NASA Surface Water Products in NCRFC Streamflow Forecasts

Project Overview

A collaboration between NCAR, Purdue University, NASA and the NWS North Central River Forecast Center is evaluating whether satellite-based estimates of inundated (flooded) land area can provide usable information to improve the quality of hydrologic simulations and forecasts, hence water management during events such as floods.

Click the links below for project information and data.

This project is sponsored by the NASA Terrestrial Hydrology Program (THP). It supports the THP goals of building a “capacity to coherently monitor inland waters” and also to provide science-based water cycle information for decision support in water management.

Project Details

Overarching Goals

The proposed effort has two major objectives:

  1. Develop and use remote sensing imagery of water inundation to augment retrospective distributed hydrologic modeling analyses to improve our understanding of the region’s large-scale runoff response to rainfall and snowmelt events coupled with terrain and subsurface influences at the field scale.
  2. Investigate the potential of current data assimiliation approaches to leverage remote sensing so as to reduce hydrologic simulation and prediction errors associated with the spring snowmelt period.


  • The study area is the Red River basin in the northern Great Plains region of the US, with the Buffalo R watershed as a pilot basin for method development
  • The forecast element of project focused on short-range flood forecasting (out to 10 days)
  • The project makes use of surface water products derived from satellite data primarily from the EOS mission MODIS sensors (viewable here and LandSat, as well as airborne LIDAR.

Highlighted Objectives

  • Develop a conceptual surface inundation (ponding) scheme for addition the NCRFC CHPS operational forecasting platform, which relies on NWS models, and test the scheme at NCRFC in a stand-alone version of CHPS
  • Implement a version of the VIC land surface model containing a suface ponding algorithm within the NASA LIS simulation platform
  • Develop a time-history of ponding imagery for the study region and assess its use for improving hydrologic simulations in the Red River basin, and for initializing short range flood forecasts


  Project Proposal

Project Team

  NCAR: Andy Wood
  Purdue University: Laura Bowling, Keith Cherkauer, Stuart Smith
  NASA GSFC: Christa Peters-Lidard and Shugong Wang
  NCRFC: Pedro Restrepo and Mike DeWeese

Operational efforts to predict flood crests on the Red River have at times exhibited large and potentially costly errors. For example, flood predictions by the National Weather Service (NWS) North Central (NC) River Forecast Center (RFC) in the spring of 2013 were significantly overforecasted, leading to unnecessary investments of millions of dollars in hazard mitigation. Considerable volumes of water were observed to pond behind county road embankments and on fields (see figure at right).

Yet only about 30% of the predicted runoff from the seasonal peak snow water equivalent and a small amount of precipitation made it to the river during the spring runoff. Even given good quality, reanalyzed meteorological forcings, NOAA’s Sacramento model (used in forecasting) was unable to accurately model and predict the water inflows to the Red River channel. There are currently no quantitive estimates of the volume of water detained on the landcape during such ponding events, and we lack a sufficiently comprehensive understanding of the mechanisms at work for practical application in the operational forecasting arena.

The region’s terrain and land use characteristics coupled with the monitoring network weaknesses make it unusually suitable for the application of space-based remote sensing of this surface water storage. The Red River Valley, for instance, has an extremely low slope, and land use is extensively agricultural, almost devoid of trees and other dense vegetation. This terrain provides an opportunity to demonstrate and achieve practical application of of NASA remotely-sensed ponded water mapping to provide new monitoring information in the operational flood forecasting context. An example of this type of product is shown in the second figure to the right.

View of Flooded Fields in the Red River Basin (May 2013)

MODIS surface ponding water shown in red in the study region (May 3-5, 2013)