Wheat basal crop coefficients determined by normalized difference vegetation index

Crop coefficient methodologies are widely used to estimate actual crop evapotranspiration (ET_c) for determining irrigation scheduling. Generalized crop coefficient curves presented in the literature are limited to providing estimates of ET_c for “optimum” crop condition within a field, which often need to be modified for local conditions and cultural practices, as well as adjusted for the variations from normal crop and weather conditions that might occur during a given growing season. Consequently, the uncertainties associated with generalized crop coefficients can result in ET_c estimates that are significantly different from actual ET_c, which could ultimately contribute to poor irrigation water management. Some important crop properties such as percent cover and leaf area index have been modeled with various vegetation indices (VIs), providing a means to quantify real-time crop variations from remotely-sensed VI observations. Limited research has also shown that VIs can be used to estimate the basal crop coefficient (K _cb) for several crops, including corn and cotton. The objective of this research was to develop a model for estimating K _cb values from observations of the normalized difference vegetation index (NDVI) for spring wheat. The K _cb data were derived from back-calculations of the FAO-56 dual crop coefficient procedures using field data obtained during two wheat experiments conducted during 1993–1994 and 1995–1996 in Maricopa, Arizona. The performance of the K _cb model for estimating ET_c was evaluated using data from a third wheat experiment in 1996–1997, also in Maricopa, Arizona. The K _cb was modeled as a function of a normalized quantity for NDVI, using a third-order polynomial regression relationship (r ²=0.90, n=232). The estimated seasonal ET_c for the 1996–1997 season agreed to within −33 mm (−5%) to 18 mm (3%) of measured ET_c. However, the mean absolute percent difference between the estimated and measured daily ET_c varied from 9% to 10%, which was similar to the 10% variation for K _cb that was unexplained by NDVI. The preliminary evaluation suggests that remotely-sensed NDVI observations could provide real-time K _cb estimates for determining the actual wheat ET_c during the growing season.     

Combining FAO-56 model and ground-based remote sensing to estimate water consumptions of wheat crops in a semi-arid region

This study was performed to test three methods based on the FAO-56 “dual” crop coefficient approach to estimate actual evapotranspiration (AET) for winter wheat under different irrigation treatments in the semi-arid region of Tensift Al Haouz, Marrakech (center of Morocco). The three methods differ in the calculation of the basal crop coefficient (K_cb) and the fraction of soil surface covered by vegetation (f_c). The first approach strictly follows the FAO-56 procedure, with K_cb given in the FAO-56 tables and f_c calculated from K_cb (No-Calibration method). The second method uses local K_cb and f_c values estimated from field measurements (Local-Calibration method) and the last approach uses a remotely-sensed vegetation index to estimate K_cb and f_c (NDVI-Calibration method). The analysis was performed on three fields using actual (AET) measured by Eddy Correlation systems. It was shown that the Local-Calibration approach gave best results. Accurate estimates of K_cb and f_c were necessary for FAO-56 “dual” crop coefficient application. The locally derived K_cb for winter wheat taken at initial, mid-season, and maturity crop growth were 0.15, 0.90 and 0.23, respectively. The K_cb value at the mid-season stage was found to be considerably less than that suggested by the FAO-56.     

The dual crop coefficient approach to estimate and partitioning evapotranspiration of the winter wheat–summer maize crop sequence in North China Plain

An accurate estimation of crop evapotranspiration (ET _c) is very useful for appropriate water management; hence, an accurate and user-friendly model is needed to support related irrigation decisions. In this view, a study was developed aimed at estimating the ET _c of winter wheat–summer maize crop sequence in the North China through eddy covariance measurements, to calibrate and validate the SIMDualKc model, to estimate the basal crop coefficients (K _cb) for both crops and to partition ET _c into soil evaporation and crop transpiration. Two years of field experimentation of that crop sequence were used to calibrate and validate the SIMDualKc model and to derive K _cb using eddy covariance measurements. Various indicators have shown the goodness of fit of the model, with estimated values very close to the observed ones and estimate errors close to 0.5 mm d^?1. The initial, mid-season and end basal crop coefficients for wheat were 0.25, 1.15 and 0.30, respectively, and those for maize were 0.15, 1.15 and 0.45, thus close to those proposed in FAO56 guidelines. The soil evaporation represented near 80 % of ET _c for the initial stages of winter wheat and summer maize and decreased to only 5–6 % during the mid-season period. Evaporation during the full crop season averaged 28 % for winter wheat and 40 % for summer maize. The importance of wetting frequency and crop ground coverage in controlling soil evaporation was evidenced.     

Consumptive water use and crop coefficients of irrigated sunflower

In semi-arid environments, the use of irrigation is necessary for sunflower production to reach its maximum potential. The aim of this study was to quantify the consumptive water use and crop coefficients of irrigated sunflower (Helianthus annuus L.) without soil water limitations during two growing seasons. The experimental work was conducted in the lysimeter facilities located in Albacete (Central Spain). A weighing lysimeter with an overall resolution of 250 g was used to measure the daily sunflower evapotranspiration throughout the growing season under sprinkler irrigation. The lysimeter container was 2.3 m × 2.7 m × 1.7 m deep, with an approximate total weight of 14.5 Mg. Daily ET _c values were calculated as the difference between lysimeter mass losses and lysimeter mass gains divided by the lysimeter area. In the lysimeter, sprinkler irrigation was applied to replace cumulative ET _c, thus maintaining non-limiting soil water conditions. Seasonal lysimeter ET _c was 619 mm in 2009 and 576 mm in 2011. The higher ET _c value in 2009 was due to earlier planting and a longer growing season with the maximum cover coinciding with the maximum ET _o period. For the two study years, maximum average K _c values reached values of approximately 1.10 and 1.20, respectively, during mid-season stage and coincided with maximum ground cover values of 75 and 88 %, respectively. The dual crop coefficient approach was used to separate crop transpiration (K _cb) from soil evaporation (K _e). As the crop canopy expanded, K _cb values increased while the K _e values decreased. The seasonal evaporation component was estimated to be about 25 % of ET _c. Linear relationships were found between the lysimeter K _cb and the canopy ground cover (f _c) for the each season, and a single relationship that related K _cb to growing degree-days was established allowing extrapolation of our results to other environments.     

Estimating crop coefficients from fraction of ground cover and height

The FAO-56 procedure for estimating the crop coefficient K _c as a function of fraction of ground cover and crop height has been formalized in this study using a density coefficient K _d. The density coefficient is multiplied by a basal K _c representing full cover conditions, K _{cb full}, to produce a basal crop coefficient that represents actual conditions of ET and vegetation coverage when the soil surface is dry. K _{cb full} is estimated primarily as a function of crop height. K _{cb full} can be adjusted for tree crops by multiplying by a reduction factor (F _r) estimated using a mean leaf stomatal resistance term. The estimate for basal crop coefficient, K _cb, is further modified for tree crops if some type of ground-cover exists understory or between trees. The single (mean) crop coefficient is similarly estimated and is adjusted using a K _soil coefficient that represents background evaporation from wet soil. The K _c estimation procedure was applied to the development periods for seven vegetable crops grown in California. The average root mean square error between estimated and measured K _c was 0.13. The K _c estimation procedure was also used to estimate K _c during midseason periods of horticultural crops (trees and vines) reported in the literature. Values for mean leaf stomatal resistance and the F _r reduction factor were derived that explain the literature K _c values and that provide a consistent means to estimate K _c over a broad range of fraction of ground cover.     

A consolidated evaluation of the FAO-56 dual crop coefficient approach using the lysimeter data in the North China Plain

The main purpose of this paper was to evaluate whether or not the dual crop coefficient (DCC) method proposed in FAO-56 was suitable for calculating the actual daily evapotranspiration of the main crops (winter wheat and summer maize) in the North China Plain (NCP). The results were evaluated with the data measured by the large-scale weighing lysimeter at the Yucheng Comprehensive Experimental Station (YCES) of the Chinese Academy of Sciences (CAS) from 1998 to 2005 using the Nash-Sutcliffe efficiency (NSE), the root mean square error (RMSE) and the root mean square error to observations’ standard deviation ratio (RSR). The evaluation results showed that the DCC method performed effective in simulating the quantity of seasonal evapotranspiration for winter wheat but was inaccurate in calculating the peak values. The RMSE value of the winter wheat during the total growing season was less than 0.9 mm/d, the NSE and RSR values during the total growing stage were “Very Good”, but the results for summer maize were “Unsatisfactory”. The recommended basal crop coefficient values K_cbtab during the initial, mid-season and end stages for winter wheat and summer maize were modified and the variation scope of basal crop coefficient K_cb was analyzed. The K_c (compositive crop coefficient, K_c = ET_c/ET₀, ET_c here is the observed values by lysimeter, ET₀ is the reference evapotranspiration) values were estimated using observed weighing lysimeter data during the corresponding stages for winter wheat and summer maize were 0.80, 1.15, 1.25, 0.95; 0.90, 0.95, 1.25, 1.00, respectively. These can be a reference for irrigation planning.     

Water requirements of olive orchards–II: determination of crop coefficients for irrigation scheduling

Intensification of olive cultivation by shifting a tree crop that was traditionally rain fed to irrigated conditions, calls for improved knowledge of tree water requirements as an input for precise irrigation scheduling. Because olive is an evergreen tree crop grown in areas of substantial rainfall, the estimation of crop evapotranspiration (ET) of orchards that vary widely in canopy cover, should be preferably partitioned into its evaporation and transpiration components. A simple, functional method to estimate olive ET using crop coefficients (K _c=ET/ET₀) based on a minimum of parameters is preferred for practical purposes. We developed functional relationships for calculating the crop coefficient, K _c, for a given month of the year in any type of olive orchard, and thus its water requirements once the reference ET (ET₀) is known. The method calculates the monthly K _c as the sum of four components: tree transpiration (K _p), direct evaporation of the water intercepted by the canopy (K _pd), evaporation from the soil (K _s1) and evaporation from the areas wetted by the emitters (K _s2). The expression used to calculate K _p requires knowledge of tree density and canopy volume. Other parameters needed for the calculation of the K _c’s include the ET₀, the fraction of the soil surface wetted by the emitters and irrigation interval. The functional equations for K _p, K _pd, K _s1 and K _s2 were fitted to mean monthly values obtained by averaging 20-year outputs of the daily time step model of Testi et al. (this issue), that was used to simulate 124 different orchard scenarios.     

Evapotranspiration and crop coefficients of irrigated biomass sorghum for energy production

New cultivars of sorghum for biomass energy production are currently available. This crop has a positive energy balance being irrigation water the largest energy consumer during the growing cycle. Thence, it is important to know the biomass sorghum water requirements, in order to minimize irrigation losses, thus saving water and energy. The objective of this study was to quantify the water use and crop coefficients of irrigated biomass sorghum without soil water limitations during two growing seasons. A weighing lysimeter located in Albacete (Central Spain) was used to measure the daily biomass sorghum evapotranspiration (ET_c) throughout the growing season under sprinkler irrigation. Seasonal lysimeter ET_c was 721 mm in 2007 and 691 mm in 2010. The 4 % higher ET_c value in 2007 was due to an 8 % higher evaporative demand in that year. Maximum average K _c values of 1.17 in 2007 and 1.21 in 2010 were reached during the mid-season stage. The average K _c values for the 2 years of study were K _c-ini: 0.64 and K _c-mid: 1.19. The seasonal evaporation component was estimated to be about 18 % of ET_c. The average basal K _c (K _cb) values for the two study years were K _cb-ini: 0.11 and K _cb-mid: 1.17. The good linear relationship found between K _cb values and the fraction of ground cover (f _c) and the excellent agreement found between Normalized Difference Vegetation Index and different biophysical parameters, such as K _cb and f _c, will allow monitoring and estimating the spatially distributed water requirements of biomass sorghum at field and regional scales.     

Monitoring wheat phenology and irrigation in Central Morocco: On the use of relationships between evapotranspiration,crops coefficients,leaf area index and remotely-sensed vegetation indices

The monitoring of crop production and irrigation at a regional scale can be based on the use of ecosystem process models and remote sensing data. The former simulate the time courses of the main biophysical variables which affect crop photosynthesis and water consumption at a fine time step (hourly or daily); the latter allows to provide the spatial distribution of these variables over a region of interest at a time span from 10 days to a month. In this context, this study investigates the feasibility of using the normalised difference vegetation index (NDVI) derived from remote sensing data to provide indirect estimates of: (1) the leaf area index (LAI), which is a key-variable of many crop process models; and (2) crop coefficients, which represent the ratio of actual (AET) to reference (ET₀) evapotranspiration.A first analysis is performed based on a dataset collected at field in an irrigated area of the Haouz plain (region of Marrakesh, Central Morocco) during the 2002–2003 agricultural season. The seasonal courses of NDVI, LAI, AET and ET₀ have been compared, then crop coefficients have been calculated using a method that allows roughly to separate soil evaporation from plant transpiration. This allows to compute the crop basal coefficient (K_cb) restricted to the plant transpiration process. Finally, three relationships have been established. The relationships between LAI and NDVI as well as between LAI and K_cb were found both exponential, with associated errors of 30% and 15%, respectively. Because the NDVI saturates at high LAI values (>4), the use of remotely-sensed data results in poor accuracy of LAI estimates for well-developed canopies. However, this inaccuracy was not found critical for transpiration estimates since AET appears limited to ET₀ for well-developed canopies. As a consequence, the relationship between NDVI and K_cb was found linear and of good accuracy (15%).Based on these relationships, maps of LAI and transpiration requirements have been derived from two Landsat7-ETM+ images acquired at the beginning and the middle of the agricultural season. These maps show the space and time variability in crop development and water requirements over a 3 km × 3 km irrigated area that surrounds the fields of study. They may give an indication on how the water should be distributed over the area of interest in order to improve the efficiency of irrigation. The availability, in the near future, of Earth Observation Systems designed to provide both high spatial resolution (10 m) and frequent revisit (day) would make it feasible to set up such approaches for the operational monitoring of crop phenology and irrigation at a regional scale.     

Effects of tree size on water use of peach (Prunus persica L. Batsch)

A short-term experiment was conducted to determine the effects of reducing tree size on peach tree water use (TWU). Tree size was progressively reduced by de-branching an individual isolated tree over a 15-day period. TWU was measured at 15-min intervals using heat pulse sap flow sensors located at eight positions in the trunk sapwood. Measures of TWU were compared with estimates derived from reference crop evapotranspiration (ET_o) and the area of shade cast by the tree on the soil surface (A _SH). A _SH was estimated prior to each de-branching event using a combination of photographs of the tree taken from the direction of the sun, and measures of fractional radiation interception in the area of shade cast by the tree. TWU and ET_o averaged 39.5 l/day and 4.7 mm/day, respectively, in the 6-day period prior to de-branching. Effective canopy cover (ECC; estimated as A _SH measured at solar noon) was 5.8 m² in that period. Five de-branching events reduced TWU and ECC by >95%. To account for the daytime variation in A _SH, we used effective area of shade (EAS), calculated from estimates of A _SH at solar noon and 3 h each side of solar noon. K _cb, the basal crop coefficient defined by Allen et al. [Crop evapotranspiration: guidelines for computing crop water requirements (FAO irrigation and drainage paper 56). Food and Agriculture Organisation of the United Nations, Rome, 1998], was related to EAS by K _cb = 1.05 EAS. These data for an isolated tree suggest that the transpiration component of orchard water use may be related to ET_o using estimates of effective fraction of shade on the soil surface.     

Agricultural water management in a humid region: sensitivity to climate,soil and crop parameters

A sensitivity analysis of irrigation water requirements at the regional scale was conducted for the humid southeastern United States. The GIS-based water resources and agricultural permitting and planning system (GWRAPPS), a regional scale, GIS-based, crop water requirement model, was used to simulate the effect of climate, soil, and crop parameters on crop irrigation requirements. The effects of reference evapotranspiration (ET_o) methods, available soil water holding capacities (ASWHC), crop coefficients (K_c), and crop root zone depths (z) were quantified for 203 ferneries and 152 potato farms. The irrigation demand exhibited a positive relationship with K_c and z, a negative relationship with ASWHC, and seasonal variations depending on the choice of ET_o methods. The average irrigation demand was most sensitive to the choice of K_c with a 10% shift in K_c values resulting in approximately 15% change in irrigation requirements. Most ET_o methods performed reasonably well in estimating annual irrigation requirements as compared to the FAO-56 PM method. However, large differences in monthly irrigation estimates were observed due to the effect of the seasonal variability exhibited by the methods. Our results suggested that the selection of ET_o method is more critical when modeling irrigation requirements at a shorter temporal scale (daily or monthly) as necessary for many applications, such as daily irrigation scheduling, than at a longer temporal scale (seasonal or annual). The irrigation requirements were more sensitive to z when the resultant timing of irrigation coincided with rainfall events. When compared with the overall average of the irrigation requirements differences, the site-to-site variability was low for K_c values and high for the other variables. In particular, soil properties had considerable average regional differences and variability among sites. Thus, the extrapolation of site-specific sensitivity studies may not be appropriate for the determination of regional responses crop water demand.     

Assessing satellite-based basal crop coefficients for irrigated grapes (Vitis vinifera L.)

A combined methodology of basal crop coefficient (K_cb) derived from vegetation indices (VI) obtained from satellite images and a daily soil water balance in the root zone of the crop was proposed to accurately estimate the daily grape crop coefficient and actual evapotranspiration. The modeled values were compared with field measurements of crop evapotranspiration (ET) using an energy balance eddy-covariance flux tower and adjusted for closure using the measured Bowen ratio. A linear relation between K_cb and VI for vineyard was obtained, K_cb = 1.44 × NDVI-0.10 and K_cb = 1.79 × SAVI-0.08. The correlation of the measured crop coefficient (K_c) and modeled (K_crf) exhibits a linear tendency, K_c = 0.96K_crf, r² = 0.67. Other derived parameters such as weekly K_c and daily and weekly ET show good consistency with measurements and higher coefficients of determination. The study of the soil water balance suggests the importance of soil water storage in grapes within the La Mancha region. These results validate the use of remote sensing as a tool for the estimation of evapotranspiration of irrigated wine grapes planted on trellis systems.     

An evaluation of common pan coefficient equations to estimate reference evapotranspiration in a subtropical climate (north of Iran)

Accurate reference evapotranspiration (ET₀) data are essential to water resources project planning and farm irrigation scheduling. Evaporation pans are widely used to estimate reference ET₀. Via the pan coefficient (K _p), ET₀ is estimated from evaporation pan data. Four common K _p equations (Orang in Potential accuracy of the popular non-linear regression equations for estimating pan coefficient values in the original and FAO-24 tables, unpublished report, 1998; Allen and Pruitt in J Irrig Drain Eng 117(5):758–773, 1991; Cuenca in Irrigation system design: an engineering approach, p 133, 1989; Snyder in J Irrig Drain Eng 118(6):977–980, 1992) to calculate daily K _p coefficients to estimate ET₀ were evaluated using a 10-year mean climate dataset for a subtropical climate (north of Iran). Overall results showed that ET₀ calculated using the daily K _p values from Orang (Potential accuracy of the popular non-linear regression equations for estimating pan coefficient values in the original and FAO-24 tables, unpublished report, 1998) provided more accurate daily, monthly, and annual total estimates compared to the others equations.     

An evaluation of two hourly reference evapotranspiration equations for semiarid conditions

The methodology proposed by the Food and Agriculture Organization (FAO) (Doorenbos, J., Pruitt, W.O., 1977. Crop water requirements. FAO irrigation and drainage. Paper No. 24. FAO, Rome) and updated by Allen et al. (Allen, R.G., Pereira, L.S., Raes, D., Smith, M., 1998. Crop evapotranspiration. Guidelines for computing crop water requirements. FAO irrigation and drainage. Paper No. 56. FAO, Rome) for calculating crop water requirements is the most extended and accepted method worldwide. This method requires the prior calculation of reference evapotranspiration (ET_o). This study evaluates the FAO-56 and American Society of Civil Engineers (ASCE) Penman–Monteith (PM) equations for estimation of hourly ET_o under the semiarid conditions of the province of Albacete (Spain). The FAO-56 and ASCE equations (hourly time step) were compared against measured lysimeter ET_o values at Albacete for 13 days during the period of April–October 2002 and 16 days during April–October 2003. The average of estimated FAO-56 Penman–Monteith ET_o values was equal to the average of measured values. However, the average of estimated ASCE Penman–Monteith values was 4% higher than the average of measured lysimeter ET_o values. This method overestimated measured lysimeter ET_o values by 0.45 mm h⁻¹.Simple linear regression and error analysis statistics suggest that agreement between both estimation methods and the lysimeter was quite good for the province of Albacete.In this paper, the FAO-56 Penman–Monteith equation for calculating hourly ET_o values was more accurate than the ASCE Penman–Monteith method under semiarid weather conditions in Albacete.     

Improvement of FAO-56 method for olive orchards through sequential assimilation of thermal infrared-based estimates of ET

The aim of this study is to use the FAO-56-based single crop coefficient approach to estimate actual evapotranspiration (AET) of an olive (Olea europaea L.) orchard in the Mediterranean semi arid region of Tensift-basin (central Morocco) during two consecutive growing seasons (2003 and 2004). The results showed that using crop coefficients K_c suggested by FAO-56 method yielded an AET overestimation by about 18% when compared against eddy covariance measurements. Therefore, the determination of appropriate K_c values is required to accurately estimate crop water requirement of olive orchards in such water scarce area.In this study, after applying the K_c values derived over olive orchard in Spain by Pastor and Orgaz [Pastor, M., Orgaz, F., 1994. Riego deficitario del olivar: los programas de recorte de riego en olivar. Agricultura 746, 768-776 (in Spanish)], a better agreement was observed between measured and simulated AET. The root mean square error (RMSE) was reduced by about 28%, from 0.80 to 0.61 mm/day for 2003 and from 0.93 to 0.69 mm/day for 2004. The used K_c values of olives at three crop growth stages (initial, mid-season and maturity) were 0.65, 0.45, and 0.65, respectively, the mid-season stage value being considerably lower than that suggested by the FAO-56.Despite these improvements in the performance of AET simulations, some discrepancies between measured and simulated AET remained, especially when water stress occurred. These discrepancies were ascribed to the estimation of the stress coefficient K_c To overcome this problem, we assimilated into FAO-56 single source model estimates of AET derived from a simple energy balance model along with thermal infrared observations. The latter were collected with the ASTER sensor in 2003 and from ground-based measurements in 2004. The results showed a clear improvement for FAO-56 performances after assimilation: for 2003 and 2004, the RMSE values between observations and simulations, respectively, dropped down from 0.61 to 0.52 and from 0.69 to 0.46 (corresponding to relative reductions of 15 and 40%, respectively).     

Evapotranspiration losses for pepper under plastic mulch and shallow water table conditions

Use of literature crop coefficient (K _c) values for quantifying evapotranspiration (ET_c) under non-standard conditions such as plastic mulch, shallow water table, and sub-tropical conditions can lead to inaccurate ET_c estimates. A 5-year experiment was conducted for fall crop growing seasons in south Florida to quantity bi-weekly ET_c and K _c for bell pepper grown under shallow water table and plastic mulch environments using large drainage lysimeters. The ET_c values varied from 205 to 320 mm with a seasonal average of 267 mm. Average K _c values for bell pepper for development, mid-season, and late stages were 1.05, 1.21, and 1.28, respectively. Higher than literature initial K _c values were due to rainfall and use of sub-irrigation system to maintain artificially high water table which results in high soil moisture in the bare soil area—such high moisture results in high evaporation. The K _c values from this study were statistically higher than literature values. Use of literature K _c values resulted in underestimating ET_c by 27–37%. The K _c values would provide improved estimates of sub-irrigated pepper ET_c in subtropical Florida and elsewhere with similar environment.     

Bahiagrass crop coefficients from eddy correlation measurements in central Florida

Bahiagrass (Paspalum notatum) is a warm-season grass used primarily in pastures and along highways and other low maintenance public areas in Florida. It is also used in landscapes to some extent because of its drought tolerance. Bahiagrass can survive under a range of moisture conditions from no irrigation to very wet conditions. Its well-watered consumptive use has not been reported previously. In this study, bahiagrass crop coefficients (K _c) for an irrigated pasture were determined for July 2003 through December 2006 in central Florida. The eddy correlation method was used to estimate crop evapotranspiration (ET_c) rates. The standardized reference evapotranspiration (ET_o) equation (ASCE-EWRI standardization of reference evapotranspiration task committee report, 2005) was applied to calculate ET_o values using on site weather data. Daily K _c values were estimated from the ratio of the measured ET_c and the calculated ET_o. The recommended K _c values for bahiagrass are 0.35 for January–February, 0.55 for March, 0.80 for April, 0.90 for May, 0.75 for June, 0.70 for July–August, 0.75 for September, 0.70 for October, 0.60 for November, and 0.45 for December in central Florida. The highest K _c value of 0.9 in May corresponded with maximum vapor pressure deficit conditions as well as cloud free conditions and the highest incoming solar radiation as compared to the rest of the year. During the summer (June to August), frequent precipitation events increased the cloud cover and reduced grass water use. The K _c annual trend was similar to estimated K _c values from another well-watered warm-season grass study in Florida.     

Evapotranspiration and responses to irrigation of broccoli

In cold, semi-arid areas, the options for crop diversification are limited by climate and by the water supply available. Growing irrigated crops outside the main season is not easy, because of climatic and market constraints. We carried out an experiment in Albacete, Central Spain, to measure the water use (evapotranspiration, ET) of broccoli (Brassica oleracea L. var. italica Plenck) planted in late summer and harvested at the end of fall. A weighing lysimeter was used to measure the seasonal ET under sprinkler irrigation. Consumptive use reached 359 mm for a period of 109 days after transplanting. The crop coefficient (K_c) for broccoli was obtained and compared to the standard recommendations for normal planting dates. Dual crop coefficient computations of the lysimeter ET data indicated that evaporation represented 31% of seasonal ET. An analysis of the variation in daily K_c values at a time of full cover suggested that the use of a grass lysimeter as a reference ET (ET_o) was superior to using the ASCE Penman-Monteith (ASCE PM) equation at hourly time steps, which in turn caused less variability in K_c than when using the FAO-56 Penman-Monteith (FAO-56 PM) equation at daily time steps for the ET_o calculation. An additional experiment aimed at evaluating the yield response to applied irrigation water by the drip method (seven treatments, from 59 to 108% of ET_c) generated a production function that gave maximum yields of near 12 t ha⁻¹ at an irrigation level of 345 mm, and a water use efficiency of 3.37 kg m⁻³. It is concluded that growing broccoli in the fall season is a viable alternative for crop diversification, as the lower yields obtained here may be more than compensated for by the higher produce prices in autumn, at a time of the year where irrigation water demand for other crops is very low.     

Estimation of dwarf green bean water use under semi-arid climate conditions through ground-based remote sensing techniques

Determination of temporal and spatial distribution of water use (WU) within agricultural land is critical for irrigation management and could be achieved by remotely sensed data. The aim of this study was to estimate WU of dwarf green beans under excessive and limited irrigation water application conditions through indicators based on remotely sensed data. For this purpose, field experiments were conducted comprising of six different irrigation water levels. Soil water content, climatic parameters, canopy temperature and spectral reflectance were all monitored. Reference evapotranspiration (ET₀), crop coefficient K_c and potential crop evapotraspiration (ET_c) were calculated by means of methods described in FAO-56. In addition, WU values were determined by using soil water balance residual and various indexes were calculated. Water use fraction (WUF), which represents both excessive and limited irrigation applications, was defined through WU, ET₀ and K_c. Based on the relationships between WUF and remotely sensed indexes, WU of each irrigation treatments were then estimated. According to comparisons between estimated and measured WU, in general crop water stress index (CWSI) can be offered for monitoring of irrigated land. At the same time, under water stress, correlation between measured WU and estimated WU based on CWSI was the highest too. However, canopy-air temperature difference (T_c − T_a) is more reliable than others for excessive water use conditions. Where there is no data related to canopy temperature, some of spectral vegetation indexes could be preferable in the estimation of WU.     

Reference evapotranspiration based on Class A pan evaporation via wavelet regression technique

Accurate estimation of reference evapotranspiration (ET₀) is important for water resources engineering. Therefore, a large number of empirical or semi-empirical equations have been developed for assessing ET₀ from numerous meteorological data. However, records of such weather variables are often incomplete or not always available for many locations, which is a shortcoming of these complex models. Therefore, practical and simpler methods are required for estimating the ET₀. In this study, the efficiency of a wavelet regression (WR) model in estimating reference evapotranspiration based on only Class A pan evaporation is examined. The results of the WR model are compared with those of three pan-based equations, namely the FAO-24 pan, Snyder ET₀ and Ghare ET₀ equations and their calibrated versions. Daily Class A pan evaporation data from the Fresno and Bakersfield stations of the United States Environmental Protection Agency in California, USA, are used in the study. The WR model estimates are compared against those of the FAO-56 Penman–Monteith equation. Results showed that the WR model is capable of accurately predicting the ET₀ values as a product of pan evaporation data.