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Command and Control ABM

The command and control policy in natural resource management, including water resources, is a
longstanding established policy that has been theoretically and practically argued from the point
of view of social-ecological complex systems. With the intention of making a system ecologically resilient, policymakers apply the top-down policies of controlling communities through regulations. To explore how these policies may work and understand whether the ecological goal can be achieved via command and control polices, this research uses the capacity of Agent-Based Modeling (ABM) as an experimental platform in the Urmia Lake Basin (ULB) in Iran, which is a social-ecological complex system and has gone through a drought process.

Despite the uncertainty of the restorability capacity of the lake, there has been a consensus on the possibility to artificially restore the lake through the nationally managed Urmia Lake Program (ULRP). To reduce water consumption in the Basin, the ULRP widely targets the agricultural sector and proposes the project of changing crop patterns from high-water-demand (HWD) to low-water-demand (LWD), which includes a component to control water consumption by establishing water-police forces.

Using a wide range of multidisciplinary studies about Urmia Lake at the Basin and sub-basins as well as qualitative information at micro-level as the main conceptual sources for the ABM, the findings under different strategies indicate that targeting crop patterns change by legally limiting farmers’ access to water could force farmers to change their crop patterns for a short period of time as long as the number of police constantly increases. However, it is not a sustainable policy for either changing the crop patterns nor restoring the lake.

Thank you for the presetation Farzaneh. Since you started the presentation on Urmia Lake Basin, I wondered how you will use empirical data from your case from your study in the modeling effort. At the moment the model is rather abstract. Do you plan to have an empirically validated model, or do you have broader research questions related to irrigated agriculture that could be applied to other parts of the world.

Thanks Marco for your attention to the Urmia Lake Basin case. Your questions about the input data, validation of the model, and the plan for a broader research on irrigated agriculture are very valuable. And they present the great opportunity that I can elaborate some of the unique challenges that I faced for this project.

As the background of the model, I have to state that, as you may know, Urmia Lake Basin received a great international attention in both academic and practical research and more than ten international universities carried out deep studies in collaboration with top universities as well as organizations at national and local levels in Iran. I have studied the Basin with different purposes in last three years. For example, I reviewed Agricultural Land Use Scenario Development Method in the Basin to understand whether the applied method was suitable for the complexity of social-ecological system of Urmia Lake. Or I studied the probability that Urmia Lake could be restored through the Restoration Program and modelled the adaptability of social-ecological complex system of Urmia Lake. However, in my studies I found out that there was nearly no studies at individual behavioral level. Only recently a narrative study was carried out by Sharif University with a very specific objective that made it difficult to use for different purposes. Even though the Command-And-Control ABM doesn’t have any direct input data, it is built on all these studies plus my own personal informal studies in the area. Therefore, I believe I have used empirical data from my studies. I would be curious if you can suggest any other ideas about the empirical data?

Regarding the empirically validating the model, besides the internal validation of the model as an exploratory that can be found in the presented paper, I would like to explain two types of information that I believe can be considered as the informal empirical validation of the model. One of them is the support that the model received in the presentation in Iran. Besides the model objectives, my personal objective of programing the Command-And-Control ABM was to present the capacity of Agent-Based Models to policy makers, academia, as well as communities in Iran in order to encourage them to carry out a participatory Agent-Based Modeling for resilience building in the Basin because based on my earlier studies the successfulness of the Urmia Lake Restoration program was sensitive to early participation and resilience building process. When I presented the Command-And-Control model in several universities and organizations at the national level it was praised. The most interesting reactions were observed at the local level. When the model was presented at the local meetings, where the experts from different communities and organizations were attending, the participants started to support the model by giving the information. For example, they explained that some of the water-polices that were recruited from the same communities ignored that people were taking extra water or digging wells. Or, some of those who were recruited from outside of the community accepted bribes to ignore the illegal water pickup. Also, it was told that some of the water-polices didn’t work effectively. All of them have been seen in the model as the water- police efficiency and whether farmers are at the vision of water-polices. Also, the photos and data were published and showed how farmers took surface water even in the places where smart control systems were installed and how many times wells were closed, yet farmers tried to dig wells again, all supported the relationships within the model. The second type of information that I believe practically validated the model was some of the published information about the result of water-police policy. For example, according to Urmia Lake Restoration Program (ULRP), in 2014 the numbers of water-police stations, which were established in three provinces of the Basin, were 9 in East Azerbaijan, 30 in West Azerbaijan, and 22 in Kurdistan. The latest report indicated that the number of police stations had been increased to 280. In the roundtable discussion with IRNA news agency, the head of the Water Department in East Azerbaijan said that they had started with 12 water-police in 2012 but their numbers had to be increased to 320 in 2018. As you may have noticed, in the model I started with 10 water-police stations and water-polices are deployed one by one randomly from each station until the policy goal is met. Therefore, the model starts with 10 water-police. In the satisfactory policy option, the number of water-police increases up to 300-400 and plays around that numbers. In the extreme policy, the number of water-polices increases up to several times of farmers and makes the farmlands a battle field, still the objective of the policy cannot be met. I am curious to know if you also consider these the empirical validation of the model. Do you have any other suggestions?

For the matter of broader research questions, I would like to say that I had expanded the model by adding the agricultural extension network as one of the other policy component of the ULRP. Moreover, I have been working to model the resilience process through learning and self-organizing. I wish I could have programed it as a participatory ABM, but unfortunately due to high political, social, and economic tension in the region and the country, I am programing it in abstract form and hoping to use it to encourage for participatory model later.

I hope I was able to answer your question and I look forward to further discussions.