Impacts of observational uncertainty on analysis and modelling of hydrological processes: Preface-Reference-Cited by-同舟云学术

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Impacts of observational uncertainty on analysis and modelling of hydrological processes: Preface

Published:2022-02 Issue:2 Volume:36 Page:
ISSN:0885-6087
Container-title:Hydrological Processes
language:en
Short-container-title:Hydrological Processes

Author:

McMillan Hilary K.¹^ORCID,Coxon Gemma²³^ORCID,Sikorska‐Senoner Anna E.⁴^ORCID,Westerberg Ida K.⁵^ORCID

Affiliation:

1. Department of Geography San Diego State University San Diego California USA

2. School of Geographical Sciences University of Bristol Bristol UK

3. The Cabot Institute University of Bristol Bristol UK

4. Department of Geography University of Zurich Zürich Switzerland

5. IVL Swedish Environmental Research Institute Stockholm Sweden

Publisher

Wiley

Subject

Water Science and Technology

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/hyp.14481

Reference76 articles.

1. Large-sample hydrology: recent progress, guidelines for new datasets and grand challenges

2. The CAMELS-CL dataset: catchment attributes and meteorology for large sample studies – Chile dataset

3. Global catchment modelling using World-Wide HYPE (WWH), open data, and stepwise parameter estimation

4. The evolving perceptual model of streamflow generation at the Panola Mountain Research Watershed

5. A precipitation shift from snow towards rain leads to a decrease in streamflow

Cited by 6 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. Sharing perceptual models of uncertainty: On the use of soft information about discharge data;Hydrological Processes;2024-05

2. CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland;Earth System Science Data;2023-12-19

3. A Signature‐Based Hydrologic Efficiency Metric for Model Calibration and Evaluation in Gauged and Ungauged Catchments;Water Resources Research;2023-10-27

4. A quality-control framework for sub-daily flow and level data for hydrological modelling in Great Britain;Hydrology Research;2023-10-13

5. On (in)validating environmental models. 1. Principles for formulating a Turing‐like Test for determining when a model is fit‐for purpose;Hydrological Processes;2022-10

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