Runoff Volume & Curve Number Methods

Stormwater Quality Training Series  |  Rainfall Excess, CN Method, and DCIA Calculations  |  Last updated: 2025

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1. Introduction & Learning Objectives

Section 1 of 11  ·  Source slides: 1–2

Accurate estimation of stormwater runoff volume is foundational to water quality work. Unlike flood-control hydrology — where peak discharge drives design — stormwater quality engineering depends on runoff volume because pollutant mass loading is the product of concentration and volume. Getting the volume right is therefore the first and most consequential step in any pollutant load analysis or BMP sizing exercise.

Learning Objectives

After completing this module, participants will be able to:

• Explain why runoff volume — rather than peak rate — is the primary metric for stormwater quality calculations.
• Define rainfall excess and describe how it differs from total precipitation.
• Apply the NRCS Curve Number (CN) method to estimate runoff volume from a given storm event.
• Distinguish between DCIA (Directly Connected Impervious Area) and non-DCIA sub-basins and calculate runoff for each separately.
• Perform hand calculations for representative land-use scenarios using CN-based runoff equations.

Module Approach

This module combines conceptual explanation with worked numerical examples. The CN method is introduced first as a theoretical framework, then applied through hand calculations on representative project sites. Example projects are drawn from real-world permit scenarios to reinforce practical application.

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2. Runoff Generation Fundamentals

Section 2 of 11  ·  Source slides: 3–4

Surface runoff is one pathway within the broader hydrologic cycle. When precipitation falls on a catchment, water is partitioned among interception by vegetation, infiltration into the soil profile, evapotranspiration back to the atmosphere, groundwater recharge, and surface runoff. The fraction that becomes surface runoff is governed by three interacting factors: precipitation characteristics, soil type, and land cover.

Governing Factors

• Precipitation: Total depth, intensity, and duration all influence how much water infiltrates versus runs off. High-intensity rainfall can exceed soil infiltration capacity even on permeable soils.
• Soil type: Hydraulic conductivity, texture, and antecedent moisture determine infiltration capacity. Sandy soils absorb water quickly; clay-rich soils with low permeability generate runoff more readily.
• Land cover: Vegetation intercepts rainfall and promotes infiltration. Impervious surfaces (roads, rooftops, parking lots) prevent infiltration entirely, routing nearly all rainfall directly to the drainage system.

Impervious Area and DCIA

Urban development dramatically increases the proportion of impervious cover in a watershed. However, not all impervious area contributes equally to runoff. The concept of Directly Connected Impervious Area (DCIA) distinguishes between impervious surfaces whose runoff flows directly into a pipe or channel system and those whose runoff first passes over a pervious area where some infiltration can occur before reaching the drainage network.

Runoff Coefficients (ROC)

A runoff coefficient (ROC) expresses the fraction of total rainfall depth that becomes surface runoff depth. An ROC of 0.40 means that 40% of rainfall, averaged over a season or year, exits the catchment as surface runoff.

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3. SCS Curve Number Method

Section 3 of 11  ·  Source slides: 5–7

Several hydrologic modeling approaches are available for estimating runoff volume — including continuous simulation models such as ICPR and SWIM — but the SCS (now NRCS) Curve Number method has been selected as the standard approach for the calculations presented in this training series. The CN method offers a well-documented, widely peer-reviewed, and computationally transparent framework appropriate for both permit-level screening and detailed BMP sizing.

Technical Background: TR-55

The CN method is documented in the Natural Resources Conservation Service (NRCS) Technical Release 55 (TR-55), Urban Hydrology for Small Watersheds. TR-55 provides the theoretical derivation, empirical lookup tables, and worked examples needed to apply the method. CN values in TR-55 were developed from extensive field data collected across a wide range of agricultural and urban land uses in the United States.

How CN Values Are Derived

Curve Numbers are empirically derived dimensionless numbers ranging from 0 (no runoff) to 100 (complete runoff). They are tabulated as a function of two primary inputs:

• Land cover type: Includes categories such as residential (by lot size), commercial, industrial, open space, meadow, woods, and cultivated agricultural land.
• Hydrologic Soil Group (HSG): A four-class soil classification system (A, B, C, D) based on the minimum infiltration rate of bare soil after prolonged wetting.

Hydrologic Soil Groups (HSG)

The four Hydrologic Soil Groups reflect a gradient from highly permeable to nearly impermeable soils:

Many soils in Florida and other coastal states exhibit dual HSG designations (e.g., A/D or B/D), reflecting conditions where the soil behaves as a high-infiltration Group A when artificially drained but as a nearly impermeable Group D under undrained, seasonally high water-table conditions. The appropriate HSG to apply depends on the drainage context of the project.

The CN Runoff Equation

Once a CN value is assigned, runoff depth Q (inches) for a given storm rainfall P (inches) is calculated as:

The term initial abstraction (I_a = 0.2S) represents rainfall intercepted by vegetation, infiltrated before ponding begins, and retained in surface depressions — all losses that occur before any runoff is generated. Only rainfall in excess of I_a is available to produce runoff.

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4. Curve Numbers & Hydrologic Conditions

Section 4 of 11  ·  Source slides: 8–10

CN values are not fixed solely by soil group and land cover type. For many pervious cover categories — particularly managed open space, pasture, meadow, and woods — TR-55 provides three CN values corresponding to three hydrologic conditions: Poor, Fair, and Good. The hydrologic condition rating describes how effectively the cover promotes infiltration and resists runoff generation.

Hydrologic Condition Ratings

• Poor condition: Heavily grazed, sparse vegetation cover, compacted soils, or otherwise degraded cover that promotes runoff. Assigned the highest CN (most runoff).
• Fair condition: Moderate vegetative cover with some bare areas. Intermediate CN value.
• Good condition: Dense vegetative cover, minimal compaction, and conditions that actively encourage infiltration. Assigned the lowest CN (least runoff). For example, a well-maintained lawn or forest in good hydrologic condition generates substantially less runoff than the same land cover in poor condition.

Special Land Cover Assignments

Two land cover categories require specific treatment in CN-based runoff accounting:

Errors from Averaging CN Values

A critical methodological point: averaging CN values across sub-areas before computing runoff introduces significant error. Because the CN–runoff relationship is nonlinear (quadratic in form), the runoff computed from an area-weighted average CN is not equal to the area-weighted average of runoffs computed separately for each sub-area. This nonlinearity means that averaging CNs systematically underestimates or overestimates total runoff depending on the distribution of CN values.

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5. DCIA and Non-DCIA Calculations

Section 5 of 11  ·  Source slides: 11–15

A cornerstone of Florida’s stormwater quality permitting framework — and of good hydrologic practice more generally — is the separate treatment of Directly Connected Impervious Area (DCIA) and Non-DCIA portions of a project site. This separation acknowledges that impervious surfaces hydraulically connected to a collection system generate runoff fundamentally differently from pervious areas or impervious areas that drain across pervious surfaces before reaching the drainage network.

Defining DCIA

DCIA consists of impervious surfaces whose stormwater runoff flows directly into a constructed conveyance system — typically a storm drain inlet, pipe, or concrete-lined channel — without first traversing any pervious land surface. Common DCIA elements include:

• Parking lots and driveways draining to curb inlets or catch basins
• Rooftops connected to downspouts that discharge to storm drains
• Roads with curb-and-gutter profiles directing flow to inlets

Defining Non-DCIA

The Non-DCIA sub-basin encompasses all land area not classified as DCIA, including:

• All pervious land covers (lawns, landscaped areas, open space, woods, wetlands)
• Impervious surfaces that are hydraulically disconnected — i.e., their runoff sheet-flows over a pervious area before reaching a collection point
• Impervious areas draining to swales or other infiltration-based BMPs

CN for Non-DCIA Impervious Surfaces

When impervious surfaces are included within the non-DCIA sub-basin (because they are disconnected), a CN of 95 is assigned to those impervious areas. This value reflects the very high runoff potential of impervious surfaces while acknowledging that a small fraction of rainfall may be retained in minor surface depressions. The CN of 95 is consistent with TR-55 guidance for impervious areas and is widely adopted in Florida regulatory practice.

Composite CN for Non-DCIA: Area vs. Volume Weighting

Because the non-DCIA sub-basin contains multiple land cover types with different CN values, a composite CN must be developed. Two weighting approaches are available:

Why Separate DCIA and Non-DCIA?

Treating DCIA and non-DCIA as distinct calculation units improves accuracy in two important ways. First, DCIA generates runoff from virtually every rainfall event — even very small storms — because there is no initial abstraction pathway. A single curve number applied to a mixed basin would underestimate DCIA runoff for small, frequent storms. Second, separating the two sub-basins provides a direct accounting of the water quality benefit achieved by disconnecting impervious areas — a benefit that would be invisible if the entire site were treated as a single composite CN.

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Topic 6: Antecedent Moisture & CN Adjustment

Section 6 of 10 — Curve Number Adjustments for Antecedent Moisture Conditions

The standard SCS/NRCS Curve Number method assumes an average antecedent moisture condition (AMC II). However, the long-term continuous simulation approach used in SFWMD’s methodology requires that CN values be adjusted to reflect the full range of soil moisture states that occur over a multi-year rainfall record. Failing to account for antecedent moisture would systematically bias the simulated annual runoff volumes.

The Three Antecedent Moisture Conditions

Three AMC classifications are recognized within the TR-55 and TR-20 framework, each associated with a different effective CN value:

• AMC I — Dry: Soils are dry but not to wilting point. Five-day antecedent rainfall is below the threshold for the dormant or growing season. The effective CN is lower than the standard value, meaning less runoff is produced per unit of rainfall.
• AMC II — Normal: Average conditions. This is the baseline CN assigned in standard land-use tables. It represents the most commonly observed antecedent moisture state and is the reference point for the AMC I and AMC III conversions.
• AMC III — Wet: Soils are nearly saturated from heavy rainfall in the preceding five days. The effective CN is higher than AMC II, producing significantly greater runoff volumes from the same storm event.

Seasonal Growth Period Factor

In addition to the five-day antecedent rainfall criterion, the AMC classification incorporates a seasonal growth period adjustment. The threshold five-day rainfall values that define the AMC I / II / III boundaries differ between the dormant season and the growing season. This is because active vegetation during the growing season increases evapotranspiration and soil water uptake, effectively lowering antecedent moisture relative to dormant-season conditions with the same rainfall total.

For Florida, the growing season generally spans the warmer, wetter months (roughly May through October), which coincide with the peak of the wet season. During this period, the threshold for transitioning from AMC I to AMC II is higher than in the dormant season — meaning that more antecedent rainfall is required before soils are classified as “normal” moisture. This interaction between seasonality and soil moisture is automatically handled within the simulation framework but must be understood when interpreting CN adjustments in hand calculations.

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Topic 7: Hydrologic Simulation Modeling

Section 7 of 10 — Structure and Scope of the SFWMD Long-Term Simulation Study

The ROC values published in Appendix N of the Applicant’s Handbook are not empirically derived from field measurements — they are the product of a large-scale, systematically designed hydrologic simulation study. Understanding the structure of that study is essential for correctly applying the ROC methodology and for recognizing its geographic and parametric limits.

Rainfall Data Inputs

Hourly rainfall records from 45 Florida rainfall gauging sites were used as the primary meteorological inputs. These sites were selected to provide broad geographic coverage across the state, capturing the wide range of rainfall regimes that exist from the Panhandle to the Keys. Key characteristics of the dataset include:

• The majority of sites had 30 or more years of continuous hourly data, providing a statistically robust period of record.
• The mean number of discrete rainfall events identified across all sites was approximately 4,685 events per site, yielding a dataset of hundreds of thousands of individual storm events for analysis.
• Events were separated using a minimum inter-event time criterion to distinguish independent storms from multi-peak continuous rainfall.

Parametric Design of the Simulation Matrix

The simulation study used a full factorial design across two key land-cover parameters, creating a matrix that spans the range of conditions typically encountered on permitted sites in Florida:

• DCIA (Directly Connected Impervious Area): Varied from 0% to 100% of the total developed area, in increments that allow interpolation across the full range of impervious cover scenarios.
• Non-DCIA Curve Number: Varied from CN 25 to CN 95 in 5-unit steps, covering everything from highly pervious, well-vegetated soils (HSG A with woods) to nearly impervious urban land cover (HSG D with commercial paving).

Runoff-to-Rainfall Ratio (ROC) Definition

The central output metric of the simulation study is the Runoff-to-Rainfall Ratio (ROC), defined as:

Because the ROC is dimensionless (depth divided by depth), it can be applied to any total annual rainfall depth to yield a predicted annual runoff depth in the same units. Multiplying by site drainage area converts runoff depth to volume. This simplicity is a key operational advantage of the ROC approach compared to event-by-event simulation.

Identification of Five Meteorological Zones

After completing all 15,750 simulations, the ROC values for each of the 45 rainfall sites were analyzed for geographic patterns. A cluster analysis was performed to group sites with statistically similar ROC behavior — i.e., sites where the same combination of DCIA and non-DCIA CN produced comparable annual runoff fractions. This analysis identified five distinct meteorological zones across Florida.

The clustering reflects differences in storm frequency, intensity distribution, and seasonal patterns rather than simply annual rainfall totals. Two sites with identical mean annual rainfall can produce different ROC values if one receives its rainfall in frequent small events (more abstraction losses) versus infrequent large events (less abstraction relative to total depth). The five-zone structure captures these regime differences in a form that can be practically applied by permit applicants.

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Topic 8: ROC Lookup Tables & BMPFast Tool

Section 8 of 10 — Accessing and Applying the ROC Methodology in Practice

The results of the simulation study are made available to permit applicants in two complementary formats: printed lookup tables in the Applicant’s Handbook and the BMPFast software tool. Both access the same underlying ROC data, but BMPFast provides significant computational advantages for sites where interpolation between tabulated values is required.

Appendix N Lookup Tables

The ROC lookup tables are published in Appendix N of the SFWMD Applicant’s Handbook. A separate table is provided for each of the five meteorological zones, structured as a matrix with the following axes:

• Columns — Annual Rainfall Depth: Tabulated at the mean annual rainfall for each zone, with variation to accommodate sites that differ from the zonal mean.
• Rows — Non-DCIA Curve Number: Listed at 5-unit intervals from CN 25 to CN 95.
• Subtables — DCIA Percentage: Separate table sections for each DCIA increment.

To retrieve a ROC value manually, the applicant must:

• Identify the correct meteorological zone for the project site.
• Determine the site’s mean annual rainfall (from isohyetal maps or gage data).
• Calculate the site’s DCIA percentage and composite non-DCIA CN.
• Locate the appropriate table, row, and column intersection.
• Interpolate if the site’s DCIA or CN falls between tabulated increments.

BMPFast Software Tool

BMPFast is the SFWMD-provided computational tool designed to automate the ROC lookup and interpolation process. It is the preferred method for ROC calculation in permit applications and provides several capabilities beyond simple table lookup:

• Automatic two-way interpolation: BMPFast accepts any DCIA percentage and any non-DCIA CN value (not just the 5-unit tabulated increments) and performs the necessary interpolations internally, eliminating the most common source of hand-calculation error.
• Zone and rainfall input: The user selects the meteorological zone and enters the site’s mean annual rainfall; BMPFast retrieves the appropriate ROC from the embedded Appendix N data.
• Sensitivity analysis via the Tools menu: BMPFast includes a sensitivity analysis function that allows the applicant to vary one or more input parameters — such as DCIA percentage or non-DCIA CN — across a range and observe the effect on annual runoff volume. This is particularly useful for evaluating the benefit of design alternatives (e.g., reducing DCIA through disconnection) or for testing the robustness of a treatment system design to CN uncertainty.
• Integrated treatment volume calculations: BMPFast can carry the ROC-derived annual runoff volume forward into BMP sizing calculations, providing an end-to-end computational workflow for the water quality volume methodology.

Required Inputs Summary

Whether using BMPFast or the printed tables, the four essential inputs for any ROC calculation are:

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Topic 9: Impact of Disconnecting DCIA

Section 9 of 10 — Design Strategies for Reducing Effective Impervious Area

One of the most powerful — and frequently underutilized — design tools in the ROC methodology is the ability to disconnect directly connected impervious area. By rerouting runoff from impervious surfaces through pervious areas before it reaches the drainage system, a designer can meaningfully reduce the site’s effective annual runoff volume and, consequently, the size of the required stormwater treatment system.

What “Disconnecting” DCIA Means

In the standard ROC model, DCIA is impervious area whose runoff flows directly to the drainage conveyance system without passing over any pervious surface that could absorb a portion of the flow. Common examples include:

• Rooftops with downspouts connected directly to curbs, gutters, or storm drains.




• Driveways with positive drainage to the street or a catch basin.




• Parking lots draining through curb cuts directly to inlets.

Disconnecting these surfaces means redesigning the drainage so that their runoff is directed onto — and must flow across — a pervious surface before entering the conveyance system. Practical disconnection measures include:

• Redirecting roof downspouts to splash onto a lawn or landscape area rather than connecting to a pipe.




• Routing driveway runoff through a grass swale or vegetated buffer strip alongside the driveway.




• Designing parking lot grades so runoff sheet-flows across a vegetated median or perimeter buffer before reaching an inlet.

How Disconnection Affects the ROC Calculation

When impervious area is successfully disconnected, its runoff is no longer counted in the DCIA percentage. Instead, the runoff from the disconnected surface is added to the runoff from the pervious area it flows across, and the combined flow is treated as originating from a single composite pervious land unit. This has two effects in the ROC model:

• DCIA decreases: The DCIA percentage used in the ROC lookup is lower, which directly reduces the ROC value and the computed annual runoff.




• Non-DCIA CN changes: The disconnected impervious area must still be accounted for in the non-DCIA CN calculation. Its CN (typically 98 for impervious surface) is included in the area-weighted composite CN for the non-DCIA lands. This increases the non-DCIA CN somewhat, partially offsetting the benefit of DCIA reduction, but the net effect is almost always a reduction in total annual runoff.

Design Significance

The ROC methodology makes the benefit of DCIA disconnection directly quantifiable in volume units — a feature that is not available in single-event design storm approaches. Because annual runoff volume is the basis for treatment system sizing under the water quality volume method, even a modest reduction in DCIA can translate to a meaningful reduction in required pond or system size. This creates a direct economic incentive for site designers to evaluate disconnection opportunities early in the design process, before drainage system layouts are fixed.

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Topic 10: Example Hand Calculations

Section 10 of 10 — Step-by-Step ROC Calculation for a Single-Family Residential Site

The following worked example demonstrates the complete hand calculation procedure for determining annual runoff volume using the SFWMD ROC methodology. The example uses a single-family residential development scenario and performs calculations for two meteorological zones to illustrate the geographic sensitivity of the results.

Site Description and Given Data

Step 1 — Calculate the Non-DCIA Composite Curve Number

The non-DCIA portion of the site consists of all land cover types that are either pervious or impervious-but-not-directly-connected. For this single-family residential site on HSG D soils, the area-weighted composite CN for the non-DCIA lands is calculated from the individual land cover areas and their respective TR-55 CN values:

Land Cover / Use	Area (ac)	Fraction of Non-DCIA	TR-55 CN (HSG D)	Weighted CN
Lawn / Open Space (good cover)	38.25	0.524	80	41.90
Roads / Paving (non-DCIA impervious)	10.80	0.148	98	14.50
Rooftops (disconnected)	13.95	0.191	98	18.72
Driveways (disconnected)	9.75	0.134	98	13.11
Lakes / Water Bodies	0.50	0.007	100	0.68
Non-DCIA Subtotal	73.25	1.000	—	88.91 → use 81.15*

Step 2 — Identify Meteorological Zones and Annual Rainfall

This example performs the ROC calculation for two locations to demonstrate the geographic variability of results:

• Pensacola — Zone 1: Mean annual rainfall ≈ 65.0 inches/year. Zone 1 encompasses northwest Florida and is characterized by higher-frequency, lower-intensity rainfall events relative to South Florida.




• Key West — Zone 3: Mean annual rainfall ≈ 40.0 inches/year. Zone 3 covers the Florida Keys and extreme South Florida, with a strongly seasonal pattern and lower total annual depth.

Step 3 — Look Up ROC Values from Appendix N

Using DCIA = 18.75% and non-DCIA CN = 81.15, the applicable ROC values are retrieved from the Appendix N tables for each zone. Because CN = 81.15 falls between the CN 80 and CN 85 tabulated rows, linear interpolation is required:

Location	Zone	Annual Rainfall (in)	DCIA (%)	Non-DCIA CN	ROC (from Appendix N)
Pensacola	1	65.0	18.75	81.15	0.3015
Key West	3	40.0	18.75	81.15	0.264

Step 4 — Calculate Annual Runoff Volume

Annual runoff volume is calculated by multiplying the ROC by the annual rainfall depth and the drainage area:

Pensacola (Zone 1):

• Annual Rainfall = 65.0 in ÷ 12 = 5.417 ft/yr




• Annual Runoff = 0.3015 × 5.417 ft/yr × 90 ac = 148.1 ac-ft/yr

Key West (Zone 3):

• Annual Rainfall = 40.0 in ÷ 12 = 3.333 ft/yr




• Annual Runoff = 0.264 × 3.333 ft/yr × 90 ac = 79.2 ac-ft/yr

Step 5 — Interpretation and Design Implications

The example demonstrates several key practical points that should inform how designers use the ROC methodology:

• Geographic zone dominates: The same 90-acre site with identical land cover, soils, and DCIA generates nearly twice the annual runoff volume in Pensacola compared to Key West — a direct consequence of higher annual rainfall and different storm frequency distributions. Zone assignment is not a minor administrative step; it is the single most geographically sensitive input in the calculation.




• CN weighting method matters modestly: The area-weighted CN of 81.15 versus the runoff-volume-weighted CN of 82.06 produces a small but real difference in the ROC lookup result. For conservative design or for sensitive receiving water bodies, the volume-weighted CN provides a more physically defensible estimate.




• Treatment system sizing scales directly: A BMP designed to treat 148.1 ac-ft/yr must have significantly greater hydraulic capacity than one sized for 79.2 ac-ft/yr. For a fixed annual pollutant load removal target, the pond volume, residence time, or outfall control structure will all differ substantially between the two zones.
• Interpolation discipline required: Because CN = 81.15 falls between tabulated rows, the 23% interpolation factor must be applied consistently to both the DCIA column and the CN row. A two-way interpolation error is the most common computational mistake in hand calculations — BMPFast eliminates this risk entirely.

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11. Key Takeaways

Section 11 — Summary of core principles and practice standards

The following points consolidate the essential concepts covered across this module. A working command of these principles is necessary for accurate stormwater runoff volume calculations in Florida permitting practice.

11.1 Spatial and Hydrologic Variability

Runoff volume in Florida is highly variable by location and catchment design. Rainfall depth, antecedent soil moisture, seasonal water table elevation, soil infiltration capacity, and land cover all interact to produce site-specific runoff responses. A single statewide default value is never appropriate; each project catchment must be characterized individually using measured or mapped inputs.

11.2 The Impervious Area–Runoff Relationship

There is a direct, measurable relationship between impervious area and runoff volume. As impervious cover increases across a catchment, infiltration opportunities decrease, depression storage is reduced, and a larger fraction of each rainfall event becomes surface runoff. This relationship underpins both the DCIA methodology and the composite CN approach: accurately mapping and quantifying impervious surfaces is the single most consequential step in any runoff volume calculation.

11.3 The Exponential CN–Runoff Relationship

The relationship between Curve Number (CN) value and computed runoff depth is nonlinear and exponential in character. Small changes in CN at the high end of the scale (CN 85–98) produce large changes in runoff; small changes at the low end (CN 30–55) produce comparatively modest changes. This sensitivity means that CN assignments must be made carefully and defensibly, particularly for high-impervious sites where the CN is already elevated.

11.4 Separate Calculations for DCIA and Mixed Land Uses

Directly Connected Impervious Area (DCIA) and mixed pervious–impervious land uses require separate runoff calculations that are then combined to produce the total catchment runoff volume. DCIA is assumed to generate runoff from every rainfall event, using a CN of 98 with no initial abstraction applied. Pervious and indirectly connected impervious areas use the standard SCS CN equation with an appropriate composite CN derived from area-weighted land use assignments. Blending these two populations into a single CN would underestimate DCIA runoff and overstate pervious area losses.

11.5 BMPFast as the Accepted Computational Tool

BMPFast enables accurate and timely runoff volume calculations consistent with Florida regulatory requirements. The tool automates the DCIA separation, CN weighting, and volume summation steps described throughout this module, reducing manual arithmetic errors and ensuring that outputs are traceable and reproducible. Practitioners should be familiar with BMPFast’s input structure — particularly how DCIA, soil groups, and land use categories are entered — so that tool outputs can be audited and defended during agency review.

11.6 Governing Regulatory Framework

Current Florida stormwater runoff volume practice is governed by two primary references:

• 2007 Harper Methodology — establishes the scientific basis for DCIA-separated runoff calculations, CN assignment protocols, and the treatment volume equations used in Florida. This methodology introduced the treatment of DCIA as a distinct hydrologic population and remains the analytical foundation for SWFWMD permitting.
• 2024 Applicant’s Handbook (SWFWMD) — provides the current procedural and submittal requirements for stormwater management system permits. The Handbook incorporates the Harper methodology and specifies how runoff calculations must be documented, formatted, and submitted for agency review.

11.7 Consolidated Takeaway Summary

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Appendix — Quick-Reference Cards

Appendix — Condensed reference material for field and office use

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