Impact of groundwater depth on crop coefficient: An improved evapotranspiration model

An understanding of evapotranspiration, which is an important component of the surface water cycle, is critical in water resource management and planning, and in meeting the water requirements of agriculture and ecological systems. Although the methods for calculating crop evapotranspiration are advanced in humid areas, the understanding of evapotranspiration in semi-arid areas is developing because evapotranspiration is significantly affected by drought. The classic crop evapotranspiration model and crop coefficients cannot be applied to estimations of actual evapotranspiration, which is rarely studied now. In this study, we analyzed differences between lysimeter evapotranspiration and evapotranspiration that was estimated with Food and Agriculture Organization (FAO)-recommended crop coefficients. In addition, changes in evapotranspiration according to the degree of drought stress were analyzed with lysimeters, evaporating dishes, ultrasonic and eddy instruments, and conventional meteorological data in spring wheat fields in typical semi-arid zones of the Dingxi arid ecological environment comprehensive scientific experiment station, which is located in the Loess Plateau. The variations in spring wheat reference evapotranspiration/pan evaporation and actual evapotranspiration/pan evaporation according to the degree of drought stress and the effects of drought stress on the spring wheat crop coefficients in this area were studied. Because crop evapotranspiration is significantly affected by drought stress in semi-arid areas, the differences between lysimeter evapotranspiration and evaporation that was estimated with FAO-recommended crop coefficients were very significant. Crop coefficients were highly dependent on drought stress, and this dependence increased according to the reduction in the degree of drought stress. In addition, its sensitivity was significantly lower after the drought stress reached about 0.7. In this study, crop coefficients that were modified during the crop development and exuberant period were far below the FAO-recommended values and the Kumar correction values. The modified crop coefficients were obviously closer to the actual observed values than the spring wheat evapotranspiration values that were estimated using other crop coefficient. The coefficient of linear fitting of the modified crop coefficient and the observations was 0.98. The coefficient of determinationwas 0.45, and the standard error was 0.85. Therefore, the modified crop coefficient was effective for estimating crop evapotranspiration in semi-arid areas.

Abstract. Irrigation agriculture plays an increasingly important role in food supply. Many evapotranspiration models are used today to estimate the water demand for irrigation. They consider different stages of crop growth by empirical crop coefficients to adapt evapotranspiration throughout the vegetation period. We investigate the importance of the model structural versus model parametric uncertainty for irrigation simulations by considering six evapotranspiration models and five crop coefficient sets to estimate irrigation water requirements for growing wheat in the Murray–Darling Basin, Australia. The study is carried out using the spatial decision support system SPARE:WATER. We find that structural model uncertainty among reference ET is far more important than model parametric uncertainty introduced by crop coefficients. These crop coefficients are used to estimate irrigation water requirement following the single crop coefficient approach. Using the reliability ensemble averaging (REA) technique, we are able to reduce the overall predictive model uncertainty by more than 10%. The exceedance probability curve of irrigation water requirements shows that a certain threshold, e.g. an irrigation water limit due to water right of 400 mm, would be less frequently exceeded in case of the REA ensemble average (45%) in comparison to the equally weighted ensemble average (66%). We conclude that multi-model ensemble predictions and sophisticated model averaging techniques are helpful in predicting irrigation demand and provide relevant information for decision making.

Evapotranspiration was estimated by crop coefficient method and Penman-Montieth model of drip and furrow irrigation in northern Xinjiang. Result showed crop coefficient consistented with the typical “S” curve. There was no significant difference of total evapotranspiration between drip and furrow irrigation. Dual crop coefficient approach was better than single crop coefficient approach in the cotton field. Furthermore, relationship between evapotranspiration and LAI was established and justified, thus this model could be used to simulate water demand of cotton field in arid area.

The study was carried out to select a best reference crop evapotranspiration model (ET(r)), developed crop coefficient (K(c)) and actual evapotranspiration of pomegranate (ET(c)) for Solapur (North latitude 17°10” to 18°32” and East longitude 74°42” to 76°15”) at 483.5 m asl in the semi-arid zone of Maharashtra. Six most commonly used reference crop evapotranspiration models were selected for testing their validity under the climatic conditions. The important reference evapotranspiration models are: (i) Penman-Monteith FAO-56 model, (ii) Modified Penman FAO-24 model, (iii) Hargreaves Samani model, (iv) FAO-24 Pan Evaporation model (v) Blaney Criddle model, and (vi) FAO Radiation model. For the estimation of shaded area at solar noon hour, a plywood board of 3.5×3.5 m size with grid marking of size 10×10 cm was used. Actual pomegranate evapotranspiration was determined by the crop coefficient approach where the effects of various weather conditions were incorporated into reference crop evapotranspiration and crop characteristics into crop coefficient. Testing of these models was done on the basis of the least root mean square error and regression analysis. Radiation method are higher followed by modified Penman method, Blanney Criddle, pan evaporation, Hargreaves-Samani and Penman Monteith. Out of six models the Hargreaves Samani method was found to least root mean square error under climatic conditions of Solapur region. The measured shaded area at solar noon increased from new leaf initiation to maturity of crop ranging from 0.68 to 10.80 m2 and decreased from harvesting period 10.80 to 7.43 m2. The water requirement of crop development and maturity period ranges from 32.85 to 65.75 L/tree/day. The crop coefficient values increased ranging from 0.15 to 1.20 from new leaf initiation to maturity period of the crop and the seasonal water requirement for the pomegranate crop during the kharif season varies from 9.6 to 65.75 L/tree/day. The present study is based on analysis of long term (25 years) climatic data and measured shaded area at solar noon of 5th year pomegranate orchards.

Evaluation of reference evapotranspiration models and determination of crop coefficient for Momordica charantia and Capsicum annuum

Current stormwater control measure (SCM) design often does not include the dynamic process of evapotranspiration (ET) for vegetated systems. This study compared two reference ET equations with a three-year data set from rain garden weighing lysimeters. The outcome was a tool to incorporate ET into SCM design. The weighing lysimeters at Villanova University, located in southeastern Pennsylvania, were used to measure water budget parameters for three scenarios: sandy loam with UO, sand with an unconstricted outflow (UO), and sand with internal water storage (IWS). The two ET models explored were the ASCE Penman-Monteith equation (a robust model) and the Hargreaves equation (a simple model). Estimated ET values from these two equations, both with and without modifications for water availability and crop presence, were compared and calibrated (if modified) with observed data. Comparisons and calibrations were performed on a daily and storm basis to explore the applicability of the two ET models for continuous and storm approaches. The observed ET was 28%–52% of inflow over the continuous three-year period and 16–30 mm on a storm scale, making ET a significant part of the lysimeters’ water budget. Due to the experimental nature of the lysimeters, 12 of the 36 study months had additional simulated runoff, such that a smaller ET as a percentage of inflow was expected in the rain garden SCM’s water balance. The Hargreaves and ASCE Penman-Monteith equations without modification provided an adequate estimate for rain garden ET for all systems at the storm scale. Modifications to ET estimations produced by both equations through crop coefficients and a soil moisture extraction function provided a good model for storm-scale ET by reducing errors and increasing efficiencies for all weighing lysimeter types. Evapotranspiration estimates from both unmodified equations provided, at best, a marginally better estimate than the average observed rate for continuous daily rain garden ET. The application of crop coefficients and a soil moisture extraction function to both equations reduced errors in ET estimates and increased the equations’ predictive power (Nash-Sutcliffe efficiency) for all weighing lysimeter types. Both equations with modifications on a daily scale produced good ET estimates for the IWS system. For both equations, crop coefficients were found in an expected range for UO systems (0.3–1.5) but were high in the IWS system (1.6–2.0). Soil moisture extraction functions were not needed to calibrate the IWS equations on the storm scale. Both the Hargreaves equation and the ASCE Penman-Monteith equation provided an adequate model (especially with modifications) to incorporate ET into a design-storm approach to SCM design. Use of both predictive models on a daily scale has potential use in continuous simulation, as in most cases the ET estimations predicted by the equations provided a better estimate than the average of the observed daily ET rates.

Water scarcity, soil salinization, and desertification threaten sustainable agricultural ecosystems of Hetao irrigation district, Yellow River Basin (YRB). Precise quantification of soil water dynamics and plant water consumption processes is essential for the agricultural sustainability of the irrigation district. Therefore, this study mainly focused on the crop coefficients and water consumption processes of three representative plant types in the Hetao irrigation district, each corresponding to a specific land system: Helianthus annuus (cultivated land), Tamarix chinensis (wasteland), and Phragmites australis (lake). The SIMDualKc model was calibrated and validated based on situ observation data (soil water content and yield) during 2018 (conventional conditions), 2023 and 2024 (deep water-saving conditions). Results show strong agreement between simulated and observed soil moisture and crop yields. The results indicate that the process curves of Kcb (basal crop coefficient) and Kcbadj (adjusted crop coefficient) nearly overlapped for the three plant types in 2018 and 2023. However, under the deep water-saving project implemented in 2024, the Kcbadj process curves for all three plant types exhibited a significant reduction (approximately 15%). Soil evaporation fractions (E/ETcadj) were stable at 19–30% during the 2018, 2023, and 2024. The contribution of capillary rise to ET reached 38.61–43.18% in cultivated land (Helianthus annuus), 41.52–48.93% in wasteland (Tamarix chinensis), and 38.08–46.57% in lake boundary areas (Phragmites australis), which underscores the significant role of groundwater recharge in sustaining plant water consumption. Actual-to-potential transpiration ratios (Ta/Tp) during 2023–2024 decreased by 3–11% for Helianthus annuus, 5–12% for Tamarix chinensis, and 23% for Phragmites australis compared to Ta/Tp values in 2018. Capillary rise decreased approximately 10% during the whole system. Deep water-saving practices increased the groundwater depth and restricted groundwater recharge to plants via capillary rise, thereby impairing plant transpiration and growth. These findings provide scientific support for sustainable agriculture and ecological security in the Yellow River Basin.

Models of water use for irrigation scheduling and for crop growth simulation require validation of the evapotranspiration (ET) submodel. In this study ET was measured for irrigated winter wheat (Triticum aestivum L.) at Bushland, Texas, in the semi-arid Southern High Plains for the 1989-1990, 1991-1992, and 1992-1993 winter wheat cropping seasons using weighing lysimeters that contained undisturbed monoliths 3 3 2.3 m deep of Pullman clay loam soil (Torrertic Paleustolls). Weather data from a nearby station were used to compute daily ET values for a reference alfalfa crop (hypothetical) using the ASCE Manual No. 70 equations based on the Penman-Monteith equation and several other widely used potential or maximum ET models. Linear regressions between ET estimated from widely used equations and the reference alfalfa ET equation indicated that direct comparisons with computed ET values could not be reliably predicted with simple ratios. For the computed reference alfalfa ET base, peak basal crop coefficients (Kcb) varied from 0.88 to 1.00 for the three seasons and were lower than those reported from other locations. Peak mean crop coefficients (Kc) varied from 0.83 to 0.94 for the three seasons. Seasonal ET varied from 791 to 957 mm for the three seasons. Evapotranspiration and crop coefficients for winter wheat varied considerably with season.

Soil water content estimation using a remote sensing based hybrid evapotranspiration modeling approach

Two common approaches for estimating crop evapotranspiration (ET) using satellite imagery are the reflectance-based crop coefficient method and the energy balance method. The reflectance-based crop coefficient method relates a reflectance-based vegetation index such as the soil adjusted vegetation index (SAVI) to ET basal crop coefficients such as those described by Wright (1982) [1] and the FAO 56 manual [2]. A time-series of remotely sensed inputs is then used to build the crop coefficient curve in each field being monitored. In order to obtain actual ET, a water balance must be maintained in the root zone of the crop in order to make the appropriate adjustments due to soil moisture deficits and wet soil surface from irrigation and/or rain. Ground meteorological data must be provided by a weather station located in the modeled area for the estimation of reference ET. In the energy balance approach, surface temperatures are used in the estimation of sensible heat fluxes and depending on the complexity of the model, different methods are used to either handle the aerodynamic temperature term or deal with sparse canopies (empirical approaches, two-source model, SEBAL model). Remotely sensed inputs are also used for the estimation of net radiation and soil heat flux, with latent heat flux (ET) obtained as a residual from the energy balance equation. The energy balance approach results in the actual ET being estimated directly. Instantaneous values of ET must be extrapolated to the entire day and over time in between satellite overpass inputs. This paper describes a hybrid approach that uses both methods in combination to monitor actual ET over a growing season for irrigated and non-irrigated crops. The model has been coded in an ArcGIS environment, using visual basic for the calculations. This paper describes the modeling environment and coded ET models within and presents some application results.

<p>Irrigation scheduling is one of the main factors that affect the crop ability to resist stress symptoms in addition to affecting directly the final yield. In the last decade, many remote sensing methods have been developed to help in scheduling irrigation with higher precision. Some of these methods estimate irrigation needs indirectly such as those using normalized difference vegetation index (NDVI) or crop coefficient curve, and other methods that directly calculate Evapotranspiration (ET) through satellite images. Cotton SmartIrrigation App (Cotton App) is one of the recent applications that have been developed to help farmers in scheduling irrigation during the growing season. The App is based on an interactive ET-based soil water balance model. In this study, remote sensing of Evapotranspiration has been used to detect and map crop water requirements in order to enhance the Cotton App predictions for irrigation schedule during the growing season. Two remote sensing ET models based on thermal infrared (TIR), The surface energy balance algorithm for land (SEBAL) and Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC), were used to derive ET over cotton. Results showed higher values of actual Evapotranspiration calculated by both SEBAL and METRIC models during the first 45 days of the growing season compared to the calculated values of ETa from crop coefficient. This is expected to be due to the higher evaporation fraction from bare soil since the plant cover is still very low and accordingly the plant transpiration too. However, later in the second growing stage, the models showed that the crop coefficient calculated ETa (ETa- Calculated) has overestimated the plant Evapotranspiration giving higher values compared to the values from the models. These results indicate that, the use of remote sensing techniques along with the ET-models will increase the app efficiency in giving more precise irrigation scheduling.</p>

This study aimed to determine cucumber crop coefficients under different greenhouse microclimatic conditions, parameterizing the Priestley-Taylor reference evapotranspiration model. Crop evapotranspiration was directly measured with the use of lysimeters, and crop coefficients were computed following the two-step climate FAO 56 methodology. Greenhouse compartments (i.e., cooled or uncooled) showed reference evapotranspiration differences of up to 12% in an autumn-winter crop. The results presented cucumber crop coefficient values from the initial to the late-season growth stages from 0.45 to 0.94 depending on the greenhouse climate. Based on the greenhouse hourly microclimatic variation of KC, it is recommended not to apply a KC as a constant for transpiration estimation even at greenhouses located within the same region Regression analysis relating crop coefficients with leaf area revealed very high correlation coefficients for the equations tested. The results indicated that evapotranspiration can be modeled satisfactory based on a significant relationship between crop coefficient and simple measurements of the leaf area index (i.e., KC = 0.447 × LAI).


 Accurate estimation of evapotranspiration of rapeseed is essentially required for irrigation scheduling and water management. The present study was undertaken during 2015-16 and 2017-18 in ICR Farm, Assam Agricultural University, Jorhat to determine the crop coefficients (Kc) and estimate evapotranspiration of rapeseed using lysimeter and eight reference evapotranspiration models viz. Penman-Monteith, Advection-Aridity (Bruitsaert-Strickler), Granger-Gray, Makkink, Blaney-Criddle, Turc (1961), Hargreaves-Somani and Priestly-Tailor models. During 2015-16, the crop coefficients were developed by these models. Actual evapotranspiration was determined by three weighing type lysimeters. During 2017-18, evapotranspiration was estimated by multiplying reference evapotranspiration with Kc derived by different models and compared with actual evapotranspiration estimated by lysimeter during similar growing periods. All the models except Turc (1961) showed less than 10% deviation between actual and estimated ET. The estimated evapotranspiration using Penman-Monteith and Priestly-Tailor reference evapotranspiration recorded the lowest MAE and RMSE. The study revealed that estimated evapotranspiration using Penman-Monteith reference evapotranspiration gave the best estimate of evapotranspiration of rapeseed followed by Priestly-Tailor. The crop coefficients for initial, mid and end stages were 0.83, 1.20 and 0.65, respectively for Penman-Monteith and 0.70, 1.05 and 0.55, respectively for Priestly-Tailor.These results can be used for efficient management of irrigation water for rapeseed.

Abstract: Efficient water management of crop requires accurate irrigation scheduling which, in turn, requires the accurate measurement of crop water requirement. Reference evapotranspiration plays an important role for the determination of water requirements for crops and irrigation scheduling. Various models/approaches varying from empirical to physically base distributed are available for the estimation of reference evapotranspiration. This study identified most suitable reference evapotranspiration model for sub-temperate, sub humid agro-climatic condition using climatic and lysimeter data. The Food and Agriculture Organization (FAO) recommended crop coefficient values are modified for the local agro-climatic conditions. The field experiment was conducted in sub-temperate and sub-humid agro-climate of Solan, Himachal Pradesh, India. Actual crop evapotranspiration for different crop growth stages of wheat (Triticum-aestivum) has been obtained from water balance studies using lysimeter set-up. Field observed and computed individual-stage wise crop evapotranspiration values are compared, to identify the most suitable reference evapotranspiration model for computing crop evapotranspiration. Penman Monteith model shows close agreement with observed value with coefficient of determination, standard error estimate and average relative discrepancy values of 0.96, 13.69 and -5.8, respectively. Further, an effort has been made to compare the accuracy of various widely used methods under different climatic conditions. Keywords: crop coefficient, crop evapotranspiration, reference evapotranspiration, lysimeter DOI: 10.3965/j.ijabe.20130604.003 Citation: Kumar R. Ecohydrologic modeling of crop evapotranspiration in wheat (Triticum-aestivum) at sub-temperate and sub-humid region of India. Int J Agric & Biol Eng, 2013; 6(4): 19－26.

Estimation of transpiration fluxes from rainfed and irrigated sugarcane in South Africa using a canopy resistance and crop coefficient model