Modeling daily reference evapotranspiration in middle south Saurashtra region of India for monsoon season using most dominant meteorological  variables and the FAO-56 Penman-Monteith method

Many methods are available to estimate reference evapotranspiration (ETo) from standard meteorological observations. The FAO-56 Penman-Monteith method is considered to be the most physical and reliable method and is often used as a standard to verify other empirical methods. However, it needs a lot of different input parameters. Hence, in the present study, a model based on most dominant meteorological variables influencing ETo is proposed to estimate ETo in the Middle South Saurashtra region of Gujarat (India). The performance of five different alternative methods and proposed model is compared with the standard FAO-56 Penman-Monteith method. The five quantitative standard statistical performance evaluation measures, Nash-Sutcliffe efficiency coefficient (E), coefficient of determination (R2), refined Willmott’s index (dr), root mean square of errors-observations standard deviation ratio (RSR) and mean absolute error (MAE) are employed in evaluating the performance of the selected methods and proposed model. The results show that the developed model and Hargreaves and Samani (1985) method with recalibrated parameters provide the most reliable results in estimation of (ETo) and it can be recommended for estimating (ETo) in the study region.

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Reference evapotranspiration for Londrina, Paraná, Brazil: performance of different estimation methods

Semina Ciências Agrárias ◽

10.5433/1679-0359.2017v38n4supl1p2363 ◽

2017 ◽

Vol 38 (4Supl1) ◽

pp. 2363

Author(s):

Rodrigo Dlugosz da Silva ◽

Marcelo Augusto de Aguiar e Silva ◽

Marcelo Giovanetti Canteri ◽

Juliandra Rodrigues Rosisca ◽

Nilson Aparecido Vieira Junior

Keyword(s):

Reference Evapotranspiration ◽

Meteorological Data ◽

Global Radiation ◽

Alternative Methods ◽

Estimation Methods ◽

Performance Indices ◽

Excellent Performance ◽

Study Region ◽

Temperature Radiation ◽

And Performance

Aiming at assessing the performance of alternative methods to Penman-Monteith FAO56 for estimating the reference evapotranspiration (ETo) for Londrina, Paraná, Brazil, the methods temperature radiation, Hicks-Hess, Hargreaves-Samani (1982), Turc, Priestley-Taylor, Tanner-Pelton, Jensen-Haise, Makkink, modified Hargreaves, Stephens-Stewart, Abtew, global radiation, Ivanov, Lungeon, Hargreaves-Samani (1985), Benavides-Lopez, original Penman, Linacre, Blaney-Morin, Romanenko, Hargreaves (1974), McCloud, Camargo, Hamon, Kharrufa, McGuiness-Bordne, and Blaney-Criddle were compared to that standard method recommended by FAO. The estimations were correlated by linear regression and assessed by using the Person’s correlation coefficient (r), concordance index (d), and performance index (c) using a set of meteorological data of approximately 40 years. The methods modified Hargreaves, Stephens-Stewart, Abtew, global radiation, Ivanov, Lungeon, Hargreaves-Samani (1985), Benavides-Lopez, original Penman, and Linacre should be avoided, as they did not present excellent results. The methods McCloud, Camargo, Hamon, Kharrufa, McGuinness-Bordne, Blaney-Criddle, Hargreaves (1974), Romanenko, and Blaney-Morin were classified as very bad, not being recommended. In contrast, the methods temperature radiation, Hicks-Hess, Hargreaves-Samani (1982), Turc, Priestley-Taylor, Tenner-Pelton, Jensen-Haise, and Makkink presented excellent performance indices and can be applied in the study region.

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Reference evapotranspiration for Londrina, Paraná, Brazil: performance of different estimation methods

Semina Ciências Agrárias ◽

10.5433/1679-0359.2017v38n4suplp2363 ◽

2017 ◽

Vol 38 (4Supl1) ◽

pp. 2363

Author(s):

Rodrigo Dlugosz da Silva ◽

Marcelo Augusto de Aguiar e Silva ◽

Marcelo Giovanetti Canteri ◽

Juliandra Rodrigues Rosisca ◽

Nilson Aparecido Vieira Junior

Keyword(s):

Reference Evapotranspiration ◽

Meteorological Data ◽

Global Radiation ◽

Alternative Methods ◽

Estimation Methods ◽

Performance Indices ◽

Excellent Performance ◽

Study Region ◽

Temperature Radiation ◽

And Performance

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MÉTODOS DE ESTIMATIVA DA EVAPOTRANSPIRAÇÃO DE REFERÊNCIA (ET0) NO MUNICÍPIO DE SANTA TERESA, ES

Irriga ◽

10.15809/irriga.2017v22n4p701-714 ◽

2017 ◽

Vol 22 (4) ◽

pp. 701-714

Author(s):

Andre Dalla Bernardina Garcia ◽

José Carlos Mendonça ◽

Claudio De Almeida Martins

Keyword(s):

Water Resources ◽

Solar Radiation ◽

Reference Evapotranspiration ◽

Irrigation Management ◽

Absolute Error ◽

Estimation Methods ◽

Coefficient Of Determination ◽

Espírito Santo ◽

Espirito Santo ◽

E Mail

MÉTODOS DE ESTIMATIVA DA EVAPOTRANSPIRAÇÃO DE REFERÊNCIA (ET0) NO MUNICÍPIO DE SANTA TERESA, ES ANDRE DALLA BERNARDINA GARCIA1; JOSÉ CARLOS MENDONÇA2 E CLAUDIO MARTINS DE ALMEIDA3 1Instituto Federal do Espírito Santo, Rodovia ES 080, Km 93, São João de Petrópolis, CEP 29660-000, Santa Teresa, ES, Fone:(27)3259-7878, E-mail:[email protected]ório de Engenharia Agrícola/UENF, Av. Alberto Lamego, 2000,P1,sl 209, Horto, Campos dos Goytacazes, RJ, Fone (22) 2739-7308, E-mail: [email protected]ório de Engenharia Agrícola/UENF, Av. Alberto Lamego, 2000,P1,sl 209, Horto, Campos dos Goytacazes, RJ, Fone (22) 2739-7308, E-mail: [email protected] 1 RESUMO Devido aos constantes debates ocorridos sobre a racionalização dos recursos hídricos, a busca de maneiras e boas práticas de utilização da água têm sido cada vez mais difundidas, principalmente na agricultura. Dentre os meios de preservar os recursos hídricos está o manejo de irrigação, por isso é muito importante realizar a estimativa da evapotranspiração de referência (ET0). Neste contexto, o presente trabalho foi desenvolvido para o município de Santa Teresa, localizado na meso região Central Espírito-Santense com o objetivo de avaliar e comparar diferentes métodos de estimativa da ET0 com o método de Penman-Monteith FAO56, considerado como padrão de calibração, na ausência de dados lisimétricos. Os métodos utilizados foram os de Hargreaves-Samani, Radiação Solar, Makkink, Jesen-Haise, Linacre e Penman Simplificado. O coeficiente de determinação (R2), índice de concordância de Willmott (D), o erro médio absoluto (MAE), o erro máximo (EMAX), a eficiência do método (EF) e o índice de desempenho (c) foram utilizados para avaliar os indicadores observados. Dentre os métodos avaliados, os que apresentaram melhores resultados foram os de Makkink e Penman Simplificado (R2 = 0,96 e 0,96; D= 0,99 e 0,97; MAE = 0,23 e 0,44; EMAX = 1,36 e 1,07; EF = 0,95 e 0,87 e c = 0,97 e 0,95) respectivamente, seguidos do método de Hargreaves-Samani (R2 = 0,86; D= 0,91; MAE = 0,60; EMAX = 2,16; EF = 0,69 e c = 0,85). Os resultados obtidos com os métodos de Linacre, Radiação Solar e Jensen-Haise foram inferiores e sendo a sua utilização não recomendada para a região de Santa Teresa, ES. Palavras-chave: Agrometeorologia, demanda hídrica, irrigação, Penman-Monteith GARCIA, A. D. B.; MENDONÇA, J. C.; MARTINS, C. A.METHODS FOR ESTIMATING REFERENCE EVAPOTRANSPIRATION (ET0) FOR THE CITY OF SANTA TERESA, ES 2 ABSTRACT Due to constant discussion about rationalization of water resources, the search for ways and good practices in water use have been increasingly widespread, especially in agriculture. Among the means of preserving water resources is irrigation management, so it is very important to estimate the reference evapotranspiration (ET0). In this context, the present work was developed for the municipality of Santa Teresa, located in Central Espírito-Santo mesoregion with the objective of evaluating and comparing different ET0 estimation methods with Penman-Monteith FAO56 method considered as calibration standard, in the absence of lysimetric data. The methods used were those of Hargreaves-Samani, Solar Radiation, Makkink, Jesen-Haise, Linacre and Penman Simplified. The coefficient of determination (R2), Willmott concordance index (D), mean absolute error (MAE), maximum error (EMAX), method efficiency (EF) and performance index (c) were used for assessing the observed indicators. Among the evaluated methods, the ones with the best results were Makkink and Penman Simplified (R² = 0.96 and 0.96 D = 0.99 and 0.97, MAE = 0.23 and 0.44, EMAX = 1.36 and 1.07, EF = .95 and 0.87 and c = 0.97 and 0.95) respectively, followed by Hargreaves-Samani methods (R² = 0.86, D = 0.91, MAE = 0.60, EMAX = 2.16, EF = 0.69 and c = 0.85). The results obtained with the methods of Linacre, Solar Radiation and Jensen-Haise were lower and their use is not recommended for the region of Santa Teresa, ES. Keywords: Agrometeorology, hydric demand, irrigation, Penman-Montheith

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Deep Learning-Based Optimal Smart Shoes Sensor Selection for Energy Expenditure and Heart Rate Estimation

Sensors ◽

10.3390/s21217058 ◽

2021 ◽

Vol 21 (21) ◽

pp. 7058

Author(s):

Heesang Eom ◽

Jongryun Roh ◽

Yuli Sun Hariyani ◽

Suwhan Baek ◽

Sukho Lee ◽

...

Keyword(s):

Heart Rate ◽

Deep Learning ◽

Energy Expenditure ◽

Mean Squared Error ◽

Pressure Sensors ◽

Absolute Error ◽

Coefficient Of Determination ◽

Proposed Model ◽

Point Pressure

Wearable technologies are known to improve our quality of life. Among the various wearable devices, shoes are non-intrusive, lightweight, and can be used for outdoor activities. In this study, we estimated the energy consumption and heart rate in an environment (i.e., running on a treadmill) using smart shoes equipped with triaxial acceleration, triaxial gyroscope, and four-point pressure sensors. The proposed model uses the latest deep learning architecture which does not require any separate preprocessing. Moreover, it is possible to select the optimal sensor using a channel-wise attention mechanism to weigh the sensors depending on their contributions to the estimation of energy expenditure (EE) and heart rate (HR). The performance of the proposed model was evaluated using the root mean squared error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). Moreover, the RMSE was 1.05 ± 0.15, MAE 0.83 ± 0.12 and R2 0.922 ± 0.005 in EE estimation. On the other hand, and RMSE was 7.87 ± 1.12, MAE 6.21 ± 0.86, and R2 0.897 ± 0.017 in HR estimation. In both estimations, the most effective sensor was the z axis of the accelerometer and gyroscope sensors. Through these results, it is demonstrated that the proposed model could contribute to the improvement of the performance of both EE and HR estimations by effectively selecting the optimal sensors during the active movements of participants.

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Evaluation of 32 Simple Equations against the Penman–Monteith Method to Estimate the Reference Evapotranspiration in the Hexi Corridor, Northwest China

Water ◽

10.3390/w12102772 ◽

2020 ◽

Vol 12 (10) ◽

pp. 2772

Author(s):

Sindikubwabo Celestin ◽

Feng Qi ◽

Ruolin Li ◽

Tengfei Yu ◽

Wenju Cheng

Keyword(s):

Water Resource Management ◽

Reference Evapotranspiration ◽

Absolute Error ◽

Northwest China ◽

Hexi Corridor ◽

Climatic Conditions ◽

Alternative Methods ◽

Accurate Estimation ◽

Irrigation Planning ◽

Simple Equations

Evapotranspiration plays an inevitable role in various fields of hydrology and agriculture. Reference evapotranspiration (ET0) is mostly applied in irrigation planning and monitoring. An accurate estimation of ET0 contributes to decision and policymaking processes governing water resource management, efficiency, and productivity. Direct measurements of ET0, however, are difficult to achieve, often requiring empirical methods. The Penman–Monteith FAO56 (PM-FAO56) method, for example, is still considered to be the best way of estimating ET0 in most regions of the globe. However, it requires a large number of meteorological variables, often restricting its applicability in regions with poor or missing meteorological observations. Furthermore, the objectivity of some elements of the empirical equations often used can be highly variable from region to region. The result is a need to find an alternative, objective method that can more accurately estimate ET0 in regions of interest. This study was conducted in the Hexi corridor, Northwest China. In it we aimed to evaluate the applicability of 32 simple empirical ET0 models designed under different climatic conditions with different data inputs requirements. The models evaluated in this study are classified into three types of methods based on temperature, solar radiation, and mass transfer. The performance of 32 simple equations compared to the PM-FAO56 model is evaluated based on model evaluation techniques including root mean square error (RMSE), mean absolute error (MAE), percentage bias (PBIAS), and Nash–Sutcliffe efficiency (NSE). The results show that the World Meteorological Organization (WMO) and the Mahringer (MAHR) models perform well and are ranked as the best alternative methods to estimate daily and monthly ET0 in the Hexi corridor. The WMO and MAHR performed well with monthly mean RMSE = 0.46 mm and 0.56 mm, PBIAS = 12.1% and −11.0%, and NSE = 0.93 and 0.93, before calibration, respectively. After calibration, both models showed significant improvements with approximately equal PBIAS of −2.5%, NSE = 0.99, and RMSE of 0.24 m. Calibration also significantly reduced the PBIAS of the Romanenko (ROM) method by 82.12% and increased the NSE by 16.7%.

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Alternative reference evapotranspiration methods for the main climate types of the state of Paraná, Brazil

Pesquisa Agropecuária Brasileira ◽

10.1590/s0100-204x2018000900003 ◽

2018 ◽

Vol 53 (9) ◽

pp. 1003-1010 ◽

Cited By ~ 1

Author(s):

Bruno César Gurski ◽

Daniela Jerszurki ◽

Jorge Luiz Moretti de Souza

Keyword(s):

Root Mean Square Error ◽

Mean Square Error ◽

Root Mean Square ◽

Reference Evapotranspiration ◽

The State ◽

Alternative Methods ◽

Coefficient Of Determination ◽

Mean Square ◽

Standard Values

Abstract: The objective of this work was to define the best alternative methods for estimating the reference evapotranspiration (ETo) in the main climatic types (Cfa and Cfb) of the state of Paraná, Brazil. The methods tested were Budyko, Camargo, Hargreaves-Samani, Linacre, and Thornthwaite, which were compared to the ETo calculated with the Penman-Monteith ASCE (EToPM) method, between 1986 and 2015, in eight meteorological stations. The performance of the alternative methods was obtained from the coefficient of determination (R2), index “d” of agreement, index “c” of performance, and root mean square error (RMSE). The Hargreaves-Samani method has a better performance in estimating the ETo for the main climatic types in the state of Paraná. The Camargo method allows smaller errors between the standard values of ETo, obtained with the Penman-Monteith method, and the estimated values. The methods of Thornthwaite, Linacre, and Budyko are not adequate to estimate the ETo in any climatic type of the state of Paraná, Brazil.

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Evaluation and Calibration of Alternative Methods for Estimating Reference Evapotranspiration in the Senegal River Basin

Hydrology ◽

10.3390/hydrology7020024 ◽

2020 ◽

Vol 7 (2) ◽

pp. 24 ◽

Cited By ~ 2

Author(s):

Papa Malick Ndiaye ◽

Ansoumana Bodian ◽

Lamine Diop ◽

Abdoulaye Deme ◽

Alain Dezetter ◽

...

Keyword(s):

River Basin ◽

Hydrological Modeling ◽

Reference Evapotranspiration ◽

Water Cycle ◽

Irrigation Management ◽

Alternative Methods ◽

Coefficient Of Determination ◽

Climate Variables ◽

Senegal River ◽

Senegal River Basin

Reference evapotranspiration (ET0) is a key element of the water cycle in tropical areas for the planning and management of water resources, hydrological modeling, and irrigation management. The objective of this research is to assess twenty methods in computing ET0 in the Senegal River Basin and to calibrate and validate the best methods that integrate fewer climate variables. The performance of alternative methods compared to the Penman Monteith (FAO56-PM) model is evaluated using the coefficient of determination (R2), normalized root mean square error (NRMSE), percentage of bias (PBIAS), and the Kling–Gupta Efficiency (KGE). The most robust methods integrating fewer climate variables were calibrated and validated and the results show that Trabert, Valiantzas 2, Valiantzas 3, and Hargreaves and Samani models are, respectively, the most robust for ET0 estimation. The calibration improves the estimates of reference evapotranspiration compared to original models. It improved the performance of these models with an increase in KGE values of 45%, 32%, 29%, and 19% for Trabert, Valiantzas 2, Valiantzas 3, and Hargreaves and Samani models, respectively. From a spatial point of view, the calibrated models of Trabert and Valiantzas 2 are robust in all the climatic zones of the Senegal River Basin, whereas, those of Valiantzas 3 and Hargreaves and Samani are more efficient in the Guinean zone. This study provides information on the choice of a model for estimating evapotranspiration in the Senegal River Basin.

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A normalized regression based regional model for generating flows at ungauged basins

Water Science & Technology ◽

10.2166/wst.2013.216 ◽

2013 ◽

Vol 68 (1) ◽

pp. 99-108

Author(s):

Borislava Blagojević ◽

Jasna Plavšić

Keyword(s):

Input Data ◽

Absolute Error ◽

Parameter Estimates ◽

Model Parameters ◽

Efficiency Coefficient ◽

Ungauged Basins ◽

Model Parameter ◽

Proposed Model ◽

Two Parameter

Revision of existing methodologies for generating monthly-flow series at ungauged basins based on multivariate nonlinear correlation has led to a simple two-parameter model. While the existing methodology used hydrological, meteorological and geomorphologic input data, the proposed model requires hydrological and geomorphologic input data only. The proposed methodology requires formation of separate pools of donor catchments for model parameter estimates. The proposed two-parameter model and improvement in the sphere of homogeneous region identification were verified using 195 runoff data sets from hydrologic stations in Serbia in the 1961–2005 period, divided into three non-overlapping 15-year periods. Nash-Sutcliffe's model efficiency coefficient (NSE) was used to assess the: (1) quality of proposed model with identified model parameters; (2) quality of a nonlinear multivariate equation for standard normal variables estimation with identified model parameters; (3) quality of proposed model with model parameter estimates. Generated time-series statistics and nonlinear multivariate equation quality are also evaluated. Five model calibration and validation results are shown. Generated flow series variation coefficient is the best replicated statistics with relative absolute error less than 10%.

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Modeling Reference Evapotranspiration in a Semiarid Area Using Data-driven Techniques: A Case Study in Lower Cheliff plain, Algeria

10.21203/rs.3.rs-773420/v1 ◽

2021 ◽

Author(s):

Mohammed ACHITE ◽

Muhammad Taghi Sattari ◽

Abderrezak Kamel Toubal ◽

Andrzej Wałęga ◽

Nir Krakauer ◽

...

Keyword(s):

Neural Network ◽

Reference Evapotranspiration ◽

Meteorological Data ◽

Gene Expression Programming ◽

Global Radiation ◽

Performance Criteria ◽

Data Driven ◽

Coefficient Of Determination ◽

Irrigated Agriculture ◽

Efficiency Coefficient

Abstract Evapotranspiration (ET) is an important part of the hydrologic cycle, especially when it comes to irrigated agriculture. For the estimation of reference evapotranspiration (ET0), direct methods either pose difficulties or call for many inputs that may not always be available from weather stations. This study compares Feed Forward Neural Network (FFNN), Radial Basis Function Neural Network (RBFNN). and Gene Expression Programming (GEP) approachs for the estimation of daily ET0 in a weather station in Lower Cheliff plain (northwest Algeria), over a 6-year period (2006–2011). Firstly, measured air temperature, relative humidity, wind speed, solar radiation and global radiation was used to calculate ET0 using FAO-56 Penman-Monteith equation as the reference. Then, the calculated ET0 using FAO-56 Penman-Monteith was considered as output for data driven models, while the measured meteorological data were considered as input of the models. The coefficient of determination (R2), root mean square error (RMSE) and Nash Sutcliffe efficiency coefficient (EF) were used to evaluate the developed models. The results of the developed models were compared with the Penman-Monteith evapotranspiration using these performance criteria. The FFNN model proved to yield the best performance compared to all the developed data-driven models, while the RBF-NN and GEP models also demonstrated potential for good performance.

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Development and Assessment of Methods for Predicting Rainfall in Unmeasured Watersheds Using the Relation Between Observed and Sensor-Measured Rainfall

Korean Society of Hazard Mitigation ◽

10.9798/kosham.2021.21.6.293 ◽

2021 ◽

Vol 21 (6) ◽

pp. 293-302

Author(s):

Chungdae Lee ◽

Hayong Kim

Keyword(s):

High Reliability ◽

Absolute Error ◽

Coefficient Of Determination ◽

Efficiency Coefficient ◽

Artificial Rainfall ◽

Information And Communication ◽

The Relationship ◽

Precipitation Station ◽

The Internet Of Things

Recently, with the development of information and communication technology and the Internet of Things (IoT), observation technology using sensors is being applied in a variety of ways, such as using a sensor to observe rainfall in an unmeasured area. In this study, the relationship between the rainfall sensor signal (S) and the amount of rainfall (R) was developed through an experiment in an artificial rainfall generator, and the applicability was evaluated through outdoor observation. The coefficient of determination of the relational expression developed through the indoor experiment was 0.95, the mean absolute error was 2.66 mm/hr, the root mean square error was 3.87 mm/hr, the efficiency coefficient was 0.89, and the concordance index was 0.97, showing very high reliability. In the outdoor test results, the error rate was 7.96% when comparing the data from the rainfall sensors in vehicles and the precipitation station, which were not observed at the same location. Despite such errors, it is judged that accurate rainfall observation using a rainfall sensor is possible in an area where a precipitation station is not installed.

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