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Messages - Pankaj Dey

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31
Floods, wildfires, heatwaves and droughts often result from a combination of interacting physical processes across multiple spatial and temporal scales. The combination of processes (climate drivers and hazards) leading to a significant impact is referred to as a ‘compound event’. Traditional risk assessment methods typically only consider one driver and/or hazard at a time, potentially leading to underestimation of risk, as the processes that cause extreme events often interact and are spatially and/or temporally dependent. Here we show how a better understanding of compound events may improve projections of potential high-impact events, and can provide a bridge between climate scientists, engineers, social scientists, impact modellers and decision-makers, who need to work closely together to understand these complex events.


Link: https://www.nature.com/articles/s41558-018-0156-3

32
Speaker: Dr. Dennis Helder
 
 
Time: 18 May 2018 (Friday) @ 3:00 pm
 
Venue: DESE Auditorium , IISc
 
 
Abstract:
 
Radiometric calibration of optical remote sensing satellite sensors is a necessary step so that the data acquired by these systems can be placed on an absolute scale of radiance or reflectance. This fundamental step converts the raw digital numbers recorded by the satellite into physical units and thus turns a ‘pretty picture’ into a scientific data set. There are two basic approaches to performing radiometric calibration. The first is to design calibration systems into the instrument itself. Often this is done by incorporating diffuser panels and/or lamps into the instrument. However, this approach adds significant additional cost and weight. Thus, many satellites do not incorporate such onboard systems. The second approach is most often termed ‘vicarious calibration’ and it involves using information acquired from a distance such as information from the earth imagery itself. The South Dakota State University Image Processing Laboratory has specialized in vicarious calibration of remote sensing imagery for over 25 years. In this presentation the fundamental concepts of vicarious calibration will be presented, examples of the surface reflectance method and the pseudo invariant calibration site (PICS) method will be provided, and application of these methods to the Landsat image archive, from 1972 to the present, will be given.
 
 
About Speaker:
 
 
Dr. Dennis Helder has been involved with the characterization and calibration of space borne and airborne  remote sensing imaging systems for over 25 years. Initial work focused on characterization and removal of radiometric artifacts of the Landsat TM and MSS sensors. More recent work has emphasized development of vicarious radiometric calibration approaches for a variety of optical remote sensing systems as well as on-orbit point spread function estimation. Dr. Helder has served on several NASA and USGS EROS science teams including Landsat 7, Landsat 8, and EO-1. He is currently Associate Dean for Engineering Research and Distinguished Professor of Electrical Engineering at South Dakota State University and is also on detail to USGS EROS as director of the EROS CalVal Center of Excellence.
 

33
JASP is statistically inclusive as it offers both frequentist and Bayesian analysis methods. Indeed, the primary motivation for JASP is to make it easier for statistical practitioners to conduct Bayesian analyses. We firmly believe that Bayesian statistics deserves to be applied more often and more widely than it is today, and that there is more to statistical inference than the frequentist p-value. A pragmatist may argue that –irrespective of one’s statistical convictions– it is prudent to report the results from both paradigms; when the results point in the same direction, this bolsters one’s confidence in the conclusions, but when the results are in blatant contradiction, this will weaken one’s confidence.


Homepage: https://jasp-stats.org/


Youtube video link: https://youtu.be/HxqB7CUA-XI

34
We are recruiting a new postdoc for an exciting position to assess the role of dams in delivering improved food security in developing countries as part of the FutureDams research centre led by the University of Manchester. The selected candidate will use remote sensing, field datasets, and crop models to evaluate impacts of historic and future dam developments on agricultural productivity and livelihoods, and investigate trade-offs between agriculture and other water users (e.g. hydropower, environment). Research activities will focus on three primary case study river basins: the Nile and Volta basins in Africa, and the Salween River basin in Myanmar. The position is available for a period of 3 years starting from summer 2018 or as soon as possible thereafter. Further details and the project application form can be accessed by clicking the buttons below.


Link: http://fosterlab.weebly.com/join-the-group.html

35
Demonstrating the “unit hydrograph” and flow routing processes involving active student participation – a university lecture experiment

 The unit hydrograph (UH) has been one of the most widely employed hydrological modelling techniques to predict rainfall–runoff behaviour of hydrological catchments, and is still used to this day. Its concept is based on the idea that a unit of effective precipitation per time unit (e.g. mm h−1) will always lead to a specific catchment response in runoff. Given its relevance, the UH is an important topic that is addressed in most (engineering) hydrology courses at all academic levels. While the principles of the UH seem to be simple and easy to understand, teaching experiences in the past suggest strong difficulties in students' perception of the UH theory and application. In order to facilitate a deeper understanding of the theory and application of the UH for students, we developed a simple and cheap lecture theatre experiment which involved active student participation. The seating of the students in the lecture theatre represented the hydrological catchment in its size and form. A set of plastic balls, prepared with a piece of magnetic strip to be tacked to any white/black board, each represented a unit amount of effective precipitation. The balls are evenly distributed over the lecture theatre and routed by some given rules down the catchment to the catchment outlet, where the resulting hydrograph is monitored and illustrated at the black/white board. The experiment allowed an illustration of the underlying principles of the UH, including stationarity, linearity, and superposition of the generated runoff and subsequent routing. In addition, some variations of the experimental setup extended the UH concept to demonstrate the impact of elevation, different runoff regimes, and non-uniform precipitation events on the resulting hydrograph. In summary, our own experience in the classroom, a first set of student exams, as well as student feedback and formal evaluation suggest that the integration of such an experiment deepened the learning experience by active participation. The experiment also initialized a more experienced based discussion of the theory and assumptions behind the UH. Finally, the experiment was a welcome break within a 3 h lecture setting, and great fun to prepare and run.


Link: https://www.hydrol-earth-syst-sci.net/22/2607/2018/hess-22-2607-2018.pdf

36
The recent levelling of global mean temperatures after the late 1990s, the so-called global warming hiatus or slowdown, ignited a surge of scientific interest into natural global mean surface temperature variability, observed temperature biases, and climate communication, but many questions remain about how these findings relate to variations in more societally relevant temperature extremes. Here we show that both summertime warm and wintertime cold extreme occurrences increased over land during the so-called hiatus period, and that these increases occurred for distinct reasons. The increase in cold extremes is associated with an atmospheric circulation pattern resembling the warm Arctic-cold continents pattern, whereas the increase in warm extremes is tied to a pattern of sea surface temperatures resembling the Atlantic Multidecadal Oscillation. These findings indicate that large-scale factors responsible for the most societally relevant temperature variations over continents are distinct from those of global mean surface temperature.


Link: https://www.nature.com/articles/s41467-018-04040-y?WT.ec_id=NCOMMS-20180502&spMailingID=56530111&spUserID=MjcxODE2NjM3OTkyS0&spJobID=1400280623&spReportId=MTQwMDI4MDYyMwS2#Sec21

37
At the EGU General Assembly 2018 in Vienna, “Hydroinformatics for hydrology” short course (SC) was run for the fourth time. The previous themes of the SC were data-driven and hybrid techniques, data assimilation, and geostatistical modelling. And this year the focus was extreme value modelling. Participants of the SC were given a state-of-the-science overview of different aspects in extreme value analysis along with relevant case studies. Available R functions for extreme value analysis were also introduced. Thanks to Hugo’s excellent lecture, we now know common issues and pitfalls in using extreme value models (i.e. modelling choices and assumptions). We would like to thank Dr. Hugo Winterfrom EDF Energy for delivering the lecture. You can find his lecture slides (and exercises) in the attachments:




38
A postdoc position is immediately available in the area of hydrological modeling. We are particularly interested in those who have interests and experience in modeling large scale water and nutrient cycles because of the climate changes.

Appointment is initially for one year, with subsequent years possible pending on availability of funds and performance.
Salary is competitive and includes fringe benefits.

Applicants should send an inquiry with a cv to Professor Chen Zhu (che...@indiana.edu).

You can also visit our web site for our research activities at www.indiana.edu/~hydrogeo.

Indiana University is an Equal Opportunity/Affirmative Action employer.
Women and minorities are especially encouraged to apply.

39
Based on the earlier post, a meeting was organised at EGU 2018 to finalise and categorize the problems into three status: gold, silver and out.


The following are the excerpts of the meeting held at EGU 2018.

We had excellent meetings on Friday 13 April 2018 (Splinter meeting at EGU in Vienna) and on Saturday 14 April (Vienna Catchment Symposium at TU Wien) with about 60 and 110 people attending, respectively.

These are the questions resulting from the LinkedIn discussion, the Friday Splinter meeting and additional email contributions received before Friday.
https://iahs.info/uploads/Unsolved%20Problems%20in%20Hydrology/Questions_13_April_2018_edited1613.pdf

On Saturday we had three rounds of discussions in four break out groups and one final plenary discussion. In each round we discussed the questions, merged them, split them and reworded them as needed followed by a voting on prioritising the questions. The voting was for gold/silver/bronze/remove in each of the three break out group rounds. Only the gold and silver ones were retained for the plenary with an additional round of voting (by the entire plenary) for gold, silver or removing them from the list. The idea of the process was to whittle down the 260 questions initially proposed to a more coherent and smaller set of those questions deemed most important by the participants. The process resulted in 16 gold and 29 silver questions which are posted here.
https://iahs.info/uploads/Unsolved%20Problems%20in%20Hydrology/Questions_14_April_2018_plenary.pdf

A paper drafting team (Günter Blöschl, Elena Toth, Jeff McDonnell, Gia Destouni, Antonio Chambel, Elena Volpi, Jim Kirchner, Marc Bierkens, Christine Stumpp, Christophe Cudennec, Hubert Savenije, Siva Sivapalan, Aldo Fiori) has been formed to
- check whether there are any obvious ‘holes’ in the list and propose a small number of additional questions if needed
- wordsmith the questions
- start with an initial draft of the summary paper.

The updated list of questions will be circulated among the co-authors (those who have substantially contributed to the process which will be around 160 scientists) with a final voting on the list, and the co-authors will also be asked to provide suggestions for any changes to the paper draft.

The plan is to submit the paper to HSJ.

Many thanks again for all your contributions


Günter

Please find the attached pdf file for the document.

40
Abstract. This article extends a previous study Seneviratne et al. (2016) to provide regional analyses of changes in climate extremes as a function of projected changes in global mean temperature. We introduce the DROUGHT-HEAT Regional Climate Atlas, an interactive tool to analyse and display a range of well-established climate extremes and water-cycle indices and their changes as a function of global warming. These projections are based on simulations from the fifth phase of the Coupled Model Intercomparison Project (CMIP5). A selection of example results are presented here, but users can visualize specific indices of interest using the online tool. This implementation enables a direct assessment of regional climate changes associated with global mean temperature targets, such as the 2 and 1.5° limits agreed within the 2015 Paris Agreement.


Link to paper: https://www.geosci-model-dev.net/10/3609/2017/


Link to interactive ploting wen interface: http://www.drought-heat.ethz.ch/atlas/

41
Hydrological sciences / Using R in Hydrology - EGU2018 Short Course
« on: April 22, 2018, 02:37:21 PM »
This was a short course conducted during EGU this year. The course was divided into six workflows as follows:


Introduction to the short course - Louise Slater
  • Accessing hydrological data using web APIs (a demo of the rnrfa package) - Claudia Vitolo
  • Processing, modelling and visualising hydrological data in R (tidyverse; piping, mapping and nesting) - Alexander Hurley
  • Extracting netCDF climate data for hydrological analyses (reading and visualising gridded data) - Louise Slater
  • Hydrological modelling and teaching modelling (airGR and airGRteaching) - Guillaume Thirel
  • Typical hydrological tasks in R (List columns, Leaflet and coordinate transformation, Open Street Maps) - Tobias Gauster

Please follow the github link to access the necessary materials: https://github.com/hydrosoc/rhydro_EGU18/




42
Streamflow data is highly relevant for a variety of socio-economic as well as ecological analyses or applications, but a high-resolution global streamflow dataset is yet lacking. We created FLO1K, a consistent streamflow dataset at a resolution of 30 arc seconds (~1 km) and global coverage. FLO1K comprises mean, maximum and minimum annual flow for each year in the period 1960–2015, provided as spatially continuous gridded layers. We mapped streamflow by means of artificial neural networks (ANNs) regression. An ensemble of ANNs were fitted on monthly streamflow observations from 6600 monitoring stations worldwide, i.e., minimum and maximum annual flows represent the lowest and highest mean monthly flows for a given year. As covariates we used the upstream-catchment physiography (area, surface slope, elevation) and year-specific climatic variables (precipitation, temperature, potential evapotranspiration, aridity index and seasonality indices). Confronting the maps with independent data indicated good agreement (R2 values up to 91%). FLO1K delivers essential data for freshwater ecology and water resources analyses at a global scale and yet high spatial resolution.


Link to the paper: https://www.nature.com/articles/sdata201852.pdf


Link to data shared in figshare: https://figshare.com/collections/FLO1K_global_maps_of_mean_maximum_and_minimum_annual_streamflow_at_1_km_resolution_from_1960_through_2015/3890224

43
Regression techniques are one of the most popular statistical techniques used for predictive modeling and data mining tasks. On average, analytics professionals know only 2-3 types of regression which are commonly used in real world. They are linear and logistic regression. But the fact is there are more than 10 types of regression algorithms designed for various types of analysis. Each type has its own significance. Every analyst must know which form of regression to use depending on type of data and distribution.


Please find the link: https://www.listendata.com/2018/03/regression-analysis.html

44
Announcements / 2018 Water Travel Award
« on: March 26, 2018, 06:32:20 PM »
We are pleased to announce that the “2018 Water Travel Award” is now open to receive applications from postdoctoral and Ph.D. researchers who plan to participate in an international conference during July–December 2018. The award will consist of three prizes each of 800 CHF(Swiss Francs).
The awardee will be determined after assessment by an evaluation committee, chaired by the Editor-in-Chief Prof. Arjen Y. Hoekstra, and also includes Prof. John W. Day, Prof. Kwok-wing Chau, Prof. Roy C. Sidle, Prof. Laodong Guo and Prof. Thilo Hofmann.
Candidates should fulfil the following criteria:Postdoctoral fellows (within three years of receiving their Ph.D.) or Ph.D. students undertaking water resources research.
  • They must present their own, original work as a poster or oral presentation at the conference for which the travel award application is being made.
Applicants are required to submit the following documents (Please provide the entire package in a PDF file):Outline of current and future work (1 page).
  • CV, including a complete list of publications.
  • Details of the conference to be attended, together with a copy of the abstract and acceptance letter or anticipated date of decision.
  • Current grant funding and travel budget, if any, and why the support of this award would be beneficial.
  • A letter of recommendation from their supervisor, research director or department head (1 page).
Please apply by clicking the button above before 30 April 2018. The decision will be announced in June 2018.
Link :http://www.mdpi.com/journal/water/awards

45
A collection of statistical tools for objective (non-supervised) applications of the Regional Frequency Analysis methods in hydrology. The package refers to the index-value method and, more precisely, helps the hydrologist to: (1) regionalize the index-value; (2) form homogeneous regions with similar growth curves; (3) fit distribution functions to the empirical regional growth curves.


Link to the reference manual:https://cran.r-project.org/web/packages/nsRFA/nsRFA.pdf

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