Computational Model Library

Displaying 7 of 7 results for 'Rabindra Nepal'

Nepali Village Model

John Janmaat Suzan L Lapp | Published Thursday, April 17, 2014

The model implements a model that reflects features of a rural hill village in Nepal. Key features of the model include water storage, social capital and migration of household members who then send remittances back to the village.

The purpose of the AdaptPumpa model is to analyze the robustness of the Pumpa irrigation system in Nepal to climate change.

Peer reviewed Pumpa irrigation model

Irene Perez Ibarra Marco Janssen | Published Wednesday, January 09, 2013 | Last modified Saturday, April 27, 2013

This is a replication of the Pumpa model that simulates the Pumpa Irrigation System in Nepal (Cifdaloz et al., 2010).

Land Use in the Chitwan Valley

Alex Zvoleff | Published Monday, June 02, 2014

chitwanabm is a spatially explicit agent-based model of population and land use in the Chitwan Valley, Nepal, designed to explore feedbacks between population and environment, with a heavy focus on community context and individual-level variation.

Peer reviewed Agent-based Renewables model for Integrated Sustainable Energy (ARISE)

Muhammad Indra Al Irsyad Anthony Halog Rabindra Nepal | Published Wednesday, November 29, 2017 | Last modified Friday, October 05, 2018

ARISE is a hybrid energy model incorporating macroeconomic data, micro socio-economic data, engineering data and environmental data. This version of ARISE can simulate scenarios of solar energy policy for Indonesia case.

Institutional change

Abigail Sullivan | Published Friday, October 07, 2016 | Last modified Sunday, December 02, 2018

This model builds on another model in this library (“diffusion of culture”).

PowerGen-ABM is an optimisation model for power plant expansions from 2010 to 2025 with Indonesian electricity systems as the case study. PowerGen-ABM integrates three approaches: techno-economic analysis (TEA), linear programming (LP), and input-output analysis (IOA) and environmental analysis. TEA is based on the revenue requirement (RR) formula by UCDavis (2016), and the environmental analysis accounts for resource consumption (i.e., steel, concrete, aluminium, and energy) and carbon dioxide equivalent (CO2e) emissions during the construction and operational stages of power plants.

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