Article
Environmental Sciences
Narongpon Sumdang, Srilert Chotpantarat, Kyung Hwa Cho, Nguyen Ngoc Thanh
Summary: The rapid expansion of urbanization has led to inadequate groundwater resources. To use groundwater more efficiently, a risk assessment of groundwater pollution is needed. This study used machine learning algorithms to identify areas at risk of arsenic contamination in Rayong coastal aquifers, Thailand and selected the best model based on model performance and uncertainty. The results showed that the Random Forest algorithm had the highest performance and the lowest uncertainty. The study's outcome can assist policymakers in managing groundwater quality and promoting sustainable use of groundwater resources.
ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY
(2023)
Article
Engineering, Environmental
Ruohan Wu, Joel Podgorski, Michael Berg, David A. Polya
Summary: Groundwater arsenic contamination poses severe health risks globally, with studies in Gujarat State revealing areas with high arsenic hazard concentrations. Despite estimated cases of diseases, the overall groundwater arsenic hazard in Gujarat State is relatively low.
ENVIRONMENTAL GEOCHEMISTRY AND HEALTH
(2021)
Article
Automation & Control Systems
Daniel R. Kowal
Summary: Subset selection is a valuable tool for interpretability, scientific discovery, and data compression. We propose a Bayesian approach to address the challenges in classical subset selection, and introduce a strategy that focuses on finding near-optimal subsets rather than a single best subset. We apply Bayesian decision analysis to derive the optimal linear coefficients for any subset of variables, and our approach outperforms competing methods in prediction, interval estimation, and variable selection. By analyzing a large education dataset, we gain unique insights into the factors that predict educational outcomes and identify over 200 distinct subsets of variables that offer near-optimal predictive accuracy.
JOURNAL OF MACHINE LEARNING RESEARCH
(2022)
Article
Environmental Sciences
Mohammad Zounemat-Kermani, Meysam Alizamir, Behrooz Keshtegar, Okke Batelaan, Reinhard Hinkelmann
Summary: This study evaluated the potential of kriging-based and machine learning models in predicting effluent arsenic concentration, with results showing that the kriging-logistic method performed the best and incorporating feature selection enhanced model performance by around 7.8%.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Oncology
Meiling Chu, Yue Zhou, Yulian Yin, Lan Jin, Hongfeng Chen, Tian Meng, Binjun He, Jingjing Wu, Meina Ye
Summary: The study aimed to establish a high-risk prediction model for aromatase inhibitor-associated bone loss (AIBL) in patients with hormone receptor-positive breast cancer. The XGBoost model outperformed the logistic and LASSO models in predicting the occurrence of AIBL in these patients.
FRONTIERS IN ONCOLOGY
(2023)
Article
Multidisciplinary Sciences
Andreas Hartmann, Scott Jasechko, Tom Gleeson, Yoshihide Wada, Bartolome Andreo, Juan Antonio Barbera, Heike Brielmann, Lhoussaine Bouchaou, Jean-Baptiste Charlier, W. George Darling, Maria Filippini, Jakob Garvelmann, Nico Goldscheider, Martin Kralik, Harald Kunstmann, Bernard Ladouche, Jens Lange, Giorgia Lucianetti, Jose Francisco Martin, Matias Mudarra, Damian Sanchez, Christine Stumpp, Eleni Zagana, Thorsten Wagener
Summary: Groundwater pollution poses a threat to human and ecosystem health globally, with focused recharge being the primary reason for rapid transport of pollutants into groundwater, posing a significant risk to groundwater quality.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Review
Cardiac & Cardiovascular Systems
Umberto Benedetto, Arnaldo Dimagli, Shubhra Sinha, Lucia Cocomello, Ben Gibbison, Massimo Caputo, Tom Gaunt, Matt Lyon, Chris Holmes, Gianni D. Angelini
Summary: This study conducted a systematic review and meta-analysis comparing the discrimination accuracy of machine learning (ML) models and logistic regression (LR) in predicting operative mortality following cardiac surgery. The findings suggest that ML models provide better discrimination in mortality prediction after cardiac surgery compared to LR.
JOURNAL OF THORACIC AND CARDIOVASCULAR SURGERY
(2022)
Article
Engineering, Environmental
Abdur Rashid, Muhammad Ayub, Jochen Bundschuh, Xubo Gao, Zahid Ullah, Liaqat Ali, Chengcheng Li, Ajaz Ahmad, Sardar Khan, Jorg Rinklebe, Parvaiz Ahmad
Summary: This study investigated the occurrence, distribution, sources, and health hazards of fluoride (F-) and arsenic (As) in the groundwater of Mardan, Pakistan. The concentrations of F- and As were relatively high, coexisting with higher pH, Na+, HCO3-, and SO4-2. Some groundwater samples exceeded the WHO guidelines. The PMF-model showed high accuracy, and the HHRA-model revealed a higher health risk for children.
JOURNAL OF HAZARDOUS MATERIALS
(2023)
Article
Pediatrics
Yang Gao, Dongyun Liu, Yingmeng Guo, Menghan Cao
Summary: The objective of this study is to develop a predictive model of bronchopulmonary dysplasia (BPD) for premature infants using clinical maternal and neonatal parameters. Through retrospective study on 237 premature infants, multivariate and LASSO logistic regression analysis identified risk predictors such as maternal age, delivery option, neonatal weight and age, invasive ventilation, and hemoglobin. The nomogram models based on these predictors exhibited ideal discrimination and calibration.
FRONTIERS IN PEDIATRICS
(2023)
Article
Medicine, General & Internal
Hanxu Guo, Xianjie Jia, Hao Liu
Summary: A risk prediction model for prostate cancer was established by matching data and conducting regression analysis, including relevant factors and a neural network model. Levels of Apo E and triglycerides in blood tests were identified as key factors influencing the occurrence of prostate cancer.
Article
Environmental Sciences
Alicia Fischer, Ming-Kuo Lee, Ann S. Ojeda, Stephanie R. Rogers
Summary: Arsenic contamination in groundwater is a global crisis known to cause various health issues, and this study aimed to determine the most accurate GIS interpolation method for mapping the effects of bioremediation on arsenic sequestration. The results showed that Ordinary Kriging consistently provided the most accurate predictions of arsenic concentrations across space and time, with a higher accuracy compared to the other interpolation methods.
JOURNAL OF ENVIRONMENTAL MANAGEMENT
(2021)
Article
Oncology
Zhencheng Zhu, Kunlun Luo, Bo Zhang, Gang Wang, Ke Guo, Pin Huang, Qiuhua Liu
Summary: This study identified age, size of gallstones, course of gallstones, CEA and CA199 as independent risk factors for gallbladder carcinoma. When two or more of these five independent risk factors were positive or the nomogram score was greater than 82.64, the risk of gallbladder carcinoma was high in patients with gallstones.
FRONTIERS IN ONCOLOGY
(2023)
Article
Biology
Sawsan Babiker, Yousif Eltayeb, Neveen Sayed-Ahmed, Sitalnesa Abdelhafeez, El Shazly Abdul Khalik, M. Saif AlDien, Omaima Nasir
Summary: This study used logistic regression to investigate advanced prediction risk factors for Coronary Heart Disease (CHD), aiming to reduce risk factors and increase awareness. The logit model was utilized to evaluate the probability of developing CHD based on various factors, with a focus on interpreting the fitted models. The research aimed to promote health by improving early detection of CHD and reducing mortality risks, aligning with the Saudi vision for 2030.
SAUDI JOURNAL OF BIOLOGICAL SCIENCES
(2021)
Article
Environmental Sciences
Joel Podgorski, Dahyann Araya, Michael Berg
Summary: This study examined the relationship between geogenic manganese and iron concentrations in groundwater and various environmental parameters in Southeast Asia and Bangladesh using machine learning methods. The results showed that drier climate is associated with higher manganese concentrations, while humid climate and higher levels of soil organic carbon are associated with higher iron concentrations. Additionally, areas with high iron concentrations often have high arsenic concentrations, and areas with high manganese and arsenic concentrations are frequently adjacent to each other.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Environmental Sciences
Khalifa M. Alkindi, Kaustuv Mukherjee, Manish Pandey, Aman Arora, Saeid Janizadeh, Quoc Bao Pham, Duong Tran Anh, Kourosh Ahmadi
Summary: In this study, Bayesian approaches were used to model groundwater nitrate contamination in a semiarid region in Iran. The results showed that the BART model was the most efficient, and identified potassium, rainfall, altitude, groundwater depth, and distance from residential areas as the main influencing factors of nitrate pollution.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2022)
Article
Environmental Sciences
Yiben Cheng, Hongbin Zhan, Wenbin Yang, Wei Feng, Qi Lu, Yunqi Wang, Qunou Jiang, Bin Wang, Mingchang Shi, Tao Wang, Zhiming Xin, Ruifang Hao
Summary: This study focused on the widely replanted Pinus sylvestris var. Mongolica (PSM) in Mu Us Sandy Land (MUSL) and examined the distribution of precipitation, soil moisture, sap flow, and deep soil recharge (DSR) in shallow soil layers. The results showed that the restoration process of PSM changed the precipitation distribution, with some infiltrating downward as DSR and some being stored in the shallow soil. The increase in vegetation led to increased soil water storage (SWS) capacity in the PSM plot. However, the reduction of shallow SWS and DSR in the PSM plot could be detrimental to the long-term development of PSM forest.
INTERNATIONAL SOIL AND WATER CONSERVATION RESEARCH
(2023)
Article
Materials Science, Ceramics
Jinping Tang, Peng Liu, Shengguo Xue, Yang Li, Yu Zhao, Kun Huang, Ziyuan Liu
Summary: Coal fly ash-based porous geopolymer (CFAPG) has potential as an adsorbent for heavy metal-contaminated water remediation and coal fly ash accumulation mitigation. The production parameters significantly influence the physicochemical properties, such as the adsorption capacity, of CFAPG. In this study, ten potential factors were examined, and the alkali activator modulus (MS), alkali-ash mass ratio (AA), foaming agent-ash mass ratio (FAR), and sodium dodecyl sulfate-ash mass ratio (SDSA) were identified as the most important factors affecting the Zn adsorption capacity of CFAPG. Ternary plots confirmed the interaction between these factors, with FAR being easily masked by other factors and MS being the least influenced. The results provide key parameters for the production of geopolymers as heavy metal adsorbents.
CERAMICS INTERNATIONAL
(2023)
Article
Environmental Sciences
Chun Cai, Yangfan Liu, Rui Xu, Jiaheng Zhou, Jin Zhang, Yu Chen, Lingyu Liu, Lexiang Zhang, Shuping Kang, Xianjun Xie
Summary: In this study, a potential process using a copper ferrite catalyst activated peroxymonosulfate (PMS) system was developed for efficient removal of residual refractory organic contaminants (ROCs) in water. The key reaction parameters, water quality components, main reactive oxygen species (ROS), probable degradation mechanism, rational degradation pathways, and catalyst stability were investigated. The results showed that the system achieved a 95.0% removal of Acid Orange 7 (AO7) at specific conditions, and both sulfate radical and hydroxyl radical were identified as the predominant radical species. The presence of bicarbonate was found to enhance the degradation efficiency, and the CuFe2O4 particles demonstrated good recyclability with acceptable leaching concentration of Cu. This work may provide a safe and sustainable technique for the elimination of ROCs from complex wastewater.
Article
Engineering, Geological
Qinggao Feng, Hongbin Zhan
Summary: An analytical model is established to analyze the two-region flow caused by constant-rate pumping at a partially penetrating well in a leaky confined aquifer. The effects of aquitard storage, wellbore storage, and wellbore skin are considered in the model. Semi-analytical solutions of drawdown are developed by using a linearization procedure combined with Laplace transform and separation of variables. The results show that the drawdowns in the abstraction well and non-Darcy region for the two-region flow model are larger than those for the non-Darcy flow model, and the drawdown in the Darcy region for the two-region flow model is larger than that for the Darcy flow model throughout the pumping duration. Sensitivity analysis reveals that the drawdowns in the abstraction well, non-Darcy region, and Darcy region are most sensitive to the non-Darcy constant n, as well as the well configuration and horizontal hydraulic conductivity of the Darcy region.
INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS
(2023)
Article
Plant Sciences
Zhiming Xin, Wei Feng, Hongbin Zhan, Xuying Bai, Wenbin Yang, Yiben Cheng, Xiuqin Wu
Summary: This study examines the ability of Tamarisk plants in the Ulan Buh Desert to absorb atmospheric water vapor. The results show that even with a low annual precipitation of 84 mm, deep soil recharge still occurs at a rate of 5 mm/year. The study also highlights the importance of small precipitation events and the ability of Tamarisk to absorb unsaturated atmospheric vapor.
Article
Geochemistry & Geophysics
Rui Xu, Kun Qian, Xianjun Xie, Jiangjun Chen, Weiguo Tang, Feng Tao, Yanxin Wang
Summary: Highly dispersed CoFe2O4 nanoparticles were successfully prepared by the sol-gel method and efficiently activated peroxymonosulfate to rapidly degrade fluoroquinolone antibiotics. Factors such as Cl-, HCO3-, and H2PO4- influenced the degradation efficiency of the CoFe2O4/PMS system. The study also identified the pH range for efficient degradation and the reactive radicals involved in the process.
APPLIED GEOCHEMISTRY
(2023)
Article
Engineering, Environmental
Yanxin Wang, Songhu Yuan, Jianbo Shi, Teng Ma, Xianjun Xie, Yamin Deng, Yao Du, Yiqun Gan, Zhilin Guo, Yiran Dong, Chunmiao Zheng, Guibin Jiang
Summary: Linking groundwater quality to health is essential for understanding the impact of natural or induced groundwater discharge on human health and ecological risks. This perspective discusses the critical substances in groundwater and the need for quantitative assessment and procedures to evaluate the risks. The knowledge gaps and future trends in this field are also highlighted.
ENVIRONMENTAL SCIENCE & TECHNOLOGY
(2023)
Article
Engineering, Civil
Lu Yan, Xianjun Xie, James W. Heiss, Kang Peng, Yamin Deng, Yiqun Gan, Qinghua Li, Yanpeng Zhang
Summary: In this study, the sources, preservation, and degradation of sedimentary organic matter (SOM) in the Dongzhai Harbor estuary were investigated using stable isotopes, spectral techniques, and hydrogeochemical analysis. The results showed that aquaculture, C3 mangrove forests, and marine plankton were the main sources of SOM along the estuarine gradient. Moreover, the preservation and degradation of SOM were controlled by sedimentation, hydrodynamic conditions, and geochemical reactions. These findings contribute to a better understanding of SOM dynamics in estuarine mangrove ecosystems and have implications for their protection and management.
JOURNAL OF HYDROLOGY
(2023)
Article
Water Resources
Chao Zhuang, Hongbin Zhan, Xiangdong Xu, Jinguo Wang, Zhifang Zhou, Zhi Dou
Summary: Low-permeability aquitards are important for protecting confined aquifers in coastal leaky aquifer systems from seawater and anthropogenic contamination. However, the integrity of the aquitard can be compromised by horizontal heterogeneities known as aquitard windows. This study developed an innovative analytical model to describe groundwater flow in coastal leaky aquifer systems with horizontal heterogeneities in hydraulic properties. The model can account for the effects of aquitard windows on tidal wave propagation. Analytical solutions were derived and compared to sandbox experiments, demonstrating the significant impact of high-permeability aquitard windows on tidal wave propagation and the importance of geostatistical inverse modeling for characterizing heterogeneities and locating aquitard windows.
ADVANCES IN WATER RESOURCES
(2023)
Article
Engineering, Environmental
Yi Wu, Lin Zhang, Zhixin Zhang, Jingyun Ling, Shiqi Yang, Jingjing Si, Hongbin Zhan, Wenling Chen
Summary: This article explores the spatial and temporal links between extreme precipitation events and Sunspot Number, El Nino Southern Oscillation, Arctic Oscillation, and Pacific Decadal Oscillation in the Yangtze River Economic Belt. The research findings show an upward trend in extreme precipitation indices, except for consecutive dry days and consecutive wet days. The study also reveals that the different factors have varying effects on extreme precipitation events during different time periods.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2023)
Article
Environmental Sciences
Wenguang Shi, Hongbin Zhan, Quanrong Wang, Xianjun Xie
Summary: A novel two-dimensional closed-form analytical solution for heat transport with vertical and nonvertical flow components was presented for the first time using Green's function method in this study. The new model was tested using field data and showed significant impact of nonvertical flow component on heat transport in streambed.
WATER RESOURCES RESEARCH
(2023)
Article
Environmental Sciences
Zehao Chen, Hongbin Zhan
Summary: This study investigates how transport properties affect contaminant transport in a multi-layer porous media system through high-resolution finite-element numerical models. The results show that porosity and retardation factor have similar impacts on the mass flux across layer interfaces, while increasing the transverse dispersivity enhances the mass flux between layers. The study has important implications for managing contaminant remediation in layered aquifers.
Article
Plant Sciences
Yujie Yan, Zhiming Xin, Xuying Bai, Hongbin Zhan, Jiaju Xi, Jin Xie, Yiben Cheng
Summary: Studying the dynamic changes in vegetation coverage on the Mongolian Plateau can help evaluate the ecological environmental quality in East Asia. Using Landsat remote sensing images from 2000 to 2019, this study extracted yearly NDVI data and analyzed the spatiotemporal characteristics of NDVI before and after the establishment of nature reserves. The results showed an improvement in vegetation due to increased precipitation and positive human activities, and the overall trend of NDVI is expected to be stable with a slight decrease in the future.
Article
Geosciences, Multidisciplinary
Wenguang Shi, Quanrong Wang, Hongbin Zhan, Renjie Zhou, Haitao Yan
Summary: In this study, a physically based new model and its associated analytical solutions in the Laplace domain were developed to interpret reactive transport in subsurface systems. The model performed better than previous models in interpreting experimental data. Sensitivity analysis demonstrated that the model is sensitive to mobile porosity and wellbore volume.
HYDROLOGY AND EARTH SYSTEM SCIENCES
(2023)
Article
Engineering, Environmental
Jinping Tang, Guangyi Sun, Xinbin Feng, Dongdong Liu, Yingxiang Fei, Jing Shang, Y. Zou Finfrock, Peng Liu
Summary: Porous geopolymers synthesized from aluminosilicate solid wastes are promising heavy metal adsorbents. However, the microstructural evidence for adsorbed heavy metals on geopolymers remains unclear due to the limitations of conventional characterization techniques. In this study, batch adsorption and column experiments coupled with advanced techniques were employed to reveal the Zn removal mechanisms with coal fly ash porous geopolymer (CFAPG) at a molecular scale. The results provide a systemic understanding of the Zn adsorption mechanisms on CFAPG, which is important for the application and prediction of geopolymers in heavy metal-contaminated water remediations.
CHEMICAL ENGINEERING JOURNAL
(2023)
Article
Engineering, Civil
Arfan Arshad, Ali Mirchi, Javier Vilcaez, Muhammad Umar Akbar, Kaveh Madani
Summary: High-resolution, continuous groundwater data is crucial for adaptive aquifer management. This study presents a predictive modeling framework that incorporates covariates and existing observations to estimate groundwater level changes. The framework outperforms other methods and provides reliable estimates for unmonitored sites. The study also examines groundwater level changes in different regions and highlights the importance of effective aquifer management.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Lihua Chen, Jie Deng, Wenzhe Yang, Hang Chen
Summary: A new grid-based distributed karst hydrological model (GDKHM) is developed to simulate streamflow in the flood-prone karst area of Southwest China. The results show that the GDKHM performs well in predicting floods and capturing the spatial variability of karst system.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Faruk Gurbuz, Avinash Mudireddy, Ricardo Mantilla, Shaoping Xiao
Summary: Machine learning algorithms have shown better performance in streamflow prediction compared to traditional hydrological models. In this study, researchers proposed a methodology to test and benchmark ML algorithms using artificial data generated by physically-based hydrological models. They found that deep learning algorithms can correctly identify the relationship between streamflow and rainfall in certain conditions, but fail to outperform traditional prediction methods in other scenarios.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yadong Ji, Jianyu Fu, Bingjun Liu, Zeqin Huang, Xuejin Tan
Summary: This study distinguishes the uncertainty in drought projection into scenario uncertainty, model uncertainty, and internal variability uncertainty. The results show that the estimation of total uncertainty reaches a minimum in the mid-21st century and that model uncertainty is dominant in tropical regions.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Z. R. van Leeuwen, M. J. Klaar, M. W. Smith, L. E. Brown
Summary: This study quantifies the effectiveness of leaky dams in reducing flood peak magnitude using a transfer function noise modelling approach. The results show that leaky dams have a significant but highly variable impact on flood peak magnitude, and managing expectations should consider event size and type.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Zeda Yin, Yasaman Saadati, M. Hadi Amini, Linlong Bian, Beichao Hu
Summary: Combined sewer overflows pose significant threats to public health and the environment, and various strategies have been proposed to mitigate their adverse effects. Smart control strategies have gained traction due to their cost-effectiveness but face challenges in balancing precision and computational efficiency. To address this, we propose exploring machine learning models and the inversion of neural networks for more efficient CSO prediction and optimization.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Qimou Zhang, Jiacong Huang, Jing Zhang, Rui Qian, Zhen Cui, Junfeng Gao
Summary: This study developed a N-cycling model for lowland rural rivers covered by macrophytes and investigated the N imports, exports, and response to sediment dredging. The findings showed a considerable N retention ability in the study river, with significant N imports from connected rivers and surrounding polders. Sediment dredging increased particulate nitrogen resuspension and settling rates, while decreasing ammonia nitrogen release, denitrification, and macrophyte uptake rates.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Xue Li, Yingyin Zhou, Jian Sha, Man Zhang, Zhong-Liang Wang
Summary: High-resolution climate data is crucial for predicting regional climate and water environment changes. In this study, a two-step downscaling method was developed to enhance the spatial resolution of GCM data and improve the accuracy for small basins. The method combined medium-resolution climate data with high-resolution topographic data to capture spatial and temporal details. The downscaled climate data were then used to simulate the impacts of climate change on hydrology and water quality in a small basin. The results demonstrated the effectiveness of the downscaling method for spatially differentiated simulations.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Tongqing Shen, Peng Jiang, Jiahui Zhao, Xuegao Chen, Hui Lin, Bin Yang, Changhai Tan, Ying Zhang, Xinting Fu, Zhongbo Yu
Summary: This study evaluates the long-term interannual dynamics of permafrost distribution and active layer thickness on the Tibetan Plateau, and predicts future degradation trends. The results show that permafrost area has been decreasing and active layer thickness has been increasing, with an accelerated degradation observed in recent decades. This has significant implications for local water cycle processes, water ecology, and water security.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Chi Zhang, Xu Zhang, Qiuhong Tang, Deliang Chen, Jinchuan Huang, Shaohong Wu, Yubo Liu
Summary: Precipitation over the Tibetan Plateau is influenced by systems such as the Asian monsoons, the westerlies, and local circulations. The Indian monsoon, the westerlies, and local circulations are the main systems affecting precipitation over the entire Tibetan Plateau. The East Asian summer monsoon primarily affects the eastern Tibetan Plateau. The Indian monsoon has the greatest influence on precipitation in the southern and central grid cells, while the westerlies have the greatest influence on precipitation in the northern and western grid cells. Local circulations have the strongest influence on the central and eastern grid cells.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Manuel Almeida, Antonio Rodrigues, Pedro Coelho
Summary: This study aimed to improve the accuracy of Total Phosphorus export coefficient models, which are essential for water management. Four different models were applied to 27 agroforestry watersheds in the Mediterranean region. The modeling approach showed significant improvements in predicting the Total Phosphorus diffuse loads.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yutao Wang, Haojie Yin, Ziyi Wang, Yi Li, Pingping Wang, Longfei Wang
Summary: This study investigated the distribution and transformation of dissolved organic nitrogen (DON) in riverbed sediments impacted by effluent discharge. The authors found that the spectral characteristics of dissolved organic matter (DOM) in surface water and sediment porewater could be used to predict DON variations in riverbed sediments. Random forest and extreme gradient boosting machine learning methods were employed to provide accurate predictions of DON content and properties at different depths. These findings have important implications for wastewater discharge management and river health.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Saba Mirza Alipour, Kolbjorn Engeland, Joao Leal
Summary: This study assesses the uncertainty associated with 100-year flood maps under different scenarios using Monte Carlo simulations. The findings highlight the importance of employing probabilistic approaches for accurate and secure flood maps, with the selection of probability distribution being the primary source of uncertainty in precipitation.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Janine A. de Wit, Marjolein H. J. van Huijgevoort, Jos C. van Dam, Ge A. P. H. van den Eertwegh, Dion van Deijl, Coen J. Ritsema, Ruud P. Bartholomeus
Summary: The study focuses on the hydrological consequences of controlled drainage with subirrigation (CD-SI) on groundwater level, soil moisture content, and soil water potential. The simulations show that CD-SI can improve hydrological conditions for crop growth, but the success depends on subtle differences in geohydrologic characteristics.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Constantin Seidl, Sarah Ann Wheeler, Declan Page
Summary: Water availability and quality issues will become increasingly important in the future due to climate change impacts. Managed Aquifer Recharge (MAR) is an effective water management tool, but often overlooked. This study analyzes global MAR applications and identifies the key factors for success, providing valuable insights for future design and application.
JOURNAL OF HYDROLOGY
(2024)
