Mauro Rossi[1,2], Marco Donnini[1,2], Francesco Frondini[2], Fausto Guzzetti[1], 2013, Estimation of infiltration in the Alpine area exploiting open data and open source software, XIV Meeting degli utenti italiani GRASS e GFOSS, Genova, Italia, 6-9 February 2013,
URL: http://www.cnr.it/prodotto/i/275434

Infiltration rates can be used to estimate the quantity of water flowing into the soil. Several methods can be used to estimate the water infiltrating into the soil as well as the different components of water cycle. Water balance models have been developed at various time scales (hourly, daily, monthly and yearly) and to varying degrees of complexity. Monthly water balance models were developed by Thornthwaite (1948) and later revised by Thornthwaite and Mather (1957). In this work - with the aim to estimate the infiltration rates in Alpine region - we implemented a code in R (a free software environment for statistical computing and graphics - R Core Team, 2012) based on a public domain software written in Java by McCabe & Markstrom (2007). The code performs a spatial monthly water balance analysis. The model input data consist of_ (1) World mean monthly temperature and monthly total precipitation values, available from the Intergovernmental Panel on Climate Change (IPCC) website; (2) World digital elevation model ASTER GDEM, available from the Earth Remote Sensing Data Analysis Center (ERSDAC) of Japan and NASA's Land Processes Distributed Active Center (LP DAAC) website; (3) Eurasian soil thematic data of the European Soil Database (v2.0), available from the Joint Research Center (JRC) website. The water balance computation was performed on a 0.5° × 0.5° grid (like the IPCC grid) covering the Alps. For each cell, we evaluated a level of uncertainty computing the minimum, maximum and mean infiltration values, and we propagated in the model the uncertainty associated to the original input parameters (climatic, morphological and soil thematic data). Although the model should be validated and tested in different study areas, it allowed to perform a water balance analysis at regional scale using open data and open source software. We expect that this will become a key input for small scale hydrological, hydro-geological and geochemical models in the Alpine region.

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