How Much Water Is Evaporated Across California? A Multiyear Assessment Using a Biophysical Model Forced With Satellite Remote Sensing Data

Abstract

California is expected to experience great spatial/temporal variations evaporation. These variations arise from strong north‐south, east‐west gradients in rainfall and vegetation, strong interannual variability in rainfall (±30%) and strong seasonal variability in the supply and demand for moisture. We used the Breathing Earth System Simulator to evaluate the rates and sums of evaporation across California, over the 2001–2017 period. Breathing Earth System Simulator is a bottom‐up, biophysical model that couples subroutines that calculate the surface energy balance, photosynthesis, and stomatal conductance. The model is forced with high‐resolution remote sensing data (1 km).The questions we address are as follows: How much water is evaporated across the natural and managed ecosystems of California? How much does evaporation vary during the booms and busts in annual rainfall? and Is evaporation increasing with time due to a warming climate? Mean annual evaporation, averaged over the 2001–2017 period, was relatively steady (393 ± 21 mm/year) given the high interannual variation in precipitation (519 ± 140 mm/year). No significant trend in evaporation at the statewide level was detected over this time period, despite a background of a warming climate. Irrigated agricultural crops and orchards, at 1‐km scale, use less water than inferred estimates for individual fields. This leaves the potential for sharing water, a scarce resource, more equitably among competing stakeholders, for example, farms, fish, people, and ecosystems.

Low Subsurface Water Storage Capacity Relative to Annual Rainfall Decouples Mediterranean Plant Productivity and Water Use From Rainfall Variability

“…To calculate S = P -ET -Q, we rely on gridded precipitation (PRISM Climate Group, Oregon State University, http://prism.oregonstate.edu), a process-based ET model driven by remotely sensed data (Baldocchi et al, 2019;Ryu et al, 2011), and U.S. Geological Survey (USGS) runoff records. To calculate S = P -ET -Q, we rely on gridded precipitation (PRISM Climate Group, Oregon State University, http://prism.oregonstate.edu), a process-based ET model driven by remotely sensed data (Baldocchi et al, 2019;Ryu et al, 2011), and U.S. Geological Survey (USGS) runoff records.…”

Plants as sensors: vegetation response to rainfall predicts subsurface water storage capacity in Mediterranean climates

“…During the dry season months of June, July, and August negligible rain falls, and therefore variability in ET is likely attributable to storage conditions. We therefore use estimates of actual evapotranspiration during these months in the prediction of S max , and obtain these estimates from a biophysical evapotranspiration model that has been evaluated across California (Baldocchi et al, 2019). This ET dataset is available from 2001 to 2017.…”

“…A second limitation of the method is the reliance on remotely sensed measures of vegetation water use. We used the BESS evapotranspiration dataset presented for California in Baldocchi et al (2019), which importantly does not include any specific representation of the subsurface. Other evapotranspiration models which explicitly incorporate soil water balance modeling for ET estimation should not be used for the method presented here (Martens et al, 2017), precisely because they make assumptions about the subsurface water storage capacity that our approach is designed to estimate.…”

BESS-STAIR: a framework to estimate daily, 30-meter, and allweather crop evapotranspiration using multi-source satellite data for the U.S. Corn Belt

“…including the 5-km resolution global radiation (Rg) and photosynthetically active radiation (PAR) and diffuse PAR products (Ryu et al, 2018), and 1-km resolution gross primary productivity (GPP) and ET products (Jiang and Ryu, 2016), which enables tracking crop growth and yields too (Huang et al, 2018). In particular, the 1-km resolution BESS ET product is able to capture the total amount and spatial and temporal variations in arid/semi-arid areas like Australia (Whitley et al, 2016(Whitley et al, , 2017, California (Baldocchi et al, 2019) and Northwestern China (Wei et al, 2019). The fidelity of coarse-resolution BESS ET product suggests its potential at fine resolutions.…”