Multivariate spatial statistics techniques can be efficiently applied to generate fine spatial patterns of climate data in presence of an appropriate multivariate spatial structure over ungauged mountainous basins. However, they can become unsuitable when the data available over complex regions are sparse and affected by discordant spatial scales in primary and (colocated)-auxiliary variables. This is the case of actual evapotranspiration (AET). Combining GIS and geoindicators (e.g., topographical and vegetational indices), we proposed an upscaling procedure to overcome this problem, transforming a preliminary-smoothed macro-scale pattern (AET grid-data), into a local-scale pattern. The procedure was applied to a cropland test site at Mediterranean sub-regional basin scale (Tammaro, South Italy) to develop a climatological baseline estimation of AET refined at slope scale. After the upscaling, the most frequent estimated AET values were about 550 mm yr(-1) (with quasi-normal distribution), while underestimations were observed in the preliminary, smoothed map (positively skewed distribution with mean 460 mm yr(-1)). The upscaling allowed the influence of the topographic factor to emerge, with a wider range of values (about 300-900 mm yr(-1)) being estimated and substantially not visible in the smoothed pattern. A temporal climate pattern of soil water depletion in the growing season was also shown as reflected in the increase of AET flux in the period 1991-2008 in comparison to the precedent climate (1961-1990). (C) 2010 Elsevier Ltd. All rights reserved.
|Titolo:||GIS-aided evaluation of evapotranspiration at multiple spatial and temporal climate patterns using geoindicators|
|Data di pubblicazione:||2010|
|Appare nelle tipologie:||1.1 Articolo in rivista|