scholarly journals Effects of water stress on evapotranspiration of soybean

2021 ◽  
pp. 118-127
Author(s):  
O. V. Zhuravlov ◽  
A. P. Shatkovskyi ◽  
V. V. Vasiuta
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Water Balance ◽  
Comparative Assessment ◽  
Percentage Error ◽  
Calculation Methods ◽  
Stress Coefficient ◽  
Daily Evapotranspiration ◽  
Water Stress Coefficient

Based on the results of observations, it was specified that when decreasing soil moisture there is a disproportionate decrease in the average daily evapotranspiration (ET). Thus, in the range of soil moisture of 94-80% minimum moisture-holding capacity (MMHC) ET was 9,76 mm a day, and in the range of 70-62% MMHC - its value decreased by 3 times. When the soil moisture reached 58,5% MMHC, the value of ET did not exceed 0,5 mm a day, which is 20 times less than the initial one. It was determined that the decrease in soil moisture by 10% in the range of 90 - 70% MMHC occurs during 3 days, and from 70 to 60% MMHC and from 60 to 58% MMHC - during 8 days. When soil moisture is 70% MMHC and below, the actual evapotranspiration is less than ETo that proves the effect of water stress on soybeans ET. When calculating water stress coefficient (Ks), a mathematical model based on the dependence of Ks on soil moisture as a percentage of MMHC was obtained. The average absolute percentage error (MAPE) is 8,6%, which corresponds to the high accuracy of the obtained dependence. In the range of soil moisture from 58 to 80% MMHC, the water stress coefficient is calculated by the formula Ks =-0.0011·FC²+0.1925·FC-7,4541. When having soil moisture as 80% MMHC and above, Ks = 1. A comprehensive comparative assessment of existing methods for calculating waster stress coefficient Ks was taken and it was found out that the actual values of Ks when having soil moisture as 80-70 and 60-65% MMHC by 8-14 % and 72-32 %, respectively, less than Ks FAO 56, and by 35-40 % larger than those determined by Saxton method. It was proved the need of taking into account the reduction in evapotranspiration when calculating water balance under water stress of plants. The calculation of evapotranspiration (ETs) by the Penman-Monteith method, without taking into account the water stress coefficient, showed that the value of the actual and calculated water balance coincides only when soil moisture does not exceed 62% MMHC. With a further decrease in soil moisture, the estimated soil moisture was 20% less than the actual, which led to the errors in determining soil moisture after irrigation, because its actual value was almost 100% MMHC, and the estimated one was only 60% MMHC. It was proved that the determination of water balance by calculation methods without taking into account the water stress coefficient leads to significant errors.

scholarly journals Determination of Wheat Growth, Crop Coefficient (KC) and Water Stress Coefficient (Ks) under Different Salinity

2016 ◽  
Author(s):  
Meysam Abedinpour
Keyword(s):  
Water Stress ◽  
Crop Coefficient ◽  
Crop Growth ◽  
Growth Patterns ◽  
Wheat Crop ◽  
Growth Stages ◽  
Stress Coefficient ◽  
Salinity Levels ◽  
Water Stress Coefficient

A field experiment was conducted for determination of crop coefficient (KC) and water stress coefficient (Ks) for wheat crop under different salinity levels, during 2015-16. Complete randomized block design of five treatments were considered, i.e., 0.51 dS/m (fresh water) as a control treatment and other four saline water treatments (4, 6, 8 and 10 dS/m), for S1, S2, S3 and S4 with three replications. The results revealed that the water consumed by plants during the different crop growth stages follows the order of FW>S1>S2>S3>S4 salinity levels. According to the obtained results, the calculated values of crop coefficients significantly differed from those suggested by FAO No.56 for the crops. The Ks values clearly differ from one stage to another because the salt stress causes both osmotic stress, due to a decrease in the soil water potential, and ionic stress which the average values of water stress coefficient (Ks) follows this order; FW(1.0)=S1(1.0)>S2(1.0)>S3(0.93)>S4(0.82). Overall, it was found the differences are attributed primarily to specific cultivar, the changes in local climatic conditions and seasonal differences in crop growth patterns. Thus, further studies are essential to determine the crop coefficient values under different variables, to make the best management practice (BMP) in agriculture.

scholarly journals Water stress coefficient determined by orbital remote sensing techniques

2020 ◽  
Vol 24 (12) ◽  
pp. 847-853
Author(s):  
Élvis da S. Alves ◽  
Roberto Filgueiras ◽  
Lineu N. Rodrigues ◽  
Fernando F. da Cunha ◽  
Catariny C. Aleman
Keyword(s):  
Remote Sensing ◽  
Water Stress ◽  
Irrigation Management ◽  
Simple Algorithm ◽  
Landsat 8 ◽  
Stress Coefficient ◽  
Use Efficiency ◽  
Remote Sensing Techniques ◽  
Water Stress Coefficient ◽  
The Relationship

ABSTRACT In regions where the irrigated area is increasing and water availability is reduced, such as the West of the Bahia state, Brazil, the use of techniques that contribute to improving water use efficiency is paramount. One of the ways to improve irrigation is by improving the calculation of actual evapotranspiration (ETa), which among other factors is influenced by soil drying, so it is important to understand this relationship, which is usually accounted for in irrigation management models through the water stress coefficient (Ks). This study aimed to estimate the water stress coefficient (Ks) through information obtained via remote sensing, combined with field data. For this, a study was carried out in the municipality of São Desidério, an area located in western Bahia, using images of the Landsat-8 satellite. Ks was calculated by the relationship between crop evapotranspiration and ETa, calculated by the Simple Algorithm for Evapotranspiration Retrieving (SAFER). The Ks estimated by remote sensing showed, for the development and medium stages, average errors on the order of 5.50%. In the final stage of maize development, the errors obtained were of 23.2%.

scholarly journals A conceptual dynamic vegetation-soil model for arid and semiarid zones

2008 ◽  
Vol 12 (5) ◽  
pp. 1175-1187 ◽  
Author(s):  
D. I. Quevedo ◽  
F. Francés
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Water Balance ◽  
Water Availability ◽  
Leaf Biomass ◽  
Soil Conditions ◽  
Model Parameters ◽  
Arid Zones ◽  
Soil Model ◽  
Arid And Semiarid

Abstract. Plant ecosystems in arid and semiarid climates show high complexity, since they depend on water availability to carry out their vital processes. In these climates, water stress is the main factor controlling vegetation development and its dynamic evolution. The available water-soil content results from the water balance in the system, where the key issues are the soil, the vegetation and the atmosphere. However, it is the vegetation, which modulates, to a great extent, the water fluxes and the feedback mechanisms between soil and atmosphere. Thus, soil moisture content is most relevant for plant growth maintenance and final water balance assessment. A conceptual dynamic vegetation-soil model (called HORAS) for arid and semi-arid zones has been developed. This conceptual model, based on a series of connected tanks, represents in a way suitable for a Mediterranean climate, the vegetation response to soil moisture fluctuations and the actual leaf biomass influence on soil water availability and evapotranspiration. Two tanks were considered using at each of them the water balance and the appropriate dynamic equation for all considered fluxes. The first one corresponds to the interception process, whereas the second one models the evolution of moisture by the upper soil. The model parameters were based on soil and vegetation properties, but reduced their numbers. Simulations for dominant species, Quercus coccifera L., were carried out to calibrate and validate the model. Our results show that HORAS succeeded in representing the vegetation dynamics and, on the one hand, reflects how following a fire this monoculture stabilizes after 9 years. On the other hand, the model shows the adaptation of the vegetation to the variability of climatic and soil conditions, demonstrating that in the presence or shortage of water, the vegetation regulates its leaf biomass as well as its rate of transpiration in an attempt to minimize total water stress.

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

2010 ◽  
Vol 14 (10) ◽  
pp. 2099-2120 ◽  
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 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.

scholarly journals Water balance for determination of excess water in soybean cultivated in lowland soils

2021 ◽  
Vol 16 (3) ◽  
pp. 1
Author(s):  
Mateus Possebon Bortoluzzi ◽  
Paulo Ivonir Gubiani ◽  
Arno Bernardo Heldwein ◽  
Roberto Trentin ◽  
Jocélia Rosa da Silva ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Lower Limit ◽  
The Other ◽  
Water Drainage ◽  
Crop Evapotranspiration ◽  
Soil Layers ◽  
Volumetric Soil Moisture ◽  
Excess Water

The aim of this study was to derive a methodology for calculating a sequential water balance that accurately estimates the occurrence of excess water in soybeans cultivated in lowlands. We tested four calculation strategies of water balance associated with the simulation of soybean development, which differed on the calculation of rainfall and time of water drainage from the soil macropores. Data of volumetric moisture monitored in three soil layers throughout the soybean cycle in the 2014/15 agricultural year were used as a reference. Microporosity was used as a lower limit for the occurrence of excess water in the area. Excess water was considered to be whenever the daily volumetric soil moisture in the 0-100 mm layer was greater than 0.39 mm3 mm-3. Over the 111 days of measurement, soil moisture indicated the presence of excess water in 38 days. The traditional calculation strategy of water balance underestimated the occurrence of excess water, as well as the other strategies that considered effective precipitation in their formulas. The calculation strategy that considers that all the rainfall infiltrates in the soil and that the water from macropores is removed only by crop evapotranspiration exhibited good performance and indicated 35 days of excess water, being the most appropriate and recommended for determining excess water in lowland soybeans.

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

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.

scholarly journals Wheat water use and yield under different salinity of irrigation water

2017 ◽  
Vol 33 (1) ◽  
pp. 3-9 ◽  
Author(s):  
Meysam Abedinpour
Keyword(s):  
Water Stress ◽  
Block Design ◽  
Regional Scale ◽  
Soil Water Potential ◽  
Crop Coefficient ◽  
Wheat Crop ◽  
Growth Stages ◽  
Stress Coefficient ◽  
Salinity Levels ◽  
Water Stress Coefficient

Abstract A field experiment was conducted for determination of crop coefficient (KC) and water stress coefficient (Ks) for wheat crop under different salinity levels, during 2015–2016. Complete randomized block design of five treatments were considered, i.e., 0.51 dS·m−1 (fresh water, FW) as a control treatment and other four saline water treatments (4, 6, 8 and 10 dS·m−1), for S1, S2, S3 and S4 with three replications. The results revealed that the water consumed by plants during the different crop growth stages follows the order of FW > S1 > S2 > S3 > S4 salinity levels. According to the obtained results, the calculated values of KC significantly differed from values released by FAO paper No 56 for the crops. The Ks values clearly differ from one stage to another because the salt accumulation in the root zone causes to reduction of total soil water potential (Ψt), therefore, the average values of water stress coefficient (Ks) follows this order; FW(1.0) = S1(1.0) > S2(1.0) > S3(0.93) > S4(0.82). Precise data of crop coefficient, which is required for regional scale irrigation management is lacking in developing countries. Thus, the estimated values of crop coefficient under different variables are essential to achieve the best management practice (BMP) in agriculture.

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