The aim of this work is to integrate the Minimal Glacier Model in a Geographic Information System Python module in order to obtain spatial simulations of glacier retreat and to assess the future scenarios with a spatial representation. The Minimal Glacier Models are a simple yet effective way of estimating glacier response to climate fluctuations. This module can be useful for the scientific and glaciological community in order to evaluate glacier behavior, driven by climate forcing. The module, called r.glacio.model, is developed in a GRASS GIS (GRASS Development Team, 2016) environment using Python programming language combined with different libraries as GDAL, OGR, CSV, math, etc. The module is applied and validated on the Rutor glacier, a glacier in the south-western region of the Italian Alps. This glacier is very large in size and features rather regular and lively dynamics. The simulation is calibrated by reconstructing the 3-dimensional dynamics flow line and analyzing the difference between the simulated flow line length variations and the observed glacier fronts coming from ortophotos and DEMs. These simulations are driven by the past mass balance record. Afterwards, the future assessment is estimated by using climatic drivers provided by a set of General Circulation Models participating in the Climate Model Inter-comparison Project 5 effort. The approach devised in r.glacio.model can be applied to most alpine glaciers to obtain a first-order spatial representation of glacier behavior under climate change.

Strigaro, D., Moretti, M., Mattavelli, M., Frigerio, I., DE AMICIS, M., Maggi, V. (2016). A GRASS GIS module to obtain an estimation of glacier behavior under climate change: A pilot study on Italian glacier. COMPUTERS & GEOSCIENCES, 94, 68-76 [10.1016/j.cageo.2016.06.009].

A GRASS GIS module to obtain an estimation of glacier behavior under climate change: A pilot study on Italian glacier

STRIGARO, DANIELE
Primo
;
MORETTI, MASSIMILIANO
Secondo
;
MATTAVELLI, MATTEO;FRIGERIO, IVAN;DE AMICIS, MATTIA GIOVANNI MARIA
Penultimo
;
MAGGI, VALTER
Ultimo
2016

Abstract

The aim of this work is to integrate the Minimal Glacier Model in a Geographic Information System Python module in order to obtain spatial simulations of glacier retreat and to assess the future scenarios with a spatial representation. The Minimal Glacier Models are a simple yet effective way of estimating glacier response to climate fluctuations. This module can be useful for the scientific and glaciological community in order to evaluate glacier behavior, driven by climate forcing. The module, called r.glacio.model, is developed in a GRASS GIS (GRASS Development Team, 2016) environment using Python programming language combined with different libraries as GDAL, OGR, CSV, math, etc. The module is applied and validated on the Rutor glacier, a glacier in the south-western region of the Italian Alps. This glacier is very large in size and features rather regular and lively dynamics. The simulation is calibrated by reconstructing the 3-dimensional dynamics flow line and analyzing the difference between the simulated flow line length variations and the observed glacier fronts coming from ortophotos and DEMs. These simulations are driven by the past mass balance record. Afterwards, the future assessment is estimated by using climatic drivers provided by a set of General Circulation Models participating in the Climate Model Inter-comparison Project 5 effort. The approach devised in r.glacio.model can be applied to most alpine glaciers to obtain a first-order spatial representation of glacier behavior under climate change.
Articolo in rivista - Articolo scientifico
Climate; Geoinformatic; GIS; Glaciology; GRASS GIS; Minimal glacier model;
GIS; Minimal glacier model; Glaciology; Geoinformatic; Grass GIS; Climate
English
2016
94
68
76
none
Strigaro, D., Moretti, M., Mattavelli, M., Frigerio, I., DE AMICIS, M., Maggi, V. (2016). A GRASS GIS module to obtain an estimation of glacier behavior under climate change: A pilot study on Italian glacier. COMPUTERS & GEOSCIENCES, 94, 68-76 [10.1016/j.cageo.2016.06.009].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/115849
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