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Our project combines archaeopedological and archaeological knowledge and data for the reconstruction of Bronze Age settlement patterns and land use practices in three landscapes in SW-Germany (Hegau, Western Allgäu, Baar). Being different in physical-geographical conditions and archaeological records, we assess Hegau as favourable and both Western Allgäu and Baar as unfavourable for prehistoric subsistence. However, we also consider a dynamic and relative comprehension of favourability and unfavourability and assume that material and immaterial requirements such as agricultural practices, knowledge, religious and cultural beliefs may have changed through time (JAMES ET AL., 2019, IN PREP.). The presentation focuses on first available archaeopedological and archaeological results at the study site Anselfingen (Hegau).Archaeological structures from Bronze Age like post holes, fire places, kilns as well as findings like shards, bones and ores within the settlement site are discussed. Hence, initial conclusions can be drawn about settlement chronology, duration and activity areas. Archaeopedological data acquisition is based on the analysis of multi-layered colluvial deposits (Zádorová et al., 2018, HENKNER ET AL., 2018, PIETSCH AND KÜHN, 2017). Such colluvial deposits are interpreted as the correlative sediments of human-induced soil erosion and as such serve as archives to reconstruct land use practices and landscape evolution (HENKNER ET AL., 2017, LEOPEOLD AND VÖLKEL, 2007). First chronostratigraphies based on luminescence dating techniques (OSL), AMS-14C radiocarbon datings and typological classification of archaeological findings are presented for the study site. Supplemented by pedological data (soil organic carbon, pH, calcium carbonate, grain size distribution, pedogenic oxides) phases of pedogenesis and soil erosion/formation of colluvial deposits will be discussed. Further, data sets of heavy metals, phosphorus, enzymatic activity (e.g. urease) and steroids should decipher human-environment interactions as ore processing, intensified anthropogenic input (waste, dung) and domestication practices in the settlement complex. The results from field work provide us with preliminary archaeological and archaeopedological assumptions for all three landscape units. Additionally, first interpretations of past human-environment interactions can be formulated based on data sets for the site Anselfingen.Henkner, J., Ahlrichs, J. J., Downey, S., Fuchs, M., James, B. R., Knopf, T., Scholten T., Teuber S. and Kühn, P. (2017). Archaeopedology and chronostratigraphy of colluvial deposits as a proxy for regional land use history (Baar, southwest Germany). Catena, 155, 93-113.Henkner, J., Ahlrichs, J., Downey, S., Fuchs, M., James, B., Junge, A., Knopf T., Scholten T and Kühn, P. (2018). Archaeopedological analysis of colluvial deposits in favourable and unfavourable areas: reconstruction of land use dynamics in SW Germany. Royal Society open science, 5(5).James B., Ahlrichs J., Henkner J., Downey S., Correa F., Knopf T., [...] (2019). Soil, Landscape, and Cultural "Favourability": Reviewing Human-Environment Interactions During the Holocene (in prep.)Leopold, M., Völkel, J., 2007. Colluvium: Definition, differentiation, and possible suitability for reconstructing Holo-cene climate data. Quaternary International 162–163 (0).Pietsch, D., Kühn, P., 2017. Buried soils in the context of geoarchaeological research—two examples from Germany and Ethiopia. Archaeol Anthropol Sci 9 (8), 1571–1583.Zádorová, T., Penížek, V., 2018. Formation, morphology and classification of colluvial soils: a review. European Journal of Soil Science 69 (4), 577–591. [ABSTRACT FROM AUTHOR]

Natural Flood Management (NFM) practices include planting catchment woodland as a technique for potential interception and attenuation of runoff to mitigate downstream flooding and deliver multiple ecosystem services (e.g., habitat, amenity). According to The Scottish Forestry Strategy (2006), upland afforestation, as part of an NFM strategy can reduce flood runoff by increasing evapotranspiration, interception and soil infiltration. The Scottish Forestry Strategy (2006) therefore aims to increase woodland cover from 17.1% to 25% of Scotland's land area by the second half of this century. To realize this ambition, they Scotland plan the creation of ~15,000 ha of new woodland per annum, and to develop novel approaches to assist in mitigating climate change, stimulate economic development and provide a range of other benefits, including sustainable flood management. Menstrie village in Clackmannanshire, central Scotland, has a history of recurrent floods due to overbank flow from the Menstrie Burn (a hillslope tributary of the River Forth). In August 2004 approximately 30 properties were flooded (Clackmannanshire council, 2005). An even larger event occurred in 2012, demonstrating a continuing vulnerability of this village to flooding. In 2015 one of the largest modern-day woodland creation projects was implemented in Clackmannanshireupstream of Menstrie village. In total, 47% of the Menstrie Burn catchment (1200 ha) was subjected to the planting of, predominantly, productive conifer woodland (Sitka spruce). This scale of land use change was expected to provide elements of NFM in the medium to long-term, but concerns were raised about the potential for pre-planting cultivation to increase flood flows in the shorter-term. In response to this research has been undertaken in Menstrie catchment since 2016 to analyze the different processes which affect flood generation namely: planting technique, overland flow sediment loading. This has been monitored at seven different locations (according to cultivation) and surface flow in the main watercourse and its tributaries.Seven study plots (one unplanted plot, three plough cultivation plots, two excavation mounding technique plots, and one hand screefing cultivation plot) with secured repetition have been modeled over a two year period using GR4H rainfall runoff conceptual model. This model used an hourly time step of observed rainfall, flow, evapotranspiration, and temperature data time series to generate behavior of each monitored plot with similar preferences of observation.The GR4H model optimizes four free parameters: maximum capacity of production store (mm), groundwater exchange coefficient (mm), the maximum capacity of routing store (mm) and time peak ordinate of hydrograph unit UH1 (day). This model has been built for two tributaries of Menstrie burn, the Menstrie burn and all seven study plots. This approach has simplified output from field observation, assisted in a better understanding of the data gaps and elaborated on the observed trends of vegetation processes. Moreover, the initial outputs from this model can be useful for future climate change mitigation via nature-based solutions.REFERENCES:Scottish Executive, 2006, Scottish Forestry Strategy. Forestry Commission Scotland. pp.87. ISBN: 0-85538-705-X Natural Flood Management Handbook, 2005, SEPA,Final Report, Flooding in Menstrie Foothills, Clackmannanshire Council, 2005Hydrological Modeling System HEC-HMS, Technical Reference Manual, USA Corps of Army 2000 [ABSTRACT FROM AUTHOR]

In many fen peatland ecosystems in e.g. brook valleys, natural vegetation is adapted to wet conditions and a large input of buffering cations. In these systems, upward seeping groundwater is a major control on water quality in the root zone and contributes to the soil's buffering capacity. The quality of groundwater entering the root zone of seepage-dependent ecosystems is controlled by many factors, including land use in the infiltration area and geohydrochemical conditions that groundwater encounters along its way from through the subsoil infiltration to exfiltration (seepage). While seepage water quality is often considered static, changes in land-use and climate may lead to considerable modifications. Specifically ecosystems reliant on groundwater that infiltrates in areas with intensified agriculture and short groundwater residence times may be at risk due to forthcoming increased nutrient inputs. However, reactive subsoil compounds may interact with dissolved nutrients and reduce, temporarily buffer, or increase pressure on vegetation of seepage-dependent peatland ecosystems. To date, however, a generic framework to identify conditions under which seepage dependent peatlands are at risk is absent. Here, we present a novel framework that (1) designates geochemical subsoil properties to any geographic position in the Pleistocene part of The Netherlands (2) quantifies the subsoil buffering potential with given input water quality and (3) provides solutions for local management to counteract negative impact (e.g. reduced carbon uptake) on peatlands. The framework allows rapid identification of how environmental changes may modify seepage water quality and under which conditions such changes put peatlands at risk. [ABSTRACT FROM AUTHOR]

Field campaigns were carried out to investigate biosphere-atmosphere exchange of reactive nitrogen compounds with the aim to test novel measurement techniques in eddy-covariance setups for continuous determination of ammonia and total reactive nitrogen fluxes. While high-frequency concentrations of ammonia were measured with a quantum cascade laser absorption spectrometer, a custom-built converter coupled to a chemiluminescence detector was used for the determination of total reactive nitrogen. Campaigns were conducted above cropland, forest and peatland ecosystems. Substantial high-frequency damping on fluxes in the range of 15-35% was observed. Damping was found to be dependent on land use and its specific setup, but appeared to be mainly invariant with wind speed and atmospheric stability. Nitrogen fluxes showed strong diurnal variability after fertilization on arable land with peak emission during midday. Moderate diurnal variability with highest uptake around noon was found at a forest site located in a national park. Exchange patterns were mainly controlled by concentration and to a lesser extent by light, vapour pressure deficit, and surface wetness depending on season and land use. An analysis of multidimensional functional relationships with artificial neural networks showed that up to 50% of the variability in nitrogen fluxes could be explained when the three most dominating factors were used. While measured data and results from a state-of-the-art inferential exchange scheme compared fairly well, a combination of the two approaches could be used for determining seasonal nitrogen budgets for natural and semi-natural sites. The results help improve our knowledge of the temporal variability of surface-atmosphere exchange over different ecosystems, thereby providing useful validation opportunities for inferential models. It is highly desired to complement standard long-term observations of greenhouse gases – at least at some selected key sites – with high-frequency reactive nitrogen measurements to strengthen process understanding of coupled nitrogen and carbon cycles. [ABSTRACT FROM AUTHOR]

The revaluation of waste as soil amendment fertilizers in the restoration of land improves environmental quality. This practice also represents an opportunity to promote economic activity in depressed areas. However, logistical aspects and those derived from technology limit the conditioning of waste so that they can be used in soils.The project focuses on waste from the forestry industry, mainly biomass ash, and sludge from water treatment from forest industries and small population centers. These residues were subjected to different types of conditioning. Different formulations were optimized to obtain quality substrates for use in degraded lands. Three plots will be established: a) quarry in the process of restoration, b) marginal agricultural land abandoned and c) soil degraded by fire. In each of these three cases, a monitoring area was established, with a small area (1000-2000 m2). The technosol applications varied between 5 and 50 L m2 (2-20 cm thick). The experimental design followed a random block design, with three repetitions per treatment. In each case, herbaceous species and / or forest species were established.Analysis of macronutrients, total heavy metals, organic compounds (BTEX + S, HAP, total hydrocarbons, etc), levels of microorganisms (Salmonella, E. coli), toxicity tests, with seeds were analyzed. Additionally, the quality of the organic matter was evaluated using C13 CPMAS NMR and infrared (FT-IR), as well as with novel calorimetry techniques (DSC-TG). [ABSTRACT FROM AUTHOR]

Hydrological regimes in arid and semi-arid areas can be significantly affected by climate and land cover changes. Due to urban expansion and ecological restoration programs, the Three-North Region in China has experienced dramatical conversions in land cover, which may result in changes in regional hydrological regime. Previous studies have demonstrated that compared to the effects of climate change, those of land cover change were less observable in recent decades. However, whether those effects may be intensified by future climate or not still remain unclear. In this study, a macro-scale hydrological model was employed to simulate the hydrological regimes in 2020-2099 under a Representative Concentration Pathway (RCP8.5) climate scenario, and remote sensing datasets of land use and leaf area index in 1983-1986 and 2011-2015 were used to generate two different vegetation parameters, which are assumed to reflect different land cover conditions for the two periods. The model was run twice based on the two vegetation parameters, and the differences between the simulations are considered as the hydrological effects of past land cover change in future. The results indicated that from 1986 to 2015, the forest area increased in northwest and north China, by 11691 km2 and 69 km2 respectively, while declined by 30042 km2 in northeast, and the total urban area has expanded by 1.3%. Based on land use condition in 2011-2015, annual evapotranspiration, runoff will both increase steadily due to the increasing temperature and precipitation in 2020-2099, and mean soil moisture will rise at first, then keep nearly unchanged at 505mm over the entire region. Compared to the simulation based on land use condition in 1983-1986, we find that the effects of land cover change will be growing significant in future and at the end of the century, runoff will be promoted by more than 3 mm/year and evapotranspiration will be decreased by more than 3 mm/year. Moreover, the spatial distribution of alteration in hydrological cycle is extremely uneven. The changes in humid zones are more obvious than those in arid and semi-amid zones. As a result, land cover change may cause more problems like dryland expansion in arid area and flooding in humid area than climate alone. Despite there are still remaining uncertainties in datasets and methods, this study provides new insights into the future impacts on hydrological regime of ecological programs and urbanization in Three-North Region. [ABSTRACT FROM AUTHOR]

In order to assess the combined effects of green-house-gas-induced climate change and land-use land-cover change (LULCC), we are producing regional climate model (RCM) simulations at multiple resolutions that are complementary to the North-American Coordinated Regional Downscaling Experiment (NA-CORDEX) simulations, but with future LULCCs that are consistent with particular Shared Socioeconomic Pathways (SSPs). In standard, existing NA-CORDEX simulations, land surface characteristics are held constant at present day conditions. These new simulations, in conjunction with the NA-CORDEX simulations, will help us assess the magnitude of the changes in regional climate forced by LULCC relative to those produced by increasing greenhouse gas concentrations. Understanding the magnitude of the regional climate effects of LULCC is important to the SSP-RCP scenarios framework. Currently, an assumption underlying this framework is that the pattern of climate change resulting from any given SSP-RCP pairing is relatively insensitive to the assumed pattern of LULCC, but the degree to which that assumption holds is an open question. Our work will help address this question, and inform thinking about possible needed modifications to the scenarios framework to better account for climate-land use interactions.Accordingly, in this presentation, we will examine the state of the climate at the end of the 21st century with and without SSP-driven LULCCs in RCM simulations produced using WRF under the RCP8.5 concentration scenario. The included LULCC change effects have been created following the SSP3 narrative using an existing agricultural land model linked with a new long-term spatial urban land model. [ABSTRACT FROM AUTHOR]

Changing-climate, -human society, and -ecosystems interact mutually within the earth system. To assess the potential impacts of climate and socioeconomic changes on each system and identify sustainable pathways, it is critical to better understand the interconnectedness among human-natural systems. While earth system models and integrated assessment models are applicable to explore this field, parts of their natural and/or human processes tend to be simplified depending on their scope. Therefore, it still remains a challenge to improve integrated modeling frameworks. In this context, the MIROC integrated terrestrial model (MIROC-INTEG) was developed. The modeling framework is composed of five process-based natural/human subcomponents. At its core is a land surface model (MATSIRO), which is coupled to three human components; water use (H08), crop production(PRYSBI2) and land use (TELMO). An ecosystem model (VISIT) calculates the C and N cycles among atmosphere-vegetation-soil. Although each sub-model can run independently, MIROC-INTEG dynamically simulates their interactions, embracing the water-food-energy nexus within a system. The goal of this study is to improve our quantitative understanding on coupled terrestrial systems at the global scale for past and future time-scales. Hence, we have run MIROC-INTEG following the Inter-Sectoral Impact Model Inter-comparison Project phase 2b simulation protocol (ISIMIP2b) with as its inputs an ensemble of bias-corrected forcing data of four general circulation models covering preindustrial, historical, and future time-periods under four representative concentration pathways. ISIMIP2b provides a unique opportunity for validation of simulation skill in comparison with other models' under a consistent protocol. Using temporally-downscaled 3 hourly climate forcing data and considering anthropogenic activities, MIROC-INTEG simulated agro-hydrological condition at a spatial resolution of 0.5°, globally.Within this contribution we present the first results of MIROC-INTEG looking specifically at the centennial-scale human-natural interactions over the period 1661-2099 and its consequences for long-term changes in fundamental hydrological variables, emphasizing on hydrological extremes. The results are presented at global, regional and large-basin scale and are compared against existing ISIMIP2b runs of the hydrological models H08 and CWatM. [ABSTRACT FROM AUTHOR]

Gradually increasing sea levels and extreme events related to changing climate conditions could trigger multiple hazards for low-lying coastal areas, determining increasing inundation and erosion risk for local communities, infrastructure and ecosystems. Moreover, there is growing evidence that socio-economic dynamics (e.g. unplanned urbanization, land use and demographic changes) would increase coastal flood risk in the next decades. Understanding how natural and human-induced drivers concur to determine exposure, vulnerability and risks in coastal areas is of paramount importance for mainstreaming effective climate adaptation and risk reduction policies into coastal zone management.In the frame of the SAVEMEDCOASTS project (www.savemedcoasts.eu), a Climate Change Coastal Vulnerability Index (CC-CVI) was developed to provide guidance and operative criteria for exposure, vulnerability and risk assessment in Mediterranean coastal areas. The overall aim of the index is to identify map and prioritize coastal areas at higher risk from climate-related hazards (sea level rise inundation and storm surge flooding) in vulnerable (flood-prone) areas, providing a knowledge base for national-scale adaptation planning and disaster risk management. The index combines a composite set of physical, environmental and socio-economic indicators representing (i) hazard-prone areas potentially inundated by sea level rise and extreme water levels in future RCP8.5 scenario; (ii) exposure, including indicators of economic, social and manufactured capitals; (iii) vulnerability, represented by indicators of geomorphic susceptibility to flooding and adaptive capacity. The CC-CVI was applied to the Italian shoreline considering a baseline scenario representing current climate and land use condition, and a future one for the 2050, integrating both climate projections and data simulating changes in the environmental and socio-economic systems. Results of the analysis include a range of spatial vulnerability indicators and statistics allowing to rank Italian coastal provinces according to their relative vulnerability to extreme sea level scenarios. The main steps of the methodology and the applicability of results for decision-makers and risk practitioners are here presented and discussed. [ABSTRACT FROM AUTHOR]

Land use is known to alter soil physical and chemical properties as well as impact on microbial communities in soils, which in combination can change soil ecosystem services. To optimise soil management for enhanced ecosystem services, we need to determine the explicit relevance of management driven diversity change for the resilience of soil functionality. Furthermore, from a regulatory and monitoring perspective, we need to better identify functionally relevant molecular indicators of land use change in order to evaluate the progress of land restoration. In this presentation, I assess the responses of a variety of soil, microbial and functional metrics to land management across a geographically distributed range of calcareous soil systems in the South of England. Their high levels of above and belowground diversity and the capacity to store large amounts of carbon are typical characteristics of calcareous grassland soils. In a landscape scale survey of old undisturbed grasslands, nearby croplands and a corresponding chronosequence of restored ex-arable grasslands, the recovery of soil was compared with microbial and plant community structures along a time gradient.DNA amplicon sequencing, microbial biomass and soil extracellular enzymatic activities are used to detect changes in the ecosystems with re-conversion of arable fields. All grasslands show higher organic matter contents than the arable fields, with a clear trend in increase with restoration time. Between treatments, land use specific differences in microbial communities are detected and significant bacterial and fungal indicators were determined on the species (OTU) level. Hydrolytic enzyme activity did not follow that classification as clearly, but interacted with soil chemistry and each other, indicating the complexity of these ecosystem functions that impact soil nutrient cycling and fertility. [ABSTRACT FROM AUTHOR]

Floods can result in significant damages and loss of life especially in remote communitiesand in developing countries. People living in such areas frequently lack flood warninginformation to prepare for floods in advance due to sparse hydrological measuring networksand delays in accessing field data. Recently, it has been suggested that the large-scale spatialcoverage and near-real time availability of remote sensing data may be suitable to identifypotential flooding during extreme events and in data-scare regions. While water levels, rivermorphologies and inundation extents can be measured directly from space, river dischargecannot be monitored directly from satellite sensors. Tremendous efforts have been devoted toestimate river discharge from these variables using rating curves, hydraulic modelsor hydraulic geometry. The ratio between brightness temperature at a land pixeland at a water pixel has also been used to estimate river discharge. However, anaccurate, fast and universally robust method to estimate river discharge or flood flowsfrom satellites has not yet been developed for use in ungauged and sparsely gaugedareas. Here we demonstrate a new approach that uses the difference in day and nightland surface temperature (ΔLST) derived from the Moderate Resolution ImagingSpectroradiometer (MODIS) products for flood detection. In previous work, ΔLST has beenassessed along with flood inundation qualitatively demonstrating that low ΔLST values areassociated with flood events while dry seasons typically had high ΔLST values. We extendthis analysis to quantify the relationship between flood flows and ΔLST values andunderstand the flood prediction potential of ΔLST. Flood flows were derived from 222hydrological reference stations at unregulated catchments across contrasting hydro-climateconditions in Australia. The relationship between flood flows and ΔLST valueswas modelled using a regression tree technique governed by climate conditions,catchment properties and hydrograph characteristics. The results reveal that theΔLST – flow relationships mainly depend on local climate conditions and catchmentproperties. Strong and moderate negative correlations were found in hot humid andcool temperate regions. Small positive correlations happened in mild temperateregions while strong positive correlations occurred in hot dry regions. The findingshighlight conditions where ΔLST will be useful for river discharge estimation, floodpredictions and flood warning system in sparsely gauged and ungauged regions. [ABSTRACT FROM AUTHOR]

Water policy, planning and design problems are often nested across scales and can require detailed understanding of upstream processes (e.g. distributed agricultural dams, upstream land use change and flow intermittency). Traditional approaches to streamflow monitoring are limited by sparse geographical coverage and relatively high costs of gathering observations with streamflow measurements typically collected at a catchment outlet. This can be problematic when attempting to understand the non-linear and complex runoff behaviour present on hillslopes and reaches throughout an entire river network. Differences in catchment characteristics result in highly variable drainage patterns. This presents challenges for the calibration of hydrological models regarding their ability to represent inter-catchment runoff behaviour. Low cost and innovative data collection approaches provide opportunities for water management questions which span multiple scales by complementing existing observations and addressing local data deficiencies.This study combines process modelling and complementary data (e.g. from distributed sensors) to improve the representation of local scale flow processes. Paired (in-stream and on-bank) temperature sensors are implemented across nine headwater sites within a small catchment located in South Australia. A classification scheme was developed to infer whether the stream was 'wet' (flowing) or 'dry' (not flowing) and low flow metrics were determined at each site (e.g. number of zero flow days, number of zero flow periods and average duration of zero flow periods). The results demonstrated a high degree of heterogeneity of flow permanence within the small catchment area (10 km2). A physically based hydrological model, HydroGeoSphere, was calibrated to the outlet and validated with the classified 'wet'-'dry' binary data showing reduced performance at three out of four upstream sites. These results highlight the value of inexpensive data collection methodologies by providing opportunities to improve the calibration and validation of hydrological models. [ABSTRACT FROM AUTHOR]

Changes in land-use and climate can contribute to important CO2 emissions from soil to the atmosphere. In such scenarios, models are necessary to predict future changes, to extrapolate results to larger areas as well as to explore and understand underlying mechanisms. Many drivers of ecosystem dynamics play a role in tropical regions, including deforestation, land use intensification, increasing concentrations of atmospheric CO2 and possible changes in temperature and precipitation. Our study aims to simulate changes in soil C associated with transitions from the natural forest vegetation to oil palm plantations as observed in the Jambi region of Sumatra, Indonesia. For this we modeled the vegetation and soil C using the Community Land Model (CLM 4.5) and changed the model parameter values to better fit the model to the observations.Two aspects were necessary to obtain realistic model outcomes: properly simulating the state of the natural forest vegetation and capturing the dynamics after land use change. Parameter adjustments were made in order to approximate simulations to observed forest productivity, biomass, soil respiration and soil C stocks. Forest disturbance through selective logging also was a factor that needed to be accounted for. Oil palm growth was simulated using a PFT recently developed and calibrated for the same site. Finally, the simulation of soil carbon stocks and soil respiration was improved by adjusting model parameters controlling the turnover time of soil C pools. When using the default parameter values, the model underestimated total soil organic carbon and overestimated soil respiration of both forest and oil palm. The simulated forest carbon stocks increased after model calibration, showing a better agreement with observations (from an average of 6.3 kg C m-2 to 23 kg C m-2; compared to the observed value of 24 kg C m-2). Simulated soil respiration decreased, also approaching observed values and lowering the model RMSE from 20.2 to 16.3 mg C m-2 hour-1. For oil palm, model calibration improved the simulation of soil C stocks (from 5.5 kg C m-2 to 13 kg C m-2, observed value18 kg C m-2) as well as soil respiration (RMSE lowered from 12.5 to 11 mg C m-2 hour-1).Once the model is fully calibrated, we will be able to estimate the long term effects of land use change and compare them to those of CO2 fertilization. We will also be able to estimate the regional short and long term impact of land use on soil C stocks and fluxes. [ABSTRACT FROM AUTHOR]

Assessment of stream flow dynamics reveals principal characteristics of a river basin as it results from a complex blend of hydrological drivers. Earlier studies suggest climatic parameters and land use changes are the major causes of river flow changes in the basin. However, introduction of large-scale irrigation and other irrigation management activities in the basin will also play a crucial role in stream flow variations. The present work aims to understand the contributions of these drivers towards decreasing river flows in the Malaprabha river basin, Karnataka, India. Results of the Mann-Kendall trend test showed non-significant decreasing trends in annual and seasonal rainfall patterns in the area. The effect of Land Use /Land Cover (LU/LC) change on stream flows was analyzed using decadal LU/LC maps for the period 1985,1995 and 2005 as inputs to the Soil Water Assessment Tool (SWAT) hydrological model. Further, the effect of Malaprabha reservoir on stream flows was analyzed by performing SWAT simulations for with and without reservoir conditions. The comparative analysis showed that there is negligible contribution of decadal LULC on river flows. However, the presence of the reservoir was found to be contributing 43% of stream flow variability. This study revealed that at catchment scale reservoir storage and related operational activities affects the river flows more significantly than LULC changes. [ABSTRACT FROM AUTHOR]

Both global changes and the growing vulnerability of urban areas to hydrological risks, show the need for implementing additional strategies for the integral management of water insecurity. Even though different objects may be differently affected by the same hazard, more than one hazard may hit objects in the same watershed and bring damage to the overall community. Risk transfer tools, such as insurance, have emerged as an effective strategy to ensure economic resilience at diverse socio-economic levels and productive sectors. Through the coupling of a risk-based insurance fund model, the Hydrological Risk-Transfer Model (HRTM-SHS), with socio-natural driver's projections, one can evaluate the actuarially fair premium value against either urban floods or hydrological droughts. The insurance mechanism in this model is based on a multi-year contract scheme (MYI) where the damage cost evaluation uses a "what if" approach at the watershed scale. The framework has been applied for both a real case with changing conditions of flooding and a scenarization of water scarcity in Southeast Brazil. With the risk-based model, we could assess the impact in the optimized premium of both climate and land use changes, as well as socio-economic scenarios of water demand. This approach is useful to evaluating the financial recovery mechanisms solvency post-disaster limited to insurance markets with low penetration and limited information. It is expected that a diversification of risk coverage and MYI would lead to more stable insurance funds. Additionally, it supports the planning of financially resilient environments to face of water hazards impacts under susceptibility scenarios. [ABSTRACT FROM AUTHOR]

Increased anthropogenic inputs of nitrogen (N) to the biosphere during the last decades have resulted in increased groundwater and surface water concentrations of N (primarily as nitrate). Although measures have been implemented to reduce N-inputs, they are not always reflected in decreasing instream nitrate concentrations and loads. This limited response to the measures can either be caused by an accumulation of N in the soils acting as a biogeochemical legacy or by long travel times (TTs) of inorganic N to the streams forming a hydrological legacy. Here we jointly analyze agricultural and atmospheric N inputs with long-term observations of nitrate concentrations and discharge in a mesoscale catchment in Central Germany to learn on time lags and the potential build-up of legacies. For three nested sub-catchments with increasing agricultural land use, we assess both, the catchment scale N budget and the effective TT of N to evaluate time lags and the potential for the buildup of N-legacies. We show that in the 42-year-long observation period, the catchment received an average N-input of 36.1 kg/(ha a), of which 97 % derived from agricultural sources. However, the riverine N-export sums up to 5.6 kg/(ha a) indicating that the catchment retained 85 % of the N-input. Removal of N by denitrification could not fully explain this imbalance hinting to the accumulation of an N-legacy in the catchment. Log-normal travel time distributions for N fitted as transfer function of the input and output time series differed seasonally, with modes spanning 8–17 years. Under low-flow conditions, TTs were found to be systematically longer than during high discharges. Systematic changes in C-Q relationships suggest a dominance of hydrological N-legacy rather than a biogeochemical N-fixation in the soils, which should result in a stronger and even increasing dampening of riverine N-concentrations after sustained high N-inputs. The input-output imbalance, the long time-lags and the lack of effective retention by denitrification in the catchment let us conclude that catchment management needs to address both, a longer-term reduction of N-inputs and shorter-term mitigation of today's high N-loads. [ABSTRACT FROM AUTHOR]

The aim of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) is to better understand climate impacts across sectors using a multi-impact model framework. The second phase of this international effort (ISIMIP2b) is designed to provide robust information about the impacts of 1.5°C and 2°C global warming, as solicited by the IPCC's special report on this topic. Here we present the ISIMIP2b simulations conducted with version 4.5 of the Community Land Model (CLM). Bias-corrected output from four global climate models contributing to phase five of the Coupled Model Intercomparison Project (CMIP5) is used to drive CLM at 0.5° resolution. Land cover information is obtained through the second phase of the Land Use Harmonization project (LUH2). Besides complementing the vast – and continuously growing – data base of publicly-available ISIMIP output, a key advantage of the CLM data set is that it provides information relevant for several sectors through one consistent set of simulations. This implies that climate and land use change impacts on agriculture, biomes, lakes, water and permafrost can now be assessed with consistent climate forcing as well as consistent model physics. [ABSTRACT FROM AUTHOR]

Fingerprinting techniques provide a means of assembling valuable information on the principal fine-grain sediment provenance at catchment scale. However, the outcome of these studies often depends on the type of model and the selection of the tracers used to determine the relative contribution from different sources. Despite the rapidly increasing number of studies reporting the use of fingerprinting as a tool to detect the sediment provenance, there is a need to refine or clarify existing approaches and the key components of the current methodological procedures.To tackle this problem the aim of this study is to compare the results from two recently used unmixing models, MixSIAR (Bayesian model) and FingerPro (Determinist model). Furthermore, the new D-MixSIAR and a hierarchical approach of the FingerPro model are tested. Both models are tested in the Barués area as a representative catchment of the Mediterranean mountainous agroecosystems. The study catchment was selected because of its independent behavior and its lithological homogeneity composed by sandstones, claystones and conglomerates of the Uncastillo Formation to better identify the factors of variation involved. Radionuclides and stable elements contents in sediment mixtures and possible sources such as agricultural, rangeland, afforestation forest, bare soil and channel bank samples collected across the catchment were used to assess the relative contribution from different land uses/land covers. After running both types of models, the results obtained allowed to identify the differences and similarities from FingerPro and D-MixSIAR when they are applied to the same dataset. Our results aim to shed light to: i) There is a need for using a tracer selection procedure? ii) Do all tracers give useful information to the model or some of them are leading the models to different results? iii) How sensitive are the models to the traditional fingerprinting procedures such as tracer selection, source grouping, and source removal? [ABSTRACT FROM AUTHOR]

Sediment connectivity is an emerging property of geomorphic system. Connectivity within a catchment widely depends on its climatic conditions and morphological heterogeneities, and it is accurately influenced by the anthropogenic (cropland, land use changes, infrastructures) alteration of the landscape (López-Vicente and Álvarez, 2018). Sediment connectivity allows to characterize the structural properties of the landscape (topography, soil roughness, drainage network) and, when considered, at a specific spatio-temporal scale, and in combination with forcing processes (e.g., rainfall-runoff and sediment delivery), can perform as a useful tool for an enhanced landscape management. The assessment of sediment connectivity through usable indices or models is a major concern for the scientific community dealing with catchment/landscape management. In this context, the present study evaluates two connectivity indices at distinct catchment scales: (i) an aggregated and new index of connectivity (AIC) developed by López-Vicente and Ben-Salem (2019) to integrate climatic and soil physical data with topographic and land use information and (ii), an index of connectivity (IC) as expressed in Cavalli et al. (2013). IC was computed using the available 'SedInConnect v2.3' software (Crema and Cavalli, 2018) and two scenarios as weighting factor: the topographic surface roughness and the land cover Manning's n values.The study area is the Vero river catchment (380 km2) that is located in the Southern Pyrenees and within the Ebro river basin (Huesca province, Aragon, NE Spain). The northern part of the catchment is sub-humid, mountainous (deep and sheer gorges are frequent), and covered with forest, whereas the southern part, under semi-arid conditions, has hilly and gentle topography, with alluvial terraces, and it is mainly devoted to agriculture (vineyards, winter cereal, alfalfa, rape, olive and almond groves). Small villages and one village (Barbastro), and many roads and trails appear along the catchment influencing the overland flow pathways. However, there is not any dam that disrupts the permanent river flows. All input (e.g., LiDAR-derived DEMs) and output maps were generated at 5 x 5 m cell size; except for those of a small headwater subcatchment for which 1 x 1 m data were obtained. The analysis in the subcatchment study area aimed at evaluating the effect of different resolutions on indices performance. Results of AIC were compared with those obtained with the two IC scenarios. The major differences of the two approaches were clustered around different cover types and slope values in the different catchment compartments. This can be ascribed to the climatic and soil information integration on the one hand, and to the roughness/slope distribution of upper subcatchments on the other. Further analysis is needed at subcatchment scale. - Cavalli M, Trevisani S, Comiti F, Marchi L (2013) Geomorphology 188, 31–41.- Crema S, Cavalli M (2018) Comput. Geosci. 111, 39–45.- López‐Vicente M, Álvarez S (2018) Earth Surf. Process. Landf. 43, 1403–1415.- López-Vicente M, Ben-Salem N (2019) Sci. Total Environ. 651, 179–191. [ABSTRACT FROM AUTHOR]

Over the past decades, the research community has made several efforts to infer hydrological information on ungauged basins by using similarity concepts. An ongoing challenge within this field is to elucidate the relation between physical, climatic and hydrologic similarities to improve process understanding, and to use that knowledge to extrapolate information from gauged to ungauged basins. We address this challenge in the context of water resources in Chile, where multi-institutional efforts have been oriented to characterize the water balance across the country under historical and future climatic conditions. Within this project, we perform catchment classification over 82 Chilean basins in natural regime, using a Bayesian clustering algorithm. Basins information is collected from satellite products and the CAMELS-CL dataset, which provides catchment-scale hydrometeorological time series and physiographic attributes for continental Chile. To explore overlaps between the different types of similarities, we apply several classification schemes: (i) physiographic (P, using land cover type and elevation), (ii) climatic (C, using aridity index, precipitation seasonality and fraction of precipitation falling as snow), (iii) hydrological (H, using a suite of selected signatures) and (iv) combinations of the above (P+C and P+C+H). Classifications solely based on P, C or H attributes, result in three, five and three clusters, respectively. The application of P+C and P+C+H schemes results in 12 and 11 clusters, respectively. Moreover, we assess the ability of the various classification schemes (e.g., C clusters) to group catchments according to the rest of predictors (i.e., P and H). Our results show that P and C classifications are able to group hydrologically different catchments (i.e., signatures). Conversely, an H classification has discriminatory power over C attributes, but not over P descriptors. Additionally, C and P+C classifications generate more classes than P clustering, allowing a finer representation of hydrological attributes (specially P+C). Overall, our results suggest that hydrological behaviour is mostly explained by P+C attributes, with predominance of C over P descriptors. [ABSTRACT FROM AUTHOR]

The Indo-Eurasian plate collision not only caused the uplift of the Himalayas and the Tibetan Plateau due to compressional tectonics, but also created rift valleys through extensional tectonics and local collapses of the plateau. One major rift valley, the Thakkhola half-graben, extends from the plateau in the North to the Dhaulagiri and Annapurna massifs in the South. Bounded by the steep Dangardzong fault in the West and the less pronounced Muktinath fault in the East, the half-graben is nowadays filled with up to 3 km thick Plio- and Pleistocene sediments. Underlying clay shales of the Jurassic Spiti Formation are strongly water swellable and prone to landslides.In the Muktinath Valley, an eastern tributary basin of the Kali Gandaki (Mustang, Nepal), these conditions led to a complex landslide system with massive impacts on the local population. Multiple interacting slope movement processes (toppling, falling, sliding, sagging, slumping, flowing) can be observed in the area, that are mainly driven by rare precipitation events during the summer monsoon in this semi-arid (c. 350 mm/a) mountain setting and artificial irrigation. The local population lives in a 'symbiotic' relationship with the landslide system using the tops of the sliding blocks as farmland and irrigating them via pipelines and open channels with water from different sources, incl. precipitation, meltwater, spring intakes (also from a neighboring catchment) and spring water originating from the landslide's active shearing planes. Since such activities are supposed to further boost the system and even trigger new sliding processes in temporary stable areas, the analysis of cause-and-effect relationships between land use and the natural environment are highly relevant. We present first results of the research project mukslide that aims i) to better understand the landslide system (drivers and controls, cause and effect), ii) to identify hotspots and quantify rates of (sub-) recent movement, and finally iii) to provide recommendations for mitigation. Here, we provide first results and introduce a geomorphological map of the catchment. Special emphasis is placed on mass movement related forms and processes, indicators of recent landslide activity (e.g. cracks and fissures, stretched roots, active shear planes, damaged infrastructure), hydrological characteristics, and the distribution of Spiti shale outcrops. Landslide dynamics are reconstructed using multi-temporal satellite scenes (Worldview, Pleiades), UAV/SfM based high-resolution DEMs, and photo comparisons. First data on recent movement indicate a complex pattern and highly variables rates of up to 0.5 m/a in large areas and up to 15 m/a in the recently most active part of the landslide. This highly active earthflow area enlarged strongly in the recent past and several signs point to a further growth in the near future. [ABSTRACT FROM AUTHOR]

Today, peatland management is more and more perceived as a fundamentally important land use based greenhouse gas (GHG) mitigation option. Understanding current peatland use and expected changes provides a background to develop recommendations for future management frameworks and can facilitate good peatland management practices (PMP) permitting long-term emission mitigation in Europe. The objective of this study was to exemplify knowledge and stakeholder's views on peatland management status and development in Europe and to show the relationship between PMP with climate mitigation potential under different environmental conditions and institutional settings. Our research questions, to facilitate in-depth examination of PMP were: i) Which PMP exist and what are expected trends? ii) What is the current implementation status of PMP with regards to evaluating their GHG mitigation potential? iii) How are GHG emissions and removals from organic soils currently reported to the UNFCCC and what are the challenges in reporting development? iv) Are there governmental incentive-based policy instruments and innovative voluntary private sector initiatives, aiming at PMP that support climate change mitigation?We carried out a web-based survey in eight peatland-rich European countries (Finland, Sweden, Norway, Denmark, UK, the Netherlands, Germany, Poland). 60 experts, including researchers, stakeholders acting as multipliers for farmers (e.g. farmer's associations, NGOs) and government representatives, provided valuable insights on a regional and national level.In our survey, stakeholders saw agriculture as main driver to peatland use, with increased GHG emissions, biodiversity loss and declined water quality as its main impacts. Majority of the stakeholders expected croplands to be used as grasslands and agricultural areas to be rewetted. However, geographic variability of expected land use changes was apparent. Prevailing PMP (such as drainage methods) were also reported to vary significantly across Europe. Therefore, the development and assessment of PMP and especially the policy instruments guiding them should account for the regional drivers and bottlenecks. Survey results further show that a range of PMP, aiming at GHG emission reduction while maintaining production options, are in testing phases across Europe. Only a few, however, can be considered mitigating climate impacts (i.e. good PMP) to the date. It is therefore required to promote further research on the mitigation potential of currently tested PMP. The lack of data (activity, mapping, and emission) and in some cases poor separation of peatlands from other land use types was also seen as a bottleneck for developing evaluation methods for national greenhouse gas reporting to the Intergovernmental Panel on Climate Change (IPCC). Integrating identified good PMP as part of the IPCC reporting, however, would provide positive feedback and motivation for practical implementation. Only few policies and policy instruments directly aiming at GHG mitigation on peatlands exist. Other policy instruments mentioned, may not set GHG mitigation on peatland as the main goal but might have a spill-over effect. Cross-sectoral institutional interlinkages on multiple governance levels indicate that climate change mitigation is just starting to be mainstreamed.The study is part of the PeatWise (Wise use of drained peatlands in a bio-based economy) – project funded by the FACCE ERAGAS. [ABSTRACT FROM AUTHOR]

Human activities are altering the global water cycle in multiple ways. Both landscape-driven hydrologic changes (land cover and land use intensification, irrigation, hydropower development), and climate-driven hydrologic changes (temperature and precipitation changes) can be identified. While catchment-scale runoff is expected to decrease due to irrigation, and increase due to certain types of land use intensification, many studies have shown complex and contrasting anthropogenic effects. For example, studies integrating land use-land cover changes to watershed-scale responses in paired catchments show that climate drivers cannot alone explain hydrological changes and thus the land use changes are likely to be important. In this analysis, we focus on how the hydrologic state of agricultural catchments is related to agricultural productivity and water use efficiency. We follow a data-based approach, and test a conceptual framework using data from 150 catchments in the US. The framework consists in comparing broad metrics of agricultural efficiency and productivity to hydrologic state variables (like rainfall-runoff ratios) across a range of agricultural settings and climates. We hypothesize that agricultural efficiency is related to hydrologic function, a measure of the capacity of the system to transfer inputs into outputs, and that this relation may constrain agricultural output under climatic changes. We use the yield-to-fertilizer use ratio, a proxy for nutrient use efficiency, as an assessment for agricultural performance. In the same way, we employ the runoff ratio as a broad metric of hydrological performance. We calculate these ratios for the major US catchments at annual temporal scales. Agricultural metrics are calculated using yield data available through the National Agricultural Statistics Services (NASS) database from USDA, and county-level fertilizer input data. County data are then masked to the watershed database and compared to the long-term discharge data, both data types available through the Global Runoff Data Centre (World Meteorological Organization). Rainfall and temperature data are available through the Climatic Research Unit (CRU) database (University of East Anglia, UK). The proposed conceptual framework is assessed by testing correlations between nutrient use efficiency and runoff ratio. [ABSTRACT FROM AUTHOR]

Peatlands constitute the largest soil carbon stock in Ireland with 75% of soil carbon stored in a peatland area covering an estimated 20% of the land surface. In spite of their crucial role as carbon stores and potential carbon sinks, peatlands often are affected by past and present disturbances related to various land use activities, such as drainage, change or loss of vegetation cover and compaction. Afforestation, grazing and turf extraction for energy and horticultural use are assumed to be major drivers of peatland degradation in Ireland, potentially leading to soil carbon mineralization, while contributing to increased carbon emissions. Current research funded by the Irish Environmental Protection Agency (EPA) addresses these land use pressures with a major goal to investigate the impact of land use on carbon stocks in Irish peatlands and to model carbon emissions from land use activity. In this context, a nationwide peatland survey has been conducted between May 2017 and December 2018, assessing vegetation structure and sampling entire peat profiles at 280 sampling points throughout Ireland. Here, we present results of the national survey hypothesizing that land use activity is a major driver for altered peatland properties and carbon stock. We examine how land use alters basic edaphic, hydrological and vegetation properties of peatlands and discuss an approach for assessing carbon loss across different land use categories. [ABSTRACT FROM AUTHOR]

Conservation state agencies need information to guide planning activities and allocation of limited mitigation resources at statewide scale. These agencies often use watershed modeling tools, but at watershed scale, to characterize site-specific processes and then to efficiently evaluate conservation alternatives. Information on few individual watersheds cannot be scaled up to the entire state. Watershed simulations are performed by multiple stakeholders under uncoordinated efforts, often using different modeling tools, varying assumptions, and time periods. Development of a single watershed simulation can be time-consuming as it requires understanding of the model input requirements, knowing of input data sources, and efficient development of model input databases. In this study, we propose an automated procedure to perform large scale non-point source assessment, such as statewide, though the implementation of linked watershed-scale simulations. The objective is to provide the means for estimation of long-term averages of non-point source pollution at state, watershed, and field scales using the same assumptions and procedures. The U.S. Department of Agriculture – Annualized Agriculture Non-Point Source (AnnAGNPS) pollution model was applied to the U.S. State of Iowa using publicly available datasets. The state was divided into 271 hydrological units with average area of 41000 hectares, each representing a watershed simulation. The model was applied in un-gauged mode with the objective of generating long-term relative trends between land use/conservation alternatives rather than absolute estimates. Individual hydrological units were further subdivided into sub-catchments (approximately 1 hectare each) and reaches to describe field conditions. Automated procedures were developed to preprocess data and to develop input database based on temporal and spatial characterization of sub-catchments and reaches for weather, soils, topography, and management. Findings from this study support state agencies in developing guidelines and recommendations for future decision support systems implementation, generation of state-wide GIS data layers of non-point source pollutants at field scale, and generation of watershed simulation templates for use as starting point for future simulations. [ABSTRACT FROM AUTHOR]

The vertical distribution of organic carbon in soil (SOC), considered to be a key component of the carbon cycle in the soil and difficult to delimit in mountain ecosystems. The purpose of this research was to determine the sequestration of organic carbon in the soil according to three types of land use in the Neamtu catchment. Being situated in the Carpathian and sub-Carpathian zone, approximately 77% of the Neamţu river basin territory is wooded with mixed forests. Furthermore, there are significant areas occupied by pastures, meadows and bushes. The most common changes of intended land use were: from forest to grassland, from forest to arable, from forest to urban use, from grassland to arable, from grassland to urban use, and less, from grassland to forest or from arable to grassland. In case of deforestation or fire, the SOC is reduced by an amount equivalent to biomass missing. As a result of the insect attack, the living biomass turns into deadwood and the total organic carbon will persist for a while even after decomposition of the wood, which will be incorporated into the forest soil. Litter and soil organic carbon last longer after fire or deforestation, but in time it is eroded either reshuffled or mineralized. Based on complexity of SOM due to heterogeneous mixture of functional groups, distinctly FTIR working procedures and data interpretation are demand to establish the fingerprint of SOM composition. The spectrum obtained is the product of the vibrations of the bonds within a molecule that are produced after passing an IR beam through a sample and collecting the resulting wavelength information.There were four intensive field campaigns of different types of use, summing up 80 sampling points at two depths (0-15cm, 15-30cm). Estimate of sequestration and carbon stock storage is achieved with greater accuracy at local scale. Spectral characterisation of soil samples was performed using a Bruker Vertex 70 equipment, while the carbon content was determined by combustion at 1000oC with Analytik Jena multi N/C 2100 with HT 1300 solid module and other general analyses. Different absorption bands were noticed along the frequency range 600-2500 cm-1 being directly related to the type of functional groups and chemical bonds from the substrate, while are influenced by the specific site conditions (layer thickness, soil type, texture, forest type, vegetation composition) and aliphatic dominating band The rate of carbon recovery depends on the type of substrate, organic compounds, volatile salts, water content, inorganic carbon and crop management. [ABSTRACT FROM AUTHOR]

Urbanization and the associated urban sprawl are ongoing global trends. Urban sprawl dynamics can be measured by the expansion of urban areas to the periphery, the scattering of settlement areas as well as the land uptake per capita. For example within some regions population densities decline, at the same time, new areas are opened up for residential constructions, resulting in high land uptake rates per person. Due to these urban sprawl dynamics, the amount of impervious surfaces is highly variable across settlements and regions; moreover, affecting ecosystem services. In general, an increase in impervious surfaces causes intensified surface runoff and inhibits infiltration. This in turn can reduce water quality of streams, urban groundwater recharge or increase the risk of flooding. This study investigates land use dynamics in two areas covering small and middle-sized cities in Lower Saxony, Germany. Different scenarios for urban-rural development are formulated based on information on the development of settlement areas and green spaces derived from the current public discourse and from regional trends described in literature and reports. Regional population dynamics are taken from population projections carried out by the statistical office of Lower Saxony. Then, the formulated scenarios are translated into percentages of settlement area and green space as well as population densities on a 1 km² grid.We simulate the changes in urban and rural water fluxes for the different scenarios using the surface urban water and energy balance scheme (SUEWS) (Järvi et al., 2011). The land use scenarios are assessed both, on a local scale, in per capita surface runoff per 1 km², and on a regional scale, in surface runoff per study region. Finally, the scenarios are ranked according to the ratio of local surface runoff to regional surface runoff. Furthermore, growing and shrinking areas are defined. Based on the ranking, development potentials and their effects on the water balance will be discussed.Järvi, L., C. S. B. Grimmond, and A. Christen. 2011. "The Surface Urban Energy and Water Balance Scheme (SUEWS): Evaluation in Los Angeles and Vancouver." Journal of Hydrology 411:219–37. [ABSTRACT FROM AUTHOR]

Understanding how land use change can affect natural dynamics of water resources in Amazon and Brazilian Cerrado is of importance due to the constant pressure for deforestation suffered by these biomes. In this work, the dynamic vegetation model with river routing and flood dynamics INLAND-THMB (Integrated LAND Surface Model - Terrestrial Hydrology Model with Biogeochemistry) was used to simulate how land use change (LUC) can affect the water balance, river discharge and flood dynamics in the Amazon Basin and in Brazilian Cerrado. To achieve this goal, we performed simulations following the recent Global Carbon Budget Land modelling protocol (Trendy-v7) and compared the S2 (historical CO2 and climate and time-invariant 1700 land use mask) and S3 (historical CO2, climate and land use). Thus we can evaluate the effects of LUC keeping the information of dry and wet events during the period. To better represent the land use state in S3 simulation, we compiled deforestation information from the PRODES/INPE project in the Brazilian Amazon and Cerrado and produced a map with remaining natural area for each year. The evaluation was performed to each biome separately and also in some of their sub-basins. In the Amazon, we looked at the upstream Amazon Basin (Alto Solimões), which includes an area with very low LUC, and at the Madeira, Tapajós and Xingu all in the arc of deforestation and in Cerrado at Tocantins Basin. Preliminary results show higher river discharge related to LUC, as expected, and also less available water, since the ET decreases when we include anthropic changes in land cover in the model. It is important to highlight that this study did not include atmospheric feedbacks in the precipitation, which can mask some of the results, since considerable amount of the Amazon precipitation is provided by recycling as shown in previous studies. [ABSTRACT FROM AUTHOR]

Coastal areas in Bangladesh undergo different morphological changes not only just bythe climate change induced different disasters and sea level rise but also humaninduced changes. Furthermore, being situated in tropical area, the country receives lotof rain during the monsoon period. This study has been conducted in two coastalunions namely Banishanta and Sutarkhali under Dacope upazila of Khulna districtin Bangladesh. During the year of 2007 and 2009, these areas had been severelyaffected by two consecutive cyclones. Several studies have been conducted on this bigdelta to understand the rate of morphological changes over time mostly in termsof land accretion or erosion mainly. However, whether this monsoon period andcyclones have an influence in coast has not received due attention yet. Therefore, themain objective of this study is to detect morphological changes occurred in thecase study areas taking seasonal monsoon and cyclones into account through theanalysis of satellite images. Two Landsat images (one for pre-monsoon (March)and another post-monsoon (November)) for every two years starting from 2005to 2017 have been acquired from USGS earth explorer site. Then, several waterindices namely NDWI, MNDWI1, MNDWI2, NDMI, WI2015,AWEIno−shadow wasused to extract the water and land feature from the images. OTSU method wasapplied on each index to determine water and non-water threshold by using IDLfunction from which a mean threshold value was generated to improve the accuracy ofwater and non-water. Amongst all those indices, NDWI performed most accuratelyto extract water and non-water surface for both case study areas in both pre andpost-monsoon period. The results indicate an intense increasing trend in land surface area inpre-monsoon period than that of post-monsoon period for Sutarkhali union, but withalmost no changes for Banishanta union in neither of these periods. Overall, thechange detection analysis showed that the land area in Baniashanta union increasedfrom 1995.48 ha to 2356.11 ha from 2005 (pre-monsoon) to 2017 (post-monsoon)and in Sutarkhali union it has been found from 1046.15 ha to 2832.12 ha frompre-monsoon 2005 to post-monsoon 2017. However, when two areas are comparedwith respect to two time period (e.g. 2005-10 and 2011-17), we found that during2005-2009 period, Sutarkhali union suffered from land erosion (940.95 ha) compared toaccretion (34.92 ha) while for Banishanta union amount of erosion (81.99 ha) is lowerthan that of accretion (395.19 ha) for the same time period. On the other hand,during 2011 to 2017, net amount of loss (42.75 ha) is higher than gain (30.96 ha) forBanishanta union. These findings lead us to conclude that in our case study areasnatural disasters like cyclones have a significant contribution to bring changes in landsurface area than that of seasonal monsoon. Further studies can be conducted toknow the implications of these changes on land use and land cover in coastal areas. [ABSTRACT FROM AUTHOR]

Projected global requirements for biomass feedstock and estimates of biomass production suggest that by the middle of this century there will be significant shortfalls in utilisable supply. Perennial rhizomatous grasses (PRGs) have physiological and morphological characteristics that mean they produce large amounts of biomass, which can be harvested on an annual basis for several years. Once established they require limited management from farmers, with the result that they have high energy output to input ratios. Life cycle assessments have shown that the use of PRGs for heat and power has the potential to be close to carbon neutral, and if used in conjunction with carbon capture and storage (CCS) in BECCS (bioenergy with carbon capture and storage) they can be can be carbon negative. These characteristics have led to the view that PRGs are the 'ideal' bioenergy crops. This being so, we ask why PRGs are yet to make a significant contribution to global bioenergy production. We review some of the constraints on scaling bioenergy production using PRGs, including impacts on biodiversity, effects of land use change and the potential for use of marginal land. We show that PRGs should have the greatest potential of all biomass resources to release these constraints. [ABSTRACT FROM AUTHOR]

The use of the Noah Land Surface Model (LSM) in regional modeling has increased during the last decades, while data assimilation is not so commonly used. Thus, this study focuses on the impact of both options on WRF simulations, and how they affect the summer surface temperature bias and energy balance over the Iberian Peninsula (IP). For that purpose, a numerical downscaling exercise over the IP was run nesting the WRF model inside ERA-Interim. Four different configurations of the model were run during 2010-2014 after a one-year spin-up (2009). In the first experiment (N), including the Noah LSM for the calculation of the soil temperature and moisture, the boundary conditions drive the model after the initialization. The second experiment (D) includes also the LSM, but the 3DVAR data assimilation step is run every six hours (00Z, 06Z, 12Z and 18Z). The third and fourth experiments (S and C respectively) present the same configurations as the previous experiments, but without the Noah LSM. The domain covers the IP with a 15x15 km2 grid and 51 vertical levels. The sea surface temperature is updated daily and observations from the PREPBUFR dataset (NCEP ADP Global Upper Air and Surface Weather Observations) are assimilated inside a 120-minute window centered at the analysis times in the 3DVAR assimilated runs (C and D). Results show that the experiment including the data assimilation and the Noah LSM (D) produces the best correlations and the smallest RMSE. Both experiments including the Noah LSM (D and N) showed similar biases, but the RMSE obtained by N is not as good as that from D. A larger bias is obtained by the C experiment (with data assimilation but without the LSM), but not as remarkable as that from the experiment without both options (S). However, the correlations obtained by C are comparable to those from D. According to these results, the effect of the Noah LSM in temperature is similar to that derived from the data assimilation scheme for temperature bias. Conversely, for day-to-day variations (correlation coefficient), data assimilation performs much better. Thus, in terms of mean square error, the combination of land surface model and data assimilation yields the optimum combination. The spatial distribution of the Bowen ratio was also calculated for each experiment. Those experiments including the Noah LSM are the ones obtaining the most similar results to those obtained by previous studies, particularly the N experiment. The mean Bowen Ratio value for the experiments without the Noah LSM is around 0.5, while for D is 1.48 and for N 3.78. If we focus on the energy balance, the experiments including Noah LSM are those able to better close the balance (residual below 25 W/m2 – mean value for the entire IP). The residual of the experiments without Noah LSM can reach values of 200 W/m2 because the estimation of Ground Flux is severely affected by the use of a diffusive soil scheme. [ABSTRACT FROM AUTHOR]

Land use affects sediment yield in the headwaters of the Sondu River basin in Kenya’s largestremaining tropical montane forest, the Mau Forest Complex. Streams containing sedimentsoriginating from eroding cultivated land or unpaved roads can lead to on- and off-site effectsthat have economic and social impacts. The Sondu River drains into Lake Victoria, thesecond largest fresh water lake in the world, which is an important water resource for fivecountries and the source of the River Nile. East African streams are often characterized by high concentrations of suspendedsediment, however, the availability of sediment yield data is severely limited. Within Kenya,there are only a few studies. Here, we report on a unique, four-year, high temporal resolutionturbidity monitoring suspended sediment dynamics data set (10.2014 – 12.2018) which weuse to assess temporal and spatial variability within three catchments (27 – 35 km2) underdistinct land uses (natural forest, smallholder agriculture and tea/ tree plantations). Asa surrogate for total suspended sediments, turbidity was calibrated by using anex-situ suspended sediment increment suspension method. The outlet of the naturalforest catchment had the lowest suspended sediment concentrations (33.75 ± 87.15mg L−1) followed by the tea/ tree plantation (49.32 ± 97.59 mg L−1) and highestconcentrations were observed at the outlet of the smallholder agricultural catchment(122.92 ± 184.43 mg L−1). Annual rainfall varied from 1677, 1580 and 1445 mm yr−1among the three catchments of the natural forest, tea/ tree plantations and smallholderagriculture, respectively. Catchment runoff coefficients (annual runoff/ annual rainfall)ranged from 0.3 for the natural forest and 0.4 for both agricultural catchments.Sediment catchment yields showed seasonal variations in all three catchments withhighest seasonal yields (3.52 – 142.05 t km−2 mth−1) during the long rains (Apr –Jul) and lowest yields (0.01 – 1.78 t km−2 mth−1) during the start of the longrains (Mar), closely followed by discharge and rainfall patterns during the four yearobservation period. The high-resolution data set showed that the catchment undersmallholder agriculture had the highest sediment yields when compared to the catchmentsunder tea/ tree plantation and natural forest (96.1, 39.0 and 17.9 t km−2 yr−1,respectively). The study indicated the importance of keeping natural forest ecosystems andmanaging agricultural systems to protect water resources from sediment pollution. [ABSTRACT FROM AUTHOR]

Nitrate transport into streams is closely controlled by hydrological processes and catchment characteristics. Storm events usually lead to high variability of nitrate-N concentration. Hysteresis patterns during storm events can be used to disentangle factors controlling stream nitrate-N concentrations and they reveal insight into the nitrate-N concentration in the flow pathways activated during storm events. In this study, six year (2012-2017) of high frequency (15 min) discharge and nitrate-N concentration at three gauging stations in the 456 km² Selke catchment (Germany) were used to investigate hysteresis during storm events. The three gauging stations: Silberhütte, Meisdorf and Hausneindorf are located in the upper (mixed land use), middle (forest) and lower parts (arable) of the Selke catchment, respectively, representing different combinations of the dominant land use and soil type classes. Both spatial and temporal variations of nitrate-N concentration in the catchment were analyzed. First, the event detection resulted in 88, 76 and 75 events for the three stations Silberhütte, Meisdorf and Hausneindorf, respectively. Second, the hysteresis loops were classified into clockwise and anticlockwise patterns, indicating different nitrate transport mechanisms (e.g., accretion or dilution from different flow paths). Results showed different numbers of clockwise and anticlockwise hysteresis patterns among the three stations. For instance, the Hausneindorf gauging station was characterized by larger number of anticlockwise hysteresis loops compared to the other stations. This can be explained by the large share of arable land and urban area land use classes in the downstream part of the Selke, compared to the upstream part where forest is dominating. This confirmed the land use effect on hysteresis loops. Also, among the three stations, boxplot results showed significant differences in the distribution of nitrate concentration but not of discharge. This reflected the nested nature of the catchment, where the high precipitation occurred in the upper part of the Selke resulting in high correlation between the discharges of the three gauging stations. Considering all stations together, the anticlockwise hysteresis patterns appeared more pronounced during summer and autumn, when discharge was relatively small, than during spring and winter. The study findings support the necessity of a long-term high-frequency monitoring program at controlling positions, which helps to gain further insights in nutrient transport processes and further guiding efficient agricultural management options. [ABSTRACT FROM AUTHOR]

Nutrient catchment models are increasing considered as important decision-making tools in exploring the biogeochemical processes and testing the effect of future land use and climate changes effects. However, the development of a comprehensive decision tool requires an adequate evaluation of the model capability to predict the different physiographical characteristic of the studied catchment. For this purpose, the semi-distributed hydrological water quality model HYPE (Hydrological Predictions for the Environment) was tested to represent the measured Nitrate-N (NO3-N) and Total Phosphorus (TP) concentrations and loads at different spatially-distributed internal gauging stations that were not included in the calibration process. The nested meso-scale Selke catchment (463 km2, central Germany) was used for this study. First, discharge, NO3-N and TP concentrations were simulated at three gauging stations for a 20 year period in the main stem of the stream; Silberhuette, Meisdorf and Hausneindorf, representing the three key geographical features of the Selke catchment from upstream to downstream parts. Second, 13 internal stations, covering different stream order, soil type and land use classes were utilised for testing the spatiotemporal performance of the model. In this study, multi-site and multi-objective calibration approach and an uncertainty analysis were conducted using the DREAM (DiffeRential Evolution Adaptive Metropolis) algorithm. Results showed that the model could represent reasonably well the discharge for both calibration (1994-1998) and validation (1999-2014) periods at three main gauging stations, with lowest Nash-Sutcliffe efficiency (NSE) of 0.75 and percentage bias (PBIAS) of water balance of less than 18%. Results indicated less performance during the validation period, due to the reduction of number of precipitation stations compared to the calibration period. The dynamics of NO3-N and TP loads were well represented by the model in the three main gauging stations during the whole simulation period (1994-2014) with the lowest NSE and PBIAS of 0.71 and 9%, respectively. Results, also, showed that the HYPE model simulations agreed well with the measured NO3-N and TP loads for the whole simulation period in the 13 internal gauging stations. The model could mimic better the nutrient concentrations in the diffuse source-dominated sub-catchments compared to the point-source dominated sub-catchments. Results suggested that combination of multi-site and multi-objective calibration using key archetypes gauging stations can ensure sound spatiotemporal identification of the semi-distributed model parameters. [ABSTRACT FROM AUTHOR]

Introduction. Ecological stoichiometry has allowed important insights into the coupled/decoupled cycling of C, N and P in terrestrial environments, at scales from local, regional, to continental and global ones. Important findings from these studies and meta-analyses were on differences in the homeostatic behavior of heterotrophs and autotrophs, on climatic/latitudinal effects on plant stoichiometry linked to large-scale changes in nutrient availability, and more recently on microbial elemental imbalances and their effect on microbial element use efficiencies and soil biogeochemical processes.Study design. In this study we investigated the C:N:P stoichiometry of different ecosystem compartments (leaf litter, roots, soils, soil microbial biomass, soil extractable pool) across 95 sites differing in climate, bedrock and management, ranging from South Spain to Northern Sweden. Stoichiometric patterns were then linked to microbial community composition and function. Sampling was performed in Mai-August 2017, from 43 forest, 28 grassland and 24 cropland sites. Sites ranged in mean annual temperature from -3.4 to 17.8 °C and in mean annual precipitation from 415 to 1396 mm. Soils covered a pH (H2O) range from 3.6 to 8.9. We used this dataset to test for large scale effects of land use, climate and bedrock on continental C:N:P stoichiometry and microbial community composition and function. Results. (1) C:N and N:P ratios in plant litter, roots, bulk soil and microbial biomass showed clear land use (croplandmineral horizons). (2) Bedrock effects were weaker than land use effects, but influenced soil extractable and microbial biomass C:N and N:P, and had little effect on plant root and litter stoichiometry, indicating relatively little geochemical effects on plant C:N:P ratios. (3) Climate explained relatively little of the overall variation in C:N:P stoichiometry across this transect, with the exception of MAT (inverse to latitude), being negatively related to soil C:N. (4) We found strict C:N and N:P homeostasis of soil microbial communities, but weak homeostasis of plant roots relative to soils (R2=0.12-0.46), the response being uniform across land uses. (5) Microbial community structure (bacteria: fungi or Gram+/Gram- ratios based on PLFA analyses) was neither related to land use and climate, nor to their biomass stoichiometry, or to their elemental imbalances or element use efficiencies, but microbial groups such as Gram+ and Gram- bacteria decreased with MAT. (6) Microbial C:N imbalances increased from agricultural land to forests, triggering microbial nitrogen use efficiency (NUE) to increase, according to stoichiometric reasoning, but at the same time also microbial carbon use efficiency (CUE) increased, hinting at co-regulation of microbial CUE and NUE in terrestrial ecosystems. (7) Linked to decreases in microbial element use efficiencies due to agricultural land use, microbial respiration and gross N mineralization increased along the same line.Conclusion: This study highlights major strengths and weaknesses of ecological stoichiometric patterns when applied to terrestrial ecosystems at the continental scale and when discerning land use and climate effects on microbial community composition and function, but allows identifying causal pathways linking biogeochemical processes. [ABSTRACT FROM AUTHOR]

Charcoal making is one of the oldest forms of forest exploitation, civilizations being used to convert wood into charcoal for energetic and metallurgic purposes for thousands of years. For this purpose, firewood domes were built in the forests in appositely shaped emplacements, then left to burn for days under controlled semi-anoxic conditions. The legacy of such an activity is still recognisable in the involved soils: in fact, these show a black, thick, charcoal-rich top layer, which often overlies a complex sequence of pedogenic horizons that altogether reveals successive land uses and/or climatic phases. In Europe, where charcoal production was particularly widespread, there is a plethora of abandoned charcoal hearths. A comprehensive survey of these sites is far for being accomplished, but most likely they are millions.This presentation aims at underlining the gaps present in the current version of the World Reference Base for Soil Resources (WRB) concerning the classification of charcoal hearth soils. Charcoal hearth soils are full Anthropogenic soils, i.e. soils markedly affected by human activities, being their formation chiefly driven by repeated activities related to platform preparation and charcoal production. As such, they should fall within one of the two Reference Soil Groups (RSGs) including soils 'with strong human influence': 'Anthrosols' and 'Technosols'. Nonetheless, both these RSGs are defined by requests that are too stringent for most charcoal hearth soils. In fact, 'Anthrosols' are soils with long and intensive agricultural use or, however, a 'pretic' horizon at least 50 cm thick, which is a diagnostic horizon dark, rich in organic matter and phosphorous, high contents of exchangeable Ca plus Mg, with at least 1% artefacts or manufactured charcoal. Here the point is that the top black horizon of the majority of charcoal hearth soils is less than 50 cm. Much harder for charcoal hearth soils is being 'Technosols', because as well as other characteristics they must have more than 20% by volume, weighted average, of manufactured charcoal in the upper 100 cm from the soil surface, which according to our experience and data in the literature rarely happens. Next edition of the WRB should lower the demands in terms of thickness of the top horizon rich in charcoal or its charcoal content to accommodate charcoal hearth soils in one or the other RSG with strong human influence. [ABSTRACT FROM AUTHOR]

The planetary boundaries framework identifies thresholds that, if exceeded, may push the Earth out of its present Holocene-like conditions. In other words, the planetary boundaries define the 'safe operating space' for modern society. While the planetary boundaries are a useful way of identify critical thresholds within and interconnections between Earth systems, one criticism is that the planetary boundaries do not provide meaningful guidance at subglobal scales (e.g. basin to national) where natural resources are managed. Here, we explore how the planetary boundary framework can define a safe operating space and inform water management and policy at local to regional scales. Specifically, we identify three pathways by which the freshwater planetary boundary can be used to inform local water management: (i) externalizing local impacts by quantifying the local contributions to the global threshold; (ii) internalizing global change by determining the impacts of global planetary boundary exceedance on local resources; and (iii) revealing local water thresholds by applying the planetary boundary framework at a smaller spatial scale to define the local to regional safe operating space. Translating the global planetary boundaries to local thresholds requires integration with existing frameworks for assessing global human impacts on ecosystems including virtual water trade, indirect land use change, and partitioning global contributions to climate change; and also considering local social boundaries that define acceptable levels of change based on local conditions. Thus, we do not intend to suggest that the planetary boundaries replace existing water management paradigms such as the EU Water Framework Directive. Rather, we show that operationalizing the planetary boundaries for local water management can provide a complementary approach guided by a cross-scale understanding of water which can provide unique scientific and management insights. [ABSTRACT FROM AUTHOR]

Climate information appears to be underutilized in water management in agriculture. A systematic and integrated assessment of efficient adaptation measures may inform decision making of farmers, policy-makers and water management authorities and may facilitate the uptake and use of climate information. Therefore, we aim at modeling interactions between hydrological processes, the groundwater status, land use and management choices considering stochastic climate scenarios on wetter and drier conditions. We have developed a spatially explicit integrated modeling framework consisting of climate scenarios, a crop rotation model, the bio-physical process model EPIC (Environmental Policy Integrated Climate), and a non-linear version of the bottom-up economic land and water use optimization model BiomAT. EPIC is used to simulate annual yields and irrigation water use on cropland, intensive and extensive grassland, and vineyards for a future period of 31 years. These land use categories are simulated with various adaptation measures including crop rotations, fertilization intensities, mowing frequencies, and irrigation intensities. EPIC simulates – inter alia – the hydrological processes at field scale as well as the CO2 fertilization effect. In BiomAT, the water balance is represented in a dynamic and spatially explicit way using monthly outputs from EPIC on percolation and irrigation by land use and management options. This allows us to assess efficient land and water use choices for adaptation considering alternative water use restrictions. The integrated modeling framework is applied to the semi-arid case study region Seewinkel in eastern Austria. Model results for the case study region show that higher net-benefits can be achieved through an expansion of vineyards, and high irrigation water and fertilizer inputs if mean annual precipitation sums increase in the next decades, or groundwater extraction beyond recharge is allowed. Large economic losses are modeled in drier climate scenario conditions, or if groundwater extraction is limited due to regulations. The model results clearly show, if water use is restricted, high flexibility in land use is required to efficiently adapt to climate change, and vice versa. The stochasticity of results emphasize the relevance of accurate and timely climate information for decision-making and thus efficient agricultural adaptation. Including a water balance in the land use optimization model highlights the importance of considering land and water interactions for agricultural adaptation in a semi-arid region. [ABSTRACT FROM AUTHOR]

Globally, delta areas are under increasing pressure from urbanization and climate change. Questions arise whether societies should preserve existing land and water uses by protecting them against the impacts of such changes, or whether one can anticipate on the impacts by adapting future land and water uses. The latter is at the heart of strategic delta planning which is a relatively new planning phenomenon applied in delta's worldwide. It is also gaining increased scientific interest. We offer a reflection on, and positioning of strategic delta planning as an emerging theme for interdisciplinary research. We draw on five years of research in Bangladesh, the Netherlands and Vietnam, an expert and stakeholder discussion during an international research workshop (November 2018), and eleven manuscripts for a special issue on strategic delta planning with additional contributions from California, Italy and Indonesia. We define strategic delta planning as a public sector led process through which a long-term vision (the strategic delta plan), as well as the actions and means for its implementation, are presented that shape and frame what a sustainable delta is and may become. Our analysis and reflection results in key features that define the current state of research on strategic delta planning:1. A strategic delta plan provides a vision, a strategy. While it seeks to develop a transparent framework for decision-making – which supports the strategic choices in society with expert knowledge, it also includes a clear political dimension, and serves political objectives. 2. Deltas are used as the physical anchoring point, focusing on the interactions between land, water and ecology, and their implications for societal goals and values.3. Uncertainty about future trends and developments is an important feature, resulting from a long-term planning horizon, to which strategic delta planning takes an open and adaptive approach, rather than a control-oriented approach.4. Strategic delta planning is an essential part of a nested planning system. It provides a top-down vision, which offers the space for bottom-up iterations and specifications.Currently underrepresented in the thinking about strategic delta planning and its supporting methods and approaches, is the role of people, at the individual level, and their importance for the course of shaping and implementing delta planning trajectories. The rapid spread of delta plans (e.g. Bangladesh, California, Indonesia, the Netherlands, and Vietnam) shows the keen interests of governments. With our contribution, we intend to broaden the scientific debate on strategic delta planning, and stimulate linkages with other disciplines including socio-hydrology and water resources management. The challenging implementation of strategic delta plans offers an highly interesting and societal relevant field for further research, meanwhile offering an entry point to critically reflect upon top-down and bottom-up planning approaches for human-water systems in delta areas. Lessons learned from the various delta examples provide interesting insights, tools and approaches for governments and delta practitioners. [ABSTRACT FROM AUTHOR]

Human society increasingly depends on information derived from Earth Observation data. In particular, there is an growing demand for information facilitating agriculture, forestry, and hydrology. To this purpose the number of space-borne satellites and small cube-sat constellations are projected to increase dramatically over the next years. This increase provides enormous challenges in terms of retrieving actual information from this big data. The current general trend is to create individual land surface products for each satellite mission. This approach originates from the fact that satellites are usually has singular research-mission, that require only a specific number of land surface products to be created. As such, the majority of available products are created using a bespoke single-sensor approaches. This production-heterogeneity severely limits the advancement of research fields due to inconsistencies in the combinations of such land surface variable. Land surface parameter retrieval suffers from illposedness: the fact that there are fewer observables than the amount of desired parameters (required for accurate retrieval). By only considering observations from singular satellites, this illposedness is worsened especially considering that varying spectral-sensitivities of different land surface parameters. A multi-sensor approach capable of integrating such sensitivities, by accurately modelling the physical radiative processes, resolves these limitations. Furthermore, such a multi-sensor approach also allows to benefit from synergies of using multi-scale/heterogeneous observation types/varying temporal frequencies of different sensors. In this view, within the MULTIscale SENTINEL land surface information retrieval PLatform (MULTIPLY) project, the main objective was to create a framework to integrate observations from different sensors in order to obtain the best possible estimate of the land surface state, taking into account the different characteristics of different sensors and data streams. The MULTIPLY framework is developed from the original idea's implemented in the EOLDAS system but with emphasis on operationally, enhanced consistency (across sensor types) and improved gap-filling. Specifically: MULTIPLY aims to 1) Combine data from SAR and Optical remote sensing data using compatible radiative transfer models2) Design a data assimilation platform incorporating as many information sources (observational, multi-temporal) to optimally retrieve satellite gap-free information. 3) Deliver a set of internally consistent data products at different resolutions with quantified uncertainties. 4) Explore potential applications that demand consistent land products, such as agriculture and forestry.At present, the prototype of the MULTIPLY has been implemented as a cloud-service and is currently undergoing expert-user-evaluations. During the presentation we present the operational MULTIPLY framework (http://www.multiply-h2020.eu/), the detailed methodology, as well as the results of our evaluation activities. In the presentation, specific emphasis will be put on the consistent coupling of Sentinel-1 (SAR) observations together with Sentinel 1&3 (optical) observations (together with auxiliary ecological information) in order to jointly and consistently retrieve soil parameters as well as vegetation traits and b) elaborate on the results of the fieldwork validation efforts. [ABSTRACT FROM AUTHOR]

Climate change and human interventions are modifying freshwater-related ecosystem services on both supply and demand side. A better understanding of the dynamic of these services, driven by the interactions among above-mentioned factors, could bring benefits to water resources management and society. In this work, we develop an integrated modeling approach, driving the Integrated Valuation of Ecosystem Services and Tradeoffs model (InVEST) with future projections of climate and land use data until 2050. Scenarios are developed by Euro-Mediterranean Center on Climate Change (CMCC) considering the more pessimistic, business as usual, RCP8.5. The core outcomes are set of maps and indicators to quantify the alterations in water availability and in quality such as annual average water yield and nutrient retention. This approach is tested in the case study of the Taro River basin (Emilia Romagna Region), within the activities of INTERREG-CE PROLINE project (https://bit.ly/2JGH1Gm). Preliminary results demonstrate that different ecosystem services respond differently to climate and land use change, i.e. reductions up to 32% for water yield service expected driven by increases in evapotranspiration demand and changes in rainfall patterns; and mean increases of about 4% for nutrient retention service. Moreover, the rate of change results different over time with maximum changes between 2020-2030 and slower changes afterwards. Finally, the responses are sensitive to the distribution of land use, i.e. more changes are found in the urban and agricultural areas while the woodland and meadowland areas are more stable. Ultimately, these results could be used to identify and prioritize the best management practices, balancing the tradeoffs among services and improving the resilience and biodiversity of the freshwater ecosystem at river basin level. [ABSTRACT FROM AUTHOR]

Land use change and climate change are the main drivers affecting hydrological regime in Anning river basin, a tributary with the largest sand generation in the upper Yangtze River. However, their contribution to the variation of flow in the subbasin keeps unclear. Firstly, the gauged precipitation, streamflow and sand data were used to analyze their trends of variation since 1980s and land use and land cover change in four representative years were studied. Then semi-distributed hydrological model MIKESHE was used to simulate the ecological and hydrological status of several scenarios reflecting the different changes of climate and land use. The results showed that the runoff of Anning River increased and the its variation decreased, which was consistent to the loss of forest cover. The comparison among scenarios showed that both climate change and land cover change contributed to the variation of flow. The land cover change exerted more influence on the variation during 1990s, which might be the main reason why the Anning River became the one that had the largest sand generation in that time. As hydrological impacts of land use change and climate change may be temporally varied, it is requisite to manage water resources adaptively to address future climate change and water resources shortage. [ABSTRACT FROM AUTHOR]

Historically, daily measurements of phosphorus (P) concentrations have been conducted in eight different Danish streams covering a range of hydrological regimes and catchment properties. Daily phosphorus concentration data exists from six smaller streams draining agricultural catchments and from two larger rivers both being impacted from diffuse and point sources. One of these rivers – the River Odense have a 20 years long time-series including for most of the period data for two P –forms - total P and dissolved inorganic P. Gauging stations were established in all the streams given access to calculated daily data for mean daily discharge from stage/discharge relationships. Data from all streams are analysed statistically for establishing relationships between P-concentrations and discharge – especially looking for seasonal changes in these relationships that might show either mobilization or retention processes for P. Moreover, a Monte-Carlo assessment of the importance of discrete sampling for P load estimation is conducted for all individual streams and the outcome linked to catchment properties such as size, point sources, land use, etc.+ [ABSTRACT FROM AUTHOR]

In southwest Bangladesh, the groundwater has a high spatial variation in salinity. Some of this variation has been explained in small scale study areas, but no mechanisms controlling the regional groundwater salinity have been described. In this study, we aim to provide guidelines for the groundwater salinity, by assessing to what extent the groundwater salinity is controlled by present-day surface features or by palaeo connate water. Groundwater salinity variation was assessed using a low-cost method, that consisted of measuring Electrical Conductivity (EC) of the groundwater at 1998 locations, complemented by 442 EC measurements from previous studies. Using 321 hydrochemical samples, an interpretation was made of the extent to which the EC values could be used as indicators for salinity. The EC database was statistically and geostatistically analysed using location data (latitude, longitude and depth of the filter) and geographical characteristics at the surface (land use, elevation, soil type and surface clay thickness). The results show that groundwater in the northwest and northeast is fresh, while it is saline in the south. In-between these extremes, a large variety in salinity is observed. EC correlates significantly with surface elevation, albeit with a low r-value, and there are significant differences in EC between groundwater under different soil and land use types, with groundwater under fluvial soils being much fresher than elsewhere. Based on the correlations, guidelines are proposed that can be used as a first estimate of the groundwater salinity throughout southwestern Bangladesh. [ABSTRACT FROM AUTHOR]

Due to increasing ecological problems resulting from high loads of fine sediments and nutrients in rivers and brooks in Central Europe the Bavarian fisheries association is funding a study focusing on changes in land use and their implications for the fine sediment and nutrient situation in riverine ecosystems. Further interests are the impacts on inland fisheries and aquaculture in fish ponds.The results of the first module indicate significant shifts in the agricultural structure due to rural planning measures and funding programs in the 1960s and 1970s. The parcel structure has changed fundamentally, as have the spatial distribution and the amount of ecologically and hydrologically relevant structures like hedges or small wetlands.A further shift, especially in the preferred crops and the intensity of land use came with the biogas boom in the last twenty years.These changes in the land use were analysed by digitalising aerial photos from different time steps. Associated hydrological impacts – like entry paths or combined interception of water, fine sediments and nutrients in the landscape – were investigated using various GIS-tools and statistical analyses.The final aim of the study is the development of a catalogue of suitable and highly effective mitigation advices for agriculture and forestry management in order to improve the situation and avoid critical conditions. Such conditions occur especially under the threat of an accelerating climate change, coming along with more likely heavy precipitation events and summer low flow phases in rivers in parts of Central Europe. [ABSTRACT FROM AUTHOR]

Natural forest succession is a process of encroach shrubs and trees on non-forest areas caused by socio-economic changes, especially after the Second World War. This process is observed in Europe often in case infrequently used pasture land, or land with a steep slope, poor soils or other difficult to access areas. In recent decades, the areas of valuable and high biodiversity semi-natural meadows in Polish Carpathians were decrease significantly. Researches of abandoned land use in mountains areas are rare and mainly focused on herbaceous vegetation. However, there is still a lack of interdisciplinary approach to the land use changes. These changes could affect soil properties especially, a microbial activity which is used as an indicator of the soil environment condition. The purpose of this study was to investigate the diversity of microbial properties in the different land covered soils from meadow via succession to forest. The study area was located in Bieszczady National Park in south-eastern Poland. The samples were taken from two layers (0-10 cm and 10-20 cm) in the four transects each consisted of a meadow, a succession (covered by 30-60 years trees) and forest (more than 150 years old trees). To determine the microbial properties biomass carbon content and selected enzyme activity were measured. Additionally, selected chemical and physical soil properties were tested (pH, total organic carbon and total nitrogen content, sorption properties). The investigated soils were strongly acid, pHKCl ranged from 3.0 to 4.0. Microbial activity of investigated soils was varied by examine layer deepness and land use type. In uppermost layer (0-10 cm) microbial biomass carbon content (MBC) was significantly higher than in 10-20 cm layer. The 0-10 cm soil layer of meadows characterised the highest dehydrogenase activity (DHA), and invertase activity (AI) compared to successions and forests, 53.2 µgTPF·g-1soil·h-1 and 44.3 mgC6H12O6·kg·h-1, respectively. MBC was positively correlated with DHA, total organic carbon, total nitrogen content and the sum of exchangeable basics. DHA was positively correlated with pH, the sum of exchangeable basics and negatively with exchangeable acidity. Moreover, AI was positively correlated with total nitrogen content.The diversity of microbial activity in the soils of Bieszczady National Park, along forest succession process is noticeable. Microbial properties, such as enzymes activity and microbial biomass carbon content are responding indicators of this changes.This research was financed by the Ministry of Science and Higher Education of the Republic of Poland, No. BM – 2125/18. [ABSTRACT FROM AUTHOR]

Changes in land use and land cover represent an important indicator in evaluating the dynamic of landscape (Feranec et al., 2002). Land use change is the result of the interaction of the natural environment and human society and it is also an important manifestation of the ecological environment changes of the earth's surface (Zhou et al., 2011; Liu et al., 2012). The geographical position in Central Europe and its socio-economic and institutional transformations after the fall of socialism in 1989, determines the study area to represent an experimental territory for land use scientists. In the framework of sustainable development, the analysis of landscape dynamic in response to land use and cover changes represent an adequate tool to identify a balance between natural, social and economic dimensions of landscapes in a given territory. The present study aims to analyze the spatial and temporal dynamic of landscape pattern in response to land use and land cover changes in the Suceava river basin, Romania, between 1990 and 2012, by the application of a diachronic analysis of freely available CORINE Land Cover data and GIS techniques. In order to analyze landscape pattern in the studied area, we examined land cover changes and transformations processes (flows) during three different periods with distinctive socio-economic, political, technological and cultural characteristics, that were delimited by several particularities: (1) 1990-2000 (transition period to the market economy); (2) 2000-2006 (pre-accession period to the European Union) and (3) 2006-2012 (post-accession period to the European Union). Results showed the surface that suffered no changes in the entire period (1990-2012) was 1657.13 km2, representing 72.65%, while the changed areas represented 623.99 km2 (27.35%). The period 2000-2006 was the most dynamic regarding land use and cover changes summing 418.36 km2 (67.05% from the entire period and 18.34% from the total study area). The dynamics of land use and cover changes over the three time horizons showed that class represented by heterogeneous agricultural areas was the most dynamic one with 199.25 km2 (31.93%), followed by urban fabric class with 114.03 km2 (18.27%) and arable land with 76.95 km2 (12.31%). Our research on the processes of landscapes transformation showed that the intensification of agriculture have the highest proportion between 1990 and 2012 (157.47 km2, representing 25.24%). As change weight over the three periods, the most active period of intensification of agriculture was 2000-2006 (125.60 km2, representing 30.02%), as a consequence of adoption and implementation of the Common Agricultural Policies. Secondly, the deforestation had also a high degree (20.47% of total changes between 1990 and 2000), as a consequence of illegal logging by implementing of the Land Reform (Act no. 18/1991), which has ruled a restructuring process and basic mutations in the ownership of land, resulting a high degree of privatization of land, especially. We hope that the present approach will improve the sustainable management of the Suceava river basin, taking into account a future rational use of natural resources adapted to societal needs in a constantly changing world. [ABSTRACT FROM AUTHOR]

The aim of the present study was to investigate changes in soil CO2 and N2O productionunder different land uses and biochar amendments during vegetation period. The differentland uses were characterized with varying anthropogenic activities. Two consecutive years ofCO2 and N2O production was measured on a weekly to bi-weekly basis during vegetationperiod (between March and October) for vineyard, maize, grassland, and forest soils. Gassamples were collected in 12mL (CO2) or 24mL (N2O) evacuated vials after 20 (CO2) or 30minutes (N2O) incubation period using static chamber method. Gas samples were analyzedby GC-FID (CO2) or GC-ECD (N2O). All land use received biochar amendment, which wascompared to control soils’ CO2 and N2O emission values to examine its greenhousegas reducing potentials. The vineyard samples included no ploughing or ploughedsoils with or without organic fertilizer or biochar addition. CO2 fluxes increased inthe second year in the vineyard samples in all treatments but the absolute control(no ploughing, no fertilizer addition, and no biochar amendment) and the control(ploughing with no fertilizer and no biochar addition). During the two year study thehighest CO2 production was observed in the case of the ploughed, not fertilized, andbiochar amended soils. During the second year of the study we found 8% higherCO2 emission in the biochar amended treatment compared to control treatment inthe case of maize, and 5.9% higher in the case of forest. In grassland the biocharamendment reduced overall CO2 emission by 6.3N2O production in the vineyard showedsimilar or even lower emission values with biochar amendment; however, duringthe second field year and consequently over the overall two year period, the N2Ofluxes increased in biochar added sites compared to the control treatment. Similarfindings were observed in the maize field. During the first year biochar amendmentresulted in a decrease, while during the second year we observed an increase inoverall N2O fluxes. In the forest and grassland sites, both first and second year of theexperiment biochar amendment decreased the N2O fluxes. Overall, biochar amendmentresulted in increased N2O production in the case of vineyard and maize samples,while reduced emission values were observed in the case of forest and grasslandsamples. [ABSTRACT FROM AUTHOR]

From an environmental standpoint, a hydrological catchment's health is in inverse proportion with its urbanization stage. As mentioned through different studies, urbanization has generally led to higher peak discharge, higher flood volumes flowing during reduced response time, but also to a poorer water quality. To predict (resp. assess) the impact of a future (resp. previous) urbanization of a catchment, one must diagnose the urban state of the catchment. To this end, the Effective Impervious Area (EIA) or Directly Connected Impervious Area (DCIA) measures were conceived as alternative urban metrics to what hydrologists define as the runoff-rainfall ratio (yield) of the catchment. At the catchment scale, it seems to be a very useful measure, since there may be a spatial combination of pervious and impervious areas that can lead to impact mitigation. Yet, it is still difficult to quantify the EIA of a catchment. An "easy" way consists in using empirical relationships to derive EIA from Total Imperviousness Area (TIA), where TIA is estimated from land cover databases. More rigorous approaches require more datasets, such as hydrologic time series and urban databanks, which are not generally available. Using a large sample of 365 French and American urbanized catchments, for which rainfall and runoff hourly time series were prepared, we propose a pragmatic approach to estimate the EIA using land cover databases, hydrographic network and population density. This approach is validated in an event-based framework, by comparing the resulting EIA values with the slope of runoff-rainfall linearly derived relationships for each catchment. [ABSTRACT FROM AUTHOR]

Soils are recognised as key resource for human well-being. There is an ongoing debate about the influence of land use (LU) and land use change (LUC) on soil properties. Especially for sustainable LU it is important to implement soil-adopted management systems to avoid soil degradation and, therefore, a decrease in soil quality. LUC is mostly initiated by socio-economic as well as political factors such as export oriented farming or urban development, which may threat soil resources. LU classification is a common method to identify different types of ground cover, where the application of machine learning (ML) based supervised-classification techniques has growing significance. In the past decades, the availability of remote sensing data, as well as the fast progress in computer architectures and cloud computing is constantly increasing and allows fast and parallel processing of large data sets. Existing land cover maps (e.g. CORINE and SIOSE) typically have an appropriate spatial resolution, but the temporal resolution is limited. This is of great concern in Mediterranean countries where LU is very heterogenous and dynamic over time. The objective of this study was to identify annual land use change over the past 30 years in the middle Guadalquivir basin, Andalusia, Spain, by applying random forests (RF) and support vector machines (SVM) on the Google Earth Engine (GEE) cloud computing platform. Furthermore, we evaluated how GEE can be utilized for big data processing for land use change detection with high temporal resolution. We used remote sensing data from the Surface Reflectance Tier 1 archives of Landsat 5 ETM and Landsat 8 OLI from 1984 to 2018. The Surface Reflectance Tier 1 products are atmospherically and geometrically corrected. Following the CORINE land cover classification scheme, we used four classes which cover the main types of agricultural LU in the study area. These were arable land, permanent crops (plantations), pastures/grassland and forests. The non-agricultural classes artificial surfaces and water bodies were excluded. For the calibration of the classification models we sampled 130 ground truth points in October 2018. We generated land use maps for the years 1984 to 2018 with the classification methods RF and SVM. For the change detection post-classification comparison was used. Preliminary results show a very high temporal resolution and high data quality for LUC in the middle Guadalquivir basin. The overall area of plantations increased compared to the area of arable land. Furthermore, the percentage of forest also increased, while the share of pastures decreased. We concluded that using GEE is an appropriate tool for big data in high temporal resolution as it provides different classification techniques and fast processing as well as direct access to the Landsat and CORINE archives. The LUC maps can be used to characterise the temporal dynamic on pixel level. Further studies will focus on the implementation of LUC as environmental covariate in soil property mapping in the study area. [ABSTRACT FROM AUTHOR]