Factors Controlling the Hydraulic Efficiency of Green Roofs in the Metropolitan Area of Milan (Italy)

Green roofs (GRs) are considered sustainable solutions for the adaptation of urban water management to climate change. The use of GRs is particularly promising in urban environments like the Metropolitan Area of Milan, the most urbanized area in Italy. In this work, we evaluated the subsurface runoff coefficient at the event-time scale, for more than one year of observations, of 68 small-scale test beds comprising different configurations of green roofs (e.g., different vegetations, types and depths of growing media, and different slopes) installed in the Metropolitan Area of Milan. The objectives of this study are three-fold. Firstly, the controlling factors of the hydraulic have been assessed for efficiency. We calculated a mean drainage flow rate of 51%, finding that growing media play a significant role in determining the drainage flow during the spring, at the beginning of the vegetative period. During this season, water retention in fertilized beds increases significantly. At the beginning of the summer, the vegetation cover is able to significantly reduce the drainage flow, playing an even more crucial role with respect to the growing medium material. However, we found that the vegetation type (grass field and Sedum) does not play a significant role in the retention processes. Secondly, the delay of the peak flow rate was determined. We found a precipitation peak delay from 1 to 2 h, which would be sufficient to guarantee environmental benefits for urban drainage. Finally, the factors controlling the hydraulic efficiency of GRs for individual precipitation events were assessed. We found that soil moisture and cumulated precipitation are both significant factors determining the drainage flow rate. In conclusion, we point out that soil moisture is one of the main parameters characterizing GR drainage and should be further considered in future research efforts devoted to the analysis of GR performance.

Distinguishing Time Scales of Katabatic Flow in Complex Terrain

To examine spatial and temporal scales of katabatic flow, a distributed temperature sensing (DTS) optical fiber was deployed 2 km down a mild slope irregularly interrupted by small-scale drainage features as part of the Mountain Terrain Atmospheric Modeling and Observation (MATERHORN) experiment conducted at the U.S. Army Dugway Proving Ground, Utah. The fiber was suspended at two heights near the surface, enabling measurement of variations in lapse rate near the surface at meter-scale spatial resolution with 1-min temporal resolution. Experimental results derived from the DTS and tower-mounted instrumentation indicate that airflow through small-scale drainage features regulated the local cooling rate whereas topographic slope and distance along the drainage strongly influenced the larger-scale cooling rate. Empirical results indicate that local cooling rate decays exponentially after local sunset and basin-wide cooling rate decreases linearly with time. The difference in the functional form for cooling rate between local and basin-wide scales suggests that small-scale features have faster timescales that manifests most strongly shortly after local sunset. More generally, partitioning drainage flow by scale provides insight and a methodology for improved understanding of drainage flow in complex terrain.

The Application of Artificial Neural Network to Predicting the Drainage from Waste Rock Storages

Reliable prediction of drainage flow rate and drainage chemistry is essential to the treatment of drainage from waste rock storages at mine sites. The traditional predictive models require simplification and assumption of geo-bio-chemical processes followed by intensive characterization, and sometimes lead to poor prediction accuracy. In the big data era, various sensors are installed in field to constantly monitor mine sites, which enables machine learning to utilize the generated monitoring data and study the underlying pattern behind the data. This chapter describes an approach to use artificial neural network to predict the drainage flow rate and drainage chemistry based on weather monitoring data collected at mine sites. The advantage of this approach is that generally no additional characterization are required to make prediction because the relevant geo-bio-chemical mechanisms are embedded naturally in the monitoring data, which can be captured through machine learning process.

IDENTIFIKASI POLA ALIRAN DI SEKITAR DAERAH GENANGAN BANJIR

Johan Pahlawan Sub-district especially Leuhan Village and Blang Beurandang Village is a residential area that was hit by a flood inundation. Rainfall intensity and flow pattern conditions cause inundation. Puddles result in physical damage to home components and cause a number of losses, with varying levels of inundation and water levels. This analysis study was conducted with the aim of identifying the condition of the pattern of drainage flow around the flood inundation area. The research approach is in the form of quantitative and qualitative research. Identification results obtained: The pattern of land flow and drainage in the form of flow direction is in accordance with the topographic conditions of the study area, with channel conditions such as shrubs, constriction and at certain points with conditions of low contoured areas so that inundation is prone to improvements such as maintenance activities and repair.

The invention relates to a method and a device for detecting the drainage flow rate of a hidden water tank

The invention discloses a method and a device for detecting the drainage flow rate of a hidden water tank. The method of real-time communication between electronic scale load-bearing device and profinet is proposed to realize the detection of drainage flow. The device consists of electronic scale load-bearing device, high-speed electronic scale acquisition module, PLC lower computer, touch screen man-machine interaction layer and so on. The device achieves fast detection response time and ensures sample integrity. It also avoid the problem of slow response of the input type liquid level sensor and inconvenient installation of magnetostrictive liquid level sensor.