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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Water Management".

Deadline for manuscript submissions: 31 August 2026 | Viewed by 5669

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Special Issue Editors

Dr. Shimin Tian

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Guest Editor

Henan Key Laboratory of Ecological Environment Protection and Restoration of Yellow River Basin, Yellow River Institute of Hydraulic Research, Zhengzhou 450003, China
Interests: hydrology and sustainable water resource management; sediment transport and river channel evolution mechanisms; river dynamics and floodplain risk assessment; ecological water demand and river habitat restoration; sediment–flow regulation and integrated reservoir management; integrated watershed governance and eco-policy synergy
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Dr. Jia Jia

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Yellow River Institute of Hydraulic Research, Zhengzhou 450003, China
Interests: polychlorinated biphenyls (PCBs); freshwater wetlands; community structure; depth distribution; possible sources

Special Issue Information

Dear Colleagues,

Water is an indispensable natural resource that delivers multifaceted value to both ecosystems and human societies. In the last half century, as the demand for water increases, the sustainable management of hydrology, water resources and ecosystems faces mounting challenges from climate change, population growth, and human activities. Growing agricultural, industrial, and urban water demands, alongside pollution and habitat destruction, demand integrated strategies that balance hydrological rhythm, socio-economic equity, and ecological resilience.

Based on the above, this Special Issue has a specific on the “Advances in Management of Hydrology, Water Resources and Ecosystem”, which aims to help the effective management and utilization of water resources while balancing their environmental, economic, and societal impacts. This comprehensive scope addresses multiple facets of water resource management, evaluation of flood and drought hazards, surface water reservoir administration, watershed stewardship programs, engineered water control structures, and the changes in water resources and hydrology effects on ecosystems. In addition, studies that focus on new developments in the processes governing hydrological and water resources cyclings, and interactions with ecology and environment, and the provision of ecosystem services under the multi-sediment and flow regulation strategy are of much concern. We particularly encourage studies that deal with new knowledge and modelling approaches relevant to the integration of water resources—water environment—water ecology.

In this Special Issue, we invite researchers, experts, and professionals from research institutions, universities, national and international organizations to contribute their understanding and achievements in these fields. Research areas may include (but are not limited to) the following:

Sustainable water resource management frameworks
Climate-resilient ecosystem restoration strategies
Integrated hydrological modeling techniques
Pollution control and water-quality management
Socio-economic equity in water governance
Remote sensing and AI in hydrological monitoring
Sustainable development goals alignment for water security
Ecosystem-based adaptation to climate extremes
Legal frameworks for resource-environment governance

I look forward to receiving your contributions.

Dr. Shimin Tian
Dr. Jia Jia
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 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

water resources management
hydrological modelling
ecological conservation
ecosystem restoration
water quality
sediment–flow regulation
water security

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Published Papers (9 papers)

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Research

17 pages, 1915 KB

Open AccessArticle

Global Lake Color Phenology Changes Since the 1980s Based on Landsat Images

by Chaoqiong Wang, Xuege Wang and Xiaoyi Shen

Sustainability 2026, 18(10), 4732; https://doi.org/10.3390/su18104732 - 9 May 2026

Viewed by 304

Abstract

Lake color is an intuitive indicator reflecting the ecological and physicochemical status of lakes and is of great value for both ecological monitoring and environmental assessment. However, the types, spatiotemporal variations, and driving mechanisms of global lake color phenology remain unclear. In this study, we systematically analyzed the color phenology of 975 global lakes based on Landsat remote sensing data from 1984 to 2021. The results indicate that lake color phenology can be categorized into six types, including the perennial green type, evergreen type, and seasonal patterns (spring green, summer green, autumn green, and winter green). Approximately 43.9% of the lakes are classified as the evergreen type, mainly concentrated in the Southern Hemisphere. Further research reveals notable spatial differences in the change in lake color phenology: about 69.4% of lakes in the Southern Hemisphere exhibit relatively stable phenological patterns (frequency of changes within the study area ≤ 2), while approximately 64.4% in the Northern Hemisphere show phenological variations. This dynamic disparity is closely related to lake attributes (area, water depth, elevation) as well as external climatic and watershed conditions (precipitation, wind speed, vegetation). Our findings contribute to developing the interannual patterns of lake color into a novel ecological indicator, thereby advancing the dynamic monitoring and assessment of global lake status. Full article

(This article belongs to the Special Issue Advances in Management of Hydrology, Water Resources and Ecosystem)

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21 pages, 1496 KB

Open AccessArticle

A Decomposition-Based Deep Learning Model for Multivariate Water Quality Prediction

by Qiliang Zhu, Xueting Yu and Hongtao Fu

Sustainability 2026, 18(8), 4129; https://doi.org/10.3390/su18084129 - 21 Apr 2026

Viewed by 376

Abstract

The extensive deployment of automatic water quality monitoring stations has generated substantial volumes of time-series data. Effectively utilizing these data is crucial for enhancing prediction accuracy. To address the limitations of existing models in capturing complex inter-indicator relationships and multi-scale temporal features, this paper proposes a hybrid prediction model integrating time series decomposition with deep learning techniques. Adopting a “decomposition–prediction–reconstruction” paradigm, the model first decomposes the raw time series into trend, seasonal, and residual components using STL (Seasonal–Trend decomposition using LOESS). For the trend component, an improved Graph Convolutional Network (GCN) is designed to explicitly model the spatial dependencies among different water quality indicators. For the seasonal component, the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method is employed for multi-scale signal analysis, followed by a coupled Long Short-Term Memory–Convolutional Neural Network (LSTM-CNN) unit to capture both long-term dependencies and local features. To validate the efficacy of the proposed model, experiments were conducted on three real-world water quality datasets from different watersheds. Experimental results demonstrate that the proposed model outperforms mainstream baseline models, including StemGCN, LSTM-CNN, CEEMDAN-LSTM-CNN, and Attention-CLX. Across the three datasets, the model consistently outperforms the best-performing baseline, achieving reductions in MAE ranging from 13.8% to 24.5% and up to a 45.3% reduction in RMSE on a single dataset, while the highest correlation coefficient between predicted and observed values reaches 0.855. These findings demonstrate that the proposed decomposition–integration framework effectively enhances the accuracy and stability of multivariate water quality prediction, offering a promising tool for supporting sustainable water resource management. Full article

(This article belongs to the Special Issue Advances in Management of Hydrology, Water Resources and Ecosystem)

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43 pages, 23396 KB

Open AccessArticle

Wildfire Impact Assessment in Watersheds of Alberta’s Regional Aquatic Monitoring Program

by Dayal Wijayarathne, Tiago Antonio Morais, Aprami Jaggi, Nicholas Kouwen, Michael Wendlandt, Tatiana Sirbu and John J. Gibson

Sustainability 2026, 18(8), 3771; https://doi.org/10.3390/su18083771 - 10 Apr 2026

Viewed by 602

Abstract

Wildfire impact on boreal watersheds was assessed across Alberta’s Regional Aquatics Monitoring Program (RAMP) domain by integrating multidecadal river, lake, and sediment physical–chemical data with historical wildfire perimeters, polycyclic aromatic hydrocarbon (PAH) indicators, continuous multiparameter sonde records, and pre-/post-fire hydrologic simulations. Site classification, distinguishing reference, industrial, wildfire, and combined influences, was used to enable spatial and temporal comparisons before, during, and after fires. Our synthesis indicated that wildfire acts as an important disturbance that alters watershed connectivity and transport pathways, resulting in shifts in water quality and quantity in surface waters and longer-term adjustments retained in sediments. The interpretation of chemical signatures, including PAHs, was complicated by overlap between areas with wildfire and industrial activities, highlighting cumulative effects and the importance of spatio–temporal context when assessing and quantifying source contributions for long-term resource sustainability. Hydrologic alteration emerged as the dominant downstream wildfire effect, emphasizing the need for long-term continuous monitoring of fire-responsive indicators, in addition to improved assessment of subsurface pathways in wildfire-prone boreal systems. Full article

(This article belongs to the Special Issue Advances in Management of Hydrology, Water Resources and Ecosystem)

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22 pages, 5074 KB

Open AccessArticle

The Interaction Between Precipitation and Multiple Factors Dominates the Spatiotemporal Evolution of Water Yield in the Minjiang River Basin of China

by Panfeng Dou, Bowen Sun, Yunfeng Tian, Jinshui Zhu and Yi Fan

Sustainability 2026, 18(6), 2756; https://doi.org/10.3390/su18062756 - 11 Mar 2026

Viewed by 317

Abstract

Understanding the complex drivers of water yield is essential for ensuring basin water resource security, yet existing linear approaches often overlook the critical nonlinear effects arising from factor interactions. Previous studies combining the InVEST model with attribution methods have typically treated climate and land use as independent factors, failing to quantify their interactive effects beyond additive assumptions. This study addresses this gap by introducing a coupled framework that explicitly isolates and quantifies nonlinear climate–land interactions through scenario-based residual decomposition and spatial interaction detection. Focusing on the Minjiang River Basin, this study first applies a locally calibrated InVEST model to analyze the spatiotemporal patterns of water yield from 2000 to 2023. Through scenario analysis and the Geographical Detector method, we decoupled the contributions of climatic factors, land use, and their interactions. The results show significant spatiotemporal heterogeneity in water yield, averaging 1053.59 mm, with a spatial pattern aligned closely with precipitation. Climatic factors dominated the changes (average contribution 93.43%), while the direct contribution of land use was minimal (−1.56%). Importantly, a significant nonlinear interaction effect was identified (average 8.13%), with the interplay between precipitation and forest land proportion showing the strongest explanatory power for spatial differentiation (q-statistic up to 96.4%). These findings highlight the necessity of an integrated climate-land regulatory strategy that enhances climate resilience and optimizes key land uses to promote sustainable water management, providing a methodological framework for analyzing complex hydrological drivers. Full article

(This article belongs to the Special Issue Advances in Management of Hydrology, Water Resources and Ecosystem)

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19 pages, 10597 KB

Open AccessArticle

Major Element Distribution, Sources, and Geological Significance in Surface Sediments of Dongping Lake, China

by Bo Li, Hongyan An, Kuanzhen Mao, Ge Gao, Yibing Wang, Yinuo Wang, Tong Zhang, Wenbin Ning and Xinfeng Wang

Sustainability 2026, 18(5), 2634; https://doi.org/10.3390/su18052634 - 8 Mar 2026

Viewed by 358

Abstract

The geochemical characteristics of major elements in lake sediments provide insights into aquatic environmental variations, the regional geological background, and the intensity of weathering processes. This study investigates Dongping Lake (DL) using 20 surface sediment samples, analyzing nine major elements. Spatial interpolation was used to characterize their distribution patterns, while principal component analysis, self-organizing maps, and absolute factor analysis–multiple linear regression methods were applied to identify element sources and interpret their geological significance using weathering indicators. Results show that surface sediments are dominated by SiO₂ (46.49%), Al₂O₃ (13.10%), and CaO (11.25%). Controlled by hydrodynamic conditions, major elements are mainly concentrated in the southern part of the lake near the inflows of the Dawen and Liuchang Rivers, with concentrations decreasing from south to north. Riverine transport is the primary source of major elements, with the Dawen River contributing the most followed by the Liuchang and Yellow rivers. Weathering indicators suggest that source rocks have experienced moderate chemical weathering, reflecting initial sedimentation in a tectonically active setting under warm and humid conditions and relatively short transport distances. These findings provide a geochemical basis for understanding sedimentary processes and environmental evolution in the Dongping Lake basin and offer valuable support for regional water resource management, ecological restoration, and sustainable watershed governance. Full article

(This article belongs to the Special Issue Advances in Management of Hydrology, Water Resources and Ecosystem)

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21 pages, 1995 KB

Open AccessArticle

Hydrological Period, Drainage and Local Environmental Conditions Influence Fish Assemblages in Upland Streams in the Eastern Amazon, Brazil

by Alberto Conceição Figueira da Silva, André Luiz Colares Canto, Sergio Melo and Frank Raynner Vasconcelos Ribeiro

Sustainability 2026, 18(5), 2483; https://doi.org/10.3390/su18052483 - 4 Mar 2026

Viewed by 413

Abstract

Amazon streams are home to a great richness and diversity of fish, having an essential role in maintaining the aquatic ecosystem multifunctionality and global biodiversity. Here, we investigated the structure of the ichthyofauna of upland streams of the Lower Tapajós River and analyzed ecological descriptors of fish assemblages in different drainages in the rainy and dry seasons. A total of 3715 individuals from 110 species were collected. Species richness was higher during the dry season (99 species) than in the rainy season (66 species). Local environmental variables were measured or obtained from publicly accessible databases. Our results showed that ichthyofauna responds to hydrological changes in upland streams in the eastern Amazon. Abundance and richness were greatest during the dry season, with important contributions from representatives of the order Characiformes. Stream structural variables explained most of the variance in assemblage composition (adjusted R² = 0.102, p = 0.004), with channel width, depth, and canopy cover as key factors. The findings underscore the importance of assessing drainage and seasonality effects not only to understand ichthyofaunal biodiversity but also to adequately design research efforts, conservation strategies, and monitoring programs for aquatic environments in the eastern Amazon. Full article

(This article belongs to the Special Issue Advances in Management of Hydrology, Water Resources and Ecosystem)

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34 pages, 5034 KB

Open AccessArticle

Toward Sustainable Restoration of Utah Lake: A Synthesis of the Existing Literature with New Active Dust Sampling Data and Analyses

by Gustavious P. Williams, Jacob B. Taggart, Kristen E. Smith, Theron G. Miller and Stephen T. Nelson

Sustainability 2026, 18(4), 2125; https://doi.org/10.3390/su18042125 - 21 Feb 2026

Cited by 1 | Viewed by 537

Abstract

Utah Lake is a large, shallow, highly eutrophic system that is naturally rich in phosphorus (P) and is prone to harmful algal blooms (HABs). While ongoing regulatory efforts often focus on reducing external anthropogenic P loads, particularly from wastewater treatment plants (WWTPs), accumulating evidence suggests that internal sediment P cycling and atmospheric deposition (AD) govern water column P concentrations and are the primary drivers of the lake’s trophic state. We synthesize the existing literature and present new data to demonstrate that (1) the lake’s P-rich, geologic sediments buffer the water column, rendering it largely insensitive to major changes in anthropogenic P inputs due to sorption dynamics, and (2) AD alone provides sufficient P to sustain the lake’s eutrophic status. New analyses on previous AD measurements combined with new active dust sampling data reinforce these conclusions by demonstrating no attenuation of dust deposition to the interior of Utah Lake. We conclude that efforts focused solely on limiting P inputs will have minimal impact on lowering the water column P concentration or improving the lake’s water quality, and that alternative physical and biological restoration methods, such as carp removal and shoreline restoration, are likely to be far more effective. Full article

(This article belongs to the Special Issue Advances in Management of Hydrology, Water Resources and Ecosystem)

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18 pages, 7325 KB

Open AccessArticle

Investigation of the Effects of Climate Change and Human Activities on the Spatio-Temporal Trends of Vegetation in the Source Region of the Yellow River in China

by Wenyan Deng, Xizhi Lv, Yongxin Ni, Li Ma, Qiufen Zhang, Jianwei Wang, Hengshuo Zhang, Xin Wen and Wenjie Cheng

Sustainability 2025, 17(21), 9399; https://doi.org/10.3390/su17219399 - 22 Oct 2025

Viewed by 789

Abstract

The dynamic changes in vegetation significantly impact the sustainability, safety, and stability of ecosystems in the source region of the Yellow River. However, the spatiotemporal patterns and driving factors of these changes remain unclear. The MODIS NDVI dataset (1998–2018), together with climatic records from meteorological stations and socio-economic statistics, was collected to investigate the spatiotemporal characteristics of vegetation coverage in the study area. For the analysis, we employed linear trend analysis to assess long-term changes, Pearson correlation analysis to examine the relationships between vegetation dynamics and climatic as well as anthropogenic factors, and t-tests to evaluate the statistical significance of the results. The results indicated the following: (1) From 1998 to 2018, vegetation in the source region of the Yellow River generally exhibited an increasing trend, with 92.7% of the area showed improvement, while only 7.3% experienced degradation. The greatest vegetation increase occurred in areas with elevations of 3250–3750 m, whereas vegetation decline was mainly concentrated in regions with elevations of 5250–6250 m. (2) Seasonal differences in vegetation trends were observed, with significant increases in spring, summer, and winter, and a non-significant decrease in autumn. Vegetation degradation in summer and autumn remains a concern, primarily in southeastern and lower-elevation areas, affecting 25% and 27% of the total area, respectively. The maximum annual average NDVI was 0.70, occurring in 2018, while the minimum value was 0.59, observed in 2003. (3) Strong correlations were observed between vegetation dynamics and climatic variables, with temperature and precipitation showing significant positive correlations with vegetation (r = 0.66 and 0.60, respectively; p < 0.01, t-test), suggesting that increases in temperature and precipitation serve as primary drivers for vegetation improvement. (4) Anthropogenic factors, particularly overgrazing and rapid population growth (both human and livestock), were identified as major contributors to the degradation of low-altitude alpine grasslands during summer and autumn periods, with notable impacts observed in counties with higher livestock density and population growth, indicating that for each unit increase in population trend, the NDVI trend decreases by an average of 0.0001. The findings of this research are expected to inform the design and implementation of targeted ecological conservation and restoration strategies in the source region of the Yellow River, such as optimizing land-use planning, guiding reforestation and grassland management efforts, and establishing region-specific policies to mitigate the impacts of climate change and human activities on vegetation ecosystems. Full article

(This article belongs to the Special Issue Advances in Management of Hydrology, Water Resources and Ecosystem)

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21 pages, 3706 KB

Open AccessArticle

Enhancing the Resilience of the Environment—Economy—Society Composite System in the Upper Yellow River from the Perspective of Configuration Analysis

by Jiaqi Li, Enhui Jiang, Bo Qu, Lingang Hao, Chang Liu and Ying Liu

Sustainability 2025, 17(19), 8719; https://doi.org/10.3390/su17198719 - 28 Sep 2025

Cited by 1 | Viewed by 855

Abstract

Evaluating and enhancing system resilience is essential to strengthen the regional ability to external shocks and promote the synergistic development of environment, economy and society. Taking the Upper Yellow River (UYR) as an example, this paper constructed a resilience evaluation index system for the environment—economy—society (EES) composite system. A three-dimensional space vector model was built to calculate the resilience development index (RDI) of three subsystems and the composite system from 2009 to 2022. Pathways supporting high resilience levels of the composite system were examined using the fuzzy-set qualitative comparative analysis (fsQCA) method from a configuration perspective. The results revealed that (1) the RDI of three subsystems and the composite system in the UYR showed an increasing trend; relatively, the environment and economy subsystems were lower, and their RDI fluctuated between 0.01 and 0.06 for most cities. (2) The emergence of high resilience is not absolutely dominated by a single factor, but rather the interaction of multiple factors. To achieve high resilience levels, all the cities must prioritize both environmental protection and economic structure as core strategic pillars. The difference is that eastern cities need to further consider social development and life quality, while western cities need to consider social development, life quality, and social security. Other cities including Lanzhou, Baiyin, Tianshui, and Ordos should focus on social construction and social security. Exploring the interactive relationship between various influencing factors of the resilience of the composite system from a configuration perspective has to some extent promoted the transformation from a single contingency perspective to a holistic and multi-dimensional perspective. These findings provide policy recommendations for achieving sustainable development in the UYR and other ecologically fragile areas around the world. Full article

(This article belongs to the Special Issue Advances in Management of Hydrology, Water Resources and Ecosystem)

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