Penman-Monteith Reference Evapotranspiration Research Articles

Daily and seasonal changes of sap flow in Gamhong apple cultivar and estimate the tree-level transpiration using Penman-Monteith reference evapotranspiration

Understanding the environmental drivers and hydraulic dynamics of plants is pivotal for elucidating future water use strategies and refining precise irrigation techniques. In our investigation, we focused on the daily and seasonal fluctuations in sap flow (SF) using compensation heat-pulse techniques on 7-year-old 'Gamhong' apple trees. Predictions of stand transpiration were integrated using the Penman-Monteith grass reference evapotranspiration. Additionally, we measured leaf-level diurnal and seasonal stomatal conductance (gs), leaf water potential (ΨLeaf), and transpiration rate (E) to explore the relationship between plant-level transpiration and orchard microclimate. Diurnal SF exhibited a pattern similar to global radiation (Rg) and vapor pressure deficit (VPD), increasing in the morning with a peak in the afternoon and decreasing towards evening. Seasonal water use varied, with rates of 10.62 ± 0.282 L day-1 in early (May–June), 8.40 ± 0.222 L day-1 in mid- (July–August), and 5.96 ± 0.154 L day-1 in late season (September–October). Plant water consumption was influenced by weather conditions and evaporative demand driven by atmospheric VPD and Rg. Clear and sunny days resulted in higher water use (10.23 ± 0.291 L day-1) compared to partially sunny but windy days (9.85 ± 0.32 L day-1) and cloudy/rainy days (5.37 ± 0.176 L day-1). Plant transpiration strongly correlated with VPD (R² = 0.565), Rg (R² = 0.616), relative humidity (R² = 0.623), and wind velocity (u, R² = 0.684), while no significant correlation was observed with air temperature (Ta, R² = 0.19) or soil moisture status (Ψsoil, R² = 0.19). VPD and Rg emerged as the primary drivers, with Ψsoil playing a minor role and not limiting tree-level transpiration. Leaf-level gs, ΨLeaf, and E displayed similar diurnal trends. In our study, the integrated daily sap flow provided valuable insights into plant-water relations differently across growing seasons and its relationship with reference evapotranspiration (Eo). The Penman–Monteith equation, using grass reference evapotranspiration indicated a positive correlation (R² = 0.764, P < 0.001) between actual and estimated transpiration. However, the slope of the relationship differed significantly from 1.0, suggesting that Eo per unit leaf area of grass corresponds to E288 = Eo/2.88 (L m-2 of leaf area d-1), which underestimated evapotranspiration.

Effect of vegetation treatment and water stress on evapotranspiration in bioretention systems

Evapotranspiration is a key hydrological process for reducing stormwater runoff in bioretention systems, regardless of their physical configuration. Understanding the volumes of stormwater that can be returned to the atmosphere via evapotranspiration is, therefore, a key consideration in the design of any bioretention system. This study establishes the evapotranspiration dynamics of three common, structurally different, bioretention vegetation treatments (an Amenity Grass mix, and mono-cultures of Deschampsia cespitosa and Iris sibirica) compared with an un-vegetated control using lab-scale column experiments. Via continuous mass and moisture loss data, observed evapotranspiration rates were compared with those predicted by the FAO-56 Penman–Monteith model for five 14-day dry periods during Spring 2021, Summer 2021, and Spring 2022. Soil moisture reductions over the 14-day trials led to reduced rates of evapotranspiration. This necessitated the use of a soil moisture extraction function alongside a crop coefficient to represent actual evapotranspiration from FAO-56 Penman–Monteith reference evapotranspiration estimates. Crop coefficients (Kc) varied between 0.65 and 2.91, with a value of 1.0 identified as a recommended default value in the absence of treatment-specific empirical data. A continuous hydrological model with Kc=1.0 and a loading ratio of 10:1 showed that evapotranspiration could account for between 1 and 12% of the annual water budget for a bioretention system located in the UK and Ireland, increasing to a maximum of 35% when using the highest Kc observed (2.91).

Global Sensitivity of Penman–Monteith Reference Evapotranspiration to Climatic Variables in Mato Grosso, Brazil

Understanding how climatic variables impact the reference evapotranspiration (ETo) is essential for water resource management, especially considering potential fluctuations due to climate change. Therefore, we used the Sobol’ method to analyze the spatiotemporal variations of Penman–Monteith ETo sensitivity to the climatic variables: downward solar radiation, relative humidity, maximum and minimum air temperature, and wind speed. The Sobol’ indices variances were estimated by Monte Carlo integration, with sample limits set to the 2.5th and 97.5th percentiles of the daily data of 33 automatic weather stations located in the state of Mato Grosso, Brazil. The results of the Sobol’ analysis indicate considerable spatiotemporal variations in the sensitivity of ETo to climatic variables and their interactions. The dominant climatic variable responsible for ETo fluctuations in Mato Grosso is incident solar radiation (53% to 93% of annual total sensitivity—Stot), which has a more significant impact in humid environments (70% to 90% of Stot), as observed in the areas of the Amazon biome in the state. Air relative humidity and wind speed have higher sensitivity indices during the dry season in the Cerrado biome (savanna) areas in Mato Grosso (20% and 30% of the Stot, respectively). Our findings show that changes in solar radiation, relative humidity, and wind speed are the main driving forces that impact the reference evapotranspiration.

Influence of synoptic weather conditions on atmometers on the Delmarva Peninsula, USA

Reference evapotranspiration data from atmometers at three locations on the Delmarva Peninsula (USA) were compared to Penman-Monteith reference evapotranspiration (ETo) data across two growing seasons. Atmometer reference evapotranspiration (ETa) was found to underestimate ETo by 22.8% in 2016 and 30.4% in 2017. Stepwise linear regression was used to examine the relationship between both ET datasets and local meteorological conditions measured by Delaware Environmental Observing System (DEOS) mesonet stations that were co-located with the atmometers. Variability of ETa and ETo are well explained (R2 equal to 0.890 and 0.956, respectively) by a combination of meteorological variables, though the R2 in 2017 (R2 = 0.754) was notably lower than in 2016 (R2 = 0.890). The ET datasets were further examined by partitioning the data into days with similar synoptic conditions using a temporal synoptic index (TSI). Using the TSI results, three dominant synoptic categories were defined during the study period: High Pressure (HP), Southwest Flow (SW), and Cold Fronts (CF). Overall, the similarity between ETa and ETo was greatest on HP days, followed by CF and SW days. This relationship was primarily driven by wind speed, which had the greatest influence on ETa-ETo differences under all synoptic weather patterns. The 2016 growing season consisted of more days with synoptic conditions that are associated with smaller ETa -ETo differences than the 2017 growing season. Thus, changes in synoptic category frequency impact the nature of the ETa-ETo relationship from season to season. This study improves upon previous atmometer comparison studies by associating atmometer correction factors with synoptic weather patterns and descriptions in order to improve the utility of atmometers and remove the need for expensive meteorological equipment to correct atmometer data.

Sensitivity of the Penman–Monteith Reference Evapotranspiration Equation to Meteorological Variables for Puerto Rico

Spatiotemporal variations in reference evapotranspiration (ETo) are sensitive to the meteorological data used in its estimation. The sensitivity of the ASCE standardized ETo equation to meteorological variables from GOES-PRWEB dataset was evaluated for the island of Puerto Rico. Island wide, ETo is most sensitive to daily mean relative humidity (RHmean), followed by solar radiation, daily maximum (Tmax) and minimum (Tmin) air temperatures, and wind speed with average absolute relative sensitivity coefficients (SCs) of 0.98, 0.57, 0.50, 0.27, and 0.12, respectively. The derived SCs guided the prioritization of bias correction of meteorological data for ETo estimation from two downscaled climate models (CNRM and CESM). The SCs were applied to evaluate how meteorological variables contribute to model errors and projected future changes in ETo from 1985–2005 to 2040–2060 at irrigated farms in the south. Both models project a 5.6% average increase in annual ETo due to projected increases in Tmax and Tmin and a decrease in RHmean. Despite ETo being most sensitive to relative changes in RHmean, the contributions from RHmean, Tmax, and Tmin to future changes in ETo are similar. CESM projects increases in ETo in March, November, and December, increasing the potential for crop water stress. Study limitations are discussed.

Estimation of corn coefficients with vegetation indices using multispectral camera and drone

Optimum irrigation scheduling and new technologies are the key to the successful practice of modern agriculture and natural resources, such as water management. Α three-year research project was conducted at Velestino, Magnesia, Greece. The aim was to study whether vegetation indices can be used to estimate the crop coefficients of corn in order to apply an intelligent method of irrigation using drones in the future. The normalised difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI), the renormalised difference vegetation index (RDVI) and a new index [difference infrared – green vegetation index (DIGVI)] were calculated using multispectral photos from a camera adapted to a drone. Three different methods were applied to calculate the crop coefficients: (i) the water balance and the FAO Penman-Monteith reference evapotranspiration, (ii) the climatic data, (iii) the vegetation indices. The irrigation dose covered 100% of the crop water needs according to the soil moisture measurements and the single crop coefficient values. The statistical analysis and the simple linear regression method showed that the corn crop coefficients can be estimated when these indices are used as independent variables.

Version 3 of the Global Aridity Index and Potential Evapotranspiration Database

The “Global Aridity Index and Potential Evapotranspiration Database - Version 3” (Global-AI_PET_v3) provides high-resolution (30 arc-seconds) global hydro-climatic data averaged (1970–2000) monthly and yearly, based upon the FAO Penman-Monteith Reference Evapotranspiration (ET0) equation. An overview of the methods used to implement the Penman-Monteith equation geospatially and a technical evaluation of the results is provided. Results were compared for technical validation with weather station data from the FAO “CLIMWAT 2.0 for CROPWAT” (ET0: r2 = 0.85; AI: r2 = 0.90) and the U.K. “Climate Research Unit: Time Series v 4.04” (ET0: r2 = 0.89; AI: r2 = 0.83), while showing significant differences to an earlier version of the database. The current version of the Global-AI_PET_v3 supersedes previous versions, showing a higher correlation to real world weather station data. Developed using the generally agreed upon standard methodology for estimation of reference ET0, this database and notably, the accompanying source code, provide a robust tool for a variety of scientific applications in an era of rapidly changing climatic conditions.

PISCOeo_pm, a reference evapotranspiration gridded database based on FAO Penman-Monteith in Peru

A new FAO Penman-Monteith reference evapotranspiration gridded dataset is introduced, called PISCOeo_pm. PISCOeo_pm has been developed for the 1981–2016 period at ~1 km (0.01°) spatial resolution for the entire continental Peruvian territory. The framework for the development of PISCOeo_pm is based on previously generated gridded data of meteorological subvariables such as air temperature (maximum and minimum), sunshine duration, dew point temperature, and wind speed. Different steps, i.e., (i) quality control, (ii) gap-filling, (iii) homogenization, and (iv) spatial interpolation, were applied to the subvariables. Based on the results of an independent validation, on average, PISCOeo_pm exhibits better precision than three existing gridded products (CRU_TS, TerraClimate, and ERA5-Land) because it presents a predictive capacity above the average observed using daily and monthly data and has a higher spatial resolution. Therefore, PISCOeo_pm is useful for better understanding the terrestrial water and energy balances in Peru as well as for its application in fields such as climatology, hydrology, and agronomy, among others.

Determination of crop-coefficients and estimation of evapotranspiration of rapeseed using lysimeter and different reference evapotranspiration models

&#x0D; Accurate estimation of evapotranspiration of rapeseed is essentially required for irrigation scheduling and water management. The present study was undertaken during 2015-16 and 2017-18 in ICR Farm, Assam Agricultural University, Jorhat to determine the crop coefficients (Kc) and estimate evapotranspiration of rapeseed using lysimeter and eight reference evapotranspiration models viz. Penman-Monteith, Advection-Aridity (Bruitsaert-Strickler), Granger-Gray, Makkink, Blaney-Criddle, Turc (1961), Hargreaves-Somani and Priestly-Tailor models. During 2015-16, the crop coefficients were developed by these models. Actual evapotranspiration was determined by three weighing type lysimeters. During 2017-18, evapotranspiration was estimated by multiplying reference evapotranspiration with Kc derived by different models and compared with actual evapotranspiration estimated by lysimeter during similar growing periods. All the models except Turc (1961) showed less than 10% deviation between actual and estimated ET. The estimated evapotranspiration using Penman-Monteith and Priestly-Tailor reference evapotranspiration recorded the lowest MAE and RMSE. The study revealed that estimated evapotranspiration using Penman-Monteith reference evapotranspiration gave the best estimate of evapotranspiration of rapeseed followed by Priestly-Tailor. The crop coefficients for initial, mid and end stages were 0.83, 1.20 and 0.65, respectively for Penman-Monteith and 0.70, 1.05 and 0.55, respectively for Priestly-Tailor.These results can be used for efficient management of irrigation water for rapeseed.&#x0D;

Changes in the reference evapotranspiration and contributions of climate factors over the Indo–China Peninsula during 1961–2017

AbstractGiven the key roles of the Indo–China Peninsula (ICP) in weather and climate systems, hydrometeorology, and ecology, the annual and monthly changes in the Food and Agriculture Organization‐56 Penman–Monteith reference evapotranspiration (ET0), which was calculated based on the Climatic Research Unit datasets, were investigated in ICP during 1961–2017. The annual ICP ET0 significantly (p &lt; .05) increased, with different increasing tendencies in most months. In particular, larger and more significant (p &lt; .05) ET0 values were found during October–December. The annual and monthly ET0 changes showed evident spatial differences, characterized by increases in more than 50% of the ICP area except for decreases in around 70% of that area during March–May. A sensitivity experiment‐based separation method was utilized to evaluate the contribution of each influential factor, and the corresponding determinants were identified by comparing the contributions. Results showed that the annual ICP ET0 increase was attributed to the increased vapour pressure deficit (Vpd). However, the annual determinants varied spatially, with net solar radiation (Rn) in the southern region of ICP, wind speed (Wnd) in the northeast, and Vpd in the remaining regions. The monthly ICP determinant was Wnd in January, March–May and December, and Vpd for the remaining months. Despite different spatial patterns of monthly dominants, Vpd and Wnd were the determinants with the most extensive distributions over ICP (&gt;75% of ICP in total). The results of this study can significantly fulfil the research gap regarding the ICP ET0 changes and the underlying mechanisms. Meanwhile, this study provides fundamental and necessary information for protecting biodiversity and understanding hydrometeorological extreme events, thus promoting specific measures to sustain the ICP development.

Elevation‐dependent changes in reference evapotranspiration due to climate change

AbstractThe Food and Agriculture Organizations' (FAO) Penman–Monteith reference evapotranspiration (ET0) is a crucial index in the research of water and energy balance. Temporal and spatial variations in ET0 from 1981–2017 were investigated in the Hengduan Mountains, China. The results showed a change point around the year 2000 in ET0 series. ET0 decreased and increased significantly by +3.200 mm/year (p &lt; 0.01) from 1981–2000 and by +4.109 mm/year (p &lt; 0.01) from 2001–2017, respectively. The contribution analysis shows that the positive significant contribution of air temperature (TA) was offset by negative effects of decreases in downward shortwave radiation (Rs) and wind speed (WS) and an increase in actual vapour pressure (ea), causing the decrease in ET0 from 1981 to 2000. WS was the largest contributing factor for the decrease in ET0 from 1981 to 2000 during spring, winter and annually, while Rs and ea were the largest negative contributors in summer and autumn, respectively. An increase in TA was responsible for the increase in ET0 in all seasons except winter and the annual scale in 2001–2017. The sensitivity analysis shows that ET0 was most sensitive to TA, and WS was the least sensitive variable. The trends of ET0 increased with elevation; we denote this as the elevation‐dependence of ET0 changes. The elevation‐dependence was also noted for the trends of WS and ea, with higher elevations showing larger changes in WS and lower changes in ea. Besides, the sensitivities of TA, Rs and ea decreased with elevation, while that of WS increased slightly with elevation. A comprehensive investigation into the trends of climatic drivers and their sensitivities revealed complex trends of the contributions of climatic variables on ET0 with elevation, with no uniform trend existed in seasons. The results will contribute to our understanding of the response of ET0 to climate change in a mountainous area, and provide a guideline for the water resources management under climate change.

Reference evapotranspiration estimating based on optimal input combination and hybrid artificial intelligent model: Hybridization of artificial neural network with grey wolf optimizer algorithm

Reference Evapotranspiration (ETo) is one of the key components of the hydrological cycle that is effective in water resources planning, irrigation and agricultural management and, other hydrological processes. Accurate estimation of ETo is valuable for various applications of water resource engineering, especially in developing countries such as Iran, which has no advanced meteorological stations and lacks facilities and information. Also, due to the existence of different climates in Iran, the estimate of ETo has become a challenge. To this end, the aim of this study is to estimate the ETo to eliminate the two limitations of the absence of a comprehensive model for all climates and the scarcity of meteorological information in Iran. The present study investigates the ability of the hybrid artificial neural network- Gray Wolf Optimization (ANN-GWO) model to estimate ETo for Iran. The accuracy of ANN-GWO was evaluated versus least square support vector regression (LS-SVR) and standalone ANN. The development of models is based on meteorological data of Iran’s 31 provinces consists of 5 different climates. Based on empirical equations and least inputs, seven different input scenarios were introduced and Penman-Monteith reference evapotranspiration was considered as the output of the models. Several statistical indicators including SI, MAE, U95, R2, Global Performance Indicator (GPI), and Taylor diagram were used to evaluate the performance of the models. The results showed that the GWO algorithm acted as an efficient tool in optimizing the structure of the ANN and the ANN-GWO model was more accurate than ANN and LS-SVR in all scenarios. ANN-GWO6 with inputs of wind speed, maximum and minimum temperatures, had the lowest error and decreased in terms of SI index by 42% (compared to ANN6) and 30% (compared to LS-SVR6). Furthermore, based on GPI, it is in the first place with a 99% reduction, compared to ANN6 and LS-SVR6. The hybrid approach used in this study can be developed as a trustful expert intelligent system for estimating ETo in Iran.

Sensitivity of FAO Penman–Monteith reference evapotranspiration (ETo) to climatic variables under different climate types in Nigeria

AbstractUnderstanding the impact of changes in climatic variables on reference evapotranspiration (ETo) is important for predicting possible implications of climate change on the overall hydrology of an area. This study aimed to determine the effects of changes in ETo with respect to changes in climatic variables. In addition, the specific objective was to determine the sensitivity coefficients of ETo in seven different locations in Nigeria with distinct agroecology, namely Maiduguri (Sahel savannah), Sokoto (Sudan savannah), Kaduna (Guinea savannah), Jos (Montane), Enugu (Derived Savannah), Ibadan (tropical rainforest), and Port Harcourt (coastal). The results showed that ETo is most sensitive to changes in maximum temperature (Tmax) in Maiduguri, Sokoto, Kaduna, and Jos. In Enugu and Ibadan, ETo is most sensitive to changes in solar radiation (Rs), while in Port Harcourt, ETo is most sensitive to relative humidity (RH). Overall, based on the average annual sensitivity coefficients (SCs) of the study area, the SC is ranked in the order: RH &amp;gt; Rs &amp;gt; Tmax &amp;gt; U2 &amp;gt; Tmin. Also, the results showed positive SCs of ETo to Rs, Tmax, U2, Tmin, and negative SC for RH. This study can serve as a baseline for sustainable water management in the context of climate change and adapted to areas with a similar climate.

Evaluation of temperature-based solar radiation models and their impact on penman-monteith reference evapotranspiration in a semiarid climate

Solar radiation is one of the most important climatic parameters that is involved in different environmental, hydrological, agricultural applications while not always measured at all weather stations due to the high equipment and maintenance cost. The objectives of this study were to evaluate the performance and accuracy of twenty temperature based solar radiation models at five weather stations (Alcalde, Fabian Garcia, Farmington, Leyendecker and Tucumcari) in New Mexico and to evaluate the impact of solar radiation prediction on the Penman-Monteith grass reference evapotranspiration (ETo) for the global period of 2009-2017. New constants of each model at each weather station were retrieved using the optimization procedure Solver in Excel that maximizes the Kling-Gupta Efficiency (KGE). The root mean squared error (RMSE), mean absolute error (MAE), mean bias error (MBE) and the Nash-Sutcliffe model efficiency coefficient (NSE) were used for model performance evaluation. The results showed that the Hargreaves and Samani (1982), improved by Allen 1995, Bristow-Campbell (1984), Hunt et al. (1998), Fan et al. (2018), Hassan et al. (2016), Samani (2000); Nage et al. (2018) 2 and the Richardson et al (2018) models were the most accurate and the best performing ones across all five research sites. The EL-Sabaii, Ert Yal and Clemence models showed the poorest performance at all five stations. The evaluation of the impact of the predicted solar radiation on the Penman-Monteith ETo showed that predicted solar radiation had non-significant effect of the daily ETo with a regression slope varying from 0.978 to 1.022, RMSE from 0.24 to 0.48 mm/day, MAE from 0.15 to 0.31 mm/day and MBE from -0.03 to 0.09 mm/day. All solar radiation models showed best performance at Farmington and Tucumcari while they registered the poorest performance at Alcalde. The Student T-test revealed non-significant differences between the daily ETo using the measured solar radiation data set and the predicted solar radiation by each of the twenty solar radiation models at each weather station. The new models developed in this study could be used to estimate daily solar radiation across the semiarid environment of New Mexico for satisfactory estimation of ETo.

Computation of daily Penman–Monteith reference evapotranspiration in the Carpathian Region and comparison with Thornthwaite estimates

Abstract. The Pannonian Basin Experiment (PannEx) is a Regional Hydroclimate Project (RHP) of the World Climate Research Programme (WCRP) Global Energy and Water Exchanges (GEWEX) Project. A gridded meteorological dataset is available for the PannEx region as part of the CarpatClim database, which consists of homogenized and harmonized daily meteorological observations for several climate parameters with 0.1∘ spatial resolution in the period of 1961–2010. The estimation of the Penman–Monteith reference evapotranspiration (ET0) on the daily scale was performed for the CarpatClim grid as one of the first results in the PannEx initiative. This study compares the already accessible Thornthwaite estimates of potential evapotranspiration (PET_Th) on the monthly scale to the newly derived Penman–Monteith estimates. The comparison is made on an annual and seasonal basis for the 50-year period. The distribution of both estimates is influenced by geographical location and orographic features. The annual time series are similar but the regional-average annual values of ET0 are ∼80 mm greater than the Thornthwaite estimate in the whole CarpatClim region. The relative bias and root mean square error was computed as well. The classical Thornthwaite method underestimates the ET0 by more than 20 % over extensive regions for selected grid points at elevations lower than 200 m in the Pannonian Basin. The slope of the fitted linear trend indicate increasing reference evapotranspiration in the Pannonian/Carpathian Basin due to climate change.

Determining Reference Evapotranspiration in Greenhouses from External Climate

AbstractEstimations of Penman-Monteith reference evapotranspiration (EToPM) in greenhouses can benefit the operation of these intensive agricultural production systems. Meteorological variables req...

Forcing the Penman-Montheith Formulation with Humidity, Radiation, and Wind Speed Taken from Reanalyses, for Hydrologic Modeling

The Penman-Monteith reference evapotranspiration (ET0) formulation was forced with humidity, radiation, and wind speed (HRW) fields simulated by four reanalyses in order to simulate hydrologic processes over six mid-sized nivo-pluvial watersheds in southern Quebec, Canada. The resulting simulated hydrologic response is comparable to an empirical ET0 formulation based exclusively on air temperature. However, Penman-Montheith provides a sounder representation of the existing relations between evapotranspiration fluctuations and climate drivers. Correcting HRW fields significantly improves the hydrologic bias over the pluvial period (June to November). The latter did not translate into an increase of the hydrologic performance according to the Kling-Gupta Efficiency (KGE) metric. The suggested approach allows for the implementation of physically-based ET0 formulations where HRW observations are insufficient for the calibration and validation of hydrologic models and a potential reinforcement of the confidence affecting the projection of low flow regimes and water availability.

Evaluation of the Penman–Monteith reference evapotranspiration under limited data and its sensitivity to key climatic variables under humid and semiarid conditions

The objectives of this study were to assess the accuracy of FAO Penman Monteith equation (FAO PM) under limited data conditions and to perform sensitivity analysis to determine approximately the change in reference evapotranspiration (ETref) expected for a known change in one of the independent variables and derive the sensitivity coefficient. Meteorological data were collected from 8 weather stations under humid and semiarid condition in Cote d’Ivoire. The results showed good performance of FAO PM equation under missing solar radiation (Rs) in semiarid condition and under missing wind speed data (U2) and relative humidity (RH) in all locations with coefficient of determination (R2) ranging from 0.70 to 0.99 and regression slope from 0.99 to 1.05. Under missing Rs, RMSE varied from 0.45 to 0.48 mm/day and AME from 0.30 to 0.35 mm/day. The RMSE and AME vary respectively from 0.12 to 0.51 mm/day and from 0.09 to 0.30 mm/day under missing RH data, and respectively from 0.11 to 0.60 mm/day and 0.04 to 0.34 mm/day under missing wind speed data. The poor performance of FAO PM method to estimate ETo was observed when three climatic variables were missing with regression slope from 0.93 to 1.06 and R2 from − 0.06 to 0.26. The response of ETo to changes in all climate variables was linear, with high R2 values (≥ 0.99) in most cases. Any error in Rs, maximum temperature (Tmax) data would have contributed to significant change in ETo estimate. The effect of Rs on change in ETo estimates had the greatest slope (≥ 2.80) in Bouake, Daloa, Korhogo, Man, Seguela whereas it had the lowest slope in Ferkessedougou (slope = 2.74), Odienne (slope = 2.73), Yamoussoukro (slope = 2.77). The effect of Tmax in change in ETo was also important in all location except Daloa and Man with low regression slope values of 1.63, 1.74, respectively. All sensitivity coefficients showed a large degree of daily and seasonal fluctuations and revealed significant differences in northern and central study locations. The sensitivity coefficients of U2 and Tmax were greatest under semiarid condition while the one of Rs were very high in humid condition. Accurate measuring of U2, Tmax and Rs in estimating reference evapotranspiration using Penman–Monteith equation is required.

Reference evapotranspiration prediction using hybridized fuzzy model with firefly algorithm: Regional case study in Burkina Faso

Reference Evapotranspiration (ETo) is one of the major components of the hydrological cycle that is very essential in water resources planning, irrigation and drainage management and several other hydrology processes. In irrigation system and design, the prediction of ETo is vital and indispensable for the quantification of crop water needs. This study investigates the capabilities of hybridized fuzzy model with firefly algorithm (ANFIS-FA) for predicting daily reference evapotranspiration over Burkina Faso region. Metrological information at Bobo Dioulasso, Bur Dedougou, and Ouahigouya stations, in Sahelian, Sudano-Sahelian, and Sudanian zone, are used for modelling development. Six different climatic input variable combinations corresponding to 6 models are inspected. The daily Penman-Monteith reference evapotranspiration for the time-period (1998–2012) are used to train and test the models. Several numerical indicators in addition to Taylor diagram are considered to evaluate the performance of the models. Results indicated that the hybrid ANFIS-FA model outperformed the classical ANFIS-based model for all three stations and the model with full inputs climatic data gave the best results. Furthermore, ANFIS-FA is performed the best for Bur Dedougou (Sahalian-Soudanian region) and less at Ouahigouya (sahalian region). In quantitative terms and for instance Bur Dedougou station, ANFIS-FA model increased the prediction accuracy remarkably (SI = 0.043, R2 = 0.97, MAPE = 0.035 and RMSE = 0.24) compared with ANFIS-based model (SI = 0.068, R2 = 0.89, MAPE = 0.037 and RMSE = 0.378). Results revealed the influence of utilizing nature-inspired firefly algorithm to substantially improve performance of the classical ANFIS model optimization for the applied application. Also, the applied modelling strategy can bring a trustful expert intelligent system for predicting reference evapotranspiration at the west desert of Africa.

Influence of climate variables on FAO Penman–Monteith reference evapotranspiration in the Upper Chenab Canal command area of Pakistan

Examining the changing trends of climatic variables, along with their respective influences identified by conventional sensitivity analysis, could play a decisive role in distinguishing the prominent variables controlling evapotranspiration variations over time. The trends of climatic variables, their influences, and subsequent contributions to FAO Penman–Monteith reference evapotranspiration (ETo) were systematically analysed for the command area of the Upper Chenab Canal, Pakistan, from 1980 to 2012. The nonparametric Mann–Kendall test was employed for trend detection, and ETo sensitivity to climatic variables was quantified via sensitivity coefficients. A significant overall increase in maximum temperature (Tmax) and minimum temperature (Tmin), a significant decrease in sunshine hours (n) and net solar radiation (Rn), and a non-significant decrease in relative humidity (RH) and wind speed (u2) resulted in a slight decrease in ETo. ETo was highly sensitive to Rn, followed by Tmax, n, Tmin, RH, and u2. The highly influential Rn and the comparatively less influential n, Tmin, and u2 appeared to be the active factors controlling the ETo fluctuations. Rn and n contributed to downward trends in ETo in the study area, whereas u2 and Tmin contributed to upward trends. The contributions of Tmax, despite being the second-most influential variable, to ETo variations were not prominent. RH had negligible impact on ETo, as it was least influential and showed non-significant variations.