RNfinity
Research Infinity Logo, Orange eye of horus, white eye of Ra
  • Home
  • Submit
    Research Articles
    Ebooks
  • Articles
    Academic
    Ebooks
  • Info
    Home
    Subject
    Submit
    About
    News
    Submission Guide
    Contact Us
  • Login/sign up
    Login
    Register

Physics Maths Engineering

Assessment of Subseasonal-to-Seasonal (S2S) Precipitation Forecast Skill for Reservoir Operation in the Yaque Del Norte River, Dominican Republic

rnfinity

info@rnfinity.com

orcid logo

Norman Pelak,

Norman Pelak

Hydrologic Research Center, San Diego, CA 92127, USA


Eylon Shamir,

Eylon Shamir

Hydrologic Research Center, San Diego, CA 92127, USA


Theresa Modrick Hansen,

Theresa Modrick Hansen

Hydrologic Research Center, San Diego, CA 92127, USA


Zhengyang Cheng

Zhengyang Cheng

Hydrologic Research Center, San Diego, CA 92127, USA


  Peer Reviewed

copyright icon

© attribution CC-BY

  • 0

rating
494 Views

Added on

2024-11-03

Doi: http://dx.doi.org/10.3390/w16142032

Related Subjects
Physics
Math
Chemistry
Computer science
Engineering
Earth science
Biology

Abstract

Operational forecasters desire information about how their reservoir and riverine systems will evolve over monthly to seasonal timescales. Seasonal traces of hydrometeorological variables at a daily or sub-daily resolution are needed to drive hydrological models at this timescale. Operationally available models such as the Climate Forecast System (CFS) provide seasonal precipitation forecasts, but their coarse spatial scale requires further processing for use in local or regional hydrologic models. We focus on three methods to generate such forecasts: (1) a bias-adjustment method, in which the CFS forecasts are bias-corrected by ground-based observations; (2) a weather generator (WG) method, in which historical precipitation data, conditioned on an index of the El Niño–Southern Oscillation, are used to generate synthetic daily precipitation time series; and (3) a historical analog method, in which the CFS forecasts are used to condition the selection of historical satellite-based mean areal precipitation (MAP) traces. The Yaque del Norte River basin in the Dominican Republic is presented herein as a case study, using an independent dataset of rainfall and reservoir inflows to assess the relative performance of the methods. The methods showed seasonal variations in skill, with the MAP historical analog method having the strongest overall performance, but the CFS and WG methods also exhibited strong performance during certain seasons. These results indicate that the strengths of each method may be combined to produce an ensemble forecast product.

Key Questions about S2S Precipitation Forecasting in the Yaque del Norte River Basin

The article "Assessment of Subseasonal-to-Seasonal (S2S) Precipitation Forecast Skill for Reservoir Operation in the Yaque del Norte River, Dominican Republic" evaluates the effectiveness of three methods for generating S2S precipitation forecasts to enhance reservoir management in the Yaque del Norte River basin. The study found that while no single method consistently outperformed the others, each provided valuable insights for operational forecasting. The authors emphasize the importance of selecting appropriate forecasting methods to improve water resource management in the region.

1. What are the three methods evaluated for generating S2S precipitation forecasts?

The study examines:

  • Bias-Corrected Seasonal Climate Forecasts: Utilizing seasonal Climate Forecast System (CFS) forecasts adjusted with monthly change factors derived from historical data.
  • Stochastic Weather Generation: Employing historical precipitation records and ENSO indices to parameterize a stochastic weather generator.
  • Satellite-Based Precipitation Time Series: Selecting an ensemble of historical satellite-based mean areal precipitation (MAP) time series conditioned on the state of the CFS forecast at the season's start.

2. What were the findings regarding the performance of these forecasting methods?

The study concluded that no single method consistently outperformed the others across all seasons. Each approach offered unique advantages, and their effectiveness varied depending on specific conditions and time frames. This variability underscores the necessity of selecting the most suitable forecasting method based on the operational context.

3. How do these findings contribute to improving water resource management in the Yaque del Norte River basin?

By assessing the skill of different S2S precipitation forecasting methods, the study provides valuable insights for developing an operational forecast system tailored to the Yaque del Norte River basin. Implementing the most effective forecasting methods can enhance reservoir operation strategies, leading to more efficient water resource management and better preparedness for seasonal variations.

Summary Video Not Available

Review 0

Login

ARTICLE USAGE


Article usage: Nov-2024 to May-2025
Show by month Manuscript Video Summary
2025 May 120 120
2025 April 75 75
2025 March 74 74
2025 February 49 49
2025 January 63 63
2024 December 47 47
2024 November 66 66
Total 494 494
Show by month Manuscript Video Summary
2025 May 120 120
2025 April 75 75
2025 March 74 74
2025 February 49 49
2025 January 63 63
2024 December 47 47
2024 November 66 66
Total 494 494
Related Subjects
Physics
Math
Chemistry
Computer science
Engineering
Earth science
Biology
copyright icon

© attribution CC-BY

  • 0

rating
494 Views

Added on

2024-11-03

Doi: http://dx.doi.org/10.3390/w16142032

Related Subjects
Physics
Math
Chemistry
Computer science
Engineering
Earth science
Biology

Follow Us

  • Xicon
  • Contact Us
  • Privacy Policy
  • Terms and Conditions

5 Braemore Court, London EN4 0AE, Telephone +442082758777

© Copyright 2025 All Rights Reserved.