Funder template: National Science Foundation · Opportunity: PD-26-370Y · closes no deadline stated

How reviewers read this: NSF merit review asks two questions of every proposal: Intellectual Merit (the potential to advance knowledge) and Broader Impacts (the potential to benefit society). Both are weighed through five elements: potential to advance knowledge/benefit society; creativity and originality; soundness of the plan and mechanism to assess success; qualifications of the team; adequacy of resources.

Verify: Conventions per NSF PAPPG as of mid-2026. Always confirm against the current PAPPG edition and the solicitation, which may override.

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Project Summary

Page limit: 1 page (three separate text boxes in Research.gov) — verify against the NOFO.

Overview

Develop a low-cost, distributed sensing and reporting system for early detection of harmful algal blooms in Oklahoma reservoirs, paired with decision protocols that help lake managers and rural water utilities act sooner. The project will combine sensor engineering, environmental measurement, and operational decision support to improve timely response to bloom risk in water supplies.

• [DRAFT] Build and test low-cost distributed sensors for early bloom indicators in reservoirs, with emphasis on robust performance in field conditions.
• [DRAFT] Develop community reporting and alert protocols that translate sensor outputs into actionable information for lake managers and rural water utilities.
• [DRAFT] Use engineering design informed by real treatment decision workflows to improve detection-to-response speed and reduce exposure risk.

Intellectual Merit

This project advances fundamental knowledge on engineered systems for accurate detection and rapid response to pathogens and toxins in water, aligned with EER’s focus on safeguarding human health and the environment. It will also generate quantitative insight into sensor performance, field deployment, and decision thresholds for early warning of harmful algal blooms in reservoir settings.

• [DRAFT] Contribute new knowledge on low-cost environmental sensing architectures for detecting bloom precursors and harmful conditions in freshwater systems.
• [DRAFT] Improve understanding of how sensor data can be translated into reliable operational signals for treatment decision-making.
• [DRAFT] Generate evidence on distributed monitoring design principles that support resilient water-quality response in rural reservoir systems.

Broader Impacts

The project will help protect drinking-water quality and public health in rural Oklahoma by improving early warning and response to harmful algal blooms. It will deliver practical tools and protocols for lake managers and utilities, with potential transferability to other reservoir systems facing similar risks.

• [DRAFT] Provide lake managers and rural water utilities with an actionable early-warning approach tailored to their treatment decision needs.
• [DRAFT] Improve protection of downstream communities through faster detection and response to bloom events.
• [DRAFT] Produce a scalable monitoring and reporting framework that can be adapted by other reservoir operators.

Project Description

Page limit: 15 pages (solicitation may differ) — verify against the NOFO.

Introduction and Objectives

State the research questions and objectives up front, centering the EER-relevant engineering challenge of rapid detection and response to harmful algal bloom risk in reservoir water supplies. Make clear that the project is about environmental resiliency, water quality protection, and engineered monitoring systems rather than human behavior or earth systems science.

• What specific harmful algal bloom indicators will the sensors target, and why are they the right early-warning targets for reservoir management?
• What are the primary objectives for sensor development, field validation, and decision protocol design?
• How will the project improve the speed or reliability of treatment decisions for lake managers and rural water utilities?

Background and Motivation

Explain the current gap: existing monitoring approaches are too expensive, too sparse, or too slow to support early action in many rural reservoirs. Situate the work within EER’s emphasis on engineered systems that safeguard health and quality of life through accurate detection and rapid response to toxins in water.

• What limitations in current harmful algal bloom monitoring make low-cost distributed sensing necessary?
• Why are Oklahoma reservoirs an important testbed for this engineering problem?
• How does this project fill a gap in the state of the art for environmental sensing and operational response?
• Why is now the right time, given advances in sensing, data integration, and field deployment?

Research Plan

Organize the plan by objective, with methods, validation, analysis, timeline, and contingencies. Reviewers will look for a clear mechanism to assess success, so specify test conditions, performance metrics, and how field feedback will shape iterative design.

• [DRAFT] Objective 1: Design and prototype low-cost distributed sensors capable of detecting early indicators of harmful algal blooms under reservoir conditions.
• [DRAFT] Objective 2: Field-test sensor performance in Oklahoma reservoirs and compare outputs against established water-quality measurements.
• [DRAFT] Objective 3: Co-develop community reporting and alert protocols with lake managers and rural water utilities, using their actual treatment decision pathways.
• What quantitative metrics will define success: detection sensitivity, false-alarm rate, response time, durability, and cost per deployment?
• How will user-informed design be incorporated without shifting the project toward social-behavioral research?
• What contingencies exist if sensor drift, fouling, or weather conditions affect field performance?

Broader Impacts

Provide a distinctly labeled, concrete plan for who benefits, what activities will occur, and how outcomes will be evaluated. Emphasize protection of drinking water, improved operational readiness, and transferable tools for other communities.

• Who are the direct beneficiaries: rural water utilities, lake managers, and downstream residents?
• What specific products or protocols will be delivered, and how will uptake be measured?
• How will the project improve equitable access to early-warning capability in resource-constrained systems?
• What dissemination channels will be used to move the results beyond the Oklahoma testbed?

Results from Prior NSF Support

Include this section only if any PI or co-PI has had NSF support in the past five years. If so, summarize both Intellectual Merit and Broader Impacts from those awards, and connect them only as relevant to the current project.

• Has any investigator received NSF support in the last five years that must be disclosed here?
• What prior results are most relevant to the proposed sensing, environmental engineering, or deployment work?
• How will prior NSF outcomes be leveraged without duplicating past aims?

Facilities, Equipment and Other Resources

Page limit: no page limit — verify against the NOFO.

Facilities, Equipment and Other Resources

Describe the institutional and project resources that enable the work, focusing on what is available and how it supports the proposed activities. Include field access, laboratory capability, analytical tools, computing, and any partner-provided resources if applicable; do not include dollar values.

• What laboratory space, electronics/prototyping capability, and water-quality analysis resources are available?
• What field access is available for reservoir deployment and sample collection?
• What computing, data management, or telemetry resources support sensor integration and analysis?
• What institutional or community resources support work with lake managers and rural utilities?

Institutional facilities & resources (boilerplate — trim to relevance)

Maintain approved paragraphs here, one block per unit/resource. Shells
append this file to facilities documents; the researcher deletes blocks
that don’t apply. Replace the placeholders with ORS-approved language.

University of Oklahoma (general). [[FILL IN: one approved paragraph on
OU as an R1 institution, research infrastructure, computing, and libraries]]

IPPRA. [[FILL IN: approved paragraph — survey research infrastructure,
M-SISNet panel, secure data enclave (Prometheus 42), staff expertise]]

OU Supercomputing Center for Education & Research (OSCER). [[FILL IN:
approved paragraph if applicable]]

[[Additional units as needed]]

Data Management and Sharing Plan

Page limit: 2 pages — verify against the NOFO.

Data Management and Sharing Plan

Describe what data and metadata the project will generate, how they will be formatted and documented, where they will be stored, and how they will be shared. If any reporting involves operational partners or utility data, address access controls, de-identification as needed, and any IRB or human-subjects considerations if applicable.

• What data types will be produced: raw sensor streams, calibration data, field notes, water-quality reference data, and decision-protocol documentation?
• What formats, standards, and metadata will be used so others can understand and reuse the data?
• Where will the data be archived, when will it be released, and what, if any, restrictions apply for partner-sensitive information?
• If community reporting includes identifiable operational information, how will privacy, de-identification, and any required approvals be handled?