Package {nwsrfsr}

Title:	NWS Hydrology Models: SAC-SMA, SNOW17, UH, CONSUSE, CHANLOSS
Version:	1.0.3
Description:	Interface to the National Weather Service operational hydrology models, Sacramento Soil Moisture Accounting (SAC-SMA), Snow Accumulation and Ablation (SNOW17). Also provides an interface to the unit hydrograph routing model (UH), consumptive use (CONSUSE) and channel loss/gain modules (CHANLOSS). The Fortran code used in this package is considered "legacy" and is not supported officially by NWS, but it should not have any significant differences from current operational models.
License:	Apache License (≥ 2)
Encoding:	UTF-8
LazyData:	true
LazyDataCompression:	xz
RoxygenNote:	7.3.3
Suggests:	testthat
URL:	https://github.com/NOAA-NWRFC/nwsrfs-hydro-models, https://noaa-nwrfc.github.io/nwsrfs-hydro-models/
BugReports:	https://github.com/NOAA-NWRFC/nwsrfs-hydro-models/issues
Config/testthat/edition:	3
Depends:	R (≥ 4.1.0)
NeedsCompilation:	yes
Packaged:	2026-07-22 01:39:56 UTC; brac840
Author:	Cameron Bracken [aut, cre], Geoffrey Walters [aut], Eric Anderson [ctb] (Original SNOW-17 and SAC-SMA Fortran code (NOAA/HRL)), George F. Smith [ctb] (Original LAG-K Fortran code (NOAA/HRL)), Janice M. Lewis [ctb] (Interpolation and LAG-K Fortran code (NOAA/HRL)), John E. Pask [ctb] (Original sorting routines (LLNL); see inst/COPYRIGHTS), Ondrej Certik [ctb] (MIT-licensed fortran-utils sorting and types modules; see inst/COPYRIGHTS), John Burkardt [ctb] (MIT-licensed implementation of Brent's zero finder; see inst/COPYRIGHTS), National Oceanic and Atmospheric Administration [cph] (International-rights holder for U.S. Government-authored components, including legacy NWSRFS Fortran and contributions by NOAA employees (C. Bracken through 2022-06-30, G. Walters); see inst/COPYRIGHTS), Battelle Memorial Institute [cph] (Copyright holder for PNNL-authored contributions by C. Bracken from 2022-07-01 onward; see inst/COPYRIGHTS)
Maintainer:	Cameron Bracken <cameron.bracken@pnnl.gov>
Repository:	CRAN
Date/Publication:	2026-07-22 08:10:02 UTC

nwsrfsr: NWS River Forecast System Hydrologic Models

Description

R interface to NWSRFS Fortran hydrologic models used operationally by NOAA's National Weather Service River Forecast Centers. Includes SAC-SMA soil moisture accounting, SNOW-17 snow accumulation/ablation, gamma unit hydrograph routing, Lag-K channel routing, channel loss/gain, and consumptive use modules.

Low-level model wrappers

Individual model components callable via Fortran interface: sac_snow(), uh(), lagk(), chanloss(), consuse(), fa_nwrfc()

High-level orchestration

nwsrfs_run() reads NWRFC autocalibration directories and runs the full model chain. load_example() provides bundled example data for NRKW1 and SFLN2.

AdjustQ preprocessing

adjustq() replicates the CHPS FEWS AdjustQ tool for creating upstream flow timeseries from observed and simulated data.

Author(s)

Maintainer: Cameron Bracken cameron.bracken@pnnl.gov (ORCID)

Authors:

• Geoffrey Walters geoffrey.walters@noaa.gov (ORCID)

Other contributors:

• Eric Anderson (Original SNOW-17 and SAC-SMA Fortran code (NOAA/HRL)) [contributor]

• George F. Smith (Original LAG-K Fortran code (NOAA/HRL)) [contributor]

• Janice M. Lewis (Interpolation and LAG-K Fortran code (NOAA/HRL)) [contributor]

• John E. Pask (Original sorting routines (LLNL); see inst/COPYRIGHTS) [contributor]

• Ondrej Certik (MIT-licensed fortran-utils sorting and types modules; see inst/COPYRIGHTS) [contributor]

• John Burkardt (MIT-licensed implementation of Brent's zero finder; see inst/COPYRIGHTS) [contributor]

• National Oceanic and Atmospheric Administration (International-rights holder for U.S. Government-authored components, including legacy NWSRFS Fortran and contributions by NOAA employees (C. Bracken through 2022-06-30, G. Walters); see inst/COPYRIGHTS) [copyright holder]

• Battelle Memorial Institute (Copyright holder for PNNL-authored contributions by C. Bracken from 2022-07-01 onward; see inst/COPYRIGHTS) [copyright holder]

See Also

Useful links:

• https://github.com/NOAA-NWRFC/nwsrfs-hydro-models

• https://noaa-nwrfc.github.io/nwsrfs-hydro-models/

• Report bugs at https://github.com/NOAA-NWRFC/nwsrfs-hydro-models/issues

Areal depeletion curve using a 3 parameter model

Description

adc=a*x^b+(1.0-a)*x^c

Usage

adc3(a, b, c)

Arguments

Value

11 element vector representing the ADC

Examples

adc <- adc3(.5, 0.1, 2)

AdjustQ: Create upstream flow timeseries from observations and simulation

Description

Replicates the CHPS FEWS AdjustQ tool. Adjusts observed mean daily discharges using observed instantaneous and simulated discharges. If both observed mean daily and instantaneous data are missing, simulated discharge is used.

Usage

adjustq(
  daily_flow,
  inst_flow,
  sim = NULL,
  blend = 10L,
  interp_type = "ratio",
  error_tol = 0.01,
  max_iterations = 15L
)

Arguments

Value

A data.frame with columns: datetime (POSIXct), flow_cfs (adjusted flow)

Load AdjustQ example

Description

Runs AdjustQ using bundled NRKW1 data.

Usage

adjustq_load_example(sim = TRUE, ...)

Arguments

Value

A data.frame (see adjustq())

Area-elevation curve for the zones of SFLN2

Description

A dataset containing the percent area covered at a complete range of elevations for the two zones of Salmon Falls Creek (SFLN2). Used as input to rsnwelev().

Usage

area_elev_curve

Format

A data.frame with 21 rows and 3 columns:

quantile

Cumulative area fraction of the basin below the reference elevation

SFLN2-1

Reference elevations for zone 1 (ft)

SFLN2-2

Reference elevations for zone 2 (ft)

Seasonal chanloss

Description

Seasonal chanloss

Usage

chanloss(flow, forcing, dt_hours, pars)

Arguments

Value

Vector of flow modified by the chanloss pattern

Daily consuse model

Description

Daily consuse model

Usage

consuse(input, pars, cfs = TRUE)

Arguments

Value

data frame with consuse variables

Conduct NWRFC style forcing adjustments

Description

Conduct NWRFC style forcing adjustments

Usage

fa_adj_nwrfc(
  dt_hours,
  forcing,
  pars,
  climo = NULL,
  dry_run = FALSE,
  return_climo = FALSE
)

Arguments

Value

Matrix (1 column per zone) of unrouted channel inflow

Examples

data(nrkw1_forcing)
data(nrkw1_pars)
dt_hours <- 6
adj <- fa_adj_nwrfc(dt_hours, nrkw1_forcing, nrkw1_pars)

Conduct NWRFC style forcing adjustments

Description

Conduct NWRFC style forcing adjustments

Usage

fa_nwrfc(
  dt_hours,
  forcing,
  pars,
  climo = NULL,
  dry_run = FALSE,
  return_adj = FALSE,
  return_climo = FALSE
)

Arguments

Value

Matrix (1 column per zone) of unrouted channel inflow

Examples

data(nrkw1_forcing)
data(nrkw1_pars)
dt_hours <- 6
forcing_adj <- fa_nwrfc(dt_hours, nrkw1_forcing, nrkw1_pars)

Adjust monthly climo based on 4 parameters

Description

description

Usage

forcing_adjust_map_pet_ptps(
  climo,
  pars,
  ll = 0.9 * climo,
  ul = 1.1 * climo,
  return_climo = FALSE
)

Arguments

Value

stuff

Examples

climo <- rep(2, 12)
pars <- c(.5, 0, 10, 0)
forcing_adjust_map_pet_ptps(climo, pars)

Adjust monthly climo based on 4 parameters

Description

description

Usage

forcing_adjust_mat(
  climo,
  pars,
  ll = climo * ifelse(climo > 0, 0.9, 1.1),
  ul = climo * ifelse(climo > 0, 1.1, 0.9),
  return_climo = FALSE
)

Arguments

Value

stuff

Examples

climo <- rep(2, 12)
pars <- c(.5, 0, 10, 0)
forcing_adjust_mat(climo, pars)

Format state output from sac_snow_states

Description

Format state output from sac_snow_states

Usage

format_states(x)

Arguments

Value

a data.frame with formatted output

Interpolate forcing adjustment factors

Description

This function interpolates 12 forcing adjustment factors (1 per month) by placing them at the 15th of the month then interpolating between the previous and next months values for every time step in between.

Usage

interp_fa(factors, month, day, hour)

Arguments

Value

A vector matching the length of month, containing interpolated adjustment factors

Examples

d1 <- as.POSIXct("2001-01-01 00:00:00", tz = "UTC")
d2 <- as.POSIXct("2001-12-31 18:00:00", tz = "UTC")
dates <- seq.POSIXt(d1, d2, by = "6 hours")

month <- as.integer(format(dates, "%m"))
day <- as.integer(format(dates, "%d"))
hour <- as.integer(format(dates, "%H"))
factors <- c(.5, 2, 1, 1.5, 2, .5, 1, 2.5, 3, -1.5, 0, 1)

ifa <- interp_fa(factors, month, day, hour)

plot(dates, ifa, t = "l")
points(as.POSIXct(paste0("2001-", 1:12, "-15"), tz = "UTC"), factors, col = "red")

Lag-K Routing for any number of upstream points

Description

Lag-K Routing for any number of upstream points

Usage

lagk(dt_hours, uptribs, pars, sum_routes = TRUE, return_states = FALSE)

Arguments

Value

vector of routed flows

Examples

NULL

Load and run a bundled example dataset

Description

Loads NRKW1 or SFLN2 bundled example data and runs the full NWSRFS model chain.

Usage

load_example(lid = "NRKW1", forcing_adj = TRUE, shift_sf = TRUE)

Arguments

Value

A list with class "nwsrfs_run" (see nwsrfs_run())

Examples

run = load_example("NRKW1")
plot(run$sim, type = "l")

NRKW1 observed daily flow

Description

Daily average observed streamflow at NRKW1.

Usage

nrkw1_daily_flow

Format

A data.frame with columns:

year,month,day

Date columns

flow_cfs

Daily average streamflow (cfs)

Source

Data source identifier

NRKW1 forcing data

Description

6-hour forcing data for Nooksack River at North Cedarville (NRKW1), 2 zones, period of record.

Usage

nrkw1_forcing

Format

A named list of 2 data.frames (NRKW1-1, NRKW1-2), each with columns:

year,month,day,hour

Datetime columns

map_mm

Mean areal precipitation (mm)

mat_degc

Mean areal temperature (deg C)

ptps

Fraction of precipitation as snow

NRKW1 observed instantaneous flow

Description

Instantaneous (6-hour) observed streamflow at NRKW1.

Usage

nrkw1_inst_flow

Format

A data.frame with columns:

year,month,day,hour

Datetime columns

flow_cfs

Instantaneous streamflow (cfs)

Source

Data source identifier

NRKW1 optimal parameters

Description

Optimal parameters from NWRFC autocalibration for Nooksack River at North Cedarville, WA (USGS-12210700). 2-zone SAC-SMA/SNOW17/UH model with 3-reach Lag-K routing (6 hour timestep).

Usage

nrkw1_pars

Format

A data.frame with 5 columns:

p_name

Unique parameter identifier

name

Parameter name

type

Model type (sac, snow, uh, fa, lagk)

zone

Zone or upstream reach name

value

Parameter value

NRKW1 upstream flow data

Description

6-hour upstream flow timeseries for 3 upstream reaches (MFNW1, NFNW1, NSSW1) routed via Lag-K to Nooksack River at North Cedarville.

Usage

nrkw1_upflow

Format

A named list of 3 data.frames, each with columns:

year,month,day,hour

Datetime columns

flow_cfs

Streamflow (cfs)

Run the full NWSRFS model chain

Description

Reads parameter, forcing, flow, and upflow CSVs from an NWRFC autocalibration directory, auto-detects which model components are present, and runs the full chain: FA -> SAC-SMA/SNOW17 -> UH -> Lag-K -> Chanloss -> Consuse.

Usage

nwsrfs_run(autocalb_dir, run_dir = NULL, forcing_adj = TRUE, shift_sf = TRUE)

Arguments

Details

The returned list contains:

sim

Numeric vector of simulated flow (cfs)

sacsnow_sf

Numeric vector of SAC-SMA/SNOW17/UH flow per zone (cfs), or NULL

sacsnow_tci

Matrix of total channel inflow per zone (mm), or NULL

lagk_route

Numeric vector of Lag-K routed flow (cfs), or NULL

forcings

List of adjusted forcing data.frames, or NULL

pars

Parameter data.frame

forcing_raw

List of raw (unadjusted) forcing data.frames

upflow

List of upstream flow data.frames, or NULL

daily_flow

Daily observed flow data.frame

inst_flow

Instantaneous observed flow data.frame, or NULL

dt_hours

Model timestep in hours

zone_names

Character vector of zone names

upflow_names

Character vector of upstream reach names, or NULL

localflow_logic

Logical; SAC-SMA/SNOW17/UH present

upflow_logic

Logical; Lag-K routing present

chanloss_logic

Logical; chanloss present

consuse_logic

Logical; consuse present

Value

A list with class "nwsrfs_run" containing model results and metadata. See Details.

Daily Potential Evapotranspiration using Hargreaves-Semani equations

Description

Daily Potential Evapotranspiration using Hargreaves-Semani equations

Usage

pet_hs(lat, jday, tave, tmax, tmin)

Arguments

Value

Daily PET (vectorized over all inputs)

Examples

pet <- pet_hs(42, 200, 20, 25, 15)

Print method for nwsrfs_run objects

Description

Print method for nwsrfs_run objects

Usage

## S3 method for class 'nwsrfs_run'
print(x, ...)

Arguments

Value

x (invisibly)

Replace ptps column with ptps derived using rain snow line code (lapse rate + MAT)

Description

Replace ptps column with ptps derived using rain snow line code (lapse rate + MAT)

Usage

rsnwelev(forcing, pars, ae_tbl)

Arguments

Value

The forcing list with each zone's ptps column replaced by the value derived from the rsnwelev model.

Examples

# area_elev_curve is bundled for SFLN2 (2 zones); pair it with SFLN2 data.
data(sfln2_forcing)
data(sfln2_pars)
data(area_elev_curve)
# rsnwelev only needs the zones that match the area-elevation table,
# so drop the SFLN2-CU consumptive-use zone before calling.
forcing_zones <- sfln2_forcing[c("SFLN2-1", "SFLN2-2")]
# rsnwelev needs elev plus a temperature lapse rate (talr, degC/100m) and a
# rain/snow threshold (pxtemp, degC) per zone. The bundled calibration only
# carries elev, so add representative talr/pxtemp rows for the two zones.
zones <- c("SFLN2-1", "SFLN2-2")
rs_pars <- rbind(
  sfln2_pars[sfln2_pars$name == "elev" & sfln2_pars$zone %in% zones, ],
  data.frame(
    p_name = paste0(rep(c("talr_", "pxtemp_"), each = 2), zones),
    name = rep(c("talr", "pxtemp"), each = 2),
    type = "rsnwelev",
    zone = rep(zones, 2),
    value = c(0.5, 0.5, 1.0, 1.0)
  )
)
forcing_adj <- rsnwelev(forcing_zones, rs_pars, area_elev_curve)

Execute SAC-SMA, SNOW17, return total channel inflow per zone, and model states

Description

Execute SAC-SMA, SNOW17, return total channel inflow per zone, and model states

Usage

sac_snow(dt_hours, forcing, pars, return_states = FALSE)

Arguments

Value

data.frame (1 column per zone) of unrouted channel inflow (tci), sac states uztwc, uzfwc, lztwc, lzfsc, lzfpc, adimc, and snow water equivalent (swe), and adjusted forcing data.

Examples

# Simple: full model chain via the bundled example
run <- load_example("NRKW1")
head(run$sacsnow_tci)

# Low-level: populate etd_mm / pet_mm via fa_nwrfc first,
# then call the SAC-SMA / SNOW17 wrapper directly. sac_snow() requires
# forcing data frames that already contain etd_mm.
data(nrkw1_forcing)
data(nrkw1_pars)
dt_hours <- 6
forcing_adj <- fa_nwrfc(dt_hours, nrkw1_forcing, nrkw1_pars)
tci <- sac_snow(dt_hours, forcing_adj, nrkw1_pars)

Execute SAC-SMA, SNOW17, return total channel inflow per zone, and model states

Description

Execute SAC-SMA, SNOW17, return total channel inflow per zone, and model states

Usage

sac_snow_states(dt_hours, forcing, pars)

Arguments

Value

data.frame (1 column per zone) of unrouted channel inflow (tci), sac states uztwc, uzfwc, lztwc, lzfsc, lzfpc, adimc, and snow water equivalent (swe), and adjusted forcing data.

Examples

# Simple: full model chain via the bundled example, tci and states returned together
run <- load_example("NRKW1")
head(run$sacsnow_tci)

# Low-level: populate etd_mm / pet_mm via fa_nwrfc first, then
# get per-zone tci and states directly.
data(nrkw1_forcing)
data(nrkw1_pars)
dt_hours <- 6
forcing_adj <- fa_nwrfc(dt_hours, nrkw1_forcing, nrkw1_pars)
states <- sac_snow_states(dt_hours, forcing_adj, nrkw1_pars)

Execute SAC-SMA, SNOW17 and UH with given parameters

Description

Execute SAC-SMA, SNOW17 and UH with given parameters

Usage

sac_snow_uh(dt_hours, forcing, pars)

Arguments

Value

Vector of routed flow in cfs

Examples

# Simple: full model chain via the bundled example
run <- load_example("NRKW1")
head(run$sim)

# Low-level: populate etd_mm / pet_mm via fa_nwrfc first,
# then call the combined SAC-SMA / SNOW17 / UH wrapper.
data(nrkw1_forcing)
data(nrkw1_pars)
dt_hours <- 6
forcing_adj <- fa_nwrfc(dt_hours, nrkw1_forcing, nrkw1_pars)
flow_cfs <- sac_snow_uh(dt_hours, forcing_adj, nrkw1_pars)

Execute SAC-SMA, SNOW17, UH and LAG-K with given parameters

Description

Execute SAC-SMA, SNOW17, UH and LAG-K with given parameters

Usage

sac_snow_uh_lagk(dt_hours, forcing, uptribs, pars)

Arguments

Value

Vector of routed flow in cfs

Examples

# Simple: full model chain via the bundled example (NRKW1 has upstream tribs)
run <- load_example("NRKW1")
head(run$sim)

# Low-level: populate etd_mm / pet_mm via fa_nwrfc first, then chain
# SAC-SMA / SNOW17 / UH with Lag-K routing of upstream tributaries.
data(nrkw1_forcing)
data(nrkw1_pars)
data(nrkw1_upflow)
dt_hours <- 6
forcing_adj <- fa_nwrfc(dt_hours, nrkw1_forcing, nrkw1_pars)
flow_cfs <- sac_snow_uh_lagk(dt_hours, forcing_adj, nrkw1_upflow, nrkw1_pars)

Find a reasonable scale upper limit for optimization

Description

Find a reasonable scale upper limit for optimization

Usage

scale_uplimit(shape, dt_hours)

Arguments

Value

numeric value indicating the upper limit for the scale

Conputes surface pressure in hPa from a given elevation

Description

Conputes surface pressure in hPa from a given elevation

Usage

sfc_pressure(elev)

Arguments

Value

Surface pressure in hPa

Examples

sp <- sfc_pressure(0)

SFLN2 observed daily flow

Description

Daily average observed streamflow at SFLN2.

Usage

sfln2_daily_flow

Format

A data.frame with columns:

year,month,day

Date columns

flow_cfs

Daily average streamflow (cfs)

Source

Data source identifier

SFLN2 forcing data

Description

6-hour forcing data for Salmon Falls Creek (SFLN2), 2 zones plus a consumptive use zone, period of record.

Usage

sfln2_forcing

Format

A named list of 3 data.frames (SFLN2-1, SFLN2-2, SFLN2-CU), each with columns:

year,month,day,hour

Datetime columns

map_mm

Mean areal precipitation (mm)

mat_degc

Mean areal temperature (deg C)

ptps

Fraction of precipitation as snow

SFLN2 observed instantaneous flow

Description

Instantaneous (6-hour) observed streamflow at SFLN2.

Usage

sfln2_inst_flow

Format

A data.frame with columns:

year,month,day,hour

Datetime columns

flow_cfs

Instantaneous streamflow (cfs)

Source

Data source identifier

SFLN2 optimal parameters

Description

Optimal parameters from NWRFC autocalibration for Salmon Falls Creek NR San Jacinto NV (USGS-13105000). 2-zone SAC-SMA/SNOW17/UH model with chanloss and consuse (6 hour timestep).

Usage

sfln2_pars

Format

A data.frame with 5 columns:

p_name

Unique parameter identifier

name

Parameter name

type

Model type (sac, snow, uh, fa, chanloss, consuse)

zone

Zone name

value

Parameter value

Two parameter unit hydrograph routing for one or more basin zones

Description

Two parameter unit hydrograph routing for one or more basin zones

Usage

uh(
  dt_hours,
  tci,
  pars,
  sum_zones = TRUE,
  start_of_timestep = TRUE,
  backfill = TRUE
)

Arguments

Value

Vector of routed flow in cfs

Examples

# Simple: full model chain via the bundled example; routed flow per zone
run <- load_example("NRKW1")
head(run$sacsnow_sf)

# Low-level: run FA -> SAC-SMA/SNOW17 to get TCI, then route it with UH.
data(nrkw1_forcing)
data(nrkw1_pars)
dt_hours <- 6
forcing_adj <- fa_nwrfc(dt_hours, nrkw1_forcing, nrkw1_pars)
tci <- sac_snow(dt_hours, forcing_adj, nrkw1_pars)
flow_cfs <- uh(dt_hours, tci, nrkw1_pars)

R port of the nwsrfs UH fortran code

Description

Returns ordinates for a 2 parameter (shape,scale) gamma unit hydrograph. The ordinates are based on the given timestep (in hours). To match the Fortran code, a max length is used. A warning is issued if the UH does not terminate before the given max length.

Usage

uh2p(shape, scale, timestep, max_len = 1000)

Arguments

Value

vector of ordinates for a 2 parameter (shape,scale) gamma unit hydrograph

Examples

dt <- 6
shape <- 2
scale <- 1
y <- uh2p(2, 1, 6)
x <- seq(dt, dt * length(y), by = dt)
plot(x, y, t = "l")

Create a 2 parameter gamma unit hydrograph with units cfs/in

Description

Create a 2 parameter gamma unit hydrograph with units cfs/in

Usage

uh2p_cfs_in(shape, scale, timestep, area)

Arguments

Value

stuff

Examples

dt <- 6
shape <- 2
scale <- 1
y <- uh2p_cfs_in(2, 1, 6, 1000)
x <- seq(dt, dt * length(y), by = dt)
plot(x, y, t = "l")

Get the scale parameter from a 2 parameter gamma unit hydrograph given the shape parameter and time of concentration.

Description

Get the scale parameter from a 2 parameter gamma unit hydrograph given the shape parameter and time of concentration.

Usage

uh2p_get_scale(shape, toc, dt_hours)

Arguments

Value

scalar scale parameter

Examples

uh2p_get_scale(2, 50, 1)

Get the scale parameter from a 2 parameter gamma unit hydrograph given the shape parameter and time of concentration.

Description

Get the scale parameter from a 2 parameter gamma unit hydrograph given the shape parameter and time of concentration.

Usage

uh2p_get_scale_r(shape, toc, dt_hours)

Arguments

Value

stuff

Examples

uh2p_get_scale_r(2, 50, 1)

root finding function for finding a scale parameter given shape and toc

Description

root finding function for finding a scale parameter given shape and toc

Usage

uh2p_root(scale, shape, dt_hours, toc)

Arguments

Value

function value for root finding

Objective function for finding a scale parameter given shape and toc

Description

Objective function for finding a scale parameter given shape and toc

Usage

uh2p_seek(scale, shape, dt_hours, toc)

Arguments

Value

objective function value

Objective function for finding a scale parameter given shape and toc

Description

Objective function for finding a scale parameter given shape and toc

Usage

uh2p_seek2(scale, shape, dt_hours, toc)

Arguments

Value

function value for root finding

Update parameters and re-run model chain

Description

Update parameters and re-run model chain

Usage

update_pars(run, new_pars)

Arguments

Value

A new "nwsrfs_run" object with updated parameters