{"id":"CONICETDig_ad57e86be633a492cf8079ffd83322f8","dc:title":"Permafrost model for the Argentinian Andes - Calibration data set","dc:creator":"Tapia Baldis, Carla Cintia","dc:date":"2024","dc:description":["Supplementary information to the following publication: Tapia Baldis C, Trombotto Liaudat D. 2020. Permafrost debris-model in Central Andes of Argentina (28\u00b0-33\u00b0 S). Cuadernos de Investigaci\u00f3n Geogr\u00e1fica 46, http:\/\/doi.org\/10.18172\/cig.3802 ------------------------------------------------------------------------------------------------------------------------- To predict regional-scale spatial patterns of permafrost occurrence, especially over remote environments with limited data, empiric-statistical models are widely used. This kind of approach correlates permafrost occurrence with topo-climatic factors (altitude, geographic position, slope, aspect, air temperature, ground temperature, solar radiation, etc.) easily available, in some cases. Different combinations of empiric-statistical models were tested to evaluate the permafrost spatial distribution in the study area. The study area (28\u00b0 to 33\u00b0S and 70\u00b030\u2019 to 69\u00b0W) comprises the middle portion of the South American (Argentinian side) Central Andes (17\u00b030\u2019 to 35\u00b0S), named Dry Andes. The landscape is expressed as mountain ranges and valleys with 50% of the terrain surface above 3000 m a.s.l. The highest elevations are represented by mountain peaks such us Mercedario (6850 m a.s.l.) or La Ramada (6400 m a.s.l.). The Dry Andes could be further separated into Desert Andes (17\u00b030\u2019 to 31\u00b0S) and Central Andes (31\u00b0 to 35\u00b0S), according to precipitation rates and landscape geomorphological characteristics. Models were trained in a calibration area to evaluate the correlation between geomorphological permafrost indicators (named explanatory variable) and the topoclimatic parameters (predictive variable). A logistic regression model with a logit link function was chosen as a mathematical approach. Data for model calibration was obtained from the Bramadero river basin, located at 31\u00b050\u2019 S and 70\u00b000\u2019 W in the Central Andes. From a geomorphological point of view, the landscape of the Dry Andes is characterized by the interdigitation of glacial, periglacial, alluvial, fluvial, and gravitational processes. The Bramadero river basin was largely glaciated during the LGM, even today it is possible to recognize erosive forms and glacial deposits all over the main valley and subordinated creeks. Even though Quaternary glacial stages modeled the landscape; periglacial features prevail today. Currently, periglacial processes are active in elevations exceeding 2700 m a.s.l. (lowest limit of seasonal freezing), however, a wide variety of periglacial deposits and permafrost indicating cryoforms occur between 3400 and >4500 m a.s.l. (permafrost periglacial belt). The complete geomorphological characterization of the Bramadero river basin and the geomorphometric data extracted from every kind of landform were used to set up the permafrost predictive categories. The first predictive category (presence) includes geoforms that indicate current permafrost, such as; active rock glaciers, inactive rock glaciers, protalus lobes, cryoplanation surfaces, and perennial snow patches. The second category (absence) includes geoforms without current permafrost (relict or fossil rock glaciers, bedrock outcrops, glacial abrasion surfaces, debris\/mud flows, and Andean wetlands\/peatlands types). It also includes geoforms where the presence of permafrost could not be certainly assessed such us: frozen and unfrozen talus slopes, glaciers and covered glaciers, moraines and morainic complexes, debris\/snow avalanches, rock avalanches, and rock slides."],"dc:format":["application\/octet-stream"],"dc:language":["eng"],"dc:type":"dataset","dc:rights":["info:eu-repo\/semantics\/openAccess","https:\/\/creativecommons.org\/licenses\/by-nc-sa\/2.5\/ar\/"],"dc:relation":["info:eu-repo\/grantAgreement\/Consejo Nacional de Investigaciones Cient\u00edficas y T\u00e9cnicas\/PIP 12222015-01000913","info:eu-repo\/grantAgreement\/\/PIP 12222015-01000913"],"dc:identifier":"https:\/\/repositoriosdigitales.mincyt.gob.ar\/vufind\/Record\/CONICETDig_ad57e86be633a492cf8079ffd83322f8"}