This data set includes 5-minute time series runoff and precipitation data of neighborhood catchments with a variety of stormwater control measures, and definition of individual precipitation-runoff events and associated runoff metrics. Also included are geospatial data that delineates the neighborhood catchments with their land use/land cover and stormwater infrastructure. This dataset is associated with the following publication: Woznicki, S., K. Hondula, and T. Jarnagin. Effectiveness of landscape‐based green infrastructure for stormwater management in suburban catchments. Hydrological Processes. John Wiley & Sons, Ltd., Indianapolis, IN, USA, 32(15): 2346-2361, (2018).

These are quality-assured time series datasets from weather stations and runoff volume monitoring infrastructure, Cleveland OH. This dataset is associated with the following publication: Shuster, W., and R. Darner. Hydrologic Performance of Retrofit Rain Gardens in a Residential Neighborhood (Cleveland Ohio USA) with a Focus on Monitoring Methods. U.S. Environmental Protection Agency, Washington, DC, USA, 2018.

Summary of rain event date, rainfall depth, and volumetric water content. This dataset is associated with the following publication: Nissen, K., M. Borst, and E. Fassman-Beck. Bioretention Flow-Through Planter Performance and Design Considerations. Journal of Sustainable Water in the Built Environment. American Society of Civil Engineers (ASCE), New York, NY, USA, 12(2): 04025018, (2026).

Green infrastructure is designed to capture and infiltrate or filter stormwater runoff through natural systems. This dataset is used in combination with precipitation numbers to update the stormwater dashboard (in progress) and Sustainable City pLAn. It is refreshed as new projects are created.

This dataset describes streamflow and precipitation event statistics for four watersheds located in Clarksburg, Maryland, USA. Streamflow and precipitation events were identified from fourteen years of sub-daily (5- and 15-minute) monitoring data spanning October 1, 2004 through September 30, 2018. A 6-hour inter-event window was used to define discrete streamflow and precipitation events. The following streamflow metrics were calculated for each event area normalized peak streamflow, runoff yield, runoff ratio, streamflow duration, time to peak, and rise rate. Precipitation event metrics include total precipitation depth and precipitation event duration.

This dataset describes streamflow and precipitation event statistics for four watersheds located in Clarksburg, Maryland, USA. Streamflow and precipitation events were identified from fourteen years of sub-daily (5- and 15-minute) monitoring data spanning October 1, 2004 through September 30, 2018. A 6-hour inter-event window was used to define discrete streamflow and precipitation events. The following streamflow metrics were calculated for each event area normalized peak streamflow, runoff yield, runoff ratio, streamflow duration, time to peak, and rise rate. Precipitation event metrics include total precipitation depth and precipitation event duration.

This dataset provides the locations of Swale Drains for community users within the City of Casey, extracted from the City of Casey's Asset Management System and GIS databases.

This tabular dataset includes precipitation data, inflow and outflow data, and other associated data for a bioretention garden in Douglas County, Nebraska. At the Douglas County Health Center (DCHC) biorentention garden the general monitoring design corresponded to a water balance approach to characterize the inputs, outputs, and change in storage within the bioretention gardens. The components of the water balance that were measured or calculated were precipitation volume, stormwater inflow volume to bioretention garden, overflow volume, and evapotranspiration. The performance of the bioretention gardens was evaluated for a series of rainfall events. The start of an event was determined based on when rainfall began at the site. The end of an event was determined based on when the water level was equal to zero in the stilling well of the inflow flume or when the water level in the bioretention garden was zero, whichever occurred last. Evapotranspiration components were not used in the event-based analysis because this analysis was used to characterize the reduction in stormwater volume and peak discharges to the storm sewer system primarily during time periods of overflow, and these components take place over longer time periods. Change in storage was also excluded from the event-based analyses because time periods were selected to represent rainfall events such that the change in storage of ponded water was always zero.

This tabular dataset includes precipitation data, inflow and outflow data, and other associated data for a bioretention garden in Douglas County, Nebraska. At the Douglas County Health Center (DCHC) biorentention garden the general monitoring design corresponded to a water balance approach to characterize the inputs, outputs, and change in storage within the bioretention gardens. The components of the water balance that were measured or calculated were precipitation volume, stormwater inflow volume to bioretention garden, overflow volume, and evapotranspiration. The performance of the bioretention gardens was evaluated for a series of rainfall events. The start of an event was determined based on when rainfall began at the site. The end of an event was determined based on when the water level was equal to zero in the stilling well of the inflow flume or when the water level in the bioretention garden was zero, whichever occurred last. Evapotranspiration components were not used in the event-based analysis because this analysis was used to characterize the reduction in stormwater volume and peak discharges to the storm sewer system primarily during time periods of overflow, and these components take place over longer time periods. Change in storage was also excluded from the event-based analyses because time periods were selected to represent rainfall events such that the change in storage of ponded water was always zero.

Data are estimated stormwater values based on curve numbers (CN) values are based on hydrologic soil groups (A, B, C, and D) and four land cover types in the study area, such as, grassland, forest land, impervious area, and other open space. We apply SMPSS-TRAC to a watershed located in Hamilton County, Ohio, USA and develop five scenarios representing increasing use of GI. We test the scenarios under a 5-year rainfall intensity and set a cap of runoff for each scenario at a level that is equal to the runoff from an undeveloped status (1.03-inch runoff depth for the watershed). With the proposed SMPSS-TRAC, the watershed authority could encourage all parcel owners to install suitable GI or purchase credits from the market. This dataset is associated with the following publication: Fu, X., M. Hopton, X. Wang, H. Goddard, and H. Liu. A runoff trading system to meet watershed-level stormwater reduction goals with parcel-level green infrastructure installation. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 689: 1149-1159, (2019).