Environmental Intelligence, Powered by Science
We combine peer-reviewed research, machine learning, and advanced GIS to solve complex water quality, watershed, and environmental challenges for government agencies across the Northeast.
What We Do
Our Services
Top-tier environmental science powered by machine learning and advanced analytics — backed by 305+ citations and published in the world's leading journals.
Water Quality Analysis
Comprehensive water quality monitoring, assessment, and data analytics. From nutrient loading to TMDL compliance, we deliver insights backed by peer-reviewed science.
Watershed Modeling
Advanced hydrological modeling using SWAT, SWMM, and custom ML models. Predict streamflow, sediment transport, and watershed responses to climate and land-use changes.
GIS & Spatial Analysis
Geospatial data processing, land-use mapping, and spatial statistical analysis using ArcGIS, QGIS, and Google Earth Engine for environmental decision-making.
AI & Environmental Data Science
Deep learning, ensemble models, and Bayesian optimization applied to environmental datasets. From DOC prediction to dam inflow forecasting, we build AI models that outperform traditional methods.
Remote Sensing
Satellite and aerial imagery analysis for land cover classification, vegetation health monitoring, water body delineation, and environmental change detection.
Environmental Consulting
Strategic environmental advisory services including Phase I/II assessments, stormwater management plans, environmental impact reviews, and regulatory compliance guidance.
About FLOW
Science-Driven
Environmental Solutions
Frontier Logic in Observational Water LLC (FLOW) is a Massachusetts-based environmental consulting firm founded by Dr. Jiyeong Hong, whose research spans water quality, watershed hydrology, machine learning, and environmental data science — published across 14 peer-reviewed journals including Environmental Science & Technology and JGR: Biogeosciences.
With a Ph.D. in Environmental Science from Boston University, a NASA Research Fellowship, and over a decade of experience applying AI and predictive modeling to environmental systems, Dr. Hong bridges the gap between cutting-edge research and practical consulting — delivering solutions that are both scientifically rigorous and operationally actionable.
At FLOW, every project is led and executed directly by Dr. Hong — no layers of project managers or subcontracted analysts. Clients work with the same PhD scientist who published the research, built the ML models, and collected the field data. This means faster turnaround, deeper expertise, and direct accountability on every deliverable.
FLOW specializes in turning complex environmental datasets into clear, decision-ready insights using machine learning, remote sensing, and advanced spatial analytics for government agencies, municipalities, and organizations managing water resources across the Northeast.
NASA Research Fellow
4-Year Full Fellowship
Full NASA Research Fellowship at Boston University. Led DOC dynamics research using remote sensing and ML, with results published in ES&T and JGR.
National Institute of Environmental Research
Korean EPA Equivalent
Full-time researcher at Korea's equivalent of the US EPA National Research Lab. Led TMDL program support, watershed water quality assessments, and regulatory compliance monitoring.
NAICS Codes
Core Expertise
Tools & Technologies
Education
Ph.D. in Environmental Science
Boston University
Research Foundation
Selected Publications
Our consulting is grounded in peer-reviewed research published in top environmental science journals.
Great Slave Lake as a modulator of dissolved organic carbon fluxes from the Mackenzie River watershed to the Arctic Ocean
Authorea Preprints (under review)
Capturing the Dynamics of Dissolved Organic Carbon (DOC) in Tidal Saltmarsh Estuaries Using Remote-Sensing-Informed Models
Journal of Geophysical Research: Biogeosciences
Improving Estimates of Dissolved Organic Carbon (DOC) Concentration from In Situ Fluorescence Measurements across Estuaries and Coastal Wetlands
Environmental Science & Technology
Development of Multi-Inflow Prediction Ensemble Model Based on Auto-Sklearn Using Combined Approach
Hydrology
Applicability evaluation of agricultural Best Management Practices to estimate reduction efficiency of suspended solids
CATENA
Estimation of rainfall erosivity factor in Italy and Switzerland using Bayesian optimization based machine learning models
CATENA
Comparison of Machine Learning Algorithms for Discharge Prediction of Multipurpose Dam
Water
Evaluation of Rainfall Erosivity Factor Estimation Using Machine and Deep Learning Models
Water
Prediction of Aquatic Ecosystem Health Indices through Machine Learning Models Using WGAN-Based Data Augmentation
Sustainability
Development and Evaluation of the Combined Machine Learning Models for the Prediction of Dam Inflow
Water
Track Record
Past Performance
Research projects that demonstrate our technical capabilities in water resources, environmental modeling, and data science.
Arctic DOC Flux Modeling
NASA-Funded Research · Boston University
Developed SWAT-based watershed model for the Mackenzie River basin to quantify dissolved organic carbon (DOC) fluxes from Great Slave Lake to the Arctic Ocean. Integrated remote sensing data with hydrological simulations to capture seasonal dynamics under climate change scenarios.
Tidal Saltmarsh DOC Dynamics
Boston University · Published in JGR: Biogeosciences
Built remote-sensing-informed models to capture dissolved organic carbon dynamics in tidal saltmarsh estuaries. Combined satellite imagery with in-situ measurements to develop predictive frameworks for coastal carbon budgets.
Estuarine Water Quality Monitoring
Boston University · Published in ES&T (IF 11.4)
Improved DOC concentration estimates from in-situ fluorescence measurements across estuaries and coastal wetlands. Developed correction algorithms that significantly reduced measurement uncertainty in complex water matrices.
Multi-Dam Inflow Prediction System
Korean Government · National Water Resources Agency
Designed and evaluated combined machine learning models for real-time dam inflow prediction across multipurpose reservoirs. Compared 10+ ML algorithms including ensemble methods, achieving state-of-the-art accuracy for operational flood management.
Rainfall Erosivity Factor Mapping
International Collaboration · Italy & Switzerland
Applied Bayesian optimization-based machine learning models to estimate rainfall erosivity factors across Italy and Switzerland. Created high-resolution erosivity maps for soil conservation planning and climate adaptation strategies.
Aquatic Ecosystem Health Assessment
National Institute of Environmental Research (Korea EPA)
Developed ML prediction models for aquatic ecosystem health indices using WGAN-based data augmentation. Addressed data scarcity challenges in environmental monitoring through synthetic data generation techniques.
Certifications
Commitment to Diversity
FLOW LLC is a woman-owned, minority-owned small business actively pursuing state and federal diversity certifications.
Women Business Enterprise
In ReviewCertified women-owned business in the Commonwealth of Massachusetts.
Minority Business Enterprise
In ReviewMinority-owned business certification for state and municipal contracting.
Disadvantaged Business Enterprise
In ReviewFederal DBE certification for transportation and infrastructure projects.
Small Business Purchasing Program
CertifiedMassachusetts small business certification for state procurement preferences.
Ready for Government Contracting
FLOW LLC actively pursues federal, state, and municipal environmental consulting opportunities across Massachusetts and the Northeast.
Get in Touch
Let's Work Together
Whether you need water quality analysis, watershed modeling, GIS expertise, or a trusted subcontractor for environmental projects, we'd love to hear from you.
We respond to all inquiries within 24 hours on business days
Location
Massachusetts, USA