About
Dr. Khandaker Iftekharul Islam is a Postdoctoral Scholar at the University of California, Santa Cruz,
focusing on equitable and climate-resilient water allocation frameworks as part of the interdisciplinary
COEQWAL project. Dr. Islam earned his PhD in Water Science and Management (Water Informatics)
from New Mexico State University in 2021, receiving the Dean's Award of Excellence upon graduation.
He holds an MSc in Civil and Environmental Engineering (Geo and Water Resources) from Chalmers University of
Technology, Sweden, and a BSc in Civil Engineering from Rajshahi University of Engineering and Technology (RUET), Bangladesh.
His research focused on water resources systems and security, including water quality and availability.
He explored process-based and data-driven approaches to simulate hydrologic response; investigated the
impact of climate change on hydrology; and identified critical factors that altered the relationship
between expected runoff and other geohydrological variables. A part of his research assessed groundwater
quality by predicting the areal extent of exceedance of health risk standards. His research interests
include analyzing the effects of land-use shifts and climate forcing on natural and human systems, and
identifying their vulnerabilities and resilience.
Dr. Islam previously worked as a Project Manager at the New Mexico Environment Department (SWQB),
a Research Associate at the USDA Southwest Climate Hub, and as a faculty member in the Department of
Civil Engineering at IUBAT University, Bangladesh. He also consulted for CEGIS under the Ministry of
Water Resources, Bangladesh.
He has presented his work at several major international venues and serves as a reviewer for journals published by leading publishers Springer Nature and Elsevier.
He experienced diverse cultural environments, transitioning from his upbringing in South Asia to
studying in Sweden, where he immersed himself in Scandinavian culture, and subsequently at a
Hispanic-serving University in the United States.
Education
PhD, Water Science and Management (Water Informatics)
New Mexico State University, USA
MSc, Civil and Environmental Engineering (Geo and Water Resources)
Chalmers University of Technology, Sweden
BSc in Civil Engineering
Rajshahi University of Engineering and Technology (RUET), Bangladesh
Academic & Professional Appointments
Research on equitable and climate-resilient water allocation frameworks as part of the COEQWAL project.
Water system model development, grant writing, lecture, and mentoring of intern researchers.
Produced water regulation development, NPDES permitting, and Gold King Mine project administration.
Engaged with tribal nations, agricultural stakeholders, and rural communities on watershed management.
Research, grant writing and exploration. Development of instructional materials.
Studied biophysical and socio-economic factors affecting drought vulnerability in the Southwest.
Analyzed changing snowpack–surface climate relationships in the upper Rio Grande basin.
Courses: Geography of the Natural Environment, GIS and Water Resources, Advanced Spatial Analysis
Responsibilities: Lecture, grading, proctoring, lab assistance, and GIS technical support
Progressed from Lecturer (Apr 2011 – Jan 2013) to Assistant Professor (Feb 2013 – Dec 2016).
Courses Taught: Hydrology, Irrigation & Flood Control, Open Channel Flow, Engineering
Mechanics.
Conducted alternative analyses; reviewed technical reports and provided consultation.
Selected Journal Articles
•
Islam, K.I.; Gilbert, M.J. Analytical framework for sensitivity evaluation of multi-objective water resources operations in California's Central Valley.
Journal of Hydrology: Regional Studies, Volume 67, 2026, 103809.
DOI:
10.1016/j.ejrh.2026.103809
•
Islam, K.I.; Gilbert, M.J. Identifying the Influence of Hydroclimatic Factors on
Streamflow: A Multi-Model Data-Driven Approach.
Journal of Hydrology, 2025, 32684.
DOI:
10.1016/j.jhydrol.2025.132684
•
Islam, K.I. Predicting areal extent of groundwater contamination through
geostatistical methods exploration in a data-limited rural basin.
Groundwater for Sustainable Development, Volume 23, 2023, 101043.
DOI:
10.1016/j.gsd.2023.101043
•
Islam, K.I.; Elias, E.; Carroll, K.C.; Brown, C. Exploring Random Forest Machine
Learning and Remote Sensing Data for Streamflow Prediction: An Alternative Approach to a Process-Based
Hydrologic Modeling in a Snowmelt-Driven Watershed.
Remote Sensing, 2023, 15, 3999.
DOI:
10.3390/rs15163999
•
Islam, K.I.; Elias, E.; Brown, C.; James, D.; Heimel, S. A Statistical Approach to
Using Remote Sensing Data to Discern Streamflow Variable Influence in the Snow Melt Dominated Upper Rio Grande
Basin.
Remote Sensing, 2022, 14, 6076.
DOI:
10.3390/rs14236076
•
Islam, K.I. Shifting hydroclimate sensitivity of streamflow under warming climate.
Journal of Hydrology: Regional Studies, Volume 67, 2026, 103790.
DOI:
10.1016/j.ejrh.2026.103790
Technical Reports & Case Studies
•
Nargis, S. and Islam, K. (2017). Quality in Higher Education: An Empirical
Investigation.
IUBAT Review, 1(2): 17–28.
•
Islam, K.I. A Model of Indicators and GIS Maps for the Assessment of Water Resources.
Journal of Water Resource and Protection, 2015.
DOI:
10.4236/jwarp.2015.713079
•
Islam, K., Khan, A. and Islam, T. (2015). Correlation between Atmospheric
Temperature and Soil Temperature: A Case Study for Dhaka, Bangladesh.
DOI:
10.4236/acs.2015.53014
Conference Presentations
•
Islam K.I., Gilbert J.M. Land Use vs. Climate: What Drives Irrigation Water Demand in
California's Central Valley?
Presented (H51R-VR8925) at 2025 AGU Fall Meeting (Virtual), Dec 15–19, 2025.
•
Islam, K.I. (Invited Speaker). Sensitivities and Trade-offs in Multi-objective Water Resource
Operations: A case study for California's Water Infrastructure.
California Water Data Summit 2025, Davis, CA., August 20, 2025.
•
Islam, K.I., Gilbert J.M. Sensitivity Analysis of Multi-Objective Systems in Alternative
Water Resource Operations.
Presented (H13F-1087) at 2024 AGU Fall Meeting, Washington D.C., USA, Dec 8–13, 2024.
•
Islam K.I., Gilbert J.M. Land Use Dynamics with Water Availability in the Bay-Delta Area and
Central Valley, California.
Presented at Bay-Delta Science Conference, Sacramento, CA., Sep 30 – Oct 2, 2024.
•
Islam K.I., James D, Brown C, Dubois D, Elias E. Seeing is believing: What long-term observed
hydrologic data tell us about sub watersheds of the Rio Grande.
Presented at 88th Annual Western Snow Conference, April 12–15, 2021.
•
Islam, K.I., Elias E. & Brown, C. Water Informatics approach to analyze the dynamics of
surface water runoff with climate change.
Presented at 2019 AGU Fall Meeting, San Francisco, CA.
•
Islam, K.I. & Brown, C. An approach for efficient surface prediction of water-quality
parameters.
Earth System Interactions and Implications for Geohealth Posters, 2018 AGU Fall Meeting, Washington
D.C., USA.
•
Islam, K.I. & Tsedy, W. A model of indicators for the assessment of water resource
status.
Session: 0175-1-C-Water Crisis, Elsevier – Planet under Pressure 2012, Excel, London, UK, March 2012.
Honors & Grants
★
Dean's Award of Excellence on Graduation, 14 May 2021 — New Mexico State
University
★
Rangeland Management Research Grant, Agricultural Research Services, US Department of
Agriculture – FY19
★
Arts and Science General Scholarship (three consecutive years, 2017–2019), New Mexico
State University
★
Water Research Grant, New Mexico Water Resources Research Institute, New Mexico State
Legislature – FY18
★
Travel Grant from Environment Change Institute, University of Oxford, for Planet
under Pressure 2012, London, UK
Voluntary Service & Leadership
★
Elected Vice President, Graduate Student Organization (WSM-GSO), New Mexico State University — organized academic events and student advocacy
★
Volunteer, COVID-19 Vaccination Team — supported community vaccination efforts during the pandemic
★
Participant and volunteer, University Cultural Bazaar — promoted cross-cultural awareness and international student engagement
Peer Review Service
- International Journal of Environmental Research | Springer
- Modeling Earth Systems and Environment | Springer
- Environmental Modelling & Software | Elsevier
- Journal of Hydrology | Elsevier
- Scientific Reports | Nature
- Sustainability | MDPI
Research Project Portfolio
Research highlights cover watershed hydrology, machine learning, geospatial modeling, water systems modeling, agricultural water management, and water policy. Each project links to its corresponding project pages or publications.
Project 01 · 2025 – Present
Agricultural Water Demand and Land-Use Dynamics in California's Central Valley
COEQWAL Project
Develops spatially explicit frameworks to quantify how land-use change and climate forcing interact
to reshape agricultural water demand at the sub-basin scale. Preliminary findings reveal non-additive,
spatially heterogeneous demand responses under orchard expansion combined with hot-dry climate
scenarios — directly relevant to equitable groundwater governance under California's SGMA.
Covered by ClimateBrief; presented at AGU Fall Meeting 2025.
CalSim Hydro
OpenET
SGMA
Land-Use Change
Project 02 · 2025 – 2026
Sensitivity Analysis of California Water Infrastructure: Reservoir Operations, Ecological Flows, and Deliveries
COEQWAL Project
Designed a scenario-based sensitivity analysis framework using the CalLite water system model to
evaluate trade-offs across reservoir operations, Delta ecological flows, and water deliveries.
A key methodological contribution is the unified treatment of numeric and categorical operational
levers within a single analytical design, making complex policy trade-offs accessible to
non-technical audiences. Invited talk at the 2025 California Water Data Summit, Davis, CA.
CalLite
Scenario Analysis
Decision Support
Bay-Delta
Water Policy
Project 03 · 2019 – 2025
Multi-Model Data-Driven Identification of Hydroclimatic Controls on Streamflow
Co-PI · NMSU / USDA Southwest Climate Hub · USDA ARS Funded
Developed a multi-model framework using Bayesian model selection and averaging to quantify
the relative influence of precipitation, temperature, soil moisture, and snowpack on runoff
and streamflow. Applied to the Upper Rio Grande Basin using remotely sensed hydroclimatic
time series, revealing temporal shifts in driver importance and non-stationarity in
climate-streamflow relationships under a warming climate.
Bayesian Model Selection
Remote Sensing
Nonstationarity
Upper Rio Grande
Project 04 · 2018 – 2023
Random Forest Machine Learning and Remote Sensing for Streamflow Prediction in Snowmelt-Driven Watersheds
PI · New Mexico State University · NM WRRI Funded
Applied Random Forest regression with remotely sensed hydroclimatic inputs as a computationally
efficient alternative to process-based SWAT modeling. Global sensitivity analysis identified
critical parameters governing watershed dynamics. Results demonstrated comparable predictive
accuracy to physics-based simulation at substantially lower computational cost, with direct
implications for hydrologic forecasting in data-limited and ungauged basins.
Random Forest
SWAT
Machine Learning
Global Sensitivity
Snowmelt
Project 05 · 2019 – 2023
Geostatistical Mapping of Groundwater Contamination in Data-Sparse Rural Basins
Independent Research · New Mexico State University
Applied six kriging variants — Ordinary, Universal, Empirical Bayesian, Indicator,
Co-kriging, and EBK-Regression — to map arsenic, nitrate, and fluoride contamination across
rural U.S. basins. Incorporating groundwater pH as a co-variable substantially improved
spatial prediction, identifying communities exceeding federal drinking water standards in
regions where conventional monitoring networks were too sparse to detect risk. A direct
GIScience application to environmental justice.
Kriging
Geostatistics
Groundwater Quality
Environmental Justice
ArcGIS
Project 06 · 2019 – 2021
County-Level Irrigation Water Use Mapping and Drought Vulnerability Assessment, New Mexico
Research Associate · USDA Southwest Climate Hub, Jornada Experimental Range · USDA ARS Funded
Led county-level GIS mapping of irrigation water use (groundwater and surface water) across
New Mexico, producing spatially explicit assessments of withdrawal variability under drought
conditions. Part of a broader USDA ARS project on biophysical and socio-economic factors
affecting drought vulnerability. Also applied cluster analysis to 33 years of rangeland
productivity raster time series (1985–2018) to characterize interannual spatial variability
across the southwestern U.S.
GIS Mapping
Irrigation
Drought Vulnerability
USDA ARS
Rangeland
Project 07 · 2019 – 2022
Changing Relationships Between Snowpack and Surface Climate in the Upper Rio Grande Basin
Co-PI · USDA Southwest Climate Hub / NMSU · USDA Funded
Developed a spatial-statistical modeling framework using remotely sensed hydroclimatic time
series to quantify shifts in seasonal snowpack-runoff relationships across the Upper Rio Grande
Basin. Identified how a warming climate is altering the timing and magnitude of snowmelt-driven
streamflow, with direct implications for water supply forecasting and transboundary water
management across the U.S.-Mexico border region.
Snowpack
Remote Sensing
Rio Grande
Climate Change
Spatial Statistics
Project 08 · 2024 – Present
Human Dimensions of Agricultural Water Demand Reduction: Equity Analysis under SGMA
Supervising Researcher · UC Santa Cruz – COEQWAL · Mentoring
Designed and delivered lecture modules on human dimensions of water systems, equity analysis,
and socio-hydrologic frameworks for intern researchers within COEQWAL. Supervising literature
synthesis and stakeholder mapping examining how SGMA-driven demand reduction differentially
affects farmers, farmworkers, rural communities, and ecosystems across geographic, institutional,
and socioeconomic dimensions — moving the lens from system performance to human consequence.
Human Dimensions
Water Equity
SGMA
Stakeholder Mapping
Socio-Hydrology
