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<metadata xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xmlns:dc="http://purl.org/dc/elements/1.1/"><dc:title>An enhanced Python framework for hydrological modeling in alpine catchments: snow hysteresis and glacier ice melt</dc:title><dc:creator>Masten,	Martin	(Avtor)
	</dc:creator><dc:creator>Seelig,	Simon	(Avtor)
	</dc:creator><dc:creator>Vremec,	Matevž	(Avtor)
	</dc:creator><dc:creator>Seelig,	Magdalena	(Avtor)
	</dc:creator><dc:creator>Winkler,	Gerfried	(Avtor)
	</dc:creator><dc:subject>snow model</dc:subject><dc:subject>glacier model</dc:subject><dc:subject>alpine hydrology</dc:subject><dc:subject>Python</dc:subject><dc:subject>snow cover hysteresis</dc:subject><dc:subject>rainfall-runoff modeling</dc:subject><dc:description>Simulating snow cover and glacier ice melt is essential for understanding hydrological processes in high-alpine catchments. We present a new Python extension to the Rainfall-Runoff Modeling Playground (RRMPG) that incorporates two key alpine-specific processes: snow cover hysteresis and glacier ice melt. Snow hysteresis captures the asymmetric evolution of snow-covered area between accumulation and melt periods, while glacier melt modeling is crucial in glacierized catchments due to its strong influence on water balance. The model is tested in two catchments in the ¨Otztal Alps and shows high accuracy in simulating runoff and snow cover dynamics. A multi-objective calibration approach using observed runoff and MODIS snow cover data improves model robustness. Designed for modularity and interoperability, the framework integrates easily with tools for calibration, sensitivity analysis, and data visualization. This open-source extension advances hydrological modeling in complex alpine environments by offering enhanced process representation, flexibility, and compatibility with Python-based workflows.</dc:description><dc:date>2026</dc:date><dc:date>2026-03-23 10:34:58</dc:date><dc:type>Neznano</dc:type><dc:identifier>13350</dc:identifier><dc:identifier>UDK: 556.38:004.438</dc:identifier><dc:identifier>ISSN pri članku: 1873-6726</dc:identifier><dc:identifier>COBISS_ID: 272597251</dc:identifier><dc:identifier>DOI: 10.1016/j.envsoft.2025.106842</dc:identifier><dc:language>sl</dc:language></metadata>
