Evapotranspiration With Modified Hargreaves Model: Saudi Arabia1

2013 ◽  
pp. 357-376
Keyword(s):  
Hargreaves Model

scholarly journals Predictive Performance of Hargreaves Model in Estimating Solar Radiation in Yola, Adamawa State Nigeria Using Minimum Climatological Data

2018 ◽  
pp. 1-8
Author(s):  
Ojo Samuel ◽  
Alimi Taofeek Ayodele ◽  
Amos Anna Solomon
Keyword(s):  
Solar Radiation ◽  
Model Performance ◽  
Predictive Performance ◽  
Global Solar Radiation ◽  
Climatic Data ◽  
Climatological Data ◽  
University Of Technology ◽  
Hargreaves Model ◽  
The Many

Mathematical models have been very useful in reducing challenges encountered by researchers due to the inability of having solar radiation data or lack of instrumental sites at every point on the Earth.  This work aimed at investigating the prediction performance of Hargreaves-Samani’s model in estimating global solar radiation (GSR) out of the many other empirical models so far formulated for this purpose. This model basically uses maximum and minimum temperature data and basically used in mid-latitudes. The paper attempts to assess the predictive performance of Hargreaves-Samani’s model in the Savanna region using Yola as a case study. Estimated values of GSR from one month data adopted from the Meteorological station of the Department of Geography, Federal University of Technology, Yola, Nigeria was used for this purpose. Using this model shows a 95% index of agreement (IA) with the observed values; which suggests a good model performance and can also be used in estimating global solar radiation in the Savanna region particularly in areas with little or no such climatic data.

scholarly journals REFERENCE EVAPOTRANSPIRATION THROUGH HARGREAVES METHOD USING THE SOLAR RADIATION ESTIMATION FOR GOIÁS STATE, BRAZIL

2020 ◽  
Vol 28 ◽  
pp. 274-292
Author(s):  
Caio Vinicius Leite ◽  
Derblai Casaroli ◽  
Marcelo Rossi Vicente ◽  
Raphael Cessa Maia Aveiro ◽  
José Alves Júnior
Keyword(s):  
Standard Method ◽  
Reference Evapotranspiration ◽  
Calibration Coefficient ◽  
Dry Period ◽  
Good Adherence ◽  
Rainy Period ◽  
Hargreaves Model ◽  
Weather Stations ◽  
Adjusted Model ◽  
Annual Period

This study evaluated the Hargreaves model (HG) with seasonal adjustments of the calibration coefficient (Krs) of the radiation equation to estimate the reference evapotranspiration (ETo) in 23 weather stations in Goiás State, Brazil, in comparison to the Penman-Monteith FAO (PM-FAO) standard method. The models were evaluated using Pearson’s correlation coefficient, Willmott’s agreement index, relative error, absolute mean error and root mean square error. The Krs values ranged from 0.146 to 0.189 ° C-0.5, while ETo PM-FAO ranged from 3.68 to 4.79 mm d-1; ETo HG from 3.99 to 5.16 mm d-1 and ETo HG-Krs from 4.15 to 5.02 mm d-1 in the annual period. Seasonal adjustments resulted in values of 0.144 to 0.205 ° C-0.5 for the dry period, from April to September, and 0.144 to 0.146 ° C-0.5 for the rainy period, from October to March. The first quarter (summer), presented Krs values from 0.150 to 0.175 ° C-0.5; the second quarter (autumn), from 0.154 to 0.218 ° C-0.5; the third quarter (winter), from 0.139 to 0.206 ° C-0.5; and, finally, the fourth quarter (spring) of 0.141 to 0.166 ° C-0.5. Thus, the use of the seasonally adjusted model proved to be viable for the estimation of ETo, in view of the simplicity and its good adherence to the standard method.

scholarly journals An Estimation of Solar Characteristic in Kelantan Using Hargreaves Model

2013 ◽  
Vol 36 ◽  
pp. 473-478 ◽  
Author(s):  
Y.M. Irwan ◽  
I. Daut ◽  
I. Safwati ◽  
M. Irwanto ◽  
N. Gomesh ◽  
...  
Keyword(s):  
Hargreaves Model

scholarly journals Evapotranspiration Response to Climate Change in Semi-Arid Areas: Using Random Forest as Multi-Model Ensemble Method

Water ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 222
Author(s):  
Marcos Ruiz-Aĺvarez ◽  
Francisco Gomariz-Castillo ◽  
Francisco Alonso-Sarría
Keyword(s):  
Climate Change ◽  
Random Forest ◽  
Climate Models ◽  
Ensemble Methods ◽  
Positive Trend ◽  
Model Ensemble ◽  
Predictive Capacity ◽  
Significant Positive Trend ◽  
Hargreaves Model ◽  
Large Ensembles

Large ensembles of climate models are increasingly available either as ensembles of opportunity or perturbed physics ensembles, providing a wealth of additional data that is potentially useful for improving adaptation strategies to climate change. In this work, we propose a framework to evaluate the predictive capacity of 11 multi-model ensemble methods (MMEs), including random forest (RF), to estimate reference evapotranspiration (ET0) using 10 AR5 models for the scenarios RCP4.5 and RCP8.5. The study was carried out in the Segura Hydrographic Demarcation (SE of Spain), a typical Mediterranean semiarid area. ET0 was estimated in the historical scenario (1970–2000) using a spatially calibrated Hargreaves model. MMEs obtained better results than any individual model for reproducing daily ET0. In validation, RF resulted more accurate than other MMEs (Kling–Gupta efficiency (KGE) M=0.903, SD=0.034 for KGE and M=3.17, SD=2.97 for absolute percent bias). A statistically significant positive trend was observed along the 21st century for RCP8.5, but this trend stabilizes in the middle of the century for RCP4.5. The observed spatial pattern shows a larger ET0 increase in headwaters and a smaller increase in the coast.

scholarly journals Improved Hargreaves Model Based on Multiple Intelligent Optimization Algorithms to Estimate Reference Crop Evapotranspiration in Humid Areas of Southwest China

Atmosphere ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 15
Author(s):  
Zongjun Wu ◽  
Ningbo Cui ◽  
Bin Zhu ◽  
Long Zhao ◽  
Xiukang Wang ◽  
...  
Keyword(s):  
Relative Error ◽  
Southwest China ◽  
Empirical Models ◽  
Crop Evapotranspiration ◽  
Estimation Model ◽  
Important Indicator ◽  
Reference Crop Evapotranspiration ◽  
Bee Colony ◽  
Hargreaves Model ◽  
Reference Crop

Reference crop evapotranspiration (ET0) is an important indicator for precise regulation of crop water content, irrigation forecast formulation, and regional water resources management. The Hargreaves model (HG) is currently recognized as the simplest and most effective ET0 estimation model. To further improve the prediction accuracy of the HG model, this study is based on the data of 98 meteorological stations in southwest China (1961–2019), using artificial bee colony (ABC), differential evolution (DE) and particle swarm optimization (PSO) algorithms to calibrate the HG model globally. The standard ET0 value was calculated by FAO-56 Penman–Monteith (PM) model. We compare the calculation accuracy of 3 calibrated HG models and 4 empirical models commonly used (Hargreaves, Priestley–Taylor, Imark–Allen and Jensen–Hais). The main outcomes demonstrated that on a daily scale, the calibrated HG models (R2 range 0.74–0.98) are more accurate than 4 empirical models (R2 range 0.55–0.84), and ET0-PSO-HG has the best accuracy, followed by ET0-ABC-HG and ET0-DE-HG, with average R2 of 0.83, 0.82 and 0.80, average RRMSE of 0.23 mm/d, 0.25 mm/d and 0.26 mm/d, average MAE of 0.52 mm/d, 0.53 mm/d and 0.57 mm/d, and average GPI of 0.17, 0.05, and 0.04, respectively; on a monthly scale, ET0-PSO-HG also has the highest accuracy, followed by ET0-ABC-HG and ET0-DE-HG, with median R2 of 0.96, 0.95 and 0.94, median RRMSE of 0.16 mm/d, 0.17 mm/d and 0.18 mm/d respectively, median MAE of 0.46 mm/d, 0.50 mm/d, and 0.55 mm/d, median GPI of 1.12, 0.44 and 0.34, respectively. The calibrated HG models (relative error of less than 10.31%) are also better than the four empirical models (relative error greater than 16.60%). Overall, the PSO-HG model has the most accurate ET0 estimation on daily and monthly scales, and it can be suggested as the preferred model to predict ET0 in humid regions in southwest China regions.

scholarly journals Study of Different Evapotranspiration Models under Polyhouse and Open Environment in Tarai Region of Uttarakhand

2019 ◽  
pp. 832-840
Author(s):  
Atish Sagar ◽  
Pramodh Kumar Singh
Keyword(s):  
Benchmark Model ◽  
Open Environment ◽  
Hargreaves Model

The average of mean monthly ET0 estimated under polyhouse by FAO PM (benchmark) model was 39.44 mm, but that of the FAO Penman, Hargreaves Stanghellini, Priestley-Taylor and FAO Radiation models were 38.37, 18.18, 37.80, 48.17 and 53.87 mm respectively. Whereas, the average of mean monthly ETo estimated under open environment by FAO PM (benchmark) model was 116.34 mm, but that of the FAO Penman, Hargreaves Stanghellini, Priestley-Taylor and FAO Radiation models were 119.33, 133, 126.41, 113.17 and 117.37 mm respectively. The FAO Penman and Hargreaves model are found to be most and least appropriate models for estimating daily ET0 under polyhouse. Whereas, FAO Radiation and Stanghellini model observed to be most and the least appropriate models in an open environment for estimating daily ET0 under polyhouse for the Pantnagar Tarai condition of Uttarakhand.

Estimating Daily Solar Radiation Using Hargreaves Model in Eastern Malaysia

2014 ◽  
Vol 699 ◽  
pp. 564-569 ◽  
Author(s):  
Mohd Irwan Yusoff ◽  
Muhamad Irwanto ◽  
Safwati Ibrahim ◽  
Gomesh Nair ◽  
Syed Idris Syed Hassan ◽  
...  
Keyword(s):  
Solar Radiation ◽  
Mean Squared Error ◽  
Coefficient Of Determination ◽  
Maximum Temperature ◽  
Percentage Error ◽  
Model Estimation ◽  
Estimation Model ◽  
Radiation Data ◽  
Squared Error ◽  
Hargreaves Model

This paper presents the forecasting of solar radiation in Kelantan, Eastern Malaysia for the year of 2011 using Hargreaves model. This estimation is based on latitude and daily minimum and maximum temperature in Kelantan. The measured and estimated solar radiation data were compared for the year 2011 and analyzed using coefficient of residual mass (CRM), root mean squared error (RMSE), coefficient of determination (R2) and percentage error (e). The results showed that the value ofCRMis 0.09, it indicates the tendency of the estimation model to under-estimate the measure solar radiation. Meanwhile, the value ofRMSEis 8.21% and the value ofR2is 0.8661, closed to 1 indicates that about 86.61% of the total variation is explained in the data. For thee, the value is 7.98%, it indicates that the model estimation is good.

scholarly journals Effect of watershed subdivision and estimation of climatic variables on hydrological simulation with the swat model in semi-arid mediterranean basins

2018 ◽  
pp. 114-133
Author(s):  
Francisco Gomariz Castillo ◽  
Francisco Alonso Sarría
Keyword(s):  
Input Data ◽  
Hydrological Model ◽  
Swat Model ◽  
Climatic Variables ◽  
Climate Information ◽  
Hydrological Simulation ◽  
Hargreaves Model ◽  
Discretization Schemes ◽  
The Usa ◽  
Semi Arid

Los resultados de cualquier intento de modelización hidrológica dependen de la calidad y discretización de los datos de entrada. En este trabajo se evalúa cómo la utilización de diferentes capas de variables climáticas de entrada (precipitación y ETP) y diferentes esquemas de discretización de la cuenca influyen en los resultados de un modelo hidrológico bien conocido (SWAT). En concreto se prueban 4 conjuntos de variables de entrada y discretización. Los estadísticos utilizados para evaluar la exactitud obtenida con estos conjuntos son RMSE, PBIAS, NSE y r2. Los resultados muestran que el uso de mejores modelos para obtener series de ETP (Penman Monteith FAO o Hargreaves calibrado) mejora considerablemente la exactitud del modelo respecto a las series obtenidas con el modelo de Hargreaves sin calibrar (opción por defecto en SWAT). Sin embargo, no se aprecian diferencias entre los resultados obtenidos con Penman Monteith FAO y Hargreaves calibrado. Por otro lado, el uso de información climática distribuida mejora notablemente los resultados obtenidos con información agregada. Se observa también la necesidad de calibrar los parámetros de SWAT ya que los valores por defecto están optimizados para ambientes templados de EEUU. The results of hydrological modelling depend on the quality and spatial resolution of the input data. This paper evaluates how the use of different estimations of climatic variables input layers (precipitation and ET P ) and different basin discretization schemes influence affect the results of a contrasted hydrological model (SWAT). Specifically, 4 se ts of input and discretization variables are tested. The statistics used to evaluate the accuracy obtained with these sets are RMSE, PBIAS, NSE and r 2 . The results show that the use of better models to obtain ET P series (Penman Monteith FAO or calibrated Hargreaves) considerably improves the accuracy of the model compared to the series obtained with the uncalibrated Hargreaves model (default option in SWAT). However, there is no difference between the results obtained with Penman Monteith FAO and calibrate d Hargreaves. On the other hand, the use of distributed climate information significantly improves the results obtained with aggregated information. There is also a need to calibrate SWAT parameters as the default values are optimized for temperate environ ments in the USA.

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