This repository contains the working code for the “Implementing the 2030 Agenda for water efficiency/productivity and water sustainability in NENA countries” project. The project is funded by the UN Food and Agricultural Organization, KTH is providing analyses and support on decision making across the climate, land, energy and water spheres in Morocco and Jordan.
The Nexus analysis developed for the Jordan and the Moroccan Souss-Massa basin cases, softlinks a water balance model developed by SEI and the countries stakeholders using the Water Evaluation and Planning system (WEAP), and the GIS-based energy model developed by KTH. The model uses WEAP for estimating water supplies based on climate-driven hydrological routines that calculate rainfall runoff and groundwater recharge. It estimates usage patterns for the main water sectors, evaluates the productivity of cropping systems under different climate futures and assess their impact on energy and water systems. Furthermore, the energy component implements GIS-based methodologies to estimate energy requirements for groundwater and surface water pumping, new water desalination projects and major wastewater treatment plants. Finally, solar PV pumping is evaluated as a clean option to supply electricity for the agricultural sector.
To install the required dependencies, install the miniconda or conda package
manager and create two conda environments running
conda env create -n <name-of-environment> -f envs/notebook.yml and
conda env create -n <name-of-environment> -f envs/snakemake.yml in the conda
shell or git bash (replace <name-of-environment> by a custom name for your
environment). Afterwards, activate the environment with conda activate <name-of-environment>.
The notebook environment is intended to run the standalone jupyter notebooks,
provided for each step of the model. While the snakemake environment is intended
for running the entire automated workflow of the project.
To run the model, first activate the previously created conda environment for
notebooks by running conda activate <name-of-environment> and then type
jupyter notebook. Alternatively, you can start the Anaconda navigator,
select the previously created environment and start a Jupyter notebook session.
Open any of the runner files of either model and follow the steps.
Activate the previously created conda environment for snakemake by running
conda activate <name-of-environment>. Then open the snakemake file of the
model you wish to run and set the user inputs to the ones desired:
######################### User defined parameters #############################
dash_folder = "dashboard" #set the dashboard folder
CLIMATE = ['Trend', 'Climate Change'] #define the list of climates to run
SCENARIOS = ['Reference', 'Desalination','Irrigation Intensification', 'Reference Wastewater Reuse', 'Desalination Wastewater Reuse']
W_RATE = [0]
BT_RATE = [0]
PV_RATE = [0]
GRID_RATE = [0]
PV_LEVELS = [10, 20, 50]
BUTANE_PHASEOUT_SCENARIOS = [None, 2040, 2030]
###############################################################################Run snakemake -s Morocco\ model/snakefile -n for a dry run (of the Moroccan
case). This will list all of the different jobs the workflow would run, without
actually running anything.
Finally, run snakemake -s Morocco\ model/snakefile -j to run all of the listed jobs.
Results for te case studies of Jordan and the Souss-Massa river basin, can be explored through interactive dashboards found in:
For exploration of results locally, you can run the visualization from your
machine in a local host by running python Morocco\ model/dashboard/index.py
(for the Moroccan case) and going to http://localhost:8080/ in your browser.
Notice that you would need to create and environment using one of the environment.yml
files found inside each case dashboard folder, and activate it before running the
dashboard locally.
Conceptualization: Youssef Almulla, Camilo Ramirez, Brian Joyce, Annette Huber-Lee
and Francesco Fuso-Nerini
Methodology: Youssef Almulla and Camilo Ramirez on the energy model, Youssef Almulla on the decarbonization strategies of the agricultural sector, Camilo Ramirez on the softlinking of models, Brian Joyce on the water-agriculture (WEAP-MABIA) model, all on the participatory approach and overall Nexus approach
Software: Camilo Ramirez & Youssef Almulla
Management and Advisory support: Annette Huber-Lee & Francesco Fuso-Nerini
Acknowledgements
We would like to acknowledge the Food and Agricultural Organization (FAO), the Jordan Ministry of Water and Irrigation, the Regional Office for Agricultural Development in Souss-Massa (ORMVA), and a special thanks goes to Domitille Vallee and Jiro Ariyama (FAO), and Prof. Lahcen Kenny (FAO consultant) for their valuable contribution to this work by providing many of the input data and validating modelling assumptions.