Having started with the simplest ways to quantify stormwater benefits of Tree Stormwater Control Measures (SCMs), we now arrive at the most complex ways. Part 1 of this series provided an overview of various ways to quantify stormwater benefits of Tree Stormwater Control Measures (SCMs), and gave an overview of tree benefits calculators and stormwater credits. Part 2 gave an overview of single event stormwater models. Today I will give an overview of continuous simulation stormwater models to quantify tree SCM benefits. Continuous models are generally quite complex, so this blog will be a high level summary of the modeling factors related to trees.
While continuous models are generally more complex (i.e. time consuming) than single event models, they generally provide an even more accurate representation of stormwater benefits. Single event models are often based on synthetic design storms. They therefore generally do not consider varying patterns of rainfall duration and intensity, variation of time between storms, changing antecedent soil moisture and surface storage conditions within the watershed, or the effects of evaporation and transpiration. Continuous models can quantify SCM benefits over the long-term, often many decades.
Because they account for many sizes and intensities of storms, as well as variation in the time between storms (typically based on long term rainfall records rather than synthetic design storms), continuous models provide a more accurate representation of infiltration, evapotranspiration (ET), depression storage, system storage, and therefore of the water balance of proposed SCMs.
For example, since evapotranspiration primarily occurs between rainfall events, single event models generally do not model it, but many continuous models can. Continuous models also tend to better represent water movement through various soil and rock layers and into the groundwater table than single event models, though the robustness of soil water calculations varies considerably between continuous models. Soil water content in turn affects evapotranspiration.
Factors to consider when selecting a continuous model to quantify tree stormwater control measure benefits include:
- How accurately is water movement through soil modeled?
- How does it model runoff into and flow out of the SCM?
- Does it include evapotranspiration?
- Can the user specify vegetation type (e.g., trees vs. herbaceous plants, etc.)?
- Can the model route runoff through multiple SCMS?
- Model complexity weighed against model accuracy
- Model calibration against field-collected data
- Model cost
There are many other factors to consider, depending on your project. Following are just a few examples related to Tree SCMs.
One continuous model that seems particularly well suited to quantify stormwater benefits of tree SCMs is WinSLAMM. Some of its strengths related to quantifying stormwater benefits of trees include:
- It is based on field monitoring data.
- User can specify soil type, porosity, field capacity, wilting point, and infiltration rate (user defined or by specifying percent of components, see Figure 1).
- It takes into account user defined level of soil compaction.
- It allows the user to set the percent of each vegetation type (trees, shrubs, prairie plants, other grasses, annuals, user defined), and it then assigns root depth and evapotranspiration crop adjustment factors based on the vegetation type, and uses these for evapotranspiration calculations (see Figure 2).
- User can also specify evaportanspiration in inches per day for each month (see Figure 2).
- User can specify whether or not biofilters will be irrigated, as well as the fraction of available capacity when irrigation starts and fraction of available capacity when irrigation stops (see Figure 2).
WinSLAMM also provides cost data, so the user can compare not only stormwater benefits, but also costs of alternative SCMS. One disadvantage of WinSLAMM is that it does not include snowmelt.
Another model that can be used to quantify stormwater benefits of tree SCMs is SWMM. Advantages of SWMM include:
- It is available for free from the EPA website (get it here).
- SWMM allows the user to choose from among four of the most widely used methods to model infiltration: Horton’s method, a modified Horton method, the Green-Ampt method, and the Curve Number method.
- “Depression storage may be used to simulate interception, the storage of rainfall on vegetation. Perhaps counter-intuitively, a tree, for instance, that intercepts rainfall can be simulated as an impervious surface, with depression storage (interception), whose runoff is onto an adjacent or underlying pervious surface. In this way, the interception capacity is regenerated only by evaporation.” (Rossman 2015)
- It models snow accumulation and snow melt.
Several proprietary models have been developed based on SWMM with additional modeling capacities, including, for example, XPSWMM and PCSWMM. Many more continuous models exist, and they vary considerably in their suitability to quantify tree SCM stormwater benefits, and their robustness.
It’s up to you
With all models, robustness of results will depend in large part on the creativity of the user in applying the model to tree SCMs. Lucas (2010) provides an example of creative and robust use of both a continuous model (SWMM) and a single even model (HydroCAD8.5) to model bioinfiltration.
While the level of detail in some of the continuous models is impressive, they are still just models, and many project-specific conditions may influence actual performance. For example, infiltration is significantly affected by soil macropores formed by root turnover, macropore radius, invertebrate organisms in the soil, and shrink swell cracks in clayey soil.
Lucas (2010) points out the magnitude of the influence of these macropores: “To appreciate the importance of macropore flow, consider that macropores created by worm holes and roots are in the range of 2 mm wide, while soils without bioturbation may have pores 1/10 that diameter (Rose 2004, p. 205). Because a macropore 2 mm wide will have 104 times the flux of macropores 1/10 the diameter, the effect of macropores therefore exerts a substantial influence upon field infiltration rates (Novák et al. 2000). This is why infiltration rates generally remain higher in bioretention systems than in infiltration basins where vegetation is absent.” That means that a soil with roots and wormholes will have 10,000 times the infiltration of soil without life in it!
In a previous blog, I wrote about why trees generally influence infiltration rates even more than lawn or pasture without trees: “Tree roots create more stable macropores for several reasons. The roots of dicotyledonous plants, like most trees, grow in thickness (secondary growth) as well as in length (primary growth). The roots of monocotyledonous plants, which includes grasses, usually do not exhibit secondary growth, so they are more prone to collapsing than the thicker macropores created by dicots. Also, woody plant roots have a lining on their roots that further increase stability of the macropores after the root decays.” So, not only does vegetation significantly affect soil infiltration rates, the type of vegetation matters also.
Many other field conditions that are not modeled can also influence infiltration rates (e.g. surface clogging), so field monitoring will be valuable regardless of the robustness of modeling. Nevertheless, models are crucial for planning and design, as well as many other uses.
Lucas, William C. 2010. Design of Integrated Bioinfiltration-Detention Urban Retrofits with Design Storm and Continuous Simulation Methods. JOURNAL OF HYDROLOGIC ENGINEERING:486-498.
Novák, V., Simunek, J., and van Genuchten, M. T. _2000_. “Infiltration of water into soil with cracks.” J. Irrig. Drain. Eng., 126_1_, 41–47.
Rose, C. W. _2004_. An introduction to the environmental physics of soil water and watersheds, Cambridge University Press, Cambridge, U.K.
Rossman, Lewis. 2015. Storm Water Management Model Reference Volume 1 – Hydrology. U.S. Environmental Protection Agency Office of Research and Development National Risk Management Laboratory. EPA/600/R-15/162. Available 12/21/2015 from http://nepis.epa.gov/Exe/ZyPDF.cgi?Dockey=P100MX13.txt
Nathalie Shanstrom is a sustainable landscape architect with The Kestrel Design Group.
Image: Bob Mical / CC BY-NC 2.0
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