Wednesday, October 18, 2017

Using Colorblind friendly Plots

Brought to my attention by Michele Bottazzi. I rarely think to this. Instead it is important. Please refers to this Brian Connelly post:

Click on the figure to be redirected. BTW, this was the 500th post!ūüéČ

Tuesday, October 17, 2017

TranspirAction

This post contains the presentation given by Michele Bottazzi. His presentation look forward to dig into the forecasting of transpiration from plants (and evaporation from soils) through concentrated parameters modelling. His findings will have a counterpart in our JGrass-NewAGE system.
The figure illustrate his willing to find a new, modern, way to scale up leaf theories to canopy and landscape. The starting point is one recent work by Schymanski and Or but it will go, hopefully, far beyond it. Click on the Figure to access his presentation.

An ML based meta modelling infrastructure for environmental meodels

This is the presentation Francesco gave for his admission to the third year of Ph.D. studies. He summarizes his work done so far and foresees his work during the next year.
Francesco's work is a keystone of the work in our group, since he sustains most of informatics and pur commitment to OMS3. Besides of this two are his major achievements: the building of the Ne3 infrastructure (an infrastructure inside an infrastructure!)  which allows an enormous flexibility to our modelling, and the new road opened towards modeling discharges through machine learning techniques. But there are other connections he opens that are visible through his talk. Please clisk on the figure to access the presentation.

Sunday, October 15, 2017

A few topics for a Master thesis in Hydrology

After the series about Meledrio I thought that each one of the post actually identifies at least one Thesis topic:

Actually, each one of them could be material for more than one Thesis, depending the direction we want to take. All the Theses topics assume that JGrass-NewAGE is the tool used for investigations.
Actually there are some spinoff of those topics:
  • Using machine learning to set part of model inputs and/or 
  • Doing hydrological modeling with machine learning
  • Preprocessing and treating (via Python or Java) satellite data as input of JGrass-NewAGE (a systematisation of some work made by Wuletawu Abera on Posina cacthment and/or Blue Nile)
  • Implementation of the new version of JGrass-NewAGE on val di Sole
  • Using satellite data, besides geometric features, to extract river networks
  • Snow models intercomparison (GEOtop and those in JGrass-NewAGE, with reference to work done by Stefano Tasin and Gabriele Massera) 
Other to other Hydrological topics:
  • Mars (also here) and planetary Hydrology (with GEOtop or some of its evolutions which account for different temperature ranges and other fluid fluxes)
  • Copying with Evapotranspiration and irrigation at various scales
  • Copying the carbon cycle to the hydrological cycle (either in GEOtop or in JGrass-NewAGE)
Other possible topics regarding water management:
  • Hypothesis on the management of reservoir for optimal water management in river Adige.
  • Managing Urban Waters Complexity
Other possible topics regards, on a more theoretical (mathematical-physical) side:
On the side of informatics:
For who wants to work with us on the Master thesis, the rules to follow are those for Ph.D. students, even if to a minor extent. See here:

Saturday, October 14, 2017

Meledrio, or a simple reflection on hydrological modelling - Part V

Another question related to discharges is, obviously their measure. Is discharge measure correct ? Is the stage-discharge relation reliable ? Why do not give intervals of confidence for the measures ? Yesterday, a colleague of mine, told me. A measure without an error band is not a measure. That is, obviously an issue. But today reflection is on a different question.  We have a record of discharges. It could look like this (forgive me the twisted lines):
Actually, what we imagine is the following:
I.e. we think it is all water. However, a little of reflection should make us think that, a more realistic picture is:
Meaning that part of the discharge volume is actually sediment transported around. This open the issue on how to quantify it. Figure enlighten than during some floods, actually the sediment could be a consistent part of the volume, and, if we are talking of small mountain catchments like Meledrio, it could be the major part of the discharge. Hydraulics and sediment transport, so far, was used separately from hydrology and hydrology separated from sediment transport, but what people see is both of them (water and sediment).
This actually could be not enough. The real picture could be, actually like this:
Where we have some darker water. The mass transport phenomena, in fact, could affect part of the basin during intense storms, but the liquid water could not be able to sustain all this transport. Aronne Armanini suggested to me that, in that case, debris flow can start and be stopped somewhere inside of the basin. Te water content they have, instead, could be equally likely released to the streams and boosting furthermore the flood.  Isn't it interesting ? Who said that modeling discharges is an assessed problem ?

Friday, October 13, 2017

Meledrio, or a simple reflection on hydrological modelling - Part IV

An issue that often is risen is about the complexity of models. Assuming the same Meledrio basin, which is the model we can think to be the simpler for getting quantitatively the water budget ?
The null-null hypothesis model is obviously using the past averages to get the future. Operatively:
  • Get precipitation and discharge 
  • Precipitation is  separated by temperature (T) in rainfall (T>0) and snowfall. Satellite data can be used for the separation. 
  • Take their average (maybe monthly average)
  • Take their difference. 
  • Assume that the difference is  50% recharge and 50% ET

My null hypothesis is the following. I kept it simple but not too simple:
  • Precipitation, discharge and temperature are the measured data
  • Their time series are split into 3 parts (one for calibration, one for selection, see below, and one for validation)
  • Precipitation is measured and separated by temperature (T) in rainfall (T>0) and snowfall (T<0). Satellite data can be used alternatively for the separation. These variable can be made spatial by using a Kriging (or
  • Infiltration is estimated by SCS-CN method. SCS parameters  interval are set according to soil cover, by distinguishing it in qualitatively 4 classes of CN (high infiltrability, medium high, medium low, low). In each subregion, identified by soil cover, CN is let vary in the range allowed by its classification. Soil needs to have a maximum storage capacity (see also ET below). Once this has been exceeded water goes to runoff. 
  • Discharge is modeled as a set of parallel linear reservoirs. One for HRU (Hydrologic Response Unit). 
  • Total discharge is simply the summation of all the discharges of the HRUs.
  • CN and mean residence time (the parameter in linear reservoirs) are calibrated to reproduce total discharge (so a calibrator must be available)
  • A set of optimal parameters is selected, let say the most 1% best performing
  • Among those the best performing, the one 1%  performing against selection phase data  are kept (at least 10^4 values then, but possibly at least 10^5).
  • Precipitation that does not infiltrates is separated into evapotranspiration, ET, and recharge.
  •  ET is estimated with Priestly-Taylor (so you need an estimator for radiation) corrected by a stress factor, linearly proportional to the water storage content. PT alpha coefficient is taken at its standard value, i.e 1.28
  • What is not ET is recharge.  Please notice that there is a feedback between recharge and ET because of the stress factor. 
  • If present, snow is modeled through Regina Hock model (paper here), in case, calibrated trough MODIS.
The Petri Net representation of the model (no snow) can be figured out to be as follows:

The setup this model, therefore is not so simple, indeed, but not overwhelmingly complicate.

Any other model has to do better than this. If successful, it become hp 1. 
A related question is how we measure goodness of fitting and if we can distinguish the performances of one model from another one. That is, obviously, another issue.

Thursday, October 12, 2017

Meledrio, or a simple reflection on hydrological modelling - Part III

Well, this is not exactly Meledrio.  It starts a little downstream of it. In fact, we do not have discharge data in Meledrio (so far) and we want to anchor our analysis to something measured. So we have a gauge station in Mal√®. A gauge station for who does not know it, measure just water levels (stages) and them convert to water discharge through a stage-discharge relation (see USGS here). Anyway, a sample signal is here:
The orange lines represent discharge simulated with one of our models (uncalibrated at this stage). The blue line is the measured discharge (meaning the measured stage after having applied an unknown stage-discharge relationship, because the guys who should did not gave us it). But look at little more closer:
We could have provided a better zooming, however, the argument of discussion is: what the hell is all that noise in the measured signal ? It is natural ? It is error of measurements ? Is due to some human action ? 
Having a better zoom, one could see that that signal is almost a square wave going up and in few hours, and therefore the suspected cause are humans. 
Next question: how can we calibrate the model that does not have this unknown action inside to reproduced the measured signal ?
Clearly the question is ill-posed and we should work the other way around. Can we filter out in the measured signal the effect of humans ?
Hints: we could try to analyze the measured signal first. Analyzing actually could mean, in this case, to decompose it, for instance in Fourier series or Wavelets and wipe away the square signal (a hint in hints), reproducing an "undisturbed signal" to cope with. 
Then we could probably calibrate the the model to the cleaned data. Ah! You do not know what calibration means ? This is another story.

P.S. - This is actually part of a more general problem, which is measurement treatments. Often we, naively, treat them as true values. Instead they are not and should pre-analyzed for consistency and validate before. MeteoIO is a tool that answers to part of the requests. But, for instance, it does not treat the specific question above.

Wednesday, October 11, 2017

Meledrio, or a simple reflection on hydrological modelling - Part II

In the previous studies made on the hydrology of Meledrio some ancillary data are produced. For instance:

Soil Use
Geo-lithology-Lithology

Usually also other maps are produced, for instance soil cover (which, in principle, could be different from soil use).  The problem I have is that, usually, I do not know what to do with these data.  There are actually two questions related to maps of such kind.
  • The first is,  are these characteristics are part of the model (see, for instance, the previous post)?. 
  • The second is, if the models somewhat contains a quantity, or a parameter,  that can be affected by the mapped characteristics, but the is not directly the characteristic,  how the parameter can be deduced ? In other words there is a (statistical) method to relate soil use to models parameters ?  
I confess that the only systematic trial to obtain this type of inference that I know are the pedotransfer functions. Whilst the concept could be exported to more general models' attributes, however they refer to very specific models that contains hydraulic conductivity or porosity as a parameter and not to other models, for instance those based on reservoirs, where hydraulic conductivity usually is not explicitly present.
Another typology of sub-models where something similar exists is the SCS-CN model.  Specific models, sometimes can contain specific conversion tables produced either by Authors than practictioners (SWAT, for instance).  In SCS-CN, the tables of soil categories are associated with values of the Curve Number parameters, and people pretend to believe that the association is reliable. But it is fiction not science.
In a time when reviewers say that modelling discharges is not enough to assess the validity of a hydrological model, at the same time they allows holes in the peer review process where papers make an unscrupulous use of the same concept.  
There is actually a whole new science branch, hydropedology, that seems devoted to the task to transform maps of soil properties into significant hydrological numbers (mine is the brutal interpretation of it, obviously hydropedology has the scope to understand, not only to predict), and I add below some relevant reference.  However, the analysis are fine and interesting food to thoughts, but the practical matter is still scanty. Probably for two facts: because normal statistical inference is not enough sophisticated to obtain important results (beyond pedotransfer functions) and because (reservoir type of) models have parameters that are too much involved to be interpreted as a simple function of a mapped characteristics. An opportunity for machine learning techniques ?

References

Lin, H., Bouma, J., Pachepsky, Y., Western, A., Thompson, J., van Genuchten, R., et al. (2006). Hydropedology: Synergistic integration of pedology and hydrology. Water Resources Research, 42(5), 2509–13. http://doi.org/10.1029/2005WR004085

Pacechepsky, Y. A., Smettem, K. R. J., Vanderborght, J., Herbst, M., Vereecken, H., & W√∂sten, J. (2004). Reality and fiction of models and data in soil hydrology (pp. 1–30).

Vereecken, H., Schenpf, A., Hoopmans, J. V., Javaux, M., Or, D., Roose, J., et al. (2016, May 13). Modeling Soil Processes: Review, Key Challenges, and New Perspectives. http://doi.org/10.2136/vzj2015.09.0131

Vereecken, H., Weynants, M., Javaux, M., Pachepsky, Y., Schaap, M. G., & Genuchten, M. T. V. (2010). Using Pedotransfer Functions to Estimate the van Genuchten–Mualem Soil Hydraulic Properties: A Review. Vadose Zone Journal, 9(4), 795–27. http://doi.org/10.2136/vzj2010.0045

Terribile, F., Coppola, A., Langella, G., Martina, M., & Basile, A. (2011). Potential and limitations of using soil mapping information to understand landscape hydrology. Hydrology and Earth System Sciences, 15(12), 3895–3933. http://doi.org/10.5194/hess-15-3895-2011

Tuesday, October 10, 2017

Meledrio, or a simple reflection on hydrological modelling - Part I

The problem is well explained by the following figure, which represents the statistics of slopes in Meledrio basin.
The overall distribution is bimodal, that make us to suspect that something was going on. In fact, this below is the Google view of the basin.
It clearly show that the hydrographical right side of the basin (on the left in figure) is the one that has steeper slopes, and the left side the one that has the lower ones. This is definitely shown by the slope map
(Please observe that the map is reversed with respect the Google view, since there we were looking to the basin from North). Different slopes, would be associated in our mind with different runoff and subsurface water velocities. This would clearly be accounted for in a model like GEOtop but not (at least explicitly) by a system of reservoirs, especially when we calibrate all the reservoirs all together. A possible partition of the basin in the Jgrass-NewAGE system is represented below
Because the single Hydrologic Response Units are mostly on one side of the catchment, they could be said to be in a area which is homogeneous from the point of view of slope statistics. Therefore, when we treat it as a collection of reservoirs, in principle we could parameterise them differently, according to their slope. In practice, however, we do not have enough measurements to be able to do this separate calibration and we look at the basin homogeneously.  Are we not missing something ?
Well, we are. The first thinking would be to try to add to our reservoir the knowledge gained from geomorphology, and assume that the mean travel time, or some relevant parameter connected to it, depends proportionally to (mean) slope (or some of its power) and inversely to the distance water has to across to get out of the HRU. This is obviously possible, and maybe we could easily try it.
In general, however,  hydrologists who are not stupid, do not care of it. Why ? The reasons can be that our assumption that slopes count is blurred by the heterogeneity of the other factors that concur to form the hydrologic response. However, the magnitude of the heterogeneity can be different at different scales and could be really nice to do some investigations in this direction.

Friday, October 6, 2017

SteepStreams preliminary Hydrological works

This contains the talk given at the 2017 meeting of the SteepStreams ERANET project. It is assumed to talk about the hydrological cycle of the Noce river in Val di Sole valley (Trentino, Italy). It is a preliminary view of what we are going to do in the project and does not pretend to present particularly deep results. However, it could give some interesting hints on methodology.
https://www.slideshare.net/GEOFRAMEcafe/lisbon-talk-for-steepstreams

Clicking on the figure, you can access the presentation.  Here below you find also a more detailed summary with links of material about the Meledrio basin, one of the experimental catchments used in the project.
As above, clicking on the figure, you can access the presentation.

Friday, September 29, 2017

Google Earth Engine

If I would say it all, I would prefer to have a non profit organisation financed by states doing it. However I cannot deny that the project is fascinating and offers (but I have to explore it) interesting possibilities. I am talking of the Google Earth Engine of which I came to know few hours ago.
Here you can watch to a YouTube video talking about the project:


The page of the system is: https://earthengine.google.com/
Having your opinions, thoughts, impressions of use, would be an interesting feedback.

Grids: Notes for an implementation

This contains some hints and discussions about how to implement Grids  (that I learned to call CW-Complexes) in a Object Oriented language. Specifically the discussion is made with Java in mind, but obviously, not limited to it.  These slides do not contain very much bibliography and are, by far, not a complete treatment of the subject. They hope to be, however, some useful "food for thought" to start with.

Clicking on the above figure you'll be redirected to the presentation that contains the seeding for a deployment, at least in our overall system.

Tuesday, September 19, 2017

Evaluation of Dr. *** work and research. For getting tenure

It often happens that an Academic is asked to assess his/her peer work. This below is an example of one letter that I made recently. However, in boldface I put comments in a less traditional language that I think would give more insight with respect to the letter I actually wrote both to people who judge the researcher. Here you find it below:

The short answer to your Institution request is: there is no doubt that Dr. *** deserves to get his/her tenured position, s/he is one of the best in the world in what s/he does.

C: The short answer is: this man/woman is damned good. S/he is far above the average and you would be stupid not to keep him/her.

The long assessment is easy too. My own research work intersects very much with Dr. ***'s one. So I came to know and follow her/his production since ten years ago. Her/His paper are among those I cited more frequently in my recent research and s/he is one of the two or three researchers younger than me that I believe it is necessary to follow when working on hydrological modelling.

C: I do not need to read her/his papers. I already read and frequently cited her/him. So: s/he is good. S/he regularly publish just on the best journals. S/he has a rate of citation slightly than mine. So, maybe s/he is better than me. Stop. 

S/he also publish regularly with some of the best researchers in the field and this does not usually happen to everyone.

C: S/he is well connected. The group s/he frequents is extremely good but tends to be self-referential. This exposes her/him to the threat to follow the main stream (which helps in publishing) and not be a paradigms breaker (which could be hard to sustain). However, if s/he is smart, as I believe, s/he will avoid the pitfalls of situation.

Finally her/his DUPER environment is a milestone in recent literature.

C: Her/his framework is damned good. It is one of the main contenders of mine. If I would be a super rampant guy, I would try to obstacle it. But I am a professor (sigh).

It happens, obviously, that I disagree on some details of her/his research, but this is matter of normal dialectics between peers.

C: S/he made some choices different from mine and sustains them with some statements that I judge debatable. But respect to the shit I see around there is by far no competition. 

From the recent papers s/he chose for evaluation, I could see that s/he also enlarged her/his view on using Bayesian techniques for estimating model’s parameters.

C: S/he is able to understand where the fashionable stuff is. This attitude does not produce science by itself but for sure is one of the characteristics that good Academics must have at least a bit (sometimes to avoid to follow fashionable stuff).

His/Her approach is sophisticate and requires certainly some deepening from myself, but I could appreciate its novelty.

C: The last paper is really technical and if s/he insists too much in this direction s/he can fall into hydrological matematistry

Whilst her/his initial production reflects also %%%% view of the matter, it is quite clear now what is Dr. *** own contribution and evolution.

C: Her/his former and influential boss quite determined her/his initial research, but s/he seems having coming out from her/his boss old fashionable approach, which was not up-to-date and could have brought her/him to produce crappy stuff. Which was not. 


To summarise, when s/he writes: "My research areas in catchment modelling can be broadly classified as: (1) the development of flexible models,which provide the building blocks for the construction of models, (2) the formulation of guidelines for model development, and (3) the use of models to interpret catchment behaviour and to produce reliable predictions. Through these research areas I have contributed to important developments in hydrological sciences in the past years, such as the use of models for hypothesis testing, the incorporation of experimental knowledge inthe modelling process, and the understanding of large scale hydrological processes and their controls.”, s/he give an image of her/himself that I fully share and think is appropriate.

C: S/he knows what s/he is and does. S/he is ready for his role. 

S/he individuates three areas of progress for his research: a) Flexible models development; b) Theory of (hydrological) models developments; c) Understanding and prediction of catchment behavior.

C: This intersects with my activities, that’s why I reformulated the name of her/his second area of interest. My, I think, is more appropriate. 

Recently there was, among many colleagues, the idea that the topics of surface hydrology were mature and that research has to move to hybrid fields like socio-hydrology, eco-hydrology (with an accent to ecology more than hydrology), ecosystem services and so on.

C: Most of colleagues, even gifted ones, tends to give for granted was is actually not (at all).

With respect to these new, certainly exciting directions, the focus of Dr. *** seems quite traditional. However, I fully approve it. The kind of research s/he is pursuing is fundamental and necessary after years of blown dilettantism that has relevant consequences in research and practice.

C: With respect to these topics most colleagues are either wrong or superficial. (Someone has to use these occasion to push out his frustration). 

Conclusions and extension obtained from ill-conceived concepts, improperly used models, and lack of hypothesis testing brings to wrong interpretations of hydrological facts and can have negative consequences on engineering applications and cause the choice of wrong policies.

C: They use wrong findings based on misconceptions and move to new subfields with wrong information. GIGO

Dr. *** work is important and its importance is going to become more and more clear in the next years. Hopefully just a few model infrastructures will emerge from the present fragmentation, and I believe the one from the evolving work of Dr. *** will be in the group.

C: Just a few framework will survive when people finally will understand the limits of hydrological dilettantism. Possibly the work of this researcher will survive and for sure, it will do for the next decade.

Probably, If I would be her/him, I would try to broaden a little the perspective including, besides the hydrologic response, the whole set of hydrological processes that concern catchments’ budget more seriously, and, in particular, evapotranspiration that, in some environments covers even sixty per cent of the water budget.

C: Engineers, even some ecohydrologists, are obsessed with discharges. These are just a part of the game. Future frameworks have to play the full game.

I would also devote some attention to the approach with travel time distributions which could open new perspectives in modeling of nutrients and pollutants, a field which Dr. *** already came across.

C: S/he forget some fundamental aspects concerning her/his own area of interest. S/he should not.

Finally, I have no doubt that Dr. *** will continue to improve and bring great contributions to your Institution.

C: I criticize her/him as I do with those I really like. S/he is a good person. Everybody can work with her/him and have benefits. They know that they want to keep her/him and I appreciate it. This will made her/him more free and more brave.

P.S. - They keep him/her

Wednesday, September 13, 2017

A smooth introduction to some Algebraic Topology topics

Since the previous post on Grids touched some topics on algebraic topology, I  selected a few sites where I found some interesting information from our point of view that can help the reading of the previous slides and, in general, of the references already presented.

I do not share many of Tonti's opinions, but some of his talks and books are, indeed, enlightening.

Monday, September 11, 2017

Meshes, Grids, CW-Complexes

Representation of space (and time) is a necessary step to implement any Physics. However, the topic is seldom faced with the appropriate generality, and this reflects into implementations in softwares that do not have a general structure. This is the rational for talking here about meshes or grids.
From a quick view of the material found in literature, it appears that a lot of work has been done, by few people (group). There are at least two pathways to follow. The first is the Ugrid mesh specification. We can describe it as the classification work of mesh by power users, i.e. people who use meshes for describing (especially environmental) numerical problems. Their work is concentrated on semantics and explaining what the mesh are,  with the scope to insert them in NetCDF, a self explaining file format conceived to contain environmental data.
The second approach, in Berti (2000) starts from more fundamental mathematical work which is also used in Heinzl (2007, but referring to the paper Heinzl, 2011, could be convenient).
In general, the first two chapters of Berti’s dissertation are a must-to-read for those who deals with scientific computing.
A subsequent number of papers cover two topics: how to store mesh in databases and how to give to these structures the right flexibility to be parallelized. Interestingly some of the mathematical work actually flowed into the creation of C++ libraries, in particular the GRAL libraries, developed by Berti himself.

https://www.slideshare.net/secret/2TufpeFQeb62FR

Browsing around, mesh are rigorously defined in Algebraic Topology (e.g. Hatcher, 2001) and this was  recognized in various papers, since the sixties (e.g. Branin, 1966, and references therein). A general discussion, which involve the nature of Physical laws, was produced by Tonti (2013) and somewhat pushed also by Ferretti (2015).  These treatments could bring in the matter some new insight and the general understanding. What we did with the slides was to try to synthetize some of the above work, especially in view of an implementation of some Java libraries. The idea suggested by the readings was to use generic programming, design patters (Gamma et al, 1994, Freeman et al., 2005) and programming to interfaces (which BTW we already have in mund: we found what we were looking for). 
But the detail of the implementation will be the topic of a future post (but you can have a glance to literature browsing the bibliography below). Now get (a little of) theories by clicking on the figure above.

References
Notes

Some of my  students asked for somewhat a milder introduction to algebraic  topology.  I dedicated a new short post to it.

Friday, September 8, 2017

Weather Generation (according to Korbinian Breinl)

How one can reasonably cope with simulating future hydrometeorological forcing for hydrological purposes ? Clearly, since meteorology is dominated by unpredictable phenomena (in the sense of chaotic ones) and we cannot pretend to simply use forecasts, when we are looking just a little far away. An option would be to use climatic models and doing dynamic downscaling of their outcomes. The previous lecture given by Jeremy Pal (GS), followed this research path. However, we can produce statistical weather scenarios using stochastic weather generators (SWG) too, once  we have an idea of what will be the mean characteristics of such system.
Literature is full of SWG that covers mainly temperature and rainfall, but it seems there exists systems also that covers other meteorological variables, like wind and radiation.
Today we had a talk on the subject given at our Department of Civil, Environmental and Mechanical Engineering given by Korbinian Breinl. He is at present a post-doc at Uppsala University with Giuliano Di Baldassarre (GS) and we are collaborating in the SteepStreams project.

https://www.slideshare.net/secret/3mSM1qPLUj4BMR
As usual you can find his presentation by clicking on the figure above. But you can see the talk on YouTube

Besides flooding (and solid flooding) which is one of the scopes of the projects, I hope we succeed in modeling all the main components of the hydrological cycle by a combine use of Korbinian’s Generator and JGrass NewAGE. I have also the video record of his presentation, but not yet the approval to share it publicly on YouTube. However you can ask it to me writing to abouthydrology @ gmail.com.

Korbinian's generator is written in Matlab, and it is available through Github.

Please find below a reference list which include, besides Korbinian’s one, some other references that I could gather through time.

References

Other available codes

Thursday, August 31, 2017

A flexible approach to the estimation of water budgets and its connection to the travel time theory

This blogpost contains the Marialaura Bancheri (in this blog) dissertation for ending her doctoral studies. There is a lot of material inside that goes from how to do better hydrological models,  to doing it, to implement and deploys some OMS3 components.  Really a lot of material.
https://zenodo.org/record/858495#.WagcLNMjHwc

Clicking on the figure above, you can access the draft of the manuscript uploaded on Zenodo.  Here below, please find the Abstract of the manuscript:

Abstract

The increasing impacts of climate changes on water related sectors are leading the scientists' attentions to the development of comprehensive models, allowing better descriptions of the water and solute transport processes. "Getting the right answers for the right reasons", in terms of hydrological response, is one of the main goals of most of the recent literature. Semi-distributed hydrological models, based on the partition of basins in hydrological response units (HRUs) to be connected, eventually, to describe a whole catchment, proved to be robust in the reproduction of observed catchment dynamics. 'Embedded reservoirs' are often used for each HRU, to allow a consistent representation of the processes. In this work, a new semi-disitrbuted model for runoff and evapotranspiration is presented: five different reservoirs are inter-connected in order to capture the dynamics of snow, canopy, surface flow, root-zone and groundwater compartments.
The knowledge of the mass of water and solute stored and released through different outputs (e.g. discharge, evapotranspiration) allows the analysis of the hydrological travel times and solute transport in catchments. The latter have been studied extensively, with some recent benchmark contributions in the last decade. However, the literature remains obscured by different terminologies and notations, as well as model assumptions are not fully explained. The thesis presents a detailed description of a new theoretical approach that reworks the theory from the point of view of the hydrological storages and fluxes involved. Major aspects of the new theory are the 'age-ranked' definition of the hydrological variables, the explicit treatment of evaporative fluxes and of their influence on the transport, the analysis of the outflows partitioning coefficients and the explicit formulation of the 'age-ranked' equations for solutes. Moreover, the work presents concepts in a new systematic and clarified way, helping the application of the theory.
To give substance to the theory, a small catchment in the prealpine area was chosen as an example and the results illustrated.
The rainfall-runoff model and the travel time theory were implemented and integrated in the semi-distributed hydrological system JGrass-NewAge. Thanks to the environmental modelling framework OMS3, each part of the hydrological cycle is implemented as a component that can be selected, adopted, and connected at run-time to obtain a user-customized hydrological model. The system is flexible, expandable and applicable in a variety of modelling solutions.
In this work, the model code underwent to an extensive revision: new components were added (coupled storages water budget, travel times components); old components were enhanced (Kriging, shortwave, longwave, evapotranspiration, rain-snow separation, SWE and melting components); documentation was standardized and deployed.
Since the Thesis regards in wide sense the building of a collaborative system, a discussion of some general purpose tools that were implemented or improved for supporting the present research is also presented. They include the description and the verification of a software component dealing with the long-wave radiation budget and another component dealing with an implementation of some Kriging procedure.

Wednesday, August 30, 2017

OMS 3 essentials

I am collecting here some essential information about the Object Modeling system v3.

The papers to start with:
David, O., Ascough, J. C., II, Lloyd, W., Green, T. R., Rojas, K. W., Leavesley, G. H., & Ahuja, L. R. (2012). A software engineering perspective on environmental modeling framework design: The Object Modeling System. Environmental Modelling and Software, 39, 1–13. http://doi.org/10.1016/j.envsoft.2012.03.006

To have a recent overview of the subject jointly with our GEOframe stuff, one can also give a look to Marialaura Bancheri's dissertation.

OMS general

OMS console installation:

The Hello world example:
https://contemplatingmontessori.wordpress.com/2011/11/14/platonic-solids/

The source code can be found at:

Project:
https://alm.engr.colostate.edu/cb/project/oms

Repos:
https://alm.engr.colostate.edu/cb/repository/19257

Our development regarding the Net3 (Francesco Serafin's work):
https://alm.engr.colostate.edu/cb/repository/24720

Other information in the material of the Summer Schools or (in Italian) among the material of 2017 hydrology class.  I need some time to sort it out. The inpatients can help me.

Hopefully they will merge soon in an official release.  All the repo at present require a password that can be asked to Olaf David (odavid <at> colostate. edu) col.

Friday, August 18, 2017

Some About the World Bank Actions related to Water Resources


One former University of Trento student who eventually moved to Cambridge, Anna Cestari, is since many years working for the World Bank. Having the occasion to have her Trento, I asked her to give a seminar on the activities and the projects of the World Bank. What she said for the general activities is actually what is also summarised in the World Bank Brochure
https://www.youtube.com/watch?v=-EFZ1r18xuA
 However, she gave also talked a little about the Virtual Water problems, how much is water demand of Agricoluture, and some other details about what she finds in developing countries. Water availability has so large implications for any of us and our society. Certainly Global Hydrological Models, or regional ones, can help to sort out the numbers  that are required to build the statistics she presented, and to build infrastructures with informed data.

Thursday, August 17, 2017

The four hours rule

I link here an article from the Guardian by Oliver Bukerman, in Italy reproduced by Internazionale dedicated to the quantity of creative work that can be done every day. He, in turn, takes inspiration from the Alex Pang's book Rest: Why You Get More Done When You Work Less.
The original article can be found here. The Italian version here.

Maybe four hours is too low but, at the same time, pretending to be creative more than four ours a day is not a sin of pride ?
I would be clear, I am not suggesting to my Ph.D.  students to work lazily, but to be conscious that quality counts more than quantity and quality also depends on rational management of our own mental health which is the what we need to preserve. Then it is clear that some (short) periods of life require exceptional efforts. But this works only if these are the exception. Not the rule.

Monday, July 31, 2017

Projecting Climate Change Impacts on Water Resources in Regions of Complex Topography: A Case Study of the Western United States and Southern California


This is the talk given by Jeremy Pal (GS) in Trento on July 26, 2017. He talked about the impact of climate change and  land use on California water resources. Actually the work he presented is part of the awarded Master Thesis of Brianna Pag√†n (see last slides).
The talk presents in a plane way the issue related to water resources management of South California, Los Angeles area. It then uses an impressive set of modeling tools to pass from climate and land use changes to water availability. You can enjoy the video and get the slides too.  
https://www.slideshare.net/GEOFRAMEcafe/projecting-climate-change-impacts-on-water-resources-in-regions-of-complex-topography-a-case-study-of-the-western-united-states-and-southern-california
 
Here it is the abstract of the talk:
 
The Western United States and California have a greater potential vulnerability to climate change impacts on water resources due to a heavy reliance on snowmelt driven streamflow. California, the most agriculturally productive and populous region in the United States, depends on a complex and extensive water storage and conveyance system to supply water primarily for irrigation, municipal and industrial use and hydropower generation. This study provides an integrated approach to assess the impacts of climate change on the hydrologic cycle and extremes for all Southern Californian water supply basins:  Owens Valley, Mono Lake, Colorado River, Sacramento River, San-Joaquin River, and Tulare Lake basins. An 11-member ensemble of coupled atmosphere-ocean global climate models is first dynamically downscaled using a regional climate model and then statistically downscaled to force a hydrological model resulting in 4-km high-resolution output for the Contiguous United States. Greenhouse gas concentrations are prescribed according to historical values for the period 1976-2005 and to the IPCC Representative Concentration Pathway 8.5 for the near term future period 2021-2050. Precipitation is projected to remain the same or slightly increase by mid-century; however, rising temperatures result in a repartitioning of precipitation type towards more rainfall and therefore a reduced snowpack and earlier snowmelt. In addition to these hydrological changes, daily annual maximum runoff and precipitation events are projected to significantly increase in intensity and frequency such that future return periods change to become substantially more common. More specifically, the current daily annual maximum runoff 10-, 25-, and 50-, and 100-year events are projected to become approximately two to ten times more likely in the future. Furthermore, annual cumulative runoff volumes are projected to increase for high flow years and in contrast decrease for low flow years reducing the reliability of the system. While the escalating likelihood of drought reduces water supply availability, earlier snowmelt and significantly more intense winter precipitation events increases flood risk requiring winter releases from reservoirs for flood control purposes. All of these factors, coupled with projected increases in population, are likely to decrease supply during the higher demand drier months necessitating multiyear storage solutions for urban and agricultural regions as well as improved infrastructure and measures for flood control.
 

Wednesday, July 26, 2017

The post-contemporary flood forecasting systems

This is the presentation that has been held at University of Calabria in Cosenza, July 27, 2017. The presentation builds upon several other presentation present in this blog, and discusses the issue of designing a modern flood forecasting system. Actually I distinguish post-modern, contemporary and post-contemporary systems. Of the latter a short manifesto is given.
Clicking on the figure above the reader can access the first (Italian) version of the presentation. The English version can be seen and downloaded at this link. Once downloaded, the pdf contains links to publication and other relevant presentations. With respect to the Italian version, the English version contains a few small variations. One, in particular, was suggested by Daniela Biondi. She suggested that in my Manifesto for the post-contemporary flood forecasting systems, I should add the estimation of errors in forecasting. Suggestion that I fully endorse.

Friday, July 21, 2017

Jackknife

I found this nice paper on Jackknife, worth to read. Easy also to understand the differences between the jackknife technique and the leave-one-out one.
You can click on the knife to download it. 


Tuesday, July 18, 2017

Hydrological Extremes and Human Societies

This presentation is part of the summer school “Hydrometeorological extremes: processes, models and human impacts”  just held at Cagliari University this July 12-16. It is a school well organised by Roberto Deidda and became over the year a standard appointment fo my Ph.D. students. This year, among the lecturer there was Giuliano di Baldassarre (GS, RG) who covered the topic on Hydrological Extremes and Human Societies. Unfortunately I could not have been present at his lecture, but I've got his slides (and the permission to publish them).  You can find them below, by clicking on the figure. 
He also suggested some readings related to the talk:

Bianchizza, C., & Frigerio, S. (2013). Domination of or Adaptation to Nature ? A lesson we can still learn from the Vajont. Italian Journal of Engineering Geology and Environment, 6, 523–530. http://doi.org/10.4408/IJEGE.2013-06.B-50

Delle Rose, M. (2012). Decision-making errors and socio-political disputes over the Vajont dam disaster. Disaster Advances, 5(3), 144–152.

Di Baldassarre, G., Martinez, F., Kalantari, Z., & Viglione, A. (2017). Drought and flood in the Anthropocene: feedback mechanisms in reservoir operation. Earth System Dynamics, 8(1), 225–233. http://doi.org/10.5194/esd-8-225-2017

Di Baldassarre, G., Viglione, A., Carr, G., Kuil, L., Yan, K., Brandimarte, L., & Bl√∂schl, G. (2015). Debates-Perspectives on socio-hydrology: Capturing feedbacks between physical and social processes. Water Resources Research, 51(6), 4770–4781. http://doi.org/10.1002/2014WR016416

Montanari, A., Young, G., Savenije, H. H. G., Hughes, D., Wagener, T., Ren, L. L., et al. (2013). “Panta Rhei—Everything Flows”: Change in hydrology and society—The IAHS Scientific Decade 2013–2022. Hydrological Sciences Journal, 58(6), 1256–1275. http://doi.org/10.1080/02626667.2013.809088

Sunday, July 16, 2017

Iowa and operational hydrology

Or operational hydrology in Iowa. I do not know if I like the name, because it usually distinguished, since Sacramento model, models that work but kind of far from the edge of research. Obviously this was due to the fact that having a model running every day faces issues that researchers of my type seldom love, like dealing with unreliable data sets, managing, in any case huge amount of data, calibration of parameters, and, more recently, data assimilation. This obviously has to be done routinely, with no loss of forecasting, when it is easy not to have data, and so on. So the focus of these systems was (is) operativity and having reliable results with unreliable tools (an not, like I do, improving the tools).
Among the various experience I saw around the world, The Iowa's one, is remarkable, because never forgot the most recent research, thanks to the effort of Ricardo Gutierrez Mantilla (GS), and Witold Krajesky (GS).
Ricardo, which whom I share a paper, was so kind to show me what he is doing with all the group of people in Iowa in the recent EGU meeting in Wien, and I was surprised by the quality of the results he has, and the quality of the overall system. One remarkable fact is also the this system is, certainly based on the knowledge of current literature but, originally developed and different from any other. He finally sent to me the couple of his presentation that I (under his permission) am sharing with who is interested. 


Click on the figures to access the presentations. 

A recent publication about the systema was published on BAMS: Witold F. Krajewski, Daniel Ceynar, Ibrahim Demir, Radoslaw Goska, Anton Kruger, Carmen Langel, Ricardo Mantilla, James Niemeier, Felipe Quintero, Bong-Chul Seo, Scott J. Small, Larry J. Weber, and Nathan C. Young, Real-Time Flood Forecasting and Information System for the State of Iowa, Real-time flood forecasting and information system for the State of Iowa, Bull. Am. Meteorol. Soc., doi:10.1175/BAMS-D-15-00243.1, 2017.

Here you can find the  IFC official website.
Here a link to the Iowa Flood Information System (IFIS) which is the platform they use to disseminate flood related information


Enjoy.