.\Stochastic Meteorology\ I. .\genpet.csv: This file contains stochastic monthly PET values for each weather station used to develop stochastic climate data in Kolars and others (2016). Column A is the weather station number, column B is the year in a stochastic simulation, column’s C through N are January through December PET values in millimeters, respectively. Simulations are stacked in order from 1 to 100 for each weather station. II. .\genprec.csv: This file contains stochastic monthly precipitation values for each weather station used to develop stochastic climate data in Kolars and others (2016). Column A is the weather station number, column B is the year in a stochastic simulation, column’s C through N are January through December precipitation values in millimeters, respectively. Simulations are stacked in order from 1 to 100 for each weather station. III. .\ grid_pet_stoch.csv: This file provides monthly stochastic PET values for each grid point used in the WBM presented in Kolars and others (2016). Column A is an unnamed index, column B, “lat”, is the latitude for a grid point, column C, “lon”, is the longitude for a grid point, column D is the year in a stochastic simulation, and columns E through P are the values of PET for January through December in millimeters, respectively. Simulations are ordered and placed on top of one another. IV. .\ grid_prec_stoch.csv: This file provides monthly stochastic precipitation values for each grid point used in the WBM presented in Kolars and others (2016). Column A is an unnamed index, column B, “lat”, is the latitude for a grid point, column C, “lon”, is the longitude for a grid point, column D is the year in a stochastic simulation, and columns E through P are the values of precipitation for January through December in millimeters, respectively. Simulations are ordered and placed on top of one another. V. .\PETMM_basinAv_stoch.csv: This file contains the Souris River Basin average PET for each month of the stochastic PET time series. Column A is an unnamed index, column B, “simnum” is the simulation number, column C, “yr”, is the year in a stochastic simulation, and columns D through O are the PET values in millimeters for January through December, respectively. VI. .\PrecipMM_basinAv_stoch.csv: This file contains the Souris River Basin average precipitation for each month of the stochastic precipitation time series. Column A is an unnamed index, column B, “simnum” is the simulation number, column C, “yr”, is the year in a stochastic simulation, and columns D through O are the precipitation values in millimeters for January through December, respectively.

i. .\File_Mapping.csv: This file relates historical reconstructed hydrology streamflow from the U.S. Army Corps of Engineers () to the appropriate stochastic streamflow file for disaggregation of streamflow. Column A is an assigned ID, column B is named “Stochastic” and is the stochastic streamflow file needed for disaggregation, column c is called “RH_Ratio_Col” and is the name of the column in the reconstructed hydrology dataset associated with a stochastic streamflow file, and column D is named “Col_Num” and is the column number in the reconstructed hydrology dataset with the name given in column C. ii. .\Original_Draw_YearDat.csv: This file contains the historical year from 1930 to 2017 with the closest total streamflow for the Souris River Basin to each year in the stochastic streamflow dataset. Column A is an index number, column B is named “V1” and is the year in a simulation, column C is called “V2” and is the stochastic simulation number, column D is an integer that can be related to historical years by adding 1929, and column D is named “year” and is the historical year with the closest total Souris River Basin streamflow volume to the associated year in the stochastic traces. iii. .\revdrawyr.csv: This file is setup the same way that .\Original_Draw_YearDat.csv was except that, when a year had over 400 occurrences, it was randomly replaced with one of the 20 other closest years. The replacement process was completed until there were less than 400 occurrences of each reconstructed hydrology year associated with stochastic simulation years. Column A is an index number, column B is named “V1” and is the year in a simulation, column C is called “V2” and is the stochastic simulation number, column D is called “V3” and is the historical year who’s streamflow ratios will be multiplied by stochastic streamflow, and column E is called “Stoch_yr” and is the total of 2999 and the year in column B. iv. .\RH_1930_2017.csv: This file contains the daily streamflow from the U.S. Army Corps of Engineers (2020), reconstructed hydrology for the Souris River Basin for the period of 1930 to 2017. Column A is the date and columns B through AA are the daily streamflow in cubic feet per second. v. .\rhmoflow_1930Present.csv: This file was created based on .\RH_1930_2017.csv and provides streamflow for each site in cubic meters for a given month. Column A is an unnamed index column, column B is historical year, column C is the historical month associated with the historical year, column D provides a day equal to 1 but does not have particular significance and columns E through AD are monthly streamflow volume for each site location. vi. .\Stoch_Annual_TotVol_CubicDecameters.csv: This file contains the total volume of streamflow for each of the 26 sites for each month in the stochastic streamflow time timeseries and provides a total streamflow volume divided by 100,000 on a monthly basis for the entire Souris River Basin. Column A is unnamed and contains an index number, column B is month and is named “V1”, column C is the year in a simulation, column D is the simulation number, columns E (V4 through V29) through AD are streamflow volume in cubic meters, and column AE (V30) is total Souris River Basin monthly streamflow volume in cubic decameters/1,000.

i. .\File_Mapping.csv: This file relates historical reconstructed hydrology streamflow from the U.S. Army Corps of Engineers () to the appropriate stochastic streamflow file for disaggregation of streamflow. Column A is an assigned ID, column B is named “Stochastic” and is the stochastic streamflow file needed for disaggregation, column c is called “RH_Ratio_Col” and is the name of the column in the reconstructed hydrology dataset associated with a stochastic streamflow file, and column D is named “Col_Num” and is the column number in the reconstructed hydrology dataset with the name given in column C. ii. .\Original_Draw_YearDat.csv: This file contains the historical year from 1930 to 2017 with the closest total streamflow for the Souris River Basin to each year in the stochastic streamflow dataset. Column A is an index number, column B is named “V1” and is the year in a simulation, column C is called “V2” and is the stochastic simulation number, column D is an integer that can be related to historical years by adding 1929, and column D is named “year” and is the historical year with the closest total Souris River Basin streamflow volume to the associated year in the stochastic traces. iii. .\revdrawyr.csv: This file is setup the same way that .\Original_Draw_YearDat.csv was except that, when a year had over 400 occurrences, it was randomly replaced with one of the 20 other closest years. The replacement process was completed until there were less than 400 occurrences of each reconstructed hydrology year associated with stochastic simulation years. Column A is an index number, column B is named “V1” and is the year in a simulation, column C is called “V2” and is the stochastic simulation number, column D is called “V3” and is the historical year who’s streamflow ratios will be multiplied by stochastic streamflow, and column E is called “Stoch_yr” and is the total of 2999 and the year in column B. iv. .\RH_1930_2017.csv: This file contains the daily streamflow from the U.S. Army Corps of Engineers (2020), reconstructed hydrology for the Souris River Basin for the period of 1930 to 2017. Column A is the date and columns B through AA are the daily streamflow in cubic feet per second. v. .\rhmoflow_1930Present.csv: This file was created based on .\RH_1930_2017.csv and provides streamflow for each site in cubic meters for a given month. Column A is an unnamed index column, column B is historical year, column C is the historical month associated with the historical year, column D provides a day equal to 1 but does not have particular significance and columns E through AD are monthly streamflow volume for each site location. vi. .\Stoch_Annual_TotVol_CubicDecameters.csv: This file contains the total volume of streamflow for each of the 26 sites for each month in the stochastic streamflow time timeseries and provides a total streamflow volume divided by 100,000 on a monthly basis for the entire Souris River Basin. Column A is unnamed and contains an index number, column B is month and is named “V1”, column C is the year in a simulation, column D is the simulation number, columns E (V4 through V29) through AD are streamflow volume in cubic meters, and column AE (V30) is total Souris River Basin monthly streamflow volume in cubic decameters/1,000.

There are 100 traces in the simulation. This metadata file is only associated with the first trace (Trace_1), although a similar naming convention is used in each trace folder. .\Reservoir SPEI Results\: This directory contains a folder for each trace (simulation) and each trace folder contains stochastic precipitation, stochastic potential evapotranspiration, stochastic temperature, and standardized precipitation evapotranspiration index (SPEI) values for Grant Devine Reservoir, Rafferty Reservoir, Lake Darling Reservoir, and Boundary Reservoir (a replicate of Rafferty Reservoir). All data are provided with a monthly time step. SPEI is calculated for a number of previous months and for each reservoir a calculation of SPEI was done with a 3-month, 6-month, and 12-month lag. In addition, the average of the 3-month and 12-month lag was taken, the October value of the average SPEI was assumed to be equal to the SPEI on November 1 of each year and subset to one value per year in the stochastic streamflow dataset. Potential evapotranspiration (PET) and precipitation have units of millimeters.

There are 100 traces in the simulation. This metadata file is only associated with the first trace (Trace_1), although a similar naming convention is used in each trace folder. .\Reservoir SPEI Results\: This directory contains a folder for each trace (simulation) and each trace folder contains stochastic precipitation, stochastic potential evapotranspiration, stochastic temperature, and standardized precipitation evapotranspiration index (SPEI) values for Grant Devine Reservoir, Rafferty Reservoir, Lake Darling Reservoir, and Boundary Reservoir (a replicate of Rafferty Reservoir). All data are provided with a monthly time step. SPEI is calculated for a number of previous months and for each reservoir a calculation of SPEI was done with a 3-month, 6-month, and 12-month lag. In addition, the average of the 3-month and 12-month lag was taken, the October value of the average SPEI was assumed to be equal to the SPEI on November 1 of each year and subset to one value per year in the stochastic streamflow dataset. Potential evapotranspiration (PET) and precipitation have units of millimeters.

This directory contains file for each of the 26 site locations required for simulation of streamflow in HEC-ResSim. Each file contains the 100, 100-year streamflow time series in monthly streamflow volume format. Streamflow volume is presented in cubic meters. In column A, there is a row number, column B is the month of the stochastic streamflow volume, column C is the year in the stochastic timeseries, column D is named “simnum” and is the simulation number, and column E is named “monthly_tot” and is the total streamflow volume for the given month, year, and simulation number in cubic meters.

This directory contains file for each of the 26 site locations required for simulation of streamflow in HEC-ResSim. Each file contains the 100, 100-year streamflow time series in monthly streamflow volume format. Streamflow volume is presented in cubic meters. In column A, there is a row number, column B is the month of the stochastic streamflow volume, column C is the year in the stochastic timeseries, column D is named “simnum” and is the simulation number, and column E is named “monthly_tot” and is the total streamflow volume for the given month, year, and simulation number in cubic meters.

This folder contains streamflow timeseries in cubic meters per second for each trace time series at each of the 26 site locations. In column A, there is a row number, column B contains “flow” and is streamflow in cubic meters per second, column C is the month that the streamflow occurs in the stochastic streamflow time series, column D is the year in a given stochastic time series, and column E is “simnum” which is the simulation number. The streamflow is ordered for each year in a timeseries and have 3 streamflow values for each month. The 3 streamflow for each month refer to the first, second, and third 10-day period in a month regardless of whether the month does or does not contain 30-days.

The datasets are gridded daily precipitation and minimum and maximum temperature for a period of 64 years for warming scenarios of 0 to 8 degrees Celsius, by 0.5 degrees for the Nashua River watershed in Massachusetts. The data are output from a Stochastic Weather Generator developed at Cornell University (Steinschneider and Najibi, 2022) and includes 100 ensembles of each warming scenario. The data files are in NetCDF format (https://www.unidata.ucar.edu/software/netcdf/). Steinschneider, S., and Najibi, N., 2022, A weather-regime based stochastic weather generator for climate scenario development across Massachusetts—Technical documentation: Ithaca, N.Y., Cornell University, [Department of] Biological and Environmental Engineering report, 47 p., accessed February 16, 2023, at https://eea-nescaum-dataservices-assets-prd.s3.amazonaws.com/cms/GUIDELINES/FinalTechnicalDocumentation_WGEN_20220405.pdf

The datasets are gridded daily precipitation and minimum and maximum temperature for a period of 64 years for warming scenarios of 0 to 8 degrees Celsius, by 0.5 degrees for the Nashua River watershed in Massachusetts. The data are output from a Stochastic Weather Generator developed at Cornell University (Steinschneider and Najibi, 2022) and includes 100 ensembles of each warming scenario. The data files are in NetCDF format (https://www.unidata.ucar.edu/software/netcdf/). Steinschneider, S., and Najibi, N., 2022, A weather-regime based stochastic weather generator for climate scenario development across Massachusetts—Technical documentation: Ithaca, N.Y., Cornell University, [Department of] Biological and Environmental Engineering report, 47 p., accessed February 16, 2023, at https://eea-nescaum-dataservices-assets-prd.s3.amazonaws.com/cms/GUIDELINES/FinalTechnicalDocumentation_WGEN_20220405.pdf