Local air temperature tolerance: a sensible basis for estimating climate variability

The customary representation of climate using sample moments is generally biased due to the noticeably nonstationary behaviour of many climate series. In this study, we introduce a moment-free climate representation based on a statistical model fitted to a long-term daily air temperature anomaly series. This model allows us to separate the climate and weather scale variability in the series. As a result, the climate scale can be characterized using the mean annual cycle of series and local air temperature tolerance, where the latter is computed using the fitted model. The representation of weather scale variability is specified using the frequency and the range of outliers based on the tolerance. The scheme is illustrated using five long-term air temperature records observed by different European meteorological stations.     

Assessment of small-diameter shallow wells for managed aquifer recharge at a site in southern Styria,Austria

An approach to establish the recharge component of managed aquifer recharge (MAR) has recently been proposed that uses small-diameter shallow wells installed using relatively inexpensive drilling methods such as direct push. As part of further development of that approach, a generalized procedure is presented for a technical and economic assessment of the approach’s potential in comparison to other systems. Following this procedure, the use of small-diameter wells was evaluated both experimentally and numerically for a site located in southern Styria, Austria. MAR is currently done at the site using a horizontal pipe infiltration system, and system expansion has been proposed with a target rate of 12 l/s using small-diameter wells as one possible option. A short-duration single-well field recharge experiment (recharge rate 1.3–3.5 l/s) was performed (recharge by gravity only). Numerical modeling of the injection test was used to estimate hydraulic conductivity (K). Quasi-steady-state, single-well recharge simulations for different locations, as well as a long-term transient simulation, were performed using the K value calibrated from the field injection test. Results indicate that a recharge capacity of 4.1 l/s was achievable with a maximum head rise of 0.2 m at the injection well. Finally, simulations were performed for three different well fields (4, 6 and 8 wells, respectively) designed to infiltrate a target rate of 12 l/s. The experimental and numerical assessments, supported by a cost analysis of the small-diameter wells, indicate that the small-diameter wells are a viable, cost-effective recharge approach at this and other similar sites.     

Forecasting rock slope failure: how reliable and effective are warning systems?

Warning systems are increasingly applied to reduce damage caused by different magnitudes of rockslides and rockfalls. In an integrated risk-management approach, the optimal risk mitigation strategy is identified by comparing the achieved effectiveness and cost; estimating the reliability of the warning system is the basis for such considerations. Here, we calculate the reliability and effectiveness of the warning system installed in Preonzo prior to a major rockfall in May 2012. “Reliability” is defined as the ability of the warning system to forecast the hazard event and to prevent damage. To be cost-effective, the warning system should forecast an event with a limited number of false alarms to avoid unnecessary costs for intervention measures. The analysis shows that to be reliable, warning systems should be designed as fail-safe constructions. They should incorporate components with low failure probabilities, high redundancy, have low warning thresholds, and additional control systems. In addition, the experts operating the warning system should have limited risk tolerance. In an additional hypothetical probabilistic analysis, we investigate the effect of the risk attitude of the decision makers and of the number of sensors on the probability of detecting the event and initiating a timely evacuation, as well as on the related intervention cost. The analysis demonstrates that quantitative assessments can support the identification of optimal warning system designs and decision criteria.     

Cutting of Phragmites australis as a lake restoration technique: Productivity calculation and nutrient removal in Wuliangsuhai Lake, northern China

Reed is one of the most frequent and dominant species in wetlands all over the world, with common reed (Phragmites australis (Cav.) Trin. ex Steud.) as the most widely distributed species. In many wetlands, P. australis plays a highly ambivalent role. On the one hand, in many wetlands it purifies wastewater, provides habitat for numerous species, and is a potentially valuable raw material, while on the other hand it is an invasive species which expands aggressively, prevents fishing, blocks ditches and waterways, and builds monospecies stands. This paper uses the eutrophic reed-swamp of Wuliangsuhai Lake in Inner Mongolia, northern China, as a case to present the multiple benefits of regular reed cutting. The reed area and aboveground biomass production are calculated based on field data. Combined with data about water and reed nutrient content, the impact of reed cutting on the lake nutrient budget (N and P) is investigated. Currently, at this lake around 100,000 tons of reed are harvested in winter annually, removing 16% and 8% of the total nitrogen and phosphorus influx, respectively. Harvesting all available winter reed could increase the nutrient removal rates to 48% and 24%, respectively. We also consider the effects of summer harvesting, in which reed biomass removal could overcompensate for the nutrient influx but could potentially reduce reed regrowth.     

Why GPS makes distances bigger than they are

Global navigation satellite systems such as the Global Positioning System (GPS) is one of the most important sensors for movement analysis. GPS is widely used to record the trajectories of vehicles, animals and human beings. However, all GPS movement data are affected by both measurement and interpolation errors. In this article we show that measurement error causes a systematic bias in distances recorded with a GPS; the distance between two points recorded with a GPS is – on average – bigger than the true distance between these points. This systematic ‘overestimation of distance’ becomes relevant if the influence of interpolation error can be neglected, which in practice is the case for movement sampled at high frequencies. We provide a mathematical explanation of this phenomenon and illustrate that it functionally depends on the autocorrelation of GPS measurement error (C). We argue that C can be interpreted as a quality measure for movement data recorded with a GPS. If there is a strong autocorrelation between any two consecutive position estimates, they have very similar error. This error cancels out when average speed, distance or direction is calculated along the trajectory. Based on our theoretical findings we introduce a novel approach to determine C in real-world GPS movement data sampled at high frequencies. We apply our approach to pedestrian trajectories and car trajectories. We found that the measurement error in the data was strongly spatially and temporally autocorrelated and give a quality estimate of the data. Most importantly, our findings are not limited to GPS alone. The systematic bias and its implications are bound to occur in any movement data collected with absolute positioning if interpolation error can be neglected.