Estimation of Evapotranspiration by Various Net Radiation Estimation Formulae for Non-Irrigated Grass in Brazil  

作　　者：Antonio Ribeiro da Cunha Edgar Ricardo Schoffel Clovis Alberto Volpe 

机构地区：[1]School of Agronomic Sciences,Sao Paulo State University(UNESP),Botucatu,Brazil [2]Eliseu Maciel School of Agronomy,Federal University of Pelotas,Pelotas,Brazil

出　　处：《Journal of Water Resource and Protection》2014年第15期1425-1436,共12页水资源与保护（英文）

基　　金：financial support from the Fundacao de Amparoa Pesquisa do Estado de Sao Paulo(FAPESP,Sao Paulo Research Foundation,Grant No.05/59535-4).

摘　　要：The objective of this study was to assess the accuracy of estimating evapotranspiration (ET) using the FAO-56 Penman-Monteith (FAO-56-PM) model, with measured and estimated net radiation (Rnmeasured and Rnestimated, respectively), the latter obtained via five different models. We used meteorological data collected between August 2005 and June 2008, on a daily basis and on a seasonal basis (wet vs. dry seasons). The following data were collected: temperature;relative humidity;global global solar radiation (Rs);wind speed and soil heat flux. The atmospheric pressure was determined by aneroid barograph, and sunshine duration was quantified with a Campbell-Stokes recorder. In addition to the sensor readings (Rnmeasured), five different models were used in order to obtain the Rnestimated. Four of those models consider the effects of cloud cover: the original Brunt model;the FAO-24 model for wet climates;the FAO-24 model for dry climates, and the FAO-56 model. The fifth was a linear regression model based on Rs. In estimating the daily ET0 with the FAO-56-PM model, Rnmeasured can be replaced by Rnestimated, in accordance with the FAO-24 model for dry climates, with a relative error of 2.9%, or with the FAO-56 model, with an error of 4.9%, when Rs is measured, regardless of the season. The Rnestimated obtained with the fifth model has a relatively high error. The original Brunt model and FAO-24 model for wet climates performed more poorly than did the other models in estimating the Rn and ET0. In overcast conditions, the original Brunt model, the FAO-24 model for wet climates, the FAO-24 model for dry climates, the FAO-56 model and the model of linear regression with Rs as the predictor variable tended to overestimate Rn and ET, those estimates becoming progressively more accurate as the cloud cover diminished.The objective of this study was to assess the accuracy of estimating evapotranspiration (ET) using the FAO-56 Penman-Monteith (FAO-56-PM) model, with measured and estimated net radiation (Rnmeasured and Rnestimated, respectively), the latter obtained via five different models. We used meteorological data collected between August 2005 and June 2008, on a daily basis and on a seasonal basis (wet vs. dry seasons). The following data were collected: temperature;relative humidity;global global solar radiation (Rs);wind speed and soil heat flux. The atmospheric pressure was determined by aneroid barograph, and sunshine duration was quantified with a Campbell-Stokes recorder. In addition to the sensor readings (Rnmeasured), five different models were used in order to obtain the Rnestimated. Four of those models consider the effects of cloud cover: the original Brunt model;the FAO-24 model for wet climates;the FAO-24 model for dry climates, and the FAO-56 model. The fifth was a linear regression model based on Rs. In estimating the daily ET0 with the FAO-56-PM model, Rnmeasured can be replaced by Rnestimated, in accordance with the FAO-24 model for dry climates, with a relative error of 2.9%, or with the FAO-56 model, with an error of 4.9%, when Rs is measured, regardless of the season. The Rnestimated obtained with the fifth model has a relatively high error. The original Brunt model and FAO-24 model for wet climates performed more poorly than did the other models in estimating the Rn and ET0. In overcast conditions, the original Brunt model, the FAO-24 model for wet climates, the FAO-24 model for dry climates, the FAO-56 model and the model of linear regression with Rs as the predictor variable tended to overestimate Rn and ET, those estimates becoming progressively more accurate as the cloud cover diminished.

关 键 词：EVAPOTRANSPIRATION Net Radiation Solar Radiation Cloud Cover Empirical Models 

分 类 号：R73[医药卫生—肿瘤]