The Army Remote Moisture System (ARMS) is a Geographic Information Systems (GIS) based modeling package that assimilates remotely sensed satellite data with process-based hydrologic models to accurately predict the surface soil moisture status of a particular domain. This is a collaborative, multi-agency effort with input and analysis from the U.S. Army Corps of Engineers, NASA, USDA-ARS, University of Wyoming, and industry leaders in soil mapping. ARMS is a modular system built around four separate components: 1) Land Information Systems (LIS) modeling and data assimilation system developed at NASA Goddard Space Flight Center, 2) Delta Index method developed at the ARS Southwest Watershed Research Center for remotely estimating soil moisture from satellite radar, 3) Parameter Estimation Tool (PEST) for parameter optimization, and 4) A GIS user interface to communicate with the separate modules of ARMS. A separate plug-in has been developed that uses a heuristic soil texture estimation method to estimate soil texture classification over the watershed.

Development and initial validation of ARMS was performed with data gathered during the Monsoon '90 field experiment at the 150 km2 Walnut Gulch Environmental Watershed (WGEW) in southwest Arizona in the summer of 1990. This dataset provided daily surface layer gravimetric soil moisture at 8 locations, daily profile soil moisture data from time-domain reflectometry sensors at two sites, and hourly meteorological data from 8 recording stations and a network of 85 rain gauges. In addition, an L-band Push Broom Microwave Radiometer was flown for 6 days in the experiment and provided shallow soil moisture products over a fairly large area. Simulation experiments aimed at model optimization and input degradation validate the potential of the system for estimating soil moisture in operational military situations.