Chemical and isotopic interpretation of major ion compositions from precipitation: a one-year temporal monitoring study in Wrocław,SW Poland

The chemical compositions (Na⁺, NH₄ ⁺, K⁺, Mg²⁺, Ca²⁺, Cl^?, NO₂ ^?, NO₃ ^?, SO₄ ^2?, HCO₃ ^?) of wet precipitation and nitrogen isotope compositions δ¹⁵N(NH₄ ⁺) were studied from January to December 2010 in Wroc?aw (SW Poland). Results of a principle component analysis show that 82 % of the data variability can be explained by three main factors: 1) F1 (40 %) observed during vegetative season (electrical conductivity, HCO₃ ^?, NO₃ ^?, NO₂ ^?, NH₄ ⁺ and SO₄ ^2?), mainly controlling rainwater mineralization; 2) F2 (26 %) observed during vegetative and heating seasons (K⁺, Ca²⁺ and Mg²⁺), probably representing a combination of two processes: anthropogenic dusts and fertilizers application in agricultural fields, and 3) F3 (16 %) reported mainly during heating season (Na⁺ and Cl^?) probably indicating the influence of marine aerosols. Variations of δ¹⁵N(NH₄ ⁺) from ?11.5 to 18.5?‰ identify three main pathways for the formation of NH₄ ⁺: 1) equilibrium fractionation between NH₃ and NH₄ ⁺; 2) kinetic exchange between NH₃ and NH₄ ⁺; 3) NH₄ ⁺ exchange between atmospheric salts particles and precipitation. The coupled chemical/statistical analysis and δ¹⁵N(NH₄ ⁺) approach shows that while fossil fuels burning is the main source of NH₄ ⁺ in precipitation during the heating season, during the vegetative season NH₄ ⁺ originates from local sewage irrigation fields in Osobowice or agricultural fertilizers.     

Retrieving air humidity,global solar radiation,and reference evapotranspiration from daily temperatures: development and validation of new methods for Mexico. Part I: humidity

The occurrence of flood and drought frequency is highly correlated with the temporal fluctuations of streamflow series; understanding of these fluctuations is essential for the improved modeling and statistical prediction of extreme changes in river basins. In this study, the complexity of daily streamflow fluctuations was investigated by using multifractal detrended fluctuation analysis (MF-DFA) in a large heterogeneous lake basin, the Poyang Lake basin in China, and the potential impacts of human activities were also explored. Major results indicate that the multifractality of streamflow fluctuations shows significant regional characteristics. In the study catchment, all the daily streamflow series present a strong long-range correlation with Hurst exponents bigger than 0.8. The q-order Hurst exponent h(q) of all the hydrostations can be characterized well by only two parameters: a (0.354 ≤ a ≤ 0.384) and b (0.627 ≤ b ≤ 0.677), with no pronounced differences. Singularity spectrum analysis pointed out that small fluctuations play a dominant role in all daily streamflow series. Our research also revealed that both the correlation properties and the broad probability density function (PDF) of hydrological series can be responsible for the multifractality of streamflow series that depends on watershed areas. In addition, we emphasized the relationship between watershed area and the estimated multifractal parameters, such as the Hurst exponent and fitted parameters a and b from the q-order Hurst exponent h(q). However, the relationship between the width of the singularity spectrum (Δα) and watershed area is not clear. Further investigation revealed that increasing forest coverage and reservoir storage can effectively enhance the persistence of daily streamflow, decrease the hydrological complexity of large fluctuations, and increase the small fluctuations.     

A method for checking the quality of geographic metadata based on ISO 19157

With recent advances in remote sensing, location-based services and other related technologies, the production of geospatial information has exponentially increased in the last decades. Furthermore, to facilitate discovery and efficient access to such information, spatial data infrastructures were promoted and standardized, with a consideration that metadata are essential to describing data and services. Standardization bodies such as the International Organization for Standardization have defined well-known metadata models such as ISO 19115. However, current metadata assets exhibit heterogeneous quality levels because they are created by different producers with different perspectives. To address quality-related concerns, several initiatives attempted to define a common framework and test the suitability of metadata through automatic controls. Nevertheless, these controls are focused on interoperability by testing the format of metadata and a set of controlled elements. In this paper, we propose a methodology of testing the quality of metadata by considering aspects other than interoperability. The proposal adapts ISO 19157 to the metadata case and has been applied to a corpus of the Spanish Spatial Data Infrastructure. The results demonstrate that our quality check helps determine different types of errors for all metadata elements and can be almost completely automated to enhance the significance of metadata.     

Late Miocene evaporite geochemistry of Lorca and Fortuna basins (Eastern Betics,SE Spain): Evidence of restriction and continentalization

The Lorca and Fortuna basins are two intramontane Neogene basins located in the eastern Betic Cordillera (SE Spain). During the Late Tortonian—Early Messinian, marine and continental evaporites precipitated in these basins as a consequence of increased marine restriction and isolation. Here we show a stratigraphic correlation between the evaporite records of these basins based on geochemical indicators. We use SO₄ isotope compositions and Sr isotopic ratios in gypsum, and halite Br contents to characterize these units and to identify the marine or continental source of the waters feeding the evaporite basins. In addition, we review the available chronological information used to date these evaporites in Lorca (La Serrata Fm), including a thick saline deposit, that we correlate with the First Evaporitic Group in Fortuna (Los Baños Fm). This correlation is also supported by micropalaeontological data, giving a Late Tortonian age for this sequence. The Second Evaporitic Group, (Chicamo Fm), and the Third Evaporitic Group (Rambla Salada Fm) developed only in Fortuna during the Messinian. According to the palaeogeographical scheme presented here, the evaporites of the Lorca and Fortuna basins were formed during the Late Tortonian—Early Messinian, close to the Betic Seaway closure. Sulphate isotope compositions and Sr isotopic ratios of the Ribera Gypsum Mb, at the base of the Rambla Salada Fm (Fortuna basin), match those of the Late Messinian selenite gypsum beds in San Miguel de Salinas, in the near Bajo Segura basin (40 km to the East), and other Messinian Salinity Crisis gypsum deposits in the Mediterranean. According to these geochemical indicators and the uncertainty of the chronology of this unit, the assignment of the Rambla Salada Fm to the MSC cannot be ruled out.     

Watermarking of digital geospatial datasets: a review of technical,legal and copyright issues

Gathering data accounts for more than 80% of the cost of any GIS project. Fast Internet connections and digital datasets threaten the investments of data producers through data piracy. Outside the GIS community this problem has been known for a long time, and possible solutions exist for digital imagery, formatted text, 3D meshes and so on, showing possible links to typical spatial data. This is largely achieved through embedding hidden information in a dataset without producing perceptible changes in the data, a process known as watermarking. The producer can recover the embedded information on request in order to produce evidence of ownership in a court, so the overall strategy relies on a legal basis rather than technical ones. This paper analyses the state-of-the-art for watermarking protection in digital geographical datasets. Digital imagery is demonstrably a more mature area than geographical information, even with multiple commercial vendors offering watermarking protection. 2D vector and point datasets have received less attention from the research community; however, 3D meshes have been considered by the CAD community and a handful of techniques are available for that case, and they are reviewed here.     

Point- and curve-based geometric conflation

Geometric conflation is the process undertaken to modify the coordinates of features in dataset A in order to match corresponding ones in dataset B. The overwhelming majority of the literature considers the use of points as features to define the transformation. In this article we present a procedure to consider one-dimensional curves also, which are commonly available as Global Navigation Satellite System (GNSS) tracks, routes, coastlines, and so on, in order to define the estimate of the displacements to be applied to each object in A. The procedure involves three steps, including the partial matching of corresponding curves, the computation of some analytical expression, and the addition of a correction term in order to satisfy basic cartographic rules. A numerical example is presented.     

Agricultural land use dynamics in the Brazilian Amazon based on remote sensing and census data

The potential impact of deforestation in the Brazilian Amazon on greenhouse gas emissions to the atmosphere calls for policies that take account of changes in forest cover. Although much research has focused on the location and effects of deforestation, little is known about the distribution and reasons for the agricultural uses that replace forest cover. We used Landsat TM-based deforestation and agricultural census data to generate maps of the distribution and proportion of four major agricultural land uses throughout the Brazilian Amazon in 1997 and 2007. We built linear and spatial regression models to assess the determinant factors of deforestation and those major agricultural land uses - pasture, temporary agriculture and permanent agriculture - for the states of Pará, Rondônia, and Mato Grosso. The data include 30 determinant factors that were grouped into two years (1996 and 2006) and in four categories: accessibility to markets, public policies, agrarian structure, and environment. We found an overall expansion of the total agricultural area between 1997 and 2007, and notable differences between the states of Pará, Rondônia, and Mato Grosso in land use changes during this period. Regression models for deforestation and pasture indicated that determinant factors such as distance to roads were more influential in 1997 than in 2007. The number of settled families played an important role in the deforestation and pasture, the effect was stronger in 2007 than 1997. Indigenous lands were significant in preventing deforestation in high-pressure areas in 2007. For temporary and permanent agricultures, our results show that in 1997 the effect of small farms was stronger than in 2007. The mapped land use time series and the models explain empirically the effects of land use changes across the region over one decade.     

Intercomparison of measurements of bulk snow density and water equivalent of snow cover with snow core samplers: Instrumental bias and variability induced by observers

Manually collected snow data are often considered as ground truth for many applications such as climatological or hydrological studies. However, there are many sources of uncertainty that are not quantified in detail. For the determination of water equivalent of snow cover (SWE), different snow core samplers and scales are used, but they are all based on the same measurement principle. We conducted two field campaigns with 9 samplers commonly used in observational measurements and research in Europe and northern America to better quantify uncertainties when measuring depth, density and SWE with core samplers. During the first campaign, as a first approach to distinguish snow variability measured at the plot and at the point scale, repeated measurements were taken along two 20 m long snow pits. The results revealed a much higher variability of SWE at the plot scale (resulting from both natural variability and instrumental bias) compared to repeated measurements at the same spot (resulting mostly from error induced by observers or very small scale variability of snow depth). The exceptionally homogeneous snowpack found in the second campaign permitted to almost neglect the natural variability of the snowpack properties and focus on the separation between instrumental bias and error induced by observers. Reported uncertainties refer to a shallow, homogeneous tundra-taiga snowpack less than 1 m deep (loose, mostly recrystallised snow and no wind impact). Under such measurement conditions, the uncertainty in bulk snow density estimation is about 5% for an individual instrument and is close to 10% among different instruments. Results confirmed that instrumental bias exceeded both the natural variability and the error induced by observers, even in the case when observers were not familiar with a given snow core sampler.     

A concerted research effort to advance the hydrological understanding of tropical páramos

Páramos, a neotropical alpine grassland-peatland biome of the northern Andes and Central America, play an essential role in regional and global cycles of water, carbon, and nutrients. They act as water towers, delivering water and ecosystem services from the high mountains down to the Pacific, Caribbean, and Amazon regions. Páramos are also widely recognized as a biodiversity and climate change hot spots, yet they are threatened by anthropogenic activities and environmental changes. Despite their importance for water security and carbon storage, and their vulnerability to human activities, only three decades ago, páramos were severely understudied. Increasing awareness of the need for hydrological evidence to guide sustainable management of páramos prompted action for generating data and for filling long-standing knowledge gaps. This has led to a remarkably successful increase in scientific knowledge, induced by a strong interaction between the scientific, policy, and (local) management communities. A combination of well-established and innovative approaches has been applied to data collection, processing, and analysis. In this review, we provide a short overview of the historical development of research and state of knowledge of the hydrometeorology, flux dynamics, anthropogenic impacts, and the influence of extreme events in páramos. We then present emerging technologies for hydrology and water resources research and management applied to páramos. We discuss how converging science and policy efforts have leveraged traditional and new observational techniques to generate an evidence base that can support the sustainable management of páramos. We conclude that this co-evolution of science and policy was able to successfully cover different spatial and temporal scales. Lastly, we outline future research directions to showcase how sustainable long-term data collection can foster the responsible conservation of páramos water towers.