scholarly journals Assessment of empirical methods for estimation of reference evapotranspiration in the Brazilian Savannah

2019 ◽  
pp. 1094-1104
Author(s):  
Lucas da Costa Santos ◽  
Guilherme Henrique Terra Cruz ◽  
Frank Freire Capuchinho ◽  
Jeffersom Vieira José ◽  
Elton Fialho dos Reis
Keyword(s):  
Air Temperature ◽  
Standard Method ◽  
Reference Evapotranspiration ◽  
Meteorological Data ◽  
Reference Method ◽  
The State ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Empirical Methods

Evapotranspiration can be sufficiently estimated when meteorological data are available to implement robust models such as Penman-Monteith (PM). However, due to data scarcity, alternative approaches are necessary. In this context, this study aims to compare the reference evapotranspiration (ETo) obtained from the PM standard method with eight empirical equations to identify the simplest method that can be alternative to the reference method (Penman Monteith method) for ten places in state of Goiás (located in west-central Brazil, Brazilian Savanna). To estimate the ETo, air temperature and relative humidity air, wind speed, sunshine and solar radiation data, which were obtained from the data platform National Institute of Meteorology and the Meteorological and Hydrological System of the State of Goiás, were used. For comparison of empirical methods with PM standard method, we used the following statistical indicators: slope and intercept coefficients (β0 and β1) of regressions equations, the coefficient of determination (r²), Pearson's correlation (r), mean bias error (MBE), root mean square error (RMSE) concordance index refined (dr) and performance index (Pi). Our results indicated that the Turc method is the best option for the state of Goiás when meteorological data are not suffeciently available to use the standard PM method. On the other hand, the method of Romanenko did not present acceptable performance in nine of the ten studied localities. Therefore, its use is advised only in the municipality of the Itumbiara. Among evaluated methods the Hargreaves-Samani method is the best alternative, when there is only air temperature data.

scholarly journals COMPARISON BETWEEN ESTIMATION METHODS OF REFERENCE EVAPOTRANSPIRATION IN BOM JESUS ​​DA LAPA, BA

2020 ◽  
Vol 28 ◽  
pp. 120-128
Author(s):  
Taiara Souza Costa ◽  
Robson Argolo dos Argolo dos Santos ◽  
Ramon Amaro Amaro de Sales ◽  
Aldnira Tolentino Tolentino Nogueira ◽  
Rosangela Leal Santos
Keyword(s):  
Reference Evapotranspiration ◽  
Meteorological Data ◽  
Estimation Methods ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Good Precision ◽  
Error Bias ◽  
Statistical Indicators

Among the reference evapotranspiration (ETo) equations, the FAO-56 Penman-Monteith (PM FAO-56) model is considered the most accurate, but this model requires a greater amount of meteorological data. On the other hand, there are other methods that require fewer variables and have shown good precision according to the location. The objective of this work was to evaluate the efficiency of four methods for estimation of daily ETo, comparing them with FAO-56 PM equation in Bom Jesus da Lapa, Bahia, Brazil. To do so, a dataset from 2010 to 2017, acquired at the National Institute of Meteorology (INMET), was used. The models were analyzed by means of statistical indicators: Willmott’s concordance index, root mean square error (RMSE), mean bias error (BIAS), coefficient of determination “R²”, correlation coefficient “r” and coefficient of confidence “c”, in addition to the classification of the coefficient of confidence. The results obtained show that Hargreaves and Samani equation was the only method classified as “good” and is recommended. While the models of Camargo, Priestley and Taylor and Benevides and Lopes are not recommended to calculate ETo in the municipality.

scholarly journals Estimation of daily global solar irradiance from the air temperature in the state of Paraná, Brazil

2020 ◽  
Vol 24 (8) ◽  
pp. 512-519
Author(s):  
Carolina K. Sgarbossa ◽  
Jorim S. das Virgens Filho
Keyword(s):  
Air Temperature ◽  
Solar Irradiance ◽  
Historical Data ◽  
Pearson Correlation ◽  
The State ◽  
Mean Bias Error ◽  
Bias Error ◽  
Empirical Methods ◽  
Irradiance Data ◽  
Weather Stations

ABSTRACT Global solar irradiance (GSI) is a fundamental source of energy on Earth. Despite its importance, sunshine or solar irradiance data are rarely available from weather stations. In the absence of available data, there are empirical methods that can be used to estimate solar irradiance. The objective of this study is to calibrate the parameters and to evaluate the performance of four empirical models of solar irradiance estimation (those of Chen, Hargreaves, Hunt, and Richardson) from air temperature data for eight localities in the state of Paraná, Brazil. Data were obtained from the Meteorological Database for Teaching and Research (BDMEP). For the comparison of means among the models, the Kruskal-Wallis non-parametric test was used. Dunn’s multiple comparison tests were used to analyze which models presented different means from the others. The performance of each model was assessed using the indices Pearson correlation coefficient (r), mean bias error (MBE), root mean square error (RMSE), Wilmott concordance index (d), performance index (c) and the Nash-Sutcliffe efficiency (NSE) coefficient. It was observed that the models proposed by Chen and Hunt presented the best performances in the estimation of GSI for the studied Paraná state localities, given that they yielded results which are closer to the observed historical data.

scholarly journals Accuracy of air temperature forecasts and its use for prediction of the reference evapotranspiration

2020 ◽  
Vol 36 (1) ◽  
Author(s):  
Claudio Ricardo da Silva ◽  
Lucas Andrade Barbosa ◽  
Rafael Resende Finzi ◽  
Bruno Teixeira Riberio ◽  
Nildo da Silva Dias
Keyword(s):  
Air Temperature ◽  
Web Sites ◽  
Reference Evapotranspiration ◽  
Meteorological Data ◽  
Irrigation Management ◽  
Mean Bias Error ◽  
Bias Error ◽  
Forecast Horizon ◽  
The Mean

The objective of this study was to verify the quality of the short-term forecasts made by some web sites, as well as the potential of its use in estimating reference evapotranspiration (ETo). For the period 2012-2013, every 4-days, the maximum (Tmax) and minimum (Tmin) air temperature forecasts for horizons of 24, 48, 72 and 96 hours provided by public sites for Uberlandia-MG were collected and used for calculating the reference evapotranspiration (ETo) by the Hargreaves-Samani (HS) calibrated equation. The sites www.accuweather.com (WEATHER); www.cemig.com.br (CEMIG); jornaldotempo.uol.com.br; (JORNAL) and www.climatempo.com.br (CLIMA) were evaluated. For the same period, the meteorological data were taken at the National Institute of Meteorology (www.inmet.gov.br). The performance of the Tmax and Tmin forecasts as well as the ETo estimates were made by regression analysis, the mean bias error (MBE), root mean square error (RMSE) and t-test. For all sites, there was a better performance in the prediction of Tmin when compared to Tmax, especially by a reduction in errors (MBE and RMSE) and an increase in coefficients b and R2. For ETo, the site CLIMA had lowest MBE and RMSE (0.9 mm d-1) following by the WEATHER and JORNAL. On the other hand, the site CEMIG presented higher values for MBE (-1.3 mm d-1) and RMSE (1.6 mm d-1). There was no worsening with an increase of the forecast horizon in these indices, except for R² values. The site CLIMA was the only one that did not differ significantly from the ETo values observed.  The results of diagnostic verification procedures indicate the potential use of air temperature forecasts in irrigation management.

Evaluation of Global Solar Radiation using Sunshine Hour, Temperature and Relative Humidity at Low Land Region of Nepal

2020 ◽  
Vol 6 (1) ◽  
pp. 16-24
Author(s):  
U. Joshi ◽  
K.N. Poudyal ◽  
I.B. Karki ◽  
N.P. Chapagain
Keyword(s):  
Solar Radiation ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Energy Potential ◽  
To Come ◽  
Empirical Constants

The accurate knowledge of solar energy potential is essential for agricultural scientists, energy engineers, architects and hydrologists for relevant applications in concerned fields. It is cleanest and freely available renewable energy measured using CMP6 Pyranometer. However, it is quite challenging to acquire accurate solar radiation data in different locations of Nepal because of the high cost of instruments and maintenances. In these circumstances, it is essential to select an appropriate empirical model to predict global solar radiation for the use of future at low land, Nepalgunj (28.102°N, 81.668°E and alt. 165 masl) for the year 2011-2012. In this paper, six different empirical models have been used based on regression technique, provided the meteorological data. The empirical constants (a = 0.61, b = 0.05, c = -0.0012 and d = -0.017) are obtained to predict Global solar radiation. The values of statistical tools such as mean percentage error, mean bias error, root mean square error, and coefficient of determination obtained for Abdalla model are 1.99%, 0.003 MJ/m2/day, 2.04 MJ/m2/day and 0.74 respectively. Using the error analysis, it is concluded that the Abdalla model is better than others. So the empirical constants of this model are utilized to predict the global solar radiation to the similar geographical sites of Nepal for the years to come and it can be used to estimate the missing data of solar radiation for the respective sites.

scholarly journals EVAPOTRANSPIRAÇÃO DE REFERÊNCIA EM FUNÇÃO DOS EXTREMOS DA TEMPERATURA DO AR NO ESTADO DO RIO DE JANEIRO

Irriga ◽  
2018 ◽  
Vol 21 (3) ◽  
pp. 449 ◽  
Author(s):  
Anderson Amorim Rocha Santos ◽  
Gustavo Bastos Lyra ◽  
Guilherme Bastos Lyra ◽  
Evaldo Paiva Lima ◽  
José Leonaldo De Souza ◽  
...  
Keyword(s):  
Air Temperature ◽  
Rio De Janeiro ◽  
Reference Evapotranspiration ◽  
Global Radiation ◽  
The State ◽  
Southeastern Brazil ◽  
Temperature Extremes ◽  
Empirical Methods ◽  
And Performance ◽  
E Mail

EVAPOTRANSPIRAÇÃO DE REFERÊNCIA EM FUNÇÃO DOS EXTREMOS DA TEMPERATURA DO AR NO ESTADO DO RIO DE JANEIRO  ANDERSON AMORIM ROCHA SANTOS1; GUSTAVO BASTOS LYRA2; GUILHERME BASTOS LYRA3; EVALDO PAIVA LIMA4; JOSÉ LEONALDO DE SOUZA5 E RAFAEL COLL DELGADO2 1 Engenheiro Agrônomo, Mestre em Engenharia de Biossistemas, Escola de Engenharia, Universidade Federal Fluminense – UFF, Campus da Praia Vermelha, 24210-240, Niterói, Rio de Janeiro, Brasil, e-mail: [email protected] Meteorologistas, Professores Doutores do Departamento de Ciências Ambientais, Instituto de Florestas, Universidade Federal Rural do Rio de Janeiro – UFRRJ, Campus UFRRJ, 23897-000, Seropédica, Rio de Janeiro, Brasil, e-mail: [email protected]; [email protected] Engenheiro Agrônomo, Professor Doutor do Centro de Ciências Agrárias, Universidade Federal de Alagoas – UFAL, BR-104, 57100-000, Rio Largo, Alagoas, Brasil, e-mail:[email protected]  4 Meteorologista, Pesquisador do Centro Nacional de Pesquisa de Solos, Empresa Brasileira de Pesquisa Agropecuária – EMBRAPA, Rua Jardim Botânico 1024, 22460-000, Rio de Janeiro, Rio de Janeiro, Brasil, e-mail: [email protected] Meteorologista, Professor Doutor do Centro de Ciências Agrárias, Universidade Federal de Alagoas – UFAL, BR-104, 57100-000, Rio Largo, Alagoas, Brasil, e-mail: [email protected]  1 RESUMO A aplicação do método de Penman-Monteith FAO56 (PM-FAO56) para estimativa da evapotranspiração de referência (ETo) requer observações de diversos elementos meteorológicos. A maior parte das estações meteorológicas não realiza medidas de todos os elementos, o que restringe a aplicação do PM-FAO56. O objetivo foi avaliar o desempenho dos métodos empíricos de Thornthwaite, Camargo, Hargreaves-Samani, Jensen-Haise e Makkink na estimativa de ETo em função dos extremos de temperatura do ar no estado do Rio de Janeiro (RJ). Foram utilizadas séries meteorológicas entre oito e 34 anos de 10 estações convencionais pertencentes ao Instituto Nacional de Meteorologia localizadas no RJ. As estimativas decendiais e mensais de ETo pelos métodos empíricos foram comparadas com ETo determinada por PM-FAO56 (padrão) para se avaliar a exatidão (Erro Padrão de Estimativa - EPE e Índice de Willmott - d), precisão (coeficiente de determinação - R²) e o desempenho (índice c de Camargo e Sentelhas) dos métodos. Independente da escala de tempo avaliada, o método de Makkink mostrou estimativas com maior exatidão (d > 0,82 e EPE < 0,68 mm d-1), precisão (R² > 0,88) e desempenho (índice c > 0,85) nas estações caracterizadas com clima úmido, subúmido, subúmido seco com pequeno excedente hídrico. Nas demais estações, clima subúmido seco com excedente nulo e semiárido, o método de Hargreaves-Samani teve melhor desempenho (índice c > 0,85). Os métodos de Thornthwaite e Camargo apresentaram estimativas com exatidão (d > 0,90 e EPE < 0,72 mm d-1) e desempenho (índice c > 0,76) entre os melhores e podem ser usados para estimativa de ETo no RJ. As menores exatidões (d < 0,73 e EPE > 1,38 mm d-1) e desempenhos (0,51 < índice c < 0,75) das estimativas foram proporcionadas por Jensen-Haise para todas as estações e escalas de tempo, não sendo recomendado sua aplicação no estado do RJ. Os métodos de Hargreaves-Samani, Jensen-Haise e Makkink devem ser ajustados às condições climáticas do RJ. Palavras-Chave: Penman-Monteith, radiação solar global, amplitude térmica   SANTOS, A. A. R.; LYRA, G.B.; LYRA, G.B.; LIMA, E. P.; SOUZA, J. L.; DELGADO, R. C.ESTIMATES OF THE REFERENCE EVAPOTRANSPIRATION USING AIR TEMPERATURE EXTREMES IN THE STATE OF THE RIO DE JANEIRO, SOUTHEASTERN BRAZIL 2 ABSTRACT The use of the Penman-Monteith FAO56 method (PM-FAO 56) to estimate reference evapotranspiration (ETo) requires several weather elements. However, most weather stations don’t measure all the elements, which restricts the application of PM-FAO 56. The aim of this article was to evaluate the performance of five empirical methods (Thornthwaite, Camargo, Hargreaves-Samani, Jensen-Haise and Makkink) to estimate ETo using air temperature extremes in the state of the Rio de Janeiro (RJ). Times series of weather elements between eight and 34 years from 10 conventional stations of the Brazilian National Institute of Meteorology located in RJ were used. The ten-day and monthly estimates of ETo by empirical methods were compared to ETo determined by PM-FAO 56 (default) to evaluate the accuracy (Standard Error of the Estimate - SEE and Willmott index - d), precision (coefficient of determination - R²) and performance (Camargo and Sentelhas – c Index) of the methods. Independent of the time scale, the Makkink method showed the highest accuracies (d > 0.82 and SEE < 0.68 mm d-1), precision (R² > 0.88) and performance (c Index > 0.85) on the stations, characterized with humid, sub-humid, dry sub-humid with small water surplus. For the other stations, semiarid and dry sub-humid climate with no surplus, the Hargreaves-Samani method had the best performance (c Index > 0.85). The Thornthwaite and Camargo methods presented accuracy (d > 0.90 and SEE < 0.72 mm d-1) and performance (Index c > 0.76) between the top and can be used to estimate ETo in RJ. For all stations and time scales, the worst accuracies (d < 0.73 and SEE > 1.38 mm d-1) and performance (0.51 < Index c < 0.75) estimates were provided by the Jensen-Haise method, so it is not recommended its application in RJ state. The Hargreaves-Samani, Jensen-Haise and Makkink methods should be fitted to the climatic conditions of RJ. Keywords: Penman-Monteith, solar global radiation, temperature amplitude

scholarly journals Empirical models for predicting global solar radiation using meteorological parameters for Sokoto, Nigeria

2019 ◽  
Vol 7 (2) ◽  
pp. 48
Author(s):  
Davidson O. Akpootu ◽  
Bello I. Tijjani ◽  
Usman M. Gana
Keyword(s):  
Solar Radiation ◽  
Meteorological Parameters ◽  
Meteorological Data ◽  
Climatic Variability ◽  
Global Solar Radiation ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Radiation Maximum

The performances of sunshine, temperature and multivariate models for the estimation of global solar radiation for Sokoto (Latitude 13.020N, Longitude 05.250E and 350.8 m asl) located in the Sahelian region in Nigeria were evaluated using measured monthly average daily global solar radiation, maximum and minimum temperatures, sunshine hours, rainfall, wind speed, cloud cover and relative humidity meteorological data during the period of thirty one years (1980-2010). The comparison assessment of the models was carried out using statistical indices of coefficient of determination (R2), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), t – test, Nash – Sutcliffe Equation (NSE) and Index of Agreement (IA). For the sunshine based models, a total of ten (10) models were developed, nine (9) existing and one author’s sunshine based model. For the temperature based models, a total of four (4) models were developed, three (3) existing and one author’s temperature based model. The results of the existing and newly developed author’s sunshine and temperature based models were compared and the best empirical model was identified and recommended. The results indicated that the author’s quadratic sunshine based model involving the latitude and the exponent temperature based models are found more suitable for global solar radiation estimation in Sokoto. The evaluated existing Ångström type sunshine based model for the location was compared with those available in literature from other studies and was found more suitable for estimating global solar radiation. Comparing the most suitable sunshine and temperature based models revealed that the temperature based models is more appropriate in the location. The developed multivariate regression models are found suitable as evaluation depends on the available combination of the meteorological parameters based on two to six variable correlations. The recommended models are found suitable for estimating global solar radiation in Sokoto and regions with similar climatic information with higher accuracy and climatic variability.   

scholarly journals REDES NEURAIS ARTIFICIAIS, REGRESSÃO E MÉTODOS EMPÍRICOS PARA A MODELAGEM DA EVAPOTRANSPIRAÇÃO DE REFERÊNCIA NA CIDADE DE INHAMBANE, MOÇAMBIQUE

Irriga ◽  
2019 ◽  
Vol 24 (4) ◽  
pp. 802-816
Author(s):  
BARTOLOMEU FÉLIX TANGUNE ◽  
Rodrigo Máximo Sánchez Román
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Root Mean Square Error ◽  
Mean Square Error ◽  
Reference Evapotranspiration ◽  
Mean Bias Error ◽  
Bias Error ◽  
Mean Square ◽  
Empirical Methods ◽  
E Mail

REDES NEURAIS ARTIFICIAIS, REGRESSÃO E MÉTODOS EMPÍRICOS PARA A MODELAGEM DA EVAPOTRANSPIRAÇÃO DE REFERÊNCIA NA CIDADE DE INHAMBANE, MOÇAMBIQUE   BARTOLOMEU FÉLIX TANGUNE1 E RODRIGO MÁXIMO SÁNCHEZ ROMÁN2   1 Departamento de Engenharia Rural, Escola Superior de Desenvolvimento Rural, Universidade Eduardo Mondlane, Vilankulo, Inhambane, Moçambique. E-mail: [email protected]. 2 Departamento de Engenharia Rural, Faculdade de Ciências Agronômicas, Universidade Estadual Paulista (UNESP) Campus de Botucatu. Fazenda Experimental Lageado, Avenida Universitária, nº 3780, Altos do Paraíso, CEP: 18610-034, Botucatu – SP. Brasil. E-mail: [email protected]     1 RESUMO   Estimativa precisa da evapotranspiração de referência (ETo) é importante para dimensionar e fazer manejo de sistemas de irrigação. Métodos de estimativa da ETo (11 métodos empíricos, 10 modelos de regressão múltipla: RLM e 10 redes neurais artificias: RNAs) foram avaliados em relação ao método padrão de Penman Monteith FAO 56, utilizando os seguintes índices: MBE (Mean Bias Error), RMSE (Root Mean Square Error) e R2, sendo RMSE utilizado como critério principal de seleção dos métodos. A significância dos métodos foi avaliada com base no teste t utilizando dados de 1985 a 2009. Os dados meteorológicos utilizados (temperatura máxima: Tmax, temperatura mínima: Tmin e temperatura média: T, umidade relativa, velocidade do vento e insolação) são da estação meteorológica convencional da cidade de Inhambane, Moçambique. Os resultados mostraram que o modelo RLM4 apresentou melhor desempenho (MBE = 0,01 mm.d-1; RMSE = 0,15 mm.d-1; R2 = 0,99). Na falta da radiação solar global, os modelos RLM6 (MBE = -0,01 mm.d-1; RMSE = 0,23 mm.d-1; R2 = 0,97) e RLM10 (MBE = 0,01 mm.d-1; RMSE = 0,23 mm.d-1; R2 = 0,97) podem ser utilizados e exigem a medição da T, Tmax e Tmin, respectivamente. Esses modelos não foram estatisticamente diferentes do método padrão.   Palavras-chave: evapotranspiração, regressão múltipla, redes neurais.     TANGUNE, B. F.; SÁNCHEZ-ROMÁN, R. M. ARTIFICIAL NEURAL NETWORKS, REGRESSION AND EMPIRICAL METHODS FOR REFERENCE EVAPOTRANSPIRATION MODELING IN INHAMBANE CITY, MOZAMBIQUE     2 ABSTRACT   Precise estimation of reference evapotranspiration (ETo) is important for designing and managing irrigation systems. Methods of ETo estimation (11 empirical methods, 10 multiple regression models: RLM and 10 artificial neural networks: RNAs) were evaluated against Penman Monteith FAO 56 method using the following indexes: MBE (Mean Bias Error), RMSE (Root Mean Square Error) and R2, and RMSE was used as the main criterion of method selection. The significance of the methods was evaluated on the basis of the t test using data from 1985 to 2009. The meteorological data used (maximum temperature: Tmax, minimum temperature: Tmin and average temperature: T, relative air humidity, wind speed and solar brightness), from 1985 to 2009, are from the conventional meteorological station of the city of Inhambane, Mozambique. The results showed that the RLM4 model presented better performance (MBE = 0.01 mm.d-1; RMSE = 0.15 mm.d-1; R2 = 0.99). In the absence of global solar radiation, RLM6 (MBE = -0.01 mm.d-1; RMSE = 0.23 mm.d-1; R2 = 0.97) and RLM10 (MBE = 0.01 mm. d-1; RMSE = 0.23 mm.d-1; R2 = 0.97) can be used, which require measurement of T, and Tmax and Tmin, respectively. These models were not statistically different from the standard method.   Keywords: evapotranspiration, multiple regression, neural networks.

scholarly journals New temperature dependent models for estimating global solar radiation across the midland climatic zone of Nigeria

2019 ◽  
Vol 7 (2) ◽  
pp. 70
Author(s):  
Davidson O. Akpootu ◽  
Bello I. Tijjani ◽  
Usman M. Gana
Keyword(s):  
Solar Radiation ◽  
Meteorological Data ◽  
Global Solar Radiation ◽  
Climatic Zone ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Percentage Error ◽  
Bias Error ◽  
Temperature Dependent ◽  
Statistical Validation

Authentic information of the availability of global solar radiation is significant to agro/hydro meteorologists, atmospheric Physicists and solar energy engineers for the purpose of local and international marketing, designs and manufacturing of solar equipment. In this study, five new proposed temperature dependent models were evaluated using measured monthly average daily global solar radiation, maximum and minimum temperature meteorological data during the period of thirty one years (1980-2010). The new models were compared with three existing temperature dependent models (Chen et al., Hargreaves and Samani and Garcia) using seven different statistical validation indicators of coefficient of determination (R2), Mean Bias Error (MBE), Root Mean Square Error (RMSE), Mean Percentage Error (MPE), t – test, Nash – Sutcliffe Equation (NSE) and Index of Agreement (IA) to ascertain the suitability of global solar radiation estimation in five different locations (Zaria, Bauchi, Jos, Minna and Yola) situated in the Midland climatic zone of Nigeria. In each location, the result shows that a new empirical regression model was found more accurate when compared to the existing models and are therefore recommended for estimating global solar radiation in the location and regions with similar climatic information where only temperature data are available. The evaluated existing Hargreaves and Samani and Garcia temperature based models for Jos were compared to those available in literature and was found more suitable for estimating global solar radiation for the location. The comparison between the measured and estimated temperature dependent models depicts slight overestimation and underestimation in some months with good fitting in the studied locations. However, the recommended models give the best fitting.   

scholarly journals Calibration methods for the Hargreaves-Samani equation

2018 ◽  
Vol 42 (1) ◽  
pp. 104-114 ◽  
Author(s):  
Lucas Borges Ferreira ◽  
Fernando França da Cunha ◽  
Anunciene Barbosa Duarte ◽  
Gilberto Chohaku Sediyama ◽  
Paulo Roberto Cecon
Keyword(s):  
Linear Regression ◽  
Reference Evapotranspiration ◽  
Meteorological Data ◽  
Absolute Error ◽  
Mean Bias Error ◽  
Bias Error ◽  
Daily Data ◽  
Calibration Methods ◽  
And Performance ◽  
Adjustment Of Parameters

ABSTRACT The estimation of the reference evapotranspiration is an important factor for hydrological studies, design and management of irrigation systems, among others. The Penman Monteith equation presents high precision and accuracy in the estimation of this variable. However, its use becomes limited due to the large number of required meteorological data. In this context, the Hargreaves-Samani equation could be used as alternative, although, for a better performance a local calibration is required. Thus, the aim was to compare the calibration process of the Hargreaves-Samani equation by linear regression, by adjustment of the coefficients (A and B) and exponent (C) of the equation and by combinations of the two previous alternatives. Daily data from 6 weather stations, located in the state of Minas Gerais, from the period 1997 to 2016 were used. The calibration of the Hargreaves-Samani equation was performed in five ways: calibration by linear regression, adjustment of parameter “A”, adjustment of parameters “A” and “C”, adjustment of parameters “A”, “B” and “C” and adjustment of parameters “A”, “B” and “C” followed by calibration by linear regression. The performances of the models were evaluated based on the statistical indicators mean absolute error, mean bias error, Willmott’s index of agreement, correlation coefficient and performance index. All the studied methodologies promoted better estimations of reference evapotranspiration. The simultaneous adjustment of the empirical parameters “A”, “B” and “C” was the best alternative for calibration of the Hargreaves-Samani equation.

scholarly journals Global radiation by simplified models for the state of Mato Grosso, Brazil

2017 ◽  
Vol 52 (4) ◽  
pp. 215-227 ◽  
Author(s):  
Adilson Pacheco de Souza ◽  
Andréa Carvalho da Silva ◽  
Adriana Aki Tanaka ◽  
Eduardo Morgan Uliana ◽  
Frederico Terra de Almeida ◽  
...  
Keyword(s):  
Global Radiation ◽  
The State ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Simplified Models ◽  
Mato Grosso ◽  
Statistical Indicator ◽  
Specific Performance ◽  
Using Data

Abstract The objective of this work was to estimate the global radiation by simplified models for the state of Mato Grosso, Brazil. The parameterized coefficients of 15 simplified models were regionally calibrated to estimate the daily global radiation, based only on air temperature, using data from 28 automatic weather stations (AWS) of the network of the Brazilian Meteorology Institute, distributed throughout the different biomes of the state of Mato Grosso. The simplified models are mostly derived from the Hargreaves and Bristow & Campbell methods, with different parameterized coefficients to be calibrated. The coefficient of determination (R2), the mean bias error (MBE), the root mean square error (RMSE), and Willmott’s d index were used to evaluate statistical performance. For the recommendation of models per station and/or biome, the models were rated numerically (position values) according to their specific performance in each statistical indicator. The simplified models derived from Bristow & Campbell showed better statistical performances for estimating daily global radiation. The values of the calibrated coefficients of the same model varied greatly among the AWS and biomes. The R2 values ranged from 0.60 to 0.75, indicating a satisfactory result for the obtained calibrations. The Bristow & Campbell model for the Amazon and the Cerrado and the Goodin et al. (1999) model for the Cerrado are recommended, with scattering varying between 1.52 and 4.33 MJ m-2 per day and adjustments greater than 65%.

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