FAO Penman-Monteith Equation Research Articles

Does recent climate warming drive spatiotemporal shifts in functioning of high-elevation hydrological systems?

Reference evapotranspiration (ETo) is the basic component of the hydrological cycle. This study systematically analyzed the spatiotemporal variations of ETo in the Three-River Headwaters Region (TRHR) by utilizing the FAO Penman–Monteith equation during the period of 1961–2016, and studied the impact of climatic variables on ETo fluctuation based on sensitivity analysis and contribution analysis. Over the past 56 years, ETo increased in most months and annually in most regions of the TRHR, and the spatial distribution for annual ETo varied apparently. Sensitivity analysis revealed that ETo responded more to changes in maximum temperature and sunshine duration than relative humidity, wind speed, and minimum temperature. The relative importance of climatic variables to ETo was influenced by the ETo sensitivity and the fluctuation of climatic variables. Contribution analysis indicated that the significant temperature increase was mainly responsible for the observed increase in ETo. Besides, spatially distributed analysis showed that the annual TRHR ETo tended to increase from east to west, north to south, and high to low elevation. The analysis also indicated a dominant altitudinal spatial gradient in the sensitivity of ETo to changes in different climatic variables. The physical mechanisms for ETo variations discussed in this study might provide a reference for water resources management and conservation of high-elevation areas.

Utilizing Recent Climate Data in Eastern Texas to Calculate Trends in Measures of Aridity and Estimate Changes in Watering Demand for Landscape Preservation

AbstractEastern Texas houses a transition zone from semiarid conditions in the far west to some of the wettest areas of the continental United States not influenced by mountainous terrain. The region, vulnerable to drought and flooding rains, is projected to experience higher water demand with its growing population. In the coming decades, municipal consumption, including water for landscape preservation, will supplant irrigation as the largest usage category. The amount of supplemental water required to maintain plantings is dependent on evapotranspirative demand and precipitation patterns. Reference evapotranspiration can be calculated using four daily climate parameters in the FAO-56 Penman–Monteith equation. This was combined with soil moisture capacity and daily accumulated precipitation to determine historical evapotranspiration rates at 14 observation stations across the eastern region of Texas from 1973 through 2017 and allowed for the creation of a recursive algorithm that introduced supplemental water for vegetation preservation as conditions crossed thresholds of dryness. Time series data analysis showed an increasing degree of aridity, as higher temperatures have decreased relative humidity and dry periods have become more prolonged and severe under stable average annual precipitation totals. Without additional increases in rainfall, the region is expected to continue its drying trend, leading to moisture-stressed plant life and higher water demands to maintain landscapes in a well-watered state.

Crop water requirement for wheat under different conservation practices in the semi arid region of India

Experiments were conducted during Rabi 2014–15 and 2015–16 at research farm of ICAR- Indian Agricultural research Institute, New Delhi to study crop water requirement for wheat under different conservation practice along with conventional practice using single crop coefficient, dual crop coefficient and water balance methods. The field experiment was carried out with seven treatments i.e. conventional tillage (CT), permanent narrow-bed without residue (PNB), permanent narrow-bed with residue (PNB+R), permanent broad-bed without residue (PBB), permanent broad-bed with residue (PBB+R), zero tilled flat bed without residue (ZT), zero tilled flat bed with residue (ZT+R) arranged in a randomized block design (RBD) with three replications. Adjusted single and dual crop coefficient values for semi-arid climate of Delhi were calculated with the help of FAO-56 method. The reference crop evapotranspiration ET0, was estimated using FAO Penman–Monteith equation. Results showed that estimated reference evapotranspiration and pan evaporation had good correlation at R2 value of 0.89 for wheat crop. The adjusted value of single and basal crop coefficient had initially lower value, increase during development phase reached maximum during mid stage and then decline during late stage. Soil evaporation coefficient Ke was low except during irrigation and precipitation events. The value of crop evapotranspiration was found to be more value during mid season stage with respect to different treatments. The crop evapotranspiration (ETc) and actual evapotranspiration (ETa) were found higher values under CT, ZT and ZT+R treatments because they had flood irrigation. PNB, PNB+R, PBB and PBB+R had less value due to furrow irrigation. Water productivity had maximum values under PBB+R treatment and lowest value under conventional treatment. PBB+R treatment had 23–27% higher value in wheat as compared to corresponding value in conventional treatment. Since dual crop coefficient method consider the effect of soil evaporation and crop transpiration both therefore the value calculated by it are more reliable as compared to single crop coefficient. Therefore dual crop coefficient method is useful for determine water stress in crop, daily evapotranspiration losses, water need of crop and for irrigation scheduling in the crop for optimum use of irrigation water. Among all treatments, PBB+R showed better water productivity than other treatments. Thus, PBB+R management practice could be adopted by farmers for improving water productivity in semi-arid region of India.

Very high resolution satellite-based monitoring of crop (olive trees) evapotranspiration in precision agriculture

Remote Sensing contributes through the processing and analysis of very high spatial and spectral resolution time series satellite data to a decision support at field level. In this paper, in the olive tree farms of the Agricultural Association of Messolonghi-Nafpaktia, the extraction of Kc and various vegetation indices, such as chlorophyll and red-edge, are presented aiming at the assessment of crop evapotranspiration and irrigation/fertiliser inflows during a period of 24 months. The methodology includes the generation of red-edge, chlorophyll and FPAR indices based on the second NIR band of WV-2, and clustering. The so-called ETc(satellite) produced by using the reference ETo from FAO-56 Penman-Monteith equation, meteorological data set and Kc(satellite) extracted by NDVI utilising the red-edge and second NIR bands of WV-2, respectively. The dynamic ETd compared with ETc. The applied methodology proved to be very useful for the implementation and verification of AGRO 2.1 and 2.2 standards.

Very high resolution satellite-based monitoring of crop (olive trees) evapotranspiration in precision agriculture

Remote Sensing contributes through the processing and analysis of very high spatial and spectral resolution time series satellite data to a decision support at field level. In this paper, in the olive tree farms of the Agricultural Association of Messolonghi-Nafpaktia, the extraction of Kc and various vegetation indices, such as chlorophyll and red-edge, are presented aiming at the assessment of crop evapotranspiration and irrigation/fertiliser inflows during a period of 24 months. The methodology includes the generation of red-edge, chlorophyll and FPAR indices based on the second NIR band of WV-2, and clustering. The so-called ETc(satellite) produced by using the reference ETo from FAO-56 Penman-Monteith equation, meteorological data set and Kc(satellite) extracted by NDVI utilising the red-edge and second NIR bands of WV-2, respectively. The dynamic ETd compared with ETc. The applied methodology proved to be very useful for the implementation and verification of AGRO 2.1 and 2.2 standards.

A smartphone APP for weather-based irrigation scheduling using artificial neural networks

Abstract: The objective of this work was to develop a smartphone application (APP) for a weather-based irrigation scheduling using artificial neural networks (ANNs), as well as to validate it in a green corn (Zea mays) crop. An APP (IrriMobile) that uses ANNs based on temperature and relative humidity, or on temperature only, was developed to estimate the reference evapotranspiration (ETo). The APP and Bernardo’s methodology for irrigation scheduling, with the ETo estimated by the FAO-56 Penman-Monteith equation, were used to schedule the irrigation for a green corn crop. The performance of empirical equations to estimate ETo was also assessed. Several corn morphological and agronomic characteristics were evaluated. The APP was used in the experiment with temperature, relative humidity, and rainfall data. Its use was also simulated with temperature and rainfall data only. There was no difference for any of the green corn characteristics evaluated. ETo estimation through the APP showed a higher performance than that by the evaluated equations. The APP overestimates the irrigation requirements by 8 and 19% when using temperature and relative humidity, and temperature only, respectively.

Evaluation of crop and irrigation water requirements for some selected crops in Apulia region -Southern Italy

Nowadays, nearly 90% of global water consumption is caused by irrigation activities, and more than 40% of the crops are produced under irrigated conditions. This study is an endeavour to estimate the irrigation water requirement (IWR) and crop water requirement (CWR) for some selected crops (Pepper, Eggplant, Potato, Soybean, Maize, Wheat Melon, Lettuce, Sunflower, Broadbean, Citrus, Cherry, Olive tree, Sugarbeet, Artichoke, Wine Grapes, Carrot...etc.) in Sothern Italy. The selected districts (Sant’ Arcangelo) have been taken as a case study area. Demanded meteorologically (rainfall, temperature, humidity, wind speed, sunshine hours) and crop data (crop coefficient and crop calendar) have been collected for 30 years period from 1981 to 2011. FAO CROPWATv8.0 software has been applied for requisite calculation of CWR and IWR along with the developing of cropping patterns. The FAO Penman-Monteith equation is used for estimating the reference evapotranspiration (ET0) by using meteorological data in the framework of CROPWAT model as it regarded as a good evaluator for a wide variety of climatic conditions. The analysis indicates that FAO Penman-Monteith suits very well for the study area and can be successfully used for the estimation of reference evapotranspiration. The important results in this study indicate that the IWR is very low from November to April (wintertime) due to higher rainfall intensity in these months and from month May to October a considerable amount of water is required for irrigation.
 JEL Classification: Q25, Q24,Q10

Reference crop evapotranspiration database in Spain (1961–2014)

Abstract. Obtaining climate grids describing distinct variables is important for developing better climate studies. These grids are also useful products for other researchers and end users. The atmospheric evaporative demand (AED) may be measured in terms of the reference evapotranspiration (ETo), a key variable for understanding water and energy terrestrial balances and an important variable in climatology, hydrology and agronomy. Despite its importance, the calculation of ETo is not commonly undertaken, mainly because datasets consisting of a high number of climate variables are required and some of the required variables are not commonly available. To address this problem, a strategy based on the spatial interpolation of climate variables prior to the calculation of ETo using FAO-56 Penman–Monteith equation was followed to obtain an ETo database for continental Spain and the Balearic Islands, covering the 1961–2014 period at a spatial resolution of 1.1 km and at a weekly temporal resolution. In this database, values for the radiative and aerodynamic components as well as the estimated uncertainty related to ETo were also provided. This database is available for download in the Network Common Data Form (netCDF) at https://doi.org/10.20350/digitalCSIC/8615 (Tomas-Burguera et al., 2019). A map visualization tool (http://speto.csic.es, last access: 10 December 2019) is available to help users download the data corresponding to one specific point in comma-separated values (csv) format. A relevant number of research areas could take advantage of this database. For example, (i) studies of the Budyko curve, which relates rainfall data to the evapotranspiration and AED at the watershed scale, (ii) calculations of drought indices using AED data, such as the Standardized Precipitation–Evapotranspiration Index (SPEI) or Palmer Drought Severity Index (PDSI), (iii) agroclimatic studies related to irrigation requirements, (iv) validation of climate models' water and energy balance, and (v) studies of the impacts of climate change in terms of the AED.

Evaluación del efecto de distintas aproximaciones de la radiación en la estimación de la evapotranspiración usando el modelo FAO Penman-Monteith

La evapotranspiración es uno de los procesos que mayor importancia tienen en la correcta cuantificación de la disponibilidad hídrica, pero es de los más difíciles de estimar del ciclo hidrológico en regiones con escasa información meteorológica. Una alternativa que se ha popularizado para resolver la problemática anterior es el uso de productos de satélite con estimaciones de la evapotranspiración a escala regional. Sin embargo, estos deben ser validados con información de campo adecuada antes de su aplicación regional, la cual es casi inexistente en latitudes tropicales. Por ello, esta investigación propone una mejora a la ecuación de la FAO Penman-Monteith, al introducir variabilidad espacial y temporal de la radiación neta (Rn) a través del algoritmo Viewshed. Los resultados muestran una mejora del 1.1% al comparar los resultados de la evapotranspiración de referencia con las estimaciones provenientes del producto satelital MOD16A3 y usando la forma tradicional de calcular la Rn.

EVALUATION OF CLIMATE CHANGE IMPACTS ON REFERENCE EVAPOTRANSPIRATION UNDER RCPs SCENARIOS IN NORTHERN GREECE

<p>Reference evapotranspiration (ETo) is an important component in water resources, agricultural and environmental modeling, thus its assessment is critical in understanding the impacts of climate change on the sector of agriculture. In this study, the effect of climate change on reference evapotranspiration in Northern Greece, was assessed. For this purpose, the climate change scenarios RCP2.6, RCP4.5 and RCP8.5 based on four Earth System Models (ESMs) CanESM2, GFDL-ESM2M, HadGEM2-ES and IPSL-CM5A-LR were used for the time periods 2041-2060 and 2081-2100 and for the baseline period (1981-2000). Reference evapotranspiration was estimated with the use of the FAO Penman-Monteith equation. Results showed that mean annual ETo is projected to increase in response to climate change during 2041-2060 and 2081-2100 according to the four ESMs with the greater increase predicted by the end of the 21st century. The increase in ETo is driven mainly by the temperature rise and secondly by the solar radiation increase in the future. The results indicate that the development of adaptation strategies is necessary for the improvement of agricultural water management and the reduction of climate change impacts on agriculture.</p>

A distributed interval nonlinear multiobjective programming approach for optimal irrigation water management in an arid area

Considering the uncertainties in agricultural system and spatiotemporal variability in evapotranspiration and precipitation, a distributed interval nonlinear multiobjective programming (DINMP) model was developed for optimal allocation of limited irrigation water resources in the middle reaches of Heihe River basin. The meteorological data from meteorological stations were used to estimate reference crop evapotranspiration (ET0) through FAO56 Penman-Monteith (PM) equation, and then the remote sensing MOD16/PET data were fitted by linear regression model according to the FAO56 PM results. The 95% confidence interval was used to further improve the accuracy of the fitting results. Thus, satellite-based potential evapotranspiration (PET) and ground-based ET0 estimation were integrated to not only reflect the spatial and temporal variability but also guarantee the accuracy of the ET0. In the terms of precipitation, spatial interpolation was used to spatial information of precipitation. Based on these spatiotemporal data, a DINMP with three objectives, including maximizing economic benefits and water saving as well as minimizing water shortage of critical growth periods, was formulated, and further solved by fuzzy coordination method. The optimal allocation scheme improves the irrigation water productivity by [0.50, 0.66] kg/m3, and decreases net irrigation water allocation by [0.33, 1.01] ×108 m3. These results show that DINMP can not only consider the uncertainties and multiple objectives in agricultural water management, but also improve the spatial resolution of optimal water allocation strategies. The framework of this study can provide a reference for agricultural water managers in similar areas to obtain more reasonable water allocation schemes.

Estimation of reference evapotranspiration in Brazil with limited meteorological data using ANN and SVM – A new approach

Reference evapotranspiration (ETo) is a variable of great importance for several purposes, such as hydrological studies and irrigation scheduling. The FAO-56 Penman-Monteith (FAO-56 PM) equation is recommended to estimate ETo given its good accuracy. However, the estimation of ETo poses a challenge when the availability of meteorological data is limited since the FAO-56 PM equation requires data on temperature, relative humidity, solar radiation and wind speed. This study evaluates, for the first time, the performance of alternative equations, artificial neural network (ANN) and support vector machine (SVM), for the estimation of daily ETo across the entirety of Brazil using measured data on temperature and relative humidity or only temperature. Two strategies, not yet used in Brazil, were used to develop the ANN and SVM models: (i) the definition of groups of weather stations with similar climatic characteristics, using the K-means clustering algorithm, to develop models specific for each group; and (ii) the addition of previous meteorological data as input for the models. Data from 203 weather stations distributed across Brazil were used. The ANN and SVM models showed higher performances than the equations that were studied, even when they were calibrated. The evaluated strategies (clustering and previous days) provided considerable performance gains. For the temperature-based models, the best performance was obtained by the ANN developed with the strategy of clustering and the use of data from two previous days as input; however, due to the similar performance and greater generalization capacity, the ANN developed without clustering and with the use of data from four previous days is recommended. For the temperature- and relative humidity-based models, the ANN developed with data from four previous days was the best option.

Modelling reference evapotranspiration for Megecha catchment by multiple linear regression

Reference evapotranspiration (ETo) is a complex process in the hydrological cycle that influences the quantity of runoff and then the irrigation water requirements. Many methods have been developed to estimate reference evapotranspiration. The reliable reference evapotranspiration methods are parameter rich models but not applicable for data scarce regions. On the other hand, accuracy and reliability of simple reference evapotranspiration models vary widely according to regional climate conditions. Estimation of reference evapotranspiration of specific area is imperative for investigating, planning, designing, and managing irrigation schemes. The objective of the present study is to determine the ETo values using combination Penman–Monteith model and to devise a model used to predict reference evapotranspiration in the Megecha catchment. In this study, the potential of multiple linear regression model using least squares is investigated in modeling of mean monthly reference evapotranspiration obtained using the standard FAO-56 Penman–Monteith equation. Various combinations of daily climatic data, namely solar radiation, air temperature, relative humidity, and wind speed were used as inputs to the model development. Thus, this can give direction to evaluate the degree and effect of each variable on estimated ETo. In line to this, residual analysis, co-efficient of determination and residual error were used as comparison tools for the evaluation of the model performance. The result of the multiple correlation showed that sun hour, wind speed, and maximum temperature were strongly positive correlation with ETOr = 0.82, 0.71, and 0.78, respectively, whereas relative humidity has moderately negative correlation (r = − 0.604). The multiple linear regression model gave residual errors of 0.26 mm/day and co-efficient of determination of 0.92 for the meteorological station considered. Based on the residual analysis results, it was found that the multiple linear regression model followed a linear trend. The input variables of the model were fitting, and this model could be successfully employed in estimating and predicting the monthly reference evapotranspiration in the study area and can be used in similar parts of data sparse regions.

The Effect of Climate Change on Future Reference Evapotranspiration in Different Climatic Zones of Iran

Evapotranspiration can be considered as an indicator in evaluating the effects of climate change. It is the sole factor with the capability of concurrently balancing the ecosystem energy and water fluxes. Reference evapotranspiration (ETo) is the amount of water evaporated from reference crop that is affected by climatic parameters. The aim of this study was to assess ETo during the period of 2020–2049 in various climatic zones of Iran (including Tabriz, Bushehr, Isfahan, Sanandaj and Urmia). Climatic parameters including relative humidity, wind speed, Sunshine hours, atmospheric pressure, maximum and minimum temperatures were utilized for calculating ETo using FAO Penman–Monteith equation. The NCEP data and HADCM3 model data (under scenario A2 and B2) were used for prediction of future climatic parameters during 2020–2049. Statistical down scaling model was used as a hybrid regression model as well as a stochastic weather data generator. The course period was between 1986 and 2015 that was regarded for calibration and evaluation of the model. Subsequently, evapotranspiration was estimated using the model outputs in the FAO Penman–Monteith equation. Results indicated that the simulated data by the model has the same accuracy and validity under both scenarios A2 and B2. Results showed that in the studied areas, ETo tend to have an increasing trend in upcoming years. In scenario A2, ETo will increase about 16.81, 0.137, 17.52, 9.46 and 2.57 mm year−1 in Tabriz, Bushehr, Isfahan, Sanandaj and Urmia stations, respectively. Also our results represented that ETo will increase about 7.67, 6.52, 10.33, 7.73 and 1.99 mm year−1 in Tabriz, Bushehr, Isfahan, Sanandaj and Urmia stations, respectively based on the B2 scenario. Although no significant trend was observed in most of the climatic variables under A2 and B2 scenarios over the time period of 2020–2049, the ETo significantly increased during this period. Hence it could be concluded that ETo is a better indicator for describing the future climate change, compared to other climatic variables.

Computing FAO56 reference grass evapotranspiration PM-ETo from temperature with focus on solar radiation

The computation of the reference crop evapotranspiration (ETo) using the FAO Penman-Monteith equation (PM-ETo) requires data on maximum and minimum air temperatures (Tmax, Tmin), vapour pressure deficit (VPD), solar radiation (Rs) and wind speed at 2 m height (u2). However, those data are often not available, or data sets may be incomplete or have questionable quality. Various procedures were proposed in FAO56 to overcome these limitations and an abundant literature has been and is being produced relative to alternative computational methods. Studies applied to a variety of climates, from hyper-arid to humid, have demonstrated that improved methods to compute PM-ETo from temperature only (PMT approach) have appropriate accuracy. These methods refer to estimating: (i) the dew point temperature (Tdew) from Tmin or, in case of humid climates, from the mean temperature, Tmean; (ii) Rs from the temperature difference (TD = Tmax-Tmin); and (iii) u2 using default global or regional values. Greater difficulties refer to the need for locally calibrating the radiation adjustment coefficient (kRs) used with the Rs equation. Therefore, considering that calibrated kRs values were made available by past studies for a large number of locations and diverse climates, the current study developed and tested simple computational approaches relating locally calibrated kRs with various observed weather variables – TD, relative humidity (RH) and average u2. The equations were developed using CLIMWAT monthly full-data relative to all the Mediterranean countries. The equations refer to all available data, or to data grouped as hyper-arid and arid, semi-arid, dry and moist sub-humid, and humid climates. To test those kRs equations, ETo computed from temperature and using the predicted kRs values were compared with ETo computed with full data sets of the same Mediterranean locations and of Iran, Inner Mongolia, Portugal and Bolivia. RMSE average values result then small, ranging from 0.34 to 0.54 mm day−1, therefore not very far from values obtained when a trial and error procedure was used for all the same locations, from 0.27 to 0.46 mm day−1. These indicators allow to propose the use of kRs obtained from the predictive equations instead of locally calibrated kRs values, which greatly eases computations and may largely favour the use of the PMT approach.

Modification of FAO Penman–Monteith equation for minor components of energy

AbstractThe conventional Food and Agriculture Organization of the United Nations (FAO) Penman–Monteith (P-M) equation requires knowledge of the available energy to estimate reference evapotranspiration (ETo); however, it is common to ignore the minor energy components (MECs). This study was conducted to determine the effect of not including the MECs in the FAO P-M equation. Fifteen-min micrometeorological records of four sites (covered with corn, soybeans, and prairie) in central Iowa, USA, during the years 2007–2012 were investigated. The major/minor components of the energy equation were either measured or estimated by in-situ eddy covariance instruments. It was discovered that, on average, the MECs accounted for at least 13% of daily net radiation, leading to 27% decrease in daily ETo. Therefore, an equation is introduced to estimate MECs as a function of net radiation, air temperature, and Monin–Obukhov length; and another equation is regressed to roughly estimate daily MECs as a function of net radiation and day of the year. The findings in this study suggest a fundamental modification of FAO P-M formula by considering the inclusion of MECs in the energy term.

Standardized Precipitation Evapotranspiration Index is highly correlated with total water storage over China under future climate scenarios

A Standardized Precipitation Evapotranspiration Index (SPEI) model, which uses the FAO-56 Penman–Monteith equation to calculate potential evapotranspiration, has been developed and is considered appropriate for drought monitoring and assessment. However, the correlation of SPEI to total water storage (TWS) across multiple timescales, derived from future climate scenarios, is still unclear for China. In this study, the correlation of SPEI on different timescales (1-, 3-, 6-, 12-, 24- and 48-month) to TWS projected by a global climate model [the Community Climate System Model, version 4 (CCSM4)] under two representative concentration pathway scenarios (RCP2.6 and RCP8.5) for the period 2021–2100 in China is analyzed. The results show that, in general, SPEI is highly correlated with CCSM TWS in most of China (especially in eastern China) at the 12-month timescale, and is therefore regarded as an adequate indicator for representing situations of water resources and evaluating hydrological droughts. At the 12-month timescale, the correlations of SPEI to CCSM TWS vary across different river basins; and the variations in the pattern of correlations are greater due to faster warming and greater precipitation under RCP8.5. It is hoped that this article will provide guidance on the use of SPEI for detecting the impacts of future climate change on drought severity in China.

Capability of Sentinel-2 data for estimating maximum evapotranspiration and irrigation requirements for tomato crop in Central Italy

The occurrence of water shortages ascribed to projected climate change, especially in the Mediterranean region, fosters the interest in remote sensing (RS) applications to optimize water use in agriculture. Remote sensing evapotranspiration and water demand estimation over large cultivated areas were used to manage irrigation to minimize losses during the crop growing cycle. The research aimed to explore the potential of the MultiSpectral Instrument (MSI) sensor on board Sentinel-2A to estimate crop parameters, mainly surface albedo (α) and Leaf Area Index (LAI) that influence the dynamics of potential evapotranspiration (ETp) and Irrigation Water Requirements (IWR) of processing tomato crop (Solanum lycopersicum L.). Maximum tomato ETp was calculated according to the FAO Penman-Monteith equation (FAO-56 PM) using appropriate values of canopy parameters derived by processing Sentinel-2A data in combination with daily weather information. For comparison, we used the actual crop evapotranspiration (ETa) derived from the soil water balance (SWB) module in the Environmental Policy Integrated Climate (EPIC) model and calibrated with in-situ Root Zone Soil Moisture (RZSM). The experiment was set up in a privately-owned farm located in the Tarquinia irrigation district (Central Italy) during two growing seasons, within the framework of the EU Project FATIMA (FArming Tools for external nutrient Inputs and water Management). The results showed that canopy growth, maximum evapotranspiration (ETp) and IWR were accurately inferred from satellite observations following seasonal rainfall and air temperature patterns. The net estimated IWR from satellite observations for the two-growing seasons was about 272 and 338 mm in 2016 and 2017, respectively. Such estimated requirement was lower compared with the actual amount supplied by the farmer with sprinkler and drip micro-irrigation system in both growing seasons resulting in 364 (276 mm drip micro-irrigation, and 88 mm sprinkler) and 662 (574 mm drip micro-irrigation, and 88 mm sprinkler) mm, respectively. Our findings indicated the suitability of Sentinel-2A to predict tomato water demand at field level, providing useful information for optimizing the irrigation over extended farmland.

A new method for indirectly estimating infiltration of paddy fields in situ

Abstract. Infiltration is one of the major procedures in water balance research and pollution load estimation in paddy fields. In this study, a new method for indirectly estimating infiltration of paddy fields in situ was proposed and implemented in Taihu Lake basin. Since when there were no rainfall, irrigation and artificial drainage, the water depth variation process of a paddy field is only influenced by evapotranspiration and infiltration (E+F). Firstly, (E+F) was estimated by deciding the steady decreasing rate of water depth; then the evapotranspiration (ET) of the paddy field was calculated by using the crop coefficient method with the recommended FAO-56 Penman-Monteith equation; finally, the infiltration of the paddy field was obtained by subtracting ET from (E+F). Results show that the mean infiltration of the studied paddy field during rice jointing-booting period was 7.41 mm day−1, and the mean vertical infiltration and lateral seepage of the paddy field were 5.46 and 1.95 mm day−1 respectively.

Analysis of Drought Intensity and Trends Using the Modified SPEI in South Korea from 1981 to 2010

The aim of this study is to analyze the characteristics of drought, such as intensity and trends, based on SPEI (Standardized Precipitation Evapotranspiration Index) at 8 stations in South Korea from 1981 to 2010. The traditional SPEI is based on the Thornthwaite equation for estimating evapotranspiration; SPEI_th. However, a standard of agricultural water management in Korea suggests the FAO Penman-Monteith equation; SPEI_pm. Therefore, we analyzed the intensity, variability, and trends of drought using SPEI_th and SPEI_pm, respectively, and compared the results. SPEI_pm showed slightly more intensive drought rather than SPEI_th except for Chuncheon and Gwangju. In 5 stations—excluding Cheoncheon, Gwangju and Jinju—the cumulative probability that SPEI_pm was below −1.5 was significantly increased from 1981–1995 to 1996–2010. In addition, the northwest and southwest regions had higher intensity of 1-month droughts, and the central and southwest regions had a higher intensity of 3-month droughts. According to the Mann–Kendall test, there was a decreasing trend of 1-month SPEI during the fall season and 3-month SPEI during winter season.