Example of Journal of Hydroinformatics format
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Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format
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Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format Example of Journal of Hydroinformatics format
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Journal of Hydroinformatics — Template for authors

Publisher: IWA Publishing
Categories Rank Trend in last 3 yrs
Geotechnical Engineering and Engineering Geology #58 of 195 down down by 22 ranks
Water Science and Technology #68 of 225 down down by 17 ranks
Civil and Structural Engineering #97 of 318 down down by 42 ranks
Atmospheric Science #57 of 124 down down by 13 ranks
journal-quality-icon Journal quality:
Good
calendar-icon Last 4 years overview: 327 Published Papers | 1215 Citations
indexed-in-icon Indexed in: Scopus
last-updated-icon Last updated: 23/09/2022
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FAQ

Related Journals

open access Open Access

Taylor and Francis

Quality:  
High
CiteRatio: 5.4
SJR: 0.95
SNIP: 1.307
open access Open Access

NRC Research Press

Quality:  
High
CiteRatio: 6.1
SJR: 2.032
SNIP: 2.259
open access Open Access

Springer

Quality:  
High
CiteRatio: 6.1
SJR: 1.292
SNIP: 1.67

Journal Performance & Insights

Impact Factor

CiteRatio

Determines the importance of a journal by taking a measure of frequency with which the average article in a journal has been cited in a particular year.

A measure of average citations received per peer-reviewed paper published in the journal.

1.728

9% from 2018

Impact factor for Journal of Hydroinformatics from 2016 - 2019
Year Value
2019 1.728
2018 1.908
2017 1.797
2016 1.634
graph view Graph view
table view Table view

3.7

6% from 2019

CiteRatio for Journal of Hydroinformatics from 2016 - 2020
Year Value
2020 3.7
2019 3.5
2018 3.5
2017 3.4
2016 3.6
graph view Graph view
table view Table view

insights Insights

  • Impact factor of this journal has decreased by 9% in last year.
  • This journal’s impact factor is in the top 10 percentile category.

insights Insights

  • CiteRatio of this journal has increased by 6% in last years.
  • This journal’s CiteRatio is in the top 10 percentile category.

SCImago Journal Rank (SJR)

Source Normalized Impact per Paper (SNIP)

Measures weighted citations received by the journal. Citation weighting depends on the categories and prestige of the citing journal.

Measures actual citations received relative to citations expected for the journal's category.

0.654

6% from 2019

SJR for Journal of Hydroinformatics from 2016 - 2020
Year Value
2020 0.654
2019 0.616
2018 0.665
2017 0.727
2016 0.73
graph view Graph view
table view Table view

1.039

16% from 2019

SNIP for Journal of Hydroinformatics from 2016 - 2020
Year Value
2020 1.039
2019 0.894
2018 1.194
2017 1.141
2016 1.021
graph view Graph view
table view Table view

insights Insights

  • SJR of this journal has increased by 6% in last years.
  • This journal’s SJR is in the top 10 percentile category.

insights Insights

  • SNIP of this journal has increased by 16% in last years.
  • This journal’s SNIP is in the top 10 percentile category.
Journal of Hydroinformatics

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IWA Publishing

Journal of Hydroinformatics

Approved by publishing and review experts on SciSpace, this template is built as per for Journal of Hydroinformatics formatting guidelines as mentioned in IWA Publishing author instructions. The current version was created on 23 Sep 2022 and has been used by 674 authors to write and format their manuscripts to this journal.

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Last updated on
23 Sep 2022
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ISSN
1464-7141
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Sherpa RoMEO Archiving Policy
Yellow faq
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Endnote Style
Download Available
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Bibliography Name
plainnat
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Citation Type
Author Year
(Blonder et al., 1982)
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Bibliography Example
G E Blonder, M Tinkham, and T M Klapwijk. Transition from metallic to tunneling regimes in superconducting microconstrictions: Excess current, charge imbalance, and supercurrent conversion. Phys. Rev. B, 25(7):4515– 4532, 1982.

Top papers written in this journal

open accessOpen access Journal Article DOI: 10.2166/HYDRO.2008.015
Data-driven modelling: some past experiences and new approaches
Dimitri Solomatine1, Avi Ostfeld2

Abstract:

Physically based (process) models based on mathematical descriptions of water motion are widely used in river basin management. During the last decade the so-called data-driven models are becoming more and more common. These models rely upon the methods of computational intelligence and machine learning, and thus assume the p... Physically based (process) models based on mathematical descriptions of water motion are widely used in river basin management. During the last decade the so-called data-driven models are becoming more and more common. These models rely upon the methods of computational intelligence and machine learning, and thus assume the presence of a considerable amount of data describing the modelled system9s physics (i.e. hydraulic and/or hydrologic phenomena). This paper is a preface to the special issue on Data Driven Modelling and Evolutionary Optimization for River Basin Management, and presents a brief overview of the most popular techniques and some of the experiences of the authors in data-driven modelling relevant to river basin management. It also identifies the current trends and common pitfalls, provides some examples of successful applications and mentions the research challenges. read more read less
View PDF
689 Citations
open accessOpen access Journal Article DOI: 10.2166/HYDRO.2013.134
Improved annual rainfall-runoff forecasting using PSO-SVM model based on EEMD
Wen chuan Wang1, Dong mei Xu1, Dong mei Xu2, Kwok Wing Chau3, Shou-yu Chen2

Abstract:

Rainfall-runoff simulation and prediction in watersheds is one of the most important tasks in water resources management. In this research, an adaptive data analysis methodology, ensemble empirical mode decomposition (EEMD), is presented for decomposing annual rainfall series in a rainfall-runoff model based on a support vect... Rainfall-runoff simulation and prediction in watersheds is one of the most important tasks in water resources management. In this research, an adaptive data analysis methodology, ensemble empirical mode decomposition (EEMD), is presented for decomposing annual rainfall series in a rainfall-runoff model based on a support vector machine (SVM). In addition, the particle swarm optimization (PSO) is used to determine free parameters of SVM. The study data from a large size catchment of the Yellow River in China are used to illustrate the performance of the proposed model. In order to measure the forecasting capability of the model, an ordinary least-squares (OLS) regression and a typical three-layer feed-forward artificial neural network (ANN) are employed as the benchmark model. The performance of the models was tested using the root mean squared error (RMSE), the average absolute relative error (AARE), the coefficient of correlation ( R ) and Nash–Sutcliffe efficiency (NSE). The PSO–SVM–EEMD model improved ANN model forecasting (65.99%) and OLS regression (64.40%), and reduced RMSE (67.7%) and AARE (65.38%) values. Improvements of the forecasting results regarding the R and NSE are 8.43%, 18.89% and 182.7%, 164.2%, respectively. Consequently, the presented methodology in this research can enhance significantly rainfall-runoff forecasting at the studied station. read more read less
View PDF
261 Citations
open accessOpen access Journal Article DOI: 10.2166/HYDRO.2003.0003
WEST: modelling biological wastewater treatment

Abstract:

Modelling is considered to be an inherent part of the design and operation of a wastewater treatment system. The models used in practice range from conceptual models and physical design models (laboratory-scale or pilot-scale reactors) to empirical or mechanistic mathematical models. These mathematical models can be used duri... Modelling is considered to be an inherent part of the design and operation of a wastewater treatment system. The models used in practice range from conceptual models and physical design models (laboratory-scale or pilot-scale reactors) to empirical or mechanistic mathematical models. These mathematical models can be used during the design, operation and optimisation of a wastewater treatment system. To do so, a good software tool is indispensable. WEST is a general modelling and simulation environment and can, together with a model base, be used for this task. The model base presented here is specific for biological wastewater treatment and is written in MSL-USER. In this high-level object-oriented language, the dynamics of systems can be represented along with symbolic information. In WEST’s graphical modelling environment, the physical layout of the plant can be rebuilt, and each building block can be linked to a specific model from the model base. The graphical information is then combined with the information in the model base to produce MSL-EXEC code, which can be compiled with a C++ compiler. In the experimentation environment, the user can design different experiments, such as simulations and optimisations of, for instance, designs, controllers and model fits to data (calibration). read more read less
View PDF
227 Citations
open accessOpen access Journal Article DOI: 10.2166/HYDRO.2007.027
Flood forecasting using support vector machines
Dawei Han1, L. Chan1, N. Zhu1

Abstract:

This paper describes an application of SVM over the Bird Creek catchment and addresses some important issues in developing and applying SVM in flood forecasting. It has been found that, like artificial neural network models, SVM also suffers from over-fitting and under-fitting problems and the over-fitting is more damaging th... This paper describes an application of SVM over the Bird Creek catchment and addresses some important issues in developing and applying SVM in flood forecasting. It has been found that, like artificial neural network models, SVM also suffers from over-fitting and under-fitting problems and the over-fitting is more damaging than under-fitting. This paper illustrates that an optimum selection among a large number of various input combinations and parameters is a real challenge for any modellers in using SVMs. A comparison with some benchmarking models has been made, i.e. Transfer Function, Trend and Naive models. It demonstrates that SVM is able to surpass all of them in the test data series, at the expense of a huge amount of time and effort. Unlike previous published results, this paper shows that linear and nonlinear kernel functions (i.e. RBF) can yield superior performances against each other under different circumstances in the same catchment. The study also shows an interesting result in the SVM response to different rainfall inputs, where lighter rainfalls would generate very different responses to heavier ones, which is a very useful way to reveal the behaviour of a SVM model. read more read less
217 Citations
open accessOpen access Journal Article DOI: 10.2166/HYDRO.2013.132
Real-time urban flood forecasting and modelling – a state of the art
J Hénonin, Beniamino Russo, Ole Mark, Philippe Gourbesville1

Abstract:

All urban drainage networks are designed to manage a maximum rainfall. This situation implies an accepted flood risk for any greater rainfall event. This risk is often underestimated as factors such as city growth and climate change are ignored. But even major structural changes cannot guarantee that urban drainage networks w... All urban drainage networks are designed to manage a maximum rainfall. This situation implies an accepted flood risk for any greater rainfall event. This risk is often underestimated as factors such as city growth and climate change are ignored. But even major structural changes cannot guarantee that urban drainage networks would cope with all future rain events. Thus, being able to forecast urban flooding in real time is one of the main issues of integrated flood risk management. Runoff and hydraulic models can be essential elements of flood forecast systems, as an active part of the system or as studying tools. This paper gives an overview of current available options for pluvial flood modelling in urban areas, from basic estimations with a one-dimensional urban drainage model to detailed flood process representation with one dimensional–two dimensional hydrodynamic coupled models. Each type of modelling solution is described with pros and cons regarding urban flood analysis. The paper then elaborates on real-time flood forecast systems and the influence of their main components. A classification of real-time urban flood systems is given based on the use of urban models, i.e. empirical scenarios, pre-simulated scenarios and real-time simulations. A review of existing operational systems is done using this classification. read more read less
208 Citations
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Journal of Hydroinformatics format uses plainnat citation style.

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Frequently asked questions

1. Can I write Journal of Hydroinformatics in LaTeX?

Absolutely not! Our tool has been designed to help you focus on writing. You can write your entire paper as per the Journal of Hydroinformatics guidelines and auto format it.

2. Do you follow the Journal of Hydroinformatics guidelines?

Yes, the template is compliant with the Journal of Hydroinformatics guidelines. Our experts at SciSpace ensure that. If there are any changes to the journal's guidelines, we'll change our algorithm accordingly.

3. Can I cite my article in multiple styles in Journal of Hydroinformatics?

Of course! We support all the top citation styles, such as APA style, MLA style, Vancouver style, Harvard style, and Chicago style. For example, when you write your paper and hit autoformat, our system will automatically update your article as per the Journal of Hydroinformatics citation style.

4. Can I use the Journal of Hydroinformatics templates for free?

Sign up for our free trial, and you'll be able to use all our features for seven days. You'll see how helpful they are and how inexpensive they are compared to other options, Especially for Journal of Hydroinformatics.

5. Can I use a manuscript in Journal of Hydroinformatics that I have written in MS Word?

Yes. You can choose the right template, copy-paste the contents from the word document, and click on auto-format. Once you're done, you'll have a publish-ready paper Journal of Hydroinformatics that you can download at the end.

6. How long does it usually take you to format my papers in Journal of Hydroinformatics?

It only takes a matter of seconds to edit your manuscript. Besides that, our intuitive editor saves you from writing and formatting it in Journal of Hydroinformatics.

7. Where can I find the template for the Journal of Hydroinformatics?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Journal of Hydroinformatics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

8. Can I reformat my paper to fit the Journal of Hydroinformatics's guidelines?

Of course! You can do this using our intuitive editor. It's very easy. If you need help, our support team is always ready to assist you.

9. Journal of Hydroinformatics an online tool or is there a desktop version?

SciSpace's Journal of Hydroinformatics is currently available as an online tool. We're developing a desktop version, too. You can request (or upvote) any features that you think would be helpful for you and other researchers in the "feature request" section of your account once you've signed up with us.

10. I cannot find my template in your gallery. Can you create it for me like Journal of Hydroinformatics?

Sure. You can request any template and we'll have it setup within a few days. You can find the request box in Journal Gallery on the right side bar under the heading, "Couldn't find the format you were looking for like Journal of Hydroinformatics?”

11. What is the output that I would get after using Journal of Hydroinformatics?

After writing your paper autoformatting in Journal of Hydroinformatics, you can download it in multiple formats, viz., PDF, Docx, and LaTeX.

12. Is Journal of Hydroinformatics's impact factor high enough that I should try publishing my article there?

To be honest, the answer is no. The impact factor is one of the many elements that determine the quality of a journal. Few of these factors include review board, rejection rates, frequency of inclusion in indexes, and Eigenfactor. You need to assess all these factors before you make your final call.

13. What is Sherpa RoMEO Archiving Policy for Journal of Hydroinformatics?

SHERPA/RoMEO Database

We extracted this data from Sherpa Romeo to help researchers understand the access level of this journal in accordance with the Sherpa Romeo Archiving Policy for Journal of Hydroinformatics. The table below indicates the level of access a journal has as per Sherpa Romeo's archiving policy.

RoMEO Colour Archiving policy
Green Can archive pre-print and post-print or publisher's version/PDF
Blue Can archive post-print (ie final draft post-refereeing) or publisher's version/PDF
Yellow Can archive pre-print (ie pre-refereeing)
White Archiving not formally supported
FYI:
  1. Pre-prints as being the version of the paper before peer review and
  2. Post-prints as being the version of the paper after peer-review, with revisions having been made.

14. What are the most common citation types In Journal of Hydroinformatics?

The 5 most common citation types in order of usage for Journal of Hydroinformatics are:.

S. No. Citation Style Type
1. Author Year
2. Numbered
3. Numbered (Superscripted)
4. Author Year (Cited Pages)
5. Footnote

15. How do I submit my article to the Journal of Hydroinformatics?

It is possible to find the Word template for any journal on Google. However, why use a template when you can write your entire manuscript on SciSpace , auto format it as per Journal of Hydroinformatics's guidelines and download the same in Word, PDF and LaTeX formats? Give us a try!.

16. Can I download Journal of Hydroinformatics in Endnote format?

Yes, SciSpace provides this functionality. After signing up, you would need to import your existing references from Word or Bib file to SciSpace. Then SciSpace would allow you to download your references in Journal of Hydroinformatics Endnote style according to Elsevier guidelines.

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I spent hours with MS word for reformatting. It was frustrating - plain and simple. With SciSpace, I can draft my manuscripts and once it is finished I can just submit. In case, I have to submit to another journal it is really just a button click instead of an afternoon of reformatting.

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