Article
Meteorology & Atmospheric Sciences
Wanshu Nie, Sujay V. Kumar, Christa D. Peters-Lidard, Benjamin F. Zaitchik, Kristi R. Arsenault, Rajat Bindlish, Pang-Wei Liu
Summary: The study shows that assimilating optical sensor-based leaf area index estimates significantly improves the simulation of irrigation water use and associated fluxes. For heavily irrigated areas, assimilation improves the simulation of evaporative fluxes and gross primary production (GPP), leading to increased correlation and reduced bias compared to reference datasets.
JOURNAL OF ADVANCES IN MODELING EARTH SYSTEMS
(2022)
Article
Geochemistry & Geophysics
Nikolay V. Shabanov, Sergey A. Bartalev, Hideki Kobayashi, Nagai Shin, Tatyana S. Khovratovich, Vasily O. Zharko, Andrei A. Medvedev, Natalya O. Telnova
Summary: This article presents a study on the decomposition of forest leaf area index (LAI) between layers, with the development of a semiempirical model. In terms of practical aspects, time series of LAI product for Russian forests was generated and compared with literature surveys.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2023)
Article
Environmental Sciences
Manashi Paul, Adnan Rajib, Masoud Negahban-Azar, Adel Shirmohammadi, Puneet Srivastava
Summary: This study aimed to improve hydrological modeling by integrating remotely sensed data, which significantly enhanced the accuracy of estimating water and crop productivity under different irrigation schemes in semi-arid regions.
SCIENCE OF THE TOTAL ENVIRONMENT
(2021)
Article
Geosciences, Multidisciplinary
James R. Stinecipher, Philip Cameron-Smith, Le Kuai, Norbert Glatthor, Michael Hoepfner, Ian Baker, Christian Beer, Kevin Bowman, Meemong Lee, Scot M. Miller, Nicholas Parazoo, J. Elliott Campbell
Summary: Understanding the magnitude of tropical gross primary production (GPP) is crucial for carbon cycle modeling and climate projections, but it is not well constrained at regional scales. This study uses the biospheric uptake of carbonyl sulfide (OCS) to estimate regional GPP in the Amazon basin. Comparison with satellite retrievals reveals a regional GPP estimate of 2375 +/- 914 g(C) m(-2) yr(-1), consistent with previous estimates.
GEOPHYSICAL RESEARCH LETTERS
(2022)
Article
Environmental Sciences
Li-An Liu, Ren-Min Yang, Xin Zhang, Chang-Ming Zhu, Zhong-Qi Zhang
Summary: The study utilized different methods to obtain soil data for modeling, revealing a significant correlation between the invasion process and soil quality index, with invasion having a direct positive effect on soil quality, while vegetation had a negative impact on soil quality in the top layer.
Article
Agronomy
Fan Liu, Chuankuan Wang, Xingchang Wang
Summary: Litterfall collection is a non-destructive method used to estimate forest leaf area index (LAI) and validate indirect LAI products. The study found significant spatial and temporal variations in specific leaf area (SLA) for different tree species, which introduced errors in LAI estimates. Recommendations for sampling protocols were made to accurately measure forest LAI and validate the use of MODIS LAI for long-term studies.
AGRICULTURAL AND FOREST METEOROLOGY
(2021)
Article
Environmental Sciences
Binbin Huang, Yanzheng Yang, Ruonan Li, Hua Zheng, Xiaoke Wang, Xuming Wang, Yan Zhang
Summary: This study analysed the impact of land use/land cover change on water retention in Beijing between 2000 and 2015. The results showed an overall increase in water retention, with forests contributing the most to the increase. However, urbanization, cropland expansion, and deforestation led to a decline in water retention.
Article
Environmental Sciences
Azbina Rahman, Viviana Maggioni, Xinxuan Zhang, Paul Houser, Timothy Sauer, David M. Mocko
Summary: This work demonstrates that assimilating satellite observations of leaf area index and surface soil moisture into a land surface model improves the estimation of land vegetation and water variables. The assimilation of leaf area index enhances the estimation of evapotranspiration and net ecosystem exchange, while the assimilation of surface soil moisture improves the estimation of surface soil moisture content.
Article
Engineering, Civil
Hocheol Seo, Yeonjoo Kim
Summary: This study demonstrated how assimilating Leaf Area Index (LAI) into a model improved carbon and water fluxes in different ecosystems across East Asia, particularly showing significant improvement in temperate needleleaf forests.
JOURNAL OF HYDROLOGY
(2021)
Article
Environmental Sciences
Yanzhong Li, Jiacheng Zhuang, Peng Bai, Wenjun Yu, Lin Zhao, Manjie Huang, Yincong Xing
Summary: Remotely sensed precipitation estimates (RSPEs) are crucial in monitoring drought in ungauged or sparsely gauged areas. This study evaluated the performance of three long-term RSPEs (PERSIANN, CHIRPS, and MSWEP) in capturing meteorological drought variations across China. Results showed that the RSPEs generally captured the spatial patterns and trends of in situ observational precipitation data. However, there were skill divergences in capturing the drought characteristics among the different basins. The findings underscore the importance of using multiple RSPEs for drought monitoring.
Article
Engineering, Electrical & Electronic
Dong Han, Pengxin Wang, Kevin Tansey, Shuyu Zhang, Huiren Tian, Yue Zhang, Hongmei Li
Summary: The proposed SAFY-V model, integrating VTCI, can better estimate winter wheat yields, especially in arid areas, thereby improving estimation accuracy.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Article
Agriculture, Multidisciplinary
Jie Wang, Pengxin Wang, Huiren Tian, Kevin Tansey, Junming Liu, Wenting Quan
Summary: Accurate and timely crop yield estimation is crucial for crop market planning and food security. In this study, a novel deep learning model called CNN-GRU was developed to estimate winter wheat yields in the Guanzhong Plain using remotely sensed variables. The CNN-GRU model showed higher accuracy compared to the GRU model and its reliability and robustness were confirmed by cross-validation.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2023)
Article
Agriculture, Multidisciplinary
Jingqi Zhang, Huiren Tian, Pengxin Wang, Kevin Tansey, Shuyu Zhang, Hongmei Li
Summary: Crop yield estimation and prediction is a key issue in agricultural management, but challenges exist in estimating crop yields based on remotely sensed data and data-driven methods due to small datasets and limited annotated samples. This study proposed a method that combines generative adversarial networks (GANs) and convolutional neural networks (CNNs) to improve winter wheat yield estimation. The results showed that using GAN to augment the training samples improved the performance of CNN in training, validation, and testing. The method achieved accurate pixel-scale yield estimation for winter wheat in the Guanzhong Plain.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Environmental Sciences
Shanshan Feng, Fenglei Fan
Summary: The importance of ecological quality assessments is highlighted in the face of ecological changes driven by increasing human activities. This study developed an enhanced ecological evaluation index (EEEI) based on remote sensing data and methods, which can quickly obtain accurate ecological parameters. Applying the EEEI to assess the ecological quality of the Guangdong-Hong Kong-Macau Greater Bay Area (GBA) revealed significant challenges and emphasized the urgency for eco-environmental protection.
Article
Engineering, Electrical & Electronic
Mercedes M. Salvia, Nilda Sanchez, Maria Piles, Romina Ruscica, Angel Gonzalez-Zamora, Esteban Roitberg, Jose Martinez-Fernandez
Summary: The study evaluated the performance of the satellite-based soil moisture agricultural drought index (SMADI) for agricultural drought detection in Argentina, comparing it with other indices. SMADI showed the best overall performance and suitability for an early warning system. SSMA had the lowest FPR but also the lowest TPR, making it unsuitable for an alert system. Field precipitation-based indices were not suitable for agricultural drought detection in Argentina.
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2021)
Editorial Material
Environmental Sciences
Caterina Valeo, Jianxun He, Kasiapillai S. Kasiviswanathan
Article
Energy & Fuels
Bohan Shao, Caterina Valeo, Phalguni Mukhopadhyaya, Jianxun He
Summary: The study found that moisture content has a significant impact on the thermal conductivity of green roof substrates at different temperatures, with thermal conductivity increasing linearly with increased moisture content. By constructing two equal-sized test cells, comparisons were made between bare roofs, varying thicknesses of green roof substrates, and vegetation configurations, revealing a 75% reduction in interior temperature amplitude for the green roof with a substrate thickness of 150 mm compared to the bare roof.
Article
Materials Science, Multidisciplinary
Bhanu P. Koya, Sakshi Aneja, Rishi Gupta, Caterina Valeo
Summary: The research utilized Machine Learning algorithms to predict concrete mechanical properties, with Support Vector Machine outperforming other models in accuracy and reliability.
MECHANICS OF ADVANCED MATERIALS AND STRUCTURES
(2021)
Article
Green & Sustainable Science & Technology
Zhiying Xu, Caterina Valeo, Angus Chu, Yao Zhao
Summary: The research investigates the use of unprocessed oyster shells for removing metals in stormwater, with good efficiency shown for copper, cadmium, and zinc ions but not for hexavalent chromium. The experimental results suggest that exposure time and initial concentration have an impact on removal efficiency, and a mid-scale experiment under real-world conditions provided significant removal efficiencies for cadmium and copper ions.
Article
Engineering, Civil
Farzam Allafchi, Caterina Valeo, Jianxun He, Norman Neumann
Summary: This paper introduces a three-dimensional CFD-based hydro-environmental model that successfully simulates the fate and transport of bacteria in water bodies. Through simulations of a stormwater pond in Calgary, Canada, the study found that the middle of the pond near the surface had the lowest levels of bacteria, making it the optimal location for water withdrawal and reuse. Additionally, planting a tree barrier on the north bank of the pond's west wing was shown to significantly reduce contamination risk and mitigate bacteria transport.
JOURNAL OF HYDRO-ENVIRONMENT RESEARCH
(2021)
Article
Green & Sustainable Science & Technology
Fatemeh Talebzadeh, Caterina Valeo, Rishi Gupta, C. Peter Constabel
Summary: Carwash wastewater can be a significant source of environmental pollution due to the presence of diverse and high concentrations of contaminants. The use of nature-based LID technologies may offer an eco-friendly and cost-effective treatment process for this toxic wastewater. Different countries have varying flow rates and contaminant concentrations in carwash wastewater, while the effectiveness of vegetated and unvegetated LIDs in removing heavy metals shows mixed results in the literature.
Article
Plant Sciences
R. Nasrollahpour, A. Skorobogatov, J. He, C. Valeo, A. Chu, B. van Duin
Summary: This paper investigates the influence of design parameters on evapotranspiration in bioretention systems. The results show that design and climatic variables have significant effects on evapotranspiration, with the surface layer being more affected. Sandy media with low organic matter and woody vegetation perform better in promoting evapotranspiration. The study also identifies the time-dependent nature of design variables' effects and the impact of media-vegetation interactions on evapotranspiration.
URBAN FORESTRY & URBAN GREENING
(2022)
Article
Engineering, Civil
Y. Zhang, A. Skorobogatov, J. He, C. Valeo, A. Chu, B. van Duin, L. van Duin
Summary: Bioretention systems have been shown to effectively reduce stormwater quantity and improve stormwater quality. However, they can also leach nutrients during initial operation, which needs to be mitigated for optimal benefits. This study examines the efficiency of six amendments in reducing phosphorus leaching and found that all amendments had varying degrees of efficacy, with water treatment residual performing the best.
JOURNAL OF HYDROLOGY
(2023)
Article
Environmental Sciences
Junlin Wang, Phalguni Mukhopadhyaya, Caterina Valeo
Summary: Green roofs are an innovative stormwater management technology that have multiple environmental benefits. Citywide implementation is crucial, especially with jurisdictional encouragement and management programs. The City of Vancouver is interested in developing a rainwater management strategy that supports wide-scale implementation of green roofs on private property. The research looked into the strategies of Toronto and Portland for insight into the best approaches for Vancouver.
Review
Chemistry, Analytical
Farhad Jalilian, Caterina Valeo, Angus Chu, Rustom Bhiladvala
Summary: Bioretention cells, or rain gardens, can reduce contaminants in polluted stormwater through phytoremediation and bioremediation. The presence of bacterial communities in the vegetated soil structure plays a significant role in the bioremediative process. However, the lack of effective and inexpensive monitoring devices for field assessment of this process is a major hurdle.
Article
Engineering, Marine
Hauke Blanken, Caterina Valeo, Charles G. Hannah, Usman T. Khan
Summary: Accurate prediction of material trajectories on the ocean surface is crucial for risk assessment and emergency responses. This article introduces a fuzzy number-based algorithm for propagating uncertainty in a time- and space-varying velocity field. The algorithm's performance was evaluated using idealized velocity fields and optimized parameter values were identified for uncertainty representation and computational cost.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Water Resources
Zhonghao Zhang, Caterina Valeo
Summary: This paper explores the scalability of PCSWMM's Low Impact Development (LID) modeling tools within the urban stormwater computer model. The study evaluates the model's performance under different spatial and temporal scales, and for different types of inputs. The results show that the model's surface layer plays a dominant role in simulating large storm events, while parameters related to the storage layer have a larger impact on continuous rainfall simulations. The study suggests that the model could be improved to better represent soil layer dynamics and vegetation cover for smaller storms, continuous time series, and larger spatial scales.
FRONTIERS IN WATER
(2022)
Review
Green & Sustainable Science & Technology
Aditya Rebally, Caterina Valeo, Jianxun He, Saeid Saidi
Summary: The transportation sector is crucial for a region's economic and social well-being, but it is directly and indirectly influenced by flooding. This impact can lead to transportation delays, infrastructure damage, and economic repercussions. The majority of studies focus on the short- and medium-term resilience of transportation networks, with less emphasis on the indirect effects of flooding and long-term temporal scales.
FRONTIERS IN SUSTAINABLE CITIES
(2021)
Proceedings Paper
Green & Sustainable Science & Technology
Fatemeh Talebzadeh, Caterina Valeo, Rishi Gupta
Summary: With increasing industrial growth, understanding factory production processes, resulting products, and pollution caused by fabrication processes is crucial. This research focuses on Cd pollution associated with motor vehicle brake discs, proposing three interventions to prevent Cd pollution, including alternative materials, bacteria coating, and permeable roads. The advantages and disadvantages of each proposition are discussed in detail.
5TH INTERNATIONAL CONFERENCE ON ENVIRONMENTAL ENGINEERING AND SUSTAINABLE DEVELOPMENT (CEESD 2020)
(2021)
Article
Environmental Sciences
Robert Thomas, Usman T. Khan, Caterina Valeo, Fatima Talebzadeh
Summary: This study investigated the potential of fuzzy modeling in reducing uncertainty and quantifying pollutant concentration changes, but did not show any advantages over ordinary kriging and inverse distance weighting methods under sparse data conditions.
