A stochastic model for vegetation water stress

Borgogno, Fabio; D’Odorico, Paolo; Laio, Francesco; Ridolfi, Luca

doi:10.1002/eco.120

Cited by 9 publications

(6 citation statements)

References 50 publications

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“…These models have been expanded (e.g. Laio et al ., ; Porporato et al ., ) and applied to questions of vegetation water stress (Porporato et al ., ; Borgogno et al ., ), vegetation distributions (Caylor et al ., ; Franz et al ., ), soil respiration and nutrient dynamics (D'Odorico et al ., ; Manzoni and Porporato, ; Botter et al ., ; Daly et al ., ), root compensation and partial rewetting of the root zone (Guswa et al ., ; Guswa, ), streamflow (Botter et al ., ), water‐table dynamics (Laio et al ., ), irrigation (Vico and Porporato, ), and root depth and distribution (Laio et al ., ; Guswa, ).…”

Section: Methodsmentioning

confidence: 99%

“…These models have been expanded (e.g. Laio et al, 2001;Porporato et al, 2004) and applied to questions of vegetation water stress Borgogno et al, 2010), vegetation distributions (Caylor et al, 2009;Franz et al, 2010), soil respiration and nutrient dynamics (D'Odorico et al, 2004;Manzoni and Porporato, 2009;Botter et al, 2008;Daly et al, 2008), root compensation and partial rewetting of the root zone (Guswa et al, 2002Guswa, 2005), streamflow (Botter et al, 2007(Botter et al, , 2010, water-table dynamics (Laio et al, 2009), irrigation (Vico and At the core of these models is the representation of infiltration as a stochastic process, characterized by both a frequency of events and a mean depth of events. Precipitation events raise the average moisture content in the root zone, and drainage and uptake losses reduce soil moisture during the interstorm periods.…”

Section: Stochastic Modelling Of Throughfall and Rechargementioning

confidence: 99%

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Effect of throughfall variability on recharge: application to hemlock and deciduous forests in western Massachusetts

Guswa

Spence

2011

Ecohydrology

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Vegetation canopies intercept and redistribute precipitation in space. Although throughfall patterns are challenging to correlate with plant characteristics, many studies have shown that the spatial patterns persist through time. This persistence leads to wet and dry spots that can affect recharge, transpiration, and other nonlinear ecohydrologic and biogeochemical processes. A stochastic framework is used to determine the effect of throughfall variability on hydrologic fluxes. Throughfall variability increases and concentrates recharge, and the magnitude of the effect depends on the character of throughfall variability along with characteristics of climate, soil, and vegetation. This framework is also used to explore specific differences in summertime recharge between stands of deciduous trees (birch, maple, and oak) and eastern hemlock (Tsuga canadensis). Throughout the eastern United States, the invasive hemlock woolly adelgid poses a significant threat to hemlock forests, and replacement of hemlock forests by other species has the potential to alter hydrologic fluxes and other processes. Field investigations in 2009 and 2010 indicate that, relative to deciduous stands, hemlock canopies intercept more water and tend to produce dry rather than wet spots. Although deciduous stands produce more throughfall, model results indicate that differences in canopy interception are outweighed by large differences in peak transpiration rates, and predictions of summertime recharge are lower in deciduous forests than in hemlock. Copyright © 2011 John Wiley & Sons, Ltd.

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Section: Methodsmentioning

confidence: 99%

Section: Stochastic Modelling Of Throughfall and Rechargementioning

confidence: 99%

Effect of throughfall variability on recharge: application to hemlock and deciduous forests in western Massachusetts

Guswa

Spence

2011

Ecohydrology

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“…The distribution of interarrival times between rainfall events (dry periods) used in rainfall and ecohydrological studies [ Laio et al ., ; Molini et al ., ; Paschalis et al ., ] is equivalent to a persistence probability. In the context of root‐zone soil moisture, applications of these concepts include discussions on analytical approaches to estimate mean first passage times and crossing dynamics of a prescribed threshold [e.g., Rodríguez‐Iturbe and Porporato , ; Borgogno et al ., ; Vico and Porporato , ]. These approaches typically assume a probability distribution for the occurrence (marked Poisson process) and depth (exponential) of rainfall at the daily timescale.…”

Section: Introductionmentioning

confidence: 99%

Persistence and memory timescales in root‐zone soil moisture dynamics

Ghannam

Nakai

Paschalis

et al. 2016

Water Resources Research

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“…The GPP PRI also outperformed GPP swc at the CRO, SHR, and DBF sites ( (Neal, 2012;Kurc and Small, 2007;Reichstein et al 2002), which may explain the generally low SWC correlations and low GPP swc performance in relation to MODIS PRI and the tower-based LUE and GPP f observations. The internal water storage capacity of woody plant tissues may also offset soil moisture demand (Borgogno et al 2010;Reichstein et al 2002), which may contribute to relatively lower daily SWC correspondence with PRI and vegetation productivity in forest and SHR areas (e.g. Table 4).…”

Section: Discussionmentioning

confidence: 99%

Satellite detection of soil moisture related water stress impacts on ecosystem productivity using the MODIS-based photochemical reflectance index

Kimball

Running

et al. 2016

Remote Sensing of Environment

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Satellite remote sensing provides continuous observations of vegetation properties that can be used to estimate global terrestrial ecosystem gross primary production (GPP). The Photochemical Reflectance Index (PRI) has been shown to be sensitive to vegetation photosynthetic light use efficiency (LUE), GPP and canopy water-stress. Here, we use the NASA EOS MODIS (Moderate Resolution Imaging Spectroradiometer) based PRI with eddy covariance CO 2 flux measurements and meteorological observations from 20 tower sites representing major plant functional type (PFT) classes within the continental USA (CONUS) to assess GPP sensitivity to soil moisture related water stress. The sPRI (scaled PRI) metric derived using MODIS band 13 as a reference channel (sPRI 13) shows generally higher correspondence with tower GPP observations than other potential MODIS reference bands. The sPRI 13 observations were used as a proxy for soil moisture related water supply constraints to LUE within a satellite data driven terrestrial carbon flux model to estimate GPP (GPP PRI). The GPP PRI calculations show generally favorable correspondence with tower GPP observations (0.457 ≤ R 2 ≤ 0.818), except for lower GPP PRI performance over evergreen needleleaf forest (ENF) sites. A regional model sensitivity analysis using the sPRI 13 as a water supply proxy indicated that water restrictions limit GPP over more than 21% of the CONUS domain, particularly in drier climate areas where atmospheric moisture (VPD) deficits alone are insufficient to represent both atmosphere demand and water supply controls affecting productivity. Our results indicate strong potential of the MODIS sPRI 13 to represent soil moisture related water supply controls influencing photosynthesis, with enhanced (1-km resolution) delineation of these processes closer to the scale of in situ tower observations. These observations may provide an effective tool for characterizing sub-grid spatial heterogeneity in soil moisture related controls that inform coarser scale observations and estimates determined from other satellite observations and global carbon, and climate models.

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A stochastic model for vegetation water stress

Cited by 9 publications

References 50 publications

Effect of throughfall variability on recharge: application to hemlock and deciduous forests in western Massachusetts

Effect of throughfall variability on recharge: application to hemlock and deciduous forests in western Massachusetts

Persistence and memory timescales in root‐zone soil moisture dynamics

Satellite detection of soil moisture related water stress impacts on ecosystem productivity using the MODIS-based photochemical reflectance index

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