Study of star formation in RCW 106 using far infrared observations

High resolution far-infrared observations of a large area of the star forming complex RCW 106 obtained using the TIFR 1-metre balloon-borne telescope are presented. Intensity maps have been obtained simultaneously in two bands centred around 150 & 210 micron. Intensity maps have also been obtained at the 4 IRAS bands using HIRES processed IRAS data. From the 150 & 210 micron maps, reliable maps of dust temperature and optical depth have been generated. The star formation in this complex has occured in five linear subclumps. Using the map at 210 micron, which has a spatial resolution superior to that of the IRAS at 100 micron, 23 sources have been identified. The SED and luminosity of these sources have been determined using the associations wit hthe IRAS maps. Luminosity distribution of these sources has been obtained. Assuming these embedded sources to be ZAMS stars and using the mass-luminosity relation, the power law slope of the Initial Mass Function is found to be -1.73+-0.5. This index for this very young complex is about the same as that for more evolved complexes and clusters. Radiation transfer calculations in spherical geometry have been undertaken to fit the SEDs of 13 sources with fluxes in both the TIFR and IRAS bands. From this, the r^-2 density distribution in the envelopes is ruled out. Finally, a correlation is seen between the luminosity of embedded sources and the computed dust masses of the envelopes.Comment: Accepted for publication in MNRAS (21 pages, 8 figures & 3 tables

Understanding Volumetric Water Storage in Monsoonal Wetlands of Northeastern Bangladesh

The volume of water stored in seasonal wetlands is a fundamental but difficult to measure variable for developing a physical understanding of wetland behavior. For seasonal wetlands that are a major source of water for rice and fish production, this physical understanding is key to planning for water-food security and ecosystem services. This study quantified variations in volumetric storage for the numerous seasonal wetlands of northeastern Bangladesh, locally known as “haors.” These haors receive transboundary runoff from densely vegetated and mountainous terrain in India and face persistent monsoonal cloud cover as they become full. We estimated volumetric storage for 13 haors by using extensive remote sensing data on water surface extent and elevation that was complemented with citizen-contributed gauge data. Assuming a trapezoidal bathymetry, an area-volume relationship was developed for selected haors. This relationship was assumed to be valid for extrapolating volumetric estimations over all the haors in the region. Results suggested that as haors get filled with the onset of monsoon rains, total estimated storage relative to the lowest observable level varied from 6.5 (±0.4) km3 in May to 30.9 (±2.0) km3 in July (peak of monsoon). Choosing a rectangular bathymetry can lead to 47% higher estimates compared to trapezoidal cross section. Estimating this intra-annual/interannual increase in storage is important for the region to plan water management policies that balance the human and ecosystem needs. Our analytical approach has potential for application to wetlands worldwide in light of the upcoming Surface Water and Ocean Topography (SWOT) mission

Monitoring variations in lake water storage with satellite imagery and citizen science

Despite lakes being a key part of the global water cycle and a crucial water resource, there is limited understanding of whether regional or lake‐specific factors control water storage variations in small lakes. Here, we study groups of small, unregulated lakes in North Carolina, Washington, Illinois, and Wisconsin, USA using lake level measurements gathered by citizen scientists and lake surface area measurements from optical satellite imagery. We show the lake level measurements to be highly accurate when compared to automated gauges (mean absolute error = 1.6 cm). We compare variations in lake water storage between pairs of lakes within these four states. On average, water storage variations in lake pairs across all study regions are moderately positively correlated (ρ = 0.49) with substantial spread in the degree of correlation. The distance between lake pairs and the extent to which their changes in volume are correlated show a weak but statistically significant negative relationship. Our results indicate that, on regional scales, distance is not a primary factor governing lake water storage patterns, which suggests that other, perhaps lakes‐specific, factors must also play important roles

Geographic information systems visualization of wind farm operational data to inform maintenance and planning discussions

As utility scale wind farms age, maintenance and contingency planning become increasingly important. Decisions about when and how to repair or replace major turbine components can critically influence profitability. Condition monitoring and prognostic reliability modelling are sometimes used to support these decision-making processes. These often resource intensive, sophisticated techniques are frequently administered by third parties and can be black boxes to wind farm stakeholders. Early experience from the YR21 Investment Decision Support Program has highlighted the importance of broad engagement across wind farm teams in maintenance and planning discussions. The utilization of geographic information systems to illustrate data trends across wind farms proved to be a valuable tool in fostering fundamental understanding of an operation’s signature performance characteristics. This graphical representation of the farm provides a useful visualization of the operation’s best and worst performers in terms of power produced, wind speeds experienced, total revolutions, or highest gear box temperature. These transparent representations of the data represent valuable starting points for discussion of performance or potential maintenance issues across farms. In some cases, it can reveal unexpected trends that may raise bigger questions about how the farm is operating in general. Finally, these simple figures can serve as complementary inputs to larger, more complex data-driven decision systems. Geographic information system plots are presented for three wind farms to demonstrate the potential utility in simple, transparent, and accessible data visualization