ALBERT

Description: Der Band zeigt die Ergebnisse des Praxisforschungsprojektes BUSLAR. Untersucht wurde, wie durch Selbstorganisation z.B. in Bürgerhilfevereinen in ländlichen Räumen Aufgaben der Unterstützung älterer Menschen übernommen werden. Von Seiten der Politik wird dieses Engagement begrüßt in der Hoffnung, es könne Lücken in der öffentlichen Daseinsvorsorge ein stückweit schließen – ohne angemessene Unterstützung, ist dieses Engagement nachhaltig gefährdet.

Description: A wireless sensor network (WSN) was deployed as part of a water balance instrument cluster across a forested 1 km2 headwater catchment in the southern Sierra Nevada of California. The network, which integrates readings from over 300 sensors, provides spatially representative measurements of snow depth, solar radiation, relative humidity, soil moisture, and matric potential. The ability of this densely instrumented watershed to capture catchment-scale snow depth and soil moisture distributions is investigated through comparison with three comprehensive gridded surveys and 1 day of detailed lidar snow data. Statistical analysis shows that the network effectively characterized catchment-wide distributions of snow depth, while offering a cost-effective, reliable, and energy-efficient means for collecting distributed data in real time. A temporal analysis of snow depth variability reveals that canopy cover is the major explanatory variable of snow depth and that under-canopy measurements persistently show higher variability compared to those in open terrain. An analysis of soil moisture shows lower variability at deeper soil depth and a correlation between mean soil moisture and variability for shallow soils. A three-phase design procedure was used to optimize the WSN deployment. First, as off-the-shelf performance of current WSN platforms for large-scale, long-term deployments cannot be guaranteed, statistics from a prototype deployment were analyzed. Two indicators of network performance, the packet delivery ratio and received signal strength indicator, showed that for our site conditions, a conservative 50 m node-to-node spacing would ensure low-power, reliable, and robust network communications. Second, results from the prototype were used to refine hardware specifications and to guide the layout of the full 57-node wireless network. Of these nodes, 23 were used actively for sensing, while the remaining 34 nodes were used as signal repeaters to ensure proper spatial radio coverage and robust network operations. Further analysis of network statistics is conducted during the third, operational, phase to validate system performance.

Description: A network of sensors for spatially representative water-balance measurements was developed and deployed across the 2000 km 2 snow-dominated portion of the upper American River basin, primarily to measure changes in snowpack and soil-water storage, air temperature and humidity. This wireless sensor network (WSN) consists of 14 sensor clusters, each with 10 measurement nodes that were strategically placed within a 1­km 2 area, across different elevations, aspects, slopes and canopy covers. Compared to existing operational sensor installations, the WSN reduces hydrologic uncertainty in at least three ways. First, redundant measurements improved estimation of lapse rates for air and dew-point temperature. Second, distributed measurements captured local variability and constrained uncertainty in air and dew-point temperature, snow accumulation and derived hydrologic attributes important for modeling and prediction. Third, the distributed relative-humidity measurements offer a unique capability to monitor upper-basin patterns in dew-point temperature and characterize elevation gradient of water vapor-pressure deficit across steep, variable topography. Network statistics during the first year of operation demonstrated that the WSN was robust for cold, wet and windy conditions in the basin. The electronic technology used in the WSN reduced adverse effects, such as high current consumption, multipath signal fading and clock drift, seen in previous remote WSNs.

Description: [1]  A wireless sensor network (WSN) was deployed as part of a water balance instrument cluster across a forested 1 km 2 headwater catchment in the southern Sierra Nevada of California. The network, which integrates readings from over 300 sensors, provides spatially representative measurements of snow depth, solar radiation, relative humidity, soil moisture, and matric potential. The ability of this densely instrumented watershed to capture catchment-scale snow depth and soil moisture distributions is investigated through comparison with three comprehensive gridded surveys and 1 day of detailed lidar snow data. Statistical analysis shows that the network effectively characterized catchment-wide distributions of snow depth, while offering a cost-effective, reliable, and energy-efficient means for collecting distributed data in real time. A temporal analysis of snow depth variability reveals that canopy cover is the major explanatory variable of snow depth and that under-canopy measurements persistently show higher variability compared to those in open terrain. An analysis of soil moisture shows lower variability at deeper soil depth and a correlation between mean soil moisture and variability for shallow soils. A three-phase design procedure was used to optimize the WSN deployment. First, as off-the-shelf performance of current WSN platforms for large-scale, long-term deployments cannot be guaranteed, statistics from a prototype deployment were analyzed. Two indicators of network performance, the packet delivery ratio and received signal strength indicator, showed that for our site conditions, a conservative 50 m node-to-node spacing would ensure low-power, reliable, and robust network communications. Second, results from the prototype were used to refine hardware specifications and to guide the layout of the full 57-node wireless network. Of these nodes, 23 were used actively for sensing, while the remaining 34 nodes were used as signal repeaters to ensure proper spatial radio coverage and robust network operations. Further analysis of network statistics is conducted during the third, operational, phase to validate system performance.