ms_fill_missing_precip: Fill gaps in precipitation gauge data
In MacroSHEDS/macrosheds: Tools for interfacing with the MacroSheds dataset

ms_fill_missing_precip

R Documentation

Fill gaps in precipitation gauge data

Fill precipitation gauges based on relationship to surrounding gauges.

ms_fill_missing_precip(
  precip,
  precip_gauge,
  fill_method = "strongest_cor",
  distance_threshold = NULL,
  out_path = NULL,
  verbose = TRUE
)

`precip`	`data.frame`. A `data.frame` or path to `data.frame` in macrosheds format of precipitation gauge data
`precip_gauge`	a sf object or path to a sf object of precipitation gauge locations
`fill_method`	One of strongest_cor, closest_gauge, or distance_weight. See details
`distance_threshold`	When distance_weight is selected, the distance in km other gauges will be used to fill each gauge of interest
`out_path`	Optional. path to save filled precipitation data
`verbose`	Optional logical. Should information be printed to console, default TRUE.

ms_fill_missing_precip uses other gauges in a network to fill gaps in gauges when they are not reported data. Three different methods can be chosen.

strongest_cor uses the gauge with the strongest correlation to the gauge with missing data, and then uses a linear regression between the two gauges to fill in times of missing data. 2) closest_gauge uses a linear regression between the nearest gauge to the gauge with missing data. 3) distance_weight uses all gauges withing the selected distance_threshold and inverse distance weighting to fill the missing values.