Interpreting water demands of forests and grasslands within a new Budyko formulation of evapotranspiration using percolation theory

The relationship between carbon cycle and water demand is key to understanding global climate change, vegetation productivity, and predicting the future of water resources. The water balance, which enumerates the relative fractions of precipitation P that run off, Q, or are returned to the atmospher...

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Veröffentlicht in:The Science of the total environment 2023-06, Vol.877, p.162905-162905, Article 162905
Hauptverfasser: Hunt, Allen G., Sahimi, Muhammad, Faybishenko, Boris A., Egli, Markus, Ghanbarian, Behzad, Yu, Fang
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container_start_page 162905
container_title The Science of the total environment
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creator Hunt, Allen G.
Sahimi, Muhammad
Faybishenko, Boris A.
Egli, Markus
Ghanbarian, Behzad
Yu, Fang
description The relationship between carbon cycle and water demand is key to understanding global climate change, vegetation productivity, and predicting the future of water resources. The water balance, which enumerates the relative fractions of precipitation P that run off, Q, or are returned to the atmosphere through evapotranspiration, ET, links drawdown of atmospheric carbon with the water cycle through plant transpiration. Our theoretical description based on percolation theory proposes that dominant ecosystems tend to maximize drawdown of atmospheric carbon in the process of growth and reproduction, thus providing a link between carbon and water cycles. In this framework, the only parameter is the fractal dimensionality df of the root system. Values of df appear to relate to the relative roles of nutrient and water accessibility. Larger values of df lead to higher ET values. Known ranges of grassland root fractal dimensions predict reasonably the range of ET(P) in such ecosystems as a function of aridity index. Forests with shallower root systems, should be characterized by a smaller df and, therefore, ET that is a smaller fraction of P. The prediction of ET/P using the 3D percolation value of df matches rather closely results deemed typical for forests based on a phenomenology already in common use. We test predictions of Q with P against data and data summaries for sclerophyll forests in southeastern Australia and the southeastern USA. Applying PET data from a nearby site constrains the data from the USA to lie between our ET predictions for 2D and 3D root systems. For the Australian site, equating cited “losses” with PET underpredicts ET. This discrepancy is mostly removed by referring to mapped values of PET in that region. Missing in both cases is local PET variability, more important for reducing data scatter in southeastern Australia, due to the greater relief. [Display omitted] •We apply percolation theory and scaling relationships to model water balance.•Simple modifications are applied to address energy- and water-limited systems.•We tackle a number of features e.g., limits at high humidity and aridity.•We address whether forests or grasslands should have the higher evapotranspiration.
doi_str_mv 10.1016/j.scitotenv.2023.162905
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The water balance, which enumerates the relative fractions of precipitation P that run off, Q, or are returned to the atmosphere through evapotranspiration, ET, links drawdown of atmospheric carbon with the water cycle through plant transpiration. Our theoretical description based on percolation theory proposes that dominant ecosystems tend to maximize drawdown of atmospheric carbon in the process of growth and reproduction, thus providing a link between carbon and water cycles. In this framework, the only parameter is the fractal dimensionality df of the root system. Values of df appear to relate to the relative roles of nutrient and water accessibility. Larger values of df lead to higher ET values. Known ranges of grassland root fractal dimensions predict reasonably the range of ET(P) in such ecosystems as a function of aridity index. Forests with shallower root systems, should be characterized by a smaller df and, therefore, ET that is a smaller fraction of P. The prediction of ET/P using the 3D percolation value of df matches rather closely results deemed typical for forests based on a phenomenology already in common use. We test predictions of Q with P against data and data summaries for sclerophyll forests in southeastern Australia and the southeastern USA. Applying PET data from a nearby site constrains the data from the USA to lie between our ET predictions for 2D and 3D root systems. For the Australian site, equating cited “losses” with PET underpredicts ET. This discrepancy is mostly removed by referring to mapped values of PET in that region. Missing in both cases is local PET variability, more important for reducing data scatter in southeastern Australia, due to the greater relief. 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The water balance, which enumerates the relative fractions of precipitation P that run off, Q, or are returned to the atmosphere through evapotranspiration, ET, links drawdown of atmospheric carbon with the water cycle through plant transpiration. Our theoretical description based on percolation theory proposes that dominant ecosystems tend to maximize drawdown of atmospheric carbon in the process of growth and reproduction, thus providing a link between carbon and water cycles. In this framework, the only parameter is the fractal dimensionality df of the root system. Values of df appear to relate to the relative roles of nutrient and water accessibility. Larger values of df lead to higher ET values. Known ranges of grassland root fractal dimensions predict reasonably the range of ET(P) in such ecosystems as a function of aridity index. Forests with shallower root systems, should be characterized by a smaller df and, therefore, ET that is a smaller fraction of P. 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The prediction of ET/P using the 3D percolation value of df matches rather closely results deemed typical for forests based on a phenomenology already in common use. We test predictions of Q with P against data and data summaries for sclerophyll forests in southeastern Australia and the southeastern USA. Applying PET data from a nearby site constrains the data from the USA to lie between our ET predictions for 2D and 3D root systems. For the Australian site, equating cited “losses” with PET underpredicts ET. This discrepancy is mostly removed by referring to mapped values of PET in that region. Missing in both cases is local PET variability, more important for reducing data scatter in southeastern Australia, due to the greater relief. 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subjects Australia
carbon
carbon cycle
climate change
drawdown
dry environmental conditions
evapotranspiration
Forests
Grasslands
hydrologic cycle
mathematical theory
Percolation theory
prediction
reproduction
root systems
Roots
Southeastern United States
transpiration
Water balance
title Interpreting water demands of forests and grasslands within a new Budyko formulation of evapotranspiration using percolation theory
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