Remote Sensing for Land Surface Hydrology: Accuracy and Uncertainty Analysis

Principal Investigator: Dr. Dubayah

 

  1. Objectives and justification for work.

    2. Over the last 20 years, sensitivity studies with Atmospheric General Circulation Models (AGCMs) have clearly demonstrated that land surface processes affect climate at regional to global scales. Understanding the nature and effects of possible changes to the terrestrial water and energy fluxes as a result of changing climate and land surface characteristics is also central to the science objectives of the World Climate Research Program (WCRP) activities under GEWEX, including GCIP, BALTEX and LBA. The inherent research strategy for EOS and WCRP for investigating these questions is through process-based, terrestrial water and energy balance models.

    There is the assumption within EOS and WCRP that remote sensing observations offers the potential to provide the required inputs. The EOS science plan assumes that EOS sensors will provide remote sensing products that are both accurate and appropriate for hydrological modeling. It is the central premise of this research proposal that such claims are currently unproved. In fact, very little know about the accuracy and uncertainty in remote sensing products and how this uncertainty manifests themselves in derived water and energy fluxes. The goal of the proposed research is to develop a better understanding of the structure of the uncertainty in remote sensing products, and how these uncertainties affect model predictions at regional to continental scales.

     

  2. Accomplishments of prior year's work

    3. Previous studies carried out by the PIs have combined hydrological modeling of land surface processes across a range of spatial scales with ground-based and remotely sensed observations. These activities include extensive distributed water and energy balance modeling ranging in scale from point measurements for BOREAS and FIFE tower sites, to study area scales for BOREAS and FIFE, to catchments within the GCIP-SW, and the Red-Arkansas continental -scale basins (640,000 sq. km.) Two of the project investigators (Wood and Lettenmaier) assembled and organized a PILPS intercomparison study using the Red-Arkansas River basins. In addition, the usefulness of remote sensing products (radiation, surface air temperature and humidity) for inputs to terrestrial water and energy modeling was tested over the Red-Arkansas River basins using one month of the Pathfinder data (June 1987).

  3. Outline of proposed work and methodology

    4. We propose to evaluate the effects of uncertainties in remotely-based hydrological parameters and forcings on derived terrestrial water and energy fluxes. A statistically-based ensemble analysis approach will be developed to estimate bias and variance in derived terrestrial water and energy fluxes. This uncertainty will be derived by propagating remote sensing uncertainties through the terrestrial water and energy balance model via ensemble simulations. Such an approach has been developed earlier by the PI to investigate the influence of soil moisture initializations on model-derived water and energy fluxes. The approach will be applied at large spatial scales, permitting the determination of the derived uncertainty over a range of spatial and temporal scales. The critical issue is whether terrestrial water and energy models enhance or filter errors in the remote sensing data.

    There are three proposed geographical areas of application. The first is the Red-Arkansas River basins for the GIST period April-August 1994; the second area is continental Africa, for the period of 1986; and the third area of application will be a set of 100 sites representative of northern hemisphere cold seasons (snow and frozen soils) processes. The work will build upon recent GOES and AVHRR pathfinder data sets, developed by other groups under NASA funding, and on current macro-scale hydrological modeling by the PIs.

  4. Relevant recent publications

Dubayah, R., E.F. Wood, M. Zion and K. Czajkowski. 1997. A remote sensing approach

to macroscale hydrological modeling, in Schultz, G. and E. Engman (Eds.) Remote

sensing in hydrology and water management, Springer-Verlag.

Peters-Lidard, C., M. Zion and E.F. Wood. 1997. "A soil-vegetation-atmosphere transfer

scheme for modeling spatially variable water and energy balance processes", J.

Geophys. Res., Vol. 102(D2), 4303-4324.

Abdulla, F.A., D.P. Lettenmaier, E.F. Wood, and J.A. Smith. 1996. "Application of a

macroscale hydrologic model to estimate the water balance of the Arkansas-Red River

basin", J. Geophys. Res., 101(D3), 7449-7459.