RAPID: RAINBOW CANYON AND PANAMINT VALLEY, DEATH VALLEY NATIONAL PARK: RECONNAISSANCE IN RESPONSE TO THE FLOOD OF AUGUST 20, 2023

Information

  • NSF Award
  • 2345167
Owner
  • Award Id
    2345167
  • Award Effective Date
    9/1/2023 - a year ago
  • Award Expiration Date
    8/31/2024 - 2 months ago
  • Award Amount
    $ 20,000.00
  • Award Instrument
    Standard Grant

RAPID: RAINBOW CANYON AND PANAMINT VALLEY, DEATH VALLEY NATIONAL PARK: RECONNAISSANCE IN RESPONSE TO THE FLOOD OF AUGUST 20, 2023

The record-breaking flood of August 2023 generated by Tropical Storm Hilary, combined with the previous record-breaking flood of 2022, offer a precious opportunity. They provide the best window in our lifetime, and indeed perhaps the best window over the next millennium, to observe directly and quantify the immediate aftermath the type of event that shapes themorphology of arid canyon and basin systems. This project focuses on collection of highly perishable data following an extreme flood event in Death Valley following Hurricane Hilary that will be used to constrain numerical models that give insight on hydrology that drives landscape forming processes in desert landscapes. The researchers will directly observe and quantify the immediate aftermath the type of event that shapes the morphology of arid canyon and basin systems which is relevant for the Basin and Range Province and in global desert settings. <br/><br/>The information and tools gained from the proposed RAPID dovetail with the recent advances in numerical models that seek to constrain morphodynamically the development of incised valleys, and therefore will prove invaluable for generating additional insights into water-driven desert geomorphic processes. The team will use field survey and observation of high-water marks throughout Rainbow Canyon to determine the flow depth during the flood, which is a first-order parameter required to refine the morphodynamic model of canyon incision. These observations will be followed up with reconnaissance surveys and detailed assessment using aerial imagery using remotely gathered data from ground-based survey, and aerial imagery.<br/><br/>This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

  • Program Officer
    Amanda Keen-Zebertakeenzeb@nsf.gov7032924984
  • Min Amd Letter Date
    9/5/2023 - a year ago
  • Max Amd Letter Date
    9/5/2023 - a year ago
  • ARRA Amount

Institutions

  • Name
    Texas Tech University
  • City
    LUBBOCK
  • State
    TX
  • Country
    United States
  • Address
    2500 BROADWAY
  • Postal Code
    79409
  • Phone Number
    8067423884

Investigators

  • First Name
    Jeffrey
  • Last Name
    Nittrouer
  • Email Address
    Jeffrey.Nittrouer@ttu.edu
  • Start Date
    9/5/2023 12:00:00 AM

Program Element

  • Text
    XC-Crosscutting Activities Pro
  • Code
    7222

Program Reference

  • Text
    RAPID
  • Code
    7914