Micro-level water-resources engineering—10: A bridge to end droughts?…

Let me ask you a simple question: Why are bridges at all necessary? I mean to refer to the bridges that get built on rivers. …Why do you at all have to build them?

Your possible answer might be this: Bridges are built on rivers primarily because there is water in the rivers, and the presence of the water body makes it impossible to continue driving across the river. Right? OK. Good.

In India, “kachchaa” (untarred) roads often exist on the sides of the main road or a high-way, as we approach a bridge on a river. These side-roads usually aren’t built after planning, but simply are a result of the tracks left by the bullock-carts plying through the fields, on both sides of the road. People from nearby villages often find such side roads very convenient for their purposes, including accessing the river. The sand-smugglers too find such approach-roads very convenient to their purposes. The same roads are also found convenient by journalists and NGO workers who wish to visit and photograph the same river-bed as it turns totally dry, for quite some time before summer even approaches.

Somewhere in there lies a certain contradiction—a technical contradiction, I should add.

If there were to be no water, ever, in these rivers, then no bridges would at all be necessary. Yet, these bridges are there. That’s because, in monsoon, it rains so much that these rivers begin to flow with full capacity; they even overflow and cause extensive flooding in the adjacent areas. So, naturally, bridges have to be built.

Yet, come even just late winter time, and the river-bed is already on its way to going completely dry. The bridge might as well not have been there.

Thus, the bridges, it would seem, are both necessary and not necessary in India. That’s the contradiction I was talking about.


But why not turn this entire situation to your advantage, and use the very site of a bridge for building a small check-dam?

After all, the very fact that there is a bridge means:

there is enough water flowing through that river, at least during monsoons. We only have to find a way to use it.


Here are some of the advantages of building check-dams nearby a bridge—or may be even directly underneath its span:

  • The patterns of water-flow across the pillars of the bridge, and even the pattern of flooding near the site of the bridge, has become well known, even if only because there is a better access to this site (as compared to other potential sites for a check-dam)—because of the existence of the main road.
  • There is already a built structure in place. This means that the nature of the rocks and of the soil at the site is already well studied. You don’t have to conduct costly geological surveys afresh; you only have to refer to the ready-made past reports.
  • Another implication of there being a pre-existing structure is this: The nearby land has already been acquired. There is no cost to be incurred in land acquisition, and the cost and other concerns in relocating the people.
  • Columns/pillars of the bridge already exist, and so, the cost of building the wall of a check-dam can come down at least a bit—especially if the wall is constructed right underneath the bridge.
  • Many times, there also is a lower-level cause-way, or an older and abandoned bridge lying nearby, which is no longer used. It can be dismantled so that the stones used in its construction can be recycled for building the wall of the check-dam. It’s another potential reduction in cost (including in the material transportation cost).
  • The existence of a bridge at a site can often mean that there is likely to be a significant population on either sides of the river—a population which had demanded that the bridge be built in the first place. Implication: If a water body comes to exist at this same site, then the water doesn’t have to be transported over long distances, because a definite demand would exist locally. Even if not, if the check-dam is equipped with gates, then the stored water can be supplied at distant locations downstream using the same river—you don’t have to build canals (starting from the acquisition of land for them, and further costs and concerns down the way).
  • Easy access to transportation would be good for side-businesses like fisheries, even for building recreational sites. (Think agro-tourism, boating, etc.)

Of course, there are certain important points of caution or concern, too. These must be considered in each individual case, on a case-to-case basis:

  • The local flow pattern would get adversely affected, which can prove to be dangerous for the bridge itself.
  • There is a likelihood of a greater flooding occurring in the nearby locations—esp. upstream! A blocked river swells easily, and does not drain as rapidly as it otherwise would—the causeway or the spillway can easily turn out to be too small, especially in the case of small dams or check-dams.
  • The height of the bridge itself may be good, but still, the river itself may turn out to be a little too shallow at a given location for a check-dam to become technically feasible, there. Given the importance of the evaporation losses, the site still may not turn out to be suitable for building a check-dam. (For evaporation losses, see my last post in this series [^].)

But overall, I think that the idea is attractive enough that it should be pursued very seriously, especially by students and faculty of engineering colleges.


We all know that there has been a great proliferation of engineering colleges all over the country. The growth is no longer limited to only big cities; many of them are situated in very rural areas too.

When a problem to be studied touches on the lives of people, say a student or two, it becomes easy for them to turn serious about it. Speaking from my own personal experience, I can say that BE project-reports from even relatively lower-quality engineering colleges have been surprisingly (unexpectedly) good, when two factors were present:

(i) When the project topic itself dealt with some issue which is close to the actual life of the students and the faculty, to their actual concerns.

For instance, consider the topic of studies of design of check-dams and farm-ponds, and their effectiveness.

During my stint as a professor, I have found that rural students consistently show (across batches) reporting of the actual data (i.e., not a copy-paste job).

In fact, even if they were not otherwise very bright academically, they did show unexpectedly better observation abilities. The observation tables in their reports would not fail to show the more rapidly falling water levels in check-dams. Invariably, they had backed the data in the tables with even photos of the almost dried up check-dams too.

Yes, the photos were often snapped unprofessionally—invariably, using their cell-phones. (Their parked bikes could be easily visible in the photos, but then, sometimes, also the Sun.) No, these rural students typically didn’t use the photo-quality glossy paper to take their printouts—which was very unlike the students from the big cities. The rural students typically had used only ordinary bond-paper even for taking color printouts of their photos (invariably using lower-resolution ink-jet printers).

But still, typically, the set of photos would unambiguously bring out the fact of multiple field visits they had made, per their teacher. The background shrubs showed seasonal variations, for instance; also the falling water levels, and the marks of the salt on the dam walls.

Invariably, the photos only corroborated—and not even once contradicted—the numbers or trends reported in their observation tables.

Gives me the hope that one relatively easy way to identify suitable bridges would be to rely on students like these.

(ii) The second factor (for good, reliable field studies) was: the presence of a teacher who guides the students right.

No, he doesn’t have to have a PhD, or even ME for that matter. But he has to know for himself, and pass on to his students, the value of the actual, direct and unadulterated observations, the value of pursuing a goal sincerely over a course of 6–8 months—and the fun one can have in doing that.


OK, a bit of a digression it all was. But the point to which I wanted to come, was academics, anyway.

I think academic institutions should take a lead in undertaking studies for feasibility of converting a bridge into a check-dam. Each academic team should pick up some actual location, and study it thoroughly from different viewpoints including (but not limited to):

  • CFD analysis for predicting the altered water-flow and flooding patterns (with the water flow possibly designed to occur over the main wall itself, i.e. without a side-weir), especially for a dam which is situated right under a bridge);
  • FEM analysis for strength and durability of the structures;
  • Total costs that will be incurred; total savings due to the site (near a bridge vs. far away from it at some location that is not easy to access); and overall cost–benefits analysis; etc.

The initiative for such studies could possibly begin from IITs or other premier engineering colleges, and then, via some research collaboration schemes, it could get spread over to other engineering colleges. Eventually, this kind of a research—a set of original studies—could come to take hold in the rural engineering colleges, too. … Hopefully.


Should the government agencies like PWD, Irrigation Dept., or “private,” American concerns like the Engineers India Limited, etc., get involved?

Here, I think that the above-mentioned academic teams certainly are going to benefit from interactions with certain select institutes like (speaking of Maharashtra) CDO Nasik, and CWPRS Pune.

However, when it comes PWD etc. proper, I do think that they operate rather in a direct project-execution mode, and not so much in a “speculative” research mode. Plus, their thinking still remains grooved in the older folds such as: either have multi-purpose large dams or have no dams at all!, etc.

But, yes, CWPRS Pune has simulation facilities (both with physical scale-models, and also via computational simulation methods), and CDO Nasik has not only design expertise but also data on all the bridges in the state. (CDO is the centralized design services organization that is responsible for engineering designs of all the dams, canals, bridges and similar structures built by the state government in Maharashtra.) The cooperation of these two organizations would therefore be important.


In the meanwhile, if you are not an engineering student or a faculty member, but still, if you are enthusiastic about this topic, then you can do one thing.

The next time you run into a site that fulfills the following criteria, go ahead, discuss it with people from the nearby villages, take a good set of snaps of the site from all sides, write a very small and informal description including the location details, and send it over by email to me. I will then see what best can be done to take it further. (The fact that there were so few engineering colleges in our times has one advantage: Many of the engineers today in responsible positions come from the COEP network.)

The absolutely essential criteria that your site should fulfill are the following two:

  1. The river gorge must be at least 25 feet deep at the candidate location.
  2. The under-side of the bridge-girder should itself be at least 35 feet above the ground or at a higher level (so that there is at least prima facie enough of a clearance for the flood water to safely pass through the bridge). But please note, this figure is purely my hunch, as of now. I may come back and revise this figure after discussing the matter with some researchers/IIT professors/experienced engineers. For visualization, remember: 10 feet means one storey, or the height of a passenger bus. Thus, the road should lie some 4 stories high from the river-bed. Only then can you overcome evaporation losses and also have enough clearance for flood water to safely pass through without doing any damage to the bridge or the dam.

Further, the preferred criteria (in site selection) would be these:

  1. The upstream of the site should not have too steep a gradient—else, the storage volume might turn out to be too small, or, severe flooding might occur upstream of the check-dam! For the same reason, avoid sites with water-falls nearby (within 1–2 km) upstream.
  2. The site should preferably be situated in a drought-prone region.
  3. Preferably, there should be an older, abandoned bridge of a much lower height (or a cause-way) parallel to a new bridge. Though not absolutely necessary I do include this factor in searches for the initial candidate locations, because it indirectly tells us that enough water flows through the river during the monsoons that the cause-way wouldn’t be enough (it would get submerged), and therefore, a proper bridge (which is tall enough) had to be built. This factor thus indirectly tells us that there is enough rainfall in the catchment area, so that the check-dam would sure get filled to its design capacity—that one wouldn’t have to do any detailed rainfall assessment for the catchment region and all.

So, if you can spot such a site, please do pursue it a bit further, and then, sure do drop me a line. I will at least look into what all can be done.


But, yes, in India, bridges do get built in the perennially drought-prone regions too. After all, when the monsoon arrives, there is flooding even in the drought-prone regions. It’s just that we haven’t applied enough engineering to convert the floods into useful volumes of stored water.

… For a pertinent example, see this YouTube video of a bridge getting washed away near Latur in the Marathwada region of Maharashtra, in September 2016 [^]. Yes, Latur is the same city where even drinking water had to be supplied using trains, starting from early April 2016 [^].

So, we supplied water by train to Latur in April 2016. But then, in September 2016 (i.e. the very next monsoon), their local rivers swelled so much, that an apparently well-built bridge got washed away in the floods. … Turns out that the caution I advised above, concerning simulating flooding, wasn’t out of place. …  But coming back to the drought-prone Latur, though I didn’t check it, I feel sure that come April 2017, and it was all back to a drought in Latur—once again. Fatigue!


PS: In fact, though this idea (of building check-dams near bridges) had occurred to me several years ago, I think I never wrote about it, primarily because I wasn’t sure whether it was practical enough to be deployed in relatively flatter region like Marathwada, where the drought is most acute, and suitable sites for dams, not so easy to come by. (See my earlier posts covering the Ujani and Jayakawadi dams.) However, as it so happened, I was somewhat surprised to find someone trying to advocate this idea within the government last year or so. … I vaguely remember the reports in the local Marathi newspapers in Pune, though I can’t off-hand give you the links.

On second thoughts, here are the links I found today, after googling for “check dams near bridges”. Here are a couple of the links this search throws up as of today: [^] and [^].

… Also, make sure to check the “images” tab produced by this Google search too. … As expected, the government agencies have been dumb enough to throw at least some money at at least a few shallow check-dams too (not good for storage due to evaporation losses) that were erected seemingly in the regions of hard rocks and all (generally, not so good for seepage and ground-water recharge either). As just one example, see here [^]. I am sure there are many, many other similar sites in many other states too. Government dumb-ness is government dumb-ness. It is not constrained by this government or that government. It is global in its reach—it’s even universal!

And that’s another reason why I insist on private initiative, and on involvement of local engineering college students and faculty members. They can be motivated when the matter is close to their concerns, their life, and so, with their involvement the results can turn out to be very beneficial. If nothing else, a project experience like this would help the students become better engineers—less wasteful ones. That too is such an enormous benefit that we could be even separately aiming for it. Here, it can come as a part of the same project.


Anyway, to close this post: Be on the lookout for good potential sites, and feel free to get in touch with me for further discussions on any technical aspects related to this issue. Take care, and bye for now…


A song I like:

(Hindi) “chori chori jab nazare mili…”
Lyrics: Rahat Indori
Music: Anu Malik
Singers: Kumar Sanu, Sanjeevani

[A song with a very fresh feel. Can’t believe it came from Anu Malik. (But, somehow, the usual plagiarism reporting sites don’t include this song! Is it really all that original? May be…)]

 

 

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Determinism, Indeterminism, Probability, and the nature of the laws of physics—a second take…

After I wrote the last post [^], several points struck me. Some of the points that were mostly implicit needed to be addressed systematically. So, I began writing a small document containing these after-thoughts, focusing more on the structural side of the argument.

However, I don’t find time to convert these points + statements into a proper write-up. At the same time, I want to get done with this topic, at least for now, so that I can better focus on some other tasks related to data science. So, let me share the write-up in whatever form it is in, currently. Sorry for its uneven tone and all (compared to even my other writing, that is!)


Causality as a concept is very poorly understood by present-day physicists. They typically understand only one sense of the term: evolution in time. But causality is a far broader concept. Here I agree with Ayn Rand / Leonard Peikoff (OPAR). See the Ayn Rand Lexicon entry, here [^]. (However, I wrote the points below without re-reading it, and instead, relying on whatever understanding I have already come to develop starting from my studies of the same material.)

Physical universe consists of objects. Objects have identity. Identity is the sum total of all characteristics, attributes, properties, etc., of an object. Objects act in accordance with their identity; they cannot act otherwise. Interactions are not primary; they do not come into being without there being objects that undergo the interactions. Objects do not change their respective identities when they take actions—not even during interactions with other objects. The law of causality is a higher-level view taken of this fact.

In the cause-effect relationship, the cause refers to the nature (identity) of an object, and the effect refers to an action that the object takes (or undergoes). Both refer to one and the same object. TBD: Trace the example of one moving billiard ball undergoing a perfectly elastic collision with another billiard ball. Bring out how the interaction—here, the pair of the contact forces—is a name for each ball undergoing an action in accordance with its nature. An interaction is a pair of actions.


A physical law as a mapping (e.g., a function, or even a functional) from inputs to outputs.

The quantitative laws of physics often use the real number system, i.e., quantification with infinite precision. An infinite precision is a mathematical concept, not physical. (Expect physicists to eternally keep on confusing between the two kinds of concepts.)

Application of a physical law traces the same conceptual linkages as are involved in the formulation of law, but in the reverse direction.

In both formulation of a physical law and in its application, there is always some regime of applicability which is at least implicitly understood for both inputs and outputs. A pertinent idea here is: range of variations. A further idea is the response of the output to small variations in the input.


Example: Prediction by software whether a cricket ball would have hit the stumps or not, in an LBW situation.

The input position being used by the software in a certain LBW decision could be off from reality by millimeters, or at least, by a fraction of a millimeter. Still, the law (the mapping) is such that it produces predictions that are within small limits, so that it can be relied on.

Two input values, each theoretically infinitely precise, but differing by a small magnitude from each other, may be taken to define an interval or zone of input variations. As to the zone of the corresponding output, it may be thought of as an oval produced in the plane of the stumps, using the deterministic method used in making predictions.

The nature of the law governing the motion of the ball (even after factoring in aspects like effects of interaction with air and turbulence, etc.) itself is such that the size of the O/P zone remains small enough. (It does not grow exponentially.) Hence, we can use the software confidently.

That is to say, the software can be confidently used for predicting—-i.e., determining—the zone of possible landing of the ball in the plane of the stumps.


Overall, here are three elements that must be noted: (i) Each of the input positions lying at the extreme ends of the input zone of variations itself does have an infinite precision. (ii) Further, the mapping (the law) has theoretically infinite precision. (iii) Each of the outputs lying at extreme ends of the output zone also itself has theoretically infinite precision.

Existence of such infinite precision is a given. But it is not at all the relevant issue.

What matters in applications is something more than these three. It is the fact that applications always involve zones of variations in the inputs and outputs.

Such zones are then used in error estimates. (Also for engineering control purposes, say as in automation or robotic applications.) But the fact that quantities being fed to the program as inputs themselves may be in error is not the crux of the issue. If you focus too much on errors, you will simply get into an infinite regress of error bounds for error bounds for error bounds…

Focus, instead, on the infinity of precision of the three kinds mentioned above, and focus on the fact that in addition to those infinitely precise quantities, application procedure does involve having zones of possible variations in the input, and it also involves the problem estimating how large the corresponding zone of variations in the output is—whether it is sufficiently small for the law and a particular application procedure or situation.

In physics, such details of application procedures are kept merely understood. They are hardly, if ever, mentioned and discussed explicitly. Physicists again show their poor epistemology. They discuss such things in terms not of the zones but of “error” bounds. This already inserts the wedge of dichotomy: infinitely precise laws vs. errors in applications. This dichotomy is entirely uncalled for. But, physicists simply aren’t that smart, that’s all.


“Indeterministic mapping,” for the above example (LBW decisions) would the one in which the ball can be mapped as going anywhere over, and perhaps even beyond, the stadium.

Such a law and the application method (including the software) would be useless as an aid in the LBW decisions.

However, phenomenologically, the very dynamics of the cricket ball’s motion itself is simple enough that it leads to a causal law whose nature is such that for a small variation in the input conditions (a small input variations zone), the predicted zone of the O/P also is small enough. It is for this reason that we say that predictions are possible in this situation. That is to say, this is not an indeterministic situation or law.


Not all physical situations are exactly like the example of the predicting the motion of the cricket ball. There are physical situations which show a certain common—and confusing—characteristic.

They involve interactions that are deterministic when occurring between two (or few) bodies. Thus, the laws governing a simple interaction between one or two bodies are deterministic—in the above sense of the term (i.e., in terms of infinite precision for mapping, and an existence of the zones of variations in the inputs and outputs).

But these physical situations also involve: (i) a nonlinear mapping, (ii) a sufficiently large number of interacting bodies, and further, (iii) coupling of all the interactions.

It is these physical situations which produce such an overall system behaviour that it can produce an exponentially diverging output zone even for a small zone of input variations.

So, a small change in I/P is sufficient to produce a huge change in O/P.

However, note the confusing part. Even if the system behaviour for a large number of bodies does show an exponential increase in the output zone, the mapping itself is such that when it is applied to only one pair of bodies in isolation of all the others, then the output zone does remain non-exponential.

It is this characteristic which tricks people into forming two camps that go on arguing eternally. One side says that it is deterministic (making reference to a single-pair interaction), the other side says it is indeterministic (making reference to a large number of interactions, based on the same law).

The fallacy arises out of confusing a characteristic of the application method or model (variations in input and output zones) with the precision of the law or the mapping.


Example: N-body problem.

Example: NS equations as capturing a continuum description (a nonlinear one) of a very large number of bodies.

Example: Several other physical laws entering the coupled description, apart from the NS equations, in the bubbles collapse problem.

Example: Quantum mechanics


The Law vs. the System distinction: What is indeterministic is not a law governing a simple interaction taken abstractly (in which context the law was formed), but the behaviour of the system. A law (a governing equation) can be deterministic, but still, the system behavior can become indeterministic.


Even indeterministic models or system designs, when they are described using a different kind of maths (the one which is formulated at a higher level of abstractions, and, relying on the limiting values of relative frequencies i.e. probabilities), still do show causality.

Yes, probability is a notion which itself is based on causality—after all, it uses limiting values for the relative frequencies. The ability to use the limiting processes squarely rests on there being some definite features which, by being definite, do help reveal the existence of the identity. If such features (enduring, causal) were not to be part of the identity of the objects that are abstractly seen to act probabilistically, then no application of a limiting process would be possible, and so not even a definition probability or randomness would be possible.

The notion of probability is more fundamental than that of randomness. Randomness is an abstract notion that idealizes the notion of absence of every form of order. … You can use the axioms of probability even when sequences are known to be not random, can’t you? Also, hierarchically, order comes before does randomness. Randomness is defined as the absence of (all applicable forms of) orderliness; orderliness is not defined as absence of randomness—it is defined via the some but any principle, in reference to various more concrete instances that show some or the other definable form of order.

But expect not just physicists but also mathematicians, computer scientists, and philosophers, to eternally keep on confusing the issues involved here, too. They all are dumb.


Summary:

Let me now mention a few important take-aways (though some new points not discussed above also crept in, sorry!):

  • Physical laws are always causal.
  • Physical laws often use the infinite precision of the real number system, and hence, they do show the mathematical character of infinite precision.
  • The solution paradigm used in physics requires specifying some input numbers and calculating the corresponding output numbers. If the physical law is based on real number system, than all the numbers used too are supposed to have infinite precision.
  • Applications always involve a consideration of the zone of variations in the input conditions and the corresponding zone of variations in the output predictions. The relation between the sizes of the two zones is determined by the nature of the physical law itself. If for a small variation in the input zone the law predicts a sufficiently small output zone, people call the law itself deterministic.
  • Complex systems are not always composed from parts that are in themselves complex. Complex systems can be built by arranging essentially very simpler parts that are put together in complex configurations.
  • Each of the simpler part may be governed by a deterministic law. However, when the input-output zones are considered for the complex system taken as a whole, the system behaviour may show exponential increase in the size of the output zone. In such a case, the system must be described as indeterministic.
  • Indeterministic systems still are based on causal laws. Hence, with appropriate methods and abstractions (including mathematical ones), they can be made to reveal the underlying causality. One useful theory is that of probability. The theory turns the supposed disadvantage (a large number of interacting bodies) on its head, and uses limiting values of relative frequencies, i.e., probability. The probability theory itself is based on causality, and so are indeterministic systems.
  • Systems may be deterministic or indeterministic, and in the latter case, they may be described using the maths of probability theory. Physical laws are always causal. However, if they have to be described using the terms of determinism or indeterminism, then we will have to say that they are always deterministic. After all, if the physical laws showed exponentially large output zone even when simpler systems were considered, they could not be formulated or regarded as laws.

In conclusion: Physical laws are always causal. They may also always be regarded as being deterministic. However, if systems are complex, then even if the laws governing their simpler parts were all deterministic, the system behavior itself may turn out to be indeterministic. Some indeterministic systems can be well described using the theory of probability. The theory of probability itself is based on the idea of causality albeit measures defined over large number of instances are taken, thereby exploiting the fact that there are far too many objects interacting in a complex manner.


A song I like:

(Hindi) “ho re ghungaroo kaa bole…”
Singer: Lata Mangeshkar
Music: R. D. Burman
Lyrics: Anand Bakshi