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ZENODO
Dataset . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2024
License: CC BY
Data sources: Datacite
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Data and Software for "Probabilistic Trade-offs Analysis for Sustainable and Equitable Management of Climate-Induced Water Risks"

Authors: Baccour, Safa; Tilmant, Amaury; Albiac, Jose; Espanmanesh, Vahid; Kahil, Taher;

Data and Software for "Probabilistic Trade-offs Analysis for Sustainable and Equitable Management of Climate-Induced Water Risks"

Abstract

Research data supporting the study "Probabilistic trade-offs analysis for sustainable and equitable management of climate-induced water risks" This repository provides data of the Stochastic Dual Dynamic Programming (SDDP) model, and the output results of the simulations of the various policies and climate scenarios considered in this study, as well as the code used for postprocessing and visualizing the results. Contents Data: Model InputsThis folder contains the physical river network, reservoir and water demand, and economic data derived from the observed database.The key files are: Input_HydrologicalData Input_SystemData Results: Model Output AnalysisThis folder includes outputs from the Stochastic Dual Dynamic Programming (SDDP) model under various policies and climate scenarios. The results showcase optimized sectoral water use, including irrigated areas, hydropower generation, and allocations for agriculture, energy, and urban demands across spatial locations (upstream and downstream).Key files include: SDDP Model Outputs (MATLAB format): EnergyPriority_Baseline.mat EnergyPriority_2070.mat EnergyPriority_2100.mat AgriculturePriority_Baseline.mat AgriculturePriority_2070.mat AgriculturePriority_2100.mat Extracted Model Results (Excel format): Organized for each policy and climate scenario to facilitate analysis. Software: Data Analysis and VisualizationPython scripts designed for outputs data analysis and visualization are included to reproduce the primary figures from the study.Scripts provided: CDF_outflow.py: Analyzes cumulative distribution functions for river discharge. CDF_sectors.py: Examines sectoral water use distributions. PCP_SI.py: Generates Parallel Coordinate Plots for trade-offs analysis. Instructions: README FileA comprehensive README file explains: Details of model input data. Instructions to interpret the SDDP model outputs. Instructions:The Python scripts process Excel files from the model output results folder to generate and visualize the figures for the paper. Each step is clearly documented within the scripts.

Keywords

Water management, Tradeoffs analysis, Stochastic optimization, River basin modelling, Water policy

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
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