Abstract

Variation in water supply prediction among mountain watersheds of the western US and corresponding differences in moisture pathways

Sarah Rogers — Fri, 27 Mar 2026 21:20:13 +0000

Variation in water supply prediction among mountain watersheds of the western US and corresponding differences in moisture pathways Sarah Rogers Fri, 03/27/2026 - 15:20 Jeremy Barroll

Western US water agencies can benefit from seasonal water supply forecasts to optimize their reservoir operations for water supply and flood protection. However, seasonal water supply in the western US is difficult to predict multiple months ahead, especially in the mid-latitudes of the western US where prediction varies widely by immediate location and derives little skill from the El Niño-Southern Oscillation (ENSO). We investigate how seasonal water supply prediction using sea surface temperatures (SST) varies between adjacent small to medium size mountain watersheds within several regions of the western US, and how this variation relates to differences in moisture pathways. Differences between rain-dominated and snow-dominated basins are also considered. Prediction centers, or areas of the oceans where SSTs have significant predictive skill for seasonal water supply, are identified separately for each watershed to further optimize prediction, since prominent crests can separate the influence of incoming moisture. Winter and spring precipitation, and co-occurring snow-water equivalent depth (SWE), are compared for their predictability by SSTs and usefulness in predicting streamflow. A particle tracking model is used to evaluate moisture pathways to watersheds and to compare their prevalence during periods characterized by positive and negative SST anomalies at identified prediction centers. Particle tracks and moisture sources are compared for storm events before and after peak SWE to understand physical mechanisms that explain seasonal differences in SST-water supply relationships. This work may improve prediction of water supply and understanding of moisture pathways for small watersheds, which can be masked via procedures to aggregate watersheds into larger regions.

Jeremy Barroll · CEAE · PhD Student

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Changes in seasonal snow and downstream drought predictability: an examination of projected western U.S. water resources

Sarah Rogers — Fri, 27 Mar 2026 21:16:03 +0000

Changes in seasonal snow and downstream drought predictability: an examination of projected western U.S. water resources Sarah Rogers Fri, 03/27/2026 - 15:16 Kaitlyn Bishay

Informed management of drought within the western U.S. has long been conditioned on the status of seasonal snowpack, which serves as an early indicator of available water supplies and comprises the majority of warm-season runoff. In this region, projected shifts in temperature, precipitation magnitude, and precipitation phase (e.g., more precipitation falling as rain) are expected to lead to increased uncertainty in the timing and magnitude of snow and, in turn, a reduced ability to forecast drought. For a range of future projections (i.e., CMIP6 ensemble members), we quantify shifts in the timing of seasonal snow cover and the effect of declining snow resources on melt-driven runoff. We train regional-scale Long Short-Term Memory (LSTM) neural networks on a large sample of basins using daily meteorology and basin attributes (elevation, SWE/P, etc.) for four discrete time periods and report changes in the fidelity of streamflow predictions at annual and seasonal (April-July) scales. We examine drought predictability across three distinct snow regimes—coastal (n=131 basins), intermountain (n=74 basins), and continental (n=151 basins)—to identify regions with increased risk resulting from decreasing snowpack. While this analysis spans the western U.S., we recognize that drought stresses are not unique to the region. By quantifying projected changes in the ability of snow information to predict seasonal streamflow—and therefore, drought conditions—we seek to illuminate whether the relationships that dominate our current understanding of global snow-dominated water resources will remain vital in their observation, prediction, and management in the coming decades.

Kaitlyn Bishay · CEAE · PhD Student

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Exploring the Use of Vulnerability-Based Analyses with Classification and Regression Trees in Reclamation's Mid-Term Operational Projections

Sarah Rogers — Fri, 27 Mar 2026 21:09:50 +0000

Exploring the Use of Vulnerability-Based Analyses with Classification and Regression Trees in Reclamation's Mid-Term Operational Projections Sarah Rogers Fri, 03/27/2026 - 15:09 Zachary Carpenter

The Bureau of Reclamation (Reclamation) projects 2 – 5-year Colorado River Basin (CRB) system conditions for stakeholders using their Colorado River Mid – Term Modeling System (CRMMS). As inputs, this model utilizes 30, 5 – year traces of simulated streamflow generated by the Colorado Basin River Forecasting Center using a historic record (1991 – 2020) of precipitation and temperature data. The 30 inflow traces result in 30 output traces of system conditions, which are together used as an ensemble to estimate probabilities of system outcomes (e.g. 30% of the traces showing Lake Powell falling below 3500 feet indicates a “30% chance” of this happening). The limited number of traces and probabilistic analysis in the 2 – 5 year forecasts of system conditions sometimes lack the degree of skill useful to stakeholders. We therefore propose providing stakeholders with a different form of analysis and the usage of a new inflow data set. Vulnerability analyses use factor – mapping algorithms to connect projected system conditions of interest to the characteristics of the model inputs that caused them; much of the prior work in vulnerability analysis has typically focused on a long-term planning context. This research seeks to adapt these methods to Reclamation’s mid-term operational CRB projections. First, we adapt an expanded set of inflow traces that represent a wide range of plausible conditions, derived from climate model outputs and other sources. We then define a critically low Lake Powell pool elevation threshold as our failure condition of interest and classify the CRMMS output traces as ‘failures’ or ‘successes’ based on whether that threshold is crossed in each output trace. We create multiple Classification and Regression Tree (CART) 91��Ҹ� that discover characteristics of the inflow dataset that are likely to cause failure conditions, defined over different time intervals (e.g., in the next 12 months, or over the entire modeling period). Each CART model identifies the inflow factors/characteristics that are the strongest indicators of the failure conditions for the specific forecasted time interval. Initial results indicate that the cumulative streamflow volumes ahead of and/or in the same year as the failure condition are strong indicators of system failures. Furthermore, annual inflow volumes below approximately 70 – 75% of the historic record (1991 – 2020) annual average are commonly linked to our failure condition.

Authors:

Zachary Carpenter, Joseph Kasprzyk, Edith Zagona

Zachary Carpenter, Joseph Kasprzyk, Edith Zagona · CEAE · MS Student and Faculty

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The 2026 water year: an analog for emerging snow drought in the Upper Colorado River Basin

Sarah Rogers — Fri, 27 Mar 2026 21:07:54 +0000

The 2026 water year: an analog for emerging snow drought in the Upper Colorado River Basin Sarah Rogers Fri, 03/27/2026 - 15:07 Sydney Carr

The western United States has emerged as a global hotspot for snow drought, posing a growing threat to water availability in the Upper Colorado River Basin (UCRB), where high-elevation snowpack generates the majority of Colorado River streamflow. Record-low snow water equivalent (SWE) during the anomalously warm, dry 2025-26 winter highlights the urgency of this risk, yet key uncertainties remain in the timing and magnitude of future snowpack deficits. Using WRF-CESM2, a high-resolution (3-km) ensemble of dynamically downscaled climate simulations (1980-2100), we define an impact-based threshold grounded in 2026 snowpack conditions (~55% of historical median peak SWE) and evaluate changes in the frequency, persistence, and clustering of threshold-exceeding years. We show that low-snow years comparable to or more extreme than 2026 shift from rare, isolated events in the historical period to frequent, multi-year sequences by late century. This transition marks a fundamental shift in snowpack reliability in runoff-generating headwaters, with direct implications for water supply planning in the Colorado River Basin.

Sydney Carr · GEOG · PhD

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Evaluating Meteorological Controls on Wet Bulb Globe Temperature Sensitivity and Implications for Urban Heat Stress

Sarah Rogers — Fri, 27 Mar 2026 21:05:35 +0000

Evaluating Meteorological Controls on Wet Bulb Globe Temperature Sensitivity and Implications for Urban Heat Stress Sarah Rogers Fri, 03/27/2026 - 15:05 Cambria Danielski

Urban heat stress poses a direct threat to the public health of urban communities in arid and semi-arid regions. Heat stress can be determined using Wet Bulb Globe Temperature (WBGT), which is calculated by integrating meteorological data including wet bulb temperature, globe temperature, and dry bulb temperature. By incorporating these variables, WBGT captures the “feel like” temperature perceived by the human body, allowing heat stress to be assessed on an index scale. Over the course of a three-month urban heat field campaign (June-August 2025), a Kestrel 5400 heat sensor measurement tool was utilized to measure WBGT across five varying landscape ground cover types - traditional grass, native grass, artificial turf, gravel, and wood mulch - at five parks throughout the Denver, Colorado area. I performed a sensitivity analysis by developing meteorological baseline conditions derived from a single representative field day, adjusting air temperature and relative humidity across a ±30% range and wind speed across a -100/+300% range to isolate and better understand their individual influence on WBGT. Initial results indicate that air temperature influences WBGT most substantially. Vegetation landscape cover types play a critical role in urban heat stress, highlighting the need for future heat mitigation strategies to be assessed.

Cambria Danielski · CEAE · Undergraduate Student

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Examination of price elasticity of residential water in Colorado

Sarah Rogers — Fri, 27 Mar 2026 21:00:42 +0000

Examination of price elasticity of residential water in Colorado Sarah Rogers Fri, 03/27/2026 - 15:00 Jade Foley-Pike

As the uncertainty of water supply looms over Colorado, water providers are seeking to reduce water demand using various methods, such as through the implementation of conservation-based rate structures. These include, for example, increasing block rates and allocation-based rates, which increase the marginal (per unit) price of water as usage increases past established thresholds. However, questions remain around how water use actually changes in response to changes in the established rate structure.

This study seeks to quantify the short-term water price elasticity of residential water use and examine the effectiveness of implementing new rate structures for conservation. We are using anonymized household water use and historical rate data provided by Colorado water utilities, focusing first on single-family households in the cities of Westminster and Fort Collins. From this, we calculated the water price elasticity of each household for a given month across significant rate changes.

According to existing literature, water price elasticity is expected to be within a range of -1 (which indicates a decrease in water use as price increases) to 0 (which indicates inelasticity). Our preliminary results indicate near-inelastic water use in winter months, but variable elasticities in summer months that do not always fall within the expected range. This can be due to several factors, including household income, climate and weather, policies, programs, and more.

Jade Foley-Pike · CEAE · MS Student

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Every winter is different in the mountains! Conditions under ice in mountain lakes.

Sarah Rogers — Fri, 27 Mar 2026 20:55:34 +0000

Every winter is different in the mountains! Conditions under ice in mountain lakes. Sarah Rogers Fri, 03/27/2026 - 14:55 Katie Gannon

Winters are changing rapidly with warming temperatures, declining ice duration and dwindling winter snowpack. Ice covers more than half of the world’s lakes each winter, and conditions under ice can impact ecosystem function in subsequent ice-free seasons. Ice cover and inverse stratification impede gas exchange between lake water and the atmosphere, and as a result, respiration can deplete oxygen concentrations under ice. Low oxygen concentrations can impact lake ecology, by creating physiological stress for animals, and biogeochemistry, by shaping redox conditions and nutrient release from sediments. However, the direct impacts of variable snowfall, winter temperatures, and ice duration on oxygen concentrations under lake ice are still poorly understood because multi-year, year-round data are rare. In this study we use 16 lake-years of high frequency temperature and oxygen observations from three lakes of varying morphometry in the southern Rocky Mountains to investigate the drivers of both inter- and intra-annual patterns of bottom-water oxygen concentration under ice. Specifically, we investigate how snowfall, freeze thaw-cycles, and incoming solar radiation impact the light environment and, in turn, oxygen concentration under ice. We found a high degree of inter and intra-annual variability in oxygen dynamics. Additionally, we provide evidence that snow accumulation on the lake surface is associated with decreased light availability and declines in oxygen concentrations, particularly early during the first half of winter. Additionally, in some lake-years we see evidence for hydrologically-mediated or convective mixing that re-oxygenates the bottom waters in mid-winter or the month(s) leading up to ice-clearance. Our study may inform predictions about how lake ecosystems will respond to future changes in winter conditions.

Katie Gannon · EBIO · PhD Student

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Residence time in a chain of Arctic Alaskan lagoons

Sarah Rogers — Fri, 27 Mar 2026 20:51:23 +0000

Residence time in a chain of Arctic Alaskan lagoons Sarah Rogers Fri, 03/27/2026 - 14:51 Tina Geller

The coastal Arctic is experiencing environmental change, influencing water quantity via shifting freshwater inputs, circulation, and biogeochemical dynamics. Residence time is often used to link material transport to water quality and biogeochemical processes, as it influences the retention and transformation of water and associated material.

To characterize residence time, we analyze its drivers and patterns in five connected lagoons around Kaktovik in Arctic Alaska for nearly ice-free conditions in 2019 (Jul-Sep) using a hydrodynamic model (ROMS). These lagoons vary in river influence, shelf connectivity, and water depth. The model accounts for winds, rivers, shelf circulation, tides, and bathymetry, and tracks neutrally buoyant particles released throughout the lagoons.

Preliminary results suggest that residence time is generally longer in lagoons that are deeper and more protected from nearby ocean currents. These protected lagoons had more uniformly high residence times of two to three weeks, while the residence time in shelf-connected lagoons ranged from a few days to about a week. Winds and rivers were the main drivers of residence time, and their variability caused residence time to vary in time. Overall, our results suggest that Arctic Alaskan lagoons may respond differently to changing environmental conditions based on the bathymetry and geometry of bays and inlets, and underscore the importance of considering both physical transport and retention when assessing change in the coastal Arctic.

Tina Geller · ATOC · PhD Student

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Evaluating the Effects of Hydrologic Model Choice on Mid-century River Warming in Southeast Alaska

Sarah Rogers — Fri, 27 Mar 2026 20:47:45 +0000

Evaluating the Effects of Hydrologic Model Choice on Mid-century River Warming in Southeast Alaska Sarah Rogers Fri, 03/27/2026 - 14:47 Colin Gilbert

Southeast Alaska represents a highly variable hydrologic environment. Headwaters are dominated by alpine glaciers and larger river basins envelop significant glacier area. Daily estimates of streamflow and river temperature provide useful insight into regions undergoing rapid change. Here we present a river temperature model framework that adapts results from two different hydrologic 91��Ҹ� applied in Southeast Alaska. We force the physically based River Basin Model with energy inputs from a 4 km resolution Regional Arctic System Model (RASM), but vary streamflow inputs based on output from two land surface 91��Ҹ�: 1) a coupled simulation of RASM-CTSM at 4 km and 2) an offline run of RASM-WRF Hydro Glacier at 1 km. The land surface 91��Ҹ� primarily differ in glacier treatment, RASM-CTSM uses a traditional five-layer snow model to account for glacial processes, while the RASM-WRF Hydro Glacier model applies the CROCUS snow model for improved glacial snow and firn simulations in river basins with glacier presence. The RASM-WRF Hydro Glacier employs the three-layer snow model from the NoahMP land surface for non-glaciated regions. The 91��Ҹ� were run for a historical (1991-2020) period, including a parameter sensitivity test for river temperature, and then applied to a mid-century (2035-2064) climate scenario. We assessed model simulations against gage observations at seven basins. In historical simulations, RASM-WRF Hydro Glacier (bias = X%; KGE = Y) outperform RASM-CTSM (bias = X%; KGE = Y) in glaciated basins, while producing nearly identical results in non-glaciated basins, indicating that the advanced treatment of glacier snow and ice by RASM-WRF Hydro Glacier produces more accurate results. Estimates of future changes in discharge and stream temperature, together with glacier contributions to runoff, provide a holistic assessment of hydrologic system change in Southeast Alaska, useful for future investigations of the impacts of hydrological processes in this glacier-dominated landscape.

Colin Gilbert · GEOG · MS Student

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Comparison of human perceived temperature between in-situ and reanalysis datasets in Denver, Colorado

Sarah Rogers — Fri, 27 Mar 2026 20:43:15 +0000

Comparison of human perceived temperature between in-situ and reanalysis datasets in Denver, Colorado Sarah Rogers Fri, 03/27/2026 - 14:43 Nicholas Guthro

Urban heat stress can be caused by transitioning from natural, non-urbanized environments to dense urban environments, as this increases the number of buildings, roads, and other infrastructure. A commonly used metric to study heat stress is Wet Bulb Globe Temperature (WBGT), which is a “feels like” temperature that incorporates wind speed, relative humidity, cloud cover, and temperature. Over a three-month field campaign in Denver, Colorado, in the summer of 2025, Kestrel 5400 heat sensors were used to measure WBGT over grass, native grass, wood mulch, gravel, and artificial grass in five parks. To better understand the individual effects of landscapes, a regional WBGT must be calculated from ERA5 climate and weather data. This study uses wind speed, dew point temperature, air temperature, and net solar radiation to determine a regional WBGT value for each park examined. This WBGT can then be compared with the value observed in the field, allowing comparison of values across different parks and days. This work is important for assessing the environmental effects of waterwise landscapes that may be implemented in arid or semi-arid cities to reduce municipal outdoor water use.

Nick Gurthro · CEAE · PhD Student

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