2001-2004, , Northern Mediterranean

In this project RIKS is developing a Policy Support System for policy makers and planners at the regional and local scale. The PSS simulates for 25 years in the future the autonomous development of a region caused by external influences like climate change and economic and demographic growth, and internal processes like land use practices. Furthermore, the system enables the policy maker to understand and visualise the impacts of different policy options (zoning, grazing, fire prevalence, construction of dams, price and maximum amount of water) for a sustainable development of the region.

In a former EU project (MODULUS) RIKS has already built a PSS for mediterranean areas which has been applied to the Marina Baixa and the Argolidas (Greece). The goal of this project was to make research from former EU projects applicable for policy makers at the regional level. We did this by building a PSS that integrates climate change, hydrology, the aquifer, irrigation, crop choice and land use. In the current MedAction project we would like to improve our system and apply it to the Guadalentin river basin.

[b]The integrated model[/b]
The MedAction PSS consists of several sub-modules which are integrated into the [d]287[dd]system diagram[/d]. In the diagram are two external driving forces: climate change on the physical side, and economic and demographic growth on the socio-economic side. The [i]climate and weather module[/i] on the left side of the diagram produces rainfall and radiation which is used for the run-off and evapotranspiration in the [i]hydrology module[/i] and the growth of plants in the [i]plant growth module[/i]. The hydrology and plant growth module are strongly interconnected in the calculation of evapotranspiration, biomass, leaf area index (LAI) and soil moisture. Incorporated on the physical side are also modules to calculate the [i]erosion and sedimentation[/i] and the [i]salinisation[/i] of the soils. These modules determine the suitability of the soil for different types of crops and natural vegetation and also produce several indicators to measure the rate of desertification. The [i]economic and demographic growth[/i] are translated into the land use functions: urban, farming, industry and tourism. These functions are in competition with eachother and with the function natural vegetation in the [i]land use module[/i]. This competition is simulated with a constrained cellular automata model that gives as output the land use change over time. The functions farming and natural vegetation are then further specified through the modules [i]farmer's decisions[/i] and [i]natural vegetation[/i] which produce the crop types and the types of natural vegetation that will cover the cells for farming and natural vegetation. The growth of the plants (crops as well as natural vegetation types) is then calculated in the [i]plant growth module[/i] mentioned before. The last module in the PSS is the [i]water resources module[/i]. This module calculates the amount of available water for irrigation and drinking water, and determines the water used by the different functions based on the maximum available amount and the price of water from different sources (ground water, reservoirs, desalinised water from the sea).
The integrated model is calculated on a spatial resolution of 100 by 100 meters. The temporal resolution of the different modules varies depending of the type of process they describe. So is the land use module calculated on a yearly basis and runs the hydrology module on a variable time step based on the showers which is in the order of minutes.

[b]Applicability for policy makers[/b]
By integrating different scientific models one will not produce a Policy Support System that can be used by policy makers and planners. First a translation has to be made from the output that the scientific modules produce to the information the policy makers want to used. In this PSS this will be done by means of policy relevant indicators. These indicators are formulated together with the policy makers to make them applicable for their decision making process. Besides the use of indicators the system needs to be understandable for the end-user (the policy maker) and has to answer to the questions he or she has.