Determining how much rainfall becomes surface runoff versus how much soaks into the ground is a foundational challenge in water resource management. Predicting this direct runoff is accomplished using the Curve Number (CN) method. This established hydrologic tool was developed by the United States Department of Agriculture’s Soil Conservation Service (now the NRCS). The empirical CN method provides a standardized index to estimate the amount of water that flows quickly off a land area following a storm event, integrating the physical properties of a watershed.
What the Curve Number Represents
The Curve Number is a dimensionless index that serves as a proxy for a land area’s potential to generate surface runoff. It estimates the total amount of rainfall a watershed can absorb and retain before runoff begins (potential maximum retention). CN values range from 0 to 100, with each number reflecting a different runoff potential.
A higher Curve Number indicates a greater likelihood of direct surface runoff and less infiltration. For example, an impervious surface like a paved road or a rooftop has a CN value close to 100, meaning nearly all rainfall becomes runoff. Conversely, a low CN, such as a value in the 30s, signifies high infiltration capacity and low runoff potential, typical of deep, well-drained soils under dense forest cover.
The CN method simplifies a complex natural process by aggregating numerous factors into a single, usable number. This index allows hydrologists to calculate the depth of runoff from a given depth of rainfall using a simple formula. The CN is an event-based calculation, designed to estimate the outcome of a single storm rather than modeling long-term annual water totals.
The Variables That Define the Curve Number
Determining the appropriate Curve Number requires combining data from several key physical and environmental factors. The primary variable is the soil’s inherent capacity to absorb water, categorized into four Hydrologic Soil Groups (HSGs). Group A soils, such as deep sands or gravels, have the highest infiltration rates and the lowest runoff potential.
In contrast, Group D soils, which often include clay soils with high swelling potential or shallow soils over impervious layers, have the slowest water transmission rates and the highest runoff potential. Groups B and C represent intermediate infiltration capacities. This soil grouping is based on the minimum infiltration rate observed after the soil has been thoroughly wetted.
The next major factor is the land cover and its treatment, which describes the type of surface where the rain falls. This includes natural covers like forest and rangeland, as well as developed areas with cultivated crops, urban lawns, and impervious surfaces. A dense forest floor allows for greater infiltration than sparsely covered agricultural land. Surface condition, such as whether a pasture is in “good” or “poor” hydrologic condition, further refines the CN value.
Finally, the Antecedent Moisture Condition (AMC) accounts for the wetness of the soil immediately before the storm event. The CN is typically calculated assuming an average moisture condition (AMC II). However, it can be adjusted to reflect dry (AMC I) or saturated (AMC III) conditions. A saturated soil absorbs less new rainfall, effectively increasing the Curve Number and leading to a higher runoff estimate.
Using Curve Numbers to Predict Runoff
The computed Curve Number is the foundational input for estimating the volume of water that flows over the land surface during a design storm. Hydrologists and civil engineers use this calculation to predict the peak rate and total volume of direct runoff from a specific rainfall event. This prediction is typically incorporated into computer models that simulate the movement of water across the watershed.
The estimated runoff volume is directly applied in the design of water control and flood mitigation structures. The CN helps determine the necessary capacity for storm drains, culverts, and bridges to safely handle predicted floodwaters. It also informs the sizing of retention ponds, which capture and slowly release runoff to prevent downstream flooding and erosion.
This predictive power is important for planning sustainable land use and development, particularly in rapidly urbanizing areas where impervious surfaces are increasing. By accurately estimating runoff, planners can design projects that minimize the impact of development on natural drainage patterns and downstream communities. The Curve Number method is an indispensable tool for protecting property and managing water resources.