Abstract. Climate models predict amplified warming at high elevations in low latitudes, making tropical glacierized regions some of the most vulnerable hydrological systems in the world. Observations reveal decreasing streamflow due to retreating glaciers in the Andes, which hold 99% of all tropical glaciers. However, the timescales over which meltwater contributes to streamflow and the pathways it takes -surface and subsurface -remain uncertain, hindering our ability to predict how shrinking glaciers will impact water resources. Two major contributors to this uncertainty are the sparsity of hydrologic mea-5 surements in tropical glacierized watersheds and the complication of hydrograph separation where there is year-round glacier melt. We address these challenges using a multi-method approach that employs repeat hydrochemical mixing model analysis, hydroclimatic time series analysis, and integrated watershed modeling. Each of these approaches interrogates distinct timescale relationships among meltwater, groundwater, and stream discharge. Our results challenge the commonly held conceptual model that glaciers buffer discharge variability. Instead, in a sub-humid watershed on Volcán Chimborazo, Ecuador, meltwater drives 10 nearly all the variability in discharge (Pearson correlation coefficient of 0.89 in simulations), with glaciers contributing a broad range of 20-60% or wider of discharge, mostly (86%) through surface runoff on hourly timescales, but also through infiltration that increases annual groundwater contributions by nearly 20%. We further found that rainfall may enhance melt contributions to discharge at timescales that complement melt generation, possibly explaining why minimum discharge occurred at the study site during warm but dry El Niño conditions, which typically heighten melt in the Andes. Our findings caution against extrap-15 olations from isolated measurements: stream discharge and meltwater contributions in tropical glacierized systems can change substantially at hourly to interannual timescales, due to climatic variability and surface to subsurface flow processes.

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Abstract.Water flow through catchments sustains ecosystems and human activity, shapes landscapes, and links climate to the outermost layers of the solid Earth. The profound importance of water moving between the atmosphere and aquifers has led to efforts to develop and maintain coupled models of surface water and groundwater. However, developing inputs to these models is usually time-consuming and requires extensive knowledge of software engineering, often prohibiting their use by many researchers 5 and water managers, and thus reducing these models' potential to promote science-driven decision-making in an era of global change and increasing water-resource stress. In response to this need, we have developed GSFLOW-GRASS, a straightforward set of open-source tools that develops inputs for and runs GSFLOW, the U.S. Geological Survey's coupled groundwatersurface-water flow model. As inputs, GSFLOW-GRASS requires at a minimum a digital elevation model, a precipitation and temperature record, and estimates of channel parameters and hydraulic conductivity. GSFLOW-GRASS is written in Python 10 as a set of (1) GRASS GIS extensions, (2) input-file-builder scripts, and (3) visualization scripts. We developed a set of custom GRASS GIS commands that generate "hydrologic response units" for surface water, discretized topologically as sub-basins of the tributary network; build the MODFLOW grid; and add necessary attributes to each of these geospatial units. These GIS outputs are interpreted by a second set of Python scripts, which link them to hydrologic variables, build inputs to GSFLOW, and run GSFLOW. Lastly, GSFLOW output files are used to produce figures and time-lapse movies of simulation results using 15 a third set of post-processing Python scripts. We demonstrate the broad applicability of these tools to diverse settings through examples based on: the high Peruvian Andes, the Channel Islands of California, and the formerly-glaciated Upper Mississippi valley in Minnesota . 1Geosci. Model Dev. Discuss., https://doi

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