ADVANCING GROUNDWATER MODELLING USING DEEP LEARNING METHODS

2024-07-23T02:11:58Z

题名: ADVANCING GROUNDWATER MODELLING USING DEEP LEARNING METHODS 作者: 蔡和江摘要:

Advances in groundwater level modelling and time series deep learning (DL) techniques have progressed separately with limited integrations. Against the backdrop of the successful advancements in Artificial Intelligence (AI) over the past few decades, we are currently witnessing the accelerated adoption of cutting-edge intelligent technologies in the field of hydrology. However, the application of deep learning in groundwater research continues to face numerous challenges. For instance, despite its powerful nonlinear fitting capabilities, deep learning models are often criticized and questioned due to their black-box nature, which limits their ability to advance the development of science. This is especially apparent in groundwater level studies, where the intricate dynamics and unique environmental variables create a need for more tailored deep learning applications in groundwater level simulation, which prompts researchers to hold new expectations for the development of deep learning in groundwater level simulation. Within these expectations, there are two crucial issues that need to be addressed: 1) How to integrate deep learning algorithms with the specific physical processes involved in groundwater modelling? 2) How to illuminate the black box of deep learning models and enhance human understanding of groundwater dynamics? This thesis contributes to addressing these challenges by undertaking three research works that explore the application of two novel intelligent technologies in catchment-scale groundwater level simulation. These research works provide new insights and avenues for resolving the aforementioned challenges. Specifically, this thesis consists of three main topics: (1) Examining the impacts of region-averaged hydrometeorological and hydrogeological characteristics on improving the accuracy of groundwater level prediction using machine learning. (2) Embedding groundwater-related water balance mechanisms into recurrent deep learning methods for groundwater level simulation. (3) Introducing a new perspective from the decision-making procedure of deep learning models by state-of-the-art interpretable techniques to explain and understand extreme groundwater dynamics. The first topic of this thesis introduces a well-designed deep learning model for groundwater level simulation, and explore the statistical relationship between the model's performance, catchment characteristics, and groundwater dynamics, supported by an ample amount of data. This research summarizes the common characteristics of basins suitable for simulating groundwater level dynamics using deep learning, thereby deepening the understanding of the features associated with using deep learning to simulate groundwater levels. The focus of the second topic is to explore deep learning models constrained by physics laws for simulating groundwater dynamics. Formulas related to groundwater-related water balances are incorporated as additional algorithmic bases and constraints within deep learning models for groundwater level simulation. In this hybrid model, the combination of physical constraints and deep learning techniques enhances the model’s ability to comprehend the hydrogeological and hydrometeorological properties of the catchments, thereby improving the accuracy and generalization capability for predicting groundwater level. The focus of the third topic is to investigate hydrological insights related to groundwater from the perspective of deep learning models. Two state-of-the-art interpretability techniques for deep learning models are employed to analyse the underlying causes of groundwater drought events at different scales and seasons. This study integrated cutting-edge explainable DL methods into groundwater drought studies, thereby providing a new perspective for analysing the cause of drought events. It underscores the ability of explainable DL to deepen the understanding of hydrological phenomena, highlighting the imperative of synthesizing knowledge from various disciplines. While I carefully acknowledge the existing limitations of current algorithms, this study also reveals prospects for their future development. Overall, this thesis demonstrates the tremendous potential of utilizing deep learning techniques based on artificial neural networks to drive advancements in groundwater simulation. With thoughtful and innovative utilization of more intelligent technologies, it can be anticipated that significant strides in addressing the urgent groundwater challenges we are currently facing. By applying deep learning techniques, This thesis offers fresh insights and practical solutions for better understanding and managing groundwater resources, contributing to incremental advancements in the field.

Identifying the wetlands of international importance in Beibu Gulf along the East Asian - Australasian Flyway, based on multiple citizen science datasets (vol 10, 1222806, 2023)

2024-08-02T19:42:52Z

题名: Identifying the wetlands of international importance in Beibu Gulf along the East Asian - Australasian Flyway, based on multiple citizen science datasets (vol 10, 1222806, 2023) 作者: Tang, Ningxin; Ma, Yanju; Li, Sixin; Yan, Yizhu; Cheng, Cheng; Lu, Gang; Li, Fei; Lv, Liuxuan; Qin, Peilin; Nguyen, Hoai Bao; Nguyen, Quang Hao; Le, Trong Trai; Wee, Shelby Qi Wei; He, Tao; Yong, Ding Li; Choi, Chi-Yeung

Beyond carbon-centric estimates: revisiting the interplay between hydroclimatic conditions and dryland forestation

2024-08-02T19:42:41Z

题名: Beyond carbon-centric estimates: revisiting the interplay between hydroclimatic conditions and dryland forestation 作者: Wang，Dashan; Liang，Shijing; Zeng，Zhenzhong 摘要: In the global pursuit of climate mitigation, extensive tree planting initiatives have targeted the vast drylands. However, the carbon sequestration potential of forestation in these regions remains uncertain, primarily due to the oversight of crucial factors like vegetation-climate interactions. By revisiting the benefits of dryland forestation using comprehensive Earth System Modeling, we underscore the vital role of hydroclimatic factors in shaping the effectiveness of nature-based solutions, urging a reassessment of criteria for accurate carbon-centric estimates and sustainable global climate change mitigation strategies.

Effect of CeO2 Nanoparticles on the Spread of Antibiotic Resistance in a Reclaimed Water-Soil-Radish System - Shenzhen City, Guangdong Province, China, April 2023

2024-08-02T19:42:41Z

题名: Effect of CeO2 Nanoparticles on the Spread of Antibiotic Resistance in a Reclaimed Water-Soil-Radish System - Shenzhen City, Guangdong Province, China, April 2023 作者: Yu, Kaiqiang; Zhao, Bixi; Yan, Yuxi; Yang, Qing; Chen, Liming; Xia, Yu 摘要: Introduction: The use of reclaimed water (RW) for irrigation in agricultural practices raises concerns regarding the dissemination of antibiotic resistance genes (ARGs) from soils to edible crops. The effectiveness of nanoparticles (NPs) in reducing antibiotic resistance in vegetables irrigated with RW remains largely unexplored. Methods: To investigate the effects, we conducted pot experiments in which radishes were planted in soil amended with CeO2 NPs using various application techniques. The abundance of ARGs was characterized using high-throughput quantitative PCR (HT-qPCR). Concurrently, we utilized 16S ribosomal RNA (rRNA) gene sequencing to evaluate the microbial community structure of both the rhizosphere soil and the endophytic compartment within the radishes. Employing bioinformatics analysis, we probed the potential mechanisms by which NPs influence the resistome within the reclaimed water-soil-radish system.Results: Following the application of CeO2 NPs, there was a noticeable reduction in both the number and concentration of ARG genotypes in the rhizosphere soil, as well as within the radish. Concurrently, CeO2 NPs appeared to mitigate the propagation of ARGs within the reclaimed water-soil radish system. The ability of CeO2 NPs to modulate the resistome is linked to alterations in microbial community structure. Soil treatment with NPs emerged as the most effective strategy for curbing the spread of ARGs. Discussion: This finding provides a theoretical foundation for the development of nano-agricultural technologies aimed at controlling the proliferation of ARGs.

Photocatalytic wood window for the removal of indoor urea pollution

2024-08-02T19:42:29Z

题名: Photocatalytic wood window for the removal of indoor urea pollution 作者: Huang, Changzhu; Dai, Wei; Deng, Shimao; Wang, Ranhao; Tian, Yixin; ShangGuan, Yangzi; Liang, Jiaxin; Liu, Xiaolin; Lin, Jia; Chen, Hong 摘要: Indoor pollution is a major health issue. In particular, urea pollution is drawing significant attention. Herein, we designed functional wooden window with the unique ability to photocatalytically degrade indoor pollutants, specifically urea. The transparent wooden window has been prepared via one-pot hydrothermal polymerization on a chemical-treated wood in order to incorporate resorcinol-formaldehyde. A hybrid wood denoted as resorcinol-formaldehyde-wood composite capable of photocatalytically degrading urea has been obtained. Mechanism study shows that the urea is degraded on composite interface via the as-formed hydroxyl radicals (center dot OH) generated from hydrogen peroxide. Further employing a large-scale (150 mm x 200 mm) resorcinol-formaldehyde-wood window for control of toilet urea pollution, a 100% urea removal efficiency was achieved in less than one hour.

Impact of soil inorganic nitrogen on bacterial phylogeny in estuarine intertidal zones: a study of nitrogen metabolism

2024-08-02T19:42:15Z

题名: Impact of soil inorganic nitrogen on bacterial phylogeny in estuarine intertidal zones: a study of nitrogen metabolism 作者: Li, Siqi; Liu, Tianyang; Liu, Cheng; Sun, Donglei; Yan, Qin; Gao, Dengzhou; Zhang, Zongxiao 摘要: Here we investigated the potential impacts of soil inorganic nitrogen (SIN) content on the phylogenetic characteristics and ecological functions of soil bacterial communities in estuarine intertidal zones in China, aiming to comprehend the response mechanism of soil microorganisms to variations in SIN content within estuarine wetlands. Our results show that SIN in estuarine areas has a significant spatiotemporal variation on spatial and seasonal scales, in this study and is significantly associated with the phylogenetic diversity and phylogenetic turnover of soil bacterial communities. In addition, the results of the metagenomic analysis showed that the relative abundance of nitrogen-cycling functional genes in bacterial communities did not differ significantly in sampling sites and seasons, and weakly correlated with SIN content. Further, the results based on structural equation modeling (SEM) analysis showed that SIN directly and significantly regulated the phylogenetic characteristics of bacterial communities, thereby indirectly affecting the potential of bacterial nitrogen metabolism. This study emphasizes the key influence of SIN variations on the phylogenetic dissimilarity in soil bacterial communities. Moreover, although there was a weak direct relationship between the functional characteristics of the bacterial nitrogen metabolism and SIN content, the spatiotemporal variation of bacterial nitrogen metabolic potential may be indirectly regulated by SIN content by influencing the phylogenetic diversity in bacterial communities. Our study unravels the pivotal mechanisms through which SIN content influences bacterial communities, thereby offering novel insights into the microbial intricacies governing nitrogen metabolism within estuaries.

Monitoring and understanding chlorophyll-a concentration changes in lakes in northeastern China using MERIS and OLCI satellite data

2024-08-02T19:42:14Z

题名: Monitoring and understanding chlorophyll-a concentration changes in lakes in northeastern China using MERIS and OLCI satellite data 作者: Zhang, Lu; Xin, Zhuohang; Guan, Qi; Feng, Lian; Hu, Chuanmin; Zhang, Chi; Zhou, Huicheng 摘要: Lakes in the Northeast Plains-Mountain Lake Region (NPLR) of China face severe risks of eutrophication due to climate change and intensive anthropogenic pressures. As a vital indicator for eutrophication status, the dynamics of chlorophyll-a (Chl-a) concentrations in NPLR lakes were, for the first time, comprehensively investigated in this study. A support vector regression (SVR)-based model was established and applied to the MERIS (2003-2011) and OLCI (2016-2019) observations to derive a long-term Chl-a record for 33 NPLR lakes. The NPLR lakes exhibited a climatological annual mean Chl-a of 12.3 mg m(-3), ranging from 6.8 to 18.6 mg m-3 among the 33 studied lakes. During the study period, 11 lakes exhibited statistically significant increases in Chl-a concentrations (p < 0.05), and 3 lakes showed significantly decreasing trends. Spatially, lakes in lowland regions had higher Chl-a than those in mountainous regions. This study quantified the relative importance of seven explanatory factors in influencing interannual Chl-a changes for each lake. Results showed statistically significant impacts of agricultural fertilizer (10 lakes), wastewater (4 lakes), runoff (7 lakes), and wind (5 lakes) in affecting the interannual variations of Chl-a. The decreases in Chl-a were primarily attributed to the reduced livestock excrement. Compared to hydro-climatic factors, anthropogenic pressures (i.e. agriculture fertilizer, livestock excrement, and wastewater discharge) had more significant impacts on the interannual variations of Chl-a, accounting for more than 50% of 18 lakes. This study enhances our understanding of the long-term Chl-a dynamics in NPLR lakes and their responses to hydro-climatic factors and anthropogenic forcing. These findings are valuable for basin-scale water environment protection and sustainable development.

Three-in-One: Coupling Chemical Reduction, Photoreduction, and Ion-Exchange Mechanisms in Greigite/Red Soil-Based Analcime Zeolite Composites for Cr(VI) Remediation in Groundwater

2024-08-02T19:41:52Z

题名: Three-in-One: Coupling Chemical Reduction, Photoreduction, and Ion-Exchange Mechanisms in Greigite/Red Soil-Based Analcime Zeolite Composites for Cr(VI) Remediation in Groundwater 作者: Tang, Huan; Deng, Shimao; Chu, Zheting; Shangguan, Yangzi; Liang, Jiaxin; Zheng, Qian; Wang, Ranhao; Chen, Hong 摘要: Simultaneously reducing and immobilizing Cr(VI) anions in groundwater are crucial to minimize their hazardous effects. Herein, benefiting from the feasible chemical-/photo-reduction capability of greigite, together with the ion-exchange functionality of zeolites, the integrated three-in-one function in greigite/Re-ANA composites (GRAs) material has been employed for removing and immobilizing Cr(VI) in groundwater remediation. GRA-3 achieved a 99.4% Cr(VI) removal efficiency in a Cr(VI) solution with 1 mg/L. Cr(VI) residue concentration is 0.006 mg/L, complying with the control guideline in drinking water according to WHO regulations. A comprehensive mechanism study reveals that the chemical reduction and photoreduction processes are involved within greigite, which drives the process of reducing Cr(VI) to Cr(III). Subsequently, the as-reduced Cr(III) is either adsorbed on a greigite surface or ion-exchanged with zeolite microporous channels, thus getting immobilized. Furthermore, environmentally relevant Cr(VI) contaminated groundwater sampling from the chromate plant has been employed for the fixed-bed column study, which achieved the discharge standard for practical Cr(VI) polluted groundwater. This work reported a composite material matrix with great potential and significance for Cr(VI) remediation, which could be employed in permeable reactive barriers for Cr(VI)-polluted groundwater remediation in the future.

Crucial Role of Tributary Bays in the Carbon Burial of Three Gorges Reservoir

2024-08-02T19:41:40Z

题名: Crucial Role of Tributary Bays in the Carbon Burial of Three Gorges Reservoir 作者: Wang, Kai; Huang, Lei; He, Guojian; Liu, Yan; Xu, Song; He, Ding; Bai, Sen; Reible, Danny; Fang, Hongwei 摘要: Tributary bays, which are formed in river tributaries for reservoir construction with a relatively lentic environment, have been estimated to hold unique biogeochemical processes and to be involved in ecological issues (e.g., algal bloom). Nevertheless, the role of tributary bays in carbon cycling is unclear, precluding an accurate assessment of the carbon budgets of reservoirs. To fill this knowledge gap, we take the Three Gorges Reservoir (TGR) as an example and assess the carbon budget of a typical tributary bay (Xiangxi River, XXR) of TGR. With laboratory experiments and numerical models, we demonstrate that XXR may be an important carbon sink. This study exhibits that primary productivity enhancement (e.g., algal bloom) in tributary bays plays a critical role in CO2 sequestration and contributes significantly to carbon burial. Moreover, the organic carbon burial flux of tributary bays in TGR is estimated to be equivalent to (22 +/- 9) % of that in the mainstream, demonstrating the crucial role of tributary bays in the carbon burial of TGR. Considering the scientific debate on whether the reservoir is a carbon sink or source, we suggest that the overlooking of tributary bays might lead to a significant error in assessing the reservoir carbon budget.

Time to Share Air Pollution Mitigation Experience with the Belt and Road Countries

2024-08-02T19:41:39Z

题名: Time to Share Air Pollution Mitigation Experience with the Belt and Road Countries 作者: Du, Wei; Cui, Zhanpeng; Ye, Jianhuai 摘要: Global urban air quality and human health are under significant threat from air pollution. China, with its successful "Clean Air Act," offers valuable expertise in mitigating air pollution over the past decade. The Belt and Road countries in the Indochina Peninsula confront severe air pollution from sources such as biomass burning. This pollution interacts with organic volatiles emitted from the Southeast Asian tropical forests, impacting the ecosystem and climate in the region. China is actively promoting the Belt and Road South-South Cooperation Initiative on climate change. The time has come for China to share its expertise in air pollution mitigation to the Belt and Road countries, with emphases on talent development, technical service export, and intergovernmental research cooperation. This initiative not only reduces cross-border air pollution transmission but also benefits local health in the broader Indochina region.