Effects of Seasonal Land Surface Conditions on Hydrometeorological Dynamics in South-western North America

Abstract

Arid and semiarid landscapes in regions with seasonal precipitation experience dramatic changes that alter land surface conditions, including soil moisture states, ecosystem productivity and river flooding. These variations in terrestrial properties have implications for vehicle mobility, airborne surveillance, target acquisition and aircraft operations and for battlefield environmental predictions supporting these operations. In this research, we developed and demonstrated novel approaches for terrestrial science studies by integrating the deployment of environmental sensor networks, unmanned aerial vehicle data acquisition and high performance computing-based hydrologic modeling designed to capture, account for and predict seasonal variations in land surface conditions. Our tests are focused in a range of arid and semiarid sites in southwestern North America that are representative of operational environments undergoing strong seasonality.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 21, 2015
Accession Number
ADA624232

Entities

People

  • Adam Schreiner-mcgraw
  • Cody A. Anderson
  • Enrique R Vivoni
  • Luis A. Mendez-barroso
  • Nicole A. Pierini
  • Ryan C. Templeton

Organizations

  • Arizona State University

Tags

Communities of Interest

  • Air Platforms
  • Autonomy
  • Materials and Manufacturing Processes
  • Sensors
  • Space

DTIC Thesaurus Topics

  • Acquisition
  • Aircrafts
  • Civil Engineering
  • Cosmic Rays
  • Detectors
  • Ecology
  • Engineering
  • Heat Energy
  • High Performance Computing
  • High Resolution
  • North America
  • Remote Sensing
  • Sensor Networks
  • Students
  • Surface Properties
  • Unmanned Aerial Vehicles
  • Water Resources

Fields of Study

  • Environmental science

Readers

  • Atmospheric Science/Meteorology
  • Marine Ecotoxicology
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • Autonomy
  • Autonomy - UAVs