Using the SARIMA model to predict the trends of evapotranspiration and runoff in the Muringato river basin, Kenya-Reference-Cited by-同舟云学术

Using the SARIMA model to predict the trends of evapotranspiration and runoff in the Muringato river basin, Kenya

Published:2023-08-10 Issue:12 Volume:37 Page:4707-4718
ISSN:1436-3240
Container-title:Stochastic Environmental Research and Risk Assessment
language:en
Short-container-title:Stoch Environ Res Risk Assess

Author:

Muthee Simon Wachira,Kuria Bartholomew Thiong’o,Mundia Charles Ndegwa,Sichangi Arthur W.,Kuria David Ndegwa,Wanjala Johanna Anyesi,Kipkemboi Wisdom,Goebel Marcus,Graw Valerie,Rienow Andreas

Funder

Bundesministerium für Bildung und Forschung

Publisher

Springer Science and Business Media LLC

Subject

General Environmental Science,Safety, Risk, Reliability and Quality,Water Science and Technology,Environmental Chemistry,Environmental Engineering

Link

https://link.springer.com/content/pdf/10.1007/s00477-023-02534-w.pdf

Reference49 articles.

1. Abdi DA, Ayenew T (2021) A scenario-based modeling of climate change impact on the hydrology of Ketar watershed, Central Rift Valley Basin, Ethiopia. Model Earth Syst Environ 8(3):3473–3486. https://doi.org/10.1007/S40808-021-01314-1

2. Aliyu AS, Auwal AM, Adenomon MO (2021) Application of SARIMA models in modelling and forecasting monthly rainfall in Nigeria. Asian J Prob Stat. https://doi.org/10.9734/AJPAS/2021/V13I330310

3. Alonso Brito GR, Rivero Villaverde A, Lau Quan A, Ruíz Pérez ME (2021) Comparison between SARIMA and Holt-Winters models for forecasting monthly streamflow in the western region of Cuba. SN Appl Sci 3(6):1–12. https://doi.org/10.1007/S42452-021-04667-5/FIGURES/7

4. Chadalawada J, Herath HMVV, Babovic V (2020) Hydrologically informed machine learning for rainfall-runoff modeling: a genetic programming-based toolkit for automatic model induction. Water Resour Res 56(4):e2019WR026933. https://doi.org/10.1029/2019WR026933

5. Chang X, Gao M, Wang Y, Hou X (2012) Seasonal autoregressive integrated moving average model for precipitation time series. J Math Stat 8(4):2012. https://doi.org/10.3844/jmssp.2012.500.505

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