caa a22 4500 445837675 CHVBK 20180317145334.0 cr unu---uuuuu 170323e20111101xx s 000 0 eng 10.1007/s00271-010-0243-3 doi (NATIONALLICENCE)springer-10.1007/s00271-010-0243-3 Reference evapotranspiration estimation without local climatic data [Elektronische Daten] [Pau Martí, Pablo González-Altozano, María Gasque] The Penman-Monteith equation for reference evapotranspiration (ETo) estimation cannot be applied in many situations, because climatic records are totally or partially not available or reliable. In these cases, empirical equations that rely on few climatic variables are necessary. Nevertheless, the uncertainty associated with empirical model estimations is often high. Thus, the improvement of methods relying on few climatic inputs as well as the development of emergency estimation tools that demand no local climatic records turns into a task of great relevance. The present study describes different approaches based on multiple linear regression, simple regression and artificial neural networks (ANNs) to deal with ETo estimation exclusively from exogenous records from secondary stations. This cross-station approach is based on a continental characterization of the study region, which enables the selection and hierarchization of the most suitable ancillary data supplier stations. This procedure is compared with different traditional and cross-station approaches, including methodologies that also consider local temperature inputs. The proposed methods are also evaluated as gap infilling procedures and compared with a simple methodology, the window averaging. The artificial neural network and the multiple linear regression approaches present very similar performance accuracies, considerably higher than simple regression and traditional temperature-based approaches. The proposed input combinations allow similar performance accuracies as ANN models relying on exogenous ETo records and local temperature measurements. The cross-station multiple linear regression procedure is recommended due to its higher simplicity. Springer-Verlag, 2010 Martí Pau Centro Valenciano de Estudios sobre el Riego (CVER), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut González-Altozano Pablo Departamento de Ingeniería Rural y Agroalimentaria, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut Gasque María Departamento de Física Aplicada, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut Irrigation Science Springer-Verlag 29/6(2011-11-01), 479-495 0342-7188 29:6<479 2011 29 271 https://doi.org/10.1007/s00271-010-0243-3 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s00271-010-0243-3 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Martí Pau Centro Valenciano de Estudios sobre el Riego (CVER), Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut NATIONALLICENCE 700 1- González-Altozano Pablo Departamento de Ingeniería Rural y Agroalimentaria, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut NATIONALLICENCE 700 1- Gasque María Departamento de Física Aplicada, Universidad Politécnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain aut NATIONALLICENCE 773 0- Irrigation Science Springer-Verlag 29/6(2011-11-01), 479-495 0342-7188 29:6<479 2011 29 271 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer