Julie A. Vano

Hydrologic Sensitivities of Colorado River Runoff to Changes in Precipitation and Temperature

The Colorado River is the primary water source for much of the rapidly growing southwestern United States. Recent studies have projected reductions in Colorado River flows from less than 10% to almost 50% by midcentury because of climate change—a range that has clouded potential management responses. These differences in projections are attributable to variations in climate model projections but also to differing land surface model (LSM) sensitivities. This second contribution to uncertainty—specifically, variations in LSM runoff change with respect to precipitation (elasticities) and temperature (sensitivities)—are evaluated here through comparisons of multidecadal simulations from five commonly used LSMs (Catchment, Community Land Model, Noah, Sacramento Soil Moisture Accounting model, and Variable Infiltration Capacity model) all applied over the Colorado River basin at 1/88 latitude by longitude spatial resolution. The annual elasticity of modeled runoff (fractional change in annual runoff divided by fractional change in annual precipitation) at Lees Ferry ranges from two to six for the different LSMs. Elasticities generally are higher in lower precipitationand/orrunoffregimes;hence,the highestvaluesare formodelsbiasedlow in runoffproduction,and the range of elasticities is reduced to two to three when adjusted to current runoff climatology. Annual temperature sensitivities (percent change in annual runoff per degree change in annual temperature) range from declines of 2% to as much as 9% per degree Celsius increase at Lees Ferry. For some LSMs, small areas, primarily at midelevation, have increasing runoff with increasing temperature; however, on a spatial basis, most sensitivities are negative.

Understanding uncertainties in future Colorado River streamflow

The Colorado River is the primary water source for more than 30 million people in the United States and Mexico. Recent studies that project streamf low changes in the Colorado River all project annual declines, but the magnitude of the projected decreases range from less than 10% to 45% by the mid-twenty-first century. To understand these differences, we address the questions the management community has raised: Why is there such a wide range of projections of impacts of future climate change on Colorado River streamflow, and how should this uncertainty be interpreted? We identify four major sources of disparities among studies that arise from both methodological and model differences. In order of importance, these are differences in 1) the global climate models (GCMs) and emission scenarios used; 2) the ability of land surface and atmospheric models to simulate properly the high-elevation runoff source areas; 3) the sensitivities of land surface hydrology models to precipitation and temperature changes; ...

Characterizing Uncertainty of the Hydrologic Impacts of Climate Change

The high climate sensitivity of hydrologic systems, the importance of those systems to society, and the imprecise nature of future climate projections all motivate interest in characterizing uncertainty in the hydrologic impacts of climate change. We discuss recent research that exposes important sources of uncertainty that are commonly neglected by the water management community, especially, uncertainties associated with internal climate system variability, and hydrologic modeling. We also discuss research exposing several issues with widely used climate downscaling methods. We propose that progress can be made following parallel paths: first, by explicitly characterizing the uncertainties throughout the modeling process (rather than using an ad hoc “ensemble of opportunity”) and second, by reducing uncertainties through developing criteria for excluding poor methods/models, as well as with targeted research to improve modeling capabilities. We argue that such research to reveal, reduce, and represent uncertainties is essential to establish a defensible range of quantitative hydrologic storylines of climate change impacts.

Seasonal hydrologic responses to climate change in the Pacific Northwest

Increased temperatures and changes in precipitation will result in fundamental changes in the seasonal distribution of streamflow in the Pacific Northwest and will have serious implications for water resources management. To better understand local impacts of regional climate change, we conducted model experiments to determine hydrologic sensitivities of annual, seasonal, and monthly runoff to imposed annual and seasonal changes in precipitation and temperature. We used the Variable Infiltration Capacity (VIC) land-surface hydrology model applied at 1/16° latitude-longitude spatial resolution over the Pacific Northwest (PNW), a scale sufficient to support analyses at the hydrologic unit code eight (HUC-8) basin level. These experiments resolve the spatial character of the sensitivity of future water supply to precipitation and temperature changes by identifying the seasons and locations where climate change will have the biggest impact on runoff. The PNW exhibited a diversity of responses, where transitional (intermediate elevation) watersheds experience the greatest seasonal shifts in runoff in response to cool season warming. We also developed a methodology that uses these hydrologic sensitivities as basin-specific transfer functions to estimate future changes in long-term mean monthly hydrographs directly from climate model output of precipitation and temperature. When principles of linearity and superposition apply, these transfer functions can provide feasible first-order estimates of the likely nature of future seasonal streamflow change without performing downscaling and detailed model simulations.

A sensitivity-based approach to evaluating future changes in Colorado River discharge

Projections of a drier, warmer climate in the U.S. Southwest would complicate management of the Colorado River system—yet these projections, often based on coarse resolution global climate models, are quite uncertain. We present an approach to understanding future Colorado River discharge based on land surface characterizations that map the Colorado River basin’s hydrologic sensitivities (e.g., changes in streamflow magnitude) to annual and seasonal temperature and precipitation changes. The approach uses a process-based macroscale land surface model (LSM; in this case, the Variable Infiltration Capacity hydrologic model, although methods are applicable to any LSM) to develop sensitivity maps (equivalent to a simple empirical model), and uses these maps to evaluate long-term annual streamflow responses to future precipitation and temperature change. We show that global climate model projections combined with estimates of hydrologic sensitivities, estimated for different seasons and at different change increments, can provide a basis for approximating cumulative distribution functions of streamflow changes similar to more common, computationally intensive full-simulation approaches that force the hydrologic model with downscaled future climate scenarios. For purposes of assessing risk, we argue that the sensitivity-based approach produces viable first-order estimates that can be easily applied to newly released climate information to assess underlying drivers of change and bound, at least approximately, the range of future streamflow uncertainties for water resource planners.

Impacts of Climate Variation and Catchment Area on Water Balance and Lake Hydrologic Type in Groundwater-Dominated Systems: A Generic Lake Model

Lakes are a major geologic feature in humid regions, and multiple lake hydrologic types exist with varying physical and chemical characteristics, connections among lakes, and relationships to the landscape. The authors developed a model of water fluxes through major components of groundwater-dominated lake catchments in a region containing thousands of lakes, the Northern Highland Lake District (NHLD) of northern Wisconsin and the Upper Peninsula of Michigan. The model was calibrated with data from widely differing lakes using the same set of simple equations to represent the hydrologic type, water residence time, and amount and timing of stream and groundwater flows of representative lakes in todays climate. The authors investigated the sensitivity of the water balance of a set of three connected

Climate change and lakes: Estimating sensitivities of water and carbon budgets

[1] As humanity develops strategies to manage and adapt to climate change, potential changes to carbon cycles are of increasing interest. The potential sensitivity of carbon sources and sinks in lakes may be of global importance, yet the direction and magnitude of possible changes are poorly understood across entire lake-rich regions. We used a spatially explicit simulation model of water and carbon cycling to explore the potential behavior of 6739 lakes and watersheds to changes in climate. Our study site was the Northern Highland Lake District of northern Wisconsin and the Upper Peninsula of Michigan. We developed two perturbation scenarios built from observed extreme high and low precipitation and evaporation values. Despite a spatially uniform change in precipitation across the region, individual lakes responded differently. Hydrologic responses were mostly predictable at both individual and regional scales, but the routing of carbon in lakes was both more sensitive and varied. We estimate that in today’s climate, 7.3E+10 g of carbon are vented annually from lake surfaces in the District to the atmosphere. Compared to today’s climate, total regional flux of carbon from lake surfaces was 31% higher in the wet scenario and 45% lower in the dry scenario. Some measures of carbon fluxes (such as net ecosystem production) appear to change uniformly and gradually at the regional scale, though aggregate change was driven primarily by considerable changes in relatively few large lakes. The simulations demonstrate that simple, spatially homogeneous perturbations in these complex connected watersheds can have both predictable and surprising effects.