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Our Conclusions
(2018)
Point clouds provide high-resolution topographic data which is often classified into bare-earth, vegetation, and building points and then filtered and aggregated to gridded Digital Elevation Models (DEMs) or Digital Terrain Models (DTMs). Based on these equally-spaced grids flow-accumulation algorithms are applied to describe the hydrologic and geomorphologic mass transport on the surface. In this contribution, we propose a stochastic point-cloud filtering that, together with a spatial bootstrap sampling, allows for a flow accumulation directly on point clouds using Facet-Flow Networks (FFN). Additionally, this provides a framework for the quantification of uncertainties in point-cloud derived metrics such as Specific Catchment Area (SCA) even though the flow accumulation itself is deterministic.
Water management tools are necessary to guarantee the preservation of natural resources while ensuring optimum utilization. Linear regression models are a simple and quick solution for creating prognostic capabilities. Multivariate models show higher precision than univariate models. In the case of Waiwera, implementation of individual production rates is more accurate than applying just the total production rate. A maximum of approximately 1,075 m3/day can be pumped to ensure a water level of at least 0.5 m a.s.l. in the monitoring well. The model should be renewed annually to implement new data and current water level trends to keep the quality.
The nature restoration project ‘Lenzener Elbtalaue’, realised from 2002 to 2011 at the river Elbe, included the first large scale dike relocation in Germany (420 ha). Its aim was to initiate the development of endangered natural wetland habitats and processes, accompanied by greater biodiversity in the former grassland dominated area. The monitoring of spatial and temporal variations of soil moisture in this dike relocation area is therefore particularly important for estimating the restoration success. The topsoil moisture monitoring from 1990 to 2017 is based on the Soil Moisture Index (SMI)1 derived with the triangle method2 by use of optical remotely sensed data: land surface temperature and Normalized Differnce Vegetation Index are calculated from Landsat 4/5/7/8 data and atmospheric corrected by use of MODIS data. Spatial and temporal soil moisture variations in the restored area of the dike relocation are compared to the agricultural and pasture area behind the new dike. Ground truth data in the dike relocation area was obtained from field measurements in October 2017 with a FDR device. Additionally, data from a TERENO soil moisture sensor network (SoilNet) and mobile cosmic ray neutron sensing (CRNS) rover measurements are compared to the results of the triangle method for a region in the Harz Mountains (Germany). The SMI time series illustrates, that the dike relocation area has become significantly wetter between 1990 and 2017, due to restructuring measurements. Whereas the SMI of the dike hinterland reflects constant and drier conditions. An influence of climate is unlikely. However, validation of the dimensionless index with ground truth measurements is very difficult, mostly due to large differences in scale.
Secondary mica minerals collected from the Santa Helena (W- (Cu) mineralization) and Venise (W-Mo mineralization) endogenic breccia structures were Ar-40/Ar-39 dated. The muscovite Ar-40/Ar-39 data yielded 286.8 +/- 1.2 (+/- 1 sigma) Ma (samples 6Ha and 11Ha) which reflect the age of secondary muscovite formation probably from magmatic biotite or feldspar alteration. Sericite Ar-40/Ar-39 data yielded 280.9 +/- 1.2 (+/- 1 sigma) Ma to 279.0 +/- 1.1 (+/- 1 sigma) Ma (samples 6Hb and 11Hb) reflecting the age of greisen alteration (T similar to 300 degrees C) where the W- disseminated mineralization occurs. The muscovite 40Ar/39Ar data of 277.3 +/- 1.3 (+/- 1 sigma) Ma and 281.3 +/- 1.2 (+/- 1 sigma) Ma (samples 5 and 6) also reflect the age of muscovite (selvage) crystallized adjacent to molybdenite veins within the Venise breccia. Geochronological data obtained confirmed that the W mineralization at Santa Helena breccia is older than Mo-mineralization at Venise breccia. Also, the timing of hydrothermal circulation and the cooling history for the W-stage deposition was no longer than 7 Ma and 4 Ma for Mo-deposition.