Comparative assessment of univariate and multivariate imputation models for varying lengths of missing rainfall data in a humid tropical region: a case study of Kozhikode, Kerala, India-Reference-Cited by-同舟云学术

Comparative assessment of univariate and multivariate imputation models for varying lengths of missing rainfall data in a humid tropical region: a case study of Kozhikode, Kerala, India

Published:2023-07-25 Issue: Volume: Page:
ISSN:1895-7455
Container-title:Acta Geophysica
language:en
Short-container-title:Acta Geophys.

Author:

Kannegowda Naveena,Udayar Pillai Surendran,Kommireddi Chinni Venkata Naga Kumar,Fousiya

Publisher

Springer Science and Business Media LLC

Subject

Geophysics

Link

https://link.springer.com/content/pdf/10.1007/s11600-023-01152-y.pdf

Reference39 articles.

1. Addi M, Gyasi-Agyei Y, Obuobie E, Amekudzi LK (2022) Evaluation of imputation techniques for infilling missing daily rainfall records on river basins in Ghana. Hydrol Sci J (just-accepted)

2. Afrifa Yamoah E, Mueller UA, Taylor SM, Fisher AJ (2020) Missing data imputation of high-resolution temporal climate time series data. Meteorol Appl 27(1):e1873

3. Aieb A, Madani K, Scarpa M, Bonaccorso B, Lefsih K (2019) A new approach for processing climate missing databases applied to daily rainfall data in Soummamwatershed. Algeria Heliyon 5(2):e01247

4. Chaplot B (2016) Prediction of rainfall time series using soft computing techniques. Environ Monit Assess 193(11):721. https://doi.org/10.1007/s10661-016-5637-5

5. Grillakis MG, Polykretis C, Manoudakis S, Seiradakis KD, Alexakis DD (2020) A quantile mapping method to fill in discontinued daily precipitation time series. Water 12(8):2304

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Assessment of Different Methods for Estimation of Missing Rainfall Data;Water Resources Management;2024-07-31

2. Grape Yield Prediction Models: Approaching Different Machine Learning Algorithms;Horticulturae;2023-11-30