Location: Hydrology and Remote Sensing Laboratory
Project Number: 8042-13610-030-005-I
Project Type: Interagency Reimbursable Agreement
Start Date: Oct 1, 2018
End Date: Sep 30, 2021
Objective:
Obtain an unbiased estimate of the one-way coupling strength between soil moisture and evapotranspiration and use this estimate to enhance the model-based representation of land processes key to the development and propagation of agricultural drought.
Approach:
Observation-based estimates of the one-way coupling strength between soil moisture and evapotranspiration are biased low by the pressence of independent random error in observations of both quantities. However, this bias can be calculated, and corrected for, via the application of a data assimilation technique called triple collocation. Application of triple collocation techniques requires the availability of three, mutually-indpendent estimates of geophysical quantities. Here, these estimates will be gleaned from a variety of microwave and remote sensing sources plus land surface model estimates. The approach will then proceed in three distinct steps:
1. Application of triple collocation analysis a series of ~15 well-instrumented AmeriFlux locations located within the contiguous United States. At these sites the assumptions underlying triple collocation will be explicitly tested. Based on the results of these tests, a specific set of globally-available modeling and (thermal + microwave) remote-sensing products will be selected for global-scale application (Project Year 1).
2. Remote sensing and modeling soil moisture and evapotranspiration products chosen in Year 1 will be applied in a global analysis (on a 0.25-degree spatial grid) to obtain a map of true, warm-season soil moisture/evapotranspiration coupling strength for important agricultural areas of the global.
3. The soil moisture/evapotranspiration coupling map generated in Project Year 3 will be compared with comparable coupling estimates provided by multiple (i.e., 2 or 3) existing land surface models. The performance of each model will be described and specific recommendations for model enhancement/modification will be compiled. (Project Year 3).
