This repository contains the figures, source code and animations of the article "Coupled model for assessing the future vulnerability of watersheds to climate change impacts using deterministic model and neural networks". Gnuplot, Julia and R languages were used for plotting the results of simulation.
Correlations of precipitation for station 11095, for every GCM. View more.
Correlations of precipitation for station 11095 for CSIRO-Mk3-6-0 precipitations after downscaling with ANN (training and validation). View more.
Training period. View more.
Validation period and RCP4.5, RCP6.0 and RCP8.5 scenarios. View more.
The next figures are examples of uncertainty and variation ranges in Monte Carlo simulation, for station 11099.
Uncertainty using random generator 1. View more.
Uncertainty using random generator 2. View more.
Boxplot random generator 1.View more.
Boxplot random generator 2.View more.
The following figures are examples of statistics that describe the accuracy of ANN predictions during simulation and using random generator 2, for station 11099.
R coefficient. View more.
Bias. View more.
Calibration period. View more.
Validation period. View more.
Global vulnerability in the Turbio River sub-basin in 2014.View vulnerabilities in 2035.
Boxplot for global vulnerability from 2015 to 2035 for the RCP6.0 scenario.View more.
Cummulative area distribution occupied by the global vulnerability for the RCP6.0 scenario. View more.
This folder have animated GIFs of the simulation of global vulnerability for RCP4.5, RCP6.0 and RCP8.5 scenarios. View more.
This folder contains the scripts to generate the figures.
Scripts to generate GCM correlations
Scripts to generate CSIRO correlations
Scripts to plot Monte Carlo results
Scripts to plot vulnerability maps
This folder contains the databases and maps in ASCII format needed to build the figures.