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Effects of Increasing Rainfall Depths and Impervious Areas on the Hydrologic Responses

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Open Journal of Modern Hydrology 2023年第2期13卷 114-128页

作者： Mosammat Mustari Khanaum md.saidul borhan Department of Civil Construction and Environmental Engineering North Dakota State University Fargo USA Texas Department of Transportation Maintenance Division Austin USA

Hydrologic modeling is a popular tool for estimating the hydrological response of a watershed. However, modeling processes are becoming more complex due to land-use changes such as urbanization, industrialization, and the expansion of agricultural activities. The primary goal of the research was to use the HEC-HMS model to evaluate the impact of impervious soil layers and the increase in rainfall-runoff processes on hydrologic processes. For these purposes, the Watershed Modelling System (WMS) and Hydrologic Engineering Center’s-Hydrologic Modeling System (HEC-HMS) models were used in this study to simulate the rainfall-runoff process. To compute runoff rate, runoff volume, base flow, and flow routing methods SCS curve number, SCS unit hydrograph, recession, and loss routing methods were selected for the research, respectively. To reduce the processing time and computational complexity, a small section of the Pipestem Creek Watershed was selected to understand the methods and concepts associated with the hydrologic simulation model building. A DEM along with other required data such as land use land cover data, soil type data, and meteorological data was utilized to delineate the watershed in WMS. The output of WMS was utilized to run the HEC-HMS model for five different scenario analyses. All the relevant data were plugged in to the model to get the desired map. Subsequently, outlets at appropriate locations were selected for the sub-basin delineation for further analysis. Finally, the model was parametrized to get successful simulation results. Overall, peak discharges and runoff volumes were increased with increasing storm depths and impervious areas. Peak discharges were increased to 36% and 51% when rainfall depths were increased by 10% and 20% from the initial rainfall depth, respectively. Runoff volumes were also increased to 35% and 49% for the same scenarios, respectively. Peak discharges were increased to 12% and 78% with a 10% and 20%, respectively, incre

关键词： Peak Discharge Runoff Impervious Area HEC-HMS WMS

Sensors and Methods for Measuring Greenhouse Gas Emissions from Different Components of Livestock Production Facilities

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Journal of Geoscience and Environment Protection 2022年第12期10卷 242-272页

作者： md.saidul borhan Mosammat Mustari Khanaum Texas Department of Transportation Maintenance Division Austin TX USA Civil Construction and Environmental Engineering Department North Dakota State University Fargo ND USA

Greenhouse gas monitoring on a broader scale is necessary to ensure that a cap-and-trade system is effective, reduces measurement uncertainty, and detects fraudulent or illegal activities. The recent strict air quality regulation in livestock production facilities has accelerated the need for accurate on-farm determination of greenhouse gas (GHG) emission rates (ERs) from livestock operations in the United States under a wide range of production, management, and climate conditions. The estimation of GHG emissions from different ground-level sources or at a property line is a very complicated process, and such measurements require multidirectional expertise including engineering, micrometeorology, agronomy, applied physics, and chemistry. Accurate measurement of gaseous concentration from an emitting source is a prerequisite and of paramount importance for estimating emissions rates (ERs) using any micro-meteorological and sampling device-based method. This paper provides an overview of the state-of-the-art sensors and analyzers used to measure GHG concentrations. Sensor and analyzer selection and their performance in the laboratory and field were discussed. In addition, protocols for data quality control (QC) and quality assurance (QA) when deploying sensors in the area for long-term use were also discussed. In addition, the preparation of measurement systems, coupling of air samplers with sensing systems for measuring gaseous concentrations, and uncertainties inherent to such measurement methods as a whole to estimate ERs were discussed in this paper.

关键词： Flux-Chamber Spectroscopic Techniques Separation Techniques Uncertainty Open-Path FTIR CRDS TDLAS

Evaluating Model Effectiveness for Soil Infiltration Attribute: Comparison of Green-Ampt, Horton and Modified Green-Ampt Infiltration Models

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Journal of Geoscience and Environment Protection 2023年第2期11卷 57-68页

作者： Mosammat Mustari Khanaum md. saidul borhan Civil Construction and Environmental Engineering North Dakota State University Fargo ND USA Texas Department of Transportation Maintenance Division TxDOT Austin TX USA

Soil infiltration is a very important concept in hydrology as well as irrigation, which plays a vital role in estimating surface runoff and groundwater recharge. It is a complicated process that varies with numerous factors. Accurate estimation of soil infiltration is required for future irrigation, and many other purposes. To estimate the infiltration process, there are numerous models. The majority of them have some presumptions, a unique calculation method, and some limitations. The purpose of the paper was to assess the model’s performance for a similar hypothetical scenario involving soil infiltration. It compared the infiltration rate, runoff rate, and incremental infiltration versus time for three different infiltration models: the Green-Ampt model (GA), the Horton model and the Modified Green-Ampt (MGA) model. A spreadsheet was used to calculate the Horton model, and HYDROL-INF (V 5.03) was used to simulate the other two models. Among those three models, the MGA model outperformed those three models, while the GA model produced greater infiltration rate than rainfall, which was insensible. The study showed that the MGA model, which provides useful infiltration predictions, outperformed the other two infiltration models. Since the Horton model does not consider ponding conditions, it is only applicable when the effective rainfall intensity exceeds the final infiltration capacity. Moreover, the GA model’s initial infiltration rate is irrational because it disregards the intensity of the rainfall. The results of this study will assist in selecting the most accurate method for estimating soil infiltration for agricultural purposes.

关键词： Infiltration Groundwater Recharge Green-Ampt Horton Model Modified Green-Ampt

Unveiling the Predictive Capabilities of Machine Learning in Air Quality Data Analysis: A Comparative Evaluation of Different Regression Models

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Open Journal of Air Pollution 2023年第4期12卷 142-159页

作者： Mosammat Mustari Khanaum md.saidul borhan Farzana Ferdoush Mohammed Ali Nause Russel Mustafa Murshed Department of Civil Construction and Environmental Engineering North Dakota State University Fargo USA Texas Department of Transportation Maintenance Division Austin USA Department of Arts and Sciences Ahsanullah University of Science and Technology Dhaka Bangladesh School of Social & Environmental Sustainability University of Glasgow Glasgow UK Department of Economics Andrew Young School of Policy Studies Georgia State University Atlanta USA

Air quality is a critical concern for public health and environmental regulation. The Air Quality Index (AQI), a widely adopted index by the US Environmental Protection Agency (EPA), serves as a crucial metric for reporting site-specific air pollution levels. Accurately predicting air quality, as measured by the AQI, is essential for effective air pollution management. In this study, we aim to identify the most reliable regression model among linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), logistic regression, and K-nearest neighbors (KNN). We conducted four different regression analyses using a machine learning approach to determine the model with the best performance. By employing the confusion matrix and error percentages, we selected the best-performing model, which yielded prediction error rates of 22%, 23%, 20%, and 27%, respectively, for LDA, QDA, logistic regression, and KNN models. The logistic regression model outperformed the other three statistical models in predicting AQI. Understanding these models' performance can help address an existing gap in air quality research and contribute to the integration of regression techniques in AQI studies, ultimately benefiting stakeholders like environmental regulators, healthcare professionals, urban planners, and researchers.

关键词： Regression Analysis Air Quality Index Linear Discriminant Analysis Quadratic Discriminant Analysis Logistic Regression K-Nearest Neighbors Machine Learning Big Data Analysis

Traffic Speed Interface Development in Route Choice Decision

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Journal of Civil Engineering and Architecture 2023年第9期17卷 473-478页

作者： md.saidul Azam Chowdhury Department of Civil and Environmental Engineering Shahjalal University of Science and TechnologySylhet 3114Bangladesh

In this paper,a method has been developed based on historic traffic data(speed),which helps the commuters to choose routes by their intelligence knowing the traffic conditions in Google *** has been collected on basis of video analysis from several segments between Tuker Bazar and Bandar Bazar *** each of the video footage,a reference length has been recorded with measurement tape for use in video analysis.A software has been also developed based on Java language to get the traffic information from historic data,which shows the output as images consisting of traffic speed details on the available routes by giving day and time limit as *** developed models provide useful insights and helpful for the policy makers that can lead to the reduction of traffic congestion and increase the scope of intelligence of the road users,at least for the underdeveloped or developing country where navigation is still unavailable.

关键词： Traffic speed route choice Google maps

In Vitro Propagation of Three Strawberry Cultivars through Runner Tips Culture

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American Journal of Plant Sciences 2023年第11期14卷 1296-1304页

作者： Sussmita Karmaker md. Mukhtar Hossain md. Aminul Hoque md. Abdul Kaium md. Al Amin md. saidul Islam Department of Agronomy and Agricultural Extension Faculty of Agriculture Rajshahi University Rajshahi Bangladesh Department of Crop Science and Technology Faculty of Agriculture Rajshahi University Rajshahi Bangladesh

At the Genetics and Plant Breeding Laboratory of the Department of Agronomy and Agricultural Extension, University of Rajshahi, Bangladesh, strawberry in vitro propagation was done. Five Benzylaminopurine (BAP) concentrations were utilized for shoot induction—0.0 mg/L (Control), 0.5 mg/L, 1.0 mg/L, 1.5 mg/L, and 2.0 mg/L and five Indole Buteric Acid (IBA) concentrations—0.0 mg/L(Control), 0.5 mg/L, 1.0 mg/L, 1.5 mg/L, and 2.0 mg/l—were used for the induction of the root. The highest mean amount of shoots (eight) and length of the shoot (3.40 cm) were observed at a concentration of BAP of 0.5 mg/L. Festival also had the highest mean amount of leaves (6) when we used the identical concentration, while RABI-3 and Camarosa did the least well. The IBA of 0.5 mg/L concentration of rooting performed the best across all metrics tested among the five concentrations. The longest (3.3 cm) roots and most roots (7) were likewise obtained from this concentration in Festival. However, RABI-3 and Camarosa performed worse than Festival in the same concentration. Half-strength MS media without IBA concentration showed no response regarding root induction for each of the three cultivars.

关键词： Strawberry Proliferation Propagation Shoot Induction Root Induction

In Vitro Propagation of Three Strawberry Cultivars through Runner Tips Culture

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A Detailed Study on IoT Platform for ECG Monitoring Using Transfer Learning

American Journal of Plant Sciences（美国植物学期刊） 2023年第11期

作者： Sussmita Karmaker md.Mukhtar Hossain md.Aminul Hoque md.Abdul Kaium md.Al Amin md.saidul Islam

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Journal on Internet of Things 2022年第3期4卷 127-140页

作者： md.saidul Islam School of Computer and Software Nanjing University of Information Science and TechnologyNanjing210044JiangsuChina

Internet of Things(IoT)technologies used in health have the potential to address systemic difficulties by offering tools for cost reduction while improving diagnostic and treatment *** works on this subject focus on clarifying the constructs and interfaces between various components of an IoT platform,such as knowledge generation via smart sensors collecting biosignals from the human body and processing them via data mining and,in recent times,deep neural networks offered to host on cloud computing *** approaches are intended to assist healthcare professionals in their daily *** this comparative research,we discuss the construction of an IoT network for real-time management and monitoring of a network of biosensors and gateways and the utilization of a cloud-based deep neural network architecture with such categorization of ECG data into various cardiovascular *** aim of this paper is to provide a quicker transmission of data at a cheaper rate.

关键词： ECG internet of things healthcare AI deep learning neural network smart health sensors