Rapid Distributed Freshwater Lake Sampling Pilot and Dissolved Organic Matter (DOM) Observations — Miami Whitewater Lake, Ohio

Abstract This technical note presents a rapid distributed environmental sampling pilot conducted at Miami Whitewater Lake, Ohio. Multiple water samples were collected from geographically distributed locations using a portable rowboat-based workflow and immediately evaluated using the EcoExposure™ environmental assessment platform.

The pilot evaluated operational feasibility of distributed freshwater lake monitoring, documented environmental heterogeneity across short distances, and investigated the influence of elevated dissolved organic matter (DOM) on optical assay performance. Dilution and saline-conditioning strategies substantially improved optical clarity and endpoint visualization in DOM-rich samples.

This work complements the previous rapid distributed shoreline pilot performed along the Seine River in central Paris, France, and demonstrates the adaptability of low-infrastructure, decentralized environmental intelligence workflows across both urban river and natural freshwater lake environments.

(Rapid Distributed Seine River Microplastic / Nanoplastic Sampling Pilot — Paris, France https://doi.org/10.5281/zenodo.20361744)

This paper is also available at: https://doi.org/10.5281/zenodo.20454247

Figure 1. Rapid distributed freshwater lake sampling pilot at Miami Whitewater Lake, Ohio. Samples were collected and tested directly from a rowboat across multiple regions (shoreline, open water, inlet, and basin). The map shows representative sampling points with visible heterogeneity; the inset photo shows a typical field-collected DOM-rich sample. Distributed collections revealed observable variation in organic burden within short distances.

Introduction Environmental monitoring programs increasingly seek scalable methods capable of generating geographically distributed observations across diverse aquatic environments. While many efforts focus on rivers, estuaries, and coastal systems, freshwater lakes and ponds represent important but often challenging monitoring targets.

Compared with flowing river systems and marine environments, lakes and ponds frequently exhibit elevated dissolved organic matter (DOM), algal products, humic substances, fulvic compounds, suspended colloids, and other naturally occurring materials that contribute coloration, turbidity, and optical interference.

This technical note describes a rapid distributed sampling pilot conducted at Miami Whitewater Lake, Ohio, and evaluates operational feasibility, environmental heterogeneity, and preliminary matrix-conditioning strategies for DOM-rich freshwater systems.

Lake Characteristics The broader Whitewater River watershed, which includes Miami Whitewater Lake, is rated as one of the higher-quality river systems in Ohio. Many segments support excellent biological communities and hold “Exceptional Warmwater Habitat” (EWH) or Warmwater Habitat (WWH) status.

However, lakes and impoundments in southwest Ohio typically differ from flowing rivers. They generally exhibit higher levels of dissolved organic matter (DOM) — consistent with the visible green-yellow coloration and greater optical interference observed in the undiluted Miami Whitewater Lake samples. The region’s limestone geology also contributes to moderate to high water hardness (typically ranging from 130–250+ ppm as CaCO₃). Additional common features include seasonal increases in algae and turbidity during warmer months, along with variable iron and nutrient inputs from runoff and surrounding vegetation.

Objectives The objectives of this pilot were to:

•        Demonstrate rapid distributed environmental sampling within a freshwater lake environment.

•        Evaluate environmental heterogeneity across multiple lake locations.

•        Demonstrate the ability to perform EcoExposure testing in the field on a boat

•        Assess the influence of dissolved organic matter on optical assay performance.

•        Explore matrix-conditioning approaches for improving optical clarity.

•        Expand distributed environmental intelligence workflows beyond urban river environments.

Methods

Environmental water samples were collected from multiple locations throughout Miami Whitewater Lake using a portable rowboat-based workflow. Sampling locations included shoreline-accessible regions, open-water areas, and transitional zones selected to capture potential environmental variability.

Representative sampling regions included:  Samples were collected directly into field containers and evaluated using the EcoExposure™ optical interaction workflow. Selected samples underwent dilution studies to evaluate effects on optical clarity and assay visualization.

 Figure 1. Rapid distributed freshwater lake sampling pilot at Miami Whitewater Lake, Ohio. Samples were collected and tested directly from a rowboat across multiple regions (shoreline, open water, inlet, and basin). The map shows representative sampling points with visible heterogeneity; the inset photo shows a typical field-collected DOM-rich sample. Distributed collections revealed observable variation in organic burden within short distances.

Figure 2. Representative Open-Water Conditions at Miami Whitewater Lake, Ohio Representative field conditions observed during environmental sampling operations at Miami Whitewater Lake, Ohio. Sampling was conducted from a small watercraft under real-world outdoor conditions, demonstrating the feasibility of distributed environmental monitoring within a freshwater lake environment. The lake exhibited characteristics consistent with a dissolved organic matter (DOM)-rich system, providing a useful testbed for evaluating environmental monitoring workflows in challenging freshwater matrices.

Results Distributed sampling demonstrated operational feasibility for environmental monitoring within a freshwater lake environment using minimal infrastructure and a single-person workflow.

Observable differences were noted among samples collected from different lake regions despite their relatively close geographic proximity. Variations in coloration, transparency, and optical characteristics suggested heterogeneous distribution of dissolved organic matter and other environmental constituents.

Undiluted lake samples generally exhibited greater optical interference than previously observed in flowing river environments. Several samples displayed green-yellow coloration consistent with elevated dissolved organic matter.

 Figure 1. Rapid distributed freshwater lake sampling pilot at Miami Whitewater Lake, Ohio. Samples were collected and tested directly from a rowboat across multiple regions (shoreline, open water, inlet, and basin). The map shows representative sampling points with visible heterogeneity; the inset photo shows a typical field-collected DOM-rich sample. Distributed collections revealed observable variation in organic burden within short distances.

Figure 2. Representative Open-Water Conditions at Miami Whitewater Lake, Ohio

Representative field conditions observed during environmental sampling operations at Miami Whitewater Lake, Ohio. Sampling was conducted from a small watercraft under real-world outdoor conditions, demonstrating the feasibility of distributed environmental monitoring within a freshwater lake environment. The lake exhibited characteristics consistent with a dissolved organic matter (DOM)-rich system, providing a useful testbed for evaluating environmental monitoring workflows in challenging freshwater matrices.

Figure 3. Representative Lake Water Sample Collected During Distributed Monitoring Operations

Environmental water sample collected from Miami Whitewater Lake during distributed sampling activities. Visible coloration and optical characteristics varied among sampling locations, supporting the concept that environmental conditions may differ across relatively short geographic distances within a single freshwater system. These observations highlight the value of distributed monitoring approaches for environmental intelligence and geospatial water-quality assessment.  The EcoExposure test was performed on the boat.  Simple steps of collecting water sample, adding the natural plant-based biodegradable reagent, and taking photos after the reaction is complete.  Because the reagent is plant-based and biodegradable, the water sample can be poured back into the lake after testing making it a convenient field test.  In typical lab-based methods 50+ or hundreds of liters of water may need to be transported back to the lab.

Matrix Conditioning Observations

Progressive dilution with filtered water improved optical clarity and visibility of the patterned reference background. Saline-conditioning approaches produced additional improvements in several DOM-rich samples, with enhanced optical organization and improved reference-pattern visibility observed relative to undiluted conditions. Salt-water dilution often performed particularly well, suggesting ionic-strength-mediated matrix conditioning benefits beyond simple volume reduction.

Discussion Freshwater lakes and ponds may represent some of the most challenging environmental matrices for portable optical monitoring approaches. The observations from Miami Whitewater Lake support the concept that environmental heterogeneity may occur across relatively short geographic distances and that distributed sampling may provide greater environmental insight than reliance on a single collection point.

The findings also demonstrate that simple field-compatible matrix-conditioning approaches  can substantially improve optical performance in DOM-rich samples without requiring complex laboratory preparation workflows.

Relationship to Previous Seine River Pilot This freshwater lake pilot complements the previous rapid distributed shoreline sampling study conducted along the Seine River in central Paris, France.

Table 1. Comparison of Distributed Sampling Approaches

Aspect	Seine River Urban Pilot (Paris)	Miami Whitewater Lake Pilot (Ohio)
Environment	Dense urban river	Natural freshwater lake (DOM-rich)
Sampling Platform	Shoreline (no boat)	Rowboat (open water + shoreline)
Primary Challenge	Urban access & logistics	Elevated DOM & matrix interference
Key Innovation Tested	Rapid multi-microsite collection	Matrix-conditioning (dilution + saline)
Time for Multiple Sites	~30 minutes	Single session with on-boat testing
Main Outcome	Feasibility in urban setting	Robustness in high-DOM natural waters

Potential ApplicationsDistributed freshwater monitoring frameworks may support:

•        Environmental intelligence networks (e.g. government agencies or researchers, etc.)

•        Citizen science initiatives

•        NGO monitoring programs

•        Municipal water assessments

•        Recreational water monitoring

•        Temporal environmental trend analysis

o   including monitoring for effects of remediation or other treatments

•        Geospatial environmental mapping

Future Work

Future studies will include expanded lake and reservoir sampling, quantitative image analysis, systematic comparison of lakes, rivers, estuaries, and marine environments, seasonal monitoring campaigns, development of geospatial environmental intelligence maps, and further evaluation of matrix-normalization strategies across diverse environmental conditions.

ConclusionsRapid distributed environmental sampling was successfully performed across multiple locations within Miami Whitewater Lake, Ohio. The study demonstrated operational feasibility for portable freshwater lake monitoring while highlighting the specific challenges and solutions associated with dissolved organic matter-rich environments.

Observable differences among sampling locations reinforce the value of distributed environmental monitoring approaches.

EcoExposure™ (ecoterahome.com) offers a portable, smartphone-enabled platform designed to detect both microplastics and nanoplastics in field-collected water samples using simple reagent-based preparation and adaptive optical analysis. These findings complement previous urban river monitoring studies and support the continued development of scalable environmental intelligence workflows capable of operating effectively across diverse aquatic ecosystems — urban rivers, inland lakes, and beyond.

Reference

Chu MB.  Rapid Distributed Seine River Microplastic / Nanoplastic Sampling Pilot — Paris, France https://doi.org/10.5281/zenodo.20361744A This paper is also available at: https://doi.org/10.5281/zenodo.20454247