Topic Editors

School of Life Sciences, Technical University of Munich, Munich, Germany
Department of Earth Sciences and Program of Environmental Studies, University of California, Santa Barbara, CA 93106, USA

Advances in Hydrogeological Research

Abstract submission deadline
31 October 2024
Manuscript submission deadline
31 December 2024
Viewed by
2574

Topic Information

Dear Colleagues,

Advances in hydrogeological research can lead to the better management of water resources and identify a roadmap to address future challenges. The hydrogeologist community has developed interdisciplinary approaches in terms of concepts, models, and techniques as well as tools at different scales (from the laboratory to the field). The aim is to highlight isotope methods, qualitative and quantitative models, vulnerability, adsorption–desorption, diffusion mechanisms, fractionation, analytical development, emerging contaminants, nanoparticles, nanoplastics, colloids, aquatic ecology, remediation, treatment, climate impacts, etc. Our goal is to repair or propose state-of-the-art technologies based on interdisciplinary and multidisciplinary hydrogeological approaches.

Prof. Dr. Karl Auerswald
Prof. Dr. Jordan Clark
Topic Editors

Keywords

  • hydrology
  • groundwater
  • soil erosion
  • water resource management
  • hydrogeology
  • surface waters
  • stable isotopes

Participating Journals

Journal Name Impact Factor CiteScore Launched Year First Decision (median) APC
Geosciences
geosciences
2.7 5.2 2011 23.6 Days CHF 1800 Submit
Hydrology
hydrology
3.2 4.1 2014 17.8 Days CHF 1800 Submit
Remote Sensing
remotesensing
5.0 7.9 2009 23 Days CHF 2700 Submit
Sustainability
sustainability
3.9 5.8 2009 18.8 Days CHF 2400 Submit
Water
water
3.4 5.5 2009 16.5 Days CHF 2600 Submit

Preprints.org is a multidiscipline platform providing preprint service that is dedicated to sharing your research from the start and empowering your research journey.

MDPI Topics is cooperating with Preprints.org and has built a direct connection between MDPI journals and Preprints.org. Authors are encouraged to enjoy the benefits by posting a preprint at Preprints.org prior to publication:

  1. Immediately share your ideas ahead of publication and establish your research priority;
  2. Protect your idea from being stolen with this time-stamped preprint article;
  3. Enhance the exposure and impact of your research;
  4. Receive feedback from your peers in advance;
  5. Have it indexed in Web of Science (Preprint Citation Index), Google Scholar, Crossref, SHARE, PrePubMed, Scilit and Europe PMC.

Published Papers (3 papers)

Order results
Result details
Journals
Select all
Export citation of selected articles as:
16 pages, 8348 KiB  
Article
Trends in Concentration and Flux of Total Suspended Matter in the Irrawaddy River
by Zhuoqi Zheng, Difeng Wang, Dongyang Fu, Fang Gong, Jingjing Huang, Xianqiang He and Qing Zhang
Remote Sens. 2024, 16(5), 753; https://doi.org/10.3390/rs16050753 - 21 Feb 2024
Viewed by 517
Abstract
Large rivers without hydrological data from remote sensing observations have recently become a hot research topic. The Irrawaddy River is among the major tropical rivers worldwide; however, published hydrological data on this river have rarely been obtained in recent years. In this paper, [...] Read more.
Large rivers without hydrological data from remote sensing observations have recently become a hot research topic. The Irrawaddy River is among the major tropical rivers worldwide; however, published hydrological data on this river have rarely been obtained in recent years. In this paper, based on the existing measured the total suspended matter flux (FTSM) and discharge data for the Irrawaddy River, an inversion model of the total suspended matter concentration (CTSM) is constructed for the Irrawaddy River, and the CTSM and FTSM from 1990 to 2020 are estimated using the L1 products of Landsat-8 OLI/TIRS and Landsat-5 TM. The results show that over the last 30 years, the FTSM of the Irrawaddy River decreased at a rate of 3.9 Mt/yr, which is significant at the 99% confidence interval. An increase in the vegetation density of the Irrawaddy Delta has increased the land conservation capacity of the region and reduced the inflow of land-based total suspended matter (TSM). The FTSM of the Irrawaddy River was estimated by fusing satellite data and data measured at hydrological stations. The research method employed in this paper provides a new supplement to the existing hydrological data for large rivers. Full article
(This article belongs to the Topic Advances in Hydrogeological Research)
Show Figures

Figure 1

22 pages, 4184 KiB  
Article
A Transfer Learning Approach Based on Radar Rainfall for River Water-Level Prediction
by Futo Ueda, Hiroto Tanouchi, Nobuyuki Egusa and Takuya Yoshihiro
Water 2024, 16(4), 607; https://doi.org/10.3390/w16040607 - 18 Feb 2024
Viewed by 726
Abstract
River water-level prediction is crucial for mitigating flood damage caused by torrential rainfall. In this paper, we attempt to predict river water levels using a deep learning model based on radar rainfall data instead of data from upstream hydrological stations. A prediction model [...] Read more.
River water-level prediction is crucial for mitigating flood damage caused by torrential rainfall. In this paper, we attempt to predict river water levels using a deep learning model based on radar rainfall data instead of data from upstream hydrological stations. A prediction model incorporating a two-dimensional convolutional neural network (2D-CNN) and long short-term memory (LSTM) is constructed to exploit geographical and temporal features of radar rainfall data, and a transfer learning method using a newly defined flow–distance matrix is presented. The results of our evaluation of the Oyodo River basin in Japan show that the presented transfer learning model using radar rainfall instead of upstream measurements has a good prediction accuracy in the case of torrential rain, with a Nash–Sutcliffe efficiency (NSE) value of 0.86 and a Kling–Gupta efficiency (KGE) of 0.83 for 6-h-ahead forecast for the top-four peak water-level height cases, which is comparable to the conventional model using upstream measurements (NSE = 0.84 and KGE = 0.83). It is also confirmed that the transfer learning model maintains its performance even when the amount of training data for the prediction site is reduced; values of NSE = 0.82 and KGE = 0.82 were achieved when reducing the training torrential-rain-period data from 12 to 3 periods (with 105 periods of data from other rivers for transfer learning). The results demonstrate that radar rainfall data and a few torrential rain measurements at the prediction location potentially enable us to predict river water levels even if hydrological stations have not been installed at the prediction location. Full article
(This article belongs to the Topic Advances in Hydrogeological Research)
Show Figures

Figure 1

22 pages, 7815 KiB  
Article
Quantitative Groundwater Modelling under Data Scarcity: The Example of the Wadi El Bey Coastal Aquifer (Tunisia)
by Hatem Baccouche, Manon Lincker, Hanene Akrout, Thuraya Mellah, Yves Armando and Gerhard Schäfer
Water 2024, 16(4), 522; https://doi.org/10.3390/w16040522 - 06 Feb 2024
Viewed by 961
Abstract
The Grombalia aquifer constitutes a complex aquifer system formed by shallow, unconfined, semi-deep, and deep aquifers at different exploitation levels. In this study, we focused on the upper aquifer, the Wadi El Bey coastal aquifer. To assess natural aquifer recharge, we used a [...] Read more.
The Grombalia aquifer constitutes a complex aquifer system formed by shallow, unconfined, semi-deep, and deep aquifers at different exploitation levels. In this study, we focused on the upper aquifer, the Wadi El Bey coastal aquifer. To assess natural aquifer recharge, we used a novel physiography-based method that uses soil texture-dependent potential infiltration coefficients and monthly rainfall data. The developed transient flow model was then applied to compute the temporal variation in the groundwater level in 34 observation wells from 1973 to 2020, taking into account the time series of spatially variable groundwater recharge, artificial groundwater recharge from 5 surface infiltration basins, pumping rates on 740 wells, and internal prescribed head cells to mimic water exchange between the wadis and aquifer. The quantified deviations in the computed hydraulic heads from measured water levels are acceptable because the database used to construct a scientifically sound and reliable groundwater model was limited. Further work is required to collect field data to quantitatively assess the local inflow and outflow rates between surface water and groundwater. The simulation of 12 climate scenarios highlighted a bi-structured north—south behaviour in the hydraulic heads: an increase in the north and a depletion in the south. A further increase in the pumping rate would, thus, be severe for the southern part of the Wadi El Bey aquifer. Full article
(This article belongs to the Topic Advances in Hydrogeological Research)
Show Figures

Figure 1

Back to TopTop