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A novel approach for estimating precipitation patterns is developed here and applied to generate a new hydrologically corrected daily precipitation dataset, called RAIN4PE (Rain for Peru and Ecuador), at 0.1 degrees spatial resolution for the period 1981-2015 covering Peru and Ecuador. It is based on the application of 1) the random forest method to merge multisource precipitation estimates (gauge, satellite, and reanalysis) with terrain elevation, and 2) observed and modeled streamflow data to first detect biases and second further adjust gridded precipitation by inversely applying the simulated results of the ecohydrological model SWAT (Soil and Water Assessment Tool). Hydrological results using RAIN4PE as input for the Peruvian and Ecuadorian catchments were compared against the ones when feeding other uncorrected (CHIRP and ERA5) and gauge-corrected (CHIRPS, MSWEP, and PISCO) precipitation datasets into the model. For that, SWAT was calibrated and validated at 72 river sections for each dataset using a range of performance metrics, including hydrograph goodness of fit and flow duration curve signatures. Results showed that gauge-corrected precipitation datasets outperformed uncorrected ones for streamflow simulation. However, CHIRPS, MSWEP, and PISCO showed limitations for streamflow simulation in several catchments draining into the Pacific Ocean and the Amazon River. RAIN4PE provided the best overall performance for streamflow simulation, including flow variability (low, high, and peak flows) and water budget closure. The overall good performance of RAIN4PE as input for hydrological modeling provides a valuable criterion of its applicability for robust countrywide hydrometeorological applications, including hydroclimatic extremes such as droughts and floods. Significance StatementWe developed a novel precipitation dataset RAIN4PE for Peru and Ecuador by merging multisource precipitation data (satellite, reanalysis, and ground-based precipitation) with terrain elevation using the random forest method. Furthermore, RAIN4PE was hydrologically corrected using streamflow data in watersheds with precipitation underestimation through reverse hydrology. The results of a comprehensive hydrological evaluation showed that RAIN4PE outperformed state-of-the-art precipitation datasets such as CHIRP, ERA5, CHIRPS, MSWEP, and PISCO in terms of daily and monthly streamflow simulations, including extremely low and high flows in almost all Peruvian and Ecuadorian catchments. This underlines the suitability of RAIN4PE for hydrometeorological applications in this region. Furthermore, our approach for the generation of RAIN4PE can be used in other data-scarce regions.
Data driven high resolution modeling and spatial analyses of the COVID-19 pandemic in Germany
(2021)
The SARS-CoV-2 virus has spread around the world with over 100 million infections to date, and currently many countries are fighting the second wave of infections. With neither sufficient vaccination capacity nor effective medication, non-pharmaceutical interventions (NPIs) remain the measure of choice.
However, NPIs place a great burden on society, the mental health of individuals, and economics. Therefore the cost/benefit ratio must be carefully balanced and a target-oriented small-scale implementation of these NPIs could help achieve this balance.
To this end, we introduce a modified SEIRD-class compartment model and parametrize it locally for all 412 districts of Germany. The NPIs are modeled at district level by time varying contact rates. This high spatial resolution makes it possible to apply geostatistical methods to analyse the spatial patterns of the pandemic in Germany and to compare the results of different spatial resolutions.
We find that the modified SEIRD model can successfully be fitted to the COVID-19 cases in German districts, states, and also nationwide. We propose the correlation length as a further measure, besides the weekly incidence rates, to describe the current situation of the epidemic.
Woody plants are expanding into the Arctic in response to the warming climate. The impact on arctic plant communities is not well understood due to the limited knowledge about plant assembly rules.
Records of past plant diversity over long time series are rare. Here, we applied sedimentary ancient DNA metabarcoding targeting the P6 loop of the chloroplast trnL gene to a sediment record from Lake Ilirney (central Chukotka, Far Eastern Russia) covering the last 28 thousand years.
Our results show that forb-rich steppe-tundra and dwarf-shrub tundra dominated during the cold climate before 14 ka, while deciduous erect-shrub tundra was abundant during the warm period since 14 ka. Larix invasion during the late Holocene substantially lagged behind the likely warmest period between 10 and 6 ka, where the vegetation biomass could be highest.
We reveal highest richness during 28-23 ka and a second richness peak during 13-9 ka, with both periods being accompanied by low relative abundance of shrubs. During the cold period before 14 ka, rich plant assemblages were phylogenetically clustered, suggesting low genetic divergence in the assemblages despite the great number of species. This probably originates from environmental filtering along with niche differentiation due to limited resources under harsh environmental conditions. In contrast, during the warmer period after 14 ka, rich plant assemblages were phylogenetically overdispersed.
This results from a high number of species which were found to harbor high genetic divergence, likely originating from an erratic recruitment process in the course of warming. Some of our evidence may be of relevance for inferring future arctic plant assembly rules and diversity changes. By analogy to the past, we expect a lagged response of tree invasion. Plant richness might overshoot in the short term; in the long-term, however, the ongoing expansion of deciduous shrubs will eventually result in a phylogenetically more diverse community.
Groundwater is critical in supporting current and future reliable water supply throughout Africa. Although continental maps of groundwater storage and recharge have been developed, we currently lack a clear understanding on how the controls on groundwater recharge vary across the entire continent. Reviewing the existing literature, we synthesize information on reported groundwater recharge controls in Africa. We find that 15 out of 22 of these controls can be characterised using global datasets. We develop 11 descriptors of climatic, topographic, vegetation, soil and geologic properties using global datasets, to characterise groundwater recharge controls in Africa. These descriptors cluster Africa into 15 Recharge Landscape Units for which we expect recharge controls to be similar. Over 80% of the continents land area is organized by just nine of these units. We also find that aggregating the Units by similarity into four broader Recharge Landscapes (Desert, Dryland, Wet tropical and Wet tropical forest) provides a suitable level of landscape organisation to explain differences in ground-based long-term mean annual recharge and recharge ratio (annual recharge / annual precipitation) estimates. Furthermore, wetter Recharge Landscapes are more efficient in converting rainfall to recharge than drier Recharge Landscapes as well as having higher annual recharge rates. In Dryland Recharge Landscapes, we found that annual recharge rates largely varied according to mean annual precipitation, whereas recharge ratio estimates increase with increasing monthly variability in P-PET. However, we were unable to explain why ground based estimates of recharge signatures vary across other Recharge Landscapes, in which there are fewer ground based recharge estimates, using global datasets alone. Even in dryland regions, there is still considerable unexplained variability in the estimates of annual recharge and recharge ratio, stressing the limitations of global datasets for investigating ground-based information.
Semi-distributed hydrological and water quality models are increasingly used as innovative and scientific-based management tools.
However, their application is usually restricted to the gauging stations where they are originally calibrated, limiting their spatial capability.
In this study, the semi-distributed hydrological water quality model HYPE (HYdrological Predictions for the Environment) was tested spatially to represent nitrate-N (NO3- N) and total phosphorus (TP) concentrations and loads of the nested and heterogeneous Selke catchment (463 km(2)) in central Germany.
First, an automatic calibration procedure and uncertainty analysis were conducted using the DiffeRential Evolution Adaptive Metropolis (DREAM) tool to simulate discharge, NO3--N and TP concentrations. A multi-site and multi-objective calibration approach was applied using three main gauging stations, covering the most important hydro-meteorological and physiographical characteristics of the whole catchment. Second, the model's capability was tested to represent further internal stations, which were not initially considered for calibration. Results showed that discharge was well represented by the model at all three main stations during both calibration (1994-1998) and validation (1999-2014) periods with lowest Nash-Sutcliffe Efficiency (NSE) of 0.71 and maximum Percentage BIAS (PBIAS) of 18.0%.
The model was able to reproduce the seasonal dynamics of NO3--N and TP concentrations with low predictive uncertainty at the three main stations, reflected by PBIAS values in the ranges from 16.1% to 6.4% and from 20.0% to 11.5% for NO3--N and TP load simulations, respectively.
At internal stations, the model could represent reasonably well the seasonal variation of nutrient concentrations with PBIAS values in the ranges from 9.0% to 14.2% for NO3--N and from 25.3% to 34.3% for TP concentration simulations.
Overall, results suggested that the spatial validation of a nutrient transport model can be better ensured when a multi-site and multi-objective calibration approach using archetypical gauging stations is implemented.
Further, results revealed that the delineation of sub-catchments should put more focus on hydro-meteorological conditions than on land-use features.
Seeing beyond the outcrop
(2021)
Paleokarst breccias are a common feature of sedimentary rift basins. The Billefjorden Trough in the High Arctic archipelago of Svalbard is an example of such a rift. Here the Carboniferous stratigraphy exhibits intervals of paleokarst breccias formed by gypsum dissolution. In this study we integrate digital outcrop models (DOMs) with a 2D ground penetrating radar (GPR) survey to extrapolate external irregular paleokarst geometries beyond the 2D outcrops. DOMs are obtained through combining a series of overlapping photographs with structure-frommotion photogrammetry, to create mmto dm-resolution georeferenced DOMs. GPR is typically used for surveying the shallow subsurface and relies on detecting the contrasts in electro-magnetic permittivity. We defined three geophysical facies based on their appearance in GPR. By integrating subsurface geophysical data with DOMs we were able to correlate reflection patterns in GPR with outcrop features. The chaotic nature of paleokarst breccias is seen both in outcrop and GPR. Key horizons in outcrop and the GPR profiles allow tying together observations between these methods. Furthermore, we show that this technique expands the twodimensional outcrop surface into a three-dimensional domain, thus complementing, strengthening and extending outcrop interpretations.
Canada's RADARSAT missions improve the potential to study past flood events; however, existing tools to derive flood depths from this remote-sensing data do not correct for errors, leading to poor estimates.
To provide more accurate gridded depth estimates of historical flooding, a new tool is proposed that integrates Height Above Nearest Drainage and Cost Allocation algorithms. This tool is tested against two trusted, hydraulically derived, gridded depths of recent floods in Canada.
This validation shows the proposed tool outperforms existing tools and can provide more accurate estimates from minimal data without the need for complex physics-based models or expert judgement.
With improvements in remote-sensing data, the tool proposed here can provide flood researchers and emergency managers accurate depths in near-real time.
Efforts have been made in the past to enhance building exposure models on a regional scale with increasing spatial resolutions by integrating different data sources. This work follows a similar path and focuses on the downscaling of the existing SARA exposure model that was proposed for the residential building stock of the communes of Valparaiso and Vina del Mar (Chile). Although this model allowed great progress in harmonising building classes and characterising their differential physical vulnerabilities, it is now outdated, and in any case, it is spatially aggregated over large administrative units. Hence, to more accurately consider the impact of future earthquakes on these cities, it is necessary to employ more reliable exposure models. For such a purpose, we propose updating this existing model through a Bayesian approach by integrating ancillary data that has been made increasingly available from Volunteering Geo-Information (VGI) activities. Its spatial representation is also optimised in higher resolution aggregation units that avoid the inconvenience of having incomplete building-by-building footprints. A worst-case earthquake scenario is presented to calculate direct economic losses and highlight the degree of uncertainty imposed by exposure models in comparison with other parameters used to generate the seismic ground motions within a sensitivity analysis. This example study shows the great potential of using increasingly available VGI to update worldwide building exposure models as well as its importance in scenario-based seismic risk assessment.
Seismic scattering and absorption of oceanic lithospheric S waves in the Eastern North Atlantic
(2021)
The scattering and absorption of high-frequency seismic waves in the oceanic lithosphere is to date only poorly constrained by observations. Such estimates would not only improve our understanding of the propagation of seismic waves, but also unravel the small-scale nature of the lithosphere and its variability. Our study benefits from two exceptional situations: (1) we deployed over 10 months a mid-aperture seismological array in the central part of the Eastern North Atlantic in 5 km water depth and (2) we could observe in total 340 high-frequency (up to 30 Hz) Po and So arrivals with tens to hundreds of seconds long seismic coda from local and regional earthquakes in a wide range of backazimuths and epicentral distances up to 850 km with a travel path in the oceanic lithosphere. Moreover, the array was located about 100 km north of the Gloria fault, defining the plate boundary between the Eurasian and African plates at this location which also allows an investigation of the influence of an abrupt change in lithospheric age (20 Ma in this case) on seismic waves. The waves travel with velocities indicating upper-mantle material. We use So waves and their coda of pre-selected earthquakes to estimate frequency-dependent seismic scattering and intrinsic attenuation parameters. The estimated scattering attenuation coefficients are between 10(-4) and 4 x 10(-5) m(-1) and are typical for the lithosphere or the upper mantle. Furthermore, the total quality factors for So waves below 5 Hz are between 20 and 500 and are well below estimates from previous modelling for observations in the Pacific Ocean. This implies that the Atlantic Ocean is more attenuative for So waves compared to the Pacific Ocean, which is inline with the expected behaviour for the lithospheric structures resulting from the slower spreading rates in the Atlantic Ocean. The results for the analysed events indicate that for frequencies above 3 Hz, intrinsic attenuation is equal to or slightly stronger than scattering attenuation and that the So-wave coda is weakly influenced by the oceanic crust. Both observations are in agreement with the proposed propagation mechanism of scattering in the oceanic mantle lithosphere. Furthermore, we observe an age dependence which shows that an increase in lithospheric age is associated with a decrease in attenuation. However, we also observe a trade-off of this age-dependent effect with either a change in lithospheric thickness or thermal variations, for example due to small-scale upwellings in the upper mantle in the southeast close to Madeira and the Canaries. Moreover, the influence of the nearby Gloria fault is visible in a reduction of the intrinsic attenuation below 3 Hz for estimates across the fault. This is the first study to estimate seismic scattering and absorption parameters of So waves for an area with several hundreds of kilometres radius centred in the Eastern North Atlantic and using them to characterize the nature of the oceanic lithosphere.
Southeastern Tibetan Plateau growth revealed by inverse analysis of landscape evolution model
(2022)
The Cenozoic history of the Tibetan Plateau topography is critical for understanding the evolution of the Indian-Eurasian collision, climate, and biodiversity. However, the long-term growth and landscape evolution of the Tibetan Plateau remain ambiguous, it remains unclear if plateau uplift occurred soon after the India-Asia collision in the Paleogene (similar to 50-25 Ma) or later in the Neogene (similar to 20-5 Ma). Here, we reproduce the uplift history of the southeastern Tibetan Plateau using a 2D landscape evolution model, which simultaneously solves fluvial erosion and sediment transport processes in the drainage basins of the Three Rivers region (Yangtze, Mekong, and Salween Rivers). Our model was optimized through a formal inverse analysis with 20,000 forward simulations, which aims to reconcile the transient states of the present-day river profiles. The results, compared to existing paleoelevation and thermochronologic data, suggest initially low elevations (similar to 300-500 m) during the Paleogene, followed by a gradual southeastward propagation of topographic uplift of the plateau margin.
Fast-localized electron loss, resulting from interactions with electromagnetic ion cyclotron (EMIC) waves, can produce deepening minima in phase space density (PSD) radial profiles. Here, we perform a statistical analysis of local PSD minima to quantify how readily these are associated with radiation belt depletions. The statistics of PSD minima observed over a year are compared to the Versatile Electron Radiation Belts (VERB) simulations, both including and excluding EMIC waves. The observed minima distribution can only be achieved in the simulation including EMIC waves, indicating their importance in the dynamics of the radiation belts. By analyzing electron flux depletions in conjunction with the observed PSD minima, we show that, in the heart of the outer radiation belt (L* < 5), on average, 53% of multi-MeV electron depletions are associated with PSD minima, demonstrating that fast localized loss by interactions with EMIC waves are a common and crucial process for ultra-relativistic electron populations.
The investigation of stresses, faults, structure and seismic hazards requires a good understanding and mapping of earthquake rupture and slip. Constraining the finite source of earthquakes from seismic and geodetic waveforms is challenging because the directional effects of the rupture itself are small and dynamic numerical solutions often include a large number of free parameters. The computational effort is large and therefore difficult to use in an exploratory forward modelling or inversion approach. Here, we use a simplified self-similar fracture model with only a few parameters, where the propagation of the fracture front is decoupled from the calculation of the slip. The approximative method is flexible and computationally efficient. We discuss the strengths and limitations of the model with real-case examples of well-studied earthquakes. These include the M-w 8.3 2015 Illapel, Chile, megathrust earthquake at the plate interface of a subduction zone and examples of continental intraplate strike-slip earthquakes like the M-w 7.1 2016 Kumamoto, Japan, multisegment variable slip event or the M-w 7.5 2018 Palu, Indonesia, supershear earthquake. Despite the simplicity of the model, a large number of observational features ranging from different rupture-front isochrones and slip distributions to directional waveform effects or high slip patches are easy to model. The temporal evolution of slip rate and rise time are derived from the incremental growth of the rupture and the stress drop without imposing other constraints. The new model is fast and implemented in the open-source Python seismology toolbox Pyrocko, ready to study the physics of rupture and to be used in finite source inversions.
Electronic databases of landslides seldom include the triggering mechanisms, rendering these inventories unusable for landslide hazard modeling. We present a method for classifying the triggering mechanisms of landslides in existing inventories, thus, allowing these inventories to aid in landslide hazard modeling corresponding to the correct event chain. Our method uses various geometric characteristics of landslides as the feature space for the machine-learning classifier random forest, resulting in accurate and robust classifications of landslide triggers. We applied the method to six landslide inventories spread over the Japanese archipelago in several different tests and training configurations to demonstrate the effectiveness of our approach. We achieved mean accuracy ranging from 67% to 92%. We also provide an illustrative example of a real-world usage scenario for our method using an additional inventory with unknown ground truth. Furthermore, our feature importance analysis indicates that landslides having identical trigger mechanisms exhibit similar geometric properties.
Pressure induced structural changes in silicate melts have a great impact on their physico-chemical properties and hence on their behaviour in the deep Earth's interior. In order to gain a deeper understanding we have studied the densification mechanism in multicomponent aluminosilicate glasses (albitic and albit-diopside composition) by means of extended X-ray absorption fine structure spectroscopy coupled to a diamond anvil cell up to 164 GPa. We have monitored the structural modifications from the network-former Ge as well as the network-modifier Sr. Notably, we tracked the evolution of Ge-O and Sr-O bond lengths (RGe-O, RSr-O) and their coordination number with pressure. We show that RGe-O increases strongly up to about 32 GPa, whereas RSr-O increases only slightly up to similar to 26 GPa. We assign these extensions to the increase of the coordination number from 4 to 6 (Ge) and from similar to 6 to at least 9 (Sr). Upon further compression RGe-O and RSr-O exhibit a continuous decrease to the highest probed pressure. These bond contractions, notably of RGe-O, that are continuous and exceed the one observed in pure SiO2 and GeO2, reflect a higher structural flexibility of multi-component glasses compared to those simple systems. Particularly, the high fraction of non-bridging oxygen atoms due to the presence of Na, Sr, Ca, Mg in the studied glasses, favours the simple compression of the highly-coordinated polyhedra of Si and Ge at pressure greater than 30 GPa. This is in strong contrast to pure oxides where cation polyhedral distortions govern the densification mechanism of the glass. The results of this study demonstrate that low field-strength alkali and alkaline earth cations, ubiquitous in deep Earth's melts, have a profound influence on the densification mechanism of glasses. Our results provide important constrains for interpreting the observed low velocity anomalies at the Earth's core-mantle boundary that have been, beyond others, referred to the presence of high-density melts. The hypothesis that non-buoyant melts at the Earth's core-mantle boundary can be formed by peculiar structural transformations in melts leading to higher coordination numbers compared to their crystalline equivalents is not supported from the present observations. The present results rather suggest that if velocity anomalies are to be explained by melts, these likely have considerable differences in chemical composition to the surrounding crystalline phase assemblage.
Marine sedimentary archives are routinely used to reconstruct past environmental changes. In many cases, bioturbation and sedimentary mixing affect the proxy time-series and the age-depth relationship. While idealized models of bioturbation exist, they usually assume homogeneous mixing, thus that a single sample is representative for the sediment layer it is sampled from.
However, it is largely unknown to which extent this assumption holds for sediments used for paleoclimate reconstructions.
To shed light on
1) the age-depth relationship and its full uncertainty,
2) the magnitude of mixing processes affecting the downcore proxy variations, and
3) the representativity of the discrete sample for the sediment layer, we designed and performed a case study on South China Sea sediment material which was collected using a box corer and which covers the last glacial cycle.
Using the radiocarbon content of foraminiferal tests as a tracer of time, we characterize the spatial age-heterogeneity of sediments in a three-dimensional setup. In total, 118 radiocarbon measurements were performed on defined small- and large-volume bulk samples ( similar to 200 specimens each) to investigate the horizontal heterogeneity of the sediment. Additionally, replicated measurements on small numbers of specimens (10 x 5 specimens) were performed to assess the heterogeneity within a sample volume. Visual assessment of X-ray images and a quantitative assessment of the mixing strength show typical mixing from bioturbation corresponding to around 10 cm mixing depth.
Notably, our 3D radiocarbon distribution reveals that the horizontal heterogeneity (up to 1,250 years), contributing to the age uncertainty, is several times larger than the typically assumed radiocarbon based age-model error (single errors up to 250 years). Furthermore, the assumption of a perfectly bioturbated layer with no mixing underneath is not met.
Our analysis further demonstrates that the age-heterogeneity might be a function of sample size; smaller samples might contain single features from the incomplete mixing and are thus less representative than larger samples.
We provide suggestions for future studies, optimal sampling strategies for quantitative paleoclimate reconstructions and realistic uncertainty in age models, as well as discuss possible implications for the interpretation of paleoclimate records.
The within-site variability in site response is the randomness in site response at a given site from different earthquakes and is treated as aleatory variability in current seismic hazard/risk analyses.
In this study, we investigate the single-station variability in linear site response at K-NET and KiK-net stations in Japan using a large number of earthquake recordings.
We found that the standard deviation of the horizontal-to-vertical Fourier spectral ratio at individual sites, that is single-station horizontal-to-vertical spectral ratio (HVSR) sigma sigma(HV,s), approximates the within-site variability in site response quantified using surface-to-borehole spectral ratios (for oscillator frequencies higher than the site fundamental frequency) or empirical ground-motion models.
Based on this finding, we then utilize the single-station HVSR sigma as a convenient tool to study the site-response variability at 697 KiK-net and 1169 K-NET sites.
Our results show that at certain frequencies, stiff, rough and shallow sites, as well as small and local events tend to have a higher sigma(HV,s).
However, when being averaged over different sites, the single-station HVSR sigma, that is sigma(HV), increases gradually with decreasing frequency. In the frequency range of 0.25-25 Hz, sigma(HV) is centred at 0.23-0.43 in ln scales (a linear scale factor of 1.26-1.54) with one standard deviation of less than 0.1. sigma(HV) is quite stable across different tectonic regions, and we present a constant, as well as earthquake magnitude- and distance-dependent sigma(HV) models.
In this study we present a novel method for the automatic detection of minerals and elements using hyperspectral transmittance imaging microscopy measurements of complete thin sections (HyperTIM).
This is accomplished by using a hyperspectral camera system that operates in the visible and near-infrared (VNIR) range with a specifically designed sample holder, scanning setup, and a microscope lens.
We utilize this method on a monazite ore thin section from Steenkampskraal (South Africa), which we analyzed for the rare earth element (REE)-bearing mineral monazite ((Ce,Nd,La)PO4), with high concentrations of Nd. The transmittance analyses with the hyperspectral VNIR camera can be used to identify REE minerals and Nd in thin sections.
We propose a three-point band depth index, the Nd feature depth index (NdFD), and its related product the Nd band depth index (NdBDI), which enables automatic mineral detection and classification for the Nd-bearing monazites in thin sections. In combination with the average concentration of the relative Nd content, it permits a destruction-free, total concentration calculation for Nd across the entire thin section.
Groundwater recharge (GWR) is one of the most challenging water fluxes to estimate, as it relies on observed data that are often limited in many developing countries.
This study developed an innovative water budget method using satellite products for estimating the spatially distributed GWR at monthly and annual scales in tropical wet sedimentary regions despite cloudy conditions.
The distinctive features proposed in this study include the capacity to address 1) evapotranspiration estimations in tropical wet regions frequently overlaid by substantial cloud cover; and 2) seasonal root-zone water storage estimations in sedimentary regions prone to monthly variations.
The method also utilises satellite-based information of the precipitation and surface runoff. The GWR was estimated and validated for the hydrologically contrasting years 2016 and 2017 over a tropical wet sedimentary region located in North-eastern Brazil, which has substantial potential for groundwater abstraction.
This study showed that applying a cloud-cleaning procedure based on monthly compositions of biophysical data enables the production of a reasonable proxy for evapotranspiration able to estimate groundwater by the water budget method.
The resulting GWR rates were 219 (2016) and 302 (2017) mm yr(-1), showing good correlations (CC = 0.68 to 0.83) and slight underestimations (PBIAS =-13 to-9%) when compared with the referenced estimates obtained by the water table fluctuation method for 23 monitoring wells. Sensitivity analysis shows that water storage changes account for +19% to-22% of our monthly evaluation.
The satellite-based approach consistently demonstrated that the consideration of cloud-cleaned evapotranspiration and root-zone soil water storage changes are essential for a proper estimation of spatially distributed GWR in tropical wet sedimentary regions because of their weather seasonality and cloudy conditions.
Agricultural production worldwide has been increasing in the last decades at a very fast pace and with it the waste generation. Livestock activities are one of the largest producers of residues in the agricultural sector and contribute greatly to climate change. The present chapter gives an introduction and an in-depth analysis of the waste management of livestock for the conversion in a circular agriculture and economy based on research and experience in the sector conducted in the last decades. The conversion of animal waste into energy generation is an opportunity for farmers to obtain additional economic benefits, while contributing to the environment by preventing the release of GHGs into the atmosphere. The use of animal waste for energy generation through anaerobic digestion is a progressive technique and is being widely accepted in Europe, where Germany is the leading country in the use of biogas plants for energy production among others in the European Union. Economically speaking, the livestock industry faces the challenge of converting its production into a clean and more profitable production. The goal of this chapter is to analyze the economic benefit as well as the environmental contribution and future challenges of the use of livestock waste in the biorefineries sector from different perspectives, based on an intensive literature review. This review is accompanied by a geospatial analysis component, mapping biogas reactor hotspots and clusters in Germany, by means of methods of spatial statistics as analysis methods as kernel density estimations (KDE) and K-means clustering, based on volunteer geographic data. The applied methods easily can be transferred to other regions and allow a quick macroscopic overview over existing biogas reactors; furthermore, an identification of cluster and hotspots with a high biogas potential, that in a subsequent step can be analyzed in depth in larger scales.
Carbonate minerals are common in both marine and lacustrine records, and are frequently used for paleoenvironmental reconstructions. The sedimentary sequence of the endorheic Dead Sea and its precursors contain aragonite laminae that provide a detailed sedimentary archive of climatic, hydrologic, limnologic and environmental conditions since the Pleistocene. However, the interpretation of these archives requires a detailed understanding of the constraints and mechanisms affecting CaCO3 precipitation, which are still debated. The implications of aragonite precipitation in the Dead Sea and in its late Pleistocene predecessor (Lake Lisan) were investigated in this study by mixing natural and synthetic brines with a synthetic bicarbonate solution that mimics flash-floods composition, with and without the addition of extracellular polymeric substances (EPS). Aragonite precipitation was monitored, and precipitation rates and carbonate yields were calculated and are discussed with respect to modern aquatic environments. The experimental insights on aragonite precipitation are then integrated with microfacies analyses in order to reconstruct and constrain prevailing limnogeological processes and their hydroclimatic drivers under low (interglacial) and high (glacial) lake level stands. Aragonite precipitation took place within days to several weeks after the mixing of the brines with a synthetic bicarbonate solution. Incubation time was proportional to bicarbonate concentration, and precipitation rates were partially influenced by ionic strength. Additionally, extracellular polymeric substances inhibited aragonite precipitation for several months. As for the lake's water budget, our calculations suggest that the precipitation of a typical aragonite lamina (0.5 mm thick) during high lake stand requires unreasonable freshwater inflow from either surface or subsurface sources. This discrepancy can be resolved by considering one or a combination of the following scenarios; (1) discontinuous aragonite deposition over parts of the lake floor; (2) supply of additional carbonate flux (or fluxes) to the lake from aeolian dust and the remobilization and dissolution of dust deposits at the watershed; (3) carbonate production via oxidation of organic carbon by sulfate-reducing bacteria. Altogether, it is suggested that aragonite laminae thickness cannot be directly interpreted for quantitatively reconstructing the hydrological balance for the entire lake, they may still prove valuable for identifying inherent hydroclimatic periodicities at a single site.