HS10.9 | Coupling of the terrestrial water and carbon cycles
EDI
Coupling of the terrestrial water and carbon cycles
Co-organized by BG3
Convener: Huimin Lei | Co-conveners: Stan Schymanski, Yuting Yang, Anke Hildebrandt, Yanlan LiuECSECS
Orals
| Fri, 19 Apr, 14:00–15:30 (CEST)
 
Room 2.15
Posters on site
| Attendance Thu, 18 Apr, 16:15–18:00 (CEST) | Display Thu, 18 Apr, 14:00–18:00
 
Hall A
Orals |
Fri, 14:00
Thu, 16:15
The terrestrial water and carbon cycles are tightly coupled through gas diffusion in plant stomata (physiological effect) and the greenhouse gas (GHG) forcing of CO2 on climate (GHG effect). Those two effects (physiological and GHG) simultaneously affect the terrestrial energy, water, and carbon cycles. Facing a continuous increase in atmospheric CO2 concentrations, the interaction between the global carbon and water cycles has emerged as a critical topic in hydrological science, and it has profound implications for water resources. This session invites submissions addressing (1) coupled modeling of carbon and water fluxes, including crop yields, and/or biomass and mineral carbon sequestration, (2) observation-based assessments of interactions between the terrestrial water and carbon cycles across different scales, including their sensitivity to climatic extremes such as droughts and heat waves, (3) impact of climate change on the interactions between water and carbon cycles, (4) theory linking transpiration and photosynthesis, such as optimality hypotheses, and (5) sustainable land management practices preserving/enhancing water resources and carbon stocks. Submissions introducing promising, new observation techniques, modeling approaches, or novel theories are particularly welcomed.

Orals: Fri, 19 Apr | Room 2.15

The oral presentations are given in a hybrid format supported by a Zoom meeting featuring on-site and virtual presentations. The button to access the Zoom meeting appears just before the time block starts.
Chairpersons: Huimin Lei, Anke Hildebrandt
14:00–14:20
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EGU24-2261
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HS10.9
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solicited
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Virtual presentation
Dan Yakir, Eyal Rotenberg, Fyodor Tatarinov, and Jonathan Muller

Climate change is predicted to change precipitation (P) and evapotranspiration (ET) over most land areas, imposing substantial pressure on water supply in some parts, while increasing flooding in others. Our global dataset shows that ET from ecosystems displays a conservative ‘saturation effect’ at ~460±190 mm across climates with P range of ~4000 mm. This implies that changes in P are preferentially reflected in the residual ecosystem water yield (WY=P-ET). Consequently, changes in WY are greatly enhanced compared with those in P both in observations and in model-based future projections. In drying regions, ecosystems will reach the unsustainable state of WY<0 faster than expected based on predicted changes in P alone, imposing land cover changes, and impacting water availability for ecological and societal needs.

How to cite: Yakir, D., Rotenberg, E., Tatarinov, F., and Muller, J.: Enhanced effects of declining precipitation on the water yield and ecosystem sustainability , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2261, https://doi.org/10.5194/egusphere-egu24-2261, 2024.

14:20–14:30
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EGU24-647
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HS10.9
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ECS
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Virtual presentation
Akash Verma and Subimal Ghosh

Socioeconomic growth in India has resulted in a substantial increase in carbon dioxide (CO2) emissions. Despite this, India emerges as the second-largest contributor to global greening, as revealed by remote sensing datasets. These conflicting factors pose a unique challenge in understanding the variability of atmospheric CO2 and its implications for global warming. The present study aims to address this research gap by presenting the first analysis of climate controls on carbon flux variability in India. Our key objectives are (1) to identify the climate drivers influencing the variability of vegetation productivity in agriculture-dominated India and (2) to understand the implications of increased plant growth on water availability by analyzing the CO2 fertilization effect. Unlike previous studies, we have not used simplistic estimates like partial correlation for causality; instead, we employed a recent tool, PCMCI, designed explicitly for detecting causality. In contrast to global studies, we find no causal connection between terrestrial water storage and vegetation productivity. Our results suggest that precipitation plays a significant role in the Indian region rather than deep groundwater, due to its immediate impact on shallow-rooted vegetation. Our findings highlight the significance of land use, land cover, and distinct irrigation practices— aspects often overlooked in current land surface models. Furthermore, we are investigating the response of soil moisture to CO2 fertilization via two pathways: increased leaf area index (LAI) and enhanced water use efficiency (WUE) using state-of-the-art CMIP6 simulations. We are evaluating whether WUE can ameliorate plant water stress, especially when the LAI can counteract its impact by increasing transpiration. The present study adopts a holistic approach to demonstrate the critical interaction and feedback between climate controls, vegetation, and CO2 fertilization, thereby significantly improving our understanding of land-atmosphere interaction.

Keywords: Climate controls, CO2 fertilization, Soil moisture, Vegetation productivity, Causal discovery

How to cite: Verma, A. and Ghosh, S.: Connecting the Carbon and Water Cycles through Vegetation   , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-647, https://doi.org/10.5194/egusphere-egu24-647, 2024.

14:30–14:40
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EGU24-3306
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HS10.9
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On-site presentation
Binghao Jia and Qing Peng

The soil freeze-thaw process has undergone significant changes on the Tibetan Plateau (TP) in the context of global change, resulting in the changes of soil physical and chemical properties, thereby affecting the vegetation phenology and photosynthesis through affecting the utilization capacity of CO2 and light by vegetation. However, little is known about how soil temperature (ST) and soil moisture (SM) affect the gross primary productivity (GPP) on the TP at different seasons and elevations. In this study, the spatiotemporal variation patterns of GPP, ST, and SM were analyzed based on the Community Land Model version 5.0 (CLM5.0) simulations in order to illustrate the impacts of ST and SM in surface (0–10 cm) and root zone soil (0–100 cm) on GPP between 1979 and 2020. The results showed that the CLM5.0-based GPP and ST were in good agreement with in situ observations. ST, SM and GPP increased at the rates of 0.04 ℃ a−1, 2.4 × 10−4 mm3 mm−3 a−1, and 5.36 g C m−2 a−2, respectively. SM dominated the variations of GPP in winter (64.3%), while ST almost was the dominant factor in other periods, especially spring (99.9%) and autumn (94.7%). The explanatory power of ST and SM for GPP increased with elevation, especially for ST. The relative contributions of ST and SM to GPP at different time scales in root zone soil were similar to those in surface soil. This study provided a new understanding of how soil freeze-thaw affected GPP changes on the TP in the context of the intensification of warming and humidification.

How to cite: Jia, B. and Peng, Q.: Increasing gross primary productivity under soil warming and wettingon the Tibetan Plateau, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3306, https://doi.org/10.5194/egusphere-egu24-3306, 2024.

14:40–14:50
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EGU24-9401
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HS10.9
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On-site presentation
Martin Bouda, Jan Vanderborght, Valentin Couvreur, Václav Šípek, and Mathieu Javaux

Mechanistic representation of soil-root hydrodynamics is necessary to make robust predictions of canopy fluxes (transpiration, photosynthesis) under water limitation. Soil water limitation can arise at a range of characteristic scales down to millimetres but its effects can be felt across entire landscapes. This mismatch between the scales of cause and effect makes representing water limitation a central challenge in Earth System Models (ESM) and a key source of uncertainty in the terrestrial carbon cycle. We aim to unify the description of soil-root water flows across scales to bridge this gap and to demonstrate cross-scale effects of root ecophysiological mechanisms on the water and carbon cycles.

We developed a new model formulation from analytical solutions to the differential equations for flows on root networks. By formulating the integrals in terms of mean water potentials over arbitrary root segments, we obtain a linear system directly without introducing a numerical approximation. Partial Gaussian elimination then yields a system of exact equations for mean water potentials in the absorbing roots at any chosen scale.

The upscaled equations reproduce exact solutions for water potentials and flows on a single plant at any scale under set boundary conditions. Fitted to explicit stand-scale simulations, the model shows non-increasing error with the addition of further plants to the explicit simulation set. Proof-of-concept results show improved agreement with field data during a seasonal drought over previous models. The computational cost of these calculations is lower or equal to methods present in ESM and other upscaling methods. Code for producing the upscaled equations for any root hydraulic architecture is available online for beta testing.

We will use this model formulation to connect observations of plant hydrodynamic functioning across scales. We are currently collecting data on root growth, turnover, and soil-plant hydrodynamics at six instrumented forest sites. We will supplement these observations with lab-based measurements at root and plant scale. By using the model to bridge across the scales of observation, we expect to quantify the cross-scale effects of individual mechanisms, such as the effect of root phenology on the seasonal variation in land-atmosphere hydrodynamics. This will be an important step towards reducing uncertainties in the plant-mediated processes that link the terrestrial carbon and water cycles.

How to cite: Bouda, M., Vanderborght, J., Couvreur, V., Šípek, V., and Javaux, M.: Quantifying cross-scale hydrodynamic effects of root ecophysiology, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9401, https://doi.org/10.5194/egusphere-egu24-9401, 2024.

14:50–15:00
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EGU24-2670
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HS10.9
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Virtual presentation
Ehud Strobach, Roi Ben-David, Avimanyu ray, and Yotam Menachem

Wheat production accounts for the largest portion of agricultural land in Israel, and it is the 2nd most productive crop worldwide after Maize. Spring wheat which is mostly grown under rain-fed conditions, is highly susceptible to changes in climate conditions. As a result, wheat grain yields (GY) are suffering from high climate-dependent year-to-year variability, particularly under changes in precipitation patterns. This large variability stresses the need for accurate seasonal predictions of wheat yield, which may assist farmers in better agro-system planning, making the right management decisions (crop rotation, sowing dates and application of irrigation), and the right varietal choice. As a widespread crop, wheat also has the potential to impact regional climate conditions through an interactive feedback loop by exchanging heat and water with the land surface and the atmosphere above. Yet, current seasonal crop yield prediction systems do not account for climate-crop feedback, and their prediction skill is lacking.

The current study hypothesizes that using a high-resolution regional climate model (WRF) coupled with a crop model (Noah-MP-Crop) may increase seasonal crop yield prediction skill, providing a practical tool for farmers to increase their revenues and increase food security. To confirm this hypothesis, we have adapted the Noah-MP-Crop model for the spring wheat cultivars grown in Israel and conducted coupled simulations using the updated observed crop model parameters. In this presentation, the in-situ calibration process of the crop model to the spring wheat cultivars grown in Israel will be presented together with several simulated results from the calibrated coupled crop-climate model. A focus will be put on the exchange of heat, water, and carbon between the land surface and the lower atmosphere.

How to cite: Strobach, E., Ben-David, R., ray, A., and Menachem, Y.: Towards a coupled crop-climate seasonal prediction system for dry-land wheat grain yield in Israel, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2670, https://doi.org/10.5194/egusphere-egu24-2670, 2024.

15:00–15:10
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EGU24-16184
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HS10.9
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ECS
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On-site presentation
Elisa Stefaniak, Jens de Bruijn, Mikhail Smilovic, Silvia Artuso, Juliette Martin, Tania Maxwell, Jaideep Joshi, and Florian Hofhansl

The recently developed Plant-FATE (Plant Functional Acclimation and Trait Evolution) model is a trait-size-structured eco-evolutionary population model derived from the ‘Plant’ model. It includes a McKendrick-von Foerster partial differential equation (PDE) describing how the size distribution of each species evolves through time. The trait structure allows for modelling functional diversity and adaptations, whereas size structure allows for modelling competition for light. Plant-FATE also includes a new P-hydro model for optimal photosynthesis, the ‘perfect plasticity approximation’ for modelling optimal crown placement, and an extended version of the T-model for biomass allocation. Forced with climatic variables and soil-water availability, Plant-FATE can predict emergent species compositions, size-distributions, and ecosystem services such as leaf area, productivity, evapotranspiration, living biomass, and seed output. 

Plant-FATE currently predicts vegetation properties and associated ecosystem functions of areas under forest cover. To analyse the -water-biodiversity nexus, it is necessary to cover additional aspects of areas under different land-use, such as croplands, plantations, and urban areas. To that end, we have coupled PlantFATE with a Community Water Model (CWatM) that captures ground water discharge and simulates basin-wide water circulation. CWatM is an open-source model to examine how future water demand will evolve in response to socioeconomic change and how water availability will change in response to climate.  

As a case study, we apply this coupled model to the Bhima Basin to examine the feedback between forest management and land-use. This coupling will enable us to better represent nexus issues, such as the feedback between biodiversity and ecosystem functioning that affect vegetation carbon storage and water provisioning under future land-use and projected climate change scenarios.

How to cite: Stefaniak, E., de Bruijn, J., Smilovic, M., Artuso, S., Martin, J., Maxwell, T., Joshi, J., and Hofhansl, F.: Modelling Water and Biodiversity: Coupling a dynamic eco-evolution trait-based vegetation model with a community water model , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16184, https://doi.org/10.5194/egusphere-egu24-16184, 2024.

15:10–15:20
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EGU24-19078
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HS10.9
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On-site presentation
Clara Gabaldón-Leal, Álvaro Sánchez-Virosta, Carolina Doña, José González-Piqueras, Juan Manuel Sánchez, and Ramón López-Urrea

Climate change projections indicate a significant increase in greenhouse gas (GHG) emissions, leading to elevated temperatures, extreme weather events, and water scarcity, particularly in regions like southern Europe. Agriculture, forestry, and other land use activities contribute to 22% of these emissions, but they also offer the potential to act as carbon sinks, supporting the transition to a climate-neutral economy as outlined in the Paris Agreement. The concept of carbon offset involves compensating for emissions by reducing, avoiding, or sequestering an equivalent amount of CO2. Practices such as carbon credits could provide new economic incentives through participation in the voluntary carbon market.

Hence, it is crucial to develop reliable methods to quantify carbon dynamics in terrestrial ecosystems, focusing on the relationship between carbon energy parameters; Net Ecosystem Exchange (NEE), Ecosystem Respiration, and Gross Primary Productivity (GPP). In Spain, the rise in irrigated almond orchards, particularly in the La Mancha region, highlights the need to understand ecosystem Water Use Efficiency (WUE) as a crucial parameter for sustainable crop management. The study employs Eddy Covariance (EC) flux towers to measure NEE, ET, and GPP, providing valuable insights into WUE and contributing to carbon cycle assessments and climate change mitigation strategies.

This study spanned six almond growing seasons (2017-2022) in two different drip-irrigated almond orchards locations in Albacete (SE Spain). These orchards, meeting minimum fetch requirements, exhibited a notable carbon-fixing capacity, comparable to other natural and agroecosystems. Seasonal variability and environmental influences were evident throughout the six-year study. In this study, we also modelled WUE as a function of remote sensing vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and meteorological data.

Seasonal variability, age and density of almond orchards significantly influence on the observed GPP and NEE. Almond orchards captured more CO2 than that released between April and October. The maximum monthly GPP values observed by EC was 263.7 g C m-2. Besides, the combination NDVI and ET proved effective in estimating GPP, with a regression coefficient (R2) of 0.78. Modelled WUE, incorporating 'NDVI, potential evapotranspiration (ETo), and air temperature (Tair),' strikes an optimal balance between explanatory capacity and simplicity. While showing promise with determination coefficients of 0.88 and 0.86, caution is advised due to the limited sample size, necessitating future further validation with larger datasets. Nevertheless, this approach could be a valuable tool for stakeholders addressing efficient water use challenges in agriculture. This study highlights the importance of quantifying carbon uptake and ecosystem water use efficiency by almond orchards as a strategy for mitigating climate change.

How to cite: Gabaldón-Leal, C., Sánchez-Virosta, Á., Doña, C., González-Piqueras, J., Sánchez, J. M., and López-Urrea, R.: Carbon Sequestration and Water Use Efficiency on almond orchards. Towards a remote sensing-based approach to monitor GPP, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19078, https://doi.org/10.5194/egusphere-egu24-19078, 2024.

15:20–15:30
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EGU24-19929
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HS10.9
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Virtual presentation
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Salim Goudarzi, Chris Soulsby, Jo Smith, Jamie Stevenson, Alessandro Gimona, Iris Aalto, Steven Hancock, and Josie Geris

Agroforestry has been suggested as a promising Nature-Based Solution (NBS) due to its potential benefits including soil water regulation and carbon storage, both of which are expected to become increasingly more important under current climate projection scenarios. But it is unclear to what degree these benefits: (i) are likely to be realised individually; and (ii) may interact/counteract with one another. While common in the tropics, agroforestry in the UK and other temperate areas is still limited. Especially given the lack of data, predicting adaptability and optimising environmental benefits of agroforestry systems in temperate regions requires a parsimonious and robust coupled water-carbon modelling approach. Soil carbon models typically tend to use simplistic soil moisture accounting (e.g., rainfall minus PET) and could yield considerably different predictions under more realistic soil moisture representations. However, while large-scale surface and above surface satellite datasets are now readily available, below-ground soil moisture datasets are either not available, not as accurate, or not on the same scale. This is particularly an issue in systems involving trees because they impact soils in general, but soil moisture in particular, at depths much greater than those covered by global satellites. Here, we present a new 1D ecohydrological model that encompasses the main soil-tree-atmospheric interactions while only requiring rainfall, potential evapotranspiration and surface soil moisture information for its calibration, making the model well-suited to be applied in conjunction with limited available datasets (e.g., those from satellites). We first demonstrate the ecohydrological model’s performance in profile soil moisture estimation using only surface information in a data-rich site in Scotland. We then couple this new model with the widely used RothC carbon model for an agroforestry site nearby. Our results show that CO2 emission estimates by RothC change considerably when a more realistic soil moisture accounting is incorporated. Finally, we explore these effects under different agroforestry and future (50-year) climate projection scenarios to inform appropriate agroforestry designs.

How to cite: Goudarzi, S., Soulsby, C., Smith, J., Stevenson, J., Gimona, A., Aalto, I., Hancock, S., and Geris, J.: Coupled water-carbon modelling at data-limited sites: a new approach to explore current and future agroforestry scenarios in Scotland, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19929, https://doi.org/10.5194/egusphere-egu24-19929, 2024.

Posters on site: Thu, 18 Apr, 16:15–18:00 | Hall A

The posters scheduled for on-site presentation are only visible in the poster hall in Vienna. If authors uploaded their presentation files, these files are linked from the abstracts below, but only on the day of the poster session.
Display time: Thu, 18 Apr 14:00–Thu, 18 Apr 18:00
Chairpersons: Stan Schymanski, Anke Hildebrandt, Huimin Lei
A.101
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EGU24-3348
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HS10.9
chaojie niu and Caihong Hu

The key factor influencing flood evolution and the progression of riverbed erosion and silting in the wide floodplain of the Lower Yellow River (LYR) is channel roughness. The distribution law of channel roughness has changed since the implementation of water storage and sand control in Xiaolangdi Reservoir in 2002, and the change in roughness has had a number of effects on the design of flood control projects and ecological environment protection planning of the lower reaches. Manning's formula was used to calculate the roughness based on cross-section data and hydrological data collected by typical hydrological stations in the wide floodplain of the LYR from 2002 to 2020. The evolution law and influencing factors of channel roughness of typical sections before and after floods were also examined. The findings indicate that: (1) The post-flood roughness was slightly higher than the pre-flood roughness in the same area. The post-flood roughness in the Huayuankou and Sunkou sections significantly increased compared to the pre-flood roughness, with an increase rate of 14.64% and 19.37%, respectively. (2) The time-to-space variation of roughness in the wandering section exhibits a decreasing trend, whereas the time-to-space variation of roughness in the transition section exhibits a slightly increasing trend. (3) The channel roughness decreases with an increase in Froude number, but there is no clear relationship between the roughness and sediment content. (4) Using Huayuankou and Gaocun stations as examples, the channel roughness is inversely proportional to the flow, the average sectional velocity, and the cross-section area of the flow. The channel roughness of the wandering section is inversely proportional to the ratio of width to depth, and the channel roughness of the transition section is proportional to the ratio of width to depth. Roughness and average velocity were determined to have the best-fitting connection, with R2 values of 0.62 and 0.78, respectively. (5) The main elements impacting channel roughness in the wide floodplain of the LYR are section shape and flow condition.

How to cite: niu, C. and Hu, C.: Evolution of channel roughness and influencing factors in the wide floodplain of the Lower Yellow River in recent 20 years, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3348, https://doi.org/10.5194/egusphere-egu24-3348, 2024.

A.102
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EGU24-3593
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HS10.9
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Haiyang Qian, Weiguang Wang, Zefeng Chen, Akash Koppa, Guoshuai Liu, and Diego Miralles

The net physiological effect of rising atmospheric carbon dioxide (aCO2) on terrestrial evaporation (ET) is highly uncertain. While increased CO2 fertilization elevates ET through more biomass production, the reduction in stomatal conductance (gs) that it downregulates ET. Here, using satellite-based estimates of ET and dynamic vegetation models, we investigate the physiological influence of aCO2 on ET, and isolate the respective contribution of biomass increase and gs reduction. Our results indicate that the CO2 fertilization had a net negative effect of –4.4±0.3×10–2 mm ppm–1 on ET over 1982–2018. The negative physiological effect tends to intensify with increasing aCO2, particularly in warm and humid forests. The high sensitivity of ET to gs may attenuate the expected water cycle acceleration over land, although the future evolution of these two competing physiological processes remains uncertain.

How to cite: Qian, H., Wang, W., Chen, Z., Koppa, A., Liu, G., and Miralles, D.: Recent intensification of the negative physiological effect of CO2 on terrestrial evaporation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3593, https://doi.org/10.5194/egusphere-egu24-3593, 2024.

A.103
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EGU24-4949
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HS10.9
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ECS
Hui Guo

Macro-scale hydrological/land surface models are important tools for assessing historical and predicting future characteristics of extreme hydrological events, yet quantitative understandings of how these large-scale models perform in simulating extreme hydrological characteristics remain limited. Here we evaluate simulated high- and low-flows from 23 macro-scale models within three modeling experiments (i.e., 14 climate models from CMIP6, 6 global hydrological models from ISIMIP2a and 3 land surface models from GLDAS) against observation in 633 unimpaired catchments globally over 1971-2010. Our findings reveal limitations in simulating extreme flow characteristics by these models. Specifically, we find that (i) most models overestimate high-flow magnitudes (bias range: +15% to +70%) and underestimate low-flow magnitudes (bias range: -80% to -20%); (ii) interannual variability in high- and low-flows is reasonably reproduced by ISIMIP2a and GLDAS models but poorly reproduced by CMIP6 models; (iii) no model consistently replicates the observed trend direction in high- and low-flows in over two-thirds of the catchments, and most models overestimate high-flow trends and underestimate low-flow trends; and (iv) CMIP6 and GLDAS models show timing biases, with early high-flows and late low-flows, while ISIMIP2a models exhibit the opposite pattern. Furthermore, all models performed better in more humid environments and non-cold regions, with model structure and parameterization contributing more to uncertainties than climatic forcings. Overall, our results demonstrate that extreme flow characteristics simulated from current state-of-the-art macro-scale models still contain large uncertainties and provide important guidance regarding the robustness of assessing extreme hydrometeorological events based on these modeling outputs.

How to cite: Guo, H.: Global evaluation of simulated high- and low-flows from 23 macro-scale models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4949, https://doi.org/10.5194/egusphere-egu24-4949, 2024.

A.104
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EGU24-5887
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HS10.9
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ECS
Yue Wang, Guangyao Gao, Yanzhang Huang, and Zhuangzhuang Wang

Water use efficiency (WUE) and carbon use efficiency (CUE) in dryland ecosystems are highly sensitive to complex climate and CO2 changes, which may cause imbalance between carbon and water cycles in terrestrial ecosystems. However, the mechanism of the systematic effects of multiple factors on WUE and CUE remains unclear. Here, we examined the trends in WUE and CUE in China’s Loess Plateau during 2001-2020 and assessed the underlying drivers using PML_V2 products and satellite-based data by employing the spatial random forest (SRF) method. Our analysis identified a significantly increasing trend in WUE and a slightly downward trend in CUE. In space, NDVI was the most important factor affecting the spatial variation of WUE and CUE, but WUE had a significant positive response to NDVI, while CUE had a significant negative response to NDVI. Precipitation and CO2 concentration were the most important environmental factors driving spatial variability in WUE and CUE, respectively. However, vapor pressure deficit was the most important factor driving CUE annual variation controlling most areas of the greening region. Our research revealed that despite the improvement in water utilization, the greening of vegetation did not enhance carbon sequestration potential in the Loess Plateau. Furthermore, we demonstrated that vegetation was the most important factor causing WUE spatiotemporal variation and CUE spatial variation, while atmospheric drought inhibiting vegetation growth was the most important factor causing CUE temporal variation, reflecting the interactivity and complexity of the driving factors behind the spatial and temporal variability of WUE and CUE. Our study provides new insights into the driving characteristics of WUE and CUE spatiotemporal variability and enhances the knowledge of how the carbon-water coupling process induced by vegetation greening responds to environmental changes in arid and semi-arid regions in the backdrop of climate change, contributing to ecological restoration practices and sustainable management in the dryland.

How to cite: Wang, Y., Gao, G., Huang, Y., and Wang, Z.: Water use efficiency and carbon use efficiency response differently to greening on the Loess Plateau in China, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5887, https://doi.org/10.5194/egusphere-egu24-5887, 2024.

A.105
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EGU24-6713
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HS10.9
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ECS
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Zihan Yan, Taihua Wang, and Dawen Yang

Ecological Restoration (ER) measures can achieve considerable carbon benefits and reduce sediment loads, concurrently resulting in unintended hydrological consequences. The Middle Yellow River Basin (MYRB), with intensive large-scale ER implementation during the past decades, serves as an excellent case to investigate the concomitant water-carbon-sediment synergies and trade-offs. This study combined a vegetation dynamics simulation scheme and a distributed hydrological model with explicit ER representation to investigate the water-sediment-carbon changes in response to ER in the MYRB. According to the results, ER promoted synergies between carbon sequestration and sediment control and led to improved water use efficiency (WUE). The actual Leaf Area Index and Gross Primary Productivity (GPP) showed improvements in region-averaged values by +0.56 m2 m-2 yr-1 (+7.4%) and +52 gC m-2 yr-1 (+10.9%) compared to those under natural conditions. In the Toudaoguai-Tongguan section which suffered the most serious soil erosion, ER decreased the sediment loads by 11.3×108 ton yr-1 (71.1% of the natural level). Furthermore, WUE changes indicated higher GPP gain per unit evapotranspiration. Meanwhile, trade-offs were also found when taking account of the water yield reduction. During 1982-2019, ER led to significant increases in actual evapotranspiration (+8.3 mm yr-1; +2.2%) and decreases in runoff (-7.6 mm yr-1; -12.7%). Two indicators evaluating the cost-effectiveness of ER, i.e., carbon sequestration and sediment settlement at the cost of per unit runoff decline, remained positive with the average values of 6.12 kgC m-3H2O yr-1 and 0.22 ton m-3H2O yr-1 during 2000-2019, respectively. Nevertheless, both indicators showed downward trends, indicating decreasing marginal benefits brought by ER measures which could have approached the optimal scale in the MYRB.

How to cite: Yan, Z., Wang, T., and Yang, D.: Water-carbon-sediment synergies and trade-offs: multi-faceted impacts of large-scale ecological restoration in the Middle Yellow River Basin, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6713, https://doi.org/10.5194/egusphere-egu24-6713, 2024.

A.106
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EGU24-7198
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HS10.9
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ECS
|
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Gabrielle Burns, Keirnan Fowler, Clare Stephens, and Murray Peel

Hydrological models, ranging from conceptual frameworks to complex physical representations, play a pivotal role in diverse applications including climate change projections and characterising floods and droughts. One crucial aspect of these models is the incorporation of vegetation dynamics, often achieved through links to evapotranspiration and interception. Our study will delve into the critical role of evapotranspiration in the terrestrial water cycle, and how this intricate relationship is simplified across various hydrological models.

Despite the versatility of hydrological models, a common limitation is the static representation of vegetation over time. This limitation becomes particularly significant under climate change, where the consequences of altered vegetation behaviour might not be accurately reflected in the model results. Our research will address this gap by exploring numerous evapotranspiration equations utilised by conceptual rainfall-runoff models, by employing a novel rainfall-runoff model comparison toolbox (MARRMoT), and integrating flux tower measurements into the calibration processes.

By examining how different evapotranspiration equations are utilised across the models and integrating flux tower measurements into the hydrological modelling processes, we seek to improve the models' adaptability to changing environmental conditions. We will do this by interchanging the numerous evapotranspiration equations, whilst keeping all other aspects of the hydrological model constant to explore potential benefits and differences among methods. Further, we will include in-situ measurements by calibrating the model outputted actual-evapotranspiration to flux tower evapotranspiration data, as well as the traditionally calibrated streamflow data.

This research contributes to advancing the accuracy of hydrological predictions and improving the reliability of models in forecasting catchment responses to future climatic shifts.

How to cite: Burns, G., Fowler, K., Stephens, C., and Peel, M.: Investigating evapotranspiration calculations within conceptual hydrological models: an intercomparison among models. , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7198, https://doi.org/10.5194/egusphere-egu24-7198, 2024.

A.107
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EGU24-8706
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HS10.9
qiying yu and Caihong Hu

Baseflow is a crucial water source in the inland river basins of high-altitude cold regions, playing a significant role in maintaining runoff stability. Analyzing the impact of climate change and underlying surface conditions on base flow, based on scientifically separating baseflow, is helpful for maintaining river ecological health and rational water resource allocation, especially in severely water-scarce high-altitude cold regions. The challenge lies in selecting the most suitable base flow separation method in data-scarce high-altitude cold regions, qualitatively analyzing the effects of climate factors and underlying surface changes on baseflow values and seasonal distribution characteristics, and providing interpretable scientific predictions for baseflow changes. Therefore, this study aims to contribute further to cold region hydrology by addressing the gap in understanding how meteorological factors and underlying surface changes under the backdrop of climate change affect base flow more reasonably and comprehensively. The study introduces the Grey Wolf Optimizer Digital Filter Method (GWO-DFM) for rapid baseflow separation, utilizes the Long Short-Term Memory (LSTM) neural network model for scientific base flow prediction, and explores the interpretability of the LSTM model in base flow forecasting. The proposed method was successfully implemented using a 63-year time series (1958-2020) of flow data from the Tairan River basin in the high-altitude cold region, along with 21 years of ERA5 meteorological data and MODIS data (2000-2020). The results indicate that: (1) GWO-DFM can rapidly identify optimal filtering parameters, and compared with three other methods (Eckhardt filter, Boughton-Chapman, and Chapman-Maxwell), the average base flow separation using GWO-DFM as the best method for the high-altitude cold region significantly increased after the second baseflow rate mutation. (2) Baseflow sources are mainly influenced by precipitation infiltration, glacier frozen soil layers, and seasonal ponding. (3) Solar radiation, temperature, precipitation, and NDVI are the primary factors influencing base flow changes, with Nash-Sutcliffe efficiency coefficients exceeding 0.78 in both the LSTM model training and prediction periods. (4) Changes in base flow are most influenced by solar radiation, temperature, and NDVI.

How to cite: yu, Q. and Hu, C.: Interpretable Baseflow Segmentation and Prediction Based on Numerical Experiments and Deep Learning, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8706, https://doi.org/10.5194/egusphere-egu24-8706, 2024.

A.108
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EGU24-10072
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HS10.9
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ECS
Jan De Pue, Simon Munier, José Miguel Barrios, Alirio Arboleda, Pierre Baguis, Rafiq Hamdi, and Françoise Meulenberghs

Phreatic groundwater hydrology has a well-documented influence on the land water/energy/carbon cycles. To capture the resilience of the biosphere to dry spells in land surface models, it is particularly crucial to incorporate groundwater dynamics. With the ISBA-CTRIP land surface system, it is possible to perform a coupled simulation of the land surface fluxes and groundwater hydrology. Here, we evaluate this model configuration over Belgium, and focus on the quality of the simulated groundwater dynamics, soil moisture and resulting surface fluxes. A network of piezometer and eddy covariance towers is used to validate the model outcomes. Furthermore, the sensitivity of the model parametrization is analyzed (considering different pedotransfer functions), and the impact of groundwater coupling on the surface fluxes is quantified.

How to cite: De Pue, J., Munier, S., Barrios, J. M., Arboleda, A., Baguis, P., Hamdi, R., and Meulenberghs, F.: Coupled simulation of phreatic groundwater and surface fluxes from the terrestrial biosphere in Belgium, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10072, https://doi.org/10.5194/egusphere-egu24-10072, 2024.

A.109
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EGU24-14210
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HS10.9
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ECS
Jianning Ren, Zhaoyang Luo, Stefano Galelli, and Simone Fatichi

Tropical forests account for approximately one-fourth of the global terrestrial carbon sink, playing an important role in the Earth’s carbon cycle. Importantly, mainland Southeast Asia has the densest vegetation surface but its ecohydrology is historically understudied due to the paucity of field observations and modelling studies. Leveraging on existing flux tower data, remote sensing products, and the mechanistic ecohydrological model T&C, we provide an enhanced understanding of carbon and water exchanges in mainland Southeast Asia. The T&C model is tested to reproduce various ecosystem types of Southeast Asia, including tropical evergreen forests, subtropical deciduous forests, savannas, rubber plantations, and rice fields. The flux tower data including gross primary productivity (GPP) and evapotranspiration (ET) along with remote sensing data of leaf area index and other vegetation indexes, allow us to better refine and constrain model simulations.  With the integration of data and model, we provide a comprehensive picture of spatiotemporal patterns and key drivers of carbon and water fluxes in mainland Southeast Asia. Our findings highlight a strong latitudinal gradient in carbon fluxes and ET associated with seasonality of rainfall as well as an important role of vapour pressure deficit (VPD) and soil moisture content with different responses in wet and dry years. Direct effects of temperature and precipitation are relatively smaller when compared to VPD and soil moisture in driving changes of carbon and water fluxes. These findings, combined with our model framework, pave the road to more accurate predictions of ecohydrological variables in the relatively understudied region of mainland Southeast Asia.

How to cite: Ren, J., Luo, Z., Galelli, S., and Fatichi, S.: Combining mechanistic modelling and observations to characterize carbon and water fluxes in mainland Southeast Asia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14210, https://doi.org/10.5194/egusphere-egu24-14210, 2024.

A.110
|
EGU24-16625
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HS10.9
Stan Schymanski, Martin Schlerf, Richard Keim, and Jean François Iffly

Connecting environmental conditions with plant growth and stress is an important part of ecosystem management in the context of a rapidly changing climate. Our understanding of how varying growing conditions (e.g., soil water availability, meteorological conditions) translate into plant stress and recovery continues to be thwarted by technical limitations in the monitoring of environmental conditions at the appropriate spatio-temporal scale and signs of stress and recovery at the plant and ecosystem scale.

One of the most limiting factors to plant growth is water availability and an important stressor is drought. During drought, physiological changes induce a reduction in photosynthesis and thus plant growth. However, intensity and duration of water stress conditions determine the plant’s physiological response. Under mild water stress, plant regulation of water loss and uptake still allows the plant to maintain its water status with little change in photosynthetic efficiency. However, severe water stress leads to effects ranging from inhibition of photosynthesis and growth to xylem embolism, leaf wilting and loss of key pigments and thus irreversible damage to the photosynthetic and water transport machinery.

Several in situ measurements and remote sensing technologies have been developed to quantify plant stress and ecophysiological response to drought, each with their own strengths and limitations. For example, dendrometers can measure very small changes in stem diameter and thus record daily growth rates and water status variations , while sap flux measurements help quantifying the amount of transpired water. While these techniques are useful for quantifying individual tree responses to stress in terms of mass fluxes and plant water status, they are difficult to apply to whole forests or agricultural fields. Quantifying radiation budgets is another approach for measuring plant stress and response to droughts. Thermal infrared (TIR) and hyperspectral (visible, near-, and shortwave infrared reflectance (VNIR)/SWIR) approaches (besides sun-induced fluorescence) are widely used remote sensing techniques for the detection of plant water stress. An important advantage of remote sensing is that it can be applied to a broader spatial scale. However, the spatial resolution is often coarse and the interpretation in relation to in-situ processes can be complicated by phenological dynamics.

Here we present results from a European beech stand in Luxembourg, where we analysed continuous in situ measurements of dendrometer, sap flux, TIR canopy temperature, meteorological variables and soil moisture. We compare water stress indices derived from sap flux and dendrometer data with a TIR-based crop water stress index (CWSI) recently developed for crops (Ekinzog et al. 2022). Results are put into context with a leaf and canopy energy balance model and implications of drought stress for short and long-term carbon and water fluxes are discussed.

Literature:

Ekinzog, E. K., Schlerf, M., Kraft, M., Werner, F., Riedel, A., Rock, G., and Mallick, K.: Revisiting crop water stress index based on potato field experiments in Northern Germany, Agricultural Water Management, 269, 107664, https://doi.org/10.1016/j.agwat.2022.107664, 2022.

 

How to cite: Schymanski, S., Schlerf, M., Keim, R., and Iffly, J. F.: Detecting forest drought stress from above and from below, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16625, https://doi.org/10.5194/egusphere-egu24-16625, 2024.

A.111
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EGU24-18435
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HS10.9
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ECS
Rodolfo Nóbrega, Rodrigo Miranda, David Sandoval, Shen Tan, and Iain Colin Prentice

Hydrology has been guided by establishing empirical relationships between the movement of water through landscapes and the application of the conservation of mass law in catchments. This has resulted in models with complex calibration frameworks that often overlook the physical and biochemical water-related processes linking plants to hydrological cycles. Studies have revealed that some of the empirical relationships in catchments might also reflect a potential ecosystem's coevolution with climate, driving catchments to optimise their supply and demand limits. This agrees with the eco-evolutionary optimality principles used in vegetation modelling that are based on the hypothesis that canopy conductance acclimates to environmental variations by balancing the costs of carbon assimilation and maintenance of transpiration rates. Here, we developed meaningful interfaces between simple models and approaches based on the use of optimality principles in vegetation modelling and hydrology. Our work is based on the application of the P-model to estimate to quantify gross primary productivity and transpiration and the use of a mass-balance approach to quantify the root zone storage. These integrations not only provide a more nuanced understanding of hydrological processes but also pave the way for more accurate and physically-informed models in hydrology. Our findings underscore the potential of using eco-evolutionary principles as a unifying framework in hydrological research, offering new insights for understanding and predicting water movement in catchments under varying climatic and ecological conditions.

How to cite: Nóbrega, R., Miranda, R., Sandoval, D., Tan, S., and Prentice, I. C.: Using optimality principles to couple terrestrial carbon and water cycles in hydrological models, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18435, https://doi.org/10.5194/egusphere-egu24-18435, 2024.

A.112
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EGU24-20457
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HS10.9
David Milodowski, Mathew Williams, Luke Smallman, and Susan Steele-Dunne

Vegetation water content varies in response to the shifting balance between transpiration loss and water supply through the soil--plant--atmosphere continuum. These variations are coupled to carbon dynamics by stomatal regulation of gas exchange, linking transpiration and photosynthesis, and through rootzone soil moisture, determined in part by the allocation and turnover of carbon to roots. Microwave sensors have been demonstrated to be sensitive to variations in vegetation water content and related measures of plant hydraulic status, such as plant water potential (PWP). We use synthetic experiments representative of a European deciduous forest to explore whether time series observations of PWP can constrain an intermediate complexity terrestrial ecosystem model (DALEC) with fully coupled carbon and water balances using a Bayesian model-data fusion framework (CARDAMOM). To generate a synthetic truth, we calibrated DALEC using detailed site-specific inventory data from the Hainich ICOS site (DE-Hai), spanning 2006-2011, from which we generated a synthetic time series of average daily mean PWP. The Hainich forest is a temperate forest dominated by beech and established on clay-rich soil. We used the calibrated model as the basis for a series of synthetic data assimilation experiments under conditions of reduced data availability to represent information typically available from satellites and/or global products (e.g. Leaf Area Index, aboveground biomass, soil characteristics) to assess the potential to constrain C cycle dynamics using information on time varying PWP. We compared the diagnostics to a baseline experiment with no assimilated PWP information. Assimilation of PWP reduced the bias in estimates of GPP and ET relative to the synthetic “truth”, with a small reduction in the width of the 90% confidence range, compared to the baseline experiment. PWP observations provided more notable constraints on model parameters that were connected to plant hydraulics and water supply, including root dynamics. The emergent constraint on root dynamics is significant, because below-ground processes are inherently challenging to observe remotely. Assimilating PWP also constrained within-ensemble covariance between certain parameter pairings, and between fluxes, particularly pairings linked to the water balance, and between the water balance and productivity, highlighting the potential for enhanced constraint through the addition of complementary information. Once the signal noise exceeded 0.20 MPa, there was very limited information transfer into either the model parameters retrieved during the inversion, or the resultant fluxes. Our synthetic experiments demonstrate the potential for satellite estimates of PWP (e.g. through microwave VOD) to provide constraints on carbon-water coupling, that these constraints extend to both fast processes (GPP, ET), and slower processes (root dynamics), and that such observations would be highly complementary to C-cycle information from other EO data streams.

How to cite: Milodowski, D., Williams, M., Smallman, L., and Steele-Dunne, S.: Can time series of plant water potential constrain carbon cycle dynamics using the CARDAMOM model-data fusion framework?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20457, https://doi.org/10.5194/egusphere-egu24-20457, 2024.