ARMSED (Army Multiple Watershed Storm Water and Sediment Runoff), a Runoff and Sediment Yield Model for Army Training Land Watershed Management. Volume 2. Program Documentation

Abstract

Army land managers and environmental planners must estimate runoff and sediment yield from small, ungaged watersheds on Army training lands to assess the condition of the lands and to evaluate alternative erosion control plans. The U.S. Army Construction Engineering Research Laboratory (USACERL) developed the Army multiple watershed storm water and sediment runoff (ARMSED) simulation model, which is based on the MULTSED model and has been adapted for Army use. ARMSED is a single event, distributed, deterministic simulation model that operates on MS-DOS compatible microcomputers with 512 K RAM. A 10-megabyte hard disk is recommended. This report provides guidance and documentation for ARMSED users. Volume I contains guidance for selecting and estimating the parameters and values needed as input for the model. Volume II describes the various subroutines of ARMSED and the modifications that have been made to arrive at the current version. As the user base for ARMSED expands, the model will be updated and modified to incorporate new data and ideas.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 1989
Accession Number
ADA212926

Entities

People

  • Robert E. Riggins
  • Timothy J. Ward
  • Winifred Hodge

Organizations

  • Construction Engineering Research Laboratory

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Army Training
  • Civil Engineering
  • Colorado
  • Computer Programs
  • Drainage Basins
  • Engineering
  • Engineers
  • Equations
  • Grain Size
  • Illinois
  • Materials
  • New Mexico
  • Personal Computers
  • Rainfall Intensity
  • Security
  • Time Intervals
  • United States

Fields of Study

  • Agricultural and Food sciences

Readers

  • Coastal and Marine Engineering/Sediment Transport/Hydraulic Engineering
  • Computational Modeling and Simulation
  • Computer Science.