Estimation of Crop Coefficients Using Satellite Remote Sensing

Crop coefficient (Kc) based estimation of crop evapotranspiration (ETc) is one of the most commonly used methods for irrigation water management. The standardized FAO56 Penman-Monteith approach for estimating ETc from reference evapotranspiration and tabulated generalized Kc values has been widely adopted worldwide to estimate ETc. In this study, we presented a modified approach toward estimating Kc values from remotely sensed data. The surface energy balance algorithm for land model was used for estimating the spatial distribution of ETc for major agronomic crops during the 2005 growing season in southcentral Nebraska. The alfalfa-based reference evapotranspiration (ETr) was calculated using data from multiple automatic weather stations with geostatistical analysis. The Kc values were estimated based on ETc and ETr (i.e., Kc = ETc/ETr). A land use map was used for sampling and profiling the Kc values from the satellite overpass for the major crops grown in southcentral Nebraska. Finally, a regression model was developed to establish the relationship between the normalized difference vegetation index (NDVI) and the ETr-based crop coefficients (Kcr) for corn, soybeans, sorghum, and alfalfa. We found that the coefficients of variation (CV) for NDVI, as well as for Kcr of crops were lower during the midseason as compared to the early and late growing seasons. High CV values during the early growing season can be attributed to differences in planting dates between the fields, whereas high CVs during the late season can be attributed to differences in maturity dates of the crops, variety, and management practices. There was a good relationship between Kcr and NDVI for all the crops except alfalfa. Validation of the developed model for irrigated corn showed very promising results. There was a good correlation between the NDVI-estimated Kcr and the Bowen ratio energy balance system based Kcr with a R2 of 0.74 and a low root mean square difference of 0.21. This approach can be a very useful tool for a large (watershed or regional) scale estimation of evapotranspiration using the crop coefficient and reference evapotranspiration approach.     

Prediction Accuracy for Projectwide Evapotranspiration Using Crop Coefficients and Reference Evapotranspiration

The Imperial Irrigation District is a large irrigation project in the western United States having a unique hydrogeologic structure such that only small amounts of deep percolation leave the project directly as subsurface flows. This structure is conducive to relatively accurate application of a surface water balance to the district, enabling the determination of crop evapotranspiration (ETc) as a residual of inflows and outflows. The ability to calculate ETc from discharge measurements provides the opportunity to assess the accuracy and consistency of an independently applied crop coefficient—reference evapotranspiration (Kc?ET0) procedure integrated over the project. The accuracy of the annual crop evapotranspiration via water balance estimates was ±6% at the 95% confidence level. Calculations using Kc and ET0 were based on the FAO-56 dual crop coefficient approach and included separate calculation of evaporation from precipitation and irrigation events. Grass reference ET0 was computed using the CIMIS Penman equation and ETc was computed for over 30 crop types. On average, Kc-based ET computations exceeded ETc determined by water balance (referred to as ETc?WB) by 8% on an annual basis over a 7 year period. The 8% overprediction was concluded to stem primarily from use of Kc that represents potential and ideal growing conditions, whereas crops in the study area were not always in full pristine condition due to various water and agronomic stresses. A 6% reduction to calculated Kc-based ET was applied to all crops, and a further 2% reduction was applied to lower value crops to bring the project-wide ET predicted by Kc-based ET into agreement with ETc?WB. The standard error of estimate (SEE) for annual ETc for the entire project based on Kc, following the reduction adjustment, was 3.4% of total annual ETc, which is considered to be quite good. The SEE for the average monthly ETc was 15% of average monthly ETc. A sensitivity analysis of the computational procedure for Kc showed that relaxation from using the FAO-56 dual Kc method to the more simple mean (i.e., single) Kc curve and relaxation of specificity of planting and harvest dates did not substantially increase the projectwide prediction error The use of the mean Kc curves, where effects of evaporation from wet soil are included as general averages, predicted 5% lower than the dual method for monthly estimates and 8% lower on an annual basis, so that no adjustment was required to match annual ET derived from water balance. About one half of the reduction in estimates when applying the single (or mean) Kc method rather than the dual Kc method was caused by the lack of accounting for evaporation from special irrigations during the off season (i.e., in between crops).     

Reference and Crop Evapotranspiration in South Central Nebraska. II: Measurement and Estimation of Actual Evapotranspiration for Corn

In planning, designing, and managing of surface and groundwater supply, it is essential to accurately quantify actual evapotranspiration (ETc) from various vegetation surfaces within the water supply areas to allow water management agencies to manipulate the land use pattern alternatives and scenarios to achieve a desired balance between water supply and demand. However, significant differences among water regulatory agencies and water users exist in terms of methods used to quantify ETc. It is essential to know the potential differences associated with using various empirical equations in quantifying ETc as compared with the measurements of this critical variable. We quantified and analyzed the differences associated with using 15 grass (ETo) and alfalfa-reference (ETr) combination, temperature and radiation-based reference ET (ETref) equations in quantifying grass-reference actual ET (ETco) and alfalfa-reference actual ET (ETcr) as compared with the Bowen ratio energy balance system (BREBS)-measured ETc (ETc-BREBS) for field corn (Zea mays L.). We analyzed the performance of the equations for their full season, irrigation season, peak ET month, and seasonal cumulative ETc estimates on a daily time step for 2005 and 2006. The step-wise Kc values instead of smoothed curves were used in the ETc calculations. The seasonal ETc-BREBS was measured as 572 and 561?mm in 2005 and 2006, respectively. The root-means-quare difference (RMSD) was higher for the full season than the irrigation season and peak ET month estimates for all equations. The standardized ASCE Penman-Monteith (PM) ETco had a RMSD of 1.37?mm?d?1 for the full growing season, 1.05?mm?d?1 for the irrigation season, and 0.76?mm?d?1 for the peak month ET. The ASCE-PM, 1963 and 1948 Penman ETc estimates were closest to the ETc-BREBS. The FAO-24 radiation and the HPRCC Penman ETc estimates also agreed well with the ETc-BREBS. Most combination equations performed best during the peak ET month except the temperature and radiation-based equations. There was an excellent correlation between the ASCE-PM ETco and ETcr with a high r2 of 0.99 and a low RMSD of 0.34?mm?d?1. The difference between the ETcr and ETco was found to be larger at the high ETc range (i.e., >8?mm), but overall, the ETcr and ETco values were within 3%. Significant differences were found between the cumulative ETco-METHOD and ETcr-METHOD versus ETc-BREBS. Most combination equations, including the standardized ASCE-PM ETco and ETcr underestimated ETc-BREBS during the early periods of the growing season where the soil evaporation was the dominant energy flux of the energy balance and in the late season near and after physiological maturity when the transpiration rates were less than the midseason. The underestimations early in the season can be attributed to the lack of ability of the physical structure of the ETref×crop coefficient approach to “fully” account for the soil surface conditions when complete canopy cover is not present. The results of this study can be used as a reference tool by the water resources regulatory agencies and water users and can provide practical information on which method to select based on the data availability for reliable estimates of daily ETc for corn.     

Modeling Reservoir Irrigation in Uncertain Hydrologic Environment

In a detailed model for reservoir irrigation taking into account the soil moisture dynamics in the root zone of the crops, the data set for reservoir inflow and rainfall in the command will usually be of sufficient length to enable their variations to be described by probability distributions. However, the potential evapotranspiration of the crop itself depends on the characteristics of the crop and the reference evaporation, the quantification of both being associated with a high degree of uncertainty. The main purpose of this paper is to propose a mathematical programming model to determine the annual relative yield of crops and to determine its reliability, for a single reservoir meant for irrigation of multiple crops, incorporating variations in inflow, rainfall in the command area, and crop consumptive use. The inflow to the reservoir and rainfall in the reservoir command area are treated as random variables, whereas potential evapotranspiration is modeled as a fuzzy set. The model’s application is illustrated with reference to an existing single-reservoir system in Southern India.     

FAO-56 Dual Crop Coefficient Method for Estimating Evaporation from Soil and Application Extensions

Crop coefficient curves provide simple, reproducible means to estimate crop evapotranspiration (ET) from weather-based reference ET values. The dual crop coefficient (Kc) method of the Food and Agricultural Organization of the United States (FAO) Irrigation and Drainage Paper No. 56 (FAO-56) is intended to improve daily simulation of crop ET by considering separately the contribution of evaporation from soil. The dual method utilizes “basal” crop coefficients representing ET from crops having a dry soil surface and separately predicts evaporation from bare soil based on a water balance of the soil surface layer. Three extensions to the evaporation calculation procedure are described here that are intended to improve accuracy when applications warrant the extra complexity. The first extension uses parallel water balances representing the portion of the soil surface wetted by irrigation and precipitation together and the portion wetted by precipitation alone. The second extension uses three “stages” for surface drying and provides for application to deep cracking soils. The third extension predicts the extraction of the transpiration component from the soil surface layer. Sensitivity and analyses and illustrations indicate moderate sensitivity of daily calculated ET to application of the extensions. The dual Kc procedure, although relatively simple computationally and structurally, estimates daily ET as measured by lysimeter relatively well for periods of bare soil and partial and full vegetation cover.     

Performance Evaluation of ANN and ANFIS Models for Estimating Garlic Crop Evapotranspiration

Estimation of evapotranspiration (ET) is necessary in water resources management, farm irrigation scheduling, and environmental assessment. Hence, in practical hydrology, it is often necessary to reliably and consistently estimate evapotranspiration. In this study, two artificial intelligence (AI) techniques, including artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS), were used to compute garlic crop water requirements. Various architectures and input combinations of the models were compared for modeling garlic crop evapotranspiration. A case study in a semiarid region located in Hamedan Province in Iran was conducted with lysimeter measurements and weather daily data, including maximum temperature, minimum temperature, maximum relative humidity, minimum relative humidity, wind speed, and solar radiation during 2008–2009. Both ANN and ANFIS models produced reasonable results. The ANN, with 6-6-1 architecture, presented a superior ability to estimate garlic crop evapotranspiration. The estimates of the ANN and ANFIS models were compared with the garlic crop evapotranspiration (ETc) values measured by lysimeter and those of the crop coefficient approach. Based on these comparisons, it can be concluded that the ANN and ANFIS techniques are suitable for simulation of ETc.     

Application of SEBAL Model for Mapping Evapotranspiration and Estimating Surface Energy Fluxes in South-Central Nebraska

Knowledge of spatiotemporal distribution of evapotranspiration (ET) on large scales, as quantified by satellite remote sensing techniques, can provide important information on a variety of water resources issues such as evaluating water distributions, water use by different land surfaces, water allocations, water rights, consumptive water use and planning, and better management of ground and surface water resources. The objective of this study was to assess the operational characteristics and performance of the surface energy balance algorithm for land (SEBAL) model for estimating crop ET (ETc) and other energy balance components, and mapping spatial distribution and seasonal variation of ETc on a large scale in south-central Nebraska climatic conditions. A total of seven cloud free Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper (ETM) satellite images (May 19, June 20, July 22, August 7, September 8, September 16, and October 18, 2005) were processed to generate ETc maps and estimate surface energy fluxes. Predictions from the SEBAL model were compared with the Bowen ratio energy balance system (BREBS)-measured fluxes on an instantaneous and daily basis. The ETc maps generated by the model for seven Landsat overpass days showed a very good progression of ETc with time during the growing season in 2005 as the surface conditions continuously changed. The predictions for some surface energy fluxes were very good. Overall, a very good correlation was found between the BREBS-measured and SEBAL-estimated ETc with a good r2 of 0.73 and a root-mean-square difference (RMSD) of 1.04?mm?day?1. The estimated ETc was within 5% of the measured ETc. The model was able to predict growing season (from emergence to physiological maturity) cumulative daily corn ET reasonable well within 5% of the BREBS-measured values. The model overestimated the surface albedo by about 26% with a RMSD of 0.05. The difference between the measured and predicted albedo was the greatest on May 19, early in the growing season before the full canopy cover. The second largest difference between the two albedo values was on October 18, a day after harvest. The model significantly under predicted soil heat flux with a large RMSD of 80?W?m?2 and most of the underestimation occurred in the late growing season. Local calibration of soil heat flux significantly improved the agreement between the measured and predicted values. Furthermore, the sensible heat flux was underestimated between September 20 (after physiological maturity) and October 18 (a day after harvest). While our results showed that SEBAL can be a viable tool for generating ETc maps to assess and quantify spatiotemporal distribution of ET on large scales as well as estimating surface energy fluxes, its operational assessment for estimating sensible heat flux and ETc, especially during the drier periods for different surfaces, needs further development.     

Estimation of Evapotranspiration of Different-Sized Navel-Orange Tree Orchards Using Energy Balance

Crop evapotranspiration (ETc) and crop coefficient (Kco) values of four clean-cultivated navel-orange orchards that were irrigated with microsprinklers, having different canopy features (e.g., age, height, and canopy cover) were evaluated. Half-hourly values of latent heat flux density were estimated as the residual of the energy balance equation using measured net radiation (Rn), soil heat flux density (G), and sensible heat flux density (H) estimated using the surface renewal method. Hourly means of latent heat flux density (LE) were calculated and were divided by the latent heat of vaporization (L) to obtain ETc. Crop coefficients were determined by calculating the ratio Kco = ETc/ETo, with reference evapotranspiration (ETo) determined using the hourly Penman–Monteith equation for short canopies. The estimated Kco values ranged from 0.45 to 0.93 for canopy covers having between 3.5 and 70% ground shading. The Kco values were compared with Kc values from FAO 24 (reported by Doorenbos and Pruitt in 1975) and FAO 56 (reported by Allen et al. in 1998) and with Kc values from research papers that estimated reference ET from pan evaporation data using the FAO 24 method. The observed Kco values were slightly higher than Kc values for clean-cultivated orchards with high-frequency drip irrigation in Arizona and were slightly lower than for nontilled orchards in Florida. The Kco values were considerably higher than Kc values from FAO 24 and FAO 56 and were higher than Kc values from border-irrigated orchards near Valencia, Spain.     

Optimal Irrigation Allocation: A Multilevel Approach

Optimal resources allocation strategies for a canal command in the semiarid region of Indian Punjab are developed in a stochastic regime, considering the competition of the crops in a season, both for irrigation water and area of cultivation. The proposed strategies are divided into two modules using a multilevel approach. The first module determines the optimal seasonal allocation of water as well as optimal cropping pattern. This module is subdivided into two stages. The first stage is a single crop intraseasonal model that employs a stochastic dynamic programming algorithm. The stochastic variables are weekly canal releases and evapotranspiration of the crop that are fitted to different probability distribution functions to determine the expected values at various risk levels. The second stage is a deterministic dynamic programming model that takes into account the multicrop situation. An exponential seasonal crop-water production function is used in this stage. The second module is a single crop stochastic dynamic programming intraseasonal model that takes the output of the first module and gives the optimal weekly irrigation allocations for each crop by considering the stress sensitivity factors of crops.     

Actual and Reference Evaporative Losses and Surface Coefficients of a Maize Field during Nongrowing (Dormant) Periods

Effective water resources planning, allocation, management, and use in agroecosystems require accurate quantification of actual evapotranspiration (ETc) during growing and nongrowing (dormant) periods. Prediction of ETc for a variety of vegetation surfaces during the growing season has been researched extensively, but relatively little information exists on evaporative losses during nongrowing periods for different surfaces. The objectives of this research were to evaluate ETc in relation to available energy, precipitation, and grass and alfalfa-reference ET (ETo and ETr) for a maize (Zea mays. L) field and to analyze the dynamics of surface coefficients (Kc) during the nongrowing period (October 15–April 30). The evaporative losses were measured using a Bowen ratio energy balance system (BREBS) on an hourly basis and averaged over 24?h for three consecutive nongrowing periods: 2004–2005 (Season I), 2005–2006 (Season II), and 2006–2007 (Season III). BREBS-measured ETc was approximately 50% of available energy (Rn?G; Rn is net radiation and G is soil heat flux density) during normal and wet seasons (Seasons I and III) and 41% of available energy during a dry season (Season II). Cumulative ETc ranged from 133?mm in Season II to 167?mm in Season III and exceeded precipitation by 21% during the dry season. The ratio of ETc to precipitation was 0.85 in Season I, 1.21 in Season II, and 0.41 in Season III. ETc was approximately 50% of ETo and 36% of ETr in both Seasons I and III, whereas in Season II, ETc was 32% of ETo and 23% of ETr. Overall, measured ETc during the dormant season was generally most strongly correlated with radiation terms, particularly Rn, albedo, incoming shortwave radiation, and outgoing longwave radiation. Average surface coefficients over the three seasons were 0.44 and 0.33 for grass and alfalfa-reference surfaces, respectively. Using geometric mean Kc values to calculate ETc using a KcETref approach over the entire nongrowing season yielded adequate predictions with overall root mean square deviations of 0.64 and 0.67?mm?day?1 for ETo and ETr, respectively. Estimates of ETc using a dual crop coefficient approach were good on a seasonal basis, but performed less well on a daily basis. Regression equations that were developed (accounting for serial autocorrelation in the ETc and ETref time series) yielded good estimates of ETc. Considering nongrowing period evaporative losses in water budget calculations would enable water regulatory agencies to better account for water use in hydrologic balance calculations over the entire year rather than only for the growing season and to better assess the progression and availability of water resources for the next growing season.     

Regional Alfalfa Yield, ETc, and Water Value in Western States

Alfalfa hay yield, yield-consumptive use ratio (Y∕ETc), and hay price across a range of rainfall and evapotranspiration conditions of the western states is evaluated to determine alfalfa hay water value or benefit. Included is a determination of long-term mean values and variability of yield, Y∕ETc ratios, and associated irrigation water values. These are compared with published hay water-use efficiencies, production, and water costs. Available rainfall, reference evapotranspiration ET0, hay yields, and prices for counties in Arizona (1987–1999), California (1998–1999), and Idaho (1993–1999) were used. Alfalfa hay Y∕ETc ratios decrease with increasing ETc, although their variability increases with increasing ETc. The greatest Y∕ETc ratios (16–17 kg∕ha-mm) and irrigation water values IW$ (IW$ = $2,800–$3,000∕ha-m), with relatively moderate variability, are associated with an irrigation water IW requirement of ～800 mm, reflecting a combination of relatively high hay values, ETc, and beneficial rain. Although this IW$ is twice that of water delivery prices below the California delta and is comparable with average municipal water costs of $4,000∕ha-m for large western cities, the average is nearly 1∕3.     

Estimating Evaporation from Bare or Nearly Bare Soil

A model is presented that uses a daily mean evapotranspiration ETo rate to estimate energy-limited (potential or Stage 1) soil evaporation, and it also uses daily mean ETo and a soil hydraulic β factor to estimate soil hydraulic property-limited (Stage 2) evaporation. The model provides good estimates of cumulative soil evaporation on both hourly and daily bases when compared to observed soil evaporation in three field trials. Crop coefficient Kc values from cumulative hourly and cumulative daily soil evaporation estimates and ETo data were comparable. Using a soil hydraulic factor (β = 2.6) in the model gave a fair approximation for the widely used Kc curves for initial growth of crops presented in the United Nations Food and Agricultural Organization's Irrigation and Drainage Paper 24. However, using a site-specific β factor should improve soil evaporation and Kc estimates for site-specific applications.     

Performance Evaluation and Uncertainty Measurement in Irrigation Scheduling Soil Water-Balance Approach

The present work aims at approaching the study of the performance and uncertainty associated with an irrigation scheduling method based on a soil-water balance. On a daily time step, a water-balance-based irrigation scheduling model has been developed. A Monte Carlo simulation of the irrigation scheduling model is developed using a series of actual daily weather data of evapotranspiration and precipitation and bootstrapping stochastic technique to resampling them. Performance evaluation measurements and their uncertainty are studied by means of several parameters: reliability, resiliency, vulnerability, total irrigation water allocation, total water loosed by deep percolation, and actual evapotranspiration/potential evapotranspiration rate along the growing season. The behaviors of 12 different types of soils (between coarse-textured soils and fine-textured soils) are compared using pedotransfer functions. Total available water (TAW) is the most important hydraulic property of the soil as far as irrigation scheduling performance is concerned. The statistical relationship between evaluation performance measures and TAW has been calculated. Soils with high values of TAW perform better. Rooting depth (Zr) and fraction of TAW that can be depleted from the root zone before moisture stress (p) are two variables that directly affect the TAW. It has been studied how evaluation performance measurements change when Zr and p change too. High values of Zr and p perform better too.     

Evapotranspiration: Concepts and Future Trends

Past research on evapotranspiration has provided sound theoretical knowledge and practical applications that have been validated through field measurements. Many different approaches have been used; however, when primary concepts and standard definitions are accepted, it is possible to find reasonable agreement among methods. This paper reviews such approaches, from Penman to Penman-Monteith. The standard concepts of potential evaporation (EP) and equilibrium evaporation (Ee), and the introduction of the climatic resistance (re), provide a better understanding of the role of the climate together with surface and aerodynamic resistances (rs and ra). Therefore, the concept of reference evapotranspiration (ETo), particularly the new one adopted by the Food and Agricultural Organization of the United Nations, can be better understood, as well as its limitations. Crop evapotranspiration (ETc) is related to both ETo and Ee. Crop coefficients (Kc) can be shown to have two components, αo and αc, with Kc = αoαc. The αo is a function of the climatic resistance and of the aerodynamic resistances of the crop and of the reference crop. The αc is a function of both surface and aerodynamic resistances of the crop and of the reference crop. From this analysis some ideas on future developments result that are directed toward providing compatibility between the one- and two-step calculation of ETc.     

Regional Salinity Modeling for Conjunctive Water Use Planning in Kheri Command

A one-dimensional water and solute transport UNSATCHEM model is calibrated and validated with a saline water use experiment for wheat and cotton crops. The model is further employed for regional scale salinity modeling with distributed data on soil, irrigation water supply, and its quality from six representative locations from the Kheri command of the Bhakra irrigation system. The wheat–cotton crop rotation, the main rotation in the command, is considered during long-term simulations. The CROPWAT model is used to determine the evapotranspiration requirements of different wheat and cotton crops, while soil water retention parameters are estimated by the RETC model. Atmospheric water and solute boundary conditions are assumed at the top boundary, while free drainage is considered for the lower boundary, as the watertable in the command is sufficiently deep. Simulated salinity and yield values are compared with observed values for regional validation of the model. Critical areas in the command are identified using regional scale modeling results, and applying irrigation water availability and root zone salinity criteria. Guidelines for sustainable conjunctive water use planning are for the Kheri command to get optimum agricultural production despite the use of saline water for irrigation under prevailing scenarios of water availability and its quality.     

Crop Coefficients for Microsprinkler-Irrigated, Clean-Cultivated, Mature Citrus in an Arid Climate

Crop evapotranspiration (ETc) was measured over a clean-cultivated, mature navel orange orchard with microsprinkler irrigation located near Lindsay, California. Hourly mean latent heat flux density was determined as the residual of the energy balance equation with measured net radiation, soil heat flux density and sensible heat flux density estimated using the surface renewal method. The ETc was compared with ETo calculated using hourly weather data and the ASCE-EWRI Penman-Monteith equation. Following pruning and topping of the trees in the spring of 2001, the Kco values slowly increased as the canopy developed in the following season. An average Kco = 0.82 was observed. In the following year, the mean summertime value increased to about Kco = 0.95, and in 2003 and 2004, the summertime value averaged near Kco = 1.00, which is somewhat higher than observed for drip irrigated trees in southwestern Arizona and considerably higher than reported in the widely used Food and Agricultural Organization of the United Nations publications that were based on infrequent surface irrigation.     

Estimating Evaporation from Bare Soil Using Soil Moisture Data

A method is presented that uses continuous soil moisture measurements and hourly reference evapotranspiration data to estimate a soil hydraulic factor (β) for modeling soil evaporation. The β factor is used to assess the end of the energy limited soil evaporation phase (Stage 1) and the evaporation rate during the soil hydraulic limited phase (Stage 2) of a two-stage soil evaporation model. A previously developed and tested method to determine β uses an energy balance approach with sensible heat flux density estimated using the surface renewal method to obtain the continuous soil evaporation. A new method is presented, which uses a hydroprobe soil moisture measuring device to estimate the continuous soil evaporation. The estimation of evaporation with soil moisture sensors was simpler and less expensive when compared to the energy balance technique. The methods, evaluated in two field experiments, showed good agreement with evaporation data. Using the evaporation model and β derived from either method provided a good estimate of measured soil evaporation. Modeled daily soil evaporation, using either energy balance or soil measurements to obtain β, gave a root-mean-square error of 0.6 mm?day?1 when compared with soil evaporation measured using the energy balance method. When daily soil evaporation from soil moisture measurements was compared with soil evaporation estimated from energy balance measurements, the root-mean-square error was 1.3 mm?day?1. Direct soil monitoring method had bigger error, but the method is less costly.     

Physically Based Coupled Model for Simulating 1D Surface–2D Subsurface Flow and Plant Water Uptake in Irrigation Furrows. I: Model Development

Physically based modeling of the interacting water flow during a furrow irrigation season can contribute to both a sustainable irrigation management and an improvement of the furrow irrigation efficiency. This paper presents a process based seasonal furrow irrigation model which describes the interacting one-dimensional surface–two-dimensional subsurface flow and crop growth during a whole growing period. The irrigation advance model presented in a previous study is extended to all hydraulic phases of an irrigation event. It is based on an analytical solution of the zero-inertia surface flow equations and is iteratively coupled with the two-dimensional subsurface flow model HYDRUS-2. A conceptual crop growth model calculates daily evaporation, transpiration and leaf area index. The crop model and HYDRUS-2 are coupled via its common boundaries, namely (1) by the flux across the soil-atmosphere interface; and (2) by the flux from the root zone, which is associated with the plant water uptake. We assume the water stress is the only environmental factor reducing crop development and hence final crop yield. The model performance is evaluated with field experimental data in the companion paper, Part II: Model Test and Evaluation (W?hling and Mailhol 2007).     

Estimating Soil Moisture Under Low Frequency Surface Irrigation Using Crop Water Stress Index

The present study investigated the relationship between the crop water stress index (CWSI) and soil moisture for surface irrigated cotton (Gossypium hirsutum, Delta Pine 90b) at Maricopa, Arizona during the 1998 season. The CWSI was linked to soil moisture through the water stress coefficient Ks that accounts for reduced crop evapotranspiration when there is a shortage of soil water. A stress recovery coefficient Krec was introduced to account for reduced crop evapotranspiration as the crop recovered from water stress after irrigation events. A soil water stress index (SWSI) was derived in terms of Ks and Krec. The SWSI compared reasonably well to the CWSI, but atmospheric stability correction for the CWSI did not improve comparisons. When the CWSI was substituted into the SWSI formulation, it gave good prediction of soil moisture depletion (fDEP; when to irrigate) and depth of root zone depletion (Dr; how much to irrigate). Disagreement was greatest for fDEP<0.6 because cotton is less sensitive to water stress in this range.     

Surface Renewal Estimation of Pasture Evapotranspiration

Experiments to measure the evapotranspiration of an improved, irrigated pasture were conducted at the University of California, Davis, CA field station and over a commercial irrigated pasture on Twitchell Island in the Sacramento-San Joaquin River Delta using the surface renewal (SR) method. In Davis, the SR method was used to determine well-watered crop evapotranspiration (ETc) over short grass, and the results were compared with the ASCE-EWRI standardized reference evapotranspiration (ET0) for a short canopy to establish that a crop coefficient Kc = 1.00 is appropriate for estimating well-watered pasture ETc. In the Twitchell Island study, surface renewal was used to determine the actual evapotranspiration (ETa) from a commercial pasture. A stress coefficient of Ks = ETa/ET0 ≈ 0.90 was observed during the high ET period (ET0>7?mm?day?1) from about mid-June through mid-July for the Twitchell Island pasture. Otherwise, the pasture was mainly unstressed, so the Ks = 1.0. Thus, assuming no future changes in irrigation management, using ET0 from Twitchell Island, a Kc = 1.00, and Ks = 1.00 will provide good estimates of ETa during low to moderate ET periods and Ks ≈ 0.90 should be used when ET0>7.0?mm?day?1. In general, a thermocouple for SR measurements costs about $100, whereas the price for a sonic anemometer varies between $3,000 and $20,000, so the SR method provides a low-cost method to measure ETa.