Package 'streamDepletr'

Title: Estimate Streamflow Depletion Due to Groundwater Pumping
Description: Implementation of analytical models for estimating streamflow depletion due to groundwater pumping, and other related tools. Functions are broadly split into two groups: (1) analytical streamflow depletion models, which estimate streamflow depletion for a single stream reach resulting from groundwater pumping; and (2) depletion apportionment equations, which distribute estimated streamflow depletion among multiple stream reaches within a stream network. See Zipper et al. (2018) <doi:10.1029/2018WR022707> for more information on depletion apportionment equations and Zipper et al. (2019) <doi:10.1029/2018WR024403> for more information on analytical depletion functions, which combine analytical models and depletion apportionment equations.
Authors: Sam Zipper [aut, cre] , Ben Kerr [ctb], Tom Gleeson [ctb] , Qiang Li [rev] , Foundry Spatial Ltd. [cph]
Maintainer: Sam Zipper <[email protected]>
License: BSD_3_clause + file LICENSE
Version: 0.2.0
Built: 2024-11-12 05:42:10 UTC
Source: https://github.com/foundryspatial/streamdepletr

Help Index

Distribute streamflow depletion within a stream network using inverse distance weighting.

Description

Distribute streamflow depletion within a stream network using inverse distance weighting.

Usage

apportion_inverse(
  reach_dist,
  w,
  max_dist = Inf,
  min_frac = 0,
  reach_name = NULL,
  dist_name = NULL
)

Arguments

reach_dist

data frame with two columns: reach, which is a grouping variable with the name of each stream reach, and dist which is the distance of that stream reach to the well of interest. There can be more than one dist per reach; the function will automatically find the minimum. Columns can either be named exactly as defined here, or set using reach_name and dist_name.
w

inverse distance weighting factor; 1 for inverse distance, 2 for inverse distance squared.
max_dist

the maximum distance of a stream to be depleted; defaults to Inf, which means all reaches will be considered.
min_frac

the minimum frac_depletion to be returned; defaults to 0, which means all reaches will be considered. If min_frac > 0 and some reaches have an estimated frac_depletion < min_frac, depletion in those reaches will be set to 0 and that depletion will be reallocated based on the proportional depletion in the remaining reaches.
reach_name

The name of the column in reach_dist indicating your stream reach grouping variable. If set to NULL (default), it will assume that the column name is reach.
dist_name

The name of the column in reach_dist indicating your distance variable. If set to NULL (default), it will assume that the column name is dist.

Details

Since analytical models assume the presence of 1 (or sometimes 2) linear streams, the apportion_* functions can be used to distribute that depletion to various reaches within a real stream network. These geometric functions are described in Zipper et al (2018), which found that apportion_web a weighting factor (w) of 2 produced the best results.

Value

A data frame with two columns:

reach

the grouping variable input in reach_dist

frac_depletion

the proportion of streamflow depletion from the well occurring in that reach.

References

Zipper, SC, T Dallemagne, T Gleeson, TC Boerman, A Hartmann (2018). Groundwater Pumping Impacts on Real Stream Networks: Testing the Performance of Simple Management Tools. Water Resources Research. doi:10.1029/2018WR022707.

Examples

reach_dist <- data.frame(reach = seq(1,5), dist = c(100, 150, 900, 300, 200))
apportion_inverse(reach_dist, w = 2)
apportion_inverse(reach_dist, w = 2, max_dist = 500)

reach_dist <- data.frame(reach = c("A", "A", "A", "B", "B"), dist = c(100, 150, 900, 300, 200))
apportion_inverse(reach_dist, w = 1)
apportion_inverse(reach_dist, w = 1, max_dist = 500)

Distribute streamflow depletion within a stream network using web distance Thiessen polygons.

Description

Distribute streamflow depletion within a stream network using web distance Thiessen polygons.

Usage

apportion_polygon(
  reach_dist_lon_lat,
  wel_lon,
  wel_lat,
  coord_crs,
  max_dist = Inf,
  min_frac = 0,
  reach_name = NULL,
  dist_name = NULL,
  lon_name = NULL,
  lat_name = NULL
)

Arguments

reach_dist_lon_lat

data frame with four columns: reach, which is a grouping variable with the name of each stream reach; dist which is the distance of a point on that stream reach to the well of interest; lon which is the longitude of that point on the stream; and lat which is the latitude of that point on the stream. There can (and likely will) be multiple rows per reach. Columns can either be named exactly as defined here, or set using reach_name, dist_name, lon_name, and lat_name.
wel_lon

longitude of well
wel_lat

latitude of well
coord_crs

coordinate reference system for sf or sfc object (create with sf::st_crs).
max_dist

the maximum distance of a stream to be depleted; defaults to Inf, which means all reaches will be considered.
min_frac

the minimum frac_depletion to be returned; defaults to 0, which means all reaches will be considered. If min_frac > 0 and some reaches have an estimated frac_depletion < min_frac, depletion in those reaches will be set to 0 and that depletion will be reallocated based on the proportional depletion in the remaining reaches.
reach_name

The name of the column in reach_dist indicating your stream reach grouping variable. If set to NULL (default), it will assume that the column name is reach.
dist_name

The name of the column in reach_dist indicating your distance variable. If set to NULL (default), it will assume that the column name is dist.
lon_name

The name of the column in reach_dist indicating your longitude variable. If set to NULL (default), it will assume that the column name is lon.
lat_name

The name of the column in reach_dist indicating your latitude variable. If set to NULL (default), it will assume that the column name is lat.

Details

Since analytical models assume the presence of 1 (or sometimes 2) linear streams, the apportion_* functions can be used to distribute that depletion to various reaches within a real stream network. These geometric functions are described in Zipper et al (2018), which found that apportion_web a weighting factor (w) of 2 produced the best results.

Value

A data frame with two columns:

reach

the grouping variable input in reach_dist

frac_depletion

the proportion of streamflow depletion from the well occurring in that reach.

References

Zipper, SC, T Dallemagne, T Gleeson, TC Boerman, A Hartmann (2018). Groundwater Pumping Impacts on Real Stream Networks: Testing the Performance of Simple Management Tools. Water Resources Research. doi:10.1029/2018WR022707.

Examples

rdll <- prep_reach_dist(wel_lon = 295500, wel_lat = 4783200,
   stream_sf = stream_lines, reach_id = "reach", stream_pt_spacing = 5)
apportion_polygon(reach_dist_lon_lat = rdll, wel_lon = 295500, wel_lat = 4783200,
   max_dist = 5000, coord_crs = sf::st_crs(stream_lines))
apportion_polygon(reach_dist_lon_lat = rdll, wel_lon = 295500, wel_lat = 4783200,
   max_dist = 5000, min_frac = 0.05, coord_crs = sf::st_crs(stream_lines))

Distribute streamflow depletion within a stream network using web distance weighting.

Description

Distribute streamflow depletion within a stream network using web distance weighting.

Usage

apportion_web(
  reach_dist,
  w,
  max_dist = Inf,
  min_frac = 0,
  reach_name = NULL,
  dist_name = NULL
)

Arguments

reach_dist

data frame with two columns: reach, which is a grouping variable with the name of each stream reach, and dist which is the distance of a point on that stream reach to the well of interest. There can (and likely will) be more than one dist per reach; if there is only one dist per reach, results will be the same as the apportion_inverse method. Columns can either be named exactly as defined here, or set using reach_name and dist_name.
w

weighting factor; 1 for web, 2 for web squared.
max_dist

the maximum distance of a stream to be depleted; defaults to Inf, which means all reaches will be considered.
min_frac

the minimum frac_depletion to be returned; defaults to 0, which means all reaches will be considered. If min_frac > 0 and some reaches have an estimated frac_depletion < min_frac, depletion in those reaches will be set to 0 and that depletion will be reallocated based on the proportional depletion in the remaining reaches.
reach_name

The name of the column in reach_dist indicating your stream reach grouping variable. If set to NULL (default), it will assume that the column name is reach.
dist_name

The name of the column in reach_dist indicating your distance variable. If set to NULL (default), it will assume that the column name is dist.

Details

Since analytical models assume the presence of 1 (or sometimes 2) linear streams, the apportion_* functions can be used to distribute that depletion to various reaches within a real stream network. These geometric functions are described in Zipper et al (2018), which found that apportion_web a weighting factor (w) of 2 produced the best results.

Value

A data frame with two columns:

reach

the grouping variable input in reach_dist

frac_depletion

the proportion of streamflow depletion from the well occurring in that reach.

References

Zipper, SC, T Dallemagne, T Gleeson, TC Boerman, A Hartmann (2018). Groundwater Pumping Impacts on Real Stream Networks: Testing the Performance of Simple Management Tools. Water Resources Research. doi:10.1029/2018WR022707.

Examples

reach_dist <- data.frame(reach = seq(1,5),
  dist = c(100, 150, 900, 300, 200))
apportion_web(reach_dist, w = 2)  # same as inverse because there's only one dist per reach
apportion_web(reach_dist, w = 2, max_dist = 500)

reach_dist <- data.frame(reach = c("A", "A", "A", "B", "B"),
  dist = c(100, 150, 900, 300, 200))
apportion_web(reach_dist, w = 1)
apportion_web(reach_dist, w = 1, max_dist = 500)

Distribute streamflow depletion between two streams in a wedge-shaped aquifer.

Description

Distribute streamflow depletion between two streams in a wedge-shaped aquifer.

Usage

apportion_wedge(angle_total, angle_well)

Arguments

angle_total

angle [radians] between the two streams.
angle_well

angle [radians] from the first (lower boundary) stream and the well.

Details

This function assumes that streams are two linear tributaries which meet at the origin. This function specifically corresponds to Equations 18 and 19 in Yeh et al. (2008).

Value

A numeric of length two with the proportion of steady-state capture fraction from the first (lower) and second (upper) streams.

References

Yeh, HD, YC Chang, VA Zlotnik (2008). Stream depletion rate and volume from groundwater pumping in wedge-shaped aquifers. Journal of Hydrology 349(3): 501-511. doi:10.1029/2018WR022707.

Examples

apportion_wedge(angle_total = (50*pi/2), angle_well = (10*pi/2))

apportion_wedge(angle_total = (50*pi/2), angle_well = (25*pi/2))

Calculate maximum distance at which streamflow depletion will exceed a user-selected threshold. Note that this only considers a single stream - depletion apportionment does not occur.

Description

Calculate maximum distance at which streamflow depletion will exceed a user-selected threshold. Note that this only considers a single stream - depletion apportionment does not occur.

Usage

depletion_max_distance(
  Qf_thres = 0.01,
  d_interval = 100,
  d_min = NULL,
  d_max = 5000,
  method = "glover",
  t,
  S,
  Tr,
  ...
)

Arguments

Qf_thres

streamflow depletion fraction (Qf) threshold used to define maximum distance. Defaults to 0.01 (1%).
d_interval

interval to use for testing; this defines the spatial resolution at which output will be returned [L]
d_min

minimum search distance [L]. If 'Qf' < 'Qf_thres' at 'd_min', function will return 'd_min' and a warning. If ‘d_min'=NULL (default), 'd_min' will be set to 'd_interval’'
d_max

maximum search distance [L]. If 'Qf' > 'Qf_thres' at 'd_max', function will return 'd_max' and a warning.
method

analytical solution to use (options= 'glover', 'hunt'). Defaults to 'glover'.
t

time you want output for [T]
S

aquifer storage coefficient (specific yield if unconfined; storativity if confined)
Tr

aquifer transmissivity [L2/T]
...

any other inputs required for your method of choice; for example, hunt needs lmda (streambed conductance)

Details

This function is useful for the 'Expanding' stream proximity criteria described in Zipper et al. (2018).

Value

A numeric of the distance at which streamflow depletion fraction (Qf) drops below the threshold at time 't'.

References

Zipper, SC, T Gleeson, B Kerr, JK Howard, MM Rohde, J Carah, J Zimmerman (2018). Rapid and accurate estimates of streamflow depletion caused by groundwater pumping using analytical depletion functions. EarthArXiv. doi:10.31223/osf.io/uqbd7.

Examples

depletion_max_distance(method = "glover", t = 730, S = 0.1, Tr = 100)
depletion_max_distance(Qf_thres = 0.001, method = "glover", t = 730, S = 0.1, Tr = 100)
depletion_max_distance(Qf_thres = 0.001, method = "hunt", t = 730, S = 0.1, Tr = 100, lmda = 0.01)
depletion_max_distance(Qf_thres = 0.001, method = "hunt", t = 7300, S = 0.1, Tr = 100, lmda = 0.01)

Streamflow for Sixmile Creek and Dorn Creek.

Description

Daily discharge data for the 2014-2015 water years for the US Geological Survey gauging stations DORN (SPRING) CREEK AT CT HIGHWAY M NR WAUNAKEE,WI (station ID 05427930) and SIXMILE CREEK @ COUNTY TRNK HGHWY M NR WAUNAKEE,WI (station ID 05427910).

Usage

discharge_df

Format

A data frame with 1450 rows and 2 variables:

date

date of streamflow measurement

Q_m3d

discharge, in cubic meters per day

stream

name of stream for each stream reach (Sixmile Creek or Dorn Creek)

...

Source

https://waterdata.usgs.gov/nwis/dv?referred_module=sw&agency_code=USGS&site_no=05427910

https://waterdata.usgs.gov/nwis/dv?referred_module=sw&agency_code=USGS&site_no=05427930

Streamflow depletion with fully-penetrating stream and no streambed.

Description

Streamflow depletion with fully-penetrating stream and no streambed.

Usage

glover(t, d, S, Tr)

Arguments

t

times you want output for [T]
d

distance from well to stream [L]
S

aquifer storage coefficient (specific yield if unconfined; storativity if confined)
Tr

aquifer transmissivity [L2/T]

Details

This function is described in Glover & Balmer (1954) based on work by Theis (1941). It contains numerous assumptions:

  • Horizontal flow >> vertical flow (Dupuit assumptions hold)

  • Homogeneous, isotropic aquifer

  • Constant Tr: Aquifer is confined, or if unconfined change in head is small relative to aquifer thickness

  • Stream is straight, infinitely long, and remains in hydraulic connection to aquifer

  • Constant stream stage

  • No changes in recharge due to pumping

  • No streambank storage

  • Constant pumping rate

  • Aquifer extends to infinity

  • Stream fully penetrates through aquifer (see hunt or hantush for partially penetrating stream)

  • No streambed resistance to flow (see hunt or hantush for streambed resistance)

Value

A numeric of Qf, streamflow depletion as fraction of pumping rate [-]. If the pumping rate of the well (Qw; [L3/T]) is known, you can calculate volumetric streamflow depletion [L3/T] as Qf*Qw

References

Glover, RE, and GG Balmer (1954).River Depletion Resulting from Pumping a Well near a River. Eos, Transactions American Geophysical Union 35(3): 468-70. doi:10.1029/TR035i003p00468.

Theis, CV (1941). The Effect of a Well on the Flow of a Nearby Stream. Eos, Transactions American Geophysical Union 22(3): 734-38. https://doi.org/10.1029/TR022i003p00734.

Examples

glover(t = 1.5777e8, d = 1000, S = 0.2, Tr = 0.1)   # Glover & Balmer (1954) Table 1, Well 1
glover(t = 1.5777e8, d = 5000, S = 0.2, Tr = 0.1)   # Glover & Balmer (1954) Table 1, Well 2
glover(t = 1.5777e8, d = 10000, S = 0.2, Tr = 0.1)  # Glover & Balmer (1954) Table 1, Well 3

Streamflow depletion in partially penetrating stream with semipervious streambed.

Description

Streamflow depletion in partially penetrating stream with semipervious streambed.

Usage

hantush(t, d, S, Kh, b, Kriv, briv, prec = 80)

Arguments

t

times you want output for [T]
d

distance from well to stream [L]
S

aquifer storage coefficient (specific yield if unconfined; storativity if confined)
Kh

aquifer horizontal hydraulic conductivity [L/T]
b

aquifer saturated thickness [L]
Kriv

streambed semipervious layer hydraulic conductivity [L/T]
briv

streambed semipervious layer thickness [L]
prec

precision for Rmpfr package for storing huge numbers; 80 seems to generally work but tweak this if you get weird results. Reducing this value will reduce accuracy but speed up computation time. If set to 'NULL', the 'mpfr' function is not used which can address an occasional issue on Mac computers but lead to problems under some combinations of 'Tr' and 'lmda'.

Details

This function is described in Hantush (1965). As the leakance term (b*Kh/Kriv) approaches 0 this is equivalent to glover. It contains numerous assumptions:

  • Horizontal flow >> vertical flow (Dupuit assumptions hold)

  • Homogeneous, isotropic aquifer

  • Constant Tr: Aquifer is confined, or if unconfined change in head is small relative to aquifer thickness

  • Stream is straight, infinitely long, and remains in hydraulic connection to aquifer

  • Constant stream stage

  • No changes in recharge due to pumping

  • No streambank storage

  • Constant pumping rate

  • Aquifer extends to infinity

Value

A numeric of Qf, streamflow depletion as fraction of pumping rate [-]. If the pumping rate of the well (Qw; [L3/T]) is known, you can calculate volumetric streamflow depletion [L3/T] as Qf*Qw

References

Hantush, MS (1965). Wells near Streams with Semipervious Beds. Journal of Geophysical Research 70(12): 2829-38. doi:10.1029/JZ070i012p02829.

Examples

hantush(t = 1826, d = 1000, S = 0.2, Kh = 86.4, b = 100, Kriv = 0.0864, briv = 1)

Qf <- hantush(t = seq(1, 1826), d = 1000, S = 0.2, Kh = 86.4, b = 100, Kriv = 0.0864, briv = 1)
plot(x = seq(1, 1826), y = Qf, type = "l")

Streamflow depletion in partially penetrating stream with semipervious streambed.

Description

Streamflow depletion in partially penetrating stream with semipervious streambed.

Usage

hunt(t, d, S, Tr, lmda, lmda_max = Inf, prec = 80)

Arguments

t

times you want output for [T]
d

distance from well to stream [L]
S

aquifer storage coefficient (specific yield if unconfined; storativity if confined)
Tr

aquifer transmissivity [L2/T]
lmda

streambed conductance term, lambda [L/T]. Can be estimated with streambed_conductance.
lmda_max

maximum allowed 'lmda' [L/T]. If 'lmda' is too high, exp and erfc calculations in Hunt solution are not computationally possible, so you may need to artifically reduce 'lmda' using this term.
prec

precision for Rmpfr package for storing huge numbers; 80 seems to generally work but tweak this if you get weird results. Reducing this value will reduce accuracy but speed up computation time. If set to 'NULL', the 'mpfr' function is not used which can address an occasional issue on Mac computers but lead to problems under some combinations of 'Tr' and 'lmda'.

Details

This function is described in Hunt (1999). When lmda term gets very large, this is equivalent to glover. It contains numerous assumptions:

  • Horizontal flow >> vertical flow (Dupuit assumptions hold)

  • Homogeneous, isotropic aquifer

  • Constant Tr: Aquifer is confined, or if unconfined change in head is small relative to aquifer thickness

  • Stream is straight, infinitely long, and remains in hydraulic connection to aquifer

  • Constant stream stage

  • No changes in recharge due to pumping

  • No streambank storage

  • Constant pumping rate

  • Aquifer extends to infinity

Value

A numeric of Qf, streamflow depletion as fraction of pumping rate [-]. If the pumping rate of the well (Qw; [L3/T]) is known, you can calculate volumetric streamflow depletion [L3/T] as Qf*Qw

References

Hunt, B (1999). Unsteady Stream Depletion from Ground Water Pumping. Ground Water 37 (1): 98-102. doi:10.1111/j.1745-6584.1999.tb00962.x.

Examples

hunt(t = 1826, d = 1000, S = 0.2, Tr = 8640, lmda = 864)    # ~equal to glover because lmda=Tr
hunt(t = 1826, d = 1000, S = 0.2, Tr = 8640, lmda = 0.864)  # less depletion due to lower lmda

lmda <- streambed_conductance(w = 10, Kriv = 0.0864, briv = 1) # estimate lmda
hunt(t = 1826, d = 1000, S = 0.2, Tr = 8640, lmda = lmda)

Qf <- hunt(t = seq(1, 1826), d = 1000, S = 0.2, Tr = 8640, lmda = 0.864)
plot(x = seq(1, 1826), y = Qf, type = "l")

Calculate the pumping rate at which pumping will induce infiltration from stream.

Description

Calculate the pumping rate at which pumping will induce infiltration from stream.

Usage

induce_infiltration_rate(d, Qa)

Arguments

d

distance from well to stream [L]
Qa

ambient groundwater inflow rate per unit length of stream [L2/T]

Details

This calculates the critical pumping rate above which induced infiltration due to groundwater pumping will occur, based on the glover model of streamflow depletion. Derived in Wilson (1993) Eq. 5.

Assumptions:

  • Groundwater flow is perpendicular to stream

  • Horizontal flow >> vertical flow (Dupuit assumptions hold)

  • Homogeneous, isotropic aquifer

  • Constant Tr: Aquifer is confined, or if unconfined change in head is small relative to aquifer thickness

  • Stream is straight, infinitely long, and remains in hydraulic connection to aquifer

  • Constant stream stage

  • No changes in recharge due to pumping

  • No streambank storage

  • Constant pumping rate

  • Aquifer extends to infinity

  • Stream fully penetrates through aquifer

  • No streambed resistance to flow (see hunt or hantush for streambed resistance)

Value

A numeric of Qc, critical pumping rate above which induced infiltration due to groundwater pumping will occur [L3/T].

References

Wilson, JL (1993). Induced Infiltration in Aquifers with Ambient Flow. Water Resources Research 29(10): 3503-12. doi:10.1029/93WR01393.

Examples

induce_infiltration_rate(d = 100, Qa = 10)
induce_infiltration_rate(d = 100, Qa = 50)
induce_infiltration_rate(d = 500, Qa = 50)

Calculate the critical time at which stream transitions from gaining to losing.

Description

Calculate the critical time at which stream transitions from gaining to losing.

Usage

induce_infiltration_time(d, S, Tr, Qa, Qw)

Arguments

d

distance from well to stream [L]
S

aquifer storage coefficient (specific yield if unconfined; storativity if confined)
Tr

aquifer transmissivity [L2/T]
Qa

ambient groundwater inflow rate per unit length of stream [L2/T]
Qw

well pumping rate [L3/T]

Details

This calculates the critical time at which induced infiltration due to groundwater pumping begins, based on the glover model of streamflow depletion. Derived in Chen (2003) Eq. 4.

Assumptions:

  • Groundwater flow is perpendicular to stream

  • Horizontal flow >> vertical flow (Dupuit assumptions hold)

  • Homogeneous, isotropic aquifer

  • Constant Tr: Aquifer is confined, or if unconfined change in head is small relative to aquifer thickness

  • Stream is straight, infinitely long, and remains in hydraulic connection to aquifer

  • Constant stream stage

  • No changes in recharge due to pumping

  • No streambank storage

  • Constant pumping rate

  • Aquifer extends to infinity

  • Stream fully penetrates through aquifer

  • No streambed resistance to flow (see hunt or hantush for streambed resistance)

Value

A numeric of tc, the critical time at which induced infiltration begins [T].

References

Chen, X (2003). Analysis of Pumping-Induced Stream-Aquifer Interactions for Gaining Streams. Journal of Hydrology 275(1): 1-11. doi:10.1016/S0022-1694(02)00320-7

Examples

# recreate Figure 2 in Chen (2003)
Qa <- c(0.0001, 0.0003, 0.0005, 0.0008, 0.001)
tc <- induce_infiltration_time(d = 575, S = 0.2, Tr = 100*15, Qa = Qa, Qw = 2727)
plot(x = (pi * Qa * 100 * 15 * 575 / 2727), y = tc, log = "y")

Streamflow depletion for an intermittent pumping schedule using superposition.

Description

Streamflow depletion for an intermittent pumping schedule using superposition.

Usage

intermittent_pumping(t, starts, stops, rates, method = "glover", d, S, Tr, ...)

Arguments

t

times you want output for [T]
starts

vector of times to start pumping [T] (must be same length as stops and rates)
stops

vector of times pumping stops [T] (must be same length as starts and rates)
rates

vector of pumping rates [L3/T] (must be same length as starts and stops)
method

analytical solution to use (options= 'glover', 'hunt'). Defaults to 'glover'.
d

distance from well to stream [L]
S

aquifer storage coefficient (specific yield if unconfined; storativity if confined)
Tr

aquifer transmissivity [L2/T]
...

any other inputs required for your method of choice; for example, hunt needs lmda (streambed conductance)

Details

This function superimposes wells and image wells to calculate a timeseries of streamflow depletion. Unlike the streamflow depletion models (e.g. glover, hunt) this is not fractional depletion (Qf) because there can be different pumping rates at different times.

Value

A numeric of Qs, streamflow depletion rate [L3/T].

References

Jenkins, C.T. (1968). Techniques for Computing Rate and Volume of Stream Depletion by Wells. Ground Water 6(2): 37-46. doi:10.1111/j.1745-6584.1968.tb01641.x

Examples

Qs <- intermittent_pumping(t = seq(0, 1000, 5),
 starts = seq(0, 900, 10), stops = seq(9, 909, 10), rates = seq(1, 1000, length.out=91),
 method = "hunt", d = 100, S = 0.1, Tr = 100, lmda = 10)

Qs <- intermittent_pumping(t = seq(0, 1000, 5),
 starts = seq(0, 900, 10), stops = seq(9, 909, 10), rates = seq(1, 1000, length.out=91),
 method = "hunt", d = 100, S = 0.1, Tr = 100, lmda = 100000, lmda_max = 10)

Calculate the distance from a well to each reach within a stream network. This function splits a polyline stream network up into a series of evenly spaced points and calculates the distance from each of those points to a well.

Description

Calculate the distance from a well to each reach within a stream network. This function splits a polyline stream network up into a series of evenly spaced points and calculates the distance from each of those points to a well.

Usage

prep_reach_dist(
  wel_lon,
  wel_lat,
  stream_sf,
  reach_id,
  stream_pt_spacing,
  nseed = 1
)

Arguments

wel_lon

longitude of well
wel_lat

latitude of well
stream_sf

simple feature collection of stream lines, i.e., loaded from a shapefile using sf::st_read.
reach_id

string indicating name of column in stream_sf that has the unique identifier for each stream line segment.
stream_pt_spacing

distance between points used for sampling each stream reach. The actual distance between points will be close to this (but not necessarily exact) due to sampling rounding error. The finer spacing you use, the more accurate your results will be but the function will run slower and use more memory.
nseed

seed for random number generator (this is used to convert stream polylines to points)

Value

A data frame with four columns:

reach

a grouping variable with the name of each stream reach

dist

distance of a point on that stream reach to the well of interest

lat

latitude of that point

lon

longitude of that point

This data frame can be plugged directly into apportion_inverse, apportion_polygon (if latlon=T), or apportion_web

Examples

rdll <- prep_reach_dist(wel_lon = 295500, wel_lat = 4783200,
   stream_sf = stream_lines, reach_id = "reach", stream_pt_spacing = 5)
head(rdll)

Stream network for Sixmile Creek Watershed, Wisconsin, USA. Extracted from US NHDPlus v2.1 national seamless dataset.

Description

Stream network for Sixmile Creek Watershed, Wisconsin, USA. Extracted from US NHDPlus v2.1 national seamless dataset.

Usage

stream_lines

Format

A simple feature LINESTRONG collection with 49 rows and 2 variables:

reach

identifier code for each stream reach

stream

name of stream for each stream reach (Sixmile Creek or Dorn Creek)

...

Source

http://www.horizon-systems.com/NHDPlusData/NHDPlusV21/Data/NationalData/

Estimate streambed conductance.

Description

Estimate streambed conductance.

Usage

streambed_conductance(w, Kriv, briv)

Arguments

w

stream width [L]
Kriv

streambed semipervious layer hydraulic conductivity [L/T]. Reeves et al. (2009) estimate this as the vertical hydraulic conductivity of the aquifer (Kv; L/T), which is itself often estimated as 10% of the horizontal hydraulic conductivity (Kh*0.1; L/T)
briv

streambed semipervious layer thickness [L] Reeves et al. (2009) estimate this as the vertical distance from the streambed to the top of the well screen, or the length of the well screen, whichever is greater [L].

Value

A numeric of lmda, the streambed conductance term [L/T]

References

Reeves, HW, DA Hamilton, PW Seelbach, and AJ Asher (2009). Ground-Water-Withdrawal Component of the Michigan Water-Withdrawal Screening Tool. USGS Scientific Investigations Report, Reston VA. https://pubs.usgs.gov/sir/2009/5003/.

Examples

streambed_conductance(w = 10, Kriv = 0.0864, briv = 1)
streambed_conductance(w = 5, Kriv = 0.0864, briv = 1)
streambed_conductance(w = 10, Kriv = 0.864, briv = 1)
streambed_conductance(w = 10, Kriv = 0.0864, briv = 0.1)