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Journals
Geographies
Special Issues
Feature Papers of Geographies in 2024
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Feature Papers of Geographies in 2024

A special issue of Geographies (ISSN 2673-7086).

Deadline for manuscript submissions: 30 December 2024 | Viewed by 605

Special Issue Editor

Dr. Xu Chen

E-Mail Website
Guest Editor
Department of Geography, School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
Interests: physical geography; environmental change; lake ecosystem; paleoecology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce this Special Issue, entitled “Feature Papers of Geographies in 2024”. This Special Issue will serve as a collection of articles from Editorial Board Members, Guest Editors, and Leading Researchers discussing new knowledge or new cutting-edge developments in centered around the different aspects of geography in 2024. Potential topics include, but are not limited to, the following:

  • Climatology;
  • Geomorphology;
  • Glaciology;
  • Biogeography;
  • Hydrology and hydrography;
  • Landscape ecology;
  • Soil geography;
  • Quaternary environmental change;
  • Environmental geography;
  • Geomatics;
  • Spatial analysis;
  • Cartography and mapping;
  • Geographical information systems.

Dr. Xu Chen
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Geographies is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • climatology
  • geomorphology
  • glaciology
  • biogeography
  • hydrology and hydrography
  • landscape ecology
  • soil geography
  • global change
  • environmental management
  • geomatics
  • spatial analysis
  • cartography and mapping
  • geographical information systems

Related Special Issue

Published Papers (1 paper)

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Research

15 pages, 2524 KiB  
Article
Application of Machine Learning Models for Improving Discharge Prediction in Ungauged Watershed: A Case Study in East DuPage, Illinois
by Amin Asadollahi, Binod Ale Magar, Bishal Poudel, Asyeh Sohrabifar and Ajay Kalra
Geographies 2024, 4(2), 363-377; https://doi.org/10.3390/geographies4020021 - 6 Jun 2024
Viewed by 366
Abstract
Accurate flood prediction models and effective flood preparedness rely on thoroughly understanding rainfall–runoff dynamics. Similarly, effective rainfall–runoff models account for multiple interrelated parameters for robust runoff prediction. Process-based physical models offer valuable insights into hydrological processes, but their effectiveness can be hindered by [...] Read more.
Accurate flood prediction models and effective flood preparedness rely on thoroughly understanding rainfall–runoff dynamics. Similarly, effective rainfall–runoff models account for multiple interrelated parameters for robust runoff prediction. Process-based physical models offer valuable insights into hydrological processes, but their effectiveness can be hindered by data limitations or difficulties in acquiring specific data. Motivated by the frequent flooding events and limited data availability in the East Branch DuPage watershed, Illinois, this study addresses a critical gap in research by investigating effective discharge prediction methods. In this study, two significant machine learning (ML) models, artificial neural network (ANN) and support vector machine (SVM), were employed for discharge prediction. Historical data spanning from 2006 to 2021 were utilized to assess the performance of the models. Hyperparameter tuning was performed on the models to optimize their performance, and root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), percent bias (PBIAS), coefficient of determination (R2), and the normalized root mean squared error (NRMSE) were used as evaluation metrics. Although both machine learning models demonstrated strong performance, the analysis revealed that the ANN model emerged as the more reliable option for predicting discharge in the watershed. Crucially, the ANN model surpassed the SVM model’s performance, achieving superior accuracy in predicting peak discharge events within the study area. Our findings have the potential to assist decision-makers and communities in implementing more dependable flood mitigation strategies, particularly in regions where hydrology data are limited. Full article
(This article belongs to the Special Issue Feature Papers of Geographies in 2024)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

1. Title: Assessing the Efficiency of Fully 2-Dimensional Hydraulic Hec-Ras Models in Rivers of Cyprus

Authors: Georgia Siakara, Nikolaos Gourgouletis, Evangelos Baltas

2. Title: A Balloon Mapping Approach to Forecast Increases in PM10 from the Shrinking Shoreline at the Salton Sea

Authors: Ryan G. Sinclair, Joseliede Gaio, Seth Wiafe, Isabella Arzeno-Soltero and William C. Porter

3. Title: Neighborhood-Scale Wildfire Evacuation Vulnerability in Hays County, TX

Authors: Yihong Yuan and Chad Ramos

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