README.md

SpatIndex

Spatial indices to monitor droughts and global change

This R package provides a simple way of computing spatially-distributed drought and extreme indices. The users can compute meteorological, agricultural, and hydrological indices as well as the extreme CLIMDEX indices by providing raster files of the required hydroclimatological variables. The drought and extreme indices that are implemented in SpatIndex are summarised in the following figure:

Installation

First, the spatstat.core package must be installed:

remotes::install_github("spatstat/spatstat.core")

Then, install the development version from GitHub:

remotes::install_github("obaezvil/SpatIndex")

Drought analysis

The drought indices implemented in the SpatIndex package are:

| Index | Function name | |----------------------------------------------------------|----------------------| | Percent of Normal Precipitation | spatial_pni() | | Deciles | spatial_deciles() | | Standardised Precipitation Index | spatial_spi() | | Standardised Precipitation Evapotranspiration Index | spatial_spei() | | Vegetation Condition Index | spatial_vci() | | Temperature Condition Index | spatial_tci() | | Vegetation Health Index | spatial_vhi() | | Empirical Standardised Soil Moisture Index | spatial_essmi() | | z-score (can be used with multiple variables) | spatial_zscore(ยด) | | Combined Drought Index | spatial_cdi() | | Standardised Streamflow Index | ssi() | | Standardised Snow Water Equivalent Index | spatial_swei() |

If the user wants to calculate the SPI-12 using the reference period 1981--2010, they could do it as follows:

spi_12 <- spatial_spi(P_data, scale = 12,  ref_start = "1981-01", ref_end = "2010-12")

Where:

The following figure shows the spatially distributed SPI-12 values over Chile for 2013 using CR2METv2.5:

This package is very useful to apply diverse drought indices using multiple gridded datasets. As an example, the next figure shows diverse hydrological (SSI and SWEI), agricultural (VCI, VHI, and ESSMI), and meteorological (Percent of Normal and Deciles) indices. These indices were calculated using diverse datasets over the Tascadero catchment (241 km$^2$) in Chile.

Extreme events analysis

These functions have the same name as the indices. For example, if the user wants to calculate the maximum 1-day precipitation (Rx1day):

rx1day <- Rx1day(rst.path, vct = NULL,  temporal.scale = c("total", "annual"),
                  start.date,  end.date,  date.fmt = "%Y-%m-%d",  pattern = NULL)

Where:

An example of the implementation of Rx1day over Sub-Saharan Africa for 1981--2021 can be observed in the following Figure:

Vignette

An introductory vignette on how to use the SpatIndex package and how to use its functions is coming soon!



obaezvil/SpatIndex documentation built on Aug. 9, 2024, 3:42 p.m.