Penman-Monteith Research Articles

Estimation of Reference Evapotranspiration in Bhavanisagar Block of Tamil Nadu Using FAO ETo Calculator

The FAO Penman-Monteith equation is used by the ETo calculator software to calculate reference evapotranspiration – ETo from meteorological data. FAO chose this technique as the standard because it is physically based, roughly approximates grass ETo in the studied region, and explicitly considers both physiological and aerodynamic aspects. The application can handle climate data on a daily, ten-day, and monthly basis. The data may be supplied in a variety of units, and it can be analyzed using regularly used meteorological parameters. In this study, ETo calculator version 3.2 is used to estimate the ETo in Bhavanisagar. The results revealed that, it is possible to estimate ETo by using the ETo calculator. The concept of the reference evapotranspiration was introduced in this study and the result obtained are used further to estimate the evaporative demand of the atmosphere independently of crop type, crop development and management practices.

Estimating oil palm water usage in peat soils using sap flow technique

Massive issues on significant water used by oil palm trees suggest further estimation of water exploited by oil palm trees. This research employed sap flow technique using thermal dissipation probes (TDP), compared to Penman-Monteith equation as the benchmark. Water utilization by plants was studied through evapotranspiration, to investigate their water footprint and water productivity. Field study was carried out in a 17 year old oil palm plantation in Siak, Riau, Indonesia. Sap flow measurement was carried out on the 17th frond over sapric peat soil during 7th January - 18th March 2019. Water used from 19th oil palm was 40.97±6.63 L day−1 equals to 0.51±0.083 mm day−1 (mean ±SD). While, estimation based on Penman-Monteith equation was 286.3 ± 64.078 L day−1 equals to 3.58±0.80 mm day−1 (mean ±SD). Total accumulated water from Penman-Monteith equation (286.3 L day−1) was considerably higher than the one from sap flow measurement (41 L day−1). The result showed that water footprint from 17 year old oil palm tree based on sap flow and Penman-Monteith equation was 0.204 and 1.43 m3 kg−1 fresh fruit bunches respectively. While water productivity estimated from sap flow was 0.70 kg m−3 while Penman-Monteith equation achieved 4.89 kg m−3.

Assessment of irrigation situation and water requirement in perennial fruit crops in Dinh Quan district, Dong Nai province

Dinh Quan is a mountainous agricultural district in Dong Nai province, focusing on agricultural development. Estimating reference and current crop evapotranspiration, as well as irrigation water requirements, is an essential foundation for effective irrigation planning for some perennial fruit crops (mandarin, banana, and mango) to manage water resources in a reasonable and sustainable way. Applying the FAO Penman-Monteith equation combined with the CROPWAT model, reference crop evapotranspiration (ETo), current crop evapotranspiration (ETc), and irrigation water requirement (IWR) of some perennial fruit crops being cultivated mainly in Dinh Quan district (banana, mandarin, and mango) were estimated. The total amount of water required for irrigation in the year of mandarin, mango, and banana trees in the study area was determined to be 592.6 mm, 473.0 mm, and 976.4 mm, respectively, corresponding to 5,926 m3/ha, 4,730 m3/ha and 9,764 m3/ha. Based on this result, the annual irrigation water requirement of the study area was calculated to be around 46 million m3 for the cultivation of mango, banana, and mandarin, mainly in the dry season (accounting for more than 95%). With current farming practices and using water resources, if there are no effective management measures and solutions, it may lead to a shortage of water for future production, especially in the dry season.

Irrigation water requirements as affected by diverse climate conditions

Determination of crop water requirement is one of the key parameters for precise irrigation scheduling, especially under limited water resources, such as in Egypt. Hence, an accurate estimation of reference evapotranspiration (ETo) is a vital factor for agriculture production, therefore the objectives of the present study were to study the influence of climate change on different seasons and comparing of ETo estimations using Blany- Criddle (BC) and FAO-56 Penman-Monteith (PM) equations under present and future climatic conditions. Data on the present climate have been collected from Wadi El-Natrun meteorological station, Egypt from 1991 to 2020. While the future climate data have been chosen for the concerned RCPs scenarios: RCP2.6, RCP4.5, RCP6.0, and RCP8.5 in 2040, 2060, 2080, and 2100. The results revealed that all months’ reordered Tmean above 20 oC, except December, January, and February where they ranged between 17.68 and 19.44 oC. The highest Tmean values were observed in July (32.3oC), August (31.9 oC), and June (31.8 oC), while February scored the lowest Tmean (17.7 oC).

Evolution of potential evapotranspiration and its sensitivity to climate change based on the Thornthwaite, Hargreaves, and Penman–Monteith equation in environmental sensitive areas of China

Global warming intensifies the water cycle and regional water condition differences by changing the surface environment. The ecological system in environmental sensitive areas of China (ESAC) is stressed by water resources, and the ecological effect of dry–wet evolution is even more profound. However, the applicability of different potential evapotranspiration (ET0) assessment methods and the response mechanism of ET0 to climate change remain unknown. In this study, we evaluated the reliability of ETTH, ETHarg, and ETPM derived from Thornthwaite (TH), Hargreaves (Harg), and Penman–Monteith (PM) formulas using the monthly average air temperature (Tavg), maximum air temperature (Tmax), minimum air temperature, sunshine duration (SSD), wind speed (WIN), and relative humidity (RHU) from 1961 to 2018. Further, non-parametric trend analysis, correlation analysis, multiple regression analysis, wavelet analysis, and seasonal and trend decomposition using Loess were used to analyze the spatial–temporal evolution of ET0 and the moisture index (MI) and its relationship with climate change in ESAC from 1961 to 2018. The results are as follows: (1) The P-M formula has excellent applicability in the research area. Under the background of average temperature rising at 0.035 °C yr−1, ETPM decreases with a rate of −0.59 mm yr−1, which indicates the “pan evaporation paradox” phenomenon. Using 1993 as the node, ETPM changed from a significant decrease to an increase. (2) WIN, SSD, Tavg, and Tmax significantly promoted changes in ETPM, and RHU and precipitation (Pr) were mainly reduced. The determinant factor of ETPM change was Tavg from 1961 to 2018. (3) MI change was mainly influenced by Pr, SSD, and ETPM. Pr promoted the change, whereas SSD and ETPM reduced it. The linear combination of ETPM and SSD could explain the change in MI. Our findings verified the applicability of PM in areas with severe interannual precipitation fluctuations, revealing the evolution of dry–wet pattern changes and their driving mechanisms in ESAC, which can deepen the cognition of the law of long-term land surface water cycle and effectively guide the formulation and implementation of regional drought and flood disaster response measures.

Evapotranspiration Variations of the Minjiang River Basin in Southeastern China from 2000 to 2019

Evapotranspiration is one of the critical processes in the terrestrial hydrological cycle, and the assessment of evapotranspiration is essential for understanding the regional hydrological cycle. In this study, the Minjiang River Basin, a typical watershed in the humid subtropical climate zone, is selected as the study region. The Penman-Monteith equation and the dual crop coefficient method are used to calculate the actual evapotranspiration (ETa) at seven meteorological stations within the study basin. Meanwhile, the applicability of the Global Land Data Assimilation System-Noah (GLDAS-Noah) ETa data in the Minjiang River Basin is evaluated based on stations P-M equation results, then to analyze the changes of the ETa in the Minjiang River Basin from 2000 to 2019. The results show that the GLDAS-Noah ETa data are well applicable in the Minjiang River Basin (R2 > 0.9 and NSE > 0.8). The ETa in the basin shows an increasing trend since 2000, and the increasing rate is 3.60 mm·yr−1 (p < 0.01). The seasonal variation results show that ETa tends to increase in winter and spring, with increasing rates of 1.10 mm·yr−1 (p < 0.01) and 2.60 mm·yr−1 (p < 0.01), respectively, while the ETa did not change significantly in summer and autumn. Annual air temperature has the largest effect on annual ETa (59.6%), followed by precipitation at 33.9%. ETa increased in spring was mainly influenced by increasing temperatures (89.4%) in the Minjiang River Basin from 2000 to 2019. The research results are of great benefit to further improve the understanding of ETa variations in the basin under global warming.

Medium‐ to long‐term forecast of reference crop evapotranspiration based on the correction of the principal control factor

AbstractThis study selected the temperature Penman–Monteith (PMT) model to solve the difficulty of reference crop evapotranspiration (ET0) prediction caused by incomplete meteorological data. Then, the principal control factor of the PMT model was determined using several indicators. The results show that the annual average correlation and sensitivity coefficients between Tmax and ET0 are the highest. Hence, among the factors, Tmax is the largest contributor in contribution proportion and amount to ET0 and the principal control factor of the PMT model. The root mean square error (RMSE), relative error (RE) and mean absolute error (MAE) of the forecast ET0 increased by 0.7, 0.2, and 0.6 mm/day, respectively, after the 16th day compared with those on the 15th day. Thus, a remarkable drop in ET0 forecast precision is observed and is hardly accurate for the purpose of water distribution management in an irrigation district. The RMSE, RE, and MAE of the Tmax forecast decrease by 2.0–3.0°C, 0.1–0.2, and 2.0–2.8°C, respectively, and those of the corresponding ET0 forecast decrease by 0.7–0.9, 0.2–0.3, and 0.6–0.7 mm/day, respectively, after Tmax correction. Compared with the decaying‐average method, the improved decaying‐average method can correct Tmax better and improve the ET0 prediction accuracy.

Estimation methods to define reference evapotranspiration: a comparative perspective

Abstract Evapotranspiration is a key variable for hydrologic, climatic, agricultural, and environmental studies. Given the non-availability of economically and technically easy to implement direct measurement methods, evapotranspiration is estimated primarily through the application of empirical and regression models, and machine learning algorithms that incorporate conventional meteorological variables. While the FAO-56 Penman-Monteith equation worldwide has been recognized as the most accurate equation to estimate the reference evapotranspiration (ETo), the number of required climatic variables makes its application questionable for regions with limited ground-based climate data. This note provides a summary of empirical and semi-empirical equations linked to its data requirement and the problems associated with these models (transferability and data quality), an overview of regression models, the potential of machine learning algorithms in regression tasks, trends of reference evapotranspiration studies, and some recommendations of the topics future research should address that would lead to a further improvement of the performance and generalization of the available models. The terminology used in this note is consistent in both the theoretical and practical field of evapotranspiration, which is often dispersed in the academic literature. The goal of this note is to provide some perspective to stimulate discussion.

Why the Effect of CO2 on Potential Evapotranspiration Estimation Should Be Considered in Future Climate

Potential evapotranspiration (PET) is an important factor that needs to be considered in regional water management and allocation; thus, the reasonable estimation of PET is an important topic in hydrometeorology and other related fields. There is evidence that increased CO2 concentration alters the physiological properties of vegetation and thus affects PET. In this study, changes in PET with and without the CO2 effect over China is investigated using seven CMIP6-GCMs outputs under seven shared socioeconomic pathways (SSPs) based scenarios (SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, and SSP5-8.5), as well as the contribution rate of CO2 on PET in different climatic regions. Changes in estimated PET based on modified Penman–Monteith (PM) method that considers the CO2 effect is compared with the traditional PM method to examine how PET quantity varies (differences) between these two approaches. The results show that the PET values estimated by the two methods explored opposite trends in 1961–2014 over entire China; it decreases with consideration of CO2 but increases without consideration of CO2. In the future, overall PET is projected to increase under all scenarios during 2015–2100 for China and its three sub-regions. PET generally tends to grow slower when CO2 is taken into account (modified PM approach), than when it is not (traditional PM method). In terms of differences in the estimated PET by the two methods, the difference between the two adopted methods increased in China and its sub-regions for the 1961–2014 period. In the future, the difference in estimated PET is anticipated to continuously increase under SSP3-7.0 and SSP5-8.5. Spatially, a much greater extent of difference is found in the arid region. Across the arid region, the PET difference is projected to be the highest at 138% in the mid-term (2041–2060) with respect to the 1995–2014 period, whereas it tends to increase slower in the long-term period (2081–2100). Importantly, CO2 is found to be the most dominant factor (−154.2% contribution) to have a great effect on PET changes across the arid region. Our findings suggest that ignorance of CO2 concentration in PET estimation will result in significant overestimation of PET in the arid region. However, consideration of CO2 in PET estimation will be beneficial for formulating strategies on future water resource management and sustainable development at the local scale.

Environmental Assessment of Future Potential Evaporation for Al-Najaf Governorate, Iraq through Evaluating Various Estimation Methods Using Statistical Downscaling Model

The hydrological cycle in nature is affected by climate changes, which are reflected in the water resources on the Earth (surface and underground) as evapotranspiration, thereby causing water scarcity. Increasing global temperature rates have exacerbated evaporation rates (PET). To estimate PET, scientists invented many mathematical equations, the most prominent of which is the Penman-Monteith equation. Most of the innovative methods require the provision of many parameters to be implemented; therefore, feasibly worthless for application in data mingy regions. The performance of the four PET estimation methods has been investigated depending either on temperature or radiation observed at Al-Najaf Governorate, Iraq. The accuracy and efficiency of each method have been evaluated with the outputs of the reference Penman-Monteith method. Through assessment, Hargreaves Samani temperature-based method reveals high acceptability of the estimated PET than the Jensen-Haise method and the other radiation-based methods (Penman and Makkink). The Statistical Downscaling Model/Tool (SDSM version 5.2) is applied to predict temperature values for the years 2050 and 2100. Estimated PET using Hargreaves Samani formula for 2050 and 2100 shows that Al-Najaf Governorate will encounter severe water scarcity due to the expected future increase in evaporation rates. Overall, regions classified as dry with high temperatures are compatible with methods of estimating PET values that depend on temperatures more than those that depend on radiation.

Reduction of Evapotranspiration in Microenvironment Conditions of Table Grape Vineyards Protected by Different Types of Plastic Covers

Saving water is a major challenge to increase environmental sustainability, particularly in semi-arid regions where most table grapes are produced. Water use is driven by atmospheric demand, which combines effects of solar radiation (prominent factor), wind, air temperature and humidity. Covering table grapes with transparent plastics is spread in many regions. Covers lower incoming solar radiation and wind speed, changing air temperature and humidity. This study assessed the effects of two plastic covers on reference evapotranspiration (ET0) in comparison to the open field. For two years, two vineyards (cv. Victoria) trained to overhead trellis systems (tendone) were covered with two transparent polyethylene sheets: an agrotextile fabric (C), and a commercial film (S). The sheet spectrophotometric properties were analyzed and the radiometric coefficients calculated. Micrometeorological data were recorded in the covered vineyards and in a nearby uncovered one. ET0 was calculated for June and July using the simplified Penman–Monteith equation. The coefficient of transmissivity to total photosynthetic radiation, a proxy of net radiation, was 73% for cover C and 83% for cover S. On average, ET0 decreased by 35% under cover C and 31% under cover S. Hence, in addition to providing protection from external agents, covers represent a valid tool for saving water in table grape viticulture; nevertheless, their radiometric properties should be considered and optimized to better achieve this goal.

Modelling hourly evapotranspiration in urban environments with SCOPE using open remote sensing and meteorological data

Abstract. Evapotranspiration (ET) is a fundamental variable for assessing water balance and the urban heat island (UHI) effect. Terrestrial ET is deeply dependent on the land cover as it derives mainly from soil evaporation and plant transpiration. The majority of well-known process-based models based on the Penman–Monteith equation focus on the atmospheric interfaces (e.g. radiation, temperature and humidity), lacking explicit input parameters to precisely describe vegetation and soil properties. The model soil-canopy-observation of photosynthesis and energy fluxes (SCOPE) accounts for a broad range of surface–atmosphere interactions to predict ET. However, like most modelling approaches, SCOPE assumes a homogeneous vegetated landscape to estimate ET. As urban environments are highly fragmented, exhibiting a mix of vegetated and impervious surfaces, we propose a two-stage modelling approach to capture most of the spatiotemporal variability of ET without making the model overly complex. After predicting ET using the SCOPE model, the bias caused by the assumption of homogeneous vegetation is corrected using the vegetation fraction extracted by footprint modelling. Two urban sites equipped with eddy flux towers presenting different levels of vegetation fraction and imperviousness located in Berlin, Germany, were used as study cases. The correction factor for urban environments increased the model accuracy significantly, reducing the relative bias in ET predictions from 0.74 to 0.001 and 2.20 to −0.13 for the two sites considering the SCOPE model with remote sensing-derived inputs. Model errors (RMSE) were considerably reduced in both sites, from 0.061 to 0.026 and 0.100 to 0.021, while the coefficient of determination (R2) remained similar after correction, 0.82 and 0.47, respectively. The novelty of this study is to provide hourly ET predictions combining the temporal dynamics of ET in a natural environment with the spatially fragmented land cover in urban environments at a low computational cost. All model inputs are open data and available globally for most medium-sized and large cities. This approach can provide ET maps in different temporal resolutions to better manage vegetation in cities in order to mitigate the UHI effect and droughts.

Uncertainties in evapotranspiration projections associated with estimation methods and CMIP6 GCMs for South Korea

This study compared the performance capabilities of three potential evapotranspiration (PET) methods, Thornthwaite (TW), Hargreaves and Samani (HS), and Penman-Monteith (PM), to simulate historical and future daily PET levels in South Korea using climate variables from Coupled Model Intercomparison Project 6 (CMIP6) Global Climate Models (GCMs). Five evaluation metrics were used to quantify the reproducibility of the climate variables and PETs at ten stations in South Korea for the historical period used here (1985–2014). The changes and uncertainty associated with the changes in PET in the near (2031–2060) and far (2071–2100) futures were calculated for two shared socioeconomic pathways (SSPs) of 2–4.5 and 5–8.5. As a result, PETs estimated using the three methods for the historical period showed high performance in terms of five evaluation metrics. Overall, PETs showed an increase for both the future periods and the SSPs. The PET estimated using the PM method showed the greatest increase, while that estimated using HS showed the most modest increase in the future. The PM method also showed the highest reliability and lowest uncertainty in the PET estimations, while the opposite was true for HS. This study contributes to our understanding of rational PET methods by which to calculate hydrological factors such as drought indexes for future periods via GCM simulations.

Using support vector machine to deal with the missing of solar radiation data in daily reference evapotranspiration estimation in China

Accurate estimation of reference evapotranspiration (ET0) is of great importance for regional water resources planning and irrigation scheduling. The FAO56 recommended Penman-Monteith (P-M) model is widely adopted as the standard method for ET0 estimation, but its application is usually restricted by limited meteorological data worldwide, especially global solar radiation (Rs). This study provided two possible solutions to deal with the missing Rs data in ET0 estimation in China mainland. In the first solution, Rs data were estimated with the Ångström-Prescott (A-P) formula and daily sunshine hours. The values of two A-P formula fundamental coefficients a and b were obtained through three ways: (1) estimated based on limited Rs measurements at 80 solar radiation measurement stations (or site-calibrated); (2) recommended by the FAO-56 manual (or FAO-recommended); and (3) estimated based on the altitude and latitude of each weather station through the support vector machine algorithm (or SVM-estimated). The second solution used the SVM algorithm and available weather variables without Rs. The results showed that the FAO-recommended coefficients a and b were separately overestimated and underestimated in China mainland, which generated the largest simulation errors of Rs. However, the transfer errors from Rs estimations to ET0 estimations were reduced by using the P-M model for all of the three kinds of coefficients. Compared with the Rs-based models, the estimation accuracy of the SVM-ET0 model yielded the highest accuracy both at the training stage (R2 = 0.979; RMSE = 0.273 mm d−1) and the testing stage (R2 = 0.973; RMSE = 0.302 mm d−1). Generally, both the P-M and the machine-learning-based methods could be used for the ET0 estimation, when only Rs data were missing. However, considering the complexity in the programming, the P-M model combining with the A-P formula with the SVM-estimated A-P coefficients is recommended for daily ET0 estimation in China.

Leaf and canopy stomatal resistance, aerodynamic resistance, and evapotranspiration of irrigated continuous no‐till and disk‐till maize

AbstractThe impact of no‐till (NT) management as compared with conventional tillage practices (e.g., disk till [DT]) on plant stomatal behavior in relation to model estimation of crop evapotranspiration (ETc) and plant physiological functions has not been sufficiently evaluated. This research investigated the effects of NT and DT management on maize (Zea mays L.) physiological parameters and ETc losses. We also tested the methodology to estimate ETc using a one‐step Penman–Monteith (PM) model with measured variable resistance from scaled‐up leaf stomatal resistance (RL) to canopy resistance (RC) with Bowen Ratio Energy Balance System (BREBS)‐measured ETc. Photosynthetic photon flux density (PPFD) explained 76 and 79% of the variability in RL for NT and DT maize, respectively, which varied with growth stage. Disk‐till maize RL was 29, 5, 25, and 4% higher than NT maize RL during the vegetative, tasseling and silking, reproductive, and near‐physiological‐maturity stages, respectively. The seasonal average scaled‐up RC values for NT and DT maize were 102.4 and 128.6 s m–1, respectively. The PM‐estimated ETc correlated strongly with the BREBS‐measured ETc, with the PM model estimates being 8 and 6% within the BREBS measurements on an hourly and daily basis, respectively. To the best of our knowledge, this research is the first to develop the response curves (PPFD vs. RL) for maize for different growth stages under NT and DT. The analyses presented here can provide invaluable data and information for plant physiology research, crop modeling, determining crop response to different management, and environmental drivers.

An integrated assessment approach for fossil groundwater quality and crop water requirements in the El-Kharga Oasis, Western Desert, Egypt

Study regionThe El-Kharga Oasis in the Western Desert of Egypt is selected as the study area due to its hyberarid climate condition and water scarcity. In this region, the fossil groundwater is the main water source; therefore, preserving groundwater quality and quantity is mandatory. Study focusThis study evaluated groundwater suitability for irrigation purposes and assessed the water requirements of cultivated crops to optimize the water supply in hyperarid climate regions. In total, 79 deep groundwater samples were hydrochemically tested to determine the suitability for irrigation by assessing the key water quality parameters. Spatial distribution maps of all chemical parameters, such as pH, EC, SAR, RSC, SSP, TDS, total hardness, Na+, K+, Ca++, Mg++, Fe, Mn, Cl-, and SO4—, were developed. The FAO CROPWAT 8.0 model, based on the Penman–Monteith equation, was used to forecast agricultural water requirements for three years, 2010, 2011, and 2012. New hydrological insights for the regionThe groundwater had medium salinity and low sodium in 84% of the cases. In comparison, high salinity was found in 16% of the samples, indicating that groundwater can be used for many soil types with a low risk of exchangeable sodium. Except for 15 of the 79 wells, all groundwater samples had chloride concentrations less than 100 mg/l. The sulfate ion distribution map showed a low sulfate ion content in the extreme western south. The total annual irrigation water requirements of all crops for 2010, 2011 and 2012 were 199.4, 215.1, and 231.7 million m3/year, respectively, reflecting a gradual increase of approximately 16.57 million m3/total area/year due to the expansion of the cultivated area. The analysis showed that modern irrigation systems reduced the amount of irrigation water by 32% and increased the cultivated area by 45% compared to conventional irrigation methods. Severe groundwater depletion occurred during the dry season from March to July, which exacerbated the water stress in the study region. The results confirmed that the region is under water stress. Accordingly, water conservation is urgently recommended.

Irrigated agriculture potential of Australia’s northern territory inferred from spatial assessment of groundwater availability and crop evapotranspiration

Agricultural expansion has been a hot topic in the Northern Territory (NT) of Australia in recent years. However, insufficient information on available water resources and crop evapotranspiration is a bottleneck to this expansion. Towards closing this gap, this study employs the newest Global Land Data Assimilation System (GLDAS; version 2.2) catchment products assimilated from the Gravity Recovery and Climate Experiment (GRACE; hereafter called GLDAS-DA) and the Food and Agriculture Organization (FAO) Penman-Monteith equation to spatially evaluate the Balance between water availability (i.e., groundwater and effective rainfall) and melons, maize and citrus crop evapotranspiration (water demand) of three representative (short-, medium-season and perennial) crop types over the NT for the 2010–2019 period. Specifically, this Balance is the estimated ratio of water availability and crop evapotranspiration, representing the crop area that can be planted in each GLDAS-DA grid cell. The larger the Balance, the greater the irrigated agriculture potential. Under the average 2010–2019 conditions, our results show that the northern part of the NT has the highest irrigated agriculture potentials with the average Balance of 9430 ha (15.7%), 5490 ha (9.1%) and 3520 ha (5.8%) for melons, maize and citrus, respectively, excluding non-agriculture areas. Irrigated agriculture in the central part of the NT shows less potential compared to the northern part of the NT, with the average Balance of 2780 ha (4.6%), 2000 ha (3.3%) and 970 ha (1.6%) for melons, maize and citrus, respectively (excluding non-agriculture areas). The southern part of the NT shows an average Balance below 1% of grid cell for all three crops, suggesting that only small-scale irrigated agriculture could be possible. In addition, the Balance across most of the northern and central parts of the NT decreased by 50% or more during 2019 dry period. Drought risk management should therefore be a serious consideration when exploring further expansion of irrigated agriculture in the NT.

A hybrid deep learning framework with physical process description for simulation of evapotranspiration

Evapotranspiration (ET) estimation models can be broadly classified as statistical or physical process based models. However, assuming the limitation of individual approaches, the integration of these two approaches has become a challenging task for ET simulation under varying surface and climatic conditions. To address this issue, a revised Penman-Monteith (PM) formula that uses a non-linear exponential Clausius-Clapeyron relationship was proposed in this study. The improved PM formula was further coupled into the loss function of the deep learning (DL) model, and subsequently, a hybrid DL model was formulated. The hybrid DL model with improved physical conceptualization considered the constraints of surface energy balance and turbulent diffusion processes in the ET simulation. The performance of the hybrid DL model was verified at 212 flux sites from the FLUXNET that contain ten types of underlying surfaces across the globe. The results revealed that as compared to the original DL model, the hybrid DL model improved the predictive capability of ET. The average root-mean-square-error (RMSE) and mean absolute percentage difference (MAPD) reduced by 12.1 W/m2 and 5.7%, respectively for latent heat flux (LE) simulation. Furthermore, the hybrid DL model also performed better than the original DL model in predicting the extreme events (such as ET under drought and heatwave conditions) which justifying its improved generalization capability. Sensitivity analysis outcomes showed that the vegetation parameters highest influence for ET simulations at the 212 flux sites, followed by soil parameters and meteorological parameters. The hybrid DL model was further applied to map the inter-seasonal distribution of global ET across twelve months of the year 2015 with five global ET products as the benchmark. Certainly, this research achieved the seamless integration of machine learning-based ET model and physical mechanism-based ET model and provided a new dimension for ET simulation. The hybrid DL model could be adopted to generate continuous ET datasets across regional and global scales.

Model Identification and Control of Evapotranspiration for Irrigation Water Optimization

Water conservation starts from rationalizing irrigation, as it is the largest consumer of this vital source. Following the critical and urgent nature of this issue, several works have been proposed. The idea of most researchers is to develop irrigation management systems to meet the water needs of plants with optimal use of this resource. In fact, irrigation water requirement is only the amount of water that must be applied to compensate the evapotranspiration loss. Penman-Monteith equation is the most common formula to evaluate reference evapotranspiration, but it requires many factors that cannot be available in many cases. This leads to a trend towards behavior model estimation. System identification with control is one of the most promising applications in this axis. The idea behind this proposal depends on three stages: First, the estimation of reference evapotranspiration (ET0) by a linear ARX model, where temperature, relative humidity, insolation duration and wind speed are used as inputs, and ET0 estimated by Penman-Monteith equation as output. The results show that the values estimated by this method were in good agreement with the measured data. The second part of this paper is to manage the quantity of water. For this purpose, two controllers are used for testing, lead-lag and PID. To adjust the first controller and optimize the choice of its parameters, Nelder-Mead algorithm is used. In the last part, a comparative study is done between the two used controllers.

Daily reference evapotranspiration models in the rice zone of Valle del Cauca, Colombia

The opportune calculations of the daily reference evapotranspiration (ETo) quantify and schedule the use of the water availability and consequently determine a daily consumption, mostly in the conditions where the lack of climatic information interrupts the performance of diverse models to estimate the daily reference evapotranspiration in a certain region. Therefore, the objective of this work is to evaluate the behavior of the equations of Hargreaves-Samani, Priestley and Taylor, García and López, and Linacre in the calculation of daily reference evapotranspiration (ETo) for the equation of FAO Penman-Monteith (PM) using daily information from five stations near the rice production area of Valle del Cauca, Colombia. The daily evapotranspiration of 28 consecutive years was estimated, the results were confirmed by the statistical indicators: Determination Coefficient (R2); the square root of the mean square of the error (RMSE); Nash-Sutcliffe Efficiency (NSE), and box diagrams. The Priestley-Taylor (PT) and Linacre (LN) models have shown the closest results to the standard model. Bengala and Ciat Quilichao stations are shown as the areas with the best behavior of all the models with the coefficient of determination index (R2); all the stations presented acceptable results with the square root of the mean square of the error (RMSE) for the different comparisons made but not with the Nash-Sutcliffe Efficiency (Nash-Sutcliffe Efficiency). However, there is limited evidence of the daily use of the Garcia and Lopez model, being this method and that of the Hargreaves-Samani the least ideal for the Independence station.