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Observation and Modelling of Past, Current and Future Water Resources...
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Observation and Modelling of Past, Current and Future Water Resources in Transboundary River Systems

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: 20 June 2026 | Viewed by 1470

Special Issue Editors

Dr. Juraj Parajka

E-Mail Website
Guest Editor
Institute of Hydraulic Engineering and Water Resources, Vienna University of Technology, A-1040 Vienna, Austria
Interests: observation and modelling of water cycle components at different scales
Special Issues, Collections and Topics in MDPI journals
Dr. Zsolt Kozma

E-Mail Website
Guest Editor
Department of Sanitary and Environmental Engineering, Budapest University of Technology and Economics, H-1111 Budapest, Hungary
Interests: hydrological modeling; vadose zone; surface–groundwater interaction; natural water retention measures; ecosystem services
Special Issues, Collections and Topics in MDPI journals
Dr. Peter Burek

E-Mail Website
Guest Editor
International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
Interests: hydrological modelling; water cycle; climate change assessment

Special Issue Information

Dear Colleagues,

Transboundary waters encompass aquifers, lakes, and river systems shared by two or more countries. These waters do not adhere to political boundaries, meaning water use, pollution, or overexploitation in one region can have significant consequences in other parts of the hydrological system. Effective transboundary water management is thus crucial to address pressing issues ranging from water scarcity and biodiversity protection to economic growth and peacekeeping.

Over half of the global population resides in transboundary basins. Given the diverse physical, political, and socio-economic contexts of these shared water bodies, integrated approaches and practices are needed to solve transboundary water problems, foster cooperation, and ensure sustainable management.

We welcome contributions on the following topics:

(1) The modelling and inter-comparison of different models (ranging from traditional hydrological models to innovative AI approaches and hybrid applications) for simulating water balance components and water quality, including climate change impact studies, sensitivity analyses, and uncertainty evaluations in transboundary river systems.

(2) The evaluation of performance and uncertainty of transboundary datasets of climate and hydrological characteristics, including remote sensing products and climate projections. We seek contributions that explore how remote sensing can help close the transboundary water data gap, offering cost-effective, scalable solutions for monitoring and assessing water resources across borders.

(3) Applications supporting the sustainable management of transboundary water, including water abstractions, water-savings, or water retention solutions in agriculture and industry.

(4) The development and implementation of joint monitoring and information systems, such as GIS-based databases, which facilitate effective cooperation in water-related risk reduction and transboundary resilience modelling. These include experiences with joint problem definition, creating a common understanding and evaluating the effectiveness of implemented strategies.

(5) The involvement of multi-level stakeholder engagement in shared water management. This includes capacity development, voluntary data collection through citizen science, participatory modelling, trust-building, and science-policy-driven decision-making.

Dr. Juraj Parajka
Dr. Zsolt Kozma
Dr. Peter Burek
Guest Editors

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 250 words) can be sent to the Editorial Office for assessment.

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. Water is an international peer-reviewed open access semimonthly 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 2600 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

  • transboundary river system
  • hydrological modelling
  • uncertainty of climate projections
  • sustainable river basin management
  • joint monitoring and information systems
  • multi-level stakeholder engagement

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Published Papers (2 papers)

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Research

21 pages, 2807 KB  
Article
Assessing Pollution Mitigation in Transboundary Waters Through Biosorption Technique in Rural Andean Bolivia
by Alejandra Paz Rios, Paula Cecilia Soto-Ríos, Cristhian Carrasco, Brenda Acevedo-Juárez, Laura Mamani-Garcia and Nidhi Nagabhatla
Water 2026, 18(6), 703; https://doi.org/10.3390/w18060703 - 17 Mar 2026
Viewed by 413
Abstract
Heavy metal pollution from mining activities and urban runoff poses a serious threat to public health and aquatic ecosystems in vulnerable communities around the Bolivia–Peru transboundary Lake Titicaca basin. This study evaluates the use of two abundant wetland plants—totora (Schoenoplectus californicus) [...] Read more.
Heavy metal pollution from mining activities and urban runoff poses a serious threat to public health and aquatic ecosystems in vulnerable communities around the Bolivia–Peru transboundary Lake Titicaca basin. This study evaluates the use of two abundant wetland plants—totora (Schoenoplectus californicus) and reed (Phragmites australis)—as low-cost, locally available biosorbents for the removal of dissolved iron (Fe2+) from the Pallina River, a major contaminant source to Cohana Bay. Monitoring data from Bolivia’s Ministry of Environment and Water (2019–2022) revealed Fe2+ concentrations exceeding the national legal limit (0.3 mg/L) by more than 20 times during the dry season. Laboratory experiments using synthetic Fe2+ solutions (20 mg/L) optimized biosorption conditions, identifying pH 5, 4–6 g/L biomass, fine particle size (0.15–0.212 mm), and a 3 h contact time as optimal. Both plants followed pseudo-second-order kinetics and Langmuir isotherms. Totora showed superior performance, achieving a maximum capacity of 7.8 mg/g compared to reed’s 2.9 mg/g. Continuous-flow column tests removed up to 95% of Fe2+ from synthetic water. When applied to real Pallina River water, totora achieved 50% Fe2+ removal despite reduced efficiency due to competing organic matter. The findings demonstrate the potential of totora-based biosorption as a scalable, nature-based solution for transboundary water management. The policy implications of this study are profound under the national and global water and wetland governance mechanisms and transboundary frameworks like the Binational Autonomous Authority of Lake Titicaca (ALT, est. 1996) and Ramsar Convention. Full article
(This article belongs to the Special Issue Observation and Modelling of Past, Current and Future Water Resources in Transboundary River Systems)
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21 pages, 2107 KB  
Article
A High-Precision Daily Runoff Prediction Model for Cross-Border Basins: RPSEMD-IMVO-CSAT Based on Multi-Scale Decomposition and Parameter Optimization
by Tianming He, Yilin Yang, Zheng Wang, Zongzheng Mo and Chu Zhang
Water 2026, 18(1), 48; https://doi.org/10.3390/w18010048 - 23 Dec 2025
Viewed by 526
Abstract
As the last critical hydrological control station on the Lancang River before it flows out of China, the daily runoff variations at the Yunjinghong Hydrological Station are directly linked to agricultural irrigation, hydropower development, and ecological security in downstream Mekong River riparian countries [...] Read more.
As the last critical hydrological control station on the Lancang River before it flows out of China, the daily runoff variations at the Yunjinghong Hydrological Station are directly linked to agricultural irrigation, hydropower development, and ecological security in downstream Mekong River riparian countries such as Laos, Myanmar, and Thailand. Aiming at the core issues of the runoff sequence in the Lancang–Mekong Basin, which is characterized by prominent nonlinearity, non-stationarity, and coupling of multi-scale features, this study proposes a synergistic prediction framework of “multi-scale decomposition-model improvement-parameter optimization”. Firstly, Regenerated Phase-Shifted Sine-Assisted Empirical Mode Decomposition (RPSEMD) is adopted to adaptively decompose the daily runoff data. On this basis, a Convolutional Sparse Attention Transformer (CSAT) model is constructed. A one-dimensional convolutional neural network (1D-CNN) module is embedded in the input layer to enhance local feature perception, making up for the deficiency of traditional Transformers in capturing detailed information. Meanwhile, the sparse attention mechanism replaces the multi-head attention, realizing efficient focusing on key time-step correlations and reducing computational costs. Additionally, an Improved Multi-Verse Optimizer (IMVO) is introduced, which optimizes the hyperparameters of CSAT through a spiral update mechanism, exponential Travel Distance Rate (T_DR), and adaptive compression factor, thereby improving the model’s accuracy in capturing short-term abrupt patterns such as flood peaks and drought transition points. Experiments are conducted using measured daily runoff data from 2010 to 2022, and the proposed model is compared with mainstream models such as LSTM, GRU, and standard Transformer. The results show that the RPSEMD-IMVO-CSAT model reduces the Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) by 15.3–28.7% and 18.6–32.4%, respectively, compared with the comparative models. Full article
(This article belongs to the Special Issue Observation and Modelling of Past, Current and Future Water Resources in Transboundary River Systems)
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