Monte Carlo Node Specifications for the Water Supply Example

A configured Monte Carlo node table for the illustrative water-supply risk assessment. It defines the input nodes, probability distributions, and sampling ranges used to evaluate the treatment and intrusion pathways.

Usage

water_mctable

Format

A data frame with 8 rows and 7 columns:

mcnode

Name of the Monte Carlo input node.

description

Description of the represented parameter.

mc_func

Random-number generation function. NA identifies a deterministic input.

from_variable

Alternative source column used to create the node, where applicable.

transformation

Transformation applied to the source values, where applicable.

sensi_variation

Expression defining variation for one-at-a-time sensitivity analysis.

sample_space

Sampling range or distribution arguments used for sample-design sensitivity analysis.

Source

Parameter ranges are illustrative. They do not represent a fitted model for a specific water system.

Details

source_conc and treatment_lrv use PERT distributions, while intrusion_conc uses a uniform distribution. The remaining inputs are deterministic in the main Monte Carlo model. The sample_space values provide illustrative ranges for optional sample-design sensitivity analyses.

See also

water_data, water_group_data, water_data_keys, water_group_data_keys, treatment_exp, intrusion_exp, eval_module()

Examples

water_mctable
#>            mcnode
#> 1     source_conc
#> 2   treatment_lrv
#> 3    water_volume
#> 4  intrusion_prob
#> 5  intrusion_conc
#> 6 dose_response_r
#> 7      population
#> 8   exposure_days
#>                                                           description mc_func
#> 1           Cryptosporidium concentration in source water (oocysts/L)   rpert
#> 2                    Cryptosporidium log10 reduction during treatment   rpert
#> 3              Daily consumption of unboiled tap water (L/person/day)    <NA>
#> 4 Daily probability that a distribution zone is affected by intrusion    <NA>
#> 5       Cryptosporidium concentration if intrusion occurs (oocysts/L)   runif
#> 6                 Exponential Cryptosporidium dose-response parameter    <NA>
#> 7                         Population exposed in the distribution zone    <NA>
#> 8                                     Number of daily exposure events    <NA>
#>   from_variable transformation sensi_variation                     sample_space
#> 1          <NA>           <NA>            <NA> min = 0.5, mode = 1.0, max = 1.5
#> 2          <NA>           <NA>            <NA> min = 2.5, mode = 3.0, max = 3.5
#> 3          <NA>           <NA>            <NA>             min = 1.0, max = 2.0
#> 4          <NA>           <NA>            <NA>        min = 0.0002, max = 0.005
#> 5          <NA>           <NA>            <NA>           min = 0.01, max = 0.05
#> 6          <NA>           <NA>            <NA>                  c(0.018, 0.018)
#> 7          <NA>           <NA>            <NA>                             <NA>
#> 8          <NA>           <NA>            <NA>                        c(30, 30)