Evapotranspiration Equations Research Articles

Dryland hydroclimatic response to large tropical volcanic eruptions during the last millennium

Drylands are highly vulnerable to climate change due to their fragile ecosystems and limited ability to adapt. In contrast to the global drying after tropical volcanic eruptions shown previously, we demonstrate that large tropical volcanic eruptions can induce significant two-year hydroclimatic wetting over drylands by employing the last millennium simulations. During this wetting period, which extends from the first to the third boreal winter after the eruption, several hydroclimatic indicators, such as self-calibrating Palmer Drought Severity Index based on the Penman-Monteith equation for potential evapotranspiration (scPDSIpm), standard precipitation evapotranspiration index (SPEI), aridity index (AI), top-10cm soil moisture (SM10cm), and leaf area index (LAI), show significant positive anomalies over most drylands. The primary contribution to the wetting response is the potential evapotranspiration (PET) reduction resulting from dryland surface cooling and reduced solar radiation, as well as a weak contribution from increased precipitation. The latter is due to the wind convergence into drylands caused by slower tropical cooling compared to drylands. The wetting response of drylands to volcanic eruptions also demonstrates some benefits over the global hydrological slowdown resulting from stratospheric aerosol injection, which replicates the cooling effects of volcanic eruptions to address global warming.

Temperature-based Evapotranspiration in the WSVI Drought Index Implementation

Drought is a natural hazard that affects environmental and socio-economic development. In this study, the Water Surplus Variability Index (WSVI), which is based on both precipitation and Penman-Monteith (PM) evapotranspiration (ET) estimates, was used to quantify drought. The application of the WSVI is not possible in some locations because of the missing data for estimating ET. The key objectives of this research were to 1. compare the different temperature-based WSVIs for the 1-, 3-, 6- and 12-month timescales with the original PM-based WSVI; 2. improve the WSVI by replacing the full-set PM equation with the corresponding temperature-based ET equation, such as Hargreaves, adjusted Hargreaves, Thornthwaite, modified Thornthwaite or temperature-based PM; and 3. compare the best temperature-based WSVI with the Standardized Precipitation Index (SPI). The set of meteorological data was obtained from several stations from Pannonian Basin (Budapest, Debrecen, Novi Sad and Sombor). According to statistical indicators, the Hargreaves-based WSVI (WSVIH) was ranked first or second for each time period at all locations. The WSVIH was additionally tested using the SPI for each location and each timescale. The obtained results indicated the capability of the WSVIH to quantify drought frequency, duration and severity identified by the SPI. Finally, the WSVI can be recommended using the Hargreaves equation instead of the full-set PM equation in future WSVI implementations in the Pannonian Basin.

Estimating crop water requirement in Madhya Pradesh's agro-climatic regions: A CROPWAT and CLIMWAT software case study

Estimating actual crop evapotranspiration is vital in water-scarce environment affected by climate change, particularly for optimizing irrigation and enhancing crop yield. This research focuses on assessing crop water and irrigation requirement for major crops across six districts of Madhya Pradesh, India, spanning diverse agro-climatic regions. Employing CLIMWAT 2.0 and CROPWAT 8.0 software, calculated crop evapotranspiration and devised irrigation strategies tailored to local climatic conditions. The FAO-Penman-Montieth (FAO-PM) equation for reference evapotranspiration (ET0), aiding in crop water requirement computation and irrigation planning. Our findings reveal substantial variations in crop water requirements across crops and districts. For instance, soybean in Indore requires the highest water input at 380 mm, while in Guna, was least at 303 mm. Wheat, on the other hand, register the highest water needs in Khandwa at 510.6 mm and the lowest in the Neemuch district at 370.8 mm, particularly during the rabi season. Besides that, this study underscores the need for district-specific considerations, taking into account climate and soil characteristics when formulating water management strategies. Employing efficient irrigation practices and techniques to manage water stress becomes imperative for optimizing crop yield and achieving economic returns. Implementing customized approaches to enhance water use efficiency and promote sustainability in agricultural production is crucial. These research outcomes provide valuable insights for policymakers, agricultural practitioners, and water resource managers to develop context-specific water management strategies.

Elementary effects for models with dimensional inputs of arbitrary type and range: Scaling and trajectory generation.

The Elementary Effects method is a global sensitivity analysis approach for identifying (un)important parameters in a model. However, it has almost exclusively been used where inputs are dimensionless and take values on [0, 1]. Here, we consider models with dimensional inputs, inputs taking values on arbitrary intervals or discrete inputs. In such cases scaling effects by a function of the input range is essential for correct ranking results. We propose two alternative dimensionless sensitivity indices by normalizing the scaled mean or median of absolute effects. Testing these indices with 9 trajectory generation methods on 4 test functions (including the Penman-Monteith equation for evapotranspiration) reveals that: i) scaled elementary effects are necessary to obtain correct parameter importance rankings; ii) small step-size methods typically produce more accurate rankings; iii) it is beneficial to compute and compare both sensitivity indices; and iv) spread and discrepancy of the simulation points are poor proxies for trajectory generation method performance.

The performance of SPEI integrated remote sensing data for monitoring agricultural drought in the North China Plain

Agricultural drought is significantly affecting sustainable crop production. One of climate-based drought indices, the Standardized Precipitation Evapotranspiration Index (SPEI) calculated by the difference between precipitation and potential evapotranspiration (PET), is being more and more widely employed to characterize the spatio-temporal pattern of agricultural drought. However, substantial uncertainties exist in the current PET methods due to unrealistic configurations of the heterogeneity of crop surface characteristics or complicated parameterization scheme. In this study, standard Penman–Monteith (PM) model is modified and derived by meteorological factors and leaf area index (LAI) and albedo data based on remote sensing. Then, the modified SPEI was calculated by the monthly difference between precipitation and PM model integrated remote sensing data (referred as PMRS) over the North China Plain (NCP) between 1982 and 2016. Comparing with the FAO56 reference evapotranspiration (referred as PMRC) and a simplified version of standard PM over open-water surface (referred as PMOW), this study examines how well the PMRS-SPEI captures drought evolution and impacts on crop growth and yield over the NCP in order to evaluate its performance in agricultural drought monitoring. The comparison of SPEIs based on three evapotranspiration equations with soil water moisture in root depth shows that a 6-month lag can be used as the optimum time scale over the NCP. Additionally, the correlation of PMRS-SPEI performs better than PMRC-SPEI and PMOW-SPEI. For typical drought events, PMRS-SPEI6 shows remarkable smaller (larger) severe drought values between April and June (August and October) and a shorter (longer) recovery period in the growing season for wheat (maize). Comparing to PMRC-SPEI6 and PMOW-SPEI6, the PMRS-SPEI6 shows better performance when examining the Vegetation Health Index and Composite Index of Crop Yield Reduction. Additionally, climate-induced crop yield correlates with PMRS-SPEI6 better than PMOW-SPEI6 and PMRC-SPEI6, particularly in the emergence and filling stages for winter wheat, and silking stage for summer maize. These results demonstrate that integrating remotely sensed data can enhance the agricultural drought monitoring accuracy of SPEI.

Alternative net longwave radiation equation for the FAO Penman–Monteith evapotranspiration equation and the Penman evaporation equation

Alternative net longwave radiation equation for the FAO Penman–Monteith evapotranspiration equation and the Penman evaporation equation

Comparison of the Performances of Pan-Based Equations to Estimate Reference Evapotranspiration (ETo) in Mediterranean Climate Conditions

Class A evaporation pan is often used to estimate reference evapotranspiration (ETo), considered one of the essential variables in water resource planning and irrigation scheduling. This study for Adana region conditions where the Mediterranean climate prevails aimed to compare the performances of the Snyder ETo (1995) and Ghare ETo (1996) equations which are pan-based approaches that do not require wind speed (U) and relative humidity (RH) data to estimate ETo, with the performance of the FAO24 Pan ETo equation. The FAO56-Penman–Monteith (PM) equation was used as a reference method to compare the performances of the equations. According to the research results, the Snyder ETo equation using only pan evaporation (epan) to estimate ETo has been the best equation on monthly and seasonal scales. The results showed that converting epan to reference evapotranspiration with the Snyder ETo equation can be used successfully in Adana region conditions.

A physically-based potential evapotranspiration model for global water availability projections

When the projections from the hydrological models conflict with those from the fully-coupled climate model, the vegetation appears to be responsible for the divergence. In the presence of an elevated concentration of atmospheric CO2 (Ca), the leaf-level stomatal conductance (gsl) tends to decrease thereby reducing water demand, and such effects can be partly offset by the increased leaf area (generally represented by leaf area index, LAI) simultaneously. Nonetheless, the impacts of vegetation are rarely explicitly quantified in existing potential evapotranspiration (EP) models. In this study, we proposed a new EP equation that combines a well-established gsl model with a simple bulk upscale model. The new model allows us to investigate the effects of elevated Ca-induced physiological and structural changes in vegetation on EP estimations. The results show that, compared to conventional EP models (e.g., the Penman-Monteith reference crop model), the new EP equation performs better in capturing long-term EP changes. Furthermore, we embedded the new EP equation in a simple hydrologic model, the Budyko framework, to estimate the changes in long-term runoff. By accounting for both physiological and structural responses of vegetation, estimated runoff by the Budyko framework shows a significant increase of ∼ 30 mm/year in 2071–2100 compared to 2006–2035, consistent with projections from fully-coupled climate models. The increase in LAI offset ∼ 30% of the water-saving caused by stomatal closure on a global average. The newly developed EP model provides a fully transparent and easy-to-use way for describing the impacts of climate change-induced vegetation responses on EP and can be effectively employed to detect long-term hydrological changes.

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.

Parametric calibration of Hargreaves–Samani (HS) reference evapotranspiration equation with different coefficient combinations under the humid environment

Evapotranspiration (ET) is a major hydrological component in irrigation system design, irrigation scheduling, and hydrologic and drainage design. Estimating crop ET requires accurate reference evapotranspiration (ET0) measurement. In this work, numerous modified Hargreaves models for ET0 were tested and calibrated against the standard FAO-56 Penman-Monteith eq. (F-56 PM) for further improvement in performance in the humid subtropical environment of Imphal West District, Manipur.The Martinez-Cob and Tejero-Juste (2004) equation resulted in best region-wide ET0 values of 3.536 mm d−1, mean absolute error (MAE) = 0.367 mm d−1, standard error of estimate (SEE) = 0.348 mm d−1, correlation coefficient (r) = 0.855, coefficient of determination (R2) =0.731, and index of agreement (d) = 0.891. Trajkovic (2007) equation has the second-best ET0 values of 3.383, MAE = 0.413 mm d−1, SEE = 0.3.77 mm d−1, r = 0.827, R2 = 0.685, and d = 0.852. The third-best equation, Ravazzani et al. (2012), with average ET0 values of 4.015 mm d−1, MAE = 0.506 mm d−1, SEE = 0.395 mm d−1, r = 0.855, R2 = 0.731, and d = 0.79.The observed wind speed data were sorted into five groups based on the average wind speed in different months in the region (1 m/s,2.5 m/s, 3.5 m/s, 4.5 m/s, and 5.5 m/s), and the estimated evapotranspiration was used to calibrate 14 selected combinations of the Hargreaves models. The calibration process significantly improved the performance of the different identified Hargreaves models.The analysis indicated that the improvement in estimation decreases with increasing wind speed. The revised coefficient predicted evapotranspiration is closer to F-56PM, with MAE (mm d−1) ranging from 0.125 at 1 m/s to 0.248 at 4.5 m/s and SEE(mm d−1) from 0.16 at 1 m/s to 0.245 at 5.5 m/s, as compared to the original Hargreaves equation, whose MAE is 0.543, and SEE is 0.400.More research must be conducted to extend the applicability of this equation to other regions of the State.

Evaluating the Performance of Calibrated Temperature-based Equations as Compared to Standard FAO-56 Penman Monteith Equation in Humid Climatic Condition of Dehradun (India)

The present study was undertaken to calibrate, validate, and evaluate the performance of temperature-based evapotranspiration equations in comparison to the standard FAO-56 Penman Monteith (FAO-56 PM) model in humid climatic condition of Dehradun district of Uttarakhand using 31-years (1989-2019) daily meteorological dataset. The quality control of dataset was ensured by omitting days with missing data and outliers. The performance of 12 calibrated temperature-based ETo equations namely, Allen (1993) [AL93], Baier and Robertson (1965) [BR65], Bogawski and Bednorz (2014) [BB14], Droogers and Allen (2002) [DA02], Dorji et al. (2016) [DO16], Hargreaves (1994) [HA94], Heydari and Heydari (2014) [HH14], Kharrufa (1985) [KA85], Ravazzani et al. (2012) [RA12], Samani (2004) [SA04], Schendel (1967) [SC67], and Trajkovic (2007) [TR07] were evaluated in comparison to standard FAO-56 PM model in terms of daily ETo estimates. The analysis showed that calibrated temperature-based equations performed well with higher value of agreement index (0.85-0.98) and reduced errors. The values of Root mean square error (RMSE), Mean bias error (MBE), Maximum absolute error (MAXE), Percent error of estimate (PE), and Standard error of estimate (SEE) for calibrated equations ranged from 0.29 to 1.15 mm.day-1, (-)0.39 to 0.53 mm.day-1, 0.64 to 3.95 mm.day-1, 4.71 to 19.11%, and 0.17 to 1.00 mm.day-1, respectively; whereas for original equations they varied in the range from 0.47 to 3.64 mm.day-1, (-)0.32 to 2.92 mm.day-1, 0.95 to 10.65 mm.day-1, 11.74 to 106.15%, and 0.18 to 1.72 mm.day-1, respectively, indicating improved performance of calibrated equations. The ranking of calibrated ETo equations on the basis of Global Performance Indicator (GPI) values confirmed that calibrated Dorji et al. (2016) equation produced best result, while Samani (2004) equation with its lowest value performed poorly. Based on GPI values, calibrated equations can be ranked (best to worst performing) as DO16> AL93> TR07> RA12> DA02> HA94> SC67> KH85> BR65> HH14>BB14> SA04. Thus, calibrated Dorji et al. (2016) equation can be used as substitute for FAO-56 PM model in the absence of large number of meteorological parameters for accurate estimation of ETo values in the study area.

Spatial Estimates of Soil Moisture for Understanding Ecological Potential and Risk: A Case Study for Arid and Semi-Arid Ecosystems

Soil temperature and moisture (soil-climate) affect plant growth and microbial metabolism, providing a mechanistic link between climate and growing conditions. However, spatially explicit soil-climate estimates that can inform management and research are lacking. We developed a framework to estimate spatiotemporal-varying soil moisture (monthly, annual, and seasonal) and temperature-moisture regimes as gridded surfaces by enhancing the Newhall simulation model. Importantly, our approach allows for the substitution of data and parameters, such as climate, snowmelt, soil properties, alternative potential evapotranspiration equations and air-soil temperature offsets. We applied the model across the western United States using monthly climate averages (1981–2010). The resulting data are intended to help improve conservation and habitat management, including but not limited to increasing the understanding of vegetation patterns (restoration effectiveness), the spread of invasive species and wildfire risk. The demonstrated modeled results had significant correlations with vegetation patterns—for example, soil moisture variables predicted sagebrush (R2 = 0.51), annual herbaceous plant cover (R2 = 0.687), exposed soil (R2 = 0.656) and fire occurrence (R2 = 0.343). Using our framework, we have the flexibility to assess dynamic climate conditions (historical, contemporary or projected) that could improve the knowledge of changing spatiotemporal biotic patterns and be applied to other geographic regions.

Evaluation of Five Equations for Short-Term Reference Evapotranspiration Forecasting Using Public Temperature Forecasts for North China Plain

Accurate short-term forecasts of daily reference evapotranspiration (ET0) are essential for real-time irrigation scheduling. Many models rely on current and historical temperature data to estimate daily ET0. However, easily accessible temperature forecasts are relatively less reported in short-term ET0 forecasting. Furthermore, the accuracy of ET0 forecasting from different models varies locally and also across regions. We used five temperature-dependent models to forecast daily ET0 for a 7-day horizon in the North China Plain (NCP): the McCloud (MC), Hargreaves-Samani (HS), Blaney-Criddle (BC), Thornthwaite (TH), and reduced-set Penman–Monteith (RPM) models. Daily meteorological data collected between 1 January 2000 and 31 December 2014 at 17 weather stations in NCP to calibrate and validate the five ET0 models against the ASCE Penman–Monteith (ASCE-PM). Forecast temperatures for up to 7 d ahead for 1 January 2015–19 June 2021 were input to the five calibrated models to forecast ET0. The performance of the five models improved for forecasts at all stations after calibration. The calibrated RPM is the preferred choice for forecasting ET0 in NCP. In descending order of preference, the remaining models were ranked as HS, TH, BC, and MC. Sensitivity analysis showed that a change in maximum temperature influenced the accuracy of ET0 forecasting by the five models, especially RPM, HS, and TH, more than other variables. Meanwhile, the calibrated RPM and HS equations were better than the other models, and thus, these two equations were recommended for short-term ET0 forecasting in NCP.

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.

Assessment of pan coefficient models for the estimation of the reference evapotranspiration in a Mediterranean environment in Turkey.

Reference evapotranspiration (ETo) is essential for irrigation practices and the management of water resources and plays a vital role in agricultural and hydro-meteorological studies. The FAO-56 Penman-Monteith (PM) equation, recommended as the sole standard method of calculating ETo by the Food and Agriculture Organization of the United Nations (FAO), is the most commonly used and accurate model to determine the ETo and evaluate ETo equations. However, it requires many meteorological variables, often restricting its applicability in regions with poor or missing meteorological observations. Many empirical and semi-empirical equations have been developed to predict the ET0 from numerous meteorological data. The FAO-24 Pan method is commonly used worldwide to estimate ETo because it is simple and requires only pan coefficients. However, pan coefficients (Kpan) should be determined accurately to estimate ET0 using the FAO-24 Pan method. As the accuracy and reliability of the Kpan models can be different from one location to another, they should be tested or calibrated for different climates and surrounding conditions. In this study, the performance of the eight Kpan models was evaluated using 22-year daily climate data for the summer growing season in Adana, which has a Mediterranean climate in Turkey. The results showed that the mean seasonal pan coefficients estimated by all Kpan models differed significantly at a 1% significance level from those observed by FAO-56 PM according to the two-tail z test. In the study, ETo values estimated by Kpan models were compared against those obtained by the FAO-56 PM equation. The seasonal and monthly performance of Kpan models was varied, and the Wahed & Snyder model presented the best performance for ETo estimates at the seasonal scale. (RMSE = 0.550 mm d−1; MAE = 0.425 mm d−1; MBE = −0.378 mm d−1; RE = 0.134). In addition, it showed a good performance in estimating ETo on a monthly scale. The Orang model showed the lowest performance in estimating ETo among all models, with a very high relative error on the seasonal scale. (RMSE = 1.867 mm d−1; MAE = 1.806 mm d−1; MBE = −1.806 mm d−1; RE = 0.455). In addition, it showed the poorest performance on a monthly scale. Hence, the Wahed & Snyder model can be considered to estimate ETo under Adana region conditions after doing the necessary calibration.

Climate change impacts on water security elements of Kafr El-Sheikh governorate, Egypt

Egypt faces great challenges to manage its limited freshwater resources. Shortage in freshwater, due to expected stresses of climatic changes and upper Nile projects, will have major impacts on Egypt's water and food security. About 85% of the annual total freshwater resource is consumed by agriculture. The objective of this work is to assess the future water security situation of Kafr El-Sheikh governorate, Nile Delta, Egypt, under climate change and urbanization stresses, compared to the current situation. Main investigated water security elements for this study were the irrigation water requirements and agricultural land areas. Two different reference evapotranspiration equations were used to calculate the future irrigation water requirements under three different Representative Concentration Pathways (RCP) (2.6, 4.5 and 8.5 scenarios) for the period 2010–2100, based on the intergovernmental panel on climate change’s 5th assessment report. Remote sensing and Geographical Information System (GIS) were used to generate a land use classification map, which was used to estimate the losses in each land use category of the study area under 0.5 and 1.0 m relative sea level rise (SLR) estimates. Combined scenarios of future changes in irrigation water consumption and agricultural land area were analysed. The results show that the future water security situation of the governorate is highly sensitive to projected climatic changes. Moreover, most future scenarios revealed that the agricultural land area would decrease, which will cause serious food security problems. The maximum decrease by about 55.9% of the agricultural land area for year 2095 compared to year 2016 is estimated, due to the current annual decreasing rate of 0.4% and 1.0 m SLR, whatever the applied RCP scenario. While the maximum increase in the required irrigation water would be about 6% due to the RCP85 scenario, assuming no change in the irrigation land area, with a mixing ratio of 1.34 (freshwater): 1 (drainage water) which would affect the crop yield productivity. A regular assessment of water security elements for each of the Egyptian governorates should be managed and an urgent integrated plan for food security to adapt with the future climate change impacts is essential.

Developing a method for integrating canopy measurements into evapotranspiration predictions

The availability of affordable instruments that measure surface radiative temperature and canopy cover have made it possible, in principle, to extend and improve existing methods of estimating potential evapotranspiration (ET) to predictions where assumptions of ‘full cover’ and ‘well-watered’ are violated. The aim of this study was to develop a model for ET whose input data requirements were not large, and would make use of surface temperature and cover measurements to predict ET in both potential and sub-potential conditions. A randomised experiment was conducted with two cultivars of barley (‘Dash’ and ‘Omaka’, erect and prostrate leaved, respectively) in combination with three irrigation treatments (High, Mid and Low) in a rain-out shelter. The treatments produced a wide range of surface temperature, cover and ET. Water fluxes in the soil were measured by methods sensitive enough to detect changes on the timescale of hours. Meteorological variables, short wave radiation albedo, ground heat flux density and surface temperature were logged on a sub-hour timescale. The Priestley and Taylor potential ET equation is modified and additional equations are derived to allow the inclusion of a crop coefficient to account for incomplete cover and to vary the alpha coefficient based on surface temperature to account for soil drying. Equations were also derived for estimating short-wave radiation, albedo and soil heat flux from canopy cover and meteorological variables. The resulting equations were able to quantify a wide range of ET values measured by detailed water balance in barley crops that often had incomplete canopy cover and encountered differing degrees of water stress. We conclude the approach presented has promise but requires broader testing. The successful integration of canopy measurements with an ET model will enable the production of ET maps which will have broad applications in research and irrigation management applications.

Forecasting evapotranspiration equation based on Hargreaves Evapotranspiration Method for Semangat Village, Merdeka Sub-district, Karo Regency, North Sumatera Province, Indonesia

Providing water according to plant water requirement is a problem faced by many farmers because it’s related to cost of production and water scarcity. Some methods of calculating evapotranspiration are very difficult for farmers to use because they require some meteorological data. Simplifying the use of calculation equation is needed to make it easier for farmers to determine plant water requirements. The aims of study were to forecast evapotranspiration equation based on Hargreaves Evapotranspiration Method for Semangat Village. The methods divided two steps, they were observing potential evapotranspiration using Hargreaves Evapotranspiration method, and forecasting evapotranspiration equation. The results show potential evapotranspiration (ETo) in Semangat Village were 2.9 – 7.1 mm/days during January until July, 2020. Forecasted evapotranspiration equation for Semangat Village y = 0.444x – 4.0964 with R2 = 0,435 for daily average temperature, y = 0.2265x – 1.9029 with R2 = 0.8518 for daily maximum temperature, and y = -0.2137x + 8.6148 with R2 = 0.1361 for minimum temperature. The conclusion shows that the formula y = 0.2265x – 1.9029 where x is daily maximum temperature is the best formula which can be used to forecast evapotranspiration in Semangat Village, Merdeka Sub-district, Karo Regency, North Sumatera Province, Indonesia.

Effect of local calibration on the performance of the Hargreaves reference crop evapotranspiration equation

Abstract Obtaining accurate estimates of reference crop evapotranspiration (ET0) using limited climatic inputs is essential in data-short situations where the preferred FAO-56 Penman–Monteith (PM) equation cannot be implemented. Among several available for ET0 estimation, the empirical temperature-based Hargreaves–Samani (HG) equation remains a popular alternative. However, accurate HG estimates can be obtained by local calibration and replacing the mean daily temperature with the effective daily temperature. Therefore, the present study was taken up to evaluate the effects of site-specific calibration of model parameters and the use of effective air temperature on the accuracy of ET0 estimates by the HG model. For this purpose, climate records for the historical period 2006–2016 of 67 stations located across 10 agro-climatic zones of Karnataka State, India, were used and the analysis was carried out using a monthly time step. Calibration and statistical performance evaluation was performed using FAO-56 PM ET0 estimates as a reference. Overall results showed significant improvement in HG estimates across all zones with the use of locally calibrated parameters, whereas the use of effective air temperature did not lead to any significant gain in prediction accuracies. The derived information on the spatial distribution of calibrated parameters will help obtain accurate ET0 estimates with only air temperature inputs.

Feasibility of using an energy balance to measure evapotranspiration in green stormwater infrastructure.

Effective green stormwater infrastructure (GSI) design requires comprehensive quantification of the volume of water that can be treated or removed over a given time period. It is recognized that evapotranspiration (ET) can be a substantial pathway for stormwater volume reduction in bioretention systems. However, measuring ET is often difficult and expensive, such as with lysimeters or a mass balance approach. This research focused on a new technique for quantifying ET in bioretention systems by exploring an approach using thermal imaging to calculate ET by measuring the flux of energy at the canopy surface. This thermal imaging approach was compared to ET measurements given by a traditional mass balance approach. The experimental setup had three benchtop scale vegetated lysimeters planted with Switchgrass. Time lapse thermal images of the Switchgrass plants were taken at 10 second intervals and paired with meteorological data. The data were used in an energy balance to estimate the mass of water lost from the lysimeter plant/soil system. That mass was compared to the change in weight measured by weighing the lysimeter before and after the data collection period. For comparison, reference ET was also calculated for the vegetated systems using three common reference ET equations. The uncalibrated energy balance equation developed here estimated an averaged ET over 12 data collection days within 1 mm of the mass balance measured ET. These findings demonstrate the feasibility of using a thermal image energy balance technique to estimate ET.