National Water Level Forecast (NWLF): An open-source customizable web application for the GEOGLOWS ECMWF global hydrological model

Details

• Journal Title:
  Information Geography
• Personal Author:
  Rojas-Lesmes, Darlly ; Sanchez-Lozano, Jorge ; Nelson, E. James ; Chancay-Sanchez, Juseth ; Rodriguez-Chaves, Jhonatan ; Larco-Erazo, Karina ; Romero, E. Giovanni ; Trujillo-Vela, Mario ; Hales, Riley C. ; Ames, Daniel P. ; Gutierrez, Angelica L.
• NOAA Program & Office:
  NWS (National Weather Service) ; CIROH (Cooperative Institute for Research to Operations in Hydrology)
• Description:
  Water-related disasters, including floods and droughts, require innovative forecasting tools for effective risk management and decision-making. The National Water Level Forecast (NWLF) application addresses this need by integrating global hydrological simulations from the GEOGLOWS ECMWF Global Hydrological Model with locally observed data. Developed using the Tethys platform, NWLF employs a pre-computed backend architecture to deliver reliable water level forecasts, ensuring operational stability and an intuitive user interface. Central to its method is the Discharge-to-Water Level Transformation (DWLT), which uses monthly duration curves to align simulated and observed data through non-exceedance probability, significantly improving forecast accuracy. Case studies across Brazil, Colombia, Ecuador, and Peru demonstrate NWLF's scalability and adaptability in addressing diverse regional hydrological challenges. Enhancements in NWLF architecture, such as pre-computation, enable faster analyses. Opportunities to improve the system include collaborative threshold refinements and enhanced stakeholder engagement, NWLF has the potential to bridge the gap between global models and local applications. This study presents the NWLF application and highlights its potential for advancing hydrological forecasting, contributing to Sustainable Development Goals (SDGs) related to water resource management and disaster risk reduction while paving the way for continuous improvement and broader adoption.
• Source:
  Information Geography, 1(1), 100008
• DOI:
  https://doi.org/10.1016/j.infgeo.2025.100008
• ISSN:
  3050-5208
• Format:
  PDF
• Publisher:
  Elsevier BV
• Document Type:
  Journal Article
• Funding:
  Grant no. NA22NWS4320003
• License:
  https://creativecommons.org/licenses/by-nc-nd/4.0/
• Rights Information:
  CC BY-NC-ND
• Compliance:
  Submitted
• Main Document Checksum:
  urn:sha-512:1305a079fff22e6abbda1796a4ec6c4fb36b6469d36c6b4ca9ded4b3387d1f3512cc7b3c9240da29b1f8e8680774fb90fc267949eee7b5cef32f420b42a225b1
• Download URL:
  https://repository.library.noaa.gov/view/noaa/72788/noaa_72788_DS1.pdf
• File Type:
  [PDF - 6.74 MB ]