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Vegetation trends in Portugal point to a generalized greening in this territory in the period 1982-2012, in agreement with global greening patterns. Nonetheless, vegetation dynamics may be altered by natural hazards, such as fires and droughts, and also by human activities like land management and land use change. The identification of trend shifts allows to better understand their impacts on vegetation, as well as the recovery after these disturbances.A recently developed a high-resolution (1.1km) spatial dataset of the Normalized Difference Vegetation Index (NDVI) for Portugal spanning the period from 1981 to 2015 is used in the present work. NDVI was derived from the Advanced Very High Resolution Radiometer (AVHRR) sensor on board of the NOAA satellites. Land cover and land cover change are identified using CORINE Land Cover maps. Trends are assessed on seasonally adjusted NDVI time series. Results show at least one breakpoint in the NDVI time series over the study area. Moreover, the majority of the breakpoints separate segments of increasing trend, indicating the recovery of the vegetation after the disturbance. In particular, the extreme drought event of 2005 is pointed out as one main cause of the vegetation shifts occurring, namely in central and southern Portugal, highlighting that water availability plays a major role in vegetation activity in these areas. Additionally, the 2005 fire season presents the second highest value of burned area during the study period, and it is also responsible for a significant number of vegetation shifts. Vegetation behaviour and recovery over the areas affected by drought and/or fires are analysed. Land cover change is also a likely driver of vegetation shifts, since they are both identified on a pixel level on some regions.Acknowledgements: This work was partially supported by national funds through FCT (Fundação para a Ciência e Tecnologia, Portugal) under Project IMDROFLOOD WaterJPI/0004/2014) and the research grant attributed to Ana Russo (SFRH/BPD/99757/2014). [ABSTRACT FROM AUTHOR]

Environmental models are common tools to simulate fluxes and states within the terrestrial energy and water cycles. Simulation results serve a wide range of purposes from infrastructure planning to weather forecasting. Regardless of the purpose, it is a common task to accurately estimate parameters within the process formulations used in environmental models for each computational unit (i.e., grid cell). The dimensionality of the parameter space is equal to the number of parameters per grid cell times the number of grid cells in distributed large-domain modelling, such as in weather forecasting. Without proper regularization of the parameter space, it is impossible to efficiently estimate parameters in this case. One regularization approach is to estimate constant parameters across the modelling domain, but this does not make use of high-resolution data that is available today (i.e., soil maps and land cover information). The Multiscale Parameter Regionalization (MPR) is a promising alternative that makes use of exactly these data sets.The multiscale parameter regionalization (MPR) translates local land surface properties into model parameters. It consists of two steps: first, it relates local geophysical data sets (e.g., soil maps) to high-resolution model parameters via transfer functions at the native resolution of the input data sets. Second, it upscales the high-resolution model parameters to the modeling scale (i.e., the scale at which the model has been applied). MPR has been introduced in the mesoscale hydrologic model (mHM, Samaniego et al. 2010, Kumar et al. 2013), but has recently been made available as a stand-alone tool.In this study, we use the stand-alone tool of MPR to apply it to the land-surface model HTESSEL. This model is the land-surface component of the ECMWF seasonal forecasting system. It uses a tiling approach to differentiate between different land cover types (e.g., high-grown vegetation and shrubs) and assumes constant parameters for each type. Soil related parameters are also considered for few soil classes for the entire domain. While this covers a large extent of subgrid variability at coarse resolutions, we find that its effect at high resolutions is reduced. In this study, we apply MPR for soil water parameters (e.g., conductivity and porosity) and vegetation parameters (e.g., stomatal conductance) that were identified as sensitive in Orth et al. (2016). We find that MPR provides more accurate fluxes over Europe across different resolutions than constant parameters in HTESSEL because it considers the subgrid variability of parameters. We also find a reduced difference between fluxes estimated at different resolutions by applying MPR (i.e., improved flux-matching).References:Samaniego L., et al. https://doi.org/10.1029/2008WR007327Kumar, R., et al. https://doi.org/10.1029/2012WR012195Orth R., et al. http://journals.ametsoc.org/doi/abs/10.1175/MWR-D-15-0283.1 [ABSTRACT FROM AUTHOR]

Extreme peatland forest burning episodes in Indonesia, notably the 1997-98, 2002, 2006 and 2015 events, are a major source of global atmospheric greenhouse gases and have adverse effects on human health and ecosystems on local and regional scales. The re-occurrence of such episodes has refocused attention on the 2002 ASEAN Agreement on Transboundary Haze Pollution, signed and ratified by a total of 10 ASEAN states, including Indonesia since 2014. An operational fire early warning system based on seasonal forecasts has been identified by these states as a key requirement of the Agreement to help mitigate the impacts of widespread burning and haze. However, such a system currently does not exist. Moreover, to develop such a system, a sound understanding of how fire activity responds to climate and human-driven changes in the region is needed.Past research demonstrates that extreme burning events in Indonesia are induced by drought conditions associated with El-Niño and/or positive Indian Ocean Dipole conditions that disrupt the normal monsoonal rainfall patterns across the maritime continent. Several studies have reported clear correlations between antecedent fire weather and fire activity at regional scales. However, most present-day fires in Indonesia result from human-driven land use and land cover (LULC) change and practices associated with agricultural and plantation activities at local scales, and as a result relationships between fire weather and fire activity can be expected to vary depending on past LULC change. Consequently, any effort to develop an operational fire danger early warning system for Indonesia must account for both fire weather and LULC. However, the impact of the interaction of the two factors on fire activity has received comparatively little quantitative attention.This study addresses this research gap by statistically analysing relationships between fire occurrence, fire weather and LULC change across Indonesia from 2002 through 2018. The study uses individual MODIS active fire detections aggregated to 0.25o grid as a proxy for fire activity. Fire weather is characterised by the Canadian Forest Fire Danger Rating System (CFFDRS) indices; Fire Weather Index (FWI) and Drought Code (DC), which are calculated using ERA-5 climate reanalysis products at 0.25 degree resolution. LULC changes are obtained from South East Asia and Peatland land cover maps and forest cover loss datasets. Previous work conducted at (sub-)regional scales in Indonesia has used piecewise regression to establish threshold values for DC and FWI, above which a precipitous increase in fire activity occurs. We revisit these analyses at finer resolutions to determine how such thresholds shift for various LULC types.Our results indicate that relationships between CFFDRS indices and fire activity vary in space and depend on land cover type. The piecewise regression analyses suggest different threshold values for FWI and DC for different land cover types examined, including pristine versus degraded peatland forests, large-scale plantations and small-holder agriculture areas. These results reinforce the importance of considering LULC as part of any future fire early warning system in Indonesia based on near-time climate forecasts. [ABSTRACT FROM AUTHOR]

Seasonal snow has received much attention in the community because of its sensitivity to global climate change and obvious effect on regional energy and water balance. Most previous studies focus on the change of seasonal snow variables under global warming, but less work on its inner principle. In this study, we analyzed the variability of snow cover fraction (SCF) and snow depth (SD) over three typical land cover types of open shrubland, evergreen needleleaf and mixed forest, which have widely distribution in Northern Hemisphere (NH). The results demonstrated that there is different annual variation between SCF and SD over all selected regions, which results that the curves of relationship between monthly SCF and SD are not overlapping between the stages of accumulation and ablation. Meanwhile, SCF and SD showed different characters over selected regions, leading to the curves of relationship between SCF and SD taking different shapes in these regions. Such relationship is an effective tool in the simulation of snow processes in model. However, the relationship is not fully considered in the CMIP5, which always has an underestimate in accumulation stage and an overestimate in ablation stage. Therefore, the different relationship between SCF and SD of snow parameterization scheme in the model over regions is a potential improvement topic to the ability of simulation in the future. [ABSTRACT FROM AUTHOR]

Extreme meteorological events are important causes of damages even in the Alpine environment where topography can interfere with windstorms. These events can be characterized by winds up to 190 km/h that can damage human infrastructures and alter intensively the vegetation. Such an event occurred in the night between 28 and 29 October 2019, the low pressure area "Vaia" over Germany caused violent gusts over the eastern Alps, which crashed about 8 million cubic meters of timber. The protective forest, that plays an important role in avalanche and landslide prevention and protection, was uprooted in several areas of the Dolomites (Livinallongo del Col di Lana, Rocca Pietore, Colle Santa Lucia, Alleghe). The occurrence of similar episodes are rare considering that in 1990 the windstorm "Vivian" destroyed the protective forest of Curaglia in the Graubünden Canton (Suisse). The impact of such an event was not limited only to the forest, the "Vaia" windstorm was combined also to an intense alluvial event, similar to that of 1966, that interrupted telecommunications and main and secondary communication routes.This study presents the support provided by the ESA's Sentinel imagery to the identification and mapping of these avalanche risk areas. The Sentinel 2A MSI imagery, 10m of resolutions, collected October 21st (pre-event) and November 10th (post-event), atmospheric corrected, were properly processed to compute NDVI. The multitemporal comparison of the NDVI values, together with the analysis of the spectral values identifying the different land cover classes, allowed the analysis of the forest cover in terms of variation and the discrimination between areas covered by "existing forest" and "uprooted forest". The area under investigation (with an altitude ranging between 1000 and 1900 m a.s.l. and an extension of about 300 km2), is characterized by a vegetation cover where firs and larches are dominant. The analysis considered in addition to the event effects also the seasonal phenological variations of the vegetation according to the forest types present in the study area. The woodland areas with uprooted trees and the deciduous forest without leaves are, in fact, extremely similar from the spectral point of view during this season. The results of the analysis of the images, integrated with the data of the digital elevation model allowed the identification of the areas with the forest on the ground and with a slope greater than 30°. These areas represent the loss of protective forest areas where the attention of decision makers must be focused on. This study can represent a tool for improving the knowledge about extreme events in alpine environments. Furthermore, this study evidences the support of remotely sensed images for a synoptic description of the territory useful for the definition of the avalanche risk. [ABSTRACT FROM AUTHOR]

Human activities exert an unprecedented reach on the biosphere, a reach that is strengthening in many respects due to climate change. There is a growing body of evidence highlighting that human activities have a direct impact on the global silica cycle. In addition to river damming and nutrient over-enrichment, land cover change is another important way by which humans are altering silica exports from terrestrial to aquatic systems. Understanding the controls on silica exports from terrestrial systems has direct implications for silica availability and carbon cycling in coastal receiving waters, due to the reliance of diatoms on silica. Due to rapid climatic warming, the Arctic is undergoing land cover change in the form of shrub expansion, increasing extent and frequency of wildfires, extended growing season length, and northern migration of the treeline. Moreover, permafrost thaw alters watershed hydrology by deepening flowpath lengths and soil-water interaction times. All of these changes are likely to alter rates of silica exchange between terrestrial and aquatic ecosystems. This talk will synthesize recent findings from the Alaskan Arctic demonstrating how rapid climate warming and associated shifts in watershed land cover and hydrology is altering silica cycling in terrestrial and freshwater aquatic systems. We will present evidence demonstrating that shrub expansion and wildfire both serve to increase the amount of silica sequestered in land plants, strengthening the magnitude of the terrestrial silica pump at local scales. Conversely, degradation of permafrost results and deepening of the active layer increases total silica exports from terrestrial systems via rivers at larger regional scales. It remains to be seen whether small-scale increases in silica retention via land plants can offset larger-scale silica releases from thawing permafrost over time. I will also address the implications of these results in the context of the global silica cycle. [ABSTRACT FROM AUTHOR]

African wetlands in arid and semi-arid regions provide a multitude of ecosystem services andhave been described as the "heart of Sahelian life systems". The Khor Abu Habil alluvialwetlands (Khor is the name given to ephemeral rivers in Sudan) are situated in thesemi-arid zone in the southern part of the Sudan. These ephemeral wetlands are fedby seasonal wadi streams and remain for several months. They provide a habitatfor migratory water birds and play a fundamental role in supporting the humanpopulation (agriculture, grazing, fishing, hunting and construction). In this study weanalyse the Land Use and Land Cover (LULC) dynamics related to agriculturalactivities. We choose agriculture as an entry point because it is the main activity and themain LULC changing factor in the study area. A questionnaire and semi-structuredinterviews were conducted in the study area, documenting different agriculturalactivities and land uses. Additionally, remote sensing data and field data on LULC werecollected and analysed with Google Earth Engine, R and GIS software. Differenttypes of agriculture are practised depending on the soil type. The agriculture inthe wadi pathways depends on floods and the agriculture on the wadi banks is arain-fed. Accordingly, two agricultural calendars were created, namely a rain-fedagricultural calendar and a flood-depending one. Additionally maps illustrating the LULCchange over a year were created. The results helped us to understand the annualchanges in the LULC between the classes agriculture, vegetation, grassland, water andbare soil. Indeed, the same piece of land may be a grassland used by pastoralists aswell as an agricultural land used by farmers, depending on the period of the year.This is a challenge for the creation of classical LULC maps. Wadis or Khors areparticular ecosystems that occur in semi-arid regions. In our study area, the economicactivities show a relationship between land uses and different human communities: theagriculturalists and the pastoralists, who live in synergy with the natural cycles of the seasonsand the wadi waters. The agricultural activities and the different LULC classes aredynamic and vary over the year depending on the wadi flood waters. This characteristicdistinguishes the Khor Abu Habil ecosystem from other ecosystems where LULC classesremain stable most of the year. Our research is part of the FAO-supported projectRESSOURCE with the overall goal to localise and study wetlands of internationalimportance in the sub-saharan Africa and declare them as Ramsar protected zones. [ABSTRACT FROM AUTHOR]

The twin German satellites TerraSAR-X and TanDEM-X have been collecting SAR data inbistatic configuration since 2010. This is currently the only available bistatic mission, wherethe interferometric image pair is acquired within the same survey avoiding temporaldecorrelation. In September 2016 the global TanDEM-X DEM was completed achieving anunprecedented homogeneity and accuracy at 12 m horizontal spacing. Its relative heightaccuracy is specified with 90% confidence level below 2 m and under 4 m for flat and steepterrain, respectively. It achieves in more than the half of the tiles globally 1 m and 2 m forflat and steep terrain, respectively. The global absolute accuracy with 90% confidencelevel is below 3.5 m. The unedited 90 m spacing version is freely available sinceOctober 2018. It is purely derived from the acquired interferometric SAR data, whichdelivers reliable values on non-water surfaces, and covers almost the completelandmass 99.89%. The generation of an edited version is planned for the end of2019, where opportune water levelling and gap filling are considered. On the otherhand, it is very important to be aware of the intrinsic radar characteristics whenusing the TanDEM-X global DEM: the height of forested and snow covered areascorresponds to the mean measured phase center that returns from the illuminatedvolume. The wave’s capability to penetrate into a volume depends on its density,structure and the radar frequency. The height of the generated DEM is in thesecases under the surface. For forest the height is over the terrain close to the topof the canopy and for ice under the terrain. This aspect is sometimes seen as anobstacle to use DEM derived by SAR, on the other hand we see an opportunity todetect volume as it leads to a certain amount of decorrelation on the data. As otherdecorrelation can be well assessed is possible to estimate the volume decorrelation fromthe coherence. Since the delivered raw data is remarkably good, further analysishave been conducted and the data has been used for mapping other bio-physicalvariables, based on these principles. Classification algorithms on ice, forest, and waterhave been developed, as well as tested and validated. A global forest map has beenderived and is freely accessible for scientists. Planned is also a global water mapand Antarctica ice facies map. Furthermore the satellites are well in shape andresources are available to acquire the globe at least once more and allow for thegeneration of a change DEM. From the lessons learned the acquisition plan hasbeen adapted in order to achieve the best in the less time, considering an editedversion of the DEM as base. Finally, the land cover maps in addition to the editedDEM and change DEM are very promising products for geomorphology purposes. [ABSTRACT FROM AUTHOR]

Climate can be perturbed by land cover change through its influence on the exchange of water, energy, and gases between the land surface and atmosphere. However, in the areas of considerable land cover changes, such as the Horn of Africa, estimating the relative contribution of the associated biophysical changes to the climate through their impact on net land surface temperature dynamics requires further study. Here we used an empirical model driven by time series data (2001 – 2013) from meteorological and moderate-resolution satellite observation, and quantified the relative contribution of radiative (albedo) and non-radiative (evapotranspiration and surface roughness) changes to surface temperature dynamics in the region. In our analysis, the impact of background climate variability signal was removed from every pixel. We find that the conversion of forest to cropland generated maximum net warming (1.3 K) compared with other conversion classes (savanna, shrubland, grassland, and cropland). The warming from the reduction of evapotranspiration and surface roughness process were up to 10-times stronger than the cooling effect from albedo increase (–0.12 K). This result indicates that albedo effect weakly counterbalances the warming from the non-radiative processes, and the climatic impacts of land cover changes were mainly driven by the non-radiative processes in the region. [ABSTRACT FROM AUTHOR]

The Iberian Peninsula is affected by different levels of water scarcity due to extensive droughts that frequently occur, creating conflicts between Portugal and Spain, and even between Spanish autonomic regions. As such, the available water resources need to be more efficiently used to fulfil the multiple demand from different uses (urban consumption, agriculture, industries, tourism), meaning that better management tools are required for that purpose.This study aims to quantify water resources availability in the Iberian Peninsula using the physically-based, fully-distributed MOHID-Land model. This model considers four compartments or mediums (atmosphere, porous media, soil surface and river network), computing water dynamics through the different mediums using mass and momentum conservation equations.The model was implemented in the simulation domains with a resolution of 5 km. Data inputs included the digital terrain model from Shuttle Radar Topography Mission of NASA with a resolution of 90 m; the soil map from the European Soil Data Centre (1:1,000,000); the Corine land cover map from 2012 with a resolution of 100 m; the soil hydraulic properties from the HYPRES class pedotransfer functions; the hourly weather data (precipitation, wind velocity, relative air humidity, solar radiation and surface air temperature) from the SAFRAN model with a resolution of 8 km; the reservoir discharge data from governmental and regional agencies.Simulations were run from October 1979 to June 2014, with model warm-up being set from 1979 to 1985, model calibration from 1985 to 2004, and model validation from 2004 to 2014. The calibration and validation process focused on the comparison of simulated flows with those measured in hydrometric stations (81 stations) with no reservoir influence, and those estimated using satellite products.Four statistical parameters (R2, RMSE, PBIAS and NSE) were used to evaluate model performance. Results differed substantially along the domain, with better results being obtained in the northern region of the Iberian Peninsula when compared with the southern region. This highlight the need for better include information related to water transfers between different catchments in the model. Additionally, information related to reservoir management needs to be included to improve the reliability of model predictions in the downstream areas. Nonetheless, considering the coarse scale of simulation domain, model performance was considered to be generally good considering the scale of the application. [ABSTRACT FROM AUTHOR]

Peatland landscapes such as northern fens are fragmented and patchy in terms of their vegetation, land cover and hydrology. Such heterogeneity leads to variation in biogeochemical cycles of e.g. carbon, nitrogen and water among different land cover types and atmosphere. Thus, there is an urgent need to classify vegetation and land cover accurately. There have been contrasting claims on the spatial resolution requirements for mapping the mosaic-like patterns in treeless northern landscapes such as tundra and peatlands. Some have argued that Landsat-scale resolution (ca. 30 m) is sufficient (Bartsch et al. 2016, Treat et al. 2018). However, according to others, a very-high spatial resolution (of the order of <5 m) is needed for constructing realistic maps of tundra and peatland vegetation (Virtanen and Ek 2014, Siewert et al. 2015, Räsänen et al. 2018). Moreover, recent studies suggest that a centimeter-level spatial resolution, obtained only with unmanned aerial vehicles, should be used for an accurate characterization of patchy landscapes (Palace et al. 2018).We present here a case study highlighting the impact of the choice of the spatial and spectral resolution, dataset combination used as source data in classification, and classification technique on the accuracy of land cover classification in a patchy subarctic landscape. This study will also shed light on the importance of accurate land cover characterization in interpreting chamber and eddy covariance carbon dioxide and methane fluxes measurements with footprint modelling, upscaling the carbon balance to the catchment scale and in process‐based biogeochemical modeling.The study area is located in Kaamanen, northern Finland (69.14°N, 27.27°E; 155 m a.s.l.) in a northern boreal vegetation zone and subarctic climate zone. The main research area is dominated by a treeless mesotrophic patterned fen, characterized by a strong pattern of strings with dwarf shrub vegetation, and flarks with sedge and brown moss vegetation. The catchment area includes also upland pine forests, shrub-dominated pine peatland, and some streams and lakes. Measurements of CO2 and CH4 exchange conducted in 2017 and 2018 using eddy covariance and manual chamber methods at representative land cover types will be used in this study.ReferencesBartsch, A.A. et al. 2016. Land Cover Mapping in Northern High Latitude Permafrost Regions with Satellite Data: Achievements and Remaining Challenges. Remote Sensing 8(12)Palace, M. et al. 2018. Determining subarctic peatland vegetation using an unmanned aerial system (UAS). Remote Sensing 10(9)Räsänen, A. et al. 2018. Predicting biomass in Arctic landscapes using very high spatial resolution satellite imagery and field sampling. International Journal of Remote SensingSiewert, M. B. et al. 2015. Comparing carbon storage of Siberian tundra and taiga permafrost ecosystems at very high spatial resolution. Journal of Geophysical Research-Biogeosciences 120(10): 1973-1994Treat, C. C. et al. 2018. Tundra landscape heterogeneity, not interannual variability, controls the decadal regional carbon balance in the Western Russian Arctic. Global Change Biology 24(11): 5188-5204Virtanen, T., and M. Ek. 2014. The fragmented nature of tundra landscape. International Journal of Applied Earth Observation and Geoinformation 27: 4-12 [ABSTRACT FROM AUTHOR]