ABSTRACT:

Introductory slides presented by Ensign on 10 September 2019. Slides 2 and 3 provide links to online resources for learning Arduino, the Mayfly Data Logger, Monitor My Watershed, and Model My Watershed.

ABSTRACT:

This resource demonstrates the workflow developed to prepare downscaled GCM data for input to Model My Watershed (ModelMyWatershed.org). GCM data for the Delaware River Basin was assembled from 19 GCMs including each model's RCP4.5 and RCP8.5; this was performed by Dr. Tim Hawkins, Shippensburg University (http://www.ship.edu/geo-ess/). Downscaled precipitation data from global climate models (GCM) does not accurately retain the magnitude and frequency of individual storm events for a given location. This lack of predictive resolution of event magnitude and frequency limits realism of rainfall-runoff models used to for predicting watershed hydrology under future climate scenarios. To address this problem, Maimone et al (2019) developed a method for summarizing the statistical distribution of precipitation event magnitude and frequency that could be applied to downscaled GCM precipitation predictions. Application of the methods here to down-scaled GCM scenarios requires that the those predictions do not include an increase in the number of days of precipitation per year. Maimone et al (2019) state this requirement: "Because GCM projections for the Philadelphia region do not indicate an increase in the number of wet days per year, future increases in precipitation are the result of the existing number and distribution of wet days becoming more intense."

I developed a workflow to replicate Maimone et al's methods and provide an example of it in this Resource. There are three sections of the R Markdown document. The first section seeks to replicate the synthetic weather generator developed by Maimone et al (2019) using an example dataset. The second section applies those methods to the downscaled GCM ensemble average conditions for the Delaware River Basin provided by Dr. Hawkins. The third section develops depth-duration-frequency statistics for the 24 hour storm event relevant to the 2080-2100 predictions. To open the R Markdown document and execute the workflow yourself, find the Open With dropdown list in the upper right hand corner of this Resource and select CUAHSI JupyterHub.

The first section uses an example precipitation dataset from the Philadelphia Airport for the period 01 January 1995 through 31 December 2013. The data were downloaded from NOAA's Climate Data Online Search portal: https://www.ncdc.noaa.gov/cdo-web/search.

The downloaded data and metadata for this NOAA Climate Data are available on Hydroshare here: http://www.hydroshare.org/resource/60058ceda8334e68be141516c5b8de3f.
Additional data on precipitation frequency at the Philadelphia Airport was downloaded from the NOAA Hydrometeorological Design Studies Center: https://hdsc.nws.noaa.gov/hdsc/pfds/index.html.

An example of working with this type of NOAA Climate Data is provided on the NEON website here:
https://www.neonscience.org/da-viz-coop-precip-data-R.

References:
Maimone, M., S. Malter, J. Rockwell, and V. Raj. 2019. Transforming Global Climate Model Precipitation Output for Use in Urban Stormwater Applications. Journal of Water Resources Planning and Management 145:04019021.

ABSTRACT:

Model My Watershed's Site Storm Model allows users to specify the amount of precipitation to be applied in the model. Typically, a user will focus on modeling a quantity of rainfall that corresponds with an annual exceedance probability. For example, a user may be interested in modeling the 24 hour precipitation that has a 50% probability of occurring in any given year (meaning that the amount of precipitation recurs only every 2 years) or a 2% probability of occurring in any given year (the amount of precipitation recurs only every 50 years). Sometimes these precipitation exceedance probabilities are referred to as the “2 year storm” or the “50 year storm”, respectively. This Resource shares the results of an analysis that can guide use of the Site Storm Model, particularly for areas of interest in the mid-Atlantic region of PA, NJ, and NY.

The HydroShare Resource "Modeling Future Climate for Model My Watershed" (Ensign, S. 2020. Modeling Future Climate for Model My Watershed, HydroShare, https://doi.org/10.4211/hs.60058ceda8334e68be141516c5b8de3f) demonstrates an algorithm for generating sequences of stochastically-selected precipitation events and inter-event durations that replicate the observed frequency and magnitude of annual weather patterns at a location. This stochastic weather-generating algorithm was used to predict a 20 year time series of daily precipitation using the predicted increase in precipitation from down-scaled global climate models. These 20 year time series predict 2080-2100 weather at eleven weather observing stations which are used by Model My Watershed's Watershed Multi-Year Model for areas of interest within the Delaware River Basin.

The depth-duration-frequency curves presented in this Resource were derived from this stochastic weather-generating algorithm at the eleven weather observing stations described above. For each weather observing station, ten iterations of 20 year stochastic weather were generated for each of the Representative Concentration Pathways (RCP) 4.5 and 8.5. From each of sets of 10 time series, the series with the lowest and highest total precipitation over the 20 year period were selected for further analysis. Following the methods outline in Maimone et al. 2019 and AlHassoun 2011, the frequency factors for a Gumbel type I extreme value distribution were used to generate depth-duration-frequency predictions at 2, 5, 10, 25, 50, 100, 200, 500, and 1000 year intervals for the low precipitation and high precipitation series. Because the RCP 4.5 and 8.5 stochastic precipitation time series were generated independently, the RCP 8.5 predictions were not a simple increase over the RCP 4.5 predictions.

For comparison with these predictions of future weather conditions at the end of the century, the historic precipitation frequency at the 11 locations of interest was downloaded from the NOAA Hydrometeorological Design Studies Center (https://hdsc.nws.noaa.gov/hdsc/pfds/index.html). The data requested included precipitation depth, metric units, Annual Maximum Series, the 24 hour estimates and upper and lower 90% confidence intervals of Annual Exceedence Probabilities (1/year) from 1/2 to 1/1000. These data are plotted along with the future projections.

There are two files in this resource for each weather observation location used by Model My Watershed's Watershed Multi-Year Model for areas of interest inside the Delaware River Basin. There is a table of exceedance probabilities listing precipitation in millimeters and a corresponding figure.

ABSTRACT:

How much do rivers contribute to the accretion balance of tidal wetlands facing sea level rise? This resource contains data answering this question for over 4,000 rivers in the 48 contiguous US states.

This Resource contains data generated as part of the project "Resolving sediment connectivity between rivers and estuaries by tracking particles with their microbial genetic signature". This project was funded from 01 May 2021 through 30 May 2024 by the National Science Foundation Award Number 2049073, Geosciences Directorate, Earth Sciences Division, Geomorphology and Land Use Dynamics Program.

ABSTRACT:

This is a repository of data and analysis methods developed in a comparison of water monitoring data reported on Monitor My Watershed and USGS Water Data. The analysis is summarized in a post on EnviroDIY.org: https://www.envirodiy.org/how-do-envirodiy-monitoring-stations-compare-with-usgs-stations/.

ABSTRACT:

This resource contains the data and R scripts necessary for replicating the results and graphics presented in the study "Advancing Freshwater Science with Sensor Data Collected by Community Scientists", intended for publication in Frontiers in Ecology and the Environment. The study authors are Diana Oviedo-Vargas, Marc Peipoch, Scott Ensign, David Bressler, David Arscott, and John Jackson.

ABSTRACT:

Under the requirements of the Clean Water Act, every state in the US must report to the EPA every two years on the designated uses for its waterways and whether those designated uses are being attained. These reports are summarized in the EPA ATTAINS database, and those data are publicly available through an application programming interface provided by EPA. This Hydroshare resource provides code for extracting these designated use attainment data, specifically those designated uses that are ecologically related, for two time periods: 2008 and 2022. The scripts summarize the the total number of river miles for each state and the US, collectively, that are attaining, not attaining, not assessed, or had insufficient data to report on.