Chlorophyll Forecasting Bayesian Network Model
| Authors: | |
|---|---|
| Owners: | Carly Hansen |
| Type: | Resource |
| Storage: | The size of this resource is 6.2 KB |
| Created: | Aug 17, 2018 at 7:14 a.m. |
| Last updated: | Aug 17, 2018 at 7:26 a.m. |
| Citation: | See how to cite this resource |
| Sharing Status: | Public |
|---|---|
| Views: | 2369 |
| Downloads: | 61 |
| +1 Votes: | Be the first one to this. |
| Comments: | No comments (yet) |
Abstract
Forecasting conditions that are indicative of algal blooms can help provide an early warning for monitoring and water management agencies. This script creates a seasonal (monthly) forecasting model which uses hydrologic and climate data from earlier in the season to predict chlorophyll concentrations throughout the late summer months. The accompanying data includes time series of monthly average extreme chlorophyll values, average streamflows, snow water equivalent, temperatures, and precipitation totals in or near Utah Lake.
Subject Keywords
Content
This resource contains links to external content. Linked content is
NOT stored in HydroShare, and we can't guarantee its availability, quality, or
security.
How to Cite
Hansen, C. (2018). Chlorophyll Forecasting Bayesian Network Model, HydroShare, http://www.hydroshare.org/resource/27f81cb47f814e32adc48f5fb9d02fa5
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
Comments
There are currently no comments
New Comment