Simulating daily, monthly and annual water balances in a land surface model using alternative root water uptake schemes

Maayar, Mustapha El; Price, David T.; Chen, Jing M.

doi:10.1016/j.advwatres.2009.07.002

Cited by 25 publications

(16 citation statements)

References 59 publications

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“…Leaf-level photosynthesis and stomatal conductance are scaled to the canopy level separately for sun and shaded leaves, using sun/shade canopy Leaf Area Index (LAI) fractions and scaling parameters to represent extinction of nitrogen and light through the vertical canopy (Dai et al, 2004). Formulations of soil moisture availability in ISAM adapted from Oleson et al (2008) and further modified based on El Maayar et al (2009). A day-length correction factor on V cmax (maximum carboxylation rate) was also included (Bonan et al, 2011).…”

Section: Gpp and Carbon Cycle Components In Isammentioning

confidence: 99%

Climate‐driven uncertainties in modeling terrestrial gross primary production: a site level to global‐scale analysis

Barman

Jain

Liang

2014

Global Change Biology

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We used a land surface model to quantify the causes and extents of biases in terrestrial gross primary production (GPP) due to the use of meteorological reanalysis datasets. We first calibrated the model using meteorology and eddy covariance data from 25 flux tower sites ranging from the tropics to the northern high latitudes and subsequently repeated the site simulations using two reanalysis datasets: NCEP/NCAR and CRUNCEP. The results show that at most sites, the reanalysis-driven GPP bias was significantly positive with respect to the observed meteorology-driven simulations. Notably, the absolute GPP bias was highest at the tropical evergreen tree sites, averaging up to ca. 0.45 kg C m(-2) yr(-1) across sites (ca. 15% of site level GPP). At the northern mid-/high-latitude broadleaf deciduous and the needleleaf evergreen tree sites, the corresponding annual GPP biases were up to 20%. For the nontree sites, average annual biases of up to ca. 20-30% were simulated within savanna, grassland, and shrubland vegetation types. At the tree sites, the biases in short-wave radiation and humidity strongly influenced the GPP biases, while the nontree sites were more affected by biases in factors controlling water stress (precipitation, humidity, and air temperature). In this study, we also discuss the influence of seasonal patterns of meteorological biases on GPP. Finally, using model simulations for the global land surface, we discuss the potential impacts of site-level reanalysis-driven biases on the global estimates of GPP. In a broader context, our results can have important consequences on other terrestrial ecosystem fluxes (e.g., net primary production, net ecosystem production, energy/water fluxes) and reservoirs (e.g., soil carbon stocks). In a complementary study (Barman et al., ), we extend the present analysis for latent and sensible heat fluxes, thus consistently integrating the analysis of climate-driven uncertainties in carbon, energy, and water fluxes using a single modeling framework.

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Section: Gpp and Carbon Cycle Components In Isammentioning

confidence: 99%

Climate‐driven uncertainties in modeling terrestrial gross primary production: a site level to global‐scale analysis

Barman

Jain

Liang

2014

Global Change Biology

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“…Root water uptake is usually simulated by a sink term incorporated in Richards' equation (Hopmans and Bristow 2002;Raats 2007;El Maayar et al 2009;Nyambayo and Potts 2010).…”

Section: Introductionmentioning

confidence: 99%

Analytical solutions for calculating pore-water pressure in an infinite unsaturated slope with different root architectures

Liu

Feng

2015

Can. Geotech. J.

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Vegetation can reduce pore water pressure in soil by root water uptake. The reduction of pore water pressure results in higher shear strength but lower water permeability of soil, affecting slope stability and rainfall infiltration, respectively. Effects of different root architectures on root water uptake and hence pore water pressure distributions are not well understood. In this study, new analytical solutions for calculating pore water pressure in an infinite unsaturated vegetated slope are derived for different root architectures, namely the uniform, triangular, exponential and parabolic root architectures. Using the newly developed solutions, four series of analytical parametric analyses are carried out to improve understanding of the factors affecting root water uptake and hence that influence pore water pressure distributions. In the dry season, different root architectures can lead to large variations in pore water pressure distributions. It is found that the exponential root architecture induces the highest negative pore water pressure in the soil, followed by the triangular, uniform and parabolic root architectures. The maximum pore water pressure induced by the parabolic root architecture is about 77% of that induced by the exponential root architecture at the steady state. For a given root architecture, vegetation in completely decomposed granite (CDG, classified as silty sand) induces the highest negative pore water pressure than that in fine sand and silt. The zone influenced by vegetation can be about three to six times the root depth. In wet season, after a ten-year return period rainfall with a duration of 24 hours, different root architectures show similar pore water pressure distributions.

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“…Therefore, information about the SWC of deeper soil layers where active roots may be present is essential for estimating the full impact of land-use management on fundamental hydrological and atmospheric processes. Such information can be useful for land surface models, large-scale climate models and ecohydrological models (Puma et al 2005, El Maayar et al 2009.…”

Section: Regional Spatial Pattern Of Deep Soil Water Content and Its mentioning

confidence: 99%

Regional spatial pattern of deep soil water content and its influencing factors

Wang

Shao

Liu

et al. 2012

Hydrological Sciences Journal

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., 2012. Regional spatial pattern of deep soil water content and its influencing factors. Hydrological Sciences Journal, 57 (2), 265-281.Abstract Plant root systems can utilize soil water to depths of 10 m or more. Spatial pattern data of deep soil water content (SWC) at the regional scale are scarce due to the labour and time constraints of field measurements. We measured gravimetric deep SWC (DSWC) at depths of 200, 300, 400, 500, 600, 800 and 1000 cm at 382 sites across the Loess Plateau, China. The coefficient of variation was high for soil water content (SWC) in the horizontal direction (48%), but was relatively small for SWC in the vertical direction (9%). Semivariogram ranges for DSWC at different depths were between 198 and 609 km. Kriged distribution maps indicated that deep soil layers became moister along northwest to southeast transects. Multiple statistical analyses related DSWC to plant characteristics (e.g. plant age explained >21% of the variability), geographical location and altitude (8-13%), soil texture and infiltrability, evaporation zone and eco-hydrological processes (P < 0.05). Regional land management decisions can be based on our DSWC distribution data to determine land uses and plant species appropriate for the soil type and location that would maintain a stable soil water balance. Maintaining infiltrability is of great importance in this and other water-scarce regions of the world.Key words spatial variability; land-use management; geostatistics; multiple linear regression; residual maximum likelihood analysis; Loess Plateau of China Répartition spatiale régionale du contenu en eau des sols profonds et des facteurs qui l'influencent Résumé Les systèmes racinaires des plantes peuvent utiliser l'eau du sol à des profondeurs de 10 m ou plus. Les données de répartition spatiale du contenu en eau des sols profonds (SWC) à l'échelle régionale sont rares en raison des contraintes de main d'oeuvre et de temps des mesures sur le terrain. Nous avons mesuré le contenu en eau du sol (CES) gravimétrique profond (CESP) à des profondeurs de 200, 300, 400, 500, 600, 800 et 1000 cm sur 382 sites à travers le plateau de loess, en Chine. Le coefficient de variation était élevé pour le CES dans le sens horizontal (48%), mais était relativement faible pour le CES dans le sens vertical (9%). Les gammes des semi-variogrammes pour le CESP à différentes profondeurs allaient de 198 à 609 km. Les cartes de répartition krigées ont indiqué que les couches profondes du sol devenaient plus humides le long de transects nord-ouest au sud-est. De multiples analyses statistiques ont relié le CESP aux caractéristiques des plantes (par exemple, l'âge des plantes expliquait plus de 21% de la variabilité), à la localisation géographique et à l'altitude (8-13%), à la texture et l'infiltrabilité du sol, à la zone d'évaporation et aux processus éco-hydrologiques (P < 0,05). Les décisions régionales de gestion foncière peuvent être basées sur nos données de distribution de CESP pour déterminer l'occupation du sol et les espèce...

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Simulating daily, monthly and annual water balances in a land surface model using alternative root water uptake schemes

Cited by 25 publications

References 59 publications

Climate‐driven uncertainties in modeling terrestrial gross primary production: a site level to global‐scale analysis

Climate‐driven uncertainties in modeling terrestrial gross primary production: a site level to global‐scale analysis

Analytical solutions for calculating pore-water pressure in an infinite unsaturated slope with different root architectures

Regional spatial pattern of deep soil water content and its influencing factors

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