Dual Crop Coefficient Approach Research Articles

Customizing pyfao56 for evapotranspiration estimation and irrigation scheduling at the Limited Irrigation Research Farm (LIRF), Greeley, Colorado

Estimation of evapotranspiration (ET, the water used by soil evaporation and plant transpiration) and soil water depletion (Dr, the amount of water to bring the soil water in the root zone to field capacity) are critical in irrigation water management. The open-source Python-based crop ET and water balance modeling package named “pyfao56” was originally developed based on the dual crop coefficient approach as described in the Food and Agricultural Organization of the United Nations, Irrigation and Drainage Paper No. 56 (FAO-56). The package later expanded on the seminal FAO-56 document to consider various options relevant to ET and water balance modeling, including both short (grass) and tall (alfalfa) reference crops, optional discretization of variable soil layers based on field capacity, and interpretation of readily available water (RAW) and Dr based on both a dynamic (growing) root zone and maximum root zone. The package requires two input data objects; the “Parameters” class defines variables affecting soil water balance and ET and the “Weather” class specifies relevant meteorological data. Other optional input data objects include the “Irrigation” class for irrigation events, the “Soil_Profile: class for defining stratified soil layer data, and the “Update” class for assimilation of measured data. Additional tools are available for estimating and forecasting standardized reference ET (ETref), providing seasonal water balance summaries, computing goodness-of-fit statistics between measured and modeled values, and visualizing time series plots of daily Dr, ET, and crop coefficients. The current pyfao56 release (v1.2.1) was incorporated into a customized workflow for specific use at the USDA-ARS Limited Irrigation Research Farm (LIRF) in Greeley, Colorado, and named the LIRF Implementation of Pyfao56 (LIRFIP). Field data from 2023 full and limited irrigation field trials were used to demonstrate the functionality of LIRFIP and its customizations and integration of pyfao56 into the LIRF workflow. Specific customizations included use of pyfao56 “customload” functions to input data from various sources, including weather from an on-site micrometerological station (using the application programming interface (API) developed by the maintainers of the Colorado Agricultural Meteorological (CoAgMet) weather station network), irrigation events (via a shared Google docs sheet), field capacity values by plot and soil layer (via an Excel spreadsheet), and measured soil water content as well as basal crop coefficient (Kcb) calculated from fractional canopy cover (fc) (via an SQLite database). To evaluate multiple research plots, LIRFIP was designed to iterate simulations from multiple instances of pyfao56 and to produce customized output summary files and interactive hypertext markup language (html) graphs as an aid for irrigation management decisions for LIRF field trials. This study demonstrated pyfao56 as a useful, flexible, customizable, and repeatable ET-based water balance model by showcasing its integration within a specific computational workflow for irrigation management field research at LIRF. The approach serves as an example for pyfao56 integration in other water management tools as conceived by water managers, researchers, and practitioners worldwide.

Evaluating maize evapotranspiration using high-resolution UAV-based imagery and FAO-56 dual crop coefficient approach

Timely and accurate estimation of crop evapotranspiration (ETc) is essential for efficient irrigation management at the farmland scale. However, effective decision-making for irrigation scheduling requires high spatiotemporal-resolution data to provide within-field heterogeneity information. The objective of this study was to evaluate the use of optical and thermal information obtained from an unmanned aerial vehicle (UAV) to quantify maize (Zea mays L.) ETc within the framework of the FAO-56 dual crop coefficient approach. Canopy temperature-based crop water stress index (CWSI) and number of degrees above canopy threshold (DACT) were used to determine the stress coefficient (Ks). Three types of normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI), and enhanced vegetation index (EVI) were adopted to determine basal crop coefficient (Kcb). Then the two forms of stress coefficient in combination with three vegetation indices (VIs) were evaluated to estimate daily crop ETc under different irrigation treatments over two years in the southwest region of Inner Mongolia, China. The results demonstrated that the combination of NDVI and CWSI produced the best estimates of maize ETc, with R2 of 0.84 and root mean square error (RMSE) of 0.50 mm/day. The DACT-based model also performed well, with R2 of 0.77–0.80 and RMSE of 0.53 mm/day. Although the results varied with irrigation levels, the daily mean bias error of ETc predictions over different years indicated acceptable accuracy, with a mean bias error (MBE) of 0.48 mm/day. Sensitivity analyses indicated that ETc models were most sensitive to the slope of the linear regression between Kcb and VIs, followed by soil evaporation constant and influential factor in Ks_DACT. From this study, the combinations of vegetation index and CWSI, as well as DACT, were recommended as alternative approaches for estimating ETc due to intrinsic simplicity and easy interpretation. These ETc models relying on UAV-based multi-sensor data thus show promising potential in farmland-scale applications.

Misconceptions of Reference and Potential Evapotranspiration: A PRISMA-Guided Comprehensive Review

One of the most important parts of the hydrological cycle is evapotranspiration (ET). Accurate estimates of ET in irrigated regions are critical to the planning, control, and regulation of agricultural natural resources. Accurate ET estimation is necessary for agricultural irrigation scheduling. ET is a nonlinear and complex process that cannot be calculated directly. Reference evapotranspiration (RET) and potential evapotranspiration (PET) are two primary forms of ET. The ideas, equations, and application areas for PET and RET are different. These two terms have been confused and used interchangeably by researchers. Therefore, terminology clarification is necessary to ensure their proper use. The research indicates that PET and RET concepts have a long and distinguished history. Thornthwaite devised the original PET idea, and it has been used ever since, although with several improvements. The development of RET, although initially confused with that of PET, was formally defined as a standard method. In this study, the Preferred Reporting Item for Systematic reviews and Meta-Analysis (PRISMA) was used. Equations for RET estimation were retrieved from 44 research articles, and equations for PET estimation were collected from 26 studies. Both the PET and RET equations were divided into three distinct categories: temperature-based, radiation-based, and combination-based. The results show that, among temperature-based equations for PET, Thornthwaite’s (1948) equation was mentioned in 12,117 publications, whereas among temperature-based equations for RET, Hargreaves and Samani’s (1985) equation was quoted in 3859 studies. Similarly, Priestley (1972) had the most highly cited equation in radiation-based PET equations (about 6379), whereas Ritchie (1972) had the most highly cited RET equations (around 2382) in radiation-based equations. Additionally, among combination-based PET equations, Penman and Monteith’s (1948) equations were cited in 9307 research studies, but the equations of Allen et al. (1998) were the subject of a significant number of citations from 23,000 publications. Based on application, PET is most often applied in the fields of hydrology, meteorology, and climatology, whereas RET is more frequently utilized in the fields of agronomy, agriculture, irrigation, and ecology. PET has been used to derive drought indices, whereas RET has been employed for single crop and dual crop coefficient approaches. This work examines and describes the ideas and methodologies, widely used equations, applications, and advanced approaches associated with PET and RET, and discusses future enhancements to increase the accuracy of ET calculation to attain accurate agricultural irrigation scheduling. The use of advanced tools such as remote sensing and satellite technologies, in addition to machine learning algorithms, will help to improve the accuracy of PET and RET estimates. Researchers will be able to distinguish between PET and RET in the future with the use of the study’s results.

Changes and determining factors of crop evapotranspiration derived from satellite-based dual crop coefficients in North China Plain

Evaluating actual crop evapotranspiration (ETc) variations and their determining factors under changing climates is crucial for agricultural irrigation management and crop productivity improvement in non-humid regions. This study analyzed the spatiotemporal characteristics and detected the determining factors of ETc for winter wheat and summer maize rotation system from 2000 to 2017 in the North China Plain (NCP), by combining the FAO-56 dual crop coefficient approach with remotely sensed vegetation indices (VIs). The results indicated that daily air temperature increased in varying degrees while wind speed and sunshine hours decreased slightly during the growing season of winter wheat and summer maize over the study period. The trends of relative humidity and effective precipitation varied in crop growing seasons. Based on the validated relationship of dual crop coefficients and VIs, the estimated multi-year average ETc of winter wheat (370.29 ± 31.28 mm) was much higher than summer maize (281.85 ± 20.14 mm), and the rotation cycle was 652.43 ± 27.67 mm. Annual ETc of winter wheat and the rotation cycle increased by 2.96 mm a−1 and 1.77 mm a−1, respectively. However, the ETc of summer maize decreased with distinct spatial variation. Spatially, winter wheat ETc increased significantly in the northeast NCP, covering the Beijing-Tianjin-Hebei areas. Meanwhile, significant increases in summer maize ETc were detected in the southwest NCP. The sensitivity and contribution analysis showed that ETc of winter wheat and summer maize was positively sensitive to temperature, wind speed, and sunshine hours while negatively to relative humidity. Moreover, wind speed and sunshine hours contributed most to changes in ETc (around 20%–40%).

Influence of different levels of irrigation and black plastic mulch on the performance of banana under drip irrigation

India, a leading fruit producing country, ranks first in banana cultivation. The crop is highly water demanding and that appears as a limitation in several areas. However, micro-irrigation has the potential to address the issue. Moreover, mulching with black plastic sheet further facilitates efficient water use. The combined application of micro-irrigation and black plastic mulch is potentially important for enhancing water use efficiency and crop productivity. Based on the above facts, a field trial was conducted to evaluate the performance of micro-irrigation levels and black plastic mulch on the performance of banana yield in the sub humid climatic condition in lateritic belt during 2019–2020. Modified penman-Montieth equation was used to estimate the crop water requirement considering the recorded local climatic data. Water requirement of banana under drip and plastic mulch may vary with non-mulched banana. Therefore, the dual crop coefficient approach has been used to estimate the crop coefficients (K) of banana under drip with black plastic mulch and without mulch conditions. The total water requirement of banana was estimated to be 1089 mm and 919 mm under non-mulched and black plastic mulched banana, respectively. To determine the optimum quantity of irrigation water requirement of banana, eight treatments were considered consisting of four irrigation levels, namely, 1.0 volume with drip (VD), 0.8 VD, 0.6 VD and 0.4 VD in combination with black plastic mulch and non-mulch. The results revealed that 0.8 VD along with black plastic mulch recorded better crop growth and yield parameters with higher yield in comparison to other treatments. Further, the treatment also resulted in maximum benefit cost ratio of 4.97.

Estimating and partitioning maize evapotranspiration as affected by salinity using weighing lysimeters and the SIMDualKc model

Water scarcity and saline stress are primary threats for water use and agricultural production in arid and semi-arid regions, such as the Hetao Irrigation District, China. The current study, using irrigation with saline water, developed through three seasons (2017–2019) of field experimental surveillance of mulched maize water use in two cropped weighing lysimeters. Measurements included crop characteristics (height, LAI, dates of development stages), soil and water salinity, and daily actual crop evapotranspiration (ETc act). Deficit surface irrigation was scheduled in 2017 and 2018 seasons, while in 2019 drip irrigation was used aimed at satisfying crop water requirements. Both approaches aimed at improving irrigation management while controlling impacts of salinity. The collected information was used to parameterize and calibrate the soil water balance model SIMDualKc. The model uses the FAO56 dual crop coefficient approach and considers the combined effect of water and salinity stresses due to salinity of both soil and irrigation water. Results show that the SIMDualKc model adequately simulates the dynamics of the observed ETc act throughout the three growing seasons. The goodness-of-fit indicators show highly appropriate model fitting of observed ETc act with low RMSE of 0.42 mm d-1 for the calibration and 0.53 mm d-1 for validation. The calibrated standard basal crop coefficients (Kcb) of maize for the initial, mid, and end stages were respectively 0.15, 1.15 and 0.25, which agree with those recently proposed by Pereira et al. (2021). Due to the impacts of both water and salt stress in 2017 and 2018, ETc act was much below the potential value ETc, ranging 64–83%, while in 2019 that percentage increased to 92% due to avoiding water stress by then. The average Kcb mid act range 0.58–1.06, therefore lower than Kcb mid, with the lower values occuring in the lysimeter that was irrigated with a large deficit. The irrigation scheduling practiced was assessed using water use and productivity indicators, which have shown the advantage in using drip irrigation with small time intervals between irrigations. Moreover, the current study and the calibrated model provide for adopting irrigation management practices that may save water and control salinity.

Yield and evapotranspiration characteristics of potato-legume intercropping simulated using a dual coefficient approach in a tropical highland

An accurate estimation of crop evapotranspiration and soil water balance under potato-legume intercropping is important for improving the crop water productivity of rainfed potato. This study quantified the evapotranspiration, yield, and soil water balance of potato (Solanum tuberosum L.) intercropped with lima bean (Phaseolus lunatus L.) or dolichos (Lablab purpureus L.) in comparison to the same crops under monocropping. The experiment was set up in three agroecological zones of Kenya: upper midland (with an altitude range of 1500–1653 m above sea level (masl)), lower highland (1892–1923 masl) and upper highland (2502–2594 masl). The dual crop coefficient approach was adopted with the SIMDualKc model to estimate crop evapotranspiration and compute the soil water balance. The dual crop coefficient partitions crop evapotranspiration into crop transpiration and soil evaporation by applying both soil evaporation and basal crop coefficient. The model was calibrated and validated using field data observed along four crop growth seasons. The basal crop coefficients, the ratios of soil evaporation to evapotranspiration, and that of transpiration to evapotranspiration were determined. The yields of different intercrops were converted into equivalent yield of potato based on price of the produce. Good agreement between the observed and simulated data for available soil water and crop evapotranspiration was found with modeling efficiency > 0.8. The residual mean square error was low and ranged from 0.01−0.08 m3 m-3 for available soil water and 0.03−0.09 mm d-1 for crop evapotranspiration. The transpiration to actual evapotranspiration ratio of potato-legume intercropping was 6−28% greater than that of the sole potato because legume intercrops fully covered the ground by mid-season, thus limiting the energy available for soil evaporation. Crop yields were significantly greater under intercropping as transpiration occurred near its potential rate, thus not limiting yields. These results support the dual crop coefficient method as an appropriate tool to estimate and accurately partition crop evapotranspiration under potato-legume intercropping.

Dual Crop Coefficient Approach in Vitis vinifera L. cv. Loureiro

Vineyard irrigation management in temperate zones requires knowledge of the crop water requirements, especially in the context of climate change. The main objective of this work was to estimate the crop evapotranspiration (ETc) of Vitis vinifera cv. Loureiro for local conditions, applying the dual crop coefficient approach. The study was carried out in a vineyard during two growing seasons (2019–2020). Three irrigation treatments, full irrigation (FI), deficit irrigation (DI), and rainfed (R), were considered. The ETc was estimated using the SIMDualKc model, which performs the soil water balance with the dual Kc approach. This balance was performed by calculating the basal coefficients for the grapevine (Kcb crop) and the active soil ground cover (Kcb gcover), which represent the transpiration component of ETc and the soil evaporation coefficient (Ke). The model was calibrated and validated by comparing the simulated soil water content (SWC) with the soil water content data measured with frequency domain reflectometry (FDR). A suitable adjustment between the simulated and observed SWC was obtained for the 2019 R strategy when the model was calibrated. As for the vine crop, the best fit was obtained for Kcb full ini = 0.33, Kcb full mid = 0.684, and Kcb full end = 0.54. In this sense, the irrigation schedule must adjust these coefficients to local conditions to achieve economically and environmentally sustainable production.

Transpiration and Water Use of an Irrigated Traditional Olive Grove with Sap-Flow Observations and the FAO56 Dual Crop Coefficient Approach

The SIMDualKc model was applied to evaluate the crop water use and the crop coefficient (Kc) of an irrigated olive grove (Olea europaea L.) located in Sicily, Italy, using experimental data collected from two crop seasons. The model applies the FAO56 dual Kc approach to compute the actual crop evapotranspiration (ETc act) and its components, i.e., the actual tree transpiration (Tc act), obtained through the basal crop coefficient (Kcb), and soil evaporation according to an evaporation coefficient (Ke). Model calibration was performed by minimizing the difference between the predicted Tc act and the observed daily tree transpiration measured with sap flow instrumentation (TSF field) acquired in 2009. The validation was performed using the independent data set of sap flow measurements from 2011. The calibrated Kcb was equal to 0.30 for the initial and non-growing season stages, 0.42 for the mid-season, and 0.37 for the end season. For both seasons, the goodness-of-fit indicators relative to comparing TSF field with the simulated Tc act resulted in root mean square errors (RMSE) lower than 0.27 mm d−1 and a slope of the linear regression close to 1.0 (0.94 ≤ b0 ≤ 1.00). The olive grove water balance simulated with SIMDualKc produced a ratio between soil evaporation (Es) and ETc act that averaged 39%. The ratio between actual (ETc act) and potential crop evapotranspiration (ETc) varied from 84% to about 99% in the mid-season, indicating that the values of ETc act are close to ETc, i.e., the adopted deficit irrigation led to limited water stress. The results confirm the suitability of the SIMDualKc model to apply the FAO56 dual Kc approach to tree crops, thus assessing the water use of olives and supporting the development of appropriate irrigation management tools that are usable by farmers. A different way to estimate Kcb is based on the approach suggested in 2009 by Allen and Pereira (A&P), which involves the measured fraction of ground covered (shaded) by the crop and the height of the trees. Its application to the studied grove produced the mid-season Kcb values ranging from 0.40–0.45 and end-season Kcb values ranging from 0.35–0.40. The comparison between the A&P-computed Tc act A&P and TSF field shows RMSE values ranging from 0.27 to 0.43 mm d−1, which demonstrates the adequacy of the latter approach for parameterizing water balance models and for irrigation scheduling decision making.

Application of reflectance based vegetation index to derive dual crop co-efficient for summer sesame

Dual crop co-efficient approach was applied to estimate seasonal water requirement for summer sesame using reflectance based vegetation indices. Field experiment was conducted to collect the required various crop physiologic parameters and NDVI data for the study crop during 2018 and 2019. Basal crop co-efficients and soil evaporation co-efficients collected from FAO-56 for initial mid and end stages of summer sesame were adjusted for study area using local weather parameters. Spectrum® Field Scout CM 1000 NDVI Meter were used to collect the NDVI data at various stages of study crop. The NDVI was measured from crop canopy and soil surface at 7 days intervals between 12.00 to 13.00 clocks. NDVI Based Basal Crop Co-efficient and Soil evaporation co-efficient were derived using standard methods. FAO estimated crop co-efficients were compared with NDVI based crop co-efficients. The co-efficient of determination of the fitted regression equation was found to be 0.836 and 0.765 for drip irrigation and 0.783 and 0.867 for surface control irrigation system for summer sesame during 2018 and 2019, respectively. Crop growing stage wise water requirement per unit area was estimated for both treatments. Results indicates that among these two methods, NDVI method estimate lowest water requirement in both cases i.e. total water requirement and during all the crop growth stages for both irrigation systems while daily crop water requirement was lower for all growth stages in drip system as compare with control system.

Spatial prediction of crop water requirement under evapotranspiration-based irrigation management: a case study in the Tropic of Cancer zone of India

Advances in information and communication technology facilitate the application of complex models for optimising agricultural water management. This study uses meteorological parameters to estimate the volume of water required to grow crops in the Bhilai region of the state of Chhattisgarh in India. Using the dual crop coefficient approach and remote sensing imagery, this study provides an easy-to-use method that can be employed to determine the water demand for crops. This research aims to estimate the ET of rice crops in the Bhilai region using the decision support software package and geographical information system techniques. Landsat8 satellite images acquired at different seasons were used to determine the normalised difference vegetation index, and ET was calculated to analyse the crop water requirements for each month during different crop seasons. Preliminary results have shown that the demand for water varies between cultivated rice fields with different soil types and land use capabilities.

Evapotranspiration and crop coefficients from lysimeter measurements for sprinkler-irrigated canola

Canola is a water-stress tolerant crop, which could be an alternative in areas with limited water resources. However, in arid and semi-arid environments where rainfall events are scarce and increasingly erratic, the use of irrigation is necessary for canola production to reach its maximum yield. The goal of this study was to determine the crop evapotranspiration (ETc) and crop coefficients of sprinkler irrigated canola (Brassica napus L.) under non-limiting soil water content conditions. A 2-year field experiment was conducted in the lysimeter facility located in Albacete (SE Spain). A large weighing lysimeter (2.7 × 2.3 × 1.7 m), with an accuracy of 0.04 mm equivalent water depth, was used to measure the daily crop evapotranspiration (ETc) rate throughout two growing seasons. ETc values were determined using daily mass change in the lysimeter. Cumulative ETc was replaced in the lysimeter through sprinkler irrigation applications, thus crop water stress was avoided. Seasonal lysimeter based (measured) canola ETc was 472 and 602 mm in 2008 and 2012, respectively. The 28 % higher ETc value in 2012 was mainly due to a much higher evaporative demand during the crop growth mid-season period of 2012. The Kc values were determined using grass reference evapotranspiration (ETo) calculated with the FAO56 Penman-Monteith equation and the ETc calculations from the lysimeter data. The dual crop coefficient approach was used to separate crop transpiration (Kcb) from soil evaporation (Ke). For the two canola seasons, mid-season Kc and Kcb values, after FAO56 climate adjustment, were Kc mid (std) = 1.15 and Kcb mid (std) = 1.11. Those values were reached coinciding with maximum fraction of ground cover (fc) values of up 0.95 and 0.97 for 2008 and 2012, respectively. The seasonal evaporation component for sprinkler-irrigated canola was estimated to be about 24 % and 19 % of ETc in 2008 and 2012, respectively. The good linear relationship found between canola Kcb values and fc and the excellent agreement found between remotely sensed vegetation indices (VIs) and different biophysical parameters, such as Kcb and fc, will allow monitoring and estimating the spatially distributed water requirements of canola at field and regional scales using multispectral satellite imagery.

The Dynamic Yield Response Factor of Alfalfa Improves the Accuracy of Dual Crop Coefficient Approach under Water and Salt Stress

The accurate quantification of crop water use or evapotranspiration (ET) under water and salt stress is needed for efficient water management and precision irrigation in water scarce regions. However, few studies were examined on alfalfa water use and its components under water and salt stress. We carried out two field experiments to quantify alfalfa water use through setting up different water and salt gradients, including two irrigation levels (full and deficit irrigation) and four soil salinity levels (0, 2‰, 4‰ and 6‰ salt of mass ratio) in an arid region of Northwest China. Electrical conductivity of soil saturation extract (ECe), soil water content (SWC), leaf area index (LAI) and soil evaporation (E) were measured. The SIMDualKc model, which uses the FAO56 dual Kc approach, was calibrated and validated using measured SWC and E. Model results show a good agreement between observed and simulated SWC and E without stress. The depletion fraction for no stress (p) and the percent yield reduction per unit increase in soil salinity (b) were 0.50 and 6.0%/(dS m−1), respectively, slightly lower than those of FAO-56 (0.55 and 7.3%/(dS m−1)). The difference indicates that alfalfa has a lower capacity of water use but a greater tolerance to salt stress after soil salinity reached its sensitivity threshold in the arid region. The model performed a reduced accuracy under water and salt stress and the differences tended to increase as stress increased, which was partly attributed to constant yield response factor (Ky) under different soil water and salt stress. The key parameter Ky dynamically increased with the increased degree of stress. Compared to constant Ky, the simulations of SWC and E showed improved accuracy with dynamic Ky. These results suggested that the response and acclimation of alfalfa to stress might be incorporated into the dual Kc model through the diversity of Ky.

Application of Dual Crop Coefficient Approach for Estimation of Crop Water Requirement for Summer Sesame using SIMDualKc Model

Dual crop coefficient approach was used to estimate the crop water requirement of summer sesame in South Gujarat Agro-climatic Zone of Gujarat state. Field experiment was conducted with drip and border irrigation systems during summer season of 2018 and 2019. Basal crop coefficient and soil evaporation coefficient were separately estimated using FAO-56 method and SIMDualKc model. The SIMDualKc model, validated using observed available soil water content (ASW), performed well for both systems (R2 = 0.76-0.85, NSE= 0.75-0.94, RMSE= 0.25- 0.50). FAO-56 estimated Kc values for initial-, mid-, development- and late-stages of drip irrigated summer sesame (0.69, 0.90, 1.04, 0.65) were lower than those for border irrigated crop (0.72, 0.98, 1.05, 0.74). Under drip irrigation system, the SIMDualKc model estimated comparatively lower values of Kc only for initial and late stages of crop growth (0.39, 0.44). Crop coefficients derived using SIMDualKc model estimated lower water requirements during initial and end stage, while FAO method estimated lower water requirement during development and mid-stage. Scheduling of drip irrigation using FAO-56 and SIMDuelKc estimated crop coefficients led to average water saving of 7.6 % and 18.0 % over border system. The SIMDualKc model-based Kc values are recommended for estimating daily actual crop coefficients and crop water requirements of summer sesame crop cultivated in the South Gujarat region.

Spatial prediction of crop water requirement under evapotranspiration-based irrigation management: a case study in the tropic of cancer zone of India

Advances in information and communication technology facilitate the application of complex models for optimising agricultural water management. This study uses meteorological parameters to estimate the volume of water required to grow crops in the Bhilai region of the state of Chhattisgarh in India. Using the dual crop coefficient approach and remote sensing imagery, this study provides an easy-to-use method that can be employed to determine the water demand for crops. This research aims to estimate the ET of rice crops in the Bhilai region using the decision support software package and geographical information system techniques. Landsat8 satellite images acquired at different seasons were used to determine the normalised difference vegetation index, and ET was calculated to analyse the crop water requirements for each month during different crop seasons. Preliminary results have shown that the demand for water varies between cultivated rice fields with different soil types and land use capabilities.

Application of Dual Crop Coefficient Approach for Estimation of Crop Water Requirement for Summer Sesame using SIMDualKc Model

Dual crop coefficient approach was used to estimate the crop water requirement of summer sesame in South Gujarat Agro-climatic Zone of Gujarat state. Field experiment was conducted with drip and border irrigation systems during summer season of 2018 and 2019. Basal crop coefficient and soil evaporation coefficient were separately estimated using FAO-56 method and SIMDualKc model. The SIMDualKc model, validated using observed available soil water content (ASW), performed well for both systems (R2 = 0.76-0.85, NSE= 0.75-0.94, RMSE= 0.25- 0.50). FAO-56 estimated Kc values for initial-, mid-, development- and late-stages of drip irrigated summer sesame (0.69, 0.90, 1.04, 0.65) were lower than those for border irrigated crop (0.72, 0.98, 1.05, 0.74). Under drip irrigation system, the SIMDualKc model estimated comparatively lower values of Kc only for initial and late stages of crop growth (0.39, 0.44). Crop coefficients derived using SIMDualKc model estimated lower water requirements during initial and end stage, while FAO method estimated lower water requirement during development and mid-stage. Scheduling of drip irrigation using FAO-56 and SIMDuelKc estimated crop coefficients led to average water saving of 7.6 % and 18.0 % over border system. The SIMDualKc model-based Kc values are recommended for estimating daily actual crop coefficients and crop water requirements of summer sesame crop cultivated in the South Gujarat region.

Estimation of maize evapotraspiration under drought stress - A case study of Huaibei Plain, China.

Given the importance and complexity of crop evapotranspiration estimation under drought stress, an experiment tailored for maize under drought stress was completed using six sets of large-scale weighing lysimeters at the Xinmaqiao Comprehensive Experimental Irrigation and Drainage Station, Anhui Province, China. Our aim was to analyze maize evapotranspiration under different drought conditions. Based on estimates of maize evapotranspiration under no drought stress using the dual crop coefficient approach, we optimized and calibrated basic crop coefficients Kcbini, Kcbmid, Kcbend, and the maximum crop coefficient Kcmax using a genetic algorithm. Measurements of solar radiation at the experimental station were used to derive the empirical parameters a and b from the Angstrom formula through the genetic algorithm, and then evapotranspiration was calculated for the reference crop (ET0). We then estimated the maize evapotranspiration under drought using the dual crop coefficient approach. The results indicated that a slight water deficit during the earlier stage of vegetative growth may stimulate the maize homeostatic mechanism and increase tolerance to drought stress in later growth periods. Maize evapotranspiration significantly decreased if drought stress continued into the elongation stage, and the same degree of drought stress had a greater influence on the middle and later stages of vegetative and reproductive growth. The calibrated results for Kcbini, Kcbmid, Kcbend, and Kcmax were 0.155, 1.218, 0.420 and 1.497 respectively. We calculated the root-mean-square error (RMSE), mean absolute error (MAE), and mean relative error (MRE) of maize evapotranspiration under no drought stress over the full growing season using a dual crop coefficient approach, and the results were 1.33 mm/day, 0.99 mm/day, and 1.30%, respectively, or 18.40%, 17.50%, and 91.11% lower than results using the recommended coefficients. The RMSE, MAE, and MRE results for maize under drought stress during two full growth periods were 1.18 mm/day, 0.98 mm/day, and 13.92%, respectively. These results were higher than maize without drought stress, but better than the estimated results based on FAO-56 recommended values. Therefore, maize evapotranspiration estimation under drought stress using the dual crop coefficient approach and genetic algorithm was reasonable and reliable. This study provides a theoretical basis for developing suitable regional irrigation programs and decreasing losses due to agricultural drought.

Estimation of water requirement of Banana crop under drip irrigation with and without plastic mulch using dual crop coefficient approach

Field experiments were conducted on the lateritic sandy loam soil and sub-humid climate of Kharagpur, West Bengal, India during 2014-2018 for two consecutive crop seasons to determine the optimum water requirement of the Banana crop under drip irrigation with and without plastic mulch. Reference evapotranspiration for the Banana crop was estimated using FAO-56 Penman-Monteith approach. The dual crop coefficient approach was used to improve the estimates of the crop coefficient (Kc) values for the irrigation treatments with black plastic mulch and without mulch. Plants treated with black plastic mulch consume about 12% less water for the main crop and about 22% less water for ratoon crop compared to non-mulch plants. The effect of black plastic mulch was studied to determine the soil moisture distribution in different soil depths (0-20, 20-40, 40-60, and 60-90 cm), and also loss of water through deep drainage. Net irrigation requirement under black plastic mulch was found to be lesser than without mulch. The deep percolation was found 50.4 % more under black plastic mulch in comparison to non-mulch treatment.

Assessing the effects of plant density and plastic film mulch on maize evaporation and transpiration using dual crop coefficient approach

Plastic film mulching, in combination with high plant density, is a common practice for rain-fed maize production, especially in Northeastern China. To explore effects of plant density and plastic film mulching on the evapotranspiration of maize during its different growth periods, a two-year split-plot field experiment with non-mulching (M0) and plastic film mulching (M1) and three plant densities (60,000 (D1), 75,000 (D2), and 90,000 plants ha−1 (D3)) was conducted at a site of Shenyang located in the Northeast China in 2016 and 2017. Based on the field experimental data of spring maize, water balance equation and dual crop coefficient method were adopted to explore effects of plant density and plastic film mulch on evapotranspiration of maize at different growing stages. The results showed that compared with non-mulching treatment, the plastic film mulching increased maize transpiration by about 20.0%–32.0% and 3.5%–15.4% and reduced soil evaporation by 51.8%–63.0% and 21.5%–39.5% in 2016 and 2017, respectively. Overall, the mulching treatment significantly reduced maize water consumption by about 12.4% and 6.2% in 2016 and 2017, respectively. The mulching treatment also increased the basic maize crop coefficient by 0.03–0.07 and reduced the average evaporation coefficient by 0.14, compared with non-mulching treatment. In addition, compared with non-mulching, plastic film mulching increased ratio of transpiration by 19%–32% and 5%–12% in 2016 and 2017, respectively. For effects of plant density on maize evapotranspiration, higher plant density resulted in more evapotranspiration during the whole growth season of maize except for its initial growth stage. The average evapotranspiration of D1–D3 treatments from two growing seasons of maize were 469.2, 509.6 and 534.1 mm, respectively. For evaporation and transpiration, the maize transpiration increased with the increase of planting density, and the maize evaporation increased with the increase of planting density under plastic film mulching conditions but decreased with non-mulching treatment.

Evaluation of the Dual Crop Coefficient Approach in Estimating Evapotranspiration of Drip-Irrigated Summer Maize in Xinjiang, China

A dual crop coefficient approach was validated experimentally to estimate evapotranspiration of drip-irrigated summer maize with partial mulch and no mulch in an arid region in Aksu, Xinjiang, China, during 2016–2017. In this study, five treatments were established based on fixed or variable irrigation cycles. Summer maize transpiration and evapotranspiration were estimated by the dual crop coefficient approach. Evapotranspiration was validated, and a positive regression with those values was obtained using the water balance method, with a root mean square error (RMSE) of 10 mm. The estimated transpiration also had a positive regression with measurements obtained by the stable carbon isotope technique, with a RMSE of 20 mm. By analyzing the RMSE, regression coefficients, and concordance index, we suggest that the dual crop coefficient approach is an effective method to estimate and partition evapotranspiration. Across the entire growing season for partially mulched summer maize, the estimated crop transpiration accounted for 78.7% and 76% of the total evapotranspiration in 2016 and 2017, respectively. For non-mulched summer maize, the estimated crop transpiration accounted for 64.9% of the total evapotranspiration over the entire growing season, which implied that the soil evaporation was about 12% higher than that of the partially mulched treatments. Water consumption with partial mulching was reduced by about 10%, compared with non-mulching, which indicated that mulching improved the use of water during irrigation.