Ab Basque Country Research Institute For Agricultural Development

Basque Country, Spain

Ab Basque Country Research Institute For Agricultural Development

Basque Country, Spain

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Kiafar H.,Islamic Azad University at Tehran | Babazadeh H.,Islamic Azad University at Tehran | Marti P.,University of the Balearic Islands | Kisi O.,Canik Basari University | And 3 more authors.
Theoretical and Applied Climatology | Year: 2016

Evapotranspiration estimation is of crucial importance in arid and hyper-arid regions, which suffer from water shortage, increasing dryness and heat. A modeling study is reported here to cross-station assessment between hyper-arid and humid conditions. The derived equations estimate ET0 values based on temperature-, radiation-, and mass transfer-based configurations. Using data from two meteorological stations in a hyper-arid region of Iran and two meteorological stations in a humid region of Spain, different local and cross-station approaches are applied for developing and validating the derived equations. The comparison of the gene expression programming (GEP)-based-derived equations with corresponding empirical-semi empirical ET0 estimation equations reveals the superiority of new formulas in comparison with the corresponding empirical equations. Therefore, the derived models can be successfully applied in these hyper-arid and humid regions as well as similar climatic contexts especially in data-lack situations. The results also show that when relying on proper input configurations, cross-station might be a promising alternative for locally trained models for the stations with data scarcity. © 2016 Springer-Verlag Wien


Shiri J.,University of Tabriz | Shiri J.,Group 47 | Kisi O.,Erciyes University | Kisi O.,Group 47 | And 8 more authors.
Journal of Hydrology | Year: 2012

Evapotranspiration, as a major component of the hydrological cycle, is of importance for water resources management and development, as well as for estimating the water budget of irrigation schemes. This study presents a Gene Expression Programming (GEP) approach, for estimating daily reference evapotranspiration (ET 0) in four weather stations in Basque Country (Northern Spain), for a 5-year period (1999-2003). The data set comprising air temperature, relative humidity, wind speed and solar radiation was employed for modeling ET 0 using FAO-56 Penman Monteith equation as the reference. The GEP results were compared with the Adaptive Neuro-Fuzzy Inference System (ANFIS), Priestley-Taylor and Hargreaves-Samani models. Based on the comparisons, the GEP was found to perform better than the ANFIS, Priestley-Taylor and Hargreaves-Samani models. The ANFIS model is ranked as the second best model. © 2011 Elsevier B.V.


Shiri J.,University of Tabriz | Sadraddini A.A.,University of Tabriz | Nazemi A.H.,University of Tabriz | Marti P.,IRTA - Institute of Agricultural-Alimentary Research and Technology | And 3 more authors.
Computers and Electronics in Agriculture | Year: 2015

There is multitude of models for estimating daily reference evapotranspiration (ET0) using meteorological parameters. Among others, the temperature-based Hargreaves-Samani (HS) model is one of the frequently applied models for estimating ET0 when meteorological parameters in the studied station are limited. However, this method tends to require a preliminary local calibration. Most calibration procedures usually apply the same data sets for calibrating and testing. At the most, some studies reserve an independent test set for evaluating the calibrated model, but considering a single data set assignment. In the present study, the HS model and its calibrated version were assessed using meteorological parameters from 29 weather stations in Iran, through complete temporal and spatial data scanning, using a k-fold testing approach. A similar procedure was also repeated using the Gene Expression Programming (GEP) technique relying on the same input variables of the HS model. The results showed the importance of adopting k-fold based independent testing approach in order to avoid problems related to the influence of selected test period on the performance of the GEP models. © 2015 Elsevier B.V.


Landeras G.,Ab Basque Country Research Institute For Agricultural Development | Ortiz-Barredo A.,Ab Basque Country Research Institute For Agricultural Development | Lopez J.J.,University of Pamplona
Irrigation and Drainage | Year: 2014

Irrigation advice is usually based on the optimization of crop yield, which sometimes does not meet the objective of economic optimization. In some regions, the information provided by irrigation scheduling schemes based on crop production optimization is not completely reliable if there are economic or environmental constraints. The objective of the present study is the development of an optimization scheme of irrigation advice based on economic optimization under different scenarios of water availability. The optimization scheme presented in this study is focused on the minimization of the economic losses related to the cost of water and the economic yield loss associated with different irrigation strategies. As a case study the developed scheme was applied to the optimization of irrigation advice on sugar beet in the Basque country (northern Spain). A comparison has been performed between the optimized and the actual irrigation strategies in the area of study. As a result of this comparison the adoption by an Irrigation Advisory Service of the developed optimization scheme seems adequate in the area of study. This comparison reveals the utility of the developed scheme for the optimization of irrigation advice under specific scenarios of water constraints. © 2014 John Wiley & Sons, Ltd.


Shiri J.,University of Tabriz | Nazemi A.H.,University of Tabriz | Sadraddini A.A.,University of Tabriz | Landeras G.,Ab Basque Country Research Institute For Agricultural Development | And 3 more authors.
Computers and Electronics in Agriculture | Year: 2014

Accurate estimation of reference evapotranspiration (ET0) values is of crucial importance in hydrology, agriculture and agro-meteorology issues. The present study reports a comprehensive comparison of empirical and semi empirical ET0 equations with the corresponding Heuristic Data Driven (HDD) models in a wide range of weather stations in Iran. Artificial Neural Networks (ANNs), Adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM) and Gene Expression Programming (GEP) techniques are applied for modeling ET0 values considering different data management scenarios, and compared with corresponding Hargreaves-Samani (HS), Makkink (MK), Priestley-Taylor (PT), and Turc (T) ET0 models as well as their linear and non-linear calibrated versions along with the regression-based Copais algorithm. The obtained results confirm the superiority of GEP-based models. Further, the HDD models generally outperform the applied empirical models. Among the empirical models, the calibrated HS model found to give the most accurate results in all local and pooled scenarios, followed by the Copais and the calibrated PT models. In both local and pooled applications, the calibrated HS equation should be applied when no training data are available for the use of HDD models. The best results of the models correspond to the humid regions, while the arid regions provide the poorest estimates. This may be attributed to higher ET0 values associated with these stations and the high advective component of these locations. © 2014 Elsevier B.V.


Shiri J.,University of Tabriz | Nazemi A.H.,University of Tabriz | Sadraddini A.A.,University of Tabriz | Landeras G.,Ab Basque Country Research Institute For Agricultural Development | And 3 more authors.
Journal of Hydrology | Year: 2013

Accurate estimation of reference evapotranspiration is important for irrigation scheduling, water resources management and planning and other agricultural water management issues. In the present paper, the capabilities of generalized neuro-fuzzy models were evaluated for estimating reference evapotranspiration using two separate sets of weather data from humid and non-humid regions of Spain and Iran. In this way, the data from some weather stations in the Basque Country and Valencia region (Spain) were used for training the neuro-fuzzy models [in humid and non-humid regions, respectively] and subsequently, the data from these regions were pooled to evaluate the generalization capability of a general neuro-fuzzy model in humid and non-humid regions. The developed models were tested in stations of Iran, located in humid and non-humid regions. The obtained results showed the capabilities of generalized neuro-fuzzy model in estimating reference evapotranspiration in different climatic zones. Global GNF models calibrated using both non-humid and humid data were found to successfully estimate ET0 in both non-humid and humid regions of Iran (the lowest MAE values are about 0.23mm for non-humid Iranian regions and 0.12mm for humid regions). non-humid GNF models calibrated using non-humid data performed much better than the humid GNF models calibrated using humid data in non-humid region while the humid GNF model gave better estimates in humid region. © 2012 Elsevier B.V.

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