Hydrologic Prediction through Changes in Soil Moisture and Snowpack: Estimating Natural and Anthropogenic Fluxes
University of Colorado / CIRES
18 July, 10 am, in 2155
Water stored at the Earth surface—in the soil and snow—represents a
window into the future and past, controlling the rate of water transfer
to the atmosphere and rivers, and providing a basis for forecasting.
The first part of this presentation will focus on two applications
using remotely sensed soil moisture to estimate evaporation and
irrigation. Evaporation is an integral component of the water balance,
yet it’s estimation over large areas is limited by observational
scarcity and is hence typically estimated using models. An approach for
producing spatial estimates of evaporation using changes in soil
moisture from NASA’s SMAP satellite will be presented and evaluated at
a set of monitoring sites across the U.S.
Next, variations in remotely sensed soil moisture are evaluated as a
means to estimate irrigation. Water withdrawals for agriculture
represent the single largest consumptive use for many parts of the
U.S., bearing a large anthropogenic footprint on the water and energy
cycles. However, practical challenges exist in estimating irrigation
magnitude and resulting impacts on water supply modeling. A synthetic
data assimilation experiment is presented to estimate irrigation, with
potential errors sources evaluated using land surface outputs in the
place of remote sensing.
The last part of the presentation will focus on how the predictive
value of snowpack-based drought indicators—identified as the most
useful and reliable drought indicator by western U.S. water
stakeholders—are expected change in a warmer world; where projections
show more rain versus snow. Across the western U.S., snow-water
equivalent (SWE) at key dates during the year (e.g., April 1) is
routinely used in water resource planning as it embodies stored water
to be released, through melt, during critical periods later in the
summer. The robustness of these snowpack-based drought indicators will
be assessed under historical and future climate.