New Mexico Geological Society Annual Spring Meeting — Abstracts

Mountainous regions in New Mexico and southern Colorado are vital sources of water for communities, agriculture, and ecosystems throughout the Southwestern United States. In these regions, high‐elevation snowpack provides the majority of annual streamflow and groundwater recharge. However, existing land surface and hydrological models used in large-scale analysis often use grid cells that are too coarse (1-10 km) to capture the land heterogeneity over mountainous terrain, which controls snowmelt, soil moisture, and runoff. Accurately predicting water availability in these regions requires a physically realistic representation of the surface energy balance because radiation (shortwave and longwave) govern snow accumulation, melt timing, soil‐moisture dynamics, and evapotranspiration. However, most land‐surface and hydrologic models still rely on plane‐parallel (1-D) radiation schemes that assume flat, uniformly illuminated terrain. These assumptions break down in complex mountain environments, where slope, aspect, terrain shading, sky-view factors, and terrain reflections strongly modify surface energy inputs. This study aims to improve how these mountain processes are represented in hydrologic models by integrating a land surface model (Noah-MP) with a spatial clustering algorithm (Hydroblocks) to study the land water and energy budget over mountainous terrain at a fine detail (< 100m, “hyper-resolution”), showing how terrain slope, aspect, and elevation affect water storage and flow. The project applies the HydroBlocks-Noah-MP model to mountain watersheds across northern New Mexico and the upper Rio Grande headwaters in southern Colorado for the period 2014-2024. The land domain in each model grid cell will be grouped into clusters, or “hydrologic response units” that share similar terrain, soil, and vegetation properties, capturing the spatial distribution of temperature and solar radiation over complex terrain. To better represent how sunlight and shading influence snowpack and soil temperature over mountainous watersheds, the study incorporates a recently developed scheme describing radiation over mountainous terrain. Model results will be compared with satellite observations from NASA’s Soil Moisture Active Passive satellite (SMAP) mission and Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover to assess model accuracy and performance in representing snow and soil moisture. The expected products of this research include high-resolution maps of soil moisture and snowpack, as well as analyses showing how terrain features control water availability across the region.

References:

1. Chaney, N. W., Metcalfe, P., and Wood, E. F. (2016), “HydroBlocks: A Field-Scale Resolving Land Surface Model for Application Over Continental Extents,” Hydrological Processes, 30, 3543–3559. DOI: 10.1002/hyp.10891.
2. Hao, D., Bisht, G., Li, L., & Leung, L. R. (2025). Representing fine‐scale topographic effects on surface radiation balance in hyper‐resolution land surface models. Journal of Advances in Modeling Earth Systems, 17, e2025MS004987. doi.org/10.1029/2025MS004987
3. Zorzetto, E., Malyshev, S., Chaney, N., Paynter, D., Menzel, R., & Shevliakova, E. (2023). Effects of complex terrain on the shortwave radiative balance: A sub-grid-scale parameterization for the GFDL Earth System Model version 4.1. Geoscientific Model Development, 16(5), 1937–1960. doi.org/10.5194/gmd-16-1937-2023