Soil water balance and plant water stress

Abstract. The statistical-dynamical annual water balance model of Eagleson (1978) is a pioneering work in the analysis of climate, soil and vegetation interactions. This paper describes several enhancements and modifications to the model that improve its physical realism at the expense of its mathematical elegance and analytical tractability. In particular, the analytical solutions for the root zone fluxes are re-derived using separate potential rates of transpiration and bare-soil evaporation. Those potential rates, along with the rate of evaporation from canopy interception, are calculated using the two-component Shuttleworth-Wallace (1985) canopy model. In addition, the soil column is divided into two layers, with the upper layer representing the dynamic root zone. The resulting ability to account for changes in root-zone water storage allows for implementation at the monthly timescale. This new version of the Eagleson model is coined the Statistical-Dynamical Ecohydrology Model (SDEM). The ability of the SDEM to capture the seasonal dynamics of the local-scale soil-water balance is demonstrated for two grassland sites in the US Great Plains. Sensitivity of the results to variations in peak green leaf area index (LAI) suggests that the mean peak green LAI is determined by some minimum in root zone soil moisture during the growing season. That minimum appears to be close to the soil matric potential at which the dominant grass species begins to experience water stress and well above the wilting point, thereby suggesting an ecological optimality hypothesis in which the need to avoid water-stress-induced leaf abscission is balanced by the maximization of carbon assimilation (and associated transpiration). Finally, analysis of the sensitivity of model-determined peak green LAI to soil texture shows that the coupled model is able to reproduce the so-called "inverse texture effect", which consists of the observation that natural vegetation in dry climates tends to be most productive in sandier soils despite their lower water holding capacity. Although the determination of LAI based on complete or near-complete utilization of soil moisture is not a new approach in ecohydrology, this paper demonstrates its use for the first time with a new monthly statistical-dynamical model of the water balance. Accordingly, the SDEM provides a new framework for studying the controls of soil texture and climate on vegetation density and evapotranspiration.

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Modeling the monthly mean soil-water balance with a statistical-dynamical ecohydrology model as coupled to a two-component canopy model

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-5-579-2008 ◽

2008 ◽

Vol 5 (2) ◽

pp. 579-648

Author(s):

J. P. Kochendorfer ◽

J. A. Ramírez

Keyword(s):

Soil Moisture ◽

Water Stress ◽

Water Balance ◽

Soil Water ◽

Soil Texture ◽

Root Zone ◽

Soil Water Balance ◽

Area Index ◽

Two Component ◽

Canopy Model

Abstract. The statistical-dynamical annual water balance model of Eagleson (1978) is a pioneering work in the analysis of climate, soil and vegetation interactions. This paper describes several enhancements and modifications to the model that improve its physical realism at the expense of its mathematical elegance and analytical tractability. In particular, the analytical solutions for the root zone fluxes are re-derived using separate potential rates of transpiration and bare-soil evaporation. Those potential rates, along with the rate of evaporation from canopy interception, are calculated using the two-component Shuttleworth-Wallace (1985) canopy model. In addition, the soil column is divided into two layers, with the upper layer representing the dynamic root zone. The resulting ability to account for changes in root-zone water storage allows for implementation at the monthly timescale. This new version of the Eagleson model is coined the Statistical-Dynamical Ecohydrology Model (SDEM). The ability of the SDEM to capture the seasonal dynamics of the local-scale soil-water balance is demonstrated for two grassland sites in the US Great Plains. Sensitivity of the results to variations in peak green Leaf Area Index (LAI) suggests that the mean peak green LAI is determined by some minimum in root zone soil moisture during the growing season. That minimum appears to be close to the soil matric potential at which the dominant grass species begins to experience water stress and well above the wilting point, thereby suggesting an ecological optimality hypothesis in which the need to avoid water-stress-induced leaf abscission is balanced by the maximization of carbon assimilation (and associated transpiration). Finally, analysis of the sensitivity of model-determined peak green LAI to soil texture shows that the coupled model is able to reproduce the so-called "inverse texture effect", which consists of the observation that natural vegetation in dry climates tends to be most productive in sandier soils despite their lower water holding capacity. Although the determination of LAI based on near-complete utilization of soil moisture is not a new approach in ecohydrology, this paper demonstrates its use for the first time with a new monthly statistical-dynamical model of the water balance. Accordingly, the SDEM provides a new framework for studying the controls of soil texture and climate on vegetation density and evapotranspiration.

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An example of spatial correlation between soil water content and irrigated alfalfa yield at sub-field scale

10.5194/egusphere-egu2020-10944 ◽

2020 ◽

Author(s):

Anatoly Zeyliger ◽

Olga Ermolaeva

Keyword(s):

Water Stress ◽

Soil Water ◽

Spatial Correlation ◽

Plant Cover ◽

Soil Surface ◽

Plant Water ◽

Water Application ◽

Field Scale ◽

Plant Water Stress ◽

Management Zones

Soil water storage (SWC) is a major spatio-temporal geophysical variable that control many atmospheric and hydrological processes including evaporation from soil surface, transpiration from plant cover, soil water uptake and plant growth. In agricultural practice is widely accepted that SWC is closely linked to plant water stress. In this respect SWC is used as main parameter in irrigation technology of agricultural crops with both uniform and non-uniform water application techniques. For both mentioned types of irrigation a determination of timing water application as well as dozes are critical for developing effective agricultural water management practices and improving of water use efficiency at sub-field scale. In case of uniform water application the SWC is averaged at the field level. In case of non-uniform water (variable rate) application the SWC is averaged for management zones at sub-field scale bringing spatially heterogeneous irrigated into group of quasi-homogeneous areas. Tuning of regulated deficit irrigation by management zones provide great opportunities to control more rigorously plant water stress at quite large agricultural field with site-specific patterns of spatial characteristics depending of surface topography as well as soil & plant cover properties.A field experiment was conducted in summer 2012 at the Research Center of the Volghsky Scientific Research Institute for Hydrotechnics and Land Reclamation (VolgNIIGiM) located near town Engels (Saratov Region, Russian Federation) at the left bank of the middle part of the Volga river. Main aim of this experiment was to examine the spatial correlation between SWC and alfalfa yield production (AY) at plot of 400m2 which included one half of the field irrigated with pivot machine providing uniform water application. The results of the analysis of variation of both parameters was suspected to be essential to test the spatial correlation between them.During the field experiment a SWC was monitored before and after 2nd alfalfa harvesting with electromagnetic sensor EM 38 (Geonics Ltd.). Spatial analyses of sets of SWC geodata showed a presence of quite stable patterns within irrigated and non-irrigated parts of experimental plot. Location of SWC patterns was controlled firstly by spatial variation of soil surface elevation forming some shallow ponds and secondly by narrow furrows of circular form formed by wheels of the irrigation machine connecting in some case not adjacent areas. To map alfalfa yield plant samples were harvested from about 10 to 10 m plots. Alfalfa yield data was resulted as organic carbon mass per m2 after drying in laboratory conditions. Spatial analysis of AY geodata set showed the presence of patterns like SWC patterns. The spatial correlation between SWC and AY indicated the quite strong relationship between both parameters.Acknowledgments: The reported study was funded by RFBR, project number 19-29-05261 &#1084;&#1082;

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Potential and Limitations of the One-Layer Soil Water Balance Model to Estimate ET and Water Stress in Grape Vineyard

10.12702/ii.inovagri.2014-a378 ◽

2014 ◽

Author(s):

I. Campos ◽

C. Balbontín ◽

M.L. López ◽

J. González-Piqueras ◽

A. Calera

Keyword(s):

Water Stress ◽

Water Balance ◽

Soil Water ◽

Water Balance Model ◽

Soil Water Balance ◽

Balance Model ◽

The One

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Stress Coefficients for Soil Water Balance Combined with Water Stress Indicators for Irrigation Scheduling of Woody Crops

Horticulturae ◽

10.3390/horticulturae3020038 ◽

2017 ◽

Vol 3 (2) ◽

pp. 38 ◽

Cited By ~ 12

Author(s):

Maria Ferreira

Keyword(s):

Water Stress ◽

Water Balance ◽

Soil Water ◽

Irrigation Scheduling ◽

Soil Water Balance ◽

Stress Indicators ◽

Woody Crops

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Study on Plant Water Stress Based on Ultrasonic Acoustic Emissions

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.367.292 ◽

2013 ◽

Vol 367 ◽

pp. 292-296

Author(s):

Jian Xin Wang ◽

Xian Wei Gao ◽

Mei Li Sui ◽

Xiu Ying Li

Keyword(s):

Water Stress ◽

Soil Water ◽

Water Status ◽

Acoustic Emissions ◽

Signal Strength ◽

Acoustic Emission Event ◽

Plant Water ◽

Plant Water Stress ◽

Noise Interference ◽

Content Status

The soil water deficit and strong transpiration can give rise to the phenomenon of plant water stress. Because of the water stress produces the fracture of the water column in conduits, and the fracture is the reflection of energy release which can be detected by the ultrasonic acoustic emissions (UAEs) technology. In order to avoid background noise interference, the UAEs detecting frequency is between 100K Hz and 1 MHz. The PCI-2 data acquisition (DAQ) card and R15 sensors are used to improve the precision of UAEs detection. When the water stress and dehydration gets heavier, the UAEs get higher. Use the tomato plant data with the empirical deduction under the modern greenhouse conditions, the relationships among UAEs, transpiration and UAEs signal strength is described by curve. The UAEs signals occur generally from 5:00~7:00 am, and stop after 20:00 at night. In the daytime, when the plant body water storage is few, and transpiration is strong, the UAEs occur two peaks, called the “Twin Peaks Area” (TPA). In the different conditions of soil water content status and environmental factors, the TPA occur time will be advance or lag, which is generally in the range of 8:00~15:00. An acoustic emission event maybe produces several UAEs counts, while the UAEs counts have a correspondence with the UAEs signal strength. It is better to use UAEs technique to diagnose the plant water status and carry out automatic and precise irrigation for the plant and to improve the effect of Water-saving irrigation.

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