Systems Approach To Link Big Socio-Ecological Geo-Data To Food Systems Sustainability,
2016
CGIAR Research Program on Dryland Systems, c/o International Center for Agricultural Research in Dry Areas (ICARDA)
Systems Approach To Link Big Socio-Ecological Geo-Data To Food Systems Sustainability, Quang Bao Le, Chandrashekhar Biradar, Enrico Bonaiuti, Richard Thomas
International Congress on Environmental Modelling and Software
Rapid development of multi-dimensionally, multi-scale, timely updated socio-ecological geo-data presents an opportunity as potential information resource for supporting effective decision- making of stakeholders involved with food systems, from daily routines of individuals to strategic decisions of manager and policy-makers. However, the use of this type of big data toward supporting the sustainability of food systems at different scales still fall short of (i) what information commonly needed by food system actors to response and adapt to socio-ecological change and enhance the system performance, (ii) interoperability between different types of data across scales, and (iii) sufficient guidance to utilize big data …
Challenges And Opportunities For Urban Decarbonization At The Global Scale,
2016
Climate Service Center Germany, Helmholtz-Zentrum Geesthacht
Challenges And Opportunities For Urban Decarbonization At The Global Scale, Roger Cremades
International Congress on Environmental Modelling and Software
Urban areas emit roughly three quarters of global carbon emissions. Cities are crucial elements for a decarbonized society, however, there is not a framework to analyse cities at the global scale. Supervised machine learning from remote sensing provides information about human settlements from 4 dates (1974, 1990, 2000 and 2014), allowing the creation of the Global Human Settlement Layer (GHSL) which jointly with the Gridded Population of the World (GPW) provides the basis for this study. This dynamic evolution of 250 metre sided cells and its population at the global scale gives an unprecedented opportunity to analyse a backbone of …
Multi-Dimensional Hydraulic Coupling For Flood Forecasting,
2016
CECI, CNRS-CERFACS
Multi-Dimensional Hydraulic Coupling For Flood Forecasting, S. Barthélémy, S. Ricci, N. Goutal, T. Morel, E. Le Pape
International Congress on Environmental Modelling and Software
In the context of hydrodynamic modelling the use of 2D models is of fundamental importance in areas where the flow is not mono-dimensional. Nonetheless, the lack of bathymetric data to develop a global 2D model over an entire network or the computational cost of a global 2D model can be prohibitive for operational flood forecasting services. To overcome this limitation a solution is to use multi-dimensional coupling with the use of 1D models where the flow is mono- dimensional and the use of 2D models when needed. Multi-dimensional coupling allows for the use of a global hydrodynamic 1D/2D model over …
Plant Trait-Based Assessment Of The Pasture Simulation Model,
2016
PEGASE, Agrocampus Ouest, INRA
Plant Trait-Based Assessment Of The Pasture Simulation Model, Anne-Isabelle Graux, Katja Klumpp, Shaoxiu Ma, Raphaël Martin, Gianni Bellocchi
International Congress on Environmental Modelling and Software
We used a functional trait-based plant classification to improve the plant module of the biogeochemical grassland model PaSim. Based on four main classes (A, B, C, D) and two derived types (b, d) covering a gradient from high to low productive/fertile grassland vegetation types, we derived new classes of model plant parameters representing an evolution of a previous parameterization obtained by calibration without considering any plant diversity. Illustrative results are presented for the French grassland site of Laqueuille, by comparing two grazing management treatments: high animal stocking rate and fertilisation “intensive” (type B) and low animal stocking rate “extensive” (type …
Comparison Of Parametric And Non-Parametric Disaggregation Models For The Top-Down Generation Of Water Demand Time Series,
2016
University of Ferrara
Comparison Of Parametric And Non-Parametric Disaggregation Models For The Top-Down Generation Of Water Demand Time Series, S. Alvisi, N. Ansaloni, M. Franchini
International Congress on Environmental Modelling and Software
This study presents a “top-down” procedure for generating synthetic time series of hourly nodal water demands from time series of the total water demands in the area that includes the nodes considered, based on the application of disaggregation models already presented in the literature in the field of hydrology. More specifically, a parametric and a nonparametric disaggregation model are compared to assess their performance in reproducing, on a nodal level, the main statistics of the time series of historically observed water demands. Moreover, with regard to the nonparametric model, two variants of the original formulation are proposed with the aim …
A Bayesian Method For Data Assimilation In Probabilistic Wave Forecasting,
2016
HR Wallingford UK
A Bayesian Method For Data Assimilation In Probabilistic Wave Forecasting, Quillon Harpham, Nigel Tozer, Paul Cleverley, David Wyncoll, Doug Cresswell
International Congress on Environmental Modelling and Software
New innovations are emerging which offer opportunities to reduce the uncertainty of forecasts of wave conditions. These include probabilistic modelling results, such as those based on an ensemble of multiple predictions which can provide a measure of the uncertainty, and new sources of observational data such as GNSS reflectometry and FerryBoxes, which can be combined with an increased availability of more traditional static sensors. This paper outlines an application of the Bayesian statistical methodology which combines these innovations. The method modifies the probabilities of ensemble wave forecasts based on recent past performance of individual members against a set of observations …
Big Data In Environmental And Human Health Risk Assessment: Opportunities And Challenges,
2016
Universitat Rovira i Virgili
Big Data In Environmental And Human Health Risk Assessment: Opportunities And Challenges, Vikas Kumar
International Congress on Environmental Modelling and Software
Big Data is broad term for large data sets arriving from multiple sources with typological and structural complexities which presents integrational, analytical and visualization challenge to extract meaningful information. In the human health risk assessment, the amount of data is exploding from basic science to clinically based omics, High Throughput Screening (HTS) to biosensors, large scale biomonitoring to multigenerational individual and population based studies. The scattered “Big Data” captures the opportunities as well as challenges in accessing, integrating, managing and analysing the datasets of diverse data types. The aim of this study is to perform a systematic review of the …
Reconciling Information From Climate-Economic Model Ensembles,
2016
International Institute for Applied Systems Analysis
Reconciling Information From Climate-Economic Model Ensembles, A. Shchiptsova, D. Kovalevsky, E. Rovenskaya
International Congress on Environmental Modelling and Software
To date, no model building process can guarantee full representation of the complex climate-economic processes and narrow down the uncertainty associated with future climate projections. Multiple highly detailed models are developed by individual research groups to capture various known aspects of the climate processes. Normally, these models represent only a part of the climate-society system due to its complexity. On the other hand, a number of the simplified integrated assessment models (IAMs) have been put forward in the attempt to introduce the full causal loop between accumulated emissions, economy and climate, and study associated uncertainty. We present a simplified system …
Measuring Household Vulnerability: A Fuzzy Approach,
2016
Bard Center for Environmental Policy
Measuring Household Vulnerability: A Fuzzy Approach, Gautam Sethi, Molly Gilligan, Amy Richmond
International Congress on Environmental Modelling and Software
This research develops an index of vulnerability for Ugandan households using a variety of economic, social and environmental variables with two objectives. First, there is only a small body of research that measures household vulnerability. Given the stresses faced by households susceptible to water, environment, food, livelihood, energy, and health security concerns, it is critical that they be identified in order to make effective policy. We draw on the socio-ecological systems (SES) framework described by Ostrom (2009) and adapt the model developed by from Giupponi, Giove, and Giannini (2013) to develop a composite measure. Second, most indices in the literature …
Data-Driven Rainfall/Runoff Modelling Based On A Neuro-Fuzzy Inferential System,
2016
University of Florence
Data-Driven Rainfall/Runoff Modelling Based On A Neuro-Fuzzy Inferential System, N. Bartoletti, F. Casagli, S. Marsili-Libelli, A. Nardi, A. Oliva, L. Palandri
International Congress on Environmental Modelling and Software
The development of rainfall/runoff models may involve extensive computation and differing platforms, including GIS. In this paper we present a simple data-driven approach which avoids the use of GIS, but is based on a combination of Principal Component Analysis (PCA) and an Adaptive Neuro Fuzzy Inference System (ANFIS) to produce a simple and effective output flow prediction based on previous rainfall/runoff data. Given the ANFIS internal complexity, the emphasis of the paper is on how to set-up the most representative and parsimonious data structure that produces an efficient output flow estimation. In the preliminary data reduction stage, the PCA approach …
Evapotranspiration Mapping Using Sebal Algorithms To Account For Agricultural Water Uses In The Upper Pangani, Tanzania,
2016
The Nelson Mandela African Institution of Science and Technology, Vrije Universiteit Brussel
Evapotranspiration Mapping Using Sebal Algorithms To Account For Agricultural Water Uses In The Upper Pangani, Tanzania, Anna Msigwa, Ann Van Griensven, Hans C. Komakech, Boud Verbeiren, Tim Hessels, Wim G. M. Bastiaanssen
International Congress on Environmental Modelling and Software
To make informed decisions, river basin managers requires information on demands and actual usage from different sectors in the basin. Such water use information has to be adequate in terms of quantities used per sector, where and when. However, because of high costs of maintaining equipment for monitoring use, it is very difficult to obtain this information in developing arid and semi- arid areas of Sub-Saharan Africa. The use of proxy method such as calculation of evapotranspiration is proposed as a cheaper means for such data acquisition. Water consumption through crop evapotranspiration (ET) is a major component of water withdrawal, …
Web Service Based Approach To Link Heterogeneous Climate-Energy-Economy Models For Climate Change Mitigation Analysis,
2016
University of Twente
Web Service Based Approach To Link Heterogeneous Climate-Energy-Economy Models For Climate Change Mitigation Analysis, Getachew F. Belete, Alexey Voinov, Tatyana Bulavskaya, Leila Niamir, Kishore Dhavala
International Congress on Environmental Modelling and Software
Climate change mitigation analysis requires understanding the causes and identifying the possible alternative actions that could be taken. We linked heterogeneous models that focus on climate, energy, and economy for the purpose of climate change mitigation. The models were originally developed to serve as standalone tools for some specific purposes. The models operate at various levels of complexity, different temporal and spatial scales, from individual to global. They were developed using quite different assumptions and modeling paradigms and tools. One of them is a Computable General Equilibrium model, the second is an Integrated Assessment Model, and the third one is …
Developing A Stochastic Simulation Model For The Generation Of Residential Water End-Use Demand Time Series,
2016
Politecnico di Milano
Developing A Stochastic Simulation Model For The Generation Of Residential Water End-Use Demand Time Series, A. Cominola, M. Giuliani, Andrea Castelleti, A. M. Abdallah, D. E. Rosenberg
International Congress on Environmental Modelling and Software
Smart metering technologies allow for gathering high resolution water demand data in the residential sector, opening up new opportunities for the development of models describing water consumers’ behaviors. Yet, gathering such accurate water demand data at the end-use level is limited by metering intrusiveness, costs, and privacy issues. In this paper, we contribute a stochastic simulation model for synthetically generating high-resolution time series of water use at the end-use level. Each water end-use fixture in our model is characterized by its signature (i.e., its typical single-use pattern), as well as frequency distributions of its number of uses per day, single …
Up In The Air: Understanding Vulnerability When Toilets Fly,
2016
United States Military Academy, West Point
Up In The Air: Understanding Vulnerability When Toilets Fly, Amy Krakowka Richmond, Suzanne Pierce, Sethi Gautam
International Congress on Environmental Modelling and Software
Across sub-Saharan Africa, both natural and social factors contribute to household level vulnerability. This case study focuses specifically on Uganda, which has made progress towards meeting the United Nation’s Millennium Development Goals, most notably halving the proportion of the population that is below the poverty line. Despite these impressive achievements, many households remain vulnerable to multiple social and environmental stressors. A better understanding of the drivers of household level vulnerability will assist stakeholders and policy-makers in determining what drives vulnerability at a household level, where vulnerable populations are, and suggest what type of aid to target specific locations to be …
Participatory Simulation And Learning Process: Technology Matters!,
2016
CNRS, UMR LIENSs
Participatory Simulation And Learning Process: Technology Matters!, Nicolas Becu, Pierre Bommel, Christophe Le Page, François Bousquet
International Congress on Environmental Modelling and Software
Participatory modelling (PM) is an approach under constant renewal due to its close link to available technologies and evolution of learning habits of citizens. Since the years 2000 many PM research projects leapt into the breach of hybrid simulation to produce new modes of interaction between PM session’s participants. This paper reports on the advances of participatory simulation (PS) – the branch of PM that focuses on learning by interacting with a collective simulation – on using different projection technologies for participants’ interfaces. The use of two types of technologies is analyzed in this paper: ultra-short throw projector and distribution …
Planning Complex Agro-Ecosystems: The Case Of Analog Forestry,
2016
Politecnico di Milano
Planning Complex Agro-Ecosystems: The Case Of Analog Forestry, F. Recanati, Giorgio Guariso, M. Saini, Sergio Vilchez Mendoza
International Congress on Environmental Modelling and Software
Traditional agroecosystems, aimed at maximizing the short term productivity, are characterized by oversimplification of ecological structure and dependence on the use of external inputs. Moreover, intensive agriculture is one of the main cause of deforestation. The main consequence of traditional agriculture is the loss of natural ecosystems and of their precious services. Analog forestry has emerged as a sustainable productive model able to be integrated in forest contexts, without degrading their ecological functions. The obtained agro-ecosystem is characterized by an ecological structure similar to the one of forest, and by the presence of several productive species in the same area. …
Developement Of Data Fusion Methods For An Improved Estimation Of Soil Moisture,
2016
Leibniz Centre for Agricultural Landscape Research (ZALF)
Developement Of Data Fusion Methods For An Improved Estimation Of Soil Moisture, Felix Linde
International Congress on Environmental Modelling and Software
This talk presents recent work on data fusion methods applied to the estimation of soil moisture by means of remote sensing. Particularly in research dealing with landscapes and agriculture there is a need for spatially and temporally resolved estimation of soil moisture from local to regional level and beyond. The methods to evaluate the water content of the soil range from direct measurements, optical and microwave remote sensing to modeling based on precipitation measurements. Usually the availability of the specific data defines the used method. The uncertainties connected to each way of estimation vary with weather conditions, region and data …
Estimation Of Evapotranspiration In Heterogeneous Landscape Using Simplified Surface Energy Balance Operational,
2016
Vrije Universiteit Brussel (VUB)
Estimation Of Evapotranspiration In Heterogeneous Landscape Using Simplified Surface Energy Balance Operational, T. Alemayehu, A. Van Griensven, G. Senay, Willy Bauwens
International Congress on Environmental Modelling and Software
Evapotranspiration (ET) has important practical significance in water resources planning and management, irrigation scheduling and environmental issues as well as hydrological model parameterization. The objective of this study is to map ET using thermal-based Simplified Surface Energy Balance Operational (SSEBop) model across a heterogeneous landscape in the Mara basin. We used level three clear sky Moderate Resolution Imaging Spectroradiometer (MODIS) land surface temperature at 1km spatial scale. Since the study area has poor weather monitoring network, the weather parameter required to derive the reference evapotranspiration and evaporative fraction is retrieved from Global Land Data Assimilation System (GLDAS) dataset. The analyses …
Uncertainty Quantification With Polynomial Chaos Expansion In Ensemble Based Data Assimilation Framework,
2016
CECI Cerfacs/CNRS
Uncertainty Quantification With Polynomial Chaos Expansion In Ensemble Based Data Assimilation Framework, N. El Mocayd, S. Ricci, M. Rochoux, N. Goutal, S. Boyaval, C. Goeury, D. Lucor
International Congress on Environmental Modelling and Software
In hydraulic simulations, water level calculations suffer from uncertainty in various physical and numerical parameters that translate into uncertainty in simulated water level. Usually, a classical Monte-Carlo method sampling is used to quantify uncertainty, but this approach is quite expensive as it requires a large number of the forward model integrations. This study aims at developing a cost- effective stochastic approach adapted to open-channel flows assuming that the uncertainty is mostly due to roughness coefficient and input discharge. We investigate the ability of a polynomial chaos expansion to evaluate the probabilistic features of the water level with the same accuracy …
Big Data In Land Change Science: Challenges And Implications Of Advanced Technologies,
2016
LISER
Big Data In Land Change Science: Challenges And Implications Of Advanced Technologies, Hichem Omrani, Amin Tayyebi
International Congress on Environmental Modelling and Software
Big data has received a lot of attentions during last decade. Dealing with big data is a complex task as it is challenging to analyse, store, model and make sense of big data. Using big data in land change science (LCS) is a new area of research. One of the main challenges in LCS is using big data for model calibration effectively. In this study, we propose using clustering technique, based on k-means approach, to handle big land-use data and overcome the limitation of model calibration. With clustering, data are partitioned into smaller subsets and are t hen analysed …
