Abstract:This paper compares different procedures for mapping reference evapotranspiration (ET o ) by means of regression-based techniques and geographical information systems (GIS). ET o is calculated following the method of Hargreaves (HG) from a dense database of meteorological stations in the northernmost semi-arid region of Europe, the Ebro valley. The HG method requires the calculation of estimates of extraterrestrial radiation (R a ). We calculated this parameter using two approaches: (1) the common approach that assumes a planar surface and determines the parameter as a function of latitude and (2) using a digital terrain model (DTM) and GIS modelling. The maps were made on a monthly basis using both approaches. We also compared possible propagations of errors in the map calculations for maps derived from modelled layers of maximum and minimum temperatures with those modelled using previously determined local ET o calculations. We demonstrate that calculations of R a from a DTM and GIS modelling provide a more realistic spatial distribution of ET o than those derived by only considering latitude. It is also preferable to model in advance the variables involved in the calculation of ET o (temperature and R a ) and to subsequently calculate ET o by means of layer algebra in the GIS rather than directly model the local ET o calculations. The obtained maps are useful for the purposes of agriculture and ecological and water resources management in the study area.
The objective of this study was to provide a simple and accurate method for mapping long-term averages of monthly snowpack (from 1986 to 2003) over large regions at a resolution suitable for management purposes (cell size 100 m 2 ). The proposed method requires few data and overcomes the problem of the limited availability of meteorological information in mountainous areas. In a case study, the proposed method is applied to the Aragón region, NE Spain. Distributed layers of monthly temperature (maximum and minimum) and precipitation are combined to compile maps of the potential magnitude of snowpack at a monthly timescale over the entire study region. Temperature and precipitation grids were obtained using interpolation techniques and data from several weather stations. Maps of snowpack magnitude were obtained for January, March, and April. For these months, it was possible to verify the results in the north of the study area using in situ snowdepth measurements for the Central Pyrenees. The results demonstrate that the maps of potential snowpack magnitude provide a reliable estimate of the observed snow-depth distribution over the study region. Calibration between the observed and predicted values enabled us to convert the potential snowpack magnitude (in dimensionless units) into real snowpack values in absolute units (snow depth, cm). The addition of a model of incoming solar radiation in the calculation procedure provided better results in terms of the final predictions because it captured local variations in snowpack related to variable relief.
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