Resumen de Development of an integrated multi-objective modelling tool to assess water and nutrient pressure of agriculture
Marco Pastori
The current growth in global population combined with an increasing consumption of natural resources puts increasing pressures on the energy, water and food sectors. Expected populations growth will be also associated with changing consumption habits that would deeply influence food demand all over the globe. More competition for land and water resources will characterize future market and water scarcity will exacerbate the issue under climate change forecast estimation. In this context the concept of Energy-Water-Food Nexus has become the headline for the global research agenda, the reference for sustainable development, and for the identification of new and future management and development strategies. Systematic and objective approaches are essential for understanding and analyse different sectors demands not only at different spatial and temporal scales but also across diversified sectors and under changing local boundary conditions. The challenge is to effectively manage and make optimal use of limited resources to meet future socioeconomic needs. Tools facilitating this analysis are urgently needed in order to develop or to increase the ability to produce analysis and assessments supporting policy measures implementation. These tools and analysis approaches must be capable of identifying the tradeoffs among various and even conflicting sectors, generating cost-effective planning, strategies and policies.
It is within this domain that I wanted to analyse the contribution of multi objective analysis routines combined with biophysical mathematical models in order to provide answers to the various and diversified questions arising from the Nexus approach. This thesis addresses the need for integrated water resources management in European and African countries by exploring the performance of alternative nutrient and water management strategies and developing integrative decision frameworks to improve human and environmental agricultural management tradeoffs. Key agricultural management objectives (crop production, nutrient leaching and runoff, irrigation strategies, etc.) are analyzed and quantified at different scales and under different context and situations. A framework GIS system was developed in order to spatially identify and allocate alternative agricultural and water management practices, by means of the integration of an optimization algorithm and biophysical (EPIC) and hydrological models (SWAT). Different case studies are used to validate the tools and analyze the topic including: 1) an application focused on agricultural food production issue at continental scale in Africa. Based on an integrated biophysical model and a multi-objective evolutionary algorithm efficient irrigation and fertilization management patterns in several African countries are identified 2) an application on the Danube river basin by integrating the hydrological model SWAT and an economic model with a multi-objective evolutionary algorithm to identify Best Management Practices to optimize crop production and water quality in synergy with waste water treatment plans development strategies, and 3) an application focused on water scarcity issue in the island of Crete for the optimal identification of agricultural irrigation management strategies.
My thesis demonstrates how the integration of biophysical and hydrological model with an optimization framework is an efficient methodology providing answers and alternative solutions for policy makers in evaluating long-term benefit with a long-term perspective based on simulations of crop productivity, water quality and quantity indicators (i.e. concentration of nitrates in surface water and in the leaching, water use and irrigation requirements), when complex scenarios of Best Management Practices are implemented, i.e. reducing fertilizer application and upgrading waste water treatment plants, irrigation and crop spatial allocation. The proposed systematic approach used in this thesis proves to be a powerful tool both for scientists, policy makers and also stakeholders, and could be extended to other models and context.
