Developing Intensity-Duration-Frequency (IDF) Curves From Satellite-Based Precipitation: Methodology and Evaluation

Given the continuous advancement in the retrieval of precipitation from satellites, it is important to develop methods that incorporate satellite-based precipitation data sets in the design and planning of infrastructure. This is because in many regions around the world, in situ rainfall observations are sparse and have insufficient record length. A handful of studies examined the use of satellite-based precipitation to develop intensity-duration-frequency (IDF) curves; however, they have mostly focused on small spatial domains and relied on combining satellite-based with ground-based precipitation data sets. In this study, we explore this issue by providing a methodological framework with the potential to be applied in ungauged regions. This framework is based on accounting for the characteristics of satellite-based precipitation products, namely, adjustment of bias and transformation of areal to point rainfall. The latter method is based on previous studies on the reverse transformation (point to areal) commonly used to obtain catchment-scale IDF curves. The paper proceeds by applying this framework to develop IDF curves over the contiguous United States (CONUS); the data set used is Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks – Climate Data Record (PERSIANN-CDR). IDFs are then evaluated against National Oceanic and Atmospheric Administration (NOAA) Atlas 14 to provide a quantitative estimate of their accuracy. Results show that median errors are in the range of (17–22%), (6–12%), and (3–8%) for one-day, two-day and three-day IDFs, respectively, and return periods in the range (2–100) years. Furthermore, a considerable percentage of satellite-based IDFs lie within the confidence interval of NOAA Atlas 14

Optimization of the MALDIxin test for the rapid identification of colistin resistance in Klebsiella pneumoniae using MALDI-TOF-MS

Background. With the dissemination of carbapenemase producers, a revival of colistin was observed for the treatment of infections caused by multidrug-resistant Gram-negatives. Unfortunately, the increasing usage of colistin led to the emergence of resistance. In Klebsiella pneumoniae, colistin resistance arises through addition of L-arabinose-4N (L-Ara4N) or phosphoethanolamine (pEtN) on the native lipid A. The underlying mechanisms involve numerous chromosome-encoded genes or the plasmid-encoded phosphoethanolamine transferase MCR. Currently, detection of colistin resistance is time consuming since it still relies on MIC determination by broth microdilution. Recently, a rapid diagnostic test based on MALDI-TOF detection of modified lipid A was developed (the MALDIxin test) and tested on Escherichia coli and Acinetobacter baumannii. Objectives. Optimize the MALDIxin test for the rapid detection of colistin resistance in Klebsiella pneumoniae. Methods. This optimization consists on an additional mild-acid hydrolysis of 15 min in 1% acetic acid. The optimized method was tested on a collection of 81 clinical K. pneumoniae isolates including 49 colistin resistant strains among which 45 correspond to chromosome-encoded resistance, 3 MCR-related resistance and one isolate harbouring both mechanisms. Results. The optimized method allowed the rapid (< 30 min) identification of L-Ara4N and pEtN modified lipid A of K. pneumoniae which are known to be the real triggers of polymyxin resistance. In the same time, it discriminates between chromosome-encoded and MCR-related polymyxin resistance. Conclusions. The MALDIxin test has the potential to become an accurate tool for the rapid diagnostic of colistin resistance in clinically-relevant Gram negative bacteria