Computing a Full Analysis with fasstr

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fasstr, the Flow Analysis Summary Statistics Tool for R, is a set of R functions to tidy, summarize, analyze, trend, and visualize streamflow data. This package summarizes continuous daily mean streamflow data into various daily, monthly, annual, and long-term statistics, completes trending and frequency analyses, with outputs in both table and plot formats.

This vignette documents the usage of the compute_full_analysis() and write_full_analysis() functions in fasstr. This vignette is a high-level adjunct to the details found in the function documentation (see ?compute_full_analysis and ?write_full_analysis). You’ll learn what arguments to provide to the function to customize your analyses, what analyses are computed, and what outputs are produced.

Overview

The full analysis functions produce a suite of tables and plots from the various fasstr functions. There are seven groups of analyses (see below) which are stored in lists in the created object for the compute_ function and written into an Excel workbook (and accompanying image files) for the write_ function. All of the data selection (data or station_number arguments), data filtering, water year selection, missing dates options, basin area, and zyp trending arguments are used in this function to customize your data and analysis.

The outputs are grouped into the following categories:

Screening
Long-term
Annual
Monthly
Daily
Annual Trends
Low-flow Frequencies

While by default the function will create all outputs from all categories, there is the option to select which groups are analyzed using the analyses argument. By default the analyses argument is 1:7, with numbers 1 through 7 representing each of the categories as listed above. So analyses = 1 would output only the screening outputs; while analyses = c(1,3,5:7) would output all but the long-term and monthly analyses.

Functions and Data Inputs

`compute_full_analysis()` Object List

When using this function all of the objects will be saved within a list with a first level of lists with each of the categories as listed above (ex. $Screening or $Annual). Within each of those lists are the outputted objects, or another list of objects (ex. $Screening$Flow_Screening or $Annual$Annual_Flow_Timing). Use subsetting techniques to extract an individual tibble or plot.

The following is an example of how to run the function and then how extract individual objects from the list:

mission_creek <- compute_full_analysis(station_number = "08NM116",
                                       start_year = 1981,
                                       end_year = 2000)

screening_plot <- mission_creek$Screening$Flow_Screening_Plot

daily_stats <- mission_creek$Daily$Daily_Summary_Stats

daily_stats_with_1985 <- mission_creek$Daily$Daily_Summary_Stats_with_Years$`1985_Daily_Statistics`

trends_results <- mission_creek$Trending$Annual_Trends_Results

`write_full_analysis()` Excel and Image Files

The writing function provides a option to directly save all results onto your computer, thereby allowing the user to explore the outputs in Excel and image file formats. You will be required to provide the name of a the Excel file to create using the file_name argument. If the analyses in groups 5 and/or 6 are selected than a folder with the same name will be created to store a number of plots that are not suitable for the Excel file. By default it will save those plots in “pdf” format, but can be altered using the plot_filetype arguments, if necessary. Within the Excel workbook each of the tables and plots are saved within specific worksheets. The first worksheet in all outputs contain an overview of the analysis to know which arguments and options were used. The second worksheet contains the data provided to the function (the data frame or the data from HYDAT). The last worksheet (after all the analysis sheets) contain a table of fasstr functions that can replicate each individual analysis output for further customization (these functions are also contained within the comments of the cells with table and plot titles).

The following is an example of how to save all analyses to your computer:

write_full_analysis(station_number = "08NM116",
                    start_year = 1981,
                    end_year = 2000,
                    file_name = "Mission Creek")

Usage, Options, and outputs

The following is a table that lists of all objects and files (if write_to_dir = TRUE) created using the compute_full_analysis() function, with their respective section list / folder, type of object, and the function use to produce the object:

Analyses	Object	Type	Function
1 - Screening	Daily_Flows	Table	`add_date_variables() %>% add_rolling_means() %>% add_basin_area()`
1 - Screening	Daily_Flows_Plot	Plot	`plot_flow_data()`
1 - Screening	Flow_Screening	Table	`screen_flow_data()`
1 - Screening	Flow_Screening_Plot	Plot	`plot_data_screening()`
1 - Screening	Missing_Dates_Plot	Plot	`plot_missing_dates()`
2 - Longterm	Longterm_Monthly_Summary_Stats_Percentiles	Table	`calc_longterm_monthly_stats()`
2 - Longterm	Longterm_Monthly_Summary_Stats_Plot	Plot	`plot_longterm_monthly_stats()`
2 - Longterm	Longterm_Daily_Summary_Stats_Percentiles	Table	`calc_longterm_daily_stats()`
2 - Longterm	Longterm_Monthly_Means_Plot	Plot	`plot_monthly_means()`
2 - Longterm	Longterm_Daily_Summary_Stats_Plot	Plot	`plot_longterm_daily_stats()`
2 - Longterm	Flow_Duration_Curves	Plot	`plot_flow_duration()`
3 - Annual	Annual_Summary_Stats	Table	`calc_annual_stats()`
3 - Annual	Annual_Summary_Stats_Plot	Plot	`plot_annual_stats()`
3 - Annual	Annual_Cumul_Volume_Stats_m3	Table	`calc_annual_cumulative_stats(include_seasons=TRUE)`
3 - Annual	Annual_Cumul_Volume_Stats_m3_Plot	Multiple Plots	`plot_annual_cumulative_stats(include_seasons=TRUE)`
3 - Annual	Annual_Cumul_Yield_Stats_mm	Table	`calc_annual_cumulative_stats(use_yield=TRUE, include_seasons=TRUE)`
3 - Annual	Annual_Cumul_Yield_Stats_mm_Plot	Multiple Plots	`plot_annual_cumulative_stats(use_yield=TRUE)`
3 - Annual	Annual_Flow_Timing	Table	`calc_annual_flow_timing()`
3 - Annual	Annual_Flow_Timing_Plot	Plot	`plot_annual_flow_timing()`
3 - Annual	Annual_Normal_Days	Table	`calc_annual_normal_days()`
3 - Annual	Annual_Normal_Days_Plot	Plot	`plot_annual_normal_days()`
3 - Annual	Annual_Low_Flows	Table	`calc_annual_lowflows()`
3 - Annual	Annual_Low_Flows_Plot	Multiple Plots	`plot_annual_lowflows()`
3 - Annual	Annual_Means	Plot	`plot_annual_means()`
4 - Monthly	Monthly_Summary_Stats	Table	`calc_monthly_stats()`
4 - Monthly	Monthly_Summary_Stats_Plot	Multiple Plots	`plot_monthly_stats()`
4 - Monthly	Monthly_Total_Cumul_Volume_m3	Table	`calc_monthly_cumulative_stats()`
4 - Monthly	Monthly_Total_Cumul_Volume_m3_Plot	Plot	`plot_monthly_cumulative_stats()`
4 - Monthly	Monthly_Total_Cumul_Yield_mm	Table	`calc_monthly_cumulative_stats(use_yield=TRUE)`
4 - Monthly	Monthly_Total_Cumul_Yield_mm_Plot	Plot	`plot_monthly_cumulative_stats(use_yield=TRUE)`
5 - Daily	Daily_Summary_Stats	Table	`calc_daily_stats()`
5 - Daily	Daily_Summary_Stats_Plot	Plot	`plot_daily_stats()`
5 - Daily	Daily_Summary_Stats_with_Years	Multiple Plots	`plot_daily_stats(add_year)`
5 - Daily	Daily_Total_Cumul_Volume_m3	Table	`calc_daily_cumulative_stats()`
5 - Daily	Daily_Total_Cumul_Volume_m3_Plot	Plot	`plot_daily_cumulative_stats()`
5 - Daily	Daily_Total_Cumul_Volume_m3_with_Years	Multiple Plots	`plot_daily_cumulative_stats(add_year)`
5 - Daily	Daily_Total_Cumul_Yield_mm	Table	`calc_daily_cumulative_stats(use_yield=TRUE)`
5 - Daily	Daily_Total_Cumul_Yield_mm_Plot	Plot	`plot_daily_cumulative_stats(use_yield=TRUE)`
5 - Daily	Daily_Total_Cumul_Yield_mm_with_Years	Multiple Plots	`plot_daily_cumulative_stats(use_yield=TRUE, add_year)`
6 - Trending	Annual_Trends_Data	Table	`compute_annual_trends()`
6 - Trending	Annual_Trends_Results	Table	`compute_annual_trends()`
6 - Trending	Annual_Trends_Results_Plots	Multiple Plots	`compute_annual_trends(include_plots=TRUE)`
7 - Lowflow Frequencies	Freq_Analysis_Data (lowflows)	Table	`compute_annual_frequencies()`
7 - Lowflow Frequencies	Freq_Plot_Data	Table	`compute_annual_frequencies()`
7 - Lowflow Frequencies	Freq_Plot	Plot	`compute_annual_frequencies()`
7 - Lowflow Frequencies	Freq_Fitted_Quantiles	Table	`compute_annual_frequencies()`

Objects Examples

The following are examples of the outputs from the full analysis functions. Each plot is presented and only the first six rows from each table.

1. Screening

Daily_Flows

Daily Flows

  STATION_NUMBER       Date Parameter Value Symbol CalendarYear Month MonthName
1        08NM116 1990-01-01      Flow  1.47   <NA>         1990     1       Jan
2        08NM116 1990-01-02      Flow  1.35   <NA>         1990     1       Jan
3        08NM116 1990-01-03      Flow  1.07   <NA>         1990     1       Jan
4        08NM116 1990-01-04      Flow  1.41   <NA>         1990     1       Jan
5        08NM116 1990-01-05      Flow  1.53   <NA>         1990     1       Jan
6        08NM116 1990-01-06      Flow  1.47   <NA>         1990     1       Jan
  WaterYear DayofYear    Q3Day    Q7Day   Q30Day Basin_Area_sqkm
1      1990         1 1.440000 1.447143 1.617733             795
2      1990         2 1.413333 1.428571 1.587400             795
3      1990         3 1.296667 1.371429 1.552067             795
4      1990         4 1.276667 1.367143 1.528733             795
5      1990         5 1.336667 1.382857 1.513067             795
6      1990         6 1.470000 1.388571 1.504400             795

Flow_Screening

  STATION_NUMBER Year n_days n_Q n_missing_Q A_Symbol B_Symbol E_Symbol
1        08NM116 1990    365 365           0        2       40        7
2        08NM116 1991    365 365           0        0       90        0
3        08NM116 1992    366 366           0        1       47        0
4        08NM116 1993    365 365           0        2      103        0
5        08NM116 1994    365 365           0        1      105       17
6        08NM116 1995    365 365           0       21       94       30
  No_Symbol Minimum Maximum     Mean Median StandardDeviation Jan_missing_Q
1       316   0.560    69.9 9.209290   1.98         14.984546             0
2       275   0.439    56.7 7.472605   1.74         11.318678             0
3       318   0.436    29.8 3.256295   1.19          4.607470             0
4       260   0.270    58.0 6.927921   2.57         10.128417             0
5       242   0.430    39.7 6.030022   1.26          8.978709             0
6       220   0.556    33.1 5.647830   2.26          7.570999             0
  Feb_missing_Q Mar_missing_Q Apr_missing_Q May_missing_Q Jun_missing_Q
1             0             0             0             0             0
2             0             0             0             0             0
3             0             0             0             0             0
4             0             0             0             0             0
5             0             0             0             0             0
6             0             0             0             0             0
  Jul_missing_Q Aug_missing_Q Sep_missing_Q Oct_missing_Q Nov_missing_Q
1             0             0             0             0             0
2             0             0             0             0             0
3             0             0             0             0             0
4             0             0             0             0             0
5             0             0             0             0             0
6             0             0             0             0             0
  Dec_missing_Q
1             0
2             0
3             0
4             0
5             0
6             0

Data_screening

Missing_Dates

2. Long-term

Long-term_Monthly_Statistics_and_Percentiles

  STATION_NUMBER Statistic       Jan       Feb       Mar       Apr      May
1        08NM116      Mean 1.0534005 1.1084117 1.9882231 10.731858 25.89132
2        08NM116    Median 1.0744194 0.9209366 1.7916613 11.245667 24.50806
3        08NM116   Maximum 1.6035484 2.1444827 3.5261290 20.200000 40.98710
4        08NM116   Minimum 0.6063226 0.6213929 0.9576129  4.085967 14.55032
5        08NM116        P5 0.6539065 0.6351821 1.0254758  5.288102 17.05460
6        08NM116       P10 0.6972903 0.6518679 1.1000710  6.305467 19.41094
        Jun       Jul      Aug       Sep       Oct       Nov       Dec
1 23.382545  7.702008 2.482245 2.2215944 2.1161156 2.2487500 1.4836962
2 22.601333  6.890484 2.391210 1.7960167 2.0062903 2.1184500 1.4615323
3 48.640000 17.443871 5.066452 4.5450000 5.2532258 4.6753333 2.7570968
4  4.954200  2.410290 1.138516 0.8591667 0.9684193 0.6556000 0.6930323
5  8.173973  2.682966 1.187927 1.0939983 0.9847774 0.7024600 0.6946113
6 10.972533  2.917523 1.244784 1.2898933 1.0045774 0.7704233 0.6959419
     Annual
1  6.881206
2  6.740340
3 11.134121
4  3.256295
5  4.010968
6  4.719439

Long-term_Monthly_Statistics

Long-term_Daily_Statistics_and_Percentiles

  STATION_NUMBER Statistic      Jan      Feb      Mar      Apr      May
1        08NM116      Mean 1.053401 1.110018 1.988223 10.73186 25.89132
2        08NM116    Median 1.005000 0.977000 1.560000  8.38500 24.30000
3        08NM116   Maximum 1.900000 2.820000 9.860000 37.90000 74.40000
4        08NM116   Minimum 0.445000 0.270000 0.400000  0.80200  7.41000
5        08NM116        P1 0.493780 0.301900 0.471300  0.90395  8.31010
6        08NM116        P2 0.542520 0.318080 0.650000  0.99508  9.18520
       Jun       Jul       Aug       Sep       Oct      Nov      Dec Long-term
1 23.38254  7.702008  2.482245  2.221594  2.116116  2.24875 1.483696  6.880568
2 20.10000  5.005000  1.935000  1.725000  1.600000  1.79000 1.300000  2.130000
3 84.50000 50.200001 12.200000 13.600000 10.600000 11.70000 7.300000 84.500000
4  0.45000  0.537000  0.522000  0.490000  0.455000  0.27400 0.440000  0.270000
5  0.77101  0.665550  0.648970  0.578210  0.513780  0.41770 0.460000  0.479100
6  1.85380  0.733000  0.663680  0.628000  0.634000  0.44934 0.472100  0.560000

Long-term_Daily_Statistics

Flow_Duration

3. Annual

Annual_Cumulative_Volume

  STATION_NUMBER Year Total_Volume_m3 Jan-Jun_Volume_m3 Jul-Dec_Volume_m3
1        08NM116 1990       290424183         230483751          59940432
2        08NM116 1991       235656087         196640352          39015734
3        08NM116 1992       102971866          78907565          24064301
4        08NM116 1993       218478903         146492323          71986580
5        08NM116 1994       190162772         169489066          20673706
6        08NM116 1995       178109971         134680061          43429910
  Jan-Mar_Volume_m3 Apr-Jun_Volume_m3 Jul-Sep_Volume_m3 Oct-Dec_Volume_m3
1           9787910         220695841          44364672          15575760
2          11722752         184917600          32558198           6457536
3          10838534          68069031          16926278           7138022
4           6043075         140449248          55045440          16941139
5          15275434         154213632          14264122           6409584
6           8210333         126469728          19188662          24241248

Annual_Cumulative_Yield

  STATION_NUMBER Year Total_Yield_mm Jan-Jun_Yield_mm Jul-Dec_Yield_mm
1        08NM116 1990       365.3134         289.9167         75.39677
2        08NM116 1991       296.4228         247.3464         49.07640
3        08NM116 1992       129.5244          99.2548         30.26956
4        08NM116 1993       274.8162         184.2671         90.54916
5        08NM116 1994       239.1985         213.1938         26.00466
6        08NM116 1995       224.0377         169.4089         54.62882
  Jan-Mar_Yield_mm Apr-Jun_Yield_mm Jul-Sep_Yield_mm Oct-Dec_Yield_mm
1        12.311837        277.60483         55.80462        19.592151
2        14.745600        232.60076         40.95371         8.122687
3        13.633377         85.62142         21.29092         8.978645
4         7.601352        176.66572         69.23955        21.309609
5        19.214382        193.97941         17.94229         8.062370
6        10.327463        159.08142         24.13668        30.492136

Annual_Normal_Days

  STATION_NUMBER Year Normal_Days Below_Normal_Days Above_Normal_Days
1        08NM116 1990         245                27                93
2        08NM116 1991         188                88                89
3        08NM116 1992         135               213                18
4        08NM116 1993         192                89                84
5        08NM116 1994         123               163                79
6        08NM116 1995         200                94                71

Annual_Normal_Days

Annual_Flow_Timing

  STATION_NUMBER Year DoY_25pct_TotalQ Date_25pct_TotalQ DoY_33.3pct_TotalQ
1        08NM116 1990              144        1990-05-24                150
2        08NM116 1991              130        1991-05-10                136
3        08NM116 1992              121        1992-04-30                127
4        08NM116 1993              134        1993-05-14                138
5        08NM116 1994              112        1994-04-22                118
6        08NM116 1995              133        1995-05-13                139
  Date_33.3pct_TotalQ DoY_50pct_TotalQ Date_50pct_TotalQ DoY_75pct_TotalQ
1          1990-05-30              160        1990-06-09              177
2          1991-05-16              147        1991-05-27              173
3          1992-05-06              142        1992-05-21              171
4          1993-05-18              149        1993-05-29              201
5          1994-04-28              132        1994-05-12              157
6          1995-05-19              153        1995-06-02              179
  Date_75pct_TotalQ
1        1990-06-26
2        1991-06-22
3        1992-06-19
4        1993-07-20
5        1994-06-06
6        1995-06-28

Annual_Flow_Timing

Annual_Low_Flows

  STATION_NUMBER Year Min_1_Day Min_1_Day_DoY Min_1_Day_Date Min_3_Day
1        08NM116 1990     0.560            12     1990-01-12 0.7000000
2        08NM116 1991     0.439           326     1991-11-22 0.4426667
3        08NM116 1992     0.436            51     1992-02-20 0.4733333
4        08NM116 1993     0.270            50     1993-02-19 0.2940000
5        08NM116 1994     0.430           326     1994-11-22 0.4500000
6        08NM116 1995     0.556           201     1995-07-20 0.6353333
  Min_3_Day_DoY Min_3_Day_Date Min_7_Day Min_7_Day_DoY Min_7_Day_Date
1            13     1990-01-13 0.9578571            51     1990-02-20
2           326     1991-11-22 0.5078571           329     1991-11-25
3           278     1992-10-04 0.5178571            21     1992-01-21
4            51     1993-02-20 0.2981429            55     1993-02-24
5           327     1994-11-23 0.4650000           349     1994-12-15
6           202     1995-07-21 0.6657143            57     1995-02-26
  Min_30_Day Min_30_Day_DoY Min_30_Day_Date
1  1.0637000             72      1990-03-13
2  0.6204000            352      1991-12-18
3  0.5775667             28      1992-01-28
4  0.4850333             72      1993-03-13
5  0.5430667            351      1994-12-17
6  0.7014667             61      1995-03-02

Annual_Low_Flows

Annual_Low_Flows_Dates

Annual_Means

Annual_Statistics

Annual_Summary_Statistics

  STATION_NUMBER Year     Mean Median Maximum Minimum    P10    P90
1        08NM116 1990 9.209290   1.98    69.9   0.560 1.0900 34.100
2        08NM116 1991 7.472605   1.74    56.7   0.439 0.7146 27.080
3        08NM116 1992 3.256295   1.19    29.8   0.436 0.6320  8.295
4        08NM116 1993 6.927921   2.57    58.0   0.270 0.6500 18.340
5        08NM116 1994 6.030022   1.26    39.7   0.430 0.6840 22.700
6        08NM116 1995 5.647830   2.26    33.1   0.556 0.7302 20.000

Annual_Total_Volume

Annual_Yield

Four_Seasons_Total_Volume

Four_Seasons_Yield

Two_Seasons_Total_Volume

Two_Seasons_Yield

4. Monthly

Monthly_Summary_Statistics

  STATION_NUMBER Year Month      Mean Median Maximum Minimum     P10   P90
1        08NM116 1990   Jan  1.220645  1.260    1.53   0.560  0.8950  1.47
2        08NM116 1990   Feb  1.075357  1.085    1.31   0.840  0.9635  1.23
3        08NM116 1990   Mar  1.462452  1.220    3.29   0.917  1.0100  1.94
4        08NM116 1990   Apr 11.435000 10.500   20.80   4.900  7.8090 17.53
5        08NM116 1990   May 24.261290 17.400   56.50  10.900 12.1000 45.80
6        08NM116 1990   Jun 48.640000 47.700   69.90  27.000 33.7400 60.75

Maximum_Monthly_Statistics

Mean_Monthly_Statistics

Median_Monthly_Statistics

Minimum_Monthly_Statistics

Monthly_Cumulative_Volumetric_Stats

  STATION_NUMBER Month      Mean    Median   Maximum  Minimum       P5
1        08NM116   Jan   2821428   2877725   4294944  1623974  1751423
2        08NM116   Feb   5530759   5172163   9166176  3478205  3535656
3        08NM116   Mar  10856016  10313222  16967232  6043075  6282291
4        08NM116   Apr  38672993  38081966  67633833 17068838 21619401
5        08NM116   May 108020297 108479779 159751008 66066279 67259506
6        08NM116   Jun 168627852 168206544 255162529 78907565 98027427
        P25       P75       P95
1   2007785   3566830   4018853
2   3765031   6934097   8693352
3   8034811  13325753  16036743
4  26824846  47787473  59668103
5  94938264 124972049 146104642
6 143539258 194588784 241589201

Monthly_Cumulative_Volume

Monthly_Cumulative_Yield_Stats

  STATION_NUMBER Month       Mean     Median    Maximum   Minimum         P5
1        08NM116   Jan   3.548966   3.619780   5.402445  2.042735   2.203048
2        08NM116   Feb   6.956930   6.505866  11.529781  4.375100   4.447367
3        08NM116   Mar  13.655366  12.972607  21.342430  7.601352   7.902253
4        08NM116   Apr  48.645274  47.901844  85.074004 21.470237  27.194215
5        08NM116   May 135.874587 136.452552 200.944665 83.102237  84.603152
6        08NM116   Jun 212.110506 211.580559 320.959156 99.254799 123.304940
         P25        P75        P95
1   2.525515   4.486578   5.055161
2   4.735888   8.722134  10.935034
3  10.106681  16.761953  20.172004
4  33.741944  60.110029  75.054218
5 119.419200 157.197546 183.779425
6 180.552525 244.765766 303.885788

Monthly_Cumulative_Yield

5. Daily

Daily_Summary_Statistics

  STATION_NUMBER   Date DayofYear     Mean Median Minimum Maximum      P5
1        08NM116 Jan-01         1 1.199917  1.080   0.611    1.85 0.65885
2        08NM116 Jan-02         2 1.158417  1.025   0.610    1.90 0.66005
3        08NM116 Jan-03         3 1.092083  0.983   0.605    1.85 0.65945
4        08NM116 Jan-04         4 1.085500  0.990   0.499    1.65 0.61340
5        08NM116 Jan-05         5 1.085500  1.030   0.596    1.65 0.65870
6        08NM116 Jan-06         6 1.101750  1.030   0.591    1.59 0.65095
     P25    P75    P95
1 0.8900 1.5275 1.8060
2 0.8725 1.4025 1.8340
3 0.8375 1.2025 1.8115
4 0.8450 1.4525 1.6170
5 0.8450 1.3800 1.5840
6 0.8275 1.4175 1.5680

Daily_Statistics

Daily_Statistics_with_Years (a folder with a plot for each year)

Daily_Cumulative_Volume

  STATION_NUMBER   Date DayofYear     Mean Median  Minimum Maximum        P5
1        08NM116 Jan-01         1 103672.8  93312  52790.4  159840  56924.64
2        08NM116 Jan-02         2 203760.0 181872 105494.4  324000 113952.96
3        08NM116 Jan-03         3 298116.0 272160 157766.4  483840 170929.44
4        08NM116 Jan-04         4 391903.2 364608 200880.0  626400 223927.20
5        08NM116 Jan-05         5 485690.4 454464 252374.4  756000 280838.88
6        08NM116 Jan-06         6 580881.6 543456 303436.8  889920 337080.96
     P25      P75      P95
1  76896 131976.0 156038.4
2 152280 258768.0 314496.0
3 225288 358948.8 471009.6
4 298296 475200.0 610243.2
5 371304 609984.0 732240.0
6 442800 739584.0 858081.6

Daily_Cumulative_Volumetric_Stats

Daily_Cumulative_Volume_with_Years (a folder with a plot for each year)

Daily_Cumulative_Yield

  STATION_NUMBER   Date DayofYear      Mean    Median    Minimum   Maximum
1        08NM116 Jan-01         1 0.1304060 0.1173736 0.06640302 0.2010566
2        08NM116 Jan-02         2 0.2563019 0.2287698 0.13269736 0.4075472
3        08NM116 Jan-03         3 0.3749887 0.3423396 0.19844831 0.6086038
4        08NM116 Jan-04         4 0.4929600 0.4586264 0.25267925 0.7879245
5        08NM116 Jan-05         5 0.6109313 0.5716528 0.31745208 0.9509434
6        08NM116 Jan-06         6 0.7306687 0.6835925 0.38168152 1.1193962
          P5        P25       P75       P95
1 0.07160332 0.09672453 0.1660076 0.1962747
2 0.14333706 0.19154717 0.3254943 0.3955924
3 0.21500559 0.28338113 0.4515079 0.5924649
4 0.28166944 0.37521509 0.5977359 0.7676015
5 0.35325645 0.46704906 0.7672755 0.9210566
6 0.42400121 0.55698113 0.9302943 1.0793479

Daily_Cumulative_Yield_Stats

Daily_Cumulative_Yield_with_Years (a folder with a plot for each year)

6. Trending

Annual_Trends_Data

  STATION_NUMBER      Statistic     1990      1991      1992      1993
1        08NM116 Annual_Maximum 69.90000 56.700001 29.799999 58.000000
2        08NM116    Annual_Mean  9.20929  7.472605  3.256295  6.927921
3        08NM116  Annual_Median  1.98000  1.740000  1.190000  2.570000
4        08NM116 Annual_Minimum  0.56000  0.439000  0.436000  0.270000
5        08NM116     Annual_P10  1.09000  0.714600  0.632000  0.650000
6        08NM116     Annual_P90 34.10000 27.080000  8.295000 18.340000
       1994     1995      1996     1997      1998      1999     2000      2001
1 39.700001 33.10000 53.900002 84.50000 44.700001 52.000000 52.50000 34.599998
2  6.030022  5.64783  8.041762 11.13412  5.538548  8.134885  6.55276  4.628427
3  1.260000  2.26000  3.000000  3.95000  1.450000  2.860000  1.92500  1.470000
4  0.430000  0.55600  0.822000  0.81400  0.490000  0.630000  0.29500  0.485000
5  0.684000  0.73020  1.465000  1.50000  0.775400  0.846200  0.70000  0.704000
6 22.700001 20.00000 22.550000 36.62000 18.020000 25.180000 21.75000 15.980000

Annual_Trends_Results

  STATION_NUMBER      Statistic      lbound       trend     trendp     ubound
1        08NM116 Annual_Maximum -3.86000061 -0.68095280 -8.1714336 2.45999985
2        08NM116    Annual_Mean -0.45884281 -0.14638448 -1.7566137 0.37128058
3        08NM116  Annual_Median -0.15499997  0.03305554  0.3966664 0.19666664
4        08NM116 Annual_Minimum -0.06072064  0.02014911  0.2417893 0.07512883
5        08NM116     Annual_P10 -0.03039051  0.03617438  0.4340926 0.06750319
6        08NM116     Annual_P90 -1.77000008 -0.44361112 -5.3233334 1.13999990
         tau       sig nruns     autocor valid_frac       linear  intercept
1 -0.1515151 0.5371338     1 -0.08447872          1 -0.636363743 58.3642887
2 -0.1515151 0.5371338     1 -0.07095118          1 -0.048107038  7.6394165
3  0.1212121 0.6312218     1 -0.07182129          1  0.038304195  1.8104167
4  0.1272727 0.6404288     5  0.32026845          1  0.006136364  0.3942882
5  0.2727273 0.2757578     4  0.33653092          1  0.003258040  0.5506098
6 -0.1818182 0.4506702     1 -0.03957500          1 -0.302045420 25.2866672
  lbound_intercept ubound_intercept min_year max_year n_years       mean
1      24.38580620       86.0332471     1990     2001      12 50.7833335
2       3.64572586       12.0196834     1990     2001      12  6.8812055
3       0.31971400        3.5263974     1990     2001      12  2.1379167
4      -0.09771161        0.8798609     1990     2001      12  0.5189167
5      -0.24247150        1.4821150     1990     2001      12  0.8742833
6      10.47997563       40.3894691     1990     2001      12 22.5512501
    median       min      max
1 52.25000 29.799999 84.50000
2  6.74034  3.256295 11.13412
3  1.95250  1.190000  3.95000
4  0.48750  0.270000  0.82200
5  0.72240  0.632000  1.50000
6 22.15000  8.295000 36.62000

Annual_Trends_Results_Plots (a folder with a plot for each statistic)

7. Low-flow Frequencies

Annual_Lowflows

  Year Measure     Value
1 1990   1-Day 0.5600000
2 1990   3-Day 0.7000000
3 1990   7-Day 0.9578571
4 1990  30-Day 1.0637000
5 1991   1-Day 0.4390000
6 1991   3-Day 0.4426667

Plotting_Data

  Year Measure Value Probability Return Period
1 1993   1-Day 0.270  0.07692308     13.000000
2 2000   1-Day 0.295  0.15384615      6.500000
3 1994   1-Day 0.430  0.23076923      4.333333
4 1992   1-Day 0.436  0.30769231      3.250000
5 1991   1-Day 0.439  0.38461538      2.600000
6 2001   1-Day 0.485  0.46153846      2.166667

Frequency_Plot

Fitted_Quantiles

  Distribution Probability Return Period     1-Day     3-Day     7-Day
1         PIII        0.01        100.00 0.2112608 0.2660753 0.2597879
2         PIII        0.05         20.00 0.2756306 0.3207233 0.3324727
3         PIII        0.10         10.00 0.3160667 0.3571885 0.3802991
4         PIII        0.20          5.00 0.3713761 0.4101155 0.4487284
5         PIII        0.50          2.00 0.4987802 0.5474475 0.6209821
6         PIII        0.80          1.25 0.6582867 0.7555537 0.8689357
     30-Day
1 0.4175355
2 0.4671200
3 0.5033345
4 0.5594392
5 0.7205906
6 0.9988929

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.

Computing a Full Analysis with fasstr

Overview

Functions and Data Inputs

compute_full_analysis() Object List

write_full_analysis() Excel and Image Files

Usage, Options, and outputs

Objects Examples

1. Screening

2. Long-term

3. Annual

4. Monthly

5. Daily

6. Trending

7. Low-flow Frequencies

`compute_full_analysis()` Object List

`write_full_analysis()` Excel and Image Files