Ali Kerem Saysel

A dynamic model of salinization on irrigated lands

A dynamic simulation model of salt accumulation on irrigated lands is presented. The original version of the model is part of a large-scale socio-economic model of irrigation-based regional development. The model introduced in this paper is a systemic one in the sense that it integrates four major sub-processes of rootzone salinization: irrigation, drainage, groundwater discharge and groundwater intrusion. It provides a comprehensive and general description of the long-term process of salt accumulation in lowlands under continuous irrigation practice, where irrigated lands are annually increased. Analysis of the model and simulation results reveal, under what conditions the salinity reaches alarming levels and with what strategies it can be controlled. For instance, in situations where the mixing of drainage water into irrigation water supplies is high, rootzone salinity quickly reaches alarming levels. More importantly, in this setting, the typical strategy of increasing the drainage in order to control the salinity level yields unprecedented exponentially growing salinity levels, a catastrophic result for the agriculture. The model structure can represent the basin wide salinization process on different geographical settings in agricultural development. In general, the model provides an experimental simulation platform, which can be used by the policy makers in the long term strategic management of large scale irrigation development projects. The model can also be of interest to the students and learners in teaching and research, in the related fields of environmental sciences.

Simulation models in Farming Systems Research: potential and challenges

Integrated simulation models can be useful tools in farming system research. This chapter reviews three commonly used approaches, i.e. linear programming, system dynamics and agent-based models. Applications of each approach are presented and strengths and drawbacks discussed. We argue that, despite some challenges, mainly related to the integration of different approaches, model validation and the representation of human agents, integrated simulation models contribute important insights to the analysis of farming systems. They help unravelling the complex and dynamic interactions and feedbacks among bio-physical, socio-economic, and institutional components across scales and levels in farming systems. In addition, they can provide a platform for integrative research, and can support transdisciplinary research by functioning as learning platforms in participatory processes.