mohammad javad anbari

Excessive water extraction from aquifers in arid and semi-arid areas poses a serious threat to natural resources and the environment. Damghan's critical forbidden plain has faced a drop in groundwater level in recent years. In this study, the agent-based model has been used to simulate the behavior of effective stakeholders in the region. First, the agent-based model is considered based on the key stakeholders of the region (farmers are the most important consumers of groundwater in the region, Regional Water Company and Agriculture- Jahad), characteristics, behavior, characteristics of the environment, how the interaction between the agents and the environment (Damghan aquifer). Information about exploitation wells and characteristics of the dominant cultivation in the region is related to 1397. To identify the behavior and characteristics of the agents, a visit to the area and interviews with experts and farmers have been done. The characteristics, behaviors, and interactions of agents are expressed by if-then rules or logical operators or by formulated equations. Then, management scenarios in the study area have been studied for 10 years. The results show that the simultaneous implementation of four projects of installing smart meters, modifying well licenses, promoting new irrigation systems, and establishing production cooperatives while maintaining farmers' net incomes will reduce water withdrawal 44% compared to the base scenario. Also, as a result of the implementation of these four projects, the irrigation method of 4000 hectares of agricultural lands will be changed to pressurized irrigation.

Regarding the supply of large amount of water demand from groundwater resources on the one hand, and increasing water level drop of the aquifers on the other hand, the importance of groundwater resources management is significantly increasing. Due to the complexities in the socio-ecological systems related to the groundwater resources, there is a need for tools to model these complexities in the form of effective agents’ relations. Agent-based modeling (ABM) is a computer simulation with a comprehensive approach of stakeholders, or agents that interact with each other and with their environment based on certain behavioral principles. In this paper, farmers, effective institutional agents and aquifer behaviors and their interactions in the Shabestar-Sofian plain is modeled using ABM with stakeholder participation through interviews and semi-structured questionnaires. The results of the implementation of five sample scenarios show that if the institutions are properly coordinated and the participation of farmers is attracted, it could be possible to reduce 202 million cubic meters of wells extraction over 10 years, in addition to increasing the income of farmers simultaneously and to compensate about 40 percent of negative groundwater balance. Using this model, a better understanding of the sophisticated system of groundwater resources management can be obtained, stakeholder participation can be attracted, and by defining scenarios in a participatory process, better solutions can be achieved in the decision-making process.

Wastewater systems form an important urban infrastructure that are used for the collection and treatment of wastewater for return into the environment or water reuse. The sewers network in this system forms its most important component, any failure in which may lead to adverse consequences and disruption in urban life. Proper functioning of a sewers network depends on its operation and maintenance (O&M) program that requires timely inspections to identify the high risk sewers with any likelihood of failure in order to gurantee the sustained and sound performance of the whole network. In this study, the Bayesian network is used to develop a model for calculating failure event probability in wastewater collection systems. Given the capabilities of the Bayesian network and the characteristic features of the sewers network, the proposed model is capable of predicting likely failure events. The procedure used for model implementation consists of the following four main steps: preparation of model inputs, training the Bayesian network, validation of the trained network, and receiving output results. To illustrate the application of this method, part of Tehran wastewater collection system is selected as a case study and failure probabilities are calculated. Based on the model results, Tehran sewers can be divided into five categories priotized according to inspection and maintenance requirements. The results indicate that the probability of failure for most of the existing sewers is very low and low (37%) or moderate (60%) due to the newly annexed sewers in the collection system.