{"publisher":"American Geophysical Union","extern":"1","publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","title":"Calibration of a physically based, spatially distributed hydrological model in a glacierized basin: On the use of knowledge from glaciometeorological processes to constrain model parameters","oa":1,"article_number":"W03509","issue":"3","scopus_import":"1","day":"01","date_published":"2012-03-01T00:00:00Z","status":"public","author":[{"last_name":"Ragettli","full_name":"Ragettli, S.","first_name":"S."},{"full_name":"Pellicciotti, Francesca","last_name":"Pellicciotti","first_name":"Francesca","id":"b28f055a-81ea-11ed-b70c-a9fe7f7b0e70"}],"oa_version":"Published Version","doi":"10.1029/2011wr010559","_id":"12644","quality_controlled":"1","volume":48,"month":"03","intvolume":"        48","article_processing_charge":"No","language":[{"iso":"eng"}],"date_updated":"2023-02-21T09:38:36Z","year":"2012","publication":"Water Resources Research","main_file_link":[{"url":"https://doi.org/10.1029/2011WR010559","open_access":"1"}],"citation":{"ama":"Ragettli S, Pellicciotti F. Calibration of a physically based, spatially distributed hydrological model in a glacierized basin: On the use of knowledge from glaciometeorological processes to constrain model parameters. <i>Water Resources Research</i>. 2012;48(3). doi:<a href=\"https://doi.org/10.1029/2011wr010559\">10.1029/2011wr010559</a>","short":"S. Ragettli, F. Pellicciotti, Water Resources Research 48 (2012).","ista":"Ragettli S, Pellicciotti F. 2012. Calibration of a physically based, spatially distributed hydrological model in a glacierized basin: On the use of knowledge from glaciometeorological processes to constrain model parameters. Water Resources Research. 48(3), W03509.","mla":"Ragettli, S., and Francesca Pellicciotti. “Calibration of a Physically Based, Spatially Distributed Hydrological Model in a Glacierized Basin: On the Use of Knowledge from Glaciometeorological Processes to Constrain Model Parameters.” <i>Water Resources Research</i>, vol. 48, no. 3, W03509, American Geophysical Union, 2012, doi:<a href=\"https://doi.org/10.1029/2011wr010559\">10.1029/2011wr010559</a>.","ieee":"S. Ragettli and F. Pellicciotti, “Calibration of a physically based, spatially distributed hydrological model in a glacierized basin: On the use of knowledge from glaciometeorological processes to constrain model parameters,” <i>Water Resources Research</i>, vol. 48, no. 3. American Geophysical Union, 2012.","chicago":"Ragettli, S., and Francesca Pellicciotti. “Calibration of a Physically Based, Spatially Distributed Hydrological Model in a Glacierized Basin: On the Use of Knowledge from Glaciometeorological Processes to Constrain Model Parameters.” <i>Water Resources Research</i>. American Geophysical Union, 2012. <a href=\"https://doi.org/10.1029/2011wr010559\">https://doi.org/10.1029/2011wr010559</a>.","apa":"Ragettli, S., &#38; Pellicciotti, F. (2012). Calibration of a physically based, spatially distributed hydrological model in a glacierized basin: On the use of knowledge from glaciometeorological processes to constrain model parameters. <i>Water Resources Research</i>. American Geophysical Union. <a href=\"https://doi.org/10.1029/2011wr010559\">https://doi.org/10.1029/2011wr010559</a>"},"abstract":[{"lang":"eng","text":"In the Dry Andes of central Chile, summer water resources originate mostly from snowmelt and ice melt. We use the physically based, spatially distributed hydrological model TOPKAPI to study the exchange between glaciers and climate in the upper Aconcagua River Basin during the summer season and identify the model parameters that are robust and transferable and those that are more dependent on calibration. TOPKAPI has recently been adapted to incorporate an enhanced temperature index approach for snow and ice melting. We suggest a calibration procedure that allows calibration of parameters in three steps by separating parameters governing distinct processes. We evaluate the parameters' transferability in time and in space by applying the model at two spatial scales. TOPKAPI's ability to simulate the relevant processes is tested against meteorological, ablation, and glacier runoff data measured on Juncal Norte Glacier during two glacier ablation seasons. The model was applied successfully to the climatic setting of the Dry Andes once its parameters were recalibrated. We found a clear distinction between parameters that are stable in time and those that need recalibration. The parameters of the melt model are transferable from one season to the other, while the parameters governing the extrapolation of meteorological input data and the routing of glacier meltwater need recalibration from one season to the other. Sensitivity analysis revealed that the model is most sensitive to the temperature lapse rate governing the extrapolation of air temperature from point measurements to the glacier scale and to the melt parameter that multiplies the shortwave radiation balance."}],"date_created":"2023-02-20T08:17:39Z","type":"journal_article","article_type":"original","publication_identifier":{"issn":["0043-1397"]}}