What are stormwater utility fees?

Stormwater utility fees (SUFs) are taxes established by municipal governments to fund the creation, improvement, and maintenance of stormwater infrastructure. More than 2,500 communities throughout the US have SUF programs in place, a number that continues to grow as municipalities seek to build climate resilience in our dynamically changing world.

For example, SUFs can fund the maintenance of sewer and stormwater infrastructure to reduce the likelihood of flooding and overflow in an extreme precipitation event. Similarly, SUFs can be leveraged for infrastructure projects that mitigate flood risk, such as the installation of stormwater medians with vegetation that absorbs excess precipitation. As climate resilience becomes increasingly top of mind for municipalities across the US, new and innovative applications of SUF funding are emerging to reduce strain on infrastructure, enhance hazard mitigation efforts, and promote sustainability.

Why do municipalities have stormwater utility fees?

Stormwater utility fees are helpful for ensuring there is a dedicated source of funding for critical infrastructure and climate resilience efforts. While some communities fund stormwater improvements through general property or income taxes, this does not guarantee funds will be available for important stormwater improvements.

Unfortunately, the need for stormwater funds is often forgotten until there is a flooding event. Having a dedicated fund for stormwater infrastructure development, maintenance, and improvement is critical for mitigating such events, as well as for providing more transparency in municipal fund allocation to property owners.

Types of stormwater utility fees

Each community has distinct stormwater needs depending on its climate, population, and infrastructure. There are four main types of SUF structures to help municipalities address these needs: flat fee, tiered, equivalent residential units (ERUs), and residential equivalency factors (REFs). 

These different SUF calculation methods each have their pros and cons. For instance, fee structures that do not account for the amount of impervious surface on a property are easiest to oversee, but less equitable. On the other hand, SUFs that determine rates based on impervious land cover more fairly distribute fees across property owners, but require high-precision data that is not always easy to create or acquire. Fortunately, advancements in artificial intelligence (AI) have made it possible for municipalities to inform their SUF strategy with comprehensive, accurate, and up-to-date impervious surface data.

Learn more about each type of stormwater utility fee below:

Equivalent residential units (ERUs)

The most popular method for calculating SUFs is by determining the number of equivalent residential units (ERUs) for a property. ERU fee structures assign a tax based on the average or median amount of impervious surface on the community’s single-family residential properties. Some communities include all residential properties or establish a maximum fee, although the majority of ERU fee structures rely on the average or median impervious land cover on single-family residential parcels.

In this system, non-residential properties then pay a fee proportional to the ratio of the impervious area and its equivalent residential units. This means that most single-family residential properties will pay the same SUF, while non-residential properties will pay a fee based on how many single-family residential properties could fit on their parcel.

The ERU method of SUF calculation is likely the most popular because it ensures fees reflect real land cover conditions in a community, but involves less administration than calculating the amount of impervious surface on each individual property. However, calculating ERUs correctly does require a complete, accurate, and up-to-date source of land cover data, which can be costly and time-consuming to maintain with traditional methods in a rapidly changing world.

Flat or fixed fees

After ERUs, the most popular SUF in the US is a flat or fixed fee for all properties in a community, regardless of land cover, size, or environmental conditions. These fees are the simplest to administer, but not always equitable. They do not consider the dynamic land use and climate factors impacting stormwater infrastructure and its effectiveness.

For example, research by stormwater experts at Western Kentucky University found that a flat SUF system resulted in properties being over or undercharged by around 126%. While flat or fixed SUFs do not require an investment in land cover data collection and maintenance, they do open municipalities up to a few risks. First, unfairly distributed SUFs can result in legal action against the municipality as property owners resist paying more than their fair share. Second, inaccurate SUF calculations can result in lower revenue for the community’s stormwater fund, meaning there are fewer resources for improving infrastructure.

Tiered fee system

The third most common SUF structure in place across US municipalities is a tiered system, which establishes a range of flat fees based on the amount of impervious surface located on each property. A tier system requires land cover data across a community in order to define the levels of impervious surface that correspond to the different groupings in the fee structure. As with the ERU method, a tiered system must rely on data that is complete, precise, and fresh, ensuring that fees are truly reflective of a property’s impervious surface, even as land use evolves.

These fees are usually more equitable than traditional flat fees, but that depends on how large the range of impervious surface is in each tier. Large ranges tend to indicate a less equitable SUF structure. Systems with more tiers are generally the most equitable, but ERU and REF fee programs are still the most effective.

Residential equivalency factors (REFs)

Other municipalities take their fee structure one step further than impervious surface calculations by also factoring in slope, soil type, and other elements. This method, known as calculating residential equivalency factors (REFs), considers how different properties vary in their contribution to runoff and stormwater infrastructure usage. 

To calculate a REF, municipalities calculate the average runoff during a standard storm for both the average single-family residential and non-residential properties, which then defines a ratio of runoff per acre that is used as a multiplier for the size of the property to determine its SUF rate. 

The REF SUF method helps ensure fees are equitably distributed based on the current environmental conditions of a property and its impact on infrastructure, but can be complex to calculate. Like ERUs and tiered systems, REFs require an authoritative land cover database that is kept up-to-date with the real world. Such databases are resource-intensive to maintain by traditional data creation methods, which can be a barrier for municipalities. 

Additionally, the climate data used to calculate average runoff for REF systems can be complicated, as the choice of the ‘standard’ storm can often favor either residential or commercial properties. Runoff calculations also involve complex hydrological modeling, so municipalities looking to implement a REF system must have a sophisticated geospatial and stormwater analytics program in place.

How to calculate stormwater utility fees

Calculating stormwater utility fees is largely dependent on understanding the amount of impervious surface in a community. As the breakdown of the main four SUF types above explains, impervious surfaces can be analyzed in a few different ways to determine an appropriate SUF. 

For example, ERU and tiered systems involve measuring the impervious surfaces on properties to determine SUFs, but do not always take the different types of impervious surfaces into consideration. In this case, accurately understanding the geographic extent of impervious land cover on a property is the most important factor in SUF calculation, so estimates and low-resolution data are insufficient.

On the other hand, REFs calculate a property’s contribution to runoff, which requires understanding how distinct types of impervious surfaces, as well as elevation, soil type, and other environmental factors, impact stormwater resilience. For this type of analysis, land cover data must include highly detailed layers of information that classify the different types of impervious and natural surfaces. Even flat fee systems can use land cover data to calculate the municipal SUF, using geospatial analysis to determine the average impervious surface throughout the community.

These differences in methodologies dictate what type of geospatial data is needed to support a municipality’s SUF program. Depending on the size and needs of the municipality, this data can be difficult to create and maintain. 

Geospatial data for stormwater utility fee calculation

As geospatial data and analysis support all four types of stormwater utility fees, municipalities are increasingly looking for ways to streamline their data creation, acquisition, and maintenance. Traditional geospatial data creation methods are extremely resource-intensive, requiring GIS teams to manually digitize all land cover features from imagery before measuring and calculating the figures needed for their particular fee structure. This often leads to stale data being used in fee calculations, as manual digitization cannot keep up with the rapid land use change occurring in our world every day. As an example, the City of Detroit was often working with impervious surface data that was two years old, which resulted in inaccurate SUF calculations amounting to about $5.6M in missed annual revenue.

Luckily, innovation in geospatial AI has created an alternative for municipalities struggling to keep their land cover databases up-to-date. It’s now possible for AI-based systems to ingest satellite, aerial, drone, or street view imagery and extract high-precision land cover features at scale, producing planimetric-level detail maps without the costly and time-consuming process of manual digitization. By switching from manual digitization to AI-powered feature extraction, Detroit was able to scale data creation by 18x, ensuring their SUF calculations are updated annually to reflect any land use change that has occurred in the past year.

Ecopia AI (Ecopia) regularly works with government organizations across the United States to create authoritative mapping data that supports all four types of SUF structures. Our AI-based mapping systems accurately and efficiently extract impervious and natural land cover features at scale to inform stormwater analysis and fee calculation. 

Examples of vector layers extracted by Ecopia for stormwater mapping include:

• grass
• shrubs
• bareland
• buildings
• sidewalks
• pavement
• driveways
• parking lots
• planting strips
• gravel
• decks
• patios
• tree canopy
• unpaved land
• sports grounds
• swimming pools
• stormwater medians
• natural water features

and similar land cover features needed to inform SUF structures across a community.

Ecopia’s data also helps communities develop resilient strategies to mitigate and reduce the impact of stormwater events on properties and infrastructure. For example, the City of Los Angeles uses Ecopia data to strategically plan the placement of stormwater medians and enhance climate resilience. 

Get started with impervious surface data for SUF calculation

Whether you’re just starting to roll out a stormwater utility fee program or are looking to scale your data creation to enhance your current operations, Ecopia’s dedicated stormwater team is here to help. We can help you determine which method of SUF calculation is right for your municipality, identify funding opportunities to support your program, and create an authoritative land cover database to inform your fee structures. Get in touch today to learn more.