Evaluating the spatial uncertainty of future land abandonment in a mountain valley (Vicdessos, Pyrenees-France) : insights form model parameterization and experiments

International audienceEuropean mountains are particularly sensitive to climatic disruptions and land use changes. The latter leads to high rates of natural reforestation over the last 50 years. Faced with the challenge of predicting possible impacts on ecosystem services, LUCC models offer new opportunities for land managers to adapt or mitigate their strategies. Assessing the spatial uncertainty of future LUCC is crucial for the defintion of sustainable land use strategies. However, the sources of uncertainty may differ, including the input parameters, the model itself, and the wide range of possible futures. The aim of this paper is to propose a method to assess the probability of occurrence of future LUCC that combines the inherent uncertainty of model parameterization and the ensemble uncertainty of the future based scenarios. For this purpose, we used the Land Change Modeler tool to simulate future LUCC on a study site located in the Pyrenees Mountains (France) and 2 scenarios illustratins 2 land use strategies. The model was parameterized with the same driving factors used for its calibration. The defintion of static vs. dynamic and quantitative vs. qualitative (discretized) driving factors, and their combination resulted in 4 parameterizations. The combination of model outcomes produced maps of spatial uncertainty of future LUCC. This work involves literature to future-based LUCC studies. It goes beyond the uncertainty of simulation models by integrating the unceertainty of the future to provide maps to help decision makers and land managers

Reduced order emulation of distributed hydraulic simulation models

Water level predictions made with hydraulic models are uncertain and evaluating this uncertainty using Monte Carlo ensemble prediction is computationally very expensive. In this paper we show how a reduced order Dynamic Model Emulator (DME) can be used to reproduce, with high accuracy, the outputs of a large and complex 1-D hydraulic model (HEC- RAS) at specified cross-sections along the Montford to Buildwas reach of the River Severn in the U.K, together with estimates of uncertainty in the predictions. This emulation model is obtained by the application of Dominant Mode Analysis (DMA), involving the identification and estimation of nonlinear State-Dependent Parameter (SDP) transfer function models, using data generated by dynamic experiments conducted on the HEC-RAS model. The paper shows how this 'nominal' DME is able to emulate the distributed hydraulic model for a nominal set of its physically-defined parameters and it presents initial results from a complete DME that emulates the HEC-RAS model over a user-defined region of its parameter space

Reduced order emulation of distributed hydraulic simulation models

Water level predictions made with hydraulic models are uncertain and evaluating this uncertainty using Monte Carlo ensemble prediction is computationally very expensive. In this paper we show how a reduced order Dynamic Model Emulator (DME) can be used to reproduce, with high accuracy, the outputs of a large and complex 1-D hydraulic model (HEC- RAS) at specified cross-sections along the Montford to Buildwas reach of the River Severn in the U.K, together with estimates of uncertainty in the predictions. This emulation model is obtained by the application of Dominant Mode Analysis (DMA), involving the identification and estimation of nonlinear State-Dependent Parameter (SDP) transfer function models, using data generated by dynamic experiments conducted on the HEC-RAS model. The paper shows how this 'nominal' DME is able to emulate the distributed hydraulic model for a nominal set of its physically-defined parameters and it presents initial results from a complete DME that emulates the HEC-RAS model over a user-defined region of its parameter space

Reduced order emulation of distributed hydraulic simulation models

Water level predictions made with hydraulic models are uncertain and evaluating this uncertainty using Monte Carlo ensemble prediction is computationally very expensive. In this paper we show how a reduced order Dynamic Model Emulator (DME) can be used to reproduce, with high accuracy, the outputs of a large and complex 1-D hydraulic model (HEC- RAS) at specified cross-sections along the Montford to Buildwas reach of the River Severn in the U.K, together with estimates of uncertainty in the predictions. This emulation model is obtained by the application of Dominant Mode Analysis (DMA), involving the identification and estimation of nonlinear State-Dependent Parameter (SDP) transfer function models, using data generated by dynamic experiments conducted on the HEC-RAS model. The paper shows how this 'nominal' DME is able to emulate the distributed hydraulic model for a nominal set of its physically-defined parameters and it presents initial results from a complete DME that emulates the HEC-RAS model over a user-defined region of its parameter space

Suitability of modelled and remotely sensed essential climate variables for monitoring Euro-Mediterranean droughts

Two new remotely sensed leaf area index (LAI) and surface soil moisture (SSM) satellite-derived products are compared with two sets of simulations of the ORganizing Carbon and Hydrology In Dynamic EcosystEms (ORCHIDEE) and Interactions between Soil, Biosphere and Atmosphere, CO2-reactive (ISBA-A-gs) land surface models. We analyse the interannual variability over the period 1991–2008. The leaf onset and the length of the vegetation growing period (LGP) are derived from both the satellite-derived LAI and modelled LAI. The LGP values produced by the photosynthesis-driven phenology model of ISBA-A-gs are closer to the satellite-derived LAI and LGP than those produced by ORCHIDEE. In the latter, the phenology is based on a growing degree day model for leaf onset, and on both climatic conditions and leaf life span for senescence. Further, the interannual variability of LAI is better captured by ISBA-A-gs than by ORCHIDEE. In order to investigate how recent droughts affected vegetation over the Euro-Mediterranean area, a case study addressing the summer 2003 drought is presented. It shows a relatively good agreement of the modelled LAI anomalies with the observations, but the two models underestimate plant regrowth in the autumn. A better representation of the root-zone soil moisture profile could improve the simulations of both models. The satellite-derived SSM is compared with SSM simulations of ISBA-A-gs only, as ORCHIDEE has no explicit representation of SSM. Overall, the ISBA-A-gs simulations of SSM agree well with the satellite-derived SSM and are used to detect regions where the satellite-derived product could be improved. Finally, a correspondence is found between the interannual variability of detrended SSM and LAI. The predictability of LAI is less pronounced using remote sensing observations than using simulated variables. However, consistent results are found in July for the croplands of the Ukraine and southern Russia.GEOLAND

Genotoxicity Study of Carbon Nanoforms using a Comet Assay

Carbon nanoforms due to their unique properties can be applied in many areas also in medicine. This article presents preliminary genotoxicity studies of electrospun carbon nanofibers (ECNF). This material, apart from its numerous applications, may also be a candidate for use in medical therapy and diagnostics. Polyacrylonitrile (PAN) nanofibers received in the electrospinning process were carbonized and thereafter subjected to oxidation treatment (ECNF-F). Both types of fibres were analyzed with regard to genotoxic influence on the fibroblast line cells using comet assay. Additionally, comet assay experiments were conducted on biocompatible carbon nanotubes with a hydrophilic surface. The results indicate the key role of the oxidation process in the functionalization of carbon nanoparticles intended for medical purposes

Applications of Comet Assay for the Evaluation of Genotoxicity and DNA Repair Efficiency in Nanomaterials Research

The single cell gel electrophoresis method, known as comet assay, is a rapid and sensitive technique for testing novel chemicals and nanoparticles for genotoxicity, monitoring environmental contamination with genotoxins and human biomonitoring. In our studies we check the applicability of this method for the evaluation of biocompatibility of modified (MWNF) and non-modified multi-walled carbon nanotubes (MWNT) as well as potential genotoxicity of mercury(II) nitrate. The obtained results enabled us to conclude that the presence of Hg(NO₃)₂ (p<0.001) and MWNT (p<0.04) cause a significantly higher level of DNA damage in comparison to functionalised nanomaterials MWNF. It was implied that for the three investigated agents only mercury significantly enhanced genotoxic effect of X-ray exposure (p<0.001) and inhibition of radio-induced DNA damage repair. On the contrary, the presence of MWNF have no influence on cellular repair efficiencies, while incubation with MWNT causes apoptosis and consequently results in lack of attached cells. In conclusion, our results confirmed the genotoxicity of mercury and non-modified carbon nanotubes as well as the biocompatibility of modified nanotubes. Additionally, we proved the usefulness of comet method for the evaluation of genotoxicity and DNA repair under the influence of different compounds and nanomaterials

Effects of projected land cover and climate changes on snow cover in the Vicdessos mountain observatory (Pyrenees, France)

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