Assessing automated gap imputation of regional scale groundwater level data sets with typical gap patterns-Reference-Cited by-同舟云学术

Assessing automated gap imputation of regional scale groundwater level data sets with typical gap patterns

Published:2023-05 Issue: Volume:620 Page:129424
ISSN:0022-1694
Container-title:Journal of Hydrology
language:en
Short-container-title:Journal of Hydrology

Author:

Bikše Jānis^ORCID,Retike Inga^ORCID,Haaf Ezra^ORCID,Kalvāns Andis^ORCID

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference70 articles.

1. Handling Complex Missing Data Using Random Forest Approach for an Air Quality Monitoring Dataset: A Case Study of Kuwait Environmental Data (2012 to 2018);Alsaber;Int. J. Environ. Res. Public Health,2021

2. Automatic gap-filling of daily streamflow time series in data-scarce regions using a machine learning algorithm;Arriagada;J. Hydrol.,2021

3. Groundwater Monitoring in Lithuania;Arustiene,2011

4. A comparison of statistical methods for evaluating missing data of monitoring wells in the Kazeroun Plain, Fars Province, Iran;Asgharinia;Groundwater Sustain. Dev.,2020

5. The use of predefined drought indices for the assessment of groundwater drought episodes in the Baltic States over the period 1989–2018;Babre;J. Hydrol.: Reg. Stud.,2022

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