SHC Hourly Flow Product

Why develop a flow model for local watersheds? Heavy precipitation generates stormwater runoff and this is the main driver behind recurring phenomena such as erosion, non-point source pollution, flooding, channel scouring, thermal excursions, salt wash-off, streambank erosion and stream sediments. These phenomena have numerous negative impacts in northeast Chester County but the stormwater runoff driving them is poorly quantified. Improving quantification of these phenomena is a priority and requires improved quantification of stormwater hydrology. GVWA's approach is to use a high resolution hourly flow model to simulate stormwater runoff and its progress through our watersheds; calibration and validation is carried out with USGS flow data currently and plans include collecting flow data at locations closer to runoff hotspots .

 Watersheds include French Creek, Pickering Creek, Pigeon Creek, Stony Run, Sixpenny Creek, Valley Creek, Hay Creek, and Stony Run . The SWAT model stream network is based on a full resolution stream network developed by GVWA previously for these watersheds, that was recently aligned with existing blue line features to improve map readability. Although a daily flow model for the entire SHC is working well, for an hourly time step the watersheds listed above are modeled separately due to computational limits; each of these watersheds are simply subsets of one larger model. This map show the current extent, subbasins and stream network.

The model GVWA is working with is the Soil and Water Assessment Tool, SWAT. It is a physically based, semi-distributed model that uses physiographic (e.g. elevation, land cover, soil), and climate (e.g. precipitation, temperature) data to evaluate hydrologic impacts of land use, land management, water regulation, and climate change at the watershed scale.

The process of simulating stormwater runoff events requires good precipitation data and a watershed model to able to process this data. NEXRAD hourly precipitation data is processed by the Soil and Water Assessment Tool (SWAT) watershed model to simulate stormwater runoff in this way.

Why build a flow model with an hourly time step rather than daily or monthly time steps? Runoff events and stormwater flows are usually short-lived, with peaks lasting a few hours at most. Peak flow conditions are preceded by peak runoff and these are also periods of peak erosion; these are the energetic events of most interest. Daily flow simulations will not resolve these energetic events well, while hourly will. To illustrate this difference in resolution, the figure below shows hourly peak flow cms (cubic meters per second) is three times that of daily peak flow. Both charts are using the same hourly data, with the daily chart using the hourly data averaged as daily flow. Hourly simulations are also better for comparing to observed flow measurements--this leverages observed flow data to a greater extent than would be possible with a daily time step.

As illustrated by this figure, the model simulates the hydrologic cycle with a detailed physical model. Runoff and on-land erosion is calculated hourly; all other variables are calculated daily and distributed into the hourly stream flow. Stream flow is observed at in-stream continuous sensor stations and with field sampling. If the weather observations are accurate, and if the model is capable of replicating the many physical processes involved, then the flows measured in the stream should align with the simulations produced by the model.

Projections for unchecked climate change in the Northeast US include increased intensity, duration and frequency (IDF) of heavy precipitation events.  Trends over the past 75 years show a 49% increase in days with 2" of precipitation, a 62% increase in days with 3" of precipitation, an 84% increase in days with 4" of precipitation, and a 103% increase in days with 5" of precipitation.  High resolution models are becoming available for the northeast US,  predicting that +5" precipitation events may be six times more likely by the end of this century.  These will clearly worsen all of the water quality issues we already have, with additional impacts downstream.

The validated SHC HFP is capable of evaluating future stormwater runoff volumes simply be changing the weather input files, running simulations, and comparing IDF change scenarios directly to existing surface hydrology at hourly resolution with little effort. This allows a wide range of IDF scenarios to be evaluated, and then compared to climate models as they become available.

Note: Calibration and validation data for the SHC HFP are located  here .

Hydrological models are typically first calibrated and then validated. Both of these steps involve comparing model outputs to observations. Calibration is done with a subset of the observations; validation is then done with a different subset of the observations. Restated, the model is dialed in with one set of data, and then it is tested with another set of data.

In simple terms,  the calibration of hydrological models involves adjusting parameters to more accurately reflect physical conditions.   SHC HFP was calibrated against hourly flow data from the USGS 01472157 station at Hoffecker Road in the French Creek for the year 2018 (figure below). 4 parameters were mildly adjusted for calibration. Channel roughness is decreased to align hourly peaks and curve number increased to align peak volume. Alpha baseflow is obtained from analysis at USGS 01472157. A google sheet the calibration data and the list of parameters adjusted is  here .

For 2023, the SHC HFP has only been calibrated for flow and with minimal adjustments to parameters. Going forward, there are many options to improve flow model performance by adjusting parameters to more closely reflect actual physical conditions. For example, in the SHC there are many areas of forest with canopy heights above 100 feet. Canopy heights even exceed 150 feet in a few areas. Adjusting model parameters to reflect the increased water use of these taller forests is expected to improve model performance.

 Validation is the process where simulations produced by the calibrated model are compared to observed data using a statistical analysis . The SHC HFP was validated against continuous flow data from the USGS 01472157 (French Creek) and USGS 01473169 (Valley Creek), as well as instantaneous data from stream flow measurements (discharge) carried out in the stream using flow meters (also by USGS). The SHC HFM is also being validated against the many instantaneous flow measurements made by USGS at locations throughout the SHC. To view the validation results, a separate story map is set up  here .

SWAT requires two kinds of input files. Inputs for soils, land cover and terrain are fixed and do not vary during a simulation. Inputs for weather are time series that do change during the simulation as the model steps forward in time.

The SWAT model performance is highly dependent upon the quality of the weather inputs. Precipitation data collected by Next Generation Weather Radar (NEXRAD). As shown in the figure below, NEXRAD collects precipitation data at good resolution.

 NEXRAD  collects precipitation data at 5 minute intervals with radar stations located across the US. This data is quality controlled and then aggregated at the national level to create the NCEP/EMC 4KM Gridded Data Stage IV Data. Precipitation is available at 1 hour, 6 hour and 24 hour intervals from 2002 forward. Updates to the data occur monthly. Other weather data inputs--Temperature, Relative Humidity, Wind Velocity and Solar Radiation--are currently obtained from  gridMET .

Land cover, soils and terrain inputs are developed from the National Land Cover Dataset, Soils Survey Geographic Database, and 3 meter digital elevation model (DEM).

The SHC HFP was developed primarily as tool for investigating existing stormwater issues, developing solutions, and predicting climate change impacts.

What are the issues? Our streams are not as healthy as they could be and face new threats going forward in the form of additional development and climate change. The primary cause of this is stormwater and sediments. These have serious negative impacts on the health of our local streams in northeast Chester County. We see the impacts as flooding during storms, in altered stream channels, scoured stream channels, eroding stream banks and sediments clogging the streams. These watershed issues can be traced to stormwater runoff, non-point source pollutants in that runoff, sediments generated by that runoff, bacteria growing in the sediments, and the scouring of stream beds by that runoff during storms.

• Mapping of stormwater runoff. We have hourly precipitation data from the NEXRAD system which allows hour by hour simulation of actual stormwater run off events. These are the same events that are being recorded by the instream sensors. We can quantitatively follow the progress of water from initial radar observations, to runoff, and to stream flow observations. There is an excellent opportunity to integrate the EnviroDIY stations by placing them close to the sources of runoff and comparing flow observations with flow simulations. The product is a high resolution mapping of actual stormwater runoff which can be used for stake holder engagement and restoration scenario development. With turbidity sensors we can also verify assumptions about sediments in runoff.
•   Legacy Sediments   (LS) erosion monitoring. For a given set of LS sites, we can measure bank position at intervals based on peak flow events and work towards developing a relationship between peak flows and erosion rates applicable to local LS sites.
• Producing histograms of stream flow for each reach and then mapping these to provide a watershed-wide view of which streams are relatively more prone to stormwater flows. This mapping will provide information on which stream reaches are experiencing the highest relative flows and would be expected to have the highest erosion rates to inform field surveys.
• Providing flow data for previous grab samples where stream flow was not measured.
• Climate change projections, including flood modeling.
• Temperature modeling.