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In rural areas of developing countries as Mexico, waste disposal has usually been solved by disposing it into places such as ravines or sideways of roads far away from cities, although there are federal regulations (e.g. the Official Norm NOM-083-SEMARNAT-2003) that indicate which conditions should be met to select a site for a sanitary landfill. Such regulations include also criteria on the characteristics of construction and operation of the landfills. This study presents a GIS-supported procedure for the identification of suitable sites for the construction of sanitary landfills. The procedure intends to meet the criteria for site selection according to the cited regulation. The mandatory criteria are restrictive concerning location and proximity to superficial hydrology, groundwater and geology; furthermore, we also include other recommended criteria such as available area, clay soil for cell covering, access, slope, visibility, dispersion and type of vegetation. This procedure has been applied for diverse research projects in Oaxaca State at the southern part of Mexico and was compiled in an ArcToolbox® to facilitate its application.

While increasing biofuel production is worldwide on the political agenda, concerns about the involved trade-offs are on the rise. However, the quantification of these trade-offs is typically based on the comparison of a limited number of plausible alternatives. We extended the analysis by applying a multi-objective genetic algorithm to estimate the set of Pareto optimal solutions which de-scribe the trade-offs between the objectives. The Pareto solutions represent the (estimated) best op-tions given the model and the specified control options. Our analysis studied food and fodder based crop rotations and two alternative biogas crop production schemes: a corn based production scheme and a two-culture production scheme which combines a summer and a winter crop. The integrated river basin model SWAT was used to evaluate the effects of the different production schemes on bio-energy crop production, food and fodder crop production, water quality and low flow discharge. The analysis took place in a medium sized agricultural watershed (~320km2) in Central Germany. We run the optimization algorithm for combinations of the three sets of crop rotations to identify the trade-offs. The two biogas crop rotation schemes showed significant differences in their trade-offs with water quality and low flow conditions. High corn yields led to increasing nitrate concentrations while high bioenergy crop yields based on the two culture system led to decreases in low flow. But trade-offs depended on the choice of food and fodder crops as well. To assess the robustness of the solutions, we compared trade-offs under current climate conditions with trade-offs under two climate scenarios (A1B and B1 scenarios statistically downscaled by WEREX-IV approach for the time period 2014-2100). The estimated trade-offs differed significantly under the different climate conditions, highlight-ing thereby that trade-off analysis has to consider changing boundary conditions.

Land is a limited resource. Its use for one purpose excludes other uses. Addressing theissue of human appropriation of natural resources thus requires understanding of a variety of complexfeedbacks between decisions on land use and ecosystem services. The complexity is caused by alarge number of mostly nonlinear feedbacks between management strategies, productivity,environmental quality, human well-being, consumption and many other aspects of land use. Here, wepresent LandYOUs: an educational online game, which aims at explaining and illustrating variousoptions and feedbacks of sustainable land management (SLM) to the interested public, students andstakeholders. The game gives the player an opportunity to govern a country by means of land use,nature protection and education. One can explore how sometime contrasting dimensions ofsustainability with respect to economic, social and environmental conditions can be balanced on aregional scale while being continuously threatened by global trade fluctuations and limited resources.The game was tested by several groups of students from high schools and universities. Based on thistesting, we received valuable information on how the game is perceived and understood by theplayers. The feedback suggests that the game has a potential to be used for educational purposes,environmental planning or stakeholder meetings.

The ecosystem service (ESS) concept increasingly enters the realms of policy and planning. Simultaneously demands for ecosystem service data and maps increase. The new ESS mapping application is intended as a contribution to solve the problem how demands for and supply of multiple ESS can be mapped in in a reliable and cost-efficient way. Comparable to efforts in biology in mapping the occurrence of plants and animals, the new smartphone application can be used as a tool in citizen science as well as in research projects by students and scientists. Based on The Common International Classification of Ecosystem Services (CICES) or other classification systems, Ecosystem Service Mapping (ESM) App users can map ESS they either observe or use, and additionally select the ecosystems or land-use types in which the ESS are used or which are providing the ESS. The App uses built-in GPS functionality of the smartphones to locate the ESS, as well as the internal clock for a time stamp. Recorded ESS can directly be displayed on a map. Once recorded, results are stored on the phone and submitted to a server, which is collecting mapping results of all users. Beyond ESS mapping, users optionally can provide their home location for distance calculations, rank how important mapped ESS are for them and export recorded ESS. All users receive a registry code number provided by the server, but all records are submitted anonymously and beyond the registry code, no user-specific information is collected. The ESM-App currently is in its beta phase and has been sent out to users for field testing. Beyond, additional server functionalities such as plausibility tests, data processing and map generation are planned, to provide more feedback for ESM-App users, and to deliver ESM-mapping results for science, policy and planning.

Soil moisture patterns are key parameters when it comes to controlling and managing process-pattern interactions in processes relating to soil, vegetation, landscape, climate and the ecosystemSoil pattern heterogeneity is hard to determine in European landscapes using direct procedures, which are used on soil with little or no vegetation, because the soil is often covered with vegetation all year round.The goal of this study is therefore to develop indirect procedures to analyze soil moisture patterns, which “use the biochemical-biophysical characteristics of plants as sensors and indicators” for soil moisture heterogeneity.For this research, geoelectrical methods which include electromagnetic induction (EMI) via a mobile geoplatform with a tractor) and the helicopter electromagnetic method (HEM) are used in the two test areas to quantify model information for soil moisture patterns.At the same time, in both study areas the suitability of optical airborne and satellite remote sensing data (hyperspectral AISA-DUAL, Modis, Landsat TM) will be examined to predict the connection between the spectral response of biochemical- biophysical vegetation characteristics and underlying soil moisture patterns.The first results show the best univariate models for predicting electrical conductivity for the vertical dipole EM38DD V with an R²=0.54 based on the spectral information NPCI (Normalized Pigments Reflectance Index). To predict the horizontal dipole EM38DD H with the spectral index NPCI an R²=0.65 was achieved. The combination of variables including the geographical elevation was tested as the input for a multivariate regression analysis. An improvement could be made to explain the variance of EMI measurement signals by combining elevation and spectral information.

This paper proposes a framework for assimilating urban temperature measurements with simulations of an urban micrometeorological model. Data assimilation, a technique that incorporates observations into a computer model of a real system, is commonly applied in global and regional weather forecasting and an emerging issue in urban meteorological modelling. For that purpose, we suggest applying a novel approach, the Spatiotemporal Epistemic Knowledge Synthesis (SEKS). It combines simulations of a thermodynamic urban climate model, as general knowledge base, with a model output statistics (MOS) of observations, as site-specific knowledge base, by means of Bayesian Maximum Entropy (BME) inference resulting in posterior distributions of the parameters.Examining real meteorological situations in an urban quarter by mobile observations with instruments in a backpack and by simulations with the urban climate model ENVI-met, we illustrate how mobile meteorological measurements can considerably up-value simulated urban meteorological fields (such as air temperature). Performance measures demonstrate that (a) the output of the simulation model is improved by an assimilation of observations, and (b) the data gathered only at a path are extrapolated to a whole urban region, for which a temperature map together with information about the confidence is provided.A conclusion is that individuals moving throughout a city are ideal explorers for the urban meteorological conditions. Recent technical developments facilitating individual-based temperature recordings, e.g. based on mobile phones, might be beneficially combined with the suggested data assimilation techniques and can help to construct urban maps of meteorological parameters. In consideration of the changing climate in cities, actual urban heat maps can be helpful for personal adaptation measures.

The complex and multidisciplinary nature of environmental problems requires that they are dealt with in an integrated manner. Modeling and software have become key instruments used to promote sustainability and improve environmental decision processes, especially through systematic integration of various knowledge and data and their ability to foster learning and help make predictions. This book presents the current state-of-the-art in environmental modeling and software and identifies the future challenges in the field.* State-of-the-art in environmental modeling and software theory and practice for integrated assessment and management serves as a starting point for researchers * Identifies the areas of research and practice required for advancing the requisite knowledge base and tools, and their wider usage* Best practices of environmental modeling enables the reader to select appropriate software and gives the reader tools to integrate natural system dynamics with human dimensions

Integrated assessment models, decision support systems (DSS) and Geographic Information Systems (GIS) are examples of a growing number of computer-based tools designed to provide decision and information support to people engaged in formulating and implementing environmental policy and management. It is recognised that environmental policy and management users are often not as receptive to using such tools as desired but that little research has been done to uncover and understand the reasons. There is a diverse range of environmental decision and information support tools (DISTs) with uses including organisational and participatory decision support, and scientific research. The different uses and users of DISTs each present particular needs and challenges to the tool developers. The lack of appreciation of the needs of end-users by developers has contributed to the lack of success of many DISTs. Therefore it is important to engage users and other stakeholders in the tool development process to help bridge the gap between design and use. Good practice recommendations for developers to involve users include being clear about the purpose of the tool, working collaboratively with other developers and stakeholders, and building social and scientific credibility.

Models have become indispensable in environmental assessment, planning and management. However as models have increasingly been developed and disseminated, the risk of their misuse or misunderstanding of their capabilities has increased. Whether a model is used for simulation, prediction, decision making or communication of scientific analyses, it is important that its development and application conform to protocols or standards that help to maximise the scientific soundness, utility and defensibility of models and their outputs. The complexity and uncertainty inherent in environmental assessment make the pursuit of good modelling practice especially important, in spite of limited time and resources. This paper is an attempt to identify the key components of best modelling practice and our collective progress in its achievement, taking into account previous relevant reviews undertaken by several authors and agencies. The details are always likely to be the subject of lively debate, but the general components of ‘good modelling practice’ are probably not controversial. They are clear purpose, adequate reporting, and serious evaluation. Although these are common strands in the various definitions of good modelling practice the emphasis varies between different types of model application. For this reason it is important that good practice should not become overly prescriptive.We report a preliminary analysis which suggests that progress towards improving modelling practice is slow. This is despite very widespread agreement on what constitutes good practice. Why is this so? In the research community at least, the drivers for model development and evaluation are funding and publication. If modelling practice needs to be improved, and we think it does, sponsors and journals need to take a lead in creating an environment where developing a model requires that the work be undertaken under some system of good modelling practice. The suggestion has been made of a ‘good pract

The Water Framework Directive (WFD) imposes a new approach to water resource management inthe EU states. Uncertainty surrounding its implementation, however, could badly affect the achievement ofthe objectives set by the Directive. Although not directly linked to a set of techniques to deal with it, the WFDand accompanying guideline documents identify uncertainty as a factor likely to play a significant role inassessing the risk of failing to achieve the objectives and setting up the required programmes of measures. In this paper, by addressing the initial description of a river basin we analyse uncertainty in socioeconomicdescriptors such as demographic and water-use data. Socioeconomic data, models and evaluation techniquessupporting the economic analysis of water uses are crucial parts of a Decision Support System (DSS) aimed at facilitating the WFD implementation.

The spatial spread of pollen is modeled by transport equations from atmospheric physics. These equations are coupled with a population dynamic and genetic model. The resulting model consists of a set of coupled partial differential equations which is solved by finite element methods. As example the spatial spread of a resistant trait is simulated.