| Drought Index from Parameters {SPIGA} | R Documentation |
Calculation of standardized precipitation index from alpha and beta parameter of the Gamma function.
Description
calculate the standardized precipitation index, from alpha and beta parameter of the Gamma function.
Usage
SPIFromParameters(Pmon, scale =3, Param_Alpha, Param_Beta)
Arguments
Pmon |
monthly precipitation series ordered according to time. It is a data frame with columns: year, month, station 1, station 2, etc. |
scale |
an integer value representing the time scale of analysis. The most common are 1, 3, 6, 9, 12, 48, etc. |
Param_Alpha |
data frame monthly data values corresponding to the alpha parameter to the function Gamma. |
Param_Beta |
data frame monthly data values corresponding to the alpha parameter to the function Gamma. |
Details
Analysis stations are in the columns of dataframe. the apha and beta parameters, are monthly and are in the rows of dataframe.
Input data
similar to Pm_Pisco.
| Mon | st_1 | st_1 | st_2 | st_3 |
| Jan | 9.584860915 | 9.227918987 | 10.35269003 | 8.433823824 |
| Feb | 13.76378505 | 15.02620223 | 12.1021093 | 10.85133914 |
| Mar | 26.09112343 | 17.41749632 | 21.10924889 | 23.53649421 |
| Apr | 17.34996675 | 17.4451073 | 13.00894394 | 16.66595319 |
| May | 9.943259493 | 9.46815537 | 9.164645239 | 9.455850664 |
| Jun | 5.103175852 | 5.041710686 | 4.080851346 | 5.790986084 |
| Jul | 2.85804336 | 3.042484994 | 2.797962575 | 2.645188236 |
| Aug | 3.033862506 | 3.183267843 | 3.435303986 | 2.631287947 |
| Sep | 3.815308513 | 2.627317533 | 3.550365645 | 3.66482456 |
| Oct | 7.430925356 | 3.956716609 | 7.023105167 | 7.540706878 |
| Nov | 6.303310502 | 5.339943557 | 6.358902249 | 5.556660824 |
| Dec | 5.84110559 | 5.899534971 | 6.581657735 | 4.889599504 |
Value
return values of standardized precipitation index in .txt formats.
Author(s)
Iván Arturo Ayala Bizarro <ivan.ayala@unh.edu.pe>
Jessica Zúñiga Mendoza <zumeje@gmail.com>
References
McKee, Thomas B. and Doesken, Nolan J. and Kleist, John. 1993. The relationship of Drought Frecuency and Duration to Time Scales. Eighth Conference on Applied Climatology
A. Belauneh and J. Adamowski. Standard Precipitation Index Drought Forecasting Using Neural Networks, Wavelet Neural Networks, and Support Vector Regression. Applied Computational Intelligence and Soft Computing, http://dx.doi.org/10.1155/2012/794061
Examples
#### Load data
data(Pm_Pisco)
data(alphaGA_SPI3)
data(betaGA_SPI3)
#### Computing SPI with Genetic Algorithms
Pmon<-Pm_Pisco
Param_Alpha <- alphaGA_SPI3
Param_Beta <- betaGA_SPI3
SPIFromParameters(Pmon, scale =3, Param_Alpha, Param_Beta)