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27 pages, 18859 KiB  
Article
Application of a Hierarchical Approach for Architectural Classification and Stratigraphic Evolution in Braided River Systems, Quaternary Strata, Songliao Basin, NE China
by Zhiwen Dong, Zongbao Liu, Yanjia Wu, Yiyao Zhang, Jiacheng Huang and Zekun Li
Appl. Sci. 2025, 15(15), 8597; https://doi.org/10.3390/app15158597 (registering DOI) - 2 Aug 2025
Viewed by 132
Abstract
The description and assessment of braided river architecture are usually limited by the paucity of real geological datasets from field observations; due to the complexity and diversity of rivers, traditional evaluation models are difficult to apply to braided river systems in different climatic [...] Read more.
The description and assessment of braided river architecture are usually limited by the paucity of real geological datasets from field observations; due to the complexity and diversity of rivers, traditional evaluation models are difficult to apply to braided river systems in different climatic and tectonic settings. This study aims to establish an architectural model suitable for the study area setting by introducing a hierarchical analysis approach through well-exposed three-dimensional outcrops along the Second Songhua River. A micro–macro four-level hierarchical framework is adopted to obtain a detailed anatomy of sedimentary outcrops: lithofacies, elements, element associations, and archetypes. Fourteen lithofacies are identified: three conglomerates, seven sandstones, and four mudstones. Five elements provide the basic components of the river system framework: fluvial channel, laterally accreting bar, downstream accreting bar, abandoned channel, and floodplain. Four combinations of adjacent elements are determined: fluvial channel and downstream accreting bar, fluvial channel and laterally accreting bar, erosionally based fluvial channel and laterally accreting bar, and abandoned channel and floodplain. Considering the sedimentary evolution process, the braided river prototype, which is an element-based channel filling unit, is established by documenting three contact combinations between different elements and six types of fine-grained deposits’ preservation positions in the elements. Empirical relationships are developed among the bankfull channel depth, mean bankfull channel depth, and bankfull channel width. For the braided river systems, the establishment of the model promotes understanding of the architecture and evolution, and the application of the hierarchical analysis approach provides a basis for outcrop, underground reservoir, and tank experiments. Full article
(This article belongs to the Section Earth Sciences)
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17 pages, 557 KiB  
Article
Derivation of a Freshwater Quality Benchmark and an Ecological Risk Assessment of Ferric Iron in China
by Qijie Geng and Fei Guo
Toxics 2025, 13(6), 475; https://doi.org/10.3390/toxics13060475 - 4 Jun 2025
Viewed by 487
Abstract
Acid drainage resulting from mining operations has led to significant iron contamination in surface waters, posing serious ecological and public health hazards. Elevated iron levels in freshwater ecosystems can severely affect aquatic organisms and human health. However, there remains a considerable gap in [...] Read more.
Acid drainage resulting from mining operations has led to significant iron contamination in surface waters, posing serious ecological and public health hazards. Elevated iron levels in freshwater ecosystems can severely affect aquatic organisms and human health. However, there remains a considerable gap in the establishment of benchmark values and ecological risk assessments (ERAs) for iron in surface waters in China. This study collected and screened 47 acute and chronic toxicity data points of 22 species for ferric iron (Fe3+) from various studies and databases. Three widely utilized methodologies were applied to derive long-term and short-term water quality criteria (LWQC and SWQC, respectively) for Fe3+; the logistic fitting curve based on the species sensitivity distribution (SSD) method was identified as the most optimal method, yielding an acute HC5 of 689 μg/L and an SWQC of 345 μg/L. The LWQC of Fe3+ was estimated to be 28 μg/L by dividing HC5 by the acute-to-chronic ratio (ACR), owing to the inadequacy of chronic toxicity data for model fitting. Utilizing these benchmarks, an ecological risk assessment (ERA) was conducted to compare the benchmarks with 68 iron exposure data points collected from surface waters across 30 provinces from eight river basins of China. The findings of 30% of the acute risk quotients and 83% of the chronic risk quotients raise substantial ecological concerns, primarily regarding the Yellow River Basin, Huaihe River Basin, and Songhua and Liaohe River Basin. This research provides critical insights into Fe3+ toxicity data collection and benchmark derivations, offering a benchmark data foundation for the remediation of surface water iron contamination and water quality management in China. Full article
(This article belongs to the Section Exposome Analysis and Risk Assessment)
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19 pages, 3536 KiB  
Article
Unlocking Synergistic Photo-Fenton Catalysis with Magnetic SrFe12O19/g-C3N4 Heterojunction for Sustainable Oxytetracycline Degradation: Mechanisms and Applications
by Song Cui, Yaocong Liu, Xiaolong Dong and Xiaohu Fan
Nanomaterials 2025, 15(11), 833; https://doi.org/10.3390/nano15110833 - 30 May 2025
Viewed by 472
Abstract
The widespread contamination of aquatic environments by tetracycline antibiotics (TCs) poses a substantial threat to public health and ecosystem stability. Although photo-Fenton processes have demonstrated remarkable efficacy in degrading TCs, their practical application is limited by challenges associated with catalyst recyclability. This study [...] Read more.
The widespread contamination of aquatic environments by tetracycline antibiotics (TCs) poses a substantial threat to public health and ecosystem stability. Although photo-Fenton processes have demonstrated remarkable efficacy in degrading TCs, their practical application is limited by challenges associated with catalyst recyclability. This study reports the development of a novel magnetic recoverable SrFe12O19/g-C3N4 heterostructure photocatalyst synthesized via a facile one-step co-calcination method using industrial-grade precursors. Comprehensive characterization revealed that nitrogen defects and the formation of heterojunction structures significantly suppress electron (e)–hole (h+) pair recombination, thereby markedly enhancing catalytic activity. The optimized 7-SFO/CN composite removes over 90% of oxytetracycline (OTC) within 60 min, achieving degradation rate constants of 0.0393 min−1, which are 9.1 times higher than those of SrFe12O19 (0.0043 min−1) and 4.2 times higher than those of g-C3N4 (0.0094 min−1). The effectively separated e play three critical roles: (i) directly activating H2O2 to generate ·OH radicals, (ii) promoting the redox cycling of Fe2+/Fe3+ ions, and (iii) reducing dissolved oxygen to form ·O2 species. Concurrently, h+ directly oxidize OTC molecules through surface-mediated reactions. Furthermore, the 7-SFO/CN composite exhibits exceptional operational stability and applicability, offering a transformative approach for scalable photocatalytic water treatment systems. This work provides an effective strategy for designing efficient and recoverable photocatalysts for environmental remediation. Full article
(This article belongs to the Special Issue Application of Nanomaterials in Catalysis for Pollution Control)
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16 pages, 1593 KiB  
Article
The Impact of Seasonally Varying Dissolved Organic Matter in Natural Aquatic Environments on the Photodegradation of Pharmaceutical Pollutants
by Yue Chen, Jingshuang Cui, Fangyuan Cheng, Jiao Qu and Ya-Nan Zhang
Toxics 2025, 13(6), 450; https://doi.org/10.3390/toxics13060450 - 29 May 2025
Viewed by 430
Abstract
Photochemical degradation is a major removal pathway for pharmaceutical pollutants in water, and dissolved organic matter (DOM) in water is an important factor affecting this process. This study investigates the differential effects of seasonally-varied dissolved organic matter (DOM) from Songhua River and Liao [...] Read more.
Photochemical degradation is a major removal pathway for pharmaceutical pollutants in water, and dissolved organic matter (DOM) in water is an important factor affecting this process. This study investigates the differential effects of seasonally-varied dissolved organic matter (DOM) from Songhua River and Liao River on the photodegradation of pharmaceutical pollutants, using levofloxacin (LFX), sulfamethoxazole (SMZ), and ibuprofen (IBP) as target compounds. The results demonstrated that summer and autumn DOM inhibited the photodegradation of LFX and SMZ through light screening and dynamic quenching effects, with inhibition rates of 35.1% and 55.5%, respectively, whereas winter DOM enhanced degradation through photo-oxidation mechanisms. DOM from Songhua River and Liao River significantly promoted the photodegradation of IBP. Quenching experiments showed differences in the contributions of photochemically reactive intermediates (PPRIs) to the photodegradation of different target pollutants, with hydroxyl radicals (•OH) dominating LFX photodegradation (48.79% contribution), excited triplet states of DOM (3DOM*) dominating SMZ photodegradation (85.20% contribution), and singlet oxygen (1O2) dominating IBP photodegradation (79.89% contribution). The photodegradation pathways were elucidated by measuring the photodegradation by-products of the target pollutants: LFX mainly underwent piperazine ring cleavage and oxidative decarboxylation, SMZ underwent isoxazole ring opening and deamination during photodegradation, and IBP underwent photodecarboxylation and oxidation reactions. Under the influence of the DOM from the Songhua River and Liao River, the generation of multiple photodegradation by-products led to an increasing trend in the acute toxicity of target pollutants to luminescent bacteria. This investigation elucidates the dual regulatory mechanisms of natural aquatic DOM on both photo-induced degradation pathways and toxicity evolution dynamics of pharmaceutical contaminants, which is of great significance for understanding the photochemical transformation behavior and risk assessment of pharmaceutical pollutants in aquatic environments. Full article
(This article belongs to the Section Emerging Contaminants)
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29 pages, 11499 KiB  
Article
Evolution Characteristics and Influencing Factors of Agricultural Drought Resilience: A New Method Based on Convolutional Neural Networks Combined with Ridge Regression
by Chenyi Jiang, Liangliang Zhang, Dong Liu, Mo Li, Xiaochen Qi, Tianxiao Li and Song Cui
Sustainability 2025, 17(11), 4808; https://doi.org/10.3390/su17114808 - 23 May 2025
Viewed by 416
Abstract
To enhance the precision of regional agricultural drought resilience evaluation, a convolutional neural network optimized with Adam with weight decay (AdamW–CNN) was constructed. Based on local agricultural economic development regulations and utilizing the Driving Force–Pressure–State–Impact–Response (DPSIR) conceptual model, sixteen indicators of agricultural drought [...] Read more.
To enhance the precision of regional agricultural drought resilience evaluation, a convolutional neural network optimized with Adam with weight decay (AdamW–CNN) was constructed. Based on local agricultural economic development regulations and utilizing the Driving Force–Pressure–State–Impact–Response (DPSIR) conceptual model, sixteen indicators of agricultural drought resilience were selected. Subsequently, data preprocessing was conducted for Qiqihar City, Heilongjiang Province, China, which encompasses an area of 42,400 km2. The drought resilience was accurately assessed based on the developed AdamW–CNN model from 2000 to 2021 in the study area. The key driving factors behind the spatiotemporal evolution of drought resilience were identified using gray relational analysis, and the future evolution trend of agricultural drought resilience was revealed through Ridge regression analysis improved by the Kepler optimization algorithm (KOA–Ridge). The results indicated that the agricultural drought resilience in Qiqihar City exhibited a trend of initial fluctuations, followed by a significant increase in the middle phase, and then stable development in the later stage. Precipitation, investment in the primary industry, grain output per unit of cultivated area, per capita cultivated land area, and the proportion of effective irrigation area were the primary driving factors in the study area. By simulating the drought resilience index of four typical regions and analyzing its evolution, it was found that the AdamW–CNN model, combined with the KOA–Ridge model, has greater advantages over the RMSProp-CNN model and the CNN model in terms of fit, stability, reliability, and evaluation accuracy. These findings provide a robust model for measuring agricultural drought resilience, offering valuable insights for regional drought prevention and management. Full article
(This article belongs to the Special Issue Climate-Driven Droughts: Pathways to Resilience in Line with SDG13)
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21 pages, 18954 KiB  
Article
Flood Risk Assessment and Driving Factors in the Songhua River Basin Based on an Improved Soil Conservation Service Curve Number Model
by Kun Liu, Pinghao Li, Yajun Qiao, Wanggu Xu and Zhi Wang
Water 2025, 17(10), 1472; https://doi.org/10.3390/w17101472 - 13 May 2025
Viewed by 641
Abstract
With the acceleration of urbanization and the increased frequency of extreme rainfall events, flooding has emerged as one of the most serious natural disaster problems, particularly affecting riparian cities. This study conducted a flooding risk assessment and an analysis of the driving factors [...] Read more.
With the acceleration of urbanization and the increased frequency of extreme rainfall events, flooding has emerged as one of the most serious natural disaster problems, particularly affecting riparian cities. This study conducted a flooding risk assessment and an analysis of the driving factors behind flood disasters in the Songhua River Basin utilizing an improved Soil Conservation Service Curve Number (SCS-CN) model. First, the model was improved by slope adjustments and effective precipitation coefficient correction, with its performance evaluated using the Nash–Sutcliffe efficiency coefficient (NSE) and the Root Mean Square Error (RMSE). Second, flood risk mapping was performed based on the improved model, and the distribution characteristics of the flooding risk were analyzed. Additionally, the Geographical Detector (GD), a spatial statistical method for detecting factor interactions, was employed to explore the influence of natural, economic, and social factors on flooding risk using factor detection and interaction detection methods. The results demonstrated that the improvements to the SCS-CN model encompassed two key aspects: (1) the optimization of the CN value through slope correction, resulting in an optimized CN value of 50.13, and (2) the introduction of a new parameter, the effective precipitation coefficient, calculated based on rainfall intensity and the static infiltration rate, with a value of 0.67. Compared to the original model (NSE = 0.71, rRMSE = 19.96), the improved model exhibited a higher prediction accuracy (NSE = 0.82, rRMSE = 15.88). The flood risk was categorized into five levels based on submersion depth: waterlogged areas, low-risk areas, medium-risk areas, high-risk areas, and extreme-risk areas. In terms of land use, the proportions of high-risk and extreme-risk areas were ranked as follows: water > wetland > cropland > grassland > shrub > forests, with man-made surfaces exacerbating flood risks. Yilan (39.41%) and Fangzheng (31.12%) faced higher flood risks, whereas the A-cheng district (6.4%) and Shuangcheng city (9.4%) had lower flood risks. Factor detection results from the GD revealed that river networks (0.404) were the most significant driver of flooding, followed by the Digital Elevation Model (DEM) (0.35) and the Normalized Difference Vegetation Index (NDVI) (0.327). The explanatory power of natural factors was found to be greater than that of economic and social factors. Interaction detection indicated that interactions between factors had a more significant impact on flooding than individual factors alone, with the highest explanatory power for flood risk observed in the interaction between annual precipitation and DEM (q = 0.762). These findings provide critical insights for understanding the spatial drivers of flood disasters and offer valuable references for disaster prevention and mitigation strategies. Full article
(This article belongs to the Section Soil and Water)
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15 pages, 6404 KiB  
Article
Inferring Water Quality in the Songhua River Basin Using Random Forest Regression Based on Satellite Imagery and Geoinformation
by Zhanqiang Yu, Hangnan Yu, Lan Li, Jiangtao Yu, Jie Yu and Xinyue Gao
Hydrology 2025, 12(3), 61; https://doi.org/10.3390/hydrology12030061 - 17 Mar 2025
Viewed by 729
Abstract
Maintaining high water quality is essential not only for human survival but also for social and ecological safety. In recent years, due to the influence of human activities and natural factors, water quality has significantly deteriorated, and effective water quality monitoring is urgently [...] Read more.
Maintaining high water quality is essential not only for human survival but also for social and ecological safety. In recent years, due to the influence of human activities and natural factors, water quality has significantly deteriorated, and effective water quality monitoring is urgently needed. Traditional water quality monitoring requires substantial financial investment, whereas the remote sensing and random forest model not only reduces operational costs but also achieves a paradigm shift from discrete sampling points to spatially continuous surveillance. The random forest model was adopted to establish a remote sensing inversion model of three water quality parameters (conductivity, total nitrogen (TN), and total phosphorus (TP)) during the growing period (May to September) from 2020 to 2022 in the Songhua River Basin (SRB), using Landsat 8 imagery and China’s national water quality monitoring section data. Model verification shows that the R2 of conductivity is 0.67, followed by that of TN at 0.52 and TP at 0.47. The results revealed that the downstream conductivity of SRB (212.72 μS/cm) was significantly higher than that upstream (161.62 μS/cm), with TN and TP concentrations exhibiting a similar increasing pattern. This study is significant for improving ecological conservation and human health in the SRB. Full article
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24 pages, 9095 KiB  
Article
Interpretation and Comprehensive Evaluation of Regional Water–Land–Energy Coupling System Carrying Capacity
by Ligao Yin, Heng Li, Dong Liu, Liangliang Zhang, Chunqing Wang, Mo Li, Muhammad Abrar Faiz, Tianxiao Li and Song Cui
Sustainability 2025, 17(4), 1669; https://doi.org/10.3390/su17041669 - 17 Feb 2025
Cited by 3 | Viewed by 689
Abstract
Previous studies on carrying capacity have primarily focused on measuring agricultural production conditions while neglecting the coupling effects among production conditions, production materials, and the external environment (the coupling effects of agricultural water, soil, energy, and the external environment). Therefore, this paper introduces [...] Read more.
Previous studies on carrying capacity have primarily focused on measuring agricultural production conditions while neglecting the coupling effects among production conditions, production materials, and the external environment (the coupling effects of agricultural water, soil, energy, and the external environment). Therefore, this paper introduces the concept of the carrying capacity of a regional agricultural water–land–energy coupling system (WLECS); develops an evaluation framework comprising 27 indicators from the perspectives of stability, collaboration, and resilience and constructs an improved random forest model based on the red-billed blue magpie optimizer (RBMO). Finally, it is applied to the evaluation of WLECS carrying capacity in China’s main grain producing area (Heilongjiang Province). The results demonstrate that the constructed RBMO-RF model exhibits stability and reasonableness with high fitting accuracy. The collaboration weight accounts for the highest proportion (0.438), indicating that the collaboration within the subsystem has the greatest impact on the carrying capacity. In terms of time scale, the WLECS carrying capacity in Heilongjiang Province shows an upward trend, characterized by three stages: a “low-level fluctuation period”, a “growth period”, and a “rapid growth period”. In terms of spatial scale, the overall spatial pattern is low in the West and high in the East, and stable in the North and South. The key driving factors are the effective irrigation index, indirect water footprint, and agricultural water-land matching degree. The research results demonstrate the carrying capacity of the WLE coupling system holds significant implications for formulating regional agricultural resource optimization allocation plans and promoting agricultural sustainable development. Full article
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18 pages, 2229 KiB  
Article
Occurrence, Transport, and Risk Assessment of Brominated Flame Retardants in Northern Wetland Multimedia
by Bo Meng, Xi-Mei Lu, Jing-Wen Jia, Fei Chen, Zhi-Zhong Zhang, Shan-Shan Jia, Ming-Song Wu, Zi-Feng Zhang and Yi-Fan Li
Processes 2025, 13(2), 423; https://doi.org/10.3390/pr13020423 - 5 Feb 2025
Cited by 1 | Viewed by 1234
Abstract
Current studies have paid extensive attention to the occurrence of brominated flame retardants (BFRs) in aquatic environments; however, there is a lack of exploration of BFRs in ice media in freshwater environments, and there are fewer studies on the distribution patterns and ecological [...] Read more.
Current studies have paid extensive attention to the occurrence of brominated flame retardants (BFRs) in aquatic environments; however, there is a lack of exploration of BFRs in ice media in freshwater environments, and there are fewer studies on the distribution patterns and ecological risks of BFRs in different media. In order to fill this gap in the current research status, this study conducted four seasonal samplings in the Songhua River wetland in Northeast China. The distribution and risk of 14 polybrominated diphenyl ethers (PBDEs) and 22 new brominated flame retardants (NBFRs) in water, ice, sediment, and soil were analyzed using liquid–liquid extraction sample pretreatment and gas chromatography–mass spectrometry instrumentation. A total of 18, 5, 8, 19, and 18 BFRs were detected in non-ice-covered water, ice-covered water, ice, sediment, and soil, respectively. NBFRs dominated contaminant concentrations in each medium. Significant correlations were found between BFRs in ice and subglacial water, suggesting that the sources of BFRs in these two media are similar and there is an exchange between them. The ice enrichment factor (IEF) revealed the water–ice distribution mechanism of BFRs, indicating that wetland ice acts as a temporary sink for 2-(Allyloxy)-1,3,5-tribromobenzene (ATE), 1,2-Dibromo-4-(1,2-dibromoethyl)cyclohexane (α-TBECH), 1,2,5,6-Tetrabromocyclooctane (TBCO), and 2-Bromoallyl 2,4,6-tribromophenyl ether (BATE). In order to achieve dynamic equilibrium, the exchange profile of BFRs between water and sediment requires the release of BFRs into water. The risk quotient (RQ) indicated that TBCO in water and ice poses a moderate risk to aquatic organisms, and its potential impact on wetland ecology cannot be ignored. Full article
(This article belongs to the Special Issue 1st SUSTENS Meeting: Advances in Sustainable Engineering Systems)
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20 pages, 10570 KiB  
Article
Solving Phosphorus Fertilization-Related Drip Irrigation Emitter Clogging by Adding Mn2+
by Tianyu Xu, Sanlin Bao, Qiuyue Yu and Yu Gao
Agronomy 2025, 15(1), 127; https://doi.org/10.3390/agronomy15010127 - 7 Jan 2025
Viewed by 918
Abstract
Drip irrigation with a fertilizer application could effectively alleviate the soil pollution caused by excessive phosphorus fertilizer. Phosphate fertilizer was dissolved in water and produced a chemical reaction with the ions in irrigation water. The new precipitates were generated, which caused more severe [...] Read more.
Drip irrigation with a fertilizer application could effectively alleviate the soil pollution caused by excessive phosphorus fertilizer. Phosphate fertilizer was dissolved in water and produced a chemical reaction with the ions in irrigation water. The new precipitates were generated, which caused more severe and complex blockage of drip irrigation emitters. Songhua River water was selected as the irrigation water. The experiment investigated the effects of three types of phosphorus fertilizers (urea phosphate, UP; potassium dihydrogen phosphate, PDP; ammonium polyphosphate, APP) and the concentrations (0.2, 0.3, and 0.4 g/L) on the blockage of drip irrigation emitter. The results showed that three types of phosphorus fertilizers intensified the degree of blockage compared with no fertilization, the order from small to large being UP < PDP < APP. The degree of blockage was directly proportional to the concentration of phosphate fertilizer. The system discharge variation ratio (Dra) under UP, PDP, and APP treatments decreased by an average of 6.2~27.7%, 13.8~33.8%, and 21.5~44.6%, respectively. The Christiansen coefficient of uniformity (CU) decreased by an average of 5.9~23.5%, 10.3~27.9%, and 19.1~38.2%. The UP was superior to PDP and APP from the perspective of drip irrigation evaluation indicators. The main reason was that UP reduced the pH value of the water source and inhibited the generation of carbonates. The APP was unable to lower the pH value and had the most serious blockage. The APP was coupled with three concentrations of Mn2+ (1, 2, and 3 mg/L) for drip irrigation, which could optimize the blockage problem and explore the efficacy of Mn2+. The 2 mg/L Mn2+ could maximize the drip irrigation efficiency of the APP. The average increase in Dra and CU was 24.57% and 18.54% macroscopically. Mn2+ could alter the lattice parameters of carbonates and had a certain impact on their size and morphological distribution on a microscopic level. The results showed that fertilization with UP at a concentration of 0.2 g/L did not significantly exacerbate clogging. The drip irrigation effect of Songhua River water combined with 0.2 g/L concentration UP was the best. Moreover, 2 mg/L of Mn2+ was proposed to alleviate the clogging characteristics of APP4. This study could provide reference for improving the efficiency of the Songhua River drip irrigation system. Full article
(This article belongs to the Special Issue Water Saving in Irrigated Agriculture: Series II)
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19 pages, 6086 KiB  
Article
Remote Sensing Estimation of CDOM for Songhua River of China: Distributions and Implications
by Pengju Feng, Kaishan Song, Zhidan Wen, Hui Tao, Xiangfei Yu and Yingxin Shang
Remote Sens. 2024, 16(23), 4608; https://doi.org/10.3390/rs16234608 - 8 Dec 2024
Cited by 2 | Viewed by 1265
Abstract
Rivers are crucial pathways for transporting organic carbon from land to ocean, playing a vital role in the global carbon cycle. Dissolved organic carbon (DOC) and chromophoric dissolved organic matter (CDOM) are major components of dissolved organic matter and have significant impacts on [...] Read more.
Rivers are crucial pathways for transporting organic carbon from land to ocean, playing a vital role in the global carbon cycle. Dissolved organic carbon (DOC) and chromophoric dissolved organic matter (CDOM) are major components of dissolved organic matter and have significant impacts on maintaining the stability of river ecosystems and driving the global carbon cycle. In this study, the in situ samples of aCDOM(355) and DOC collected along the main stream of the Songhua River were matched with Sentinel-2 imagery. Multiple linear regression and five machine learning models were used to analyze the data. Among these models, XGBoost demonstrated a superior, highly stable performance on the validation set (R2 = 0.85, RMSE = 0.71 m−1). The multiple linear regression results revealed a strong correlation between CDOM and DOC (R2 = 0.73), indicating that CDOM can be used to indirectly estimate DOC concentrations. Significant seasonal variations in the CDOM distribution in the Songhua River were observed: aCDOM(355) in spring (6.23 m−1) was higher than that in summer (5.3 m−1) and autumn (4.74 m−1). The aCDOM(355) values in major urban areas along the Songhua River were generally higher than those in non-urban areas. Using the predicted DOC values and annual flow data at the sites, the annual DOC flux in Harbin was calculated to be approximately 0.2275 Tg C/Yr. Additionally, the spatial variation in annual CDOM was influenced by both natural changes in the watershed and human activities. These findings are pivotal for a deeper understanding of the role of river systems in the global carbon cycle. Full article
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28 pages, 32302 KiB  
Article
Reconstructing Long-Term, High-Resolution Groundwater Storage Changes in the Songhua River Basin Using Supplemented GRACE and GRACE-FO Data
by Chuanqi Liu, Zhijie Zhang, Chi Xu and Wanchang Zhang
Remote Sens. 2024, 16(23), 4566; https://doi.org/10.3390/rs16234566 - 5 Dec 2024
Cited by 1 | Viewed by 1653
Abstract
The Gravity Recovery and Climate Experiment (GRACE) enables large-scale monitoring of terrestrial water storage changes, significantly contributing to hydrology and related fields. However, the coarse resolution of groundwater storage anomaly (GWSA) data limits local-scale research utilizing GRACE and GRACE-FO missions. In this study, [...] Read more.
The Gravity Recovery and Climate Experiment (GRACE) enables large-scale monitoring of terrestrial water storage changes, significantly contributing to hydrology and related fields. However, the coarse resolution of groundwater storage anomaly (GWSA) data limits local-scale research utilizing GRACE and GRACE-FO missions. In this study, we develop a regional downscaling model based on the linear regression relationship between GWSA and environmental variables, reducing the grid resolution of GWSA obtained from GRACE from approximately 25 km to 1 km. First, we estimate the missing values of monthly continuous terrestrial water storage anomaly (TWSA) for the period from 2003 to 2020 using interpolated multi-channel singular spectrum analysis (IMSSA). Next, we apply the water balance equation to separate GWSA from TWSA, which is provided jointly by the Global Land Data Assimilation System (GLDAS) and the distributed ecohydrological model ESSI-3. We then employ a partial least squares regression (PLSR) model to identify the most significant environmental variables related to GWSA. Precipitation (Prec), normalized difference vegetation index (NDVI), and actual evapotranspiration (AET), with variable importance in projection (VIP) values greater than 1.0, are recognized as effective variables for reconstructing long-term, high-resolution groundwater storage changes. Finally, we downscale and reconstruct the long-term (2003–2020), high-resolution (1 km × 1 km) monthly GWSA in the Songhua River Basin using fused and supplemented GRACE/GRACE-FO data, employing either geographically weighted regression (GWR) or random forest (RF) models. The results demonstrate superior performance of the GWR model (CC = 0.995, NSE = 0.989, RMSE = 2.505 mm) compared to the RF model in downscaling. The downscaled GWSA in the Songhua River Basin not only achieves high spatial resolution but also exhibits improved accuracy when compared to in situ groundwater observation records. This research enhances understanding of spatiotemporal variations in regional groundwater due to local agricultural and industrial water use, providing a scientific basis for regional water resource management. Full article
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25 pages, 11255 KiB  
Article
A Framework for Separating Climate and Anthropogenic Contributions to Evapotranspiration Changes in Natural to Agricultural Regions of Watersheds Based on Machine Learning
by Zixin Liang, Fengping Li, Hongyan Li, Guangxin Zhang and Peng Qi
Remote Sens. 2024, 16(23), 4408; https://doi.org/10.3390/rs16234408 - 25 Nov 2024
Viewed by 843
Abstract
Evapotranspiration is a crucial component of the water cycle and is significantly influenced by climate change and human activities. Agricultural expansion, as a major aspect of human activity, together with climate change, profoundly affects regional ET variations. This study proposes a quantification framework [...] Read more.
Evapotranspiration is a crucial component of the water cycle and is significantly influenced by climate change and human activities. Agricultural expansion, as a major aspect of human activity, together with climate change, profoundly affects regional ET variations. This study proposes a quantification framework to assess the impacts of climate change (ETm) and agricultural development (ETh) on regional ET variations based on the Random Forest algorithm. The framework was applied in a large-scale agricultural expansion area in China, specifically, the Songhua River Basin. Meteorological, topographic, and ET remote sensing data for the years of 1980 and 2015 were selected. The Random Forest model effectively simulates ET in the natural areas (i.e., forest, grassland, marshland, and saline-alkali land) in the Songhua River Basin, with R2 values of around 0.99. The quantification results showed that climate change has altered ET by −8.9 to 24.9 mm and −3.4 to 29.7 mm, respectively, in the natural areas converted to irrigated and rainfed agricultural areas. Deducting the impact of climate change on the ET variation, the development of irrigated and rainfed agriculture resulted in increases of 2.9 mm to 55.9 mm and 0.9 mm to 53.4 mm in ET, respectively, compared to natural vegetation types. Finally, the Self-Organizing Map method was employed to explore the spatial heterogeneity of ETh and ETm. In the natural–agriculture areas, ETm is primarily influenced by moisture conditions. When moisture levels are adequate, energy conditions become the predominant factor. ETh is intricately linked not only to meteorological conditions but also to the types of original vegetation. This study provides theoretical support for quantifying the effects of climate change and farmland development on ET, and the findings have important implications for water resource management, productivity enhancement, and environmental protection as climate change and agricultural expansion persist. Full article
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11 pages, 7218 KiB  
Article
Remote Sensing Inversion of Water Quality Grades Using a Stacked Generalization Approach
by Ziqi Zhao, Luhe Wan, Lei Wang and Lina Che
Sensors 2024, 24(20), 6716; https://doi.org/10.3390/s24206716 - 18 Oct 2024
Cited by 2 | Viewed by 1127
Abstract
Understanding water quality is crucial for environmental management and policy formulation. However, existing methods for assessing water quality are often unable to fully integrate with multi-source remote sensing data. This study introduces a method that employs a stacking algorithm within the Google Earth [...] Read more.
Understanding water quality is crucial for environmental management and policy formulation. However, existing methods for assessing water quality are often unable to fully integrate with multi-source remote sensing data. This study introduces a method that employs a stacking algorithm within the Google Earth Engine (GEE) for classifying water quality grades in the Songhua River Basin (SHRB). By leveraging the strengths of multiple machine learning models, the Stacked Generalization (SG) model achieved an accuracy of 91.67%, significantly enhancing classification performance compared to traditional approaches. Additionally, the analysis revealed substantial correlations between the normalized difference vegetation index (NDVI) and precipitation with water quality grades. These findings underscore the efficacy of this method for effective water quality monitoring and its implications for understanding the influence of natural factors on water pollution. Full article
(This article belongs to the Section Remote Sensors)
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17 pages, 2453 KiB  
Article
Stoichiometric and Accumulation Characteristics of Nitrogen and Phosphorus in Artificial and Natural Herbaceous Plants along Lakeshore Buffer Zone
by Qiang Liu, Yan Cheng, Chunnan Fan and Boyuan Bai
Sustainability 2024, 16(20), 8772; https://doi.org/10.3390/su16208772 - 11 Oct 2024
Viewed by 1321
Abstract
Lakeshore buffer zones serve as transitional areas between terrestrial and aquatic ecosystems, playing a crucial role in intercepting non-point source pollutants, purifying river and lake water, and maintaining ecological system dynamics. This study focuses on the vegetation of the lakeshore buffer zone in [...] Read more.
Lakeshore buffer zones serve as transitional areas between terrestrial and aquatic ecosystems, playing a crucial role in intercepting non-point source pollutants, purifying river and lake water, and maintaining ecological system dynamics. This study focuses on the vegetation of the lakeshore buffer zone in Songhua Lake, the largest artificial lake in Northeast China. The nitrogen (N) and phosphorus (P) pollutant contents and accumulation characteristics of herbaceous plants were investigated and analyzed in different regions and with different species. The study results indicate that there were no significant differences in N and P content, N: P ratio, and average accumulation among vegetation in the near-water, middle, and far lakeshores of the buffer area. The herbaceous plants with the highest N and P content and N: P ratios were Artemisia sieversiana, Sium suave, and Artemisia sieversiana, respectively. Purus frumentum planted in the middle lakeshore accumulated the highest amounts of N and P, reaching 87.97 g plant−1 and 3.86 g plant−1, respectively. The aboveground parts of plants showed significantly higher accumulation of N and P compared to the underground parts. The average enrichment coefficient for aboveground parts and underground parts for N were 4.83 and 4.35, respectively, all exceeding 1. However, their capability to enrich P was relatively weak, with only the aboveground parts of F − 3 showing some enrichment ability. Among herbaceous plants, Artemisia sieversiana and Sium suave exhibited the strongest capability for transporting N and P from underground to aboveground. Overall, harvesting aboveground biomass for the ecological removal of N and P in the study area appears feasible. Biomass is a critical factor influencing the nutrient interception capacity of vegetation, with Purus frumentum identified as an optimal restoration plant for sustainable management practices, and Artemisia sieversiana and Sium suave have the potential for rapid remediation. Full article
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