Checking for non-preferred file/folder path names (may take a long time depending on the number of files/folders) ...

WaterResourcesResearch2022WR032779


Authors:
Owners: This resource does not have an owner who is an active HydroShare user. Contact CUAHSI (help@cuahsi.org) for information on this resource.
Type: Resource
Storage: The size of this resource is 638.9 KB
Created: Jan 27, 2023 at 2:32 a.m.
Last updated: Jan 27, 2023 at 1:33 p.m.
DOI: 10.4211/hs.a85f6240d2c94e2281f4a88c5728323b
Citation: See how to cite this resource
Sharing Status: Published
Views: 311
Downloads: 0
+1 Votes: Be the first one to 
 this.
Comments: No comments (yet)

Abstract

The reservoir operation changes the downstream water level and the surrounding groundwater level. Predicting the groundwater level flux is crucial, especially before making the dam removal decision. However, investigating the condition of dam removal without demolishing the infrastructure is challenging. The novelty of this study comes from analyzing the groundwater level changes using the observed pre- and post-weir removal data. We built daily groundwater level prediction models for 14 groundwater observation wells using five machine learning algorithms. The support vector regression was the best machine learning algorithm in predicting the daily groundwater level. The groundwater level was the highest during normal operation and summer (rainy season) and the lowest during the full opening and winter (dry season). The groundwater changes were up to 3.15 m near the weir, and impacts extended 3.80 km but no further than 7 km. The final product was groundwater level maps that can assist groundwater level management and weir operation strategies based on groundwater level forecasting. Future studies can reconfigure and modify the groundwater prediction process used in this research to fit different hydrological and metrological variables to dams or weirs under consideration for removal.

Subject Keywords

Content

How to Cite

Yi, S. (2023). WaterResourcesResearch2022WR032779, HydroShare, https://doi.org/10.4211/hs.a85f6240d2c94e2281f4a88c5728323b

This resource is shared under the Creative Commons Attribution CC BY.

http://creativecommons.org/licenses/by/4.0/
CC-BY

Comments

There are currently no comments

New Comment

required