Systems dynamic modeling on sustainable apples agriculture

History shows the long process of apple plants originating from subtropical regions adapting to Indonesia's tropical climate until its popularity is increasingly marginalized and replaced with other commodities, as evidenced by the decreasing land area, especially in Batu City. Indonesia. In developing and analyzing solutions based on the principles of sustainable development, an integrated and holistic approach is required. To understand problems and find solutions, we can use Systems dynamics. The purpose of this study is to obtain a policy scenario that encourages sustainable apple farming. Data is collected from the local government and BPS City or Province so that the selected variables follow the specific location. The system approach is used to identify needs, problem formulation, preparation of input-output diagrams, cause-effect diagrams and stock-flow diagrams. A series of scenarios is created and tested through simulation to understand the system's dynamic behavior better and obtain the desired output. The best scenario was chosen, namely by replanting 10% of old plant each year, using integrated agriculture with 3 female and 1 male brooders, reduction of land change with 50% success, Local economic development by integrating tourist ticket and hotels with 0,75 kg apple fruits also increasing health support for students

Modeling electricity supply in a small island: A case study in Sebira island, Indonesia

Sebira is a small island located at the northernmost of the Thousand Islands, Indonesia. The Electricity supply at the island uses an isolated network system for its territory. This study aims to model a system of electrical energy supply in Sebira Island. We explore literature studies related to the electricity supply system to support our model to be more representative. We then describe the system with a Causal Loop Diagram and a Stock Flow Diagram. The current electricity supply comes from solar power plants 400 kWp and three units diesel power plants with capacities of 125 kVA (2 units) and 250 kVA (1 unit). In this model, we consider the variables of population growth, initial investment, electricity shortages, fuel costs, profits, and margins. Furthermore, we create two scenarios in the simulation, with and without additional wave energy. The results show that in a sufficiently long period, the second scenario (with extra wave energy) is more profitable for the electricity supply in Sebira Island; however, it requires more initial investment than the first scenario.

Resource competition and technological diversity

The work develops and investigates a mathematical model for evolution of the technological structure of an economic system where different technologies compete for the common essential resources. The model is represented by a system of consumer–resource rate equations. Consumers are technologies formalized as populations of weakly differentiated firms producing a similar commodity with like average output. Firms are characterized by the Leontief–Liebig production function in stock-flow representation. Firms self-replicate with a rate proportional to production output of the respective technology and dissolve with a constant rate of decay. The resources are supplied to the system from outside and consumed by concerned technologies; the unutilized resource amounts are removed elsewhere. The inverse of a per firm break-even resource availability is proposed to serve as a measure for competitiveness towards a given resource. The necessary conditions for coexistence of different technologies are derived, according to which each contender must be a superior competitor for one specific resource and an inferior competitor for the others. The model yields a version of the principle of competitive exclusion: in a steady state, the number of competing technologies cannot exceed the number of limiting resources. Competitive outcomes (either dominance or coexistence) in the general system of multiple technologies feeding on multiple essential resources are shown to be predictable from knowledge of the resource-dependent consumption and growth rates of each technological population taken alone. The proposed model of exploitative competition with explicit resource dynamics enables more profound insight into the patterns of technological change as opposed to conventional mainstream models of innovation diffusion.

Identifying Climate Adjacency for Enhancing Climate Action Using Systems Thinking and Modelling

This paper presents findings from a process aimed at identifying the climate linkages of non-climate focused environment and development projects in India. Findings from four case studies based on workshops using participatory systems thinking are summarized. These climate adjacencies are documented as systems stories using the tools of systems thinking—behavior over time graphs and causal loop diagrams. These place-based stories highlight how the environment and development projects have linkages with climate change mitigation and adaptation. An attempt has been made to convert one of the systems stories into a computable simulation model using system dynamics modelling. A small concept model has been created thus and used to perform simulation runs. Four scenarios have been generated and the results discussed. Our learning from converting feedback maps into stock-flow models is presented. The insights generated from interpreting the feedback maps and simulation results are also presented. These insights are then compared and the benefits of simulation evaluated. The paper highlights the need to document climate linkages of non-climate-focused development projects and the benefit of converting systems stories into simulation models for developing operational insights. The important role such methods can play in developing capacities for enhancing climate action is also discussed.

System dynamics kinetic model for predicting biogas production in anaerobic condition: Preliminary assessment

Introduction: This preliminary assessment of a grey-box model, was predicated on system dynamics principles and developed using Vensim® DSS software. The purpose is to predict biogas production under anaerobic conditions for energy utilization at the design stage. Objective: To describe the process of a developed system dynamics model to predict biogas production under anaerobic conditions. Methods: This method involves two-stage kinetics of the biogas production process in anaerobic conditions using the first-order and Gompertz functions. The model is depicted in two parts: causal loop diagram and stock–flow diagram. The causal loop diagram describes the anaerobic digestion process a substrate undergoes for the production of biogas, while stock–flow diagram depicts basic building blocks of the dynamic behavior of an anaerobic digestion process. Primary data is from a laboratory-scale experiment of biogas production using vegetal wastes, while the secondary one is from the literature on studies using similar substrates. Results: Primary and secondary data are used to validate and stimulate the developed model. The kinetic model shows the substrate being reduced exponentially with increasing time; consumption of substrate and production of methane and carbon dioxide follows exponential growth and decay pattern, with carbon dioxide production starting early compared to methane, and was produced at a rate faster due to the strong and resilient characteristics of fermentative microorganisms. Discussion: Comparing data from empirical and model simulation shows some close relationship, though not too perfectly. Both results reflect signs of inhibitions occurring within the substrates in the digester under anaerobic conditions explaining the low methane yield or instability.