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1.
The present study evaluates firstly the ability of the FAO-56 methodology, based on the two-step approach “reference evapotranspiration (ET0)—crop coefficient (K c),” to accurately determine the actual evapotranspiration (ET) of irrigated crops and proposes, secondly, the alternative approaches for improving this determination. The FAO-56 methodology is supported by two hypotheses: (1) ET0 represents all effects of weather and (2) K c varies predominately with specific crop characteristics and only marginally with climate, which enables the transfer of K c standard values among locations and climates. On the base of the theoretical analysis and experimental observations, a critical examination of the previous hypotheses demonstrates that they are not verified by reality. The first hypothesis is not verified for two reasons: (a) The formulation adapted by the Penman–Monteith equation and proposed in FAO-56 methodology for calculating ET0 uses climatic variables determined at a 24-h average scale. However, in principle it is only valid in permanent regime, in other words at least on an hourly scale. (b) The FAO-56-proposed formulation attributes a constant value to the canopy resistance of the reference surface; but in reality, this resistance is variable in relation to the climatic variables. The second hypothesis, concerning the two-step approach, is also not verified because the values of K c largely vary in relation to climatic variables (radiation, air vapour pressure deficit and wind speed). This fact does not support the possibility of the transferability of K c values into locations where the local conditions deviate from the conditions where the adjusted values of K c were determined. The weakness of the ET estimation, observed on several crops cultivated in the Mediterranean region, through the application of the FAO-56 methodology, is the result of errors accumulation, associated with that affects the determination of either ET0 or K c. The present study underlines the advantage of using a one-step approach in the calculation of ET, since it is based on fewer computation steps and, consequently, on fewer error sources than the two-step model. Two models adopting this approach are proposed and validated, one of which can be considered as operational, i.e. it only needs standard meteorological data as input. The use of these models enables an improvement of the ET estimation. This objective is a key component of any strategy to improve agricultural water management in Mediterranean region.  相似文献   

2.
In this study, weighing lysimeters were used to investigate the daily crop coefficient and evapotranspiration of wheat and maize in the Fars province, Iran. The locally calibrated Food and Agriculture Organization (FAO) Penman–Monteith equation was used to calculate the reference crop evapotranspiration (ETo). Micro-lysimetry was used to measure soil evaporation (E). Transpiration (T) was estimated by the difference between crop evapotranspiration (ETc) and E. The single crop coefficient (K c) was calculated by the ratio of ETc to ETo. Furthermore, the dual crop coefficient is composed of the soil evaporation coefficient (K e) and the basal crop coefficients (K cb) calculated from the ratio of E and T to ETo, respectively. The maximum measured evapotranspiration rate for wheat was 9.9 mm?day?1 and for maize was 10 mm?day?1. The total evaporation from the soil surface was about 30 % of the total wheat ETc and 29.8 % of total maize ETc. The single crop coefficient (K c) values for the initial, mid-, and end-season growth stages of maize were 0.48, 1.40, and 0.31 and those of wheat were 0.77, 1.35, and 0.26, respectively. The measured K c values for the initial and mid-season stages were different from the FAO recommended values. Therefore, the FAO standard equation for K c-mid was calibrated locally for wheat and maize. The K cb values for the initial, mid-, and end-season growth stages were 0.23, 1.14, and 0.13 for wheat and 0.10, 1.07, and 0.06 for maize, respectively. Furthermore, the FAO procedure for single crop coefficient showed better predictions on a daily basis, although the dual crop coefficient method was more accurate on seasonal scale.  相似文献   

3.
The study compares two formulas for calculating the daily evapotranspiration ET0 for a reference crop. The first formula was proposed by Allen et al. (AL), while the second one was proposed by Katerji and Perrier with the addition of the carbon dioxide (CO2) effect on evapotranspiration (KP). The study analyses the impact of the calculation by the two formulas on the irrigation requirement (IR). Both formulas are based on the Penman-Monteith equation but adopt different approaches for parameterising the canopy resistance r c . In the AL formula, r c is assumed constant and not sensitive to climate change, whereas in the KP formula, r c is first parameterised as a function of climatic variables, then ET0 is corrected for the air CO2 concentration. The two formulas were compared in two periods. The first period involves data from two sites in the Mediterranean region within a measured climate change period (1981–2006) when all the input climatic variables were measured. The second period (2070–2100) involves data from a future climate change period at one site when the input climatic variables were forecasted for two future climate scenarios (A2 and B2). The annual cumulated values of ET0 calculated by the AL formula are systematically lower than those determined by the KP formula. The differences between the ET0 estimation with the AL and KP formulas have a strong impact on the determination of the IR for the reference crop. In fact, for the two periods, the annual values of IR when ET0 is calculated by the AL formula are systematically lower than those calculated by the KP formula. For the actual measured climate change period, this reduction varied from 26 to 28 %, while for the future climate change period, it varied based on the scenario from 16 % (A2) to 20 % (B2).  相似文献   

4.
Summary This paper presents a study of the sensibility of the Penman-Monteith evapotranspiration model to climatic (available energy and vapour pressure deficit) and parametric (aerodynamic and canopy resistances, r a and r c respectively) factors in a semi-arid climate, for crops in contrasting water status (well irrigated and under water stress) and of different heights. Three experiments were carried out in southern Italy on reference grass (≈ 0.1 m), grain sorghum (≈ 1 m) and sweet sorghum (≈ 3 m). For this analysis the sensitivity coefficients, taken as hourly means, were evaluated during the growth season when the crops completely covered the soil. The relative errors on evapotranspiration were also evaluated for r a and r c . The results showed that, for reference grass, available energy and aerodynamic resistance play a major role. For crops under water stress the most important term to evaluate is canopy resistance. For a tall crop, as sweet sorghum, the role of the vapour pressure deficit is fundamental, both when the crop is in good water status and under water stress. Received July 14, 1997 Revised February 5, 1998  相似文献   

5.
Summary In this paper a model for estimating actual evapotranspiration is developed and tested for field crops (grain sorghum and sunflower) maintained under water stress conditions. The model is based on the Penman-Monteith formulation of ET in which canopy resistance (r c) is modeled with respect to the crop water status and local climatological conditions. The model was previously tested on reference grass; in this last case no reference was made to soil water conditions andr c was modeled only as a function of climatological parameters. Herer c is expressed as a function of available energy, vapour pressure deficit, aerodynamic resistance and crop water status by means of predawn leaf water potential. Results, obtained with various crop water stress intensities, show that, on a daily scale, calculated ET is 98% and 95% of the measured ET for sorghum and sunflower respectively. The correlation between daily calculated and measured ET is very high (r 2 = 0.95 for sorghum andr 2 = 0.98 for sunflower). On an hourly scale, the model works very well when the crops were not stressed and during the senescence stage. In case of weak and strong stress the model has to be used with some precautions.With 9 Figures  相似文献   

6.
A field experiment was conducted in a maize field in 2006 in an arid area of the Yellow River Basin in China. The daytime evapotranspiration (ETc) and soil evaporation beneath the maize canopy (E g) were measured by Bowen ratio energy balance method and micro-lysimeters, respectively. The results showed that the total ETc during maize growth season was 696 mm, and the maximum values occurred at about 90–140 days after sowing. The crop coefficient (K c), which was calculated from the ratio of ETc to reference evapotranspiration (ET0), was quite different from the values reported by other researchers in similar climate areas, with average values of 0.34, 0.47, 1.0 and 0.9 for initial, development, mid-season and late-season stages, respectively. High correlations between leaf area index (LAI) and average K c for every 4 days were obtained. The total E g was 201.4 mm with average values ranged from 0.92 to 2.05 for four growth stages of maize; and accounted for around 28.9 % of ETc. The ratio E g/ETc showed high negative relationship with LAI. These results were very important in precise management of irrigation for maize in Yellow River Basin areas.  相似文献   

7.
Global warming has caused unevenly distributed changes in precipitation and evapotranspiration, which has and will certainly impact on the wet-dry variations. Based on daily meteorological data collected at 91 weather stations in Northeast China (NEC), the spatiotemporal characteristics of dry and wet climatic variables (precipitation, crop reference evapotranspiration (ET0), and humid index (HI)) are analyzed, and the probable reasons causing the changes in these variables are discussed during the period of 1961–2014. Precipitation showed non-significant trend over the period of 1961–2014, while ET0 showed a significant decreasing trend, which led to climate wetting in NEC. The period of 2001–2012 exhibited smaller semiarid area and larger humid area compared to the period of 1961–1980, indicating NEC has experienced wetting process at decadal scale. ET0 was most sensitive to relative humidity, and wind speed was the second most sensitive variable. Sunshine hours and temperature were found to be less influential to ET0 in the study area. The changes in wind speed in the recent 54 years have caused the greatest influence on ET0, followed by temperature. For each month, wind speed was the most significant variable causing ET0 reduction in all months except July. Temperature, as a dominant factor, made a positive contribution to ET0 in February and March, as well as sunshine hours in June and July, and relative humidity in August and September. In summary, NEC has experienced noticeable climate wetting due to the significantly decreasing ET0, and the decrease in wind speed was the biggest contributor for the ET0 reduction. Although agricultural drought crisis is expected to be partly alleviated, regional water resources management and planning in Northeast China should consider the potential water shortage and water conflict in the future because of spatiotemporal dry-wet variations in NEC.  相似文献   

8.
Evapotranspiration and canopy resistance of grass in a Mediterranean region   总被引：1，自引：3，他引：1  
Summary A simple method for estimating actual evapotranspiration (ET) could become a suitable tool for irrigation scheduling. Resistance models can be useful if data on canopy resistance to water vapor flow (rc) and on aerodynamic resistance (ra) are available. These parameters are complex and hard to obtain. In this studyrc is analysed for a reference crop (grass meadow). Canopy resistance is dependent on climate, weather (radiation, atmospheric vapor pressure deficit, aerodynamic resistance), agronomic practices (irrigation, grass cutting) and time scale (hour, day). Anrc model, proposed by Katerji and Perrier (KP model), using some meteorological parameters as inputs, is presented. Canopy resistance calculated according to the KP model was used to estimate a referenceET ref on hourly and daily time scales.TheET ref estimated using the KP model on a daily time scale was compared with a model proposed by Allen, Jensen, Wright and Burman (AJWB model) — in whichrc depends on leaf area index only — and with direct measurements from a weighing lysimeter. The results show an underestimation of 18% for the AJWB model against an underestimation of 2% for the KP model. Since the hypotheses are the same for both models and aerodynamic resistance plays a secondary role, the better results obtained by the KP model are due torc modelling.With 11 Figures  相似文献   

9.
This paper examines the potential for the use of artificial neural networks (ANNs) to estimate the reference crop evapotranspiration (ET0) based on air temperature data under humid subtropical conditions on the southern coast of the Caspian Sea situated in the north of Iran. The input variables for the networks were the maximum and minimum air temperature and extraterrestrial radiation. The temperature data were obtained from eight meteorological stations with a range of latitude, longitude, and elevation throughout the study area. A comparison of the estimates provided by the ANNs and by Hargreaves equation was also conducted. The FAO-56 Penman–Monteith model was used as a reference model for assessing the performance of the two approaches. The results of this study showed that ANNs using air temperature data successfully estimated the daily ET0 and that the ANNs with an R 2 of 0.95 and a root mean square error (RMSE) of 0.41 mm day?1 simulated ET0 better than the Hargreaves equation, which had an R 2 of 0.91 and a RMSE of 0.51 mm day?1.  相似文献   

10.
Reference evapotranspiration (ETo) is significant for water resources planning and environmental studies. Many equations have been developed for ETo estimation in various geographic and climatic conditions, of which, the Penman–Monteith FAO 56 (PMF-56) equation was accepted as reference method. A major complication in estimating ETo by the PMF-56 model is the requirement for meteorological data that may not be readily available from typical weather stations in many areas of the globe. This restriction necessitates use of simpler models which require less input data. In this study, the original and five modified versions of the Hargreaves equation that require only temperature and rainfall were evaluated in humid, semi-humid, semi-arid and arid climates in Iran. The results showed that the original and modified versions of the Hargreaves equation had the poorest performance in semi-humid climate and the best performance in windy humid environment. Further, the ETo estimations with the Hargreaves equations having rainfall parameter were poor as compared to those from the PMF-56 method under majority of the climatic situations studied.  相似文献   

11.
To investigate the alfalfa crop response to environmental factors, a Bowen ratio-energy balance method was used to evaluate short-term alfalfa canopy resistance. Continuous evapotranspiration (ET a ) and the aerodynamic resistance (r a ) for an alfalfa crop in each 20-min interval were calculated. Using the calculated ET a and r a and the Penman-Monteith approach, the bulk stomatal or actual canopy resistance (r c ) was evaluated. The continuous 20-min resistances were computed for clear and partially cloudy sky conditions, and different average crop heights. The results show that this technique can satisfactorily be used to study the manner in which the aerodynamic and canopy resistances respond to short-term variations in weather elements such as photosynthetically active radiation (PAR), wind speed and atmospheric saturation vapor deficit.Research Assistant Professor and Assistant Utah State Climatologist, Research Associate Professor and Research Assistant, respectively.  相似文献   

12.
Sunshine duration data are desirable for calculating daily solar radiation (R s) and subsequent reference evapotranspiration (ET0) using the Penman–Monteith (PM) method. In the absence of measured R s data, the Ångström equation has been recommended by the Food and Agriculture Organization (FAO) of the United Nations. This equation requires actual sunshine duration that is not commonly observed at many weather stations. This paper examines the potential for the use of artificial neural networks (ANNs) to estimate sunshine duration based on air temperature and humidity data under arid environment. This is important because these data are commonly available parameters. The impact of the estimated sunshine duration on estimation of R s and ET0 was also conducted. The four weather stations selected for this study are located in Sistan and Baluchestan Province (southeast of Iran). The study demonstrated that modelling of sunshine duration through the use of ANN technique made acceptable estimates. Models were compared using the determination coefficient (R 2), the root mean square error (RMSE) and the mean bias error (MBE). Average R 2, RMSE and MBE for the comparison between measured and estimated sunshine duration were calculated resulting 0.81, 6.3 % and 0.1 %, respectively. Our analyses also demonstrate that the difference between the measured and estimated sunshine duration has less effect on the estimated R s and ET0 by using Ångström and FAO-PM equations, respectively.  相似文献   

13.
Accurate estimation of reference evapotranspiration (ET0) becomes imperative for better managing the more and more limited agricultural water resources. This study examined the feasibility of developing generalized artificial neural network (GANN) models for ET0 estimation using weather data from four locations representing different climatic patterns. Four GANN models with different combinations of meteorological variables as inputs were examined. The developed models were directly tested with climatic data from other four distinct stations. The results showed that the GANN model with five inputs, maximum temperature, minimum temperature, relative humidity, solar radiation, and wind speed, performed the best, while that considering only maximum temperature and minimum temperature resulted in the lowest accuracy. All the GANN models exhibited high accuracy under both arid and humid conditions. The GANN models were also compared with multivariate linear regression (MLR) models and three conventional methods: Hargreaves, Priestley–Taylor, and Penman equations. All the GANN models showed better performance than the corresponding MLR models. Although Hargreaves and Priestley–Taylor equations performed slightly better than the GANN models considering the same inputs at arid and semiarid stations, they showed worse performance at humid and subhumid stations, and GANN models performed better on average. The results of this study demonstrated the great generalization potential of artificial neural techniques in ET0 modeling.  相似文献   

14.
Accurate estimation of reference evapotranspiration (ET 0 ) is essential for the computation of crop water requirements, irrigation scheduling, and water resources management. In this context, having a battery of alternative local calibrated ET 0 estimation methods is of great interest for any irrigation advisory service. The development of irrigation advisory services will be a major breakthrough for West African agriculture. In the case of many West African countries, the high number of meteorological inputs required by the Penman-Monteith equation has been indicated as constraining. The present paper investigates for the first time in Ghana, the estimation ability of artificial intelligence-based models (Artificial Neural Networks (ANNs) and Gene Expression Programing (GEPs)), and ancillary/external approaches for modeling reference evapotranspiration (ET 0 ) using limited weather data. According to the results of this study, GEPs have emerged as a very interesting alternative for ET 0 estimation at all the locations of Ghana which have been evaluated in this study under different scenarios of meteorological data availability. The adoption of ancillary/external approaches has been also successful, moreover in the southern locations. The interesting results obtained in this study using GEPs and some ancillary approaches could be a reference for future studies about ET 0 estimation in West Africa.  相似文献   

15.
Identifying changes in reference evapotranspiration (ETo) can help in future planning of crop water requirements and water resources for high water-use efficiency. This study analyzes the ETo trends on a seasonal and annual timescale by applying various statistical tools to data from 41 Iranian weather stations during the period between 1966 and 2005. The Mann–Kendall test after removal of significant serial correlation was used to determine the statistical significance of the trends, and the change point in the ETo time series was determined using the cumulative sum technique. The results showed that (1) the significant increasing trends of annual ETo were observed at seven stations which are located in different parts of Iran, (2) the stations located at the southeast, northeast, and northwest corners of Iran experienced the highest positive change of annual ETo, and (3) the changes in seasonal ETo were most pronounced in the winter season, both in terms of trend magnitude and the number of stations with significant trends.  相似文献   

16.
Summary A methodological study on a tall canopy in a Mediterranean region was carried out in order to identify the most suitable method for measuring the actual evapotranspiration (ET). ET from a sweet sorghum crop was measured by 4 different methods: (i) energy balance/eddy correlation, (ii) energy balance/Bowen ratio, (iii) energy balance/aerodynamic simplified, and (iv) floating lysimeter (ETmeter). In order to compare a very large range of ET values and to reduce experimental errors due to low gradients of air humidity and temperature, the crop was submitted to two soil drying-wetting cycles. To evaluate the main limitations of each method with respect to crop height, crop ET was monitored during the entire vegetative cycle, from stem elongation (crop height 0.85 m, full canopy) to grain filling (when the crop was 2.5 m high). The comparison between the micrometeorological methods (i, ii, and iii) was made on hourly and daily time steps, while the analysis of ETmeter measurements was made on a daily time step only. On an hourly scale: eddy correlation ET was 106% of Bowen ratio ET and simplified aerodynamic ET was 116%, 125% and 135% of Bowen ratio ET with the first sensors are placed at the top of the canopy and the second sensors at 0.7 m, 1.4 m and 2.8 m from the first sensors, respectively. On a daily scale: eddy correlation ET was 102% of Bowen ratio ET, simplified aerodynamic was 114% of Bowen ratio ET and ETmeter ET was 97% of Bowen ratio ET. In the last case the values are very widely spread and the correlation is really not so good. The results show that the Bowen ratio method and the eddy correlation method are in good agreement on daily scales, however, certain precautions, must be taken concerning the eddy correlation method on an hourly scale. The simplified aerodynamic method failed when crop height was > 1.5 m and the ETmeter failed under windy conditions (wind speed > 2.0 m/s) and limited crop water conditions.With 13 Figures  相似文献   

17.
Coupled atmosphere-ocean general circulation models (GCMs) simulate different realizations of possible future climates at global scale under contrasting scenarios of land-use and greenhouse gas emissions. Such data require several additional processing steps before it can be used to drive impact models. Spatial downscaling, typically by regional climate models (RCM), and bias-correction are two such steps that have already been addressed for Europe. Yet, the errors in resulting daily meteorological variables may be too large for specific model applications. Crop simulation models are particularly sensitive to these inconsistencies and thus require further processing of GCM-RCM outputs. Moreover, crop models are often run in a stochastic manner by using various plausible weather time series (often generated using stochastic weather generators) to represent climate time scale for a period of interest (e.g. 2000 ± 15 years), while GCM simulations typically provide a single time series for a given emission scenario. To inform agricultural policy-making, data on near- and medium-term decadal time scale is mostly requested, e.g. 2020 or 2030. Taking a sample of multiple years from these unique time series to represent time horizons in the near future is particularly problematic because selecting overlapping years may lead to spurious trends, creating artefacts in the results of the impact model simulations. This paper presents a database of consolidated and coherent future daily weather data for Europe that addresses these problems. Input data consist of daily temperature and precipitation from three dynamically downscaled and bias-corrected regional climate simulations of the IPCC A1B emission scenario created within the ENSEMBLES project. Solar radiation is estimated from temperature based on an auto-calibration procedure. Wind speed and relative air humidity are collected from historical series. From these variables, reference evapotranspiration and vapour pressure deficit are estimated ensuring consistency within daily records. The weather generator ClimGen is then used to create 30 synthetic years of all variables to characterize the time horizons of 2000, 2020 and 2030, which can readily be used for crop modelling studies.  相似文献   

18.
As one of the key grain-producing regions in China, the agricultural system in the North China Plain (NCP) is vulnerable to climate change due to its limited water resources and strong dependence on irrigation for crop production. Exploring the impacts of climate change on crop evapotranspiration (ET) is of importance for water management and agricultural sustainability. The VIP (Vegetation Interface Processes) process-based ecosystem model and WRF (Weather Research and Forecasting) modeling system are applied to quantify ET responses of a wheat-maize cropping system to climate change. The ensemble projections of six General Circulation Models (GCMs) under the B2 and A2 scenarios in the 2050s over the NCP are used to account for the uncertainty of the projections. The thermal time requirements (TTR) of crops are assumed to remain constant under air warming conditions. It is found that in this case the length of the crop growth period will be shortened, which will result in the reduction of crop water consumption and possible crop productivity loss. Spatially, the changes of ET during the growth periods (ETg) for wheat range from ?7 to 0 % with the average being ?1.5?±?1.2 % under the B2 scenario, and from ?8 to 2 % with the average being ?2.7?±?1.3 % under the A2 scenario/consistently, changes of ETg for maize are from ?10 to 8 %, with the average being ?0.4?±?4.9 %, under the B2 scenario and from ?8 to 8 %, with the average being ?1.2?±?4.1 %, under the A2 scenario. Numerical analysis is also done on the condition that the length of the crop growth periods remains stable under the warming condition via breeding new crop varieties. In this case, TTR will be higher and the crop water requirements will increase, with the enhancement of the productivity. It is suggested that the options for adaptation to climate change include no action and accepting crop loss associated with the reduction in ETg, or breeding new cultivars that would maintain or increase crop productivity and result in an increase in ETg. In the latter case, attention should be paid to developing improved water conservation techniques to help compensate for the increased ETg.  相似文献   

19.
Summary ?The performance of the Penman-Monteith (PM) equation to estimate daily reference evapotranspiration (ETO) was investigated by attributing three distinct features to the canopy resistance (r c): (i) r c constant at 70 s m−1 (Allen et al., 1998; FAO Irrigation and Drainage Paper n. 56), (ii) r c variable as linear function of a critical resistance r c, depending on weather variables and empirical parameters relating r c to r * (Katerji and Perrier, 1983; Agronomie, 3[6]: 513–521) and (iii) r c variable as a mechanistic function of weather variables only (Todorovic, 1999; J. Irrig. Drainage Eng., ASCE, 125[5]: 235–245). Daily weather and grass lysimeter data, measured for a period of seven years at Policoro (Southern Italy), were used. The results confirmed the relative robustness of the PM method with constant r c while better estimates were obtained only when variable r c was used. The mechanistic approach of Todorovic (1999) provided the best estimates, while the approach of Katerji and Perrier (1983), with empirically derived parameters, has shown to be not conservative enough to be extended to different locations without calibration. Received January 2, 2002; revised October 31, 2002; accepted December 7, 2002  相似文献   

20.
Estimation of reference evapotranspiration (ET0) is needed to support irrigation design and scheduling, and watershed hydrology studies. There are many available methods to estimate evapotranspiration from a water surface, comprising both direct and indirect methods. In the first part of this study, the generalized regression neural networks model (GRNN) and radial basis function neural network (RBFNN) are developed and compared in order to estimate the reference ET0 for the first time in Algeria. Various daily climatic data, that is, daily mean relative humidity, sunshine duration, maximum, minimum and mean air temperature, and wind speed from Dar El Beida, Algiers, Algeria, are used as inputs to the GRNN and RBFNN models to estimate the ET0 obtained using the FAO-56 Penman-Monteith equation (PM56). The performances of the models are evaluated using root mean square errors (RMSE), mean absolute error (MAE), Willmott index of agreement (d) and correlation coefficient (CC) statistics. In the second part of the study, the empirical Hargreaves-Samani (HG) and Priestley-Taylor (PT) equations are also considered for the comparison. Based on the comparisons, the GRNN was found to perform better than the RBFNN, Priestley-Taylor and Hargreaves-Samani models. The RBFNN model is ranked as the second best model.  相似文献   

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