A Multi-Timescale Evaluation of Global Hydrologic Phenomena Using Observations and Models

Hydrologic extremes occur on multiple timescales, from short-duration floods to multi-year drought, and have become more frequent and severe across many regions over the past several decades. Here, simulations of historical and future hydroclimate derived from general circulation models (GCMs) are used to assess the direction of historical trends into the 21st century as global temperatures rise. A new generation of GCM simulations were deployed as part of the Coupled Intercomparison Model Project &ndash; Phase 6 (CMIP6), which allows evaluation of both (i) the fidelity of the simulated hydroclimate in state-of-the-art climate models and (ii) potential future changes to hydrologic extremes. This dissertation analyzes future changes in hydroclimatic phenomena across three temporal scales ranging from daily wet extremes to multi-year surface water deficits. The first chapter leverages observations of daily precipitation from 4,800 weather stations and three gridded hydroclimate datasets to explore the fidelity of GCM simulated large-storm dominance across the Western United States. The focus is on quantifying how refining the spatial resolution of GCMs might improve the simulation of precipitation that occur on spatial scales ranging from tens to hundreds of kilometers. Transitioning from the daily to monthly timescale, the following chapter describes the creation of a global dataset of historical and future projected evaporative demand from an ensemble of CMIP6 GCM simulations. The development of this dataset was motivated by the need to understand how future increases in net-surface radiation and changes to advection might increase evaporative demand and potentially reduce surface water availability across the globe. Lastly, on the seasonal to multi-year timescale, CMIP6 GCM projections are used to evaluate future global &ldquo;storylines&rdquo; of hydrologic drought. These storylines combine long-term trends in runoff with multiple co-occurring changes to the frequency, severity, and seasonal timing of drought to determine which regions of the globe are at the greatest risk of future drought-related water stress. While the analyses of this dissertation focus on hydrological processes at different timescales, they all share a common goal improving understanding of the utility and usability of climate model projections in planning for future changes to surface water availability across the globe.</p

Growing impact of wildfire on western US water supply

Streamflow often increases after fire, but the persistence of this effect and its importance to present and future regional water resources are unclear. This paper addresses these knowledge gaps for the western United States (WUS), where annual forest fire area increased by more than 1,100% during 1984 to 2020. Among 72 forested basins across the WUS that burned between 1984 and 2019, the multibasin mean streamflow was significantly elevated by 0.19 SDs (P 20% of forest area burned in a year, streamflow over the first 6 water years postfire increased by a multibasin average of 0.38 SDs, or 30%. Postfire streamflow increases were significant in all four seasons. Historical fire–climate relationships combined with climate model projections suggest that 2021 to 2050 will see repeated years when climate is more fire-conducive than in 2020, the year currently holding the modern record for WUS forest area burned. These findings center on relatively small, minimally managed basins, but our results suggest that burned areas will grow enough over the next 3 decades to enhance streamflow at regional scales. Wildfire is an emerging driver of runoff change that will increasingly alter climate impacts on water supplies and runoff-related risks

Observed and Projected Snowmelt Runoff in the Upper Rio Grande in a Changing Climate

As climate has warmed over the past half century, the strength of the covariance between interannual snowpack and streamflow anomalies in the Rio Grande headwaters has decreased. This change has caused an amplification of errors in seasonal streamflow forecasts using traditional statistical forecasting methods, based on the diminishing correlation between peak snow water equivalent (SWE) and subsequent snowmelt runoff. Therefore, at a time when water resources in south-western North America are becoming scarcer, water supply forecasters need to develop prediction schemes that account for the dynamic nature of the relationship between precipitation, temperature, snowpack and streamflow. We quantify temporal changes in statistical predictive models of streamflow in the upper Rio Grande basin using observed data, and interpret the results in terms of processes that control runoff season discharge. We then compare these observed changes to corresponding statistics in downscaled global climate models (GCMs), to gain insight into which GCMs most appropriately replicate the dynamics of interannual streamflow variability represented by the hydro-climate parameters in the headwaters of the Rio Grande. We quantify how the correlations among temperature, precipitation, SWE, and v streamflow have changed over the last half century within the local climatic and hydrological system. We then assess different long-term GCM-based streamflow projections by their ability to reproduce observed relationships between climate and streamflow, and thereby better constrain projections of future flows as climate warms in the 21st century. In the Rio Grande system, we find that spring season precipitation increasingly contributes to the variability of runoff generation as the contribution of snowpack declines

Evaluating Large‐Storm Dominance in High‐Resolution GCMs and Observations Across the Western Contiguous United States

Abstract Extreme precipitation events are projected to increase in frequency across much of the land‐surface as the global climate warms, but such projections have typically relied on coarse‐resolution (100–250 km) general circulation models (GCMs). The ensemble of HighResMIP GCMs presents an opportunity to evaluate how a more finely resolved atmosphere and land‐surface might enhance the fidelity of the simulated contribution of large‐magnitude storms to total precipitation, particularly across topographically complex terrain. Here, the simulation of large‐storm dominance, that is, the number of wettest days to reach half of the total annual precipitation, is quantified across the western United States (WUS) using four GCMs within the HighResMIP ensemble and their coarse resolution counterparts. Historical GCM simulations (1950–2014) are evaluated against a baseline generated from station‐observed daily precipitation (4,803 GHCN‐D stations) and from three gridded, observationally based precipitation data sets that are coarsened to match the resolution of the GCMs. All coarse‐resolution simulations produce less large‐storm dominance than in observations across the WUS. For two of the four GCMs, bias in the median large‐storm dominance is reduced in the HighResMIP simulation, decreasing by as much as 62% in the intermountain west region. However, the other GCMs show little change or even an increase (+28%) in bias of median large‐storm dominance across multiple sub‐regions. The spread in differences with resolution amongst GCMs suggests that, in addition to resolution, model structure and parameterization of precipitation generating processes also contribute to bias in simulated large‐storm dominance

Growing impact of wildfire on western US water supply.

Streamflow often increases after fire, but the persistence of this effect and its importance to present and future regional water resources are unclear. This paper addresses these knowledge gaps for the western United States (WUS), where annual forest fire area increased by more than 1,100% during 1984 to 2020. Among 72 forested basins across the WUS that burned between 1984 and 2019, the multibasin mean streamflow was significantly elevated by 0.19 SDs (P &lt; 0.01) for an average of 6 water years postfire, compared to the range of results expected from climate alone. Significance is assessed by comparing prefire and postfire streamflow responses to climate and also to streamflow among 107 control basins that experienced little to no wildfire during the study period. The streamflow response scales with fire extent: among the 29 basins where &gt;20% of forest area burned in a year, streamflow over the first 6 water years postfire increased by a multibasin average of 0.38 SDs, or 30%. Postfire streamflow increases were significant in all four seasons. Historical fire-climate relationships combined with climate model projections suggest that 2021 to 2050 will see repeated years when climate is more fire-conducive than in 2020, the year currently holding the modern record for WUS forest area burned. These findings center on relatively small, minimally managed basins, but our results suggest that burned areas will grow enough over the next 3 decades to enhance streamflow at regional scales. Wildfire is an emerging driver of runoff change that will increasingly alter climate impacts on water supplies and runoff-related risks