RESEARCH BASE ASSESSMENT OF INTEGRATED ...
BACKGROUND
The Vaal Dam is South Africa's second largest dam by area and a vital national resource. Since its levels are linked to summer rainfall in its catchment, summer inundation and drought have a significant impact on inflows and discharge. Due to the lack of operational real-time seasonal forecasting systems specific to the Vaal Dam, the project set out to develop and test statistical forecast systems for the Vaal dam on seasonal time scales, with the goal of eventually demonstrating operational forecasting capability using the developed models.
AIMS
In this project we test for seasonal predictability for Vaal Dam characteristics such as dam levels and downstream flows. We establish pragmatic and cost-effective ways that can also lead to real-time prediction and decision-making. In this project we use simplified statistical models to test for predictability and to establish real-time forecasting for the dam. The following are the aims of the project:
1. To develop statistical forecast systems for the Vaal Dam on seasonal time scales.
2. To test the models’ performances for both deterministic and probabilistic forecasts.
3. To test operational forecasting capability using the developed models over various lead-times.
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Additional Information
Field | Value |
---|---|
Data last updated | March 21, 2023 |
Metadata last updated | unknown |
Created | unknown |
Format | |
License | Creative Commons Attribution |
Authors | Willem A. Landman, Emma Archer, Pearl Gosiame, Brian Nkal |
Publication date | August 1, 2022 |
Access level | info:eu-repo/semantics/closedAccess |
Version | unknown |
Created | over 1 year ago |
Media type | application/pdf |
Size | 2,921,749 |
format | |
id | a30e20f4-cb2a-4d30-98ad-05bc8434e5e2 |
last modified | over 1 year ago |
license id | cc-by |
license title | Creative Commons Attribution |
license url | http://www.opendefinition.org/licenses/cc-by |
on same domain | True |
package id | a047d7be-9e8d-434c-b3e0-f25887cfd500 |
position | 5 |
revision id | 70d0086f-2314-4150-8ecf-2b0565c89d98 |
state | active |
url type | upload |