Dynamic quantile regression for trend analysis of streamflow time series-Reference-Cited by-同舟云学术

Dynamic quantile regression for trend analysis of streamflow time series

Published:2022-05-09 Issue:6 Volume:38 Page:1051-1060
ISSN:1535-1459
Container-title:River Research and Applications
language:en
Short-container-title:River Research & Apps

Author:

Lima Luciano B.¹^ORCID,Cribari‐Neto Francisco²,Lima‐Junior Dilermando Pereira¹

Affiliation:

1. Laboratório de Ecologia e Conservação de Ecossistemas Aquáticos Universidade Federal de Mato Grosso Pontal do Araguaia Brazil

2. Departamento de Estatística Universidade Federal de Pernambuco Recife Brazil

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Wiley

Subject

General Environmental Science,Water Science and Technology,Environmental Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/rra.3983

Reference57 articles.

1. Threats for biodiversity in the floodplain of the Upper Paraná River: Effects of hydrological regulation by dams;Agostinho A. A.;Ecohydrology & Hydrobiology,2004

2. Scientists’ warning to humanity on the freshwater biodiversity crisis

3. Long-Term Trends and Seasonality Detection of the Observed Flow in Yangtze River Using Mann-Kendall and Sen’s Innovative Trend Method

4. CABra: a novel large-sample dataset for Brazilian catchments

5. A Recent Systematic Increase in Vapor Pressure Deficit over Tropical South America

Cited by 3 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. Quantile-based dynamic modeling of asymmetric data: a novel Burr XII approach for positive continuous random variables;International Journal of Data Science and Analytics;2024-05-24

2. Evidence of water surface and flow reduction in the main hydrographic basin of the Brazilian savannah (Cerrado biome): the Araguaia river;Hydrobiologia;2024-02-09

3. Forecasting the proportion of stored energy using the unit Burr XII quantile autoregressive moving average model;Computational and Applied Mathematics;2023-12-23