetation greening also increased the possibility of drought and reduced a quarter of WY on average during drought periods.
Aaron J. Neill, Christian Birkel, Marco P. Maneta, Doerthe Tetzlaff, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 4861–4886, https://doi.org/10.5194/hess-25-4861-2021, https://doi.org/10.5194/hess-25-4861-2021, 2021
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Structural changes (cover and height of vegetation plus tree canopy characteristics) to forests during regeneration on degraded land affect how water is partitioned between streamflow, groundwater recharge and evapotranspiration. Partitioning most strongly deviates from baseline conditions during earlier stages of regeneration with dense forest, while recovery may be possible as the forest matures and opens out. This has consequences for informing sustainable landscape restoration strategies.
Jianning Ren, Jennifer C. Adam, Jeffrey A. Hicke, Erin J. Hanan, Christina L. Tague, Mingliang Liu, Crystal A. Kolden, and John T. Abatzoglou
Hydrol. Earth Syst. Sci., 25, 4681–4699, https://doi.org/10.5194/hess-25-4681-2021, https://doi.org/10.5194/hess-25-4681-2021, 2021
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Mountain pine beetle outbreaks have caused widespread tree mortality. While some research shows that water yield increases after trees are killed, many others document no change or a decrease. The climatic and environmental mechanisms driving hydrologic response to tree mortality are not well understood. We demonstrated that the direction of hydrologic response is a function of multiple factors, so previous studies do not necessarily conflict with each other; they represent different conditions.
Haidong Zhao, Gretchen F. Sassenrath, Mary Beth Kirkham, Nenghan Wan, and Xiaomao Lin
Hydrol. Earth Syst. Sci., 25, 4357–4372, https://doi.org/10.5194/hess-25-4357-2021, https://doi.org/10.5194/hess-25-4357-2021, 2021
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This study was done to develop an improved soil temperature model for the USA Great Plains by using common weather station variables as inputs. After incorporating knowledge of estimated soil moisture and observed daily snow depth, the improved model showed a near 50 % gain in performance compared to the original model. We conclude that our improved model can better estimate soil temperature at the surface soil layer where most hydrological and biological processes occur.
Brandon P. Sloan, Sally E. Thompson, and Xue Feng
Hydrol. Earth Syst. Sci., 25, 4259–4274, https://doi.org/10.5194/hess-25-4259-2021, https://doi.org/10.5194/hess-25-4259-2021, 2021
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Plants affect the global water and carbon cycles by modifying their water use and carbon intake in response to soil moisture. Global climate models represent this response with either simple empirical models or complex physical models. We reveal that the latter improves predictions in plants with large flow resistance; however, adding dependence on atmospheric moisture demand to the former matches performance of the latter, leading to a new tool for improving carbon and water cycle predictions.
Maria Magdalena Warter, Michael Bliss Singer, Mark O. Cuthbert, Dar Roberts, Kelly K. Caylor, Romy Sabathier, and John Stella
Hydrol. Earth Syst. Sci., 25, 3713–3729, https://doi.org/10.5194/hess-25-3713-2021, https://doi.org/10.5194/hess-25-3713-2021, 2021
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Intensified drying of soil and grassland vegetation is raising the impact of fire severity and extent in Southern California. While browned grassland is a common sight during the dry season, this study has shown that there is a pronounced shift in the timing of senescence, due to changing climate conditions favoring milder winter temperatures and increased precipitation variability. Vegetation may be limited in its ability to adapt to these shifts, as drought periods become more frequent.
Mikael Gillefalk, Dörthe Tetzlaff, Reinhard Hinkelmann, Lena-Marie Kuhlemann, Aaron Smith, Fred Meier, Marco P. Maneta, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 3635–3652, https://doi.org/10.5194/hess-25-3635-2021, https://doi.org/10.5194/hess-25-3635-2021, 2021
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We used a tracer-aided ecohydrological model to quantify water flux–storage–age interactions for three urban vegetation types: trees, shrub and grass. The model results showed that evapotranspiration increased in the order shrub < grass < trees during one growing season. Additionally, we could show how
infiltration hotspotscreated by runoff from sealed onto vegetated surfaces can enhance both evapotranspiration and groundwater recharge.
Yuting Yang, Tim R. McVicar, Dawen Yang, Yongqiang Zhang, Shilong Piao, Shushi Peng, and Hylke E. Beck
Hydrol. Earth Syst. Sci., 25, 3411–3427, https://doi.org/10.5194/hess-25-3411-2021, https://doi.org/10.5194/hess-25-3411-2021, 2021
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This study developed an analytical ecohydrological model that considers three aspects of vegetation response to eCO2 (i.e., stomatal response, LAI response, and rooting depth response) to detect the impact of eCO2 on continental runoff over the past 3 decades globally. Our findings suggest a minor role of eCO2 on the global runoff changes, yet highlight the negative runoff–eCO2 response in semiarid and arid regions which may further threaten the limited water resource there.
Yanlan Liu, Nataniel M. Holtzman, and Alexandra G. Konings
Hydrol. Earth Syst. Sci., 25, 2399–2417, https://doi.org/10.5194/hess-25-2399-2021, https://doi.org/10.5194/hess-25-2399-2021, 2021
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The flow of water through plants varies with species-specific traits. To determine how they vary across the world, we mapped the traits that best allowed a model to match microwave satellite data. We also defined average values across a few clusters of trait behavior. These form a tractable solution for use in large-scale models. Transpiration estimates using these clusters were more accurate than if using plant functional types. We expect our maps to improve transpiration forecasts.
Aaron Smith, Doerthe Tetzlaff, Lukas Kleine, Marco Maneta, and Chris Soulsby
Hydrol. Earth Syst. Sci., 25, 2239–2259, https://doi.org/10.5194/hess-25-2239-2021, https://doi.org/10.5194/hess-25-2239-2021, 2021
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We used a tracer-aided ecohydrological model on a mixed land use catchment in northeastern Germany to quantify water flux–storage–age interactions at four model grid resolutions. The model's ability to reproduce spatio-temporal flux–storage–age interactions decreases with increasing model grid sizes. Similarly, larger model grids showed vegetation-influenced changes in blue and green water partitioning. Simulations reveal the value of measured soil and stream isotopes for model calibration.
Yiping Hou, Mingfang Zhang, Xiaohua Wei, Shirong Liu, Qiang Li, Tijiu Cai, Wenfei Liu, Runqi Zhao, and Xiangzhuo Liu
Hydrol. Earth Syst. Sci., 25, 1447–1466, https://doi.org/10.5194/hess-25-1447-2021, https://doi.org/10.5194/hess-25-1447-2021, 2021
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Ecohydrological sensitivity, defined as the response intensity of streamflow to vegetation change, indicates the hydrological sensitivity to vegetation change. The study revealed seasonal ecohydrological sensitivities were highly variable, depending on climate condition and watershed attributes. Dry season ecohydrological sensitivity was mostly determined by topography, soil and vegetation, while wet season ecohydrological sensitivity was mainly controlled by soil, landscape and vegetation.
Xiangyu Luan and Giulia Vico
Hydrol. Earth Syst. Sci., 25, 1411–1423, https://doi.org/10.5194/hess-25-1411-2021, https://doi.org/10.5194/hess-25-1411-2021, 2021
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Crop yield is reduced by heat and water stress, particularly when they co-occur. We quantify the joint effects of (unpredictable) air temperature and soil water availability on crop heat stress via a mechanistic model. Larger but more infrequent precipitation increased crop canopy temperatures. Keeping crops well watered via irrigation could reduce canopy temperature but not enough to always exclude heat damage. Thus, irrigation is only a partial solution to adapt to warmer and drier climates.
Songyan Yu, Hong Xuan Do, Albert I. J. M. van Dijk, Nick R. Bond, Peirong Lin, and Mark J. Kennard
Hydrol. Earth Syst. Sci., 24, 5279–5295, https://doi.org/10.5194/hess-24-5279-2020, https://doi.org/10.5194/hess-24-5279-2020, 2020
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There is a growing interest globally in the spatial distribution and temporal dynamics of intermittently flowing streams and rivers. We developed an approach to quantify catchment-wide flow intermittency over long time frames. Modelled patterns of flow intermittency in eastern Australia revealed highly dynamic behaviour in space and time. The developed approach is transferable to other parts of the world and can inform hydro-ecological understanding and management of intermittent streams.
Natasha MacBean, Russell L. Scott, Joel A. Biederman, Catherine Ottlé, Nicolas Vuichard, Agnès Ducharne, Thomas Kolb, Sabina Dore, Marcy Litvak, and David J. P. Moore
Hydrol. Earth Syst. Sci., 24, 5203–5230, https://doi.org/10.5194/hess-24-5203-2020, https://doi.org/10.5194/hess-24-5203-2020, 2020
Yusen Yuan, Taisheng Du, Honglang Wang, and Lixin Wang
Hydrol. Earth Syst. Sci., 24, 4491–4501, https://doi.org/10.5194/hess-24-4491-2020, https://doi.org/10.5194/hess-24-4491-2020, 2020
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The isotopic composition of ambient water vapor is an important source of atmospheric water vapor and has not been able to be estimated to date using the Keeling plot approach. Here we proposed two new methods to estimate the isotopic composition of ambient water vapor: one using the intersection point method and another relying on the intermediate value theorem.
Valentin Couvreur, Youri Rothfuss, Félicien Meunier, Thierry Bariac, Philippe Biron, Jean-Louis Durand, Patricia Richard, and Mathieu Javaux
Hydrol. Earth Syst. Sci., 24, 3057–3075, https://doi.org/10.5194/hess-24-3057-2020, https://doi.org/10.5194/hess-24-3057-2020, 2020
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Isotopic labeling of soil water is a broadly used tool for tracing the origin of water extracted by plants and computing root water uptake (RWU) profiles with multisource mixing models. In this study, we show how a method such as this may misconstrue time series of xylem water isotopic composition as the temporal dynamics of RWU by simulating data collected during a tall fescue rhizotron experiment with an isotope-enabled physical soil–root model accounting for variability in root traits.
Thibault Hallouin, Michael Bruen, and Fiachra E. O'Loughlin
Hydrol. Earth Syst. Sci., 24, 1031–1054, https://doi.org/10.5194/hess-24-1031-2020, https://doi.org/10.5194/hess-24-1031-2020, 2020
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A hydrological model was used to compare different parameterisation strategies in view of predicting ecologically relevant streamflow indices in 33 Irish catchments. Compared for 14 different periods, a strategy fitting simulated and observed streamflow indices yielded better performance than fitting simulated and observed streamflow, but it also yielded a less consistent ensemble of parameter sets, suggesting that these indices may not be hydrologically relevant for model parameterisation.
Robert N. Armstrong, John W. Pomeroy, and Lawrence W. Martz
Hydrol. Earth Syst. Sci., 23, 4891–4907, https://doi.org/10.5194/hess-23-4891-2019, https://doi.org/10.5194/hess-23-4891-2019, 2019
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Digital and thermal images taken near midday were used to scale daily point observations of key factors driving actual-evaporation estimates across a complex Canadian Prairie landscape. Point estimates of actual evaporation agreed well with observed values via eddy covariance. Impacts of spatial variations on areal estimates were minor, and no covariance was found between model parameters driving the energy term. The methods can be applied further to improve land surface parameterisations.
Zhongkai Li, Hu Liu, Wenzhi Zhao, Qiyue Yang, Rong Yang, and Jintao Liu
Hydrol. Earth Syst. Sci., 23, 4685–4706, https://doi.org/10.5194/hess-23-4685-2019, https://doi.org/10.5194/hess-23-4685-2019, 2019
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A database of soil moisture measurements from the middle Heihe River basin of China was used to test the potential of a soil moisture database in estimating the soil water balance components (SWBCs). We determined SWBCs using a method that combined the soil water balance method and the inverse Richards equation. This work confirmed that relatively reasonable estimations of the SWBCs in coarse-textured sandy soils can be derived using soil moisture measurements.
Inês Gomes Marques, João Nascimento, Rita M. Cardoso, Filipe Miguéns, Maria Teresa Condesso de Melo, Pedro M. M. Soares, Célia M. Gouveia, and Cathy Kurz Besson
Hydrol. Earth Syst. Sci., 23, 3525–3552, https://doi.org/10.5194/hess-23-3525-2019, https://doi.org/10.5194/hess-23-3525-2019, 2019
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Mediterranean cork woodlands are very particular agroforestry systems present in a confined area of the Mediterranean Basin. They are of great importance due to their high socioeconomic value; however, a decrease in water availability has put this system in danger. In this paper we build a model that explains this system's tree-species distribution in southern Portugal from environmental variables. This could help predict their future distribution under changing climatic conditions.
Samuli Launiainen, Mingfu Guan, Aura Salmivaara, and Antti-Jussi Kieloaho
Hydrol. Earth Syst. Sci., 23, 3457–3480, https://doi.org/10.5194/hess-23-3457-2019, https://doi.org/10.5194/hess-23-3457-2019, 2019
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Boreal forest evapotranspiration and water cycle is modeled at stand and catchment scale using physiological and physical principles, open GIS data and daily weather data. The approach can predict daily evapotranspiration well across Nordic coniferous-dominated stands and successfully reproduces daily streamflow and annual evapotranspiration across boreal headwater catchments in Finland. The model is modular and simple and designed for practical applications over large areas using open data.
Regina T. Hirl, Hans Schnyder, Ulrike Ostler, Rudi Schäufele, Inga Schleip, Sylvia H. Vetter, Karl Auerswald, Juan C. Baca Cabrera, Lisa Wingate, Margaret M. Barbour, and Jérôme Ogée
Hydrol. Earth Syst. Sci., 23, 2581–2600, https://doi.org/10.5194/hess-23-2581-2019, https://doi.org/10.5194/hess-23-2581-2019, 2019
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We evaluated the system-scale understanding of the propagation of the oxygen isotope signal (δ18O) of rain through soil and xylem to leaf water in a temperate drought-prone grassland. Biweekly δ18O observations of the water pools made during seven growing seasons were accurately reproduced by the 18O-enabled process-based model MuSICA. While water uptake occurred from shallow soil depths throughout dry and wet periods, leaf water 18O enrichment responded to both soil and atmospheric moisture.
Christoph Schürz, Brigitta Hollosi, Christoph Matulla, Alexander Pressl, Thomas Ertl, Karsten Schulz, and Bano Mehdi
Hydrol. Earth Syst. Sci., 23, 1211–1244, https://doi.org/10.5194/hess-23-1211-2019, https://doi.org/10.5194/hess-23-1211-2019, 2019
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For two Austrian catchments we simulated discharge and nitrate-nitrogen (NO3-N) considering future changes of climate, land use, and point source emissions together with the impact of different setups and parametrizations of the implemented eco-hydrological model. In a comprehensive analysis we identified the dominant sources of uncertainty for the simulation of discharge and NO3-N and further examined how specific properties of the model inputs control the future simulation results.
Yu-Ting Shih, Pei-Hao Chen, Li-Chin Lee, Chien-Sen Liao, Shih-Hao Jien, Fuh-Kwo Shiah, Tsung-Yu Lee, Thomas Hein, Franz Zehetner, Chung-Te Chang, and Jr-Chuan Huang
Hydrol. Earth Syst. Sci., 22, 6579–6590, https://doi.org/10.5194/hess-22-6579-2018, https://doi.org/10.5194/hess-22-6579-2018, 2018
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DOC and DIC export in Taiwan shows that the annual DOC and DIC fluxes were 2.7–4.8 and 48.4–54.3 ton C km2 yr1, respectively, which were approximately 2 and 20 times higher than the global means of 1.4 and 2.6 ton C km2 yr1, respectively.
Zun Yin, Catherine Ottlé, Philippe Ciais, Matthieu Guimberteau, Xuhui Wang, Dan Zhu, Fabienne Maignan, Shushi Peng, Shilong Piao, Jan Polcher, Feng Zhou, Hyungjun Kim, and other China-Trend-Stream project members
Hydrol. Earth Syst. Sci., 22, 5463–5484, https://doi.org/10.5194/hess-22-5463-2018, https://doi.org/10.5194/hess-22-5463-2018, 2018
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Simulations in China were performed in ORCHIDEE driven by different forcing datasets: GSWP3, PGF, CRU-NCEP, and WFDEI. Simulated soil moisture was compared to several datasets to evaluate the ability of ORCHIDEE in reproducing soil moisture dynamics. Results showed that ORCHIDEE soil moisture coincided well with other datasets in wet areas and in non-irrigated areas. It suggested that the ORCHIDEE-MICT was suitable for further hydrological studies in China.
Matthias J. R. Speich, Heike Lischke, and Massimiliano Zappa
Hydrol. Earth Syst. Sci., 22, 4097–4124, https://doi.org/10.5194/hess-22-4097-2018, https://doi.org/10.5194/hess-22-4097-2018, 2018
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To simulate the water balance of, e.g., a forest plot, it is important to estimate the maximum volume of water available to plants. This depends on soil properties and the average depth of roots. Rooting depth has proven challenging to estimate. Here, we applied a model assuming that plants dimension their roots to optimize their carbon budget. We compared its results with values obtained by calibrating a dynamic water balance model. In most cases, there is good agreement between both methods.
Gordon C. O'Brien, Chris Dickens, Eleanor Hines, Victor Wepener, Retha Stassen, Leo Quayle, Kelly Fouchy, James MacKenzie, P. Mark Graham, and Wayne G. Landis
Hydrol. Earth Syst. Sci., 22, 957–975, https://doi.org/10.5194/hess-22-957-2018, https://doi.org/10.5194/hess-22-957-2018, 2018
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In global water resource allocation, robust tools are required to establish environmental flows. In addition, tools should characterize past, present and future consequences of altered flows and non-flow variables to social and ecological management objectives. PROBFLO is a risk assessment method designed to meet best practice principles for regional-scale holistic E-flow assessments. The approach has been developed in Africa and applied across the continent.
Katrina E. Bennett, Theodore J. Bohn, Kurt Solander, Nathan G. McDowell, Chonggang Xu, Enrique Vivoni, and Richard S. Middleton
Hydrol. Earth Syst. Sci., 22, 709–725, https://doi.org/10.5194/hess-22-709-2018, https://doi.org/10.5194/hess-22-709-2018, 2018
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We applied the Variable Infiltration Capacity hydrologic model to examine scenarios of change under climate and landscape disturbances in the San Juan River basin, a major sub-watershed of the Colorado River basin. Climate change coupled with landscape disturbance leads to reduced streamflow in the San Juan River basin. Disturbances are expected to be widespread in this region. Therefore, accounting for these changes within the context of climate change is imperative for water resource planning.
Fernando Jaramillo, Neil Cory, Berit Arheimer, Hjalmar Laudon, Ype van der Velde, Thomas B. Hasper, Claudia Teutschbein, and Johan Uddling
Hydrol. Earth Syst. Sci., 22, 567–580, https://doi.org/10.5194/hess-22-567-2018, https://doi.org/10.5194/hess-22-567-2018, 2018
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Which is the dominant effect on evapotranspiration in northern forests, an increase by recent forests expansion or a decrease by the water use response due to increasing CO2 concentrations? We determined the dominant effect during the period 1961–2012 in 65 Swedish basins. We used the Budyko framework to study the hydroclimatic movements in Budyko space. Our findings suggest that forest expansion is the dominant driver of long-term and large-scale evapotranspiration changes.
Jie Zhu, Ge Sun, Wenhong Li, Yu Zhang, Guofang Miao, Asko Noormets, Steve G. McNulty, John S. King, Mukesh Kumar, and Xuan Wang
Hydrol. Earth Syst. Sci., 21, 6289–6305, https://doi.org/10.5194/hess-21-6289-2017, https://doi.org/10.5194/hess-21-6289-2017, 2017
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Forested wetlands provide myriad ecosystem services threatened by climate change. This study develops empirical hydrologic models by synthesizing hydrometeorological data across the southeastern US. We used global climate projections to model hydrological changes for five wetlands. We found all wetlands are predicted to become drier by the end of this century. This study suggests that climate change may substantially affect wetland biogeochemical cycles and other functions in the future.
Guiomar Ruiz-Pérez, Julian Koch, Salvatore Manfreda, Kelly Caylor, and Félix Francés
Hydrol. Earth Syst. Sci., 21, 6235–6251, https://doi.org/10.5194/hess-21-6235-2017, https://doi.org/10.5194/hess-21-6235-2017, 2017
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Plants are shaping the landscape and controlling the hydrological cycle, particularly in arid and semi-arid ecosystems. Remote sensing data appears as an appealing source of information for vegetation monitoring, in particular in areas with a limited amount of available field data. Here, we present an example of how remote sensing data can be exploited in a data-scarce basin. We propose a mathematical methodology that can be used as a springboard for future applications.
Rui Rivaes, Isabel Boavida, José M. Santos, António N. Pinheiro, and Teresa Ferreira
Hydrol. Earth Syst. Sci., 21, 5763–5780, https://doi.org/10.5194/hess-21-5763-2017, https://doi.org/10.5194/hess-21-5763-2017, 2017
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We analyzed the influence of considering riparian requirements for the long-term efficiency of environmental flows. After a decade, environmental flows disregarding riparian requirements promoted riparian degradation and consequently the change in the hydraulic characteristics of the river channel and the modification of the available habitat area for fish species. Environmental flows regarding riparian vegetation requirements were able to sustain the fish habitat close to the natural condition.
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evapotranspiration and gross primary production in 2002–2017, Remote Sens.
Environ., 222, 165–182, https://doi.org/10.1016/j.rse.2018.12.031, 2019.
Short summary
The novel hybrid predictive modeling (HPM) approach uses a long short-term memory recurrent neural network to estimate evapotranspiration (ET) and ecosystem respiration (Reco) with only meteorological and remote-sensing inputs. We developed four use cases to demonstrate the applicability of HPM. The results indicate HPM is capable of providing ET and Reco estimations in challenging mountainous systems and enhances our understanding of watershed dynamics at sparsely monitored watersheds.
The novel hybrid predictive modeling (HPM) approach uses a long short-term memory recurrent...