Improvement of evapotranspiration estimates over arid and semi-arid regions with a physically based water stress constraint scheme

2020 ◽  
Author(s):  
Kun Zhang ◽  
Donghai Zheng ◽  
Yunquan Wang ◽  
Gaofeng Zhu
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Soil Water ◽  
Arid Regions ◽  
Bare Soil ◽  
Stress Constraint ◽  
Near Surface ◽  
Soil Water Stress ◽  
Physically Based ◽  
Semi Arid

<p>In the arid and semi-arid regions, the bare soil evaporation dominates the total evapotranspiration (ET). To date, in most of the process-based ET models, the constraint on the actual evaporation from bare soil due to water stress is either related to an empirical function of near-surface humidity or represented by a water stress factor linked with surface soil moisture. However, the relative humidity (RH) shows a hysteretic effect on the ET event, and the relationship between soil water stress and soil moisture is nonlinear, usually leading to the overestimation of ET in arid and semi-arid regions. In this study, we plan to improve the ET estimates on dry land by implementing a physically-based water stress constraint method, which is developed by parameterizing the Buckingham-Darcy’s law and yielded an excellent performance with laboratory data. The physically-based water stress constraint scheme is further incorporated into two different ET models (i.e. PT-JPL, MOD16) to generate the global ET estimates, whereby the latest ERA5-land reanalysis data and MODIS NDVI\LAI is adopted as model inputs. We not only validate the simulated ET with available flux observations but also intercompare the performances of different schemes in estimating ET in the arid and semi-arid regions. This study will provide a new way to characterize the regional soil water stress on the ET estimates especially in the arid and semi-arid conditions.</p>

scholarly journals Relating surface backscatter response from TRMM Precipitation Radar to soil moisture: results over a semi-arid region

2009 ◽  
Vol 6 (5) ◽  
pp. 6425-6454
Author(s):  
H. Stephen ◽  
S. Ahmad ◽  
T. C. Piechota ◽  
C. Tang
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Arid Regions ◽  
Vegetation Index ◽  
Temporal Trends ◽  
Model Parameters ◽  
Precipitation Radar ◽  
Semi Arid

Abstract. The Tropical Rainfall Measuring Mission (TRMM) carries aboard the Precipitation Radar (TRMMPR) that measures the backscatter (σ°) of the surface. σ° is sensitive to surface soil moisture and vegetation conditions. Due to sparse vegetation in arid and semi-arid regions, TRMMPR σ° primarily depends on the soil water content. In this study we relate TRMMPR σ° measurements to soil water content (ms) in Lower Colorado River Basin (LCRB). σ° dependence on ms is studied for different vegetation greenness values determined through Normalized Difference Vegetation Index (NDVI). A new model of σ° that couples incidence angle, ms, and NDVI is used to derive parameters and retrieve soil water content. The calibration and validation of this model are performed using simulated and measured ms data. Simulated ms is estimated using Variable Infiltration Capacity (VIC) model whereas measured ms is acquired from ground measuring stations in Walnut Gulch Experimental Watershed (WGEW). σ° model is calibrated using VIC and WGEW ms data during 1998 and the calibrated model is used to derive ms during later years. The temporal trends of derived ms are consistent with VIC and WGEW ms data with correlation coefficient (R) of 0.89 and 0.74, respectively. Derived ms is also consistent with the measured precipitation data with R=0.76. The gridded VIC data is used to calibrate the model at each grid point in LCRB and spatial maps of the model parameters are prepared. The model parameters are spatially coherent with the general regional topography in LCRB. TRMMPR σ° derived soil moisture maps during May (dry) and August (wet) 1999 are spatially similar to VIC estimates with correlation 0.67 and 0.76, respectively. This research provides new insights into Ku-band σ° dependence on soil water content in the arid regions.

Simulating Gross Primary Productivity of vegetation under soil water stress using in-situ and reanalysis soil moisture data inputs

2020 ◽  
Author(s):  
Timothy Lam ◽  
Amos P. K. Tai
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Soil Water ◽  
Primary Productivity ◽  
Gross Primary Productivity ◽  
Efficiency Coefficient ◽  
Community Land Model ◽  
Soil Water Stress ◽  
Soil Moisture Data

<p>This study utilises in-situ and reanalysis soil moisture data inputs from various sources to evaluate the effect of soil water stress on Gross Primary Productivity (GPP) of different Plant Functional Types (PFTs) using Terrestrial Ecosystem Model in R (TEMIR), which is under development by Tai Group of Atmosphere-Biosphere Interactions (Tai et al. in prep.). An empirical soil water stress function with reference to Community Land Model (CLM) Version 4.5 is employed to quantify water stress experienced by vegetation which hinders stomatal conductance and thus carboxylation rate. The model results are compared against observations at FLUXNET sites in semi-arid regions across the globe at daily timescale where in-situ GPP data is available and water stress inhibits plant functions to some extent. By dividing the soil into two layers (topsoil and root zone), GPP simulation improves significantly comparing with using single layer bulk soil (Modified Nash-Sutcliffe Model Efficiency Coefficient N increases from -0.686 to -0.586). Such upgrade is particularly substantial for vegetation with shallow roots such as grass PFTs. Despite this improvement, the model is characterised by an overall overestimation of GPP when water stress occurs, and inconsistency of accuracy subject to PFTs and degree of water stress experienced. This study informs responses of various PFTs to soil water stress, capacity of TEMIR in simulating the responses, and possible drawbacks of empirical soil water stress functions, and highlights the importance of topsoil moisture data input for vegetation drought monitoring.</p><p>Keywords: Soil water stress, Terrestrial model representation, Photosynthesis, In-situ data, Reanalysis data, FLUXNET</p>

scholarly journals Effect of Irrigation and Soil Water Stress on Densities of Macrophomina phaseolina in Soil and Roots of Two Soybean Cultivars

Plant Disease ◽  
2000 ◽  
Vol 84 (8) ◽  
pp. 895-900 ◽  
Author(s):  
S. R. Kendig ◽  
J. C. Rupe ◽  
H. D. Scott
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Soil Water ◽  
Growth Stage ◽  
Root Colonization ◽  
Growing Season ◽  
Moisture Stress ◽  
Macrophomina Phaseolina ◽  
Soil Moisture Stress ◽  
Soil Water Stress

The effects of irrigation and soil water stress on Macrophomina phaseolina microsclerotial (MS) densities in the soil and roots of soybean were studied in 1988, 1989, and 1990. Soybean cvs. Davis and Lloyd received irrigation until flowering (TAR2), after flowering (IAR2), full season (FSI), or not at all (NI). Soil water matric potentials at 15- and 30-cm depths were recorded throughout the growing season and used to schedule irrigation. Soil MS densities were determined at the beginning of each season. Root MS densities were determined periodically throughout the growing season. Microsclerotia were present in the roots of irrigated as well as nonirrigated soybean within 6 weeks after planting. By vegetative growth stage V13, these densities reached relatively stable levels in the NI and FSI treatments (2.23 to 2.35 and 1.35 to 1.63 log [microsclerotia per gram of dry root], respectively) through reproductive growth stage R6. After R6, irrigation was discontinued and root densities of microsclerotia increased in all treatments. Initiation (IAR2) or termination (TAR2) of irrigation at R2 resulted in significant changes in root MS densities, with densities reaching levels intermediate between those of FSI and NI treatments. Year to year differences in root colonization reflected differences in soil moisture due to rainfall. The rate of root colonization in response to soil moisture stress decreased with plant age. Root colonization was significantly greater in Davis than Lloyd at R5 and R8. This was reflected in a trend toward higher soil densities of M. phaseolina at planting in plots planted with Davis than in plots planted with Lloyd. Although no charcoal rot symptoms in the plant were observed in this study, these results indicated that water management can limit, but not prevent, colonization of soybean by M. phaseolina, that cultivars differ in colonization, and that these differences may affect soil densities of the fungus.

Four decades of soil water stress history together with host genotype constrain the response of the wheat microbiome to soil moisture

2020 ◽  
Vol 96 (7) ◽  
Author(s):  
Hamed Azarbad ◽  
Julien Tremblay ◽  
Charlotte Giard-Laliberté ◽  
Luke D Bainard ◽  
Etienne Yergeau
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Soil Water ◽  
Its Region ◽  
Rrna Gene ◽  
Short Term ◽  
Host Genotype ◽  
Stress History ◽  
Wheat Field ◽  
Soil Water Stress

ABSTRACT There is little understanding about how soil water stress history and host genotype influence the response of wheat-associated microbiome under short-term decreases in soil moisture. To address this, we investigated how plant breeding history (four wheat genotypes; two with recognized drought resistance and two without) and soil water stress history (same wheat field soil from Saskatchewan with contrasting long-term irrigation) independently or interactively influenced the response of the rhizosphere, root and leaf bacterial and fungal microbiota to short-term decreases in soil water content (SWC). We used amplicon sequencing (16S rRNA gene for bacteria and ITS region for fungi) to characterize the wheat microbiome. Fungal and bacterial communities responses to short-term decreases in SWC were mainly constrained by soil water stress history, with some smaller, but significant influence of plant genotype. One exception was the leaf-associated fungal communities, for which the largest constraint was genotype, resulting in a clear differentiation of the communities based on the genotype's sensitivity to water stress. Our results clearly indicate that soil legacy does not only affect the response to water stress of the microbes inhabiting the soil, but also of the microorganisms more closely associated with the plant tissues, and even of the plant itself.

scholarly journals Plant Hydraulic Transport Controls Transpiration Response to Soil Water Stress

2021 ◽  
Author(s):  
Brandon P. Sloan ◽  
Sally E. Thompson ◽  
Xue Feng
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Soil Water ◽  
Land Surface ◽  
Correction Function ◽  
Additional Parameter ◽  
Hydraulic Transport ◽  
Atmospheric Moisture ◽  
Soil Water Stress ◽  
Demand Variation

Abstract. Plant transpiration downregulation in the presence of soil water stress is a critical mechanism for predicting global water, carbon, and energy cycles. Currently, many terrestrial biosphere models (TBMs) represent this mechanism with an empirical correction function (β) of soil moisture – a convenient approach that can produce large prediction uncertainties. To reduce this uncertainty, TBMs have increasingly incorporated physically-based Plant Hydraulic Models (PHMs). However, PHMs introduce additional parameter uncertainty and computational demands. Therefore, understanding why and when PHM and β predictions diverge would usefully inform model selection within TBMs. Here, we use a minimalist PHM to demonstrate that coupling the effects of soil water stress and atmospheric moisture demand leads to a spectrum of transpiration response controlled by soil-plant hydraulic transport (conductance). Within this transport-limitation spectrum, β emerges as an end-member scenario of PHMs with infinite conductance, completely decoupling the effects of soil water stress and atmospheric moisture demand on transpiration. As a result, PHM and β transpiration predictions diverge most when conductance is low (transport-limited), atmospheric moisture demand variation is high, and soil moisture is moderately available to plants. We apply these minimalist model results to land surface modeling of an Ameriflux site. At this transport-limited site, a PHM downregulation scheme outperforms the β scheme due to its sensitivity to variations in atmospheric moisture demand. Based on this observation, we develop a new dynamic β that varies with atmospheric moisture demand – an approach that balances realism with parsimony and overcomes existing biases within β schemes.

scholarly journals Plant hydraulic transport controls transpiration sensitivity to soil water stress

2021 ◽  
Vol 25 (8) ◽  
pp. 4259-4274
Author(s):  
Brandon P. Sloan ◽  
Sally E. Thompson ◽  
Xue Feng
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Soil Water ◽  
Land Surface ◽  
Correction Function ◽  
Surface Model ◽  
Additional Parameter ◽  
Hydraulic Transport ◽  
Atmospheric Moisture ◽  
Soil Water Stress

Abstract. Plant transpiration downregulation in the presence of soil water stress is a critical mechanism for predicting global water, carbon, and energy cycles. Currently, many terrestrial biosphere models (TBMs) represent this mechanism with an empirical correction function (β) of soil moisture – a convenient approach that can produce large prediction uncertainties. To reduce this uncertainty, TBMs have increasingly incorporated physically based plant hydraulic models (PHMs). However, PHMs introduce additional parameter uncertainty and computational demands. Therefore, understanding why and when PHM and β predictions diverge would usefully inform model selection within TBMs. Here, we use a minimalist PHM to demonstrate that coupling the effects of soil water stress and atmospheric moisture demand leads to a spectrum of transpiration responses controlled by soil–plant hydraulic transport (conductance). Within this transport-limitation spectrum, β emerges as an end-member scenario of PHMs with infinite conductance, completely decoupling the effects of soil water stress and atmospheric moisture demand on transpiration. As a result, PHM and β transpiration predictions diverge most for soil–plant systems with low hydraulic conductance (transport-limited) that experience high variation in atmospheric moisture demand and have moderate soil moisture supply for plants. We test these minimalist model results by using a land surface model at an AmeriFlux site. At this transport-limited site, a PHM downregulation scheme outperforms the β scheme due to its sensitivity to variations in atmospheric moisture demand. Based on this observation, we develop a new “dynamic β” that varies with atmospheric moisture demand – an approach that overcomes existing biases within β schemes and has potential to simplify existing PHM parameterization and implementation.

scholarly journals On the Treatment of Soil Water Stress in GCM Simulations of Vegetation Physiology

2021 ◽  
Vol 9 ◽  
Author(s):  
P. L. Vidale ◽  
G. Egea ◽  
P. C. McGuire ◽  
M. Todt ◽  
W. Peters ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Stomatal Conductance ◽  
Soil Water ◽  
Land Surface ◽  
Spatiotemporal Variability ◽  
Climate Conditions ◽  
Soil Water Stress ◽  
Forest Meteorology ◽  
Weather And Climate

Current land surface schemes in weather and climate models make use of the so-called coupled photosynthesis–stomatal conductance (A–gs) models of plant function to determine the surface fluxes that govern the terrestrial energy, water and carbon budgets. Plant physiology is controlled by many environmental factors, and a number of complex feedbacks are involved, but soil moisture control on root water uptake is primary, particularly in sub-tropical to temperate ecosystems. Land surface models represent plant water stress in different ways, but most implement a water stress factor, β, which ranges linearly (more recently also curvilinearly) between β = 1 for unstressed vegetation and β = 0 at the wilting point, expressed in terms of volumetric water content (θ).  β is most commonly used to either limit A or gs, and hence carbon and water fluxes, and a pertinent research question is whether these treatments are in fact interchangeable. Following Egea et al. (Agricultural and Forest Meteorology, 2011, 151 (10), 1,370–1,384) and Verhoef et al. (Agricultural and Forest Meteorology, 2014, 191, 22–32), we have implemented new β treatments, reflecting higher levels of biophysical complexity in a state-of-the-art LSM, Joint UK Land Environment Simulator, by allowing root zone soil moisture to limit plant function non-linearly and via individual routes (carbon assimilation, stomatal conductance, or mesophyll conductance) as well as any (non-linear) combinations thereof. The treatment of β does matter to the prediction of water and carbon fluxes: this study demonstrates that it represents a key structural uncertainty in contemporary LSMs, in terms of predictions of gross primary productivity, energy fluxes and soil moisture evolution, both in terms of climate means and response to a number of European droughts, including the 2003 heat wave. Treatments allowing ß to act on vegetation fluxes via stomatal and mesophyll routes are able to simulate the spatiotemporal variability in water use efficiency with higher fidelity during the growing season; they also support a broader range of ecosystem responses, e.g., those observed in regions that are radiation limited or water limited. We conclude that current practice in weather and climate modelling is inconsistent, as well as too simplistic, failing to credibly simulate vegetation response to soil water stress across the typical range of variability that is encountered for current European weather and climate conditions, including extremes of land surface temperature and soil moisture drought. A generalized approach performs better in current climate conditions and promises to be, based on responses to recently observed extremes, more trustworthy for predicting the impacts of climate change.

scholarly journals Relating surface backscatter response from TRMM precipitation radar to soil moisture: results over a semi-arid region

2010 ◽  
Vol 14 (2) ◽  
pp. 193-204 ◽  
Author(s):  
H. Stephen ◽  
S. Ahmad ◽  
T. C. Piechota ◽  
C. Tang
Keyword(s):  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Arid Regions ◽  
Vegetation Index ◽  
Temporal Trends ◽  
Model Parameters ◽  
Precipitation Radar ◽  
Semi Arid

Abstract. The Tropical Rainfall Measuring Mission (TRMM) carries aboard the Precipitation Radar (TRMMPR) that measures the backscatter (σ°) of the surface. σ° is sensitive to surface soil moisture and vegetation conditions. Due to sparse vegetation in arid and semi-arid regions, TRMMPR σ° primarily depends on the soil water content. In this study we relate TRMMPR σ° measurements to soil water content (ms) in the Lower Colorado River Basin (LCRB). σ° dependence on ms is studied for different vegetation greenness values determined through Normalized Difference Vegetation Index (NDVI). A new model of σ° that couples incidence angle, ms, and NDVI is used to derive parameters and retrieve soil water content. The calibration and validation of this model are performed using simulated and measured ms data. Simulated ms is estimated using the Variable Infiltration Capacity (VIC) model and measured ms is acquired from ground measuring stations in Walnut Gulch Experimental Watershed (WGEW). σ° model is calibrated using VIC and WGEW ms data during 1998 and the calibrated model is used to derive ms during later years. The temporal trends of derived ms are consistent with VIC and WGEW ms data with a correlation coefficient (R) of 0.89 and 0.74, respectively. Derived ms is also consistent with the measured precipitation data with R=0.76. The gridded VIC data is used to calibrate the model at each grid point in LCRB and spatial maps of the model parameters are prepared. The model parameters are spatially coherent with the general regional topography in LCRB. TRMMPR σ° derived soil moisture maps during May (dry) and August (wet) 1999 are spatially similar to VIC estimates with correlation 0.67 and 0.76, respectively. This research provides new insights into Ku-band σ° dependence on soil water content in the arid regions.

scholarly journals DETECTION AND CORRECTION OF MIDSEASON P DEFICIENCY IN IRRIGATED POTATOES

1988 ◽  
Vol 68 (2) ◽  
pp. 523-534 ◽  
Author(s):  
D. C. MacKAY ◽  
J. M. CAREFOOT ◽  
T. ENTZ
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Soil Water ◽  
Field Experiments ◽  
P Fertilization ◽  
P Deficiency ◽  
Leaf Analysis ◽  
Moisture Management ◽  
Soil Water Stress ◽  
Leaf P

Three experiments were performed in an automatic rainshelter and two in the field to determine the role of soil moisture management and phosphorus (P) fertilization in controlling P nutrition of potatoes (Solanum tuberosum L. ’Russet Burbank’). The rainshelter experiments indicated that permitting the upper layer (25 cm) of soil to remain dry during the early part of the growing season depressed the total P concentrations in the leaf blades at the 10% bloom stage to well below the sufficiency range of 0.45 – 0.50%, in spite of high P application rates at planting. Relieving stress at 10% bloom and maintaining soil water potential between −60 and −20 kPa until harvest significantly increased P concentrations. Tuber yields were only slightly less than on those soils without water stress throughout the growing period, provided ample P had been applied. By delaying stress relief in the upper soil layer for 3 wk, 6 wk, or until maturity, tuber yields were reduced 28, 47 and 49% respectively. Without P fertilization of this P-deficient soil at planting, leaf-P levels at 10% bloom were very low (0.26%), but application of P at this stage (banded, broadcast, or in solution) increased leaf-P concentrations and yields were similar to treatments receiving P at planting. Trimetaphosphate was particularly effective in increasing P concentrations in the leaves. In the two field experiments, tuber yields were high on all plots and treatment differences were small, even though leaf-P concentrations were relatively low. However, in the highest-yielding treatment (banded at planting) leaf-P levels averaged from 0.40 to 0.49% which is close to that considered as a sufficiency range (0.45 – 0.50), reported previously. From the practical standpoint, leaf analysis at the early bloom stage can be used to detect P deficiency, which may be caused by inadequate P fertilization or early season soil water stress. If soil and fertilizer P are insufficient, immediate application of fertilizer P will correct deficiencies and enhance yields if adequate soil water is also provided. Soil moisture stress from early bloom to near maturity should be avoided with this crop to obtain efficient use of applied P and maximum yields of tubers.Key words: Leaf analysis, P fertilizers, trimetaphosphate, soil water stress, automated rainshelter.

scholarly journals Estimating evapotranspiration over vegetated surfaces based on wet patch patterns

2019 ◽  
Vol 50 (4) ◽  
pp. 1037-1046 ◽  
Author(s):  
Peiyuan Li ◽  
Zhi-Hua Wang
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Energy Exchange ◽  
Hydrological Cycle ◽  
Turbulent Transfer ◽  
Near Surface ◽  
Local Climate ◽  
Water Energy Nexus ◽  
Physically Based ◽  
Moisture Conditions

Abstract Evapotranspiration (ET) is a critical component of the hydrological cycle and natural water-energy nexus. The dynamics of soil water content (θ) in the top surface layer, regulated by local climate, predominates the surface energy exchange and ET behavior. In this study, we proposed a novel ET-θ relation using a physically based wet patch radius coupling the near surface turbulent transfer and soil water availability. The model is tested against the dataset from eddy covariance (EC) sites in the AmeriFlux network. The results show that ET rate is supply-driven under low soil moisture conditions since the plant controls the transpiration rate to conserve water due to water stress. While in energy-limited condition, increasing soil moisture will not promote ET rate as it is bounded by the lower atmospheric demand. The proposed method is practically designed to calculate ET using variables readily measured by standard EC towers such as soil moisture and meteorological measurements. The method can also potentially be extended to predict the spatial and physical patterns of ecosystem services under different hydroclimatic conditions.

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