The human-water system, exemplified by irrigation systems, can be viewed as a highly intricate adaptive system that emerges from the dynamic and continuous interplay of environmental and societal elements over time and space. A thorough examination of the interconnections between humans, water resources, crops, and hydraulic infrastructure in the practice of irrigation management could yield profound insights into how irrigation systems function. Southern Mesopotamia boasts renowned, advanced irrigation systems that have supported the development of vast urban centers. Nevertheless, the historical workings and evolution of these irrigation systems in Southern Mesopotamia remain shrouded in mystery. It is imperative to explicitly address the interplay between human activities and the water system when investigating the development of irrigation systems and the landscapes they nurture. In this thesis, I propose that a systematic exploration of the evolution of irrigation systems, progressing from small-scale to large-scale, from short-term to long-term, and from individual to collective, can provide a deeper comprehension of the intertwined environmental and societal dimensions of irrigation systems in Southern Mesopotamia. This exploration offers invaluable insights into understanding the co-evolutionary history of the environment and human society. To this end, I have developed an Agent-Based Model Framework with three model versions from the vantage points of human agents, hydrology, and hydraulics to simulate the irrigation systems in Southern Mesopotamia. The first model version, the Irrigation-Related Agent-Based Model (IRABM), simulates the key functions of irrigation actions across various scenarios, infusing water realism and human realism into the agent-based model (ABM), thereby representing human-water interactions. This study primarily focuses on water distribution through the manipulation of hydraulic infrastructure and human-made strategies. The IRABM serves as a platform for the integration of human and non-human agents, facilitating actions and interactions among model agents. Furthermore, this theoretically and empirically informed computer model can offer fresh insights into the simulation of human-water systems, elucidating the emergence of irrigation patterns and yields from a dynamic environment. The second model version, the Advanced Irrigation-Related Agent-Based Model (AI- RABM), in contrast to the IRABM, incorporates learning behaviors, decision-making processes, and mechanisms at both the individual farmer and irrigation system levels. This model contributes to our understanding of the decision-making processes and mechanisms at both individual and collective levels, particularly concerning water conflicts among farmers in irrigation management. It also guides efforts to enhance communication and cooperation among farmers to optimize irrigation system performance. The model retains flexibility in the parameters, enabling its application to various irrigation systems worldwide. In comparison to the IRABM and AIRABM, the third version of Irrigation-Related Agent-Based Model (IRABM3) maintains the core components of individual decision-making regarding farmland dynamics and collective decision-making in irrigation management. Through a comprehensive computational approach, including sensitivity analysis and Gini coefficient evaluation, I investigate the emergence of patterns in irrigation systems under diverse scenarios of water availability and the decisions made by heterogeneous agents. This allows for the discussion of the potential processes involved in the development of ancient societies in Southern Mesopotamia. Moreover, the IRABM3 offers adaptability to accommodate spatial and temporal variations within the irrigation system. This adaptability permits the exploration of irrigation-based societies in ancient Southern Mesopotamia on a larger scale, contributing to a broader understanding of the intricate dynamics at play in these societies. Furthermore, IRABM3 forms a foundation for future research by incorporating additional agents into the irrigation system, facilitating a more comprehensive grasp of the evolutionary dynamics of irrigation systems in ancient Southern Mesopotamia and providing researchers with a powerful tool for further investigation. These three models, presented in this series, demonstrate the potential and reliability of using ABM to simulate the operation of irrigation systems. They enable the interaction, adaptation, and decision-making of agents in response to changing parameters, such as river discharge, gate capacity, various water allocation strategies, and learning behaviors. They make a significant contribution to the study of the development of irrigation systems, both in Southern Mesopotamia and in irrigation systems worldwide.@en

Early Southern Mesopotamia shows a complex history of expansion of (irrigated) farming in relation to urban developments and changing landscapes. As a first step to study expanding irrigated farming system, an irrigation-related agent-based model was developed to explore farm(land)s and irrigation systems in relation to decision-making processes, both of farms and their farmlands (an agriculture unit) and collective decision-making processes for irrigation system management—especially sharing water between farms. The decision-making processes include options to move farms, expand the system, or start a new system, as these would be options available for Mesopotamian farmers as well. In this text, we report how model parameters contribute to the generation of various patterns of yields and expansion of farms and system. Additionally, the Gini coefficient (based on yields) is applied to estimate levels of inequality among farmers. Our results show how (1) human decision-making determines the level of influence of and benefits for farms, as well as the overall irrigation system; (2) Gini values effectively capture the degree of inequality in yields among farms based on water availability; and (3) our model is a suitable base for further study, by incorporating additional agents into the irrigation system and expanding the spatial–temporal scales of the irrigated landscapes, to reach a more comprehensive understanding of the evolutionary dynamics of irrigation systems in Southern Mesopotamia.

@en

Often, individual, communal, regional, or even national conflicts arise when water resources are shared and used. For equitable water-sharing strategies to be implemented, adequate collective action is required to allocate water – not limited to, but specifically in irrigation systems. In this research, we develop an Advanced Irrigation-Related Agent-Based Model (AIRABM) to explore issues of unequal access to water in relation to water use on farm and system levels. By simulating farmer activities and system management decisions within an irrigation system, our research aims to explore farmland dynamics in response to different levels of decision-making according to water availability. We incorporate both individual and collective decision-making processes to explore patterns in farmers’ yields and the dynamics of farmlands. Our results show that (1) within a prevailing trend of increasing yields for higher river discharge and gate capacity, (2) the influence of water availability is characterized by nonlinear changes in yields in response to variations in river discharge and gate capacity, revealing thresholds and tipping points, with (3) strategies for water redistribution partially alleviate inequitable water allocation between upstream and downstream farmers, although considerable variation persists in individual farmers’ and system-wide harvest outcomes. The AIRABM emphasizes individual and collective decision-making processes, encapsulating the uncertainty stemming from water availability and harvests of individual farmers. The modeling framework serves as a valuable tool to explore cooperative approaches in shared (water) resource management. Our findings provide meaningful suggestions to study and promote communication and (conditional) cooperation measures between farmers and management, thereby enhancing the effectiveness of irrigation water distribution.

@en

An Advanced Irrigation-Related Agent-Based Model (AIRABM) of farmers' decision-making mechanism and feedback among farmers is developed. The model explores the interactions among human and non-human agents in the irrigation system. In this paper, we discuss harvest patterns as they result from more equal or unequal water distribution in the system. In a baseline model run, farmers are not restricted in their water use. For those situations that yields are low on the system or farmer level, we allow gate settings to be adjusted to improve poor harvest situations. Our model results show that 1) in the baseline scenario, upstream farmers generally receive more water and gain higher yields compared to downstream farmers; 2) gate capacity adjustments of upstream and middle stream farmers can push more water to downstream farmers, but those specific variations are considerable. We observe unexpected emerging system performance. The AIRABM model offers options for how combinations of individual farmers' decisions on water use and farming create (un)equal yield patterns in irrigation systems.

@en

The literature on irrigated agriculture is primarily concerned with irrigation techniques, irrigation water-use efficiency, and crop yields. How human and non-human agents co-shape(d) irrigation landscapes through their activities and how these actions impact long-term developments are less well studied. In this study, we aim to (1) explore interactions between human and non-human agents in an irrigation system; (2) model the realistic operation of an irrigation system in an agent-based model environment, and; (3) study how short-term irrigation management actions create long-term irrigation system patterns. An agent-based model (ABM) was used to build our Irrigation-Related Agent-Based Model (IRABM). We implemented various scenarios, combining different irrigation control methods (time versus water demand), different river discharges, varied gate capacities, and several water allocation strategies. These scenarios result in different yields, which we analyse on the levels of individual farmer, canal, and system. Demand control gives better yields under conditions of sufficient water availability, whereas time control copes better with water deficiency. As expected, barley (Hordeum vulgare, Poaceae) yields generally increase when irrigation time and/or river discharge increase. The effect of gate capacity is visible with yields not changing linearly with changing gate capacities, but showing threshold behaviour. With the findings and analysis, we conclude that IRABM provides a new perspective on modelling the human-water system, as non-human model agents can create the dynamics that realistic irrigation systems show as well. Moreover, this type of modelling approach has a large potential to be theoretically and empirically used to explore the interactions between irrigation-related agents and understand how these interactions create water and yields patterns. Furthermore, the developed user-interface model allows non-technical stakeholders to participate and play a role in modelling work.@en

In order to explore possibilities of mimicking the operation of an irrigation system under varied scenarios, the authors have designed the Irrigation-Related Agent-Based Model (IRABM), providing a platform for integrating human and non-human agents (water managers, farmers, barley, river, canals, and gates) together and analyzing the interactions among these agents. IRABM illustrates how barley yields respond to varied irrigation strategies and how patterns of yields vary among the levels of individual farmers, canals, and the whole irrigation system. The model proves how this type of theoretically and empirically informed computer model can be used to develop new insights into studying and simulating interactions between individuals and their environment in an irrigation system. Furthermore, it demonstrates how and why irrigation and yield patterns can emerge from changing actions. One of the applications of the model will be for ancient Southern Mesopotamia, the pluvial land between the two rivers Euphrates and Tigris. Our knowledge of irrigation management and irrigated-landscapes in southern Mesopotamia fairly scant due to lack of data, but also because attention for the details of irrigation management has been ignored in archaeological analysis to date. IRABM offers options to synchronize the general features of irrigation systems to the specifics of Mesopotamia. How to represent ancient Mesopotamia in IRABM is the key question we address in this paper. Given the low precipitation, the available water in Mesopotamia’s watercourses for cultivation was vital. This prompted the establishment of irrigated agriculture, leading to its sophisticated irrigation systems over time. Management of irrigation activities is both related to water volumes in the different (levels of) water courses, and to the size of a system. Because of the expanding Mesopotamian society, and this its irrigated areas, the unpredictable water availability, and the threat of water scarcity during the crop growing period, coordinating issues were critical. How to present ancient Mesopotamian irrigation systems in IRABM and how to fully explore the temporal and spatial coordination issues is our current challenge. Using the standard composition of irrigation systems in the primary canal, secondary canals, and tertiary canals, we can draft sizes of these levels. The cultivated size of agricultural land varied among the different levels of canals. Generally, the primary canal would supply 5 to 6 villages, while the second and tertiary canals might irrigate land in 2 to 3 villages and 1 village, respectively. The main crops were winter crops (barley and wheat). The water regimes of the two rivers are characterized by great, rather unpredictable fluctuations that do not coincide with winter crops. This presentation will discuss how the data on ancient Mesopotamian irrigation (including water availability in rivers, canals, and fields, and surface areas of irrigated landscapes) can be meaningfully included in an ABM that allows studying how small/short processes contribute to large-scale patterns and processes occurring in irrigation systems.@en