# And to think…

Many of you must have watched the news headlines on TV this week; many might have gathered it from the ‘net.

Mumbai—and much of Maharashtra—has gone down under. Under water.

And to think that all this water is now going to go purely to waste, completely unused.

… And that, starting some time right from say February next year, we are once again going to yell desperately about water shortage, about how water-tankers have already begun plying on the “roads” near the drought-hit villages. … May be we will get generous and send not just 4-wheeler tankers but also an entire train to a drought-hit city or two…

Depressing!

OK. Here’s something less depressing. [H/t Jennifer Ouellette (@JenLucPiquant) ]:

“More than 2,000 years ago, people were able to create ice in the desert even with temperatures above freezing!” [^]

The write-up mentions a TED video by Prof. Aaswath Raman. Watched it out of idle interest, checked out his Web site, and found another TED video by him, here [^]. Raman cites statistics that blew me!

They spend “only” $24 billion on supermarket refrigeration (and other food-related cooling), but they already spend$42 billion on data-center cooling!!

But, any way, I did some further “research” and landed at a few links, like the Wiki on Yakhchal [^], on wind-catcher [^], etc.  Prof. Raman’s explanation in terms of the radiative cooling was straight-forwards, but I am not sure I understand the mechanism behind the use of a qanat [^] in Yakhchal/windcatcher cooling. It would be cool to do some CFD simulations though.

Finally, since I am once again out of a job (and out of all my saved money and in fact also into credit-card loans due to some health issue cropping up once again), I was just idly wondering about all this renewable energy business, when something struck me.

The one big downside of windmills is that the electricity they generate fluctuates too much. You can’t rely on it; the availability is neither 24X7 nor uniform. Studies in fact also show that in accommodating the more or less “random” output of windmills into the conventional grid, the price of electricity actually goes up—even if the cost of generation alone at the windmill tower may be lower. Further, battery technology has not improved to such a point that you could store the randomly generated electricity economically.

So, I thought, why not use that randomly fluctuating windmill electricity in just producing the hydrogen gas?

No, I didn’t let out a Eureka. Instead, I let out a Google search. After all, the hydrogen gas could be used in fuel-cells, right? Would the cost of packaging and transportation of hydrogen gas be too much? … A little searching later, I landed at this link: [^]. Ummm… No, no, no…. Why shoot it into the natural gas grid? Why not compress it into cylinders and transport by trains? How does the cost economics work out in that case? Any idea?

Addendum on the same day, but after about a couple of hours:

Yes, I did run into this link: “Hydrogen: Hope or Hype?” [^] (with all the links therein, and then, also this: [^]).

But before running into those links, even as my googling on “hydrogen fuel energy density” still was in progress, I thought of this idea…

Why at all transport the hydrogen fuel from the windmill farm site to elsewhere? Why not simply install a fuel cell electricity generator right at the windmill farm? That is to say, why not use the hydrogen fuel generated via electrolysis as a flywheel of sorts? Get the idea? You introduce a couple of steps in between the windmill’s electricity and the conventional grid. But you also take out the fluctuations, the bad score on the 24X7 availability. And, you don’t have to worry about the transportation costs either.

What do you think?

Addendum on 12th July 2018, 13:27 hrs IST

Further, I also browsed a few links that explore another,  solution: using compressed air: a press report [^], and a technical paper [^]. (PDF of the paper is available, but the paper would be accessible only to mechanical engineers though. Later Update: As to the press report, well, the company it talks about has already merged with another company, and has abandoned the above-ground storage of compressed air [^])

I think that such a design reduces the number of steps of energy conversions. However, that does not necessarily mean that the solution involving hydrogen fuel generation and utilization (both right at the wind-farm) isn’t going to be economical.

Economics determines (or at least must determine) the choice. Enough on this topic for now. Wish I had a student working with me; I could have then written a paper after studying the solution I have proposed above. (The idea is worth a patent too. Too bad I don’t have the money to file one. Depressing, once again!!)

OK. Enough for the time being. I may later on add the songs section if I feel like it. And, iterative modifications will always be done, but will be mostly limited to small editorial changes. Bye for now.

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# Micro-level water-resources engineering—8: Measure that water evaporation! Right now!!

It’s past the middle of May—the hottest time of the year in India.

The day-time is still lengthening. And it will continue doing so well up to the summer solstice in the late June, though once monsoon arrives some time in the first half of June, the solar flux in this part of the world would get reduced due to the cloud cover, and so, any further lengthening of the day would not matter.

In the place where I these days live, the day-time temperature easily goes up to 42–44 deg. C. This high a temperature is, that way, not at all unusual for most parts of Maharashtra; sometimes Pune, which is supposed to be a city of a pretty temperate climate (mainly because of the nearby Sahyaadris), also registers the max. temperatures in the early 40s. But what makes the region where I currently live worse than Pune are these two factors: (i) the minimum temperature too stays as high as 30–32 deg. C here whereas in Pune it could easily be falling to 27–26 deg. C even during May, and (ii) the fall of the temperatures at night-time proceeds very gradually here. On a hot day, it can easily be as high as 38 deg C. even after the sunset, and even 36–37 deg. C right by the time it’s the mid-night; the drop below 35 deg. C occurs only for the 3–4 hours in the early morning, between 4 to 7 AM. In comparison, Pune is way cooler. The max. temperatures Pune registers may be similar, but the evening- and the night-time temperatures fall down much more rapidly there.

There is a lesson for the media here. Media obsesses over the max. temperature (and its record, etc.). That’s because the journos mostly are BAs. (LOL!) But anyone who has studied physics and calculus knows that it’s the integral of temperature with respect to time that really matters, because it is this quantity which scales with the total thermal energy transferred to a body. So, the usual experience common people report is correct. Despite similar max. temperatures, this place is hotter, much hotter than Pune.

And, speaking of my own personal constitution, I can handle a cold weather way better than I can handle—if at all I can handle—a hot weather. [Yes, in short, I’ve been in a bad shape for the past month or more. Lethargic. Lackadaisical. Enervated. You get the idea.]

But why is it that the temperature does not matter as much as the thermal energy does?

Consider a body, say a cube of metal. Think of some hypothetical apparatus that keeps this body at the same cool temperature at all times, say, at 20 deg. C.  Here, choose the target temperature to be lower than the minimum temperature in the day. Assume that the atmospheric temperature at two different places varies between the same limits, say, 42 to 30 deg. C. Since the target temperature is lower than the minimum ambient temperature, you would have to take heat out of the cube at all times.

The question is, at which of the two places the apparatus has to work harder. To answer that question, you have to calculate the total thermal energy that has be drained out of the cube over a single day. To answer this second question, you would need the data of not just the lower and upper limits of the temperature but also how it varies with time between two limits.

The humidity too is lower here as compared to in Pune (and, of course, in Mumbai). So, it feels comparatively much more drier. It only adds to the real feel of a real hot weather.

One does not realize it, but the existence of a prolonged high temperature makes the atmosphere here imperceptibly slowly but also absolutely insurmountably, dehydrating.

Unlike in Mumbai, one does not notice much perspiration here, and that’s because the air is so dry that any perspiration that does occur also dries up very fast. Shirts getting drenched by perspiration is not a very common sight here. Overall, desiccating would be the right word to describe this kind of an air.

So, yes, it’s bad, but you can always take precautions. Make sure to drink a couple of glasses of cool water (better still, fresh lemonade) before you step out—whether you are thirsty or not. And take an onion with you when you go out; if you begin to feel too much of heat, you can always crush the onion with hand and apply the juice onto the top of your head. [Addendum: A colleague just informed me that it’s even better to actually cut the onion and keep its cut portion touching to your body, say inside your shirt. He has spent summers in eastern Maharashtra, where temperatures can reach 47 deg. C. … Oh well!]

Also, eat a lot more onions than you normally do.

And, once you return home, make sure not to drink water immediately. Wait for 5–10 minutes. Otherwise, the body goes into a shock, and the ensuing transient spikes in your biological metabolism can, at times, even trigger the sun-stroke—which can even be fatal. A simple precaution helps avoid it.

For the same reason, take care to sit down in the shade of a tree for a few minutes before you eat that slice of water-melon. Water-melon is nothing but more than 95% water, thrown with a little sugar, some fiber, and a good measure of minerals. All in all, good for your body because even if the perspiration is imperceptible in the hot and dry regions, it is still occurring, and with it, the body is being drained of the necessary electrolytes and minerals. … Lemonades and water-melons supply the electrolytes and the minerals. People do take care not to drink lemonade in the Sun, but they don’t always take the same precaution for water-melon. Yet, precisely because a water-melon has so much water, you should take care not to expose your body to a shock. [And, oh, BTW, just in case you didn’t know already, the doctor-recommended alternative to Electral powder is: your humble lemonade! Works exactly equivalently!!]

Also, the very low levels of humidity also imply that in places like this, the desert-cooler is effective, very effective. The city shops are full of them. Some of these air-coolers sport a very bare-bones design. Nothing fancy like the Symphony Diet cooler (which I did buy last year in Pune!). The air-coolers locally made here can be as simple as just an open tray at the bottom to hold the water, a cube made of a coarse wire-mesh which is padded with the khus/wood sheathings curtain, and a robust fan operating [[very] noisily]. But it works wonderfully. And these local-made air-coolers also are very inexpensive. You can get one for just Rs. 2,500 or 3,000. I mean the ones which have a capacity to keep at least 3–4 people cool.(Branded coolers like the one I bought in Pune—and it does work even in Pune—often go above Rs. 10,000. [I bought that cooler last year because I didn’t have a job, thanks to the Mechanical Engineering Professors in the Savitribai Phule Pune University.])

That way, I also try to think of the better things this kind of an air brings. How the table salt stays so smoothly flowing, how the instant coffee powder or Bournvita never turns into a glue, how an opened packet of potato chips stays so crisp for days, how washed clothes dry up in no time…

Which, incidentally, brings me to the topic of this post.

The middle—or the second half—of May also is the most ideal time to conduct evaporation experiments.

If you are looking for a summer project, here is one: to determine the evaporation rate in your locality.

Take a couple of transparent plastic jars of uniform cross section. The evaporation rate is not very highly sensitive to the cross-sectional area, but it does help to take a vessel or a jar of sizeable diameter.

Affix a mm scale on the outside of each jar, say using cello-tape. Fill the plastic jars to some level almost to the full.

Keep one jar out in the open (exposed to the Sun), and another one, inside your home, in the shade. For the jar kept outside, make sure that birds don’t come and drink the water, thereby messing up with your measurements. For this purpose, you may surround the jar with an enclosure having a coarse mesh. The mesh must be coarse; else it will reduce the solar flux. The “reduction in the solar flux” is just a fancy [mechanical [thermal] engineering] term for saying that the mesh, if too fine, might cast too significant a shadow.

Take measurements of the heights of the water daily at a fixed time of the day, say at 6:00 PM. Conduct the experiment for a week or 10 days.

Then, plot a graph of the daily water level vs. the time elapsed, for each jar.

Realize, the rate of evaporation is measured in terms of the fall in the height, and not in terms of the volume of water lost. That’s because once the exposed area is bigger than some limit, the evaporation rate (the loss in height) is more or less independent of the cross-sectional area.

Now figure out:

Does the evaporation rate stay the same every day? If there is any significant departure from a straight-line graph, how do you explain it? Was there a measurement error? Was there an unusually strong wind on a certain day? a cloud cover?

Repeat the experiment next winter (around the new year), and determine the rate of evaporation at that time.

Later on, also make some calculations. If you are building a check-dam or a farm-pond, how much would be the evaporation loss over the five months from January to May-end? Is the height of your water storage system enough to make it practically useful? economically viable?

A Song I Like:

(Hindi) “mausam aayegaa, jaayegaa, pyaar sadaa muskuraayegaa…”
Music: Manas Mukherjee
Singers: Manna Dey and Asha Bhosale
Lyrics: Vithalbhai Patel

# Micro-level water-resources engineering—7: Dealing with the [upcoming] summer

Last monsoon, we’ve mostly had excess rain-fall in most parts of Maharashtra, even over India, taken as a whole.

Though the weather in Maharashtra still is, for the most part, pleasantly cool, the autumn season this year (in India) is about to get over, right this month.

Therefore, right now, i.e. right at the beginning of February, is the perfect time to empirically check the water levels in all those check-dams/farm-ponds you have. … That’s because, evaporation is going to happen at an accelerating pace from now on…

Between end-October (say Diwali) and March (say Holi), every solar year in India, the reduction in the levels of the stored water is dominated by the following two factors:
(i) seepage (i.e. the part which occurs after the rains cease), and
(ii) usage (i.e. the irrigation for the “rabbi” (i.e. the winter agricultural) season).

But from now on, the dominant factor is going to be the third one, namely, (iii) evaporation, and it is going to be increasingly ever more important throughout the upcoming summer, i.e., until the arrival of the next monsoon.

As I had earlier pointed out in this series  [^][^], in Maharashtra, the losses due to evaporation are expected to be about 5–8 feet (or 1 to 1.5 “puruSh”) deep.

Don’t take my word for it. … Go out and actually check it out. (Take snap-shots for your own record, if you wish.)

The beginning of February is also the perfect time to start executing on your plans for any maintenance- or new construction-activities on any check-dams/farm-ponds/residential water conservation that you might have thought of, in your mind. If you start executing on it now, you still have a very realistic framework of about 4–4.5 months left, before the next monsoon rains are slated to arrive [give or take about a half month here or there].

…Just a reminder, that’s all.

Keep in touch, best, and bye for now…

[As usual, I may come back and edit this post a bit after its publication, say, after a couple of days or so… I don’t know why, but things like that—viz., thinking about what I did happen to write, always happen to me. But the editing wouldn’t be too much. … OK. … Bye [really] for now.]

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# Micro-level water-resources engineering—6: Evaporation

As compared to the last year, public awareness about water resources has certainly increased this year. It has been a second drought-year straight in a row. None can miss it—the water issue—now. [Not even the breweries.]

There are several NGO initiatives involved in the awareness campaigns, as always. Even celebrities, now. Also politicians.

The heartening part this year is that there also is now a much greater participation of the common people.

Indeed, water conservation schemes are these days receiving quite a broad-based support, cutting across all political party-lines. People are actively getting into the building nallah-bunds, farm-ponds, and all. Good.

Good? … This is India, so how can anything be so straight-forwardly good?

With that question mark, I began taking a second look at this entire scene. It all occurred to me during a show that I saw on TV last week or so.

Well, that way, I don’t watch TV much. At least in India, TV has gone beyond being a stupor- or passivity-inducing device; it has become an active noise generator. So, the most I can put up with is only some channel-flipping, once in a while. [In my case it is typically limited to less than 15 minutes at a time, less than 7 times a week]. In one such episode [of flipping through the channels], I happened to catch a few minutes of a chat that some Marathi journos were having with Aamir Khan and Satyajit Bhatkal. [They should have been in awe of Bhatkal, but instead were, of Aamir Khan. [Journos.]]

Both Khan and Bhatkal were being all earnest and also trying to be all reasonable on that show, and in that vein, at one point, Bhatkal mentioned that there have been hundreds (or thousands) of KT-weirs, nallah-bunds and all, which have been implemented by the successive Maharashtra State governments. These are the structures or works which now have become defunct because of a lack of maintenance. Mentioning this point, he then added something like the following: [not his precise words, but as my casual impression of what he effectively was saying]:

For the best or the most optimum utilization of the available money, it would be better to begin with a revival or maintenance (like silt-removal/wall-repairs) of these thousands of the already existing structures, rather than building everything anew, because the latter would cost even more money.

Looks like quite sensible an approach to take, doesn’t it?

Well, yes, on the face of it. But not so, once you begin to think like an engineer about it. In fact, I do want to raise one flag here—one very big, red flag. [No, I am not a communist, just in case you have begun reading this blog only now.]

Let’s look at some hard facts—and also some simplest physical principles—first.

The only primary source of water is: the rainfall.

The two means of conserving water are: (i) surface storage, and (ii) ground-water recharge.

The two big [physical] enemies of water conservation are: (i) run-off and (ii) evaporation.

Run-off means: Rain-water running off the earth’s surface as floods (may be as flash-floods), without getting intercepted or stored anywhere. Evaporation means: the loss of the stored water due to ambient heat.

It’s good that people have gotten aware about the first part—the runoff factor. The by-now popular Marathi slogan: “paaNee aDavaa, paaNee jirawaa” [English: “block water, percolate water”] refers to this first factor. Unfortunately, it has come to refer to only the first factor.

People must also become fully aware about the second factor—namely, evaporation. It too is just as important in India, particularly in places like Maharashtra.

Evaporation is not always an acute concern in the cooler climates (think USA, Canada, Europe, Japan, Australia, New Zealand). But it is, in the hotter climates (think most of the third world). My focus is exclusively on India, mostly on Maharashtra. Since most of the advanced countries happen to lie in the cooler regions, and since in India we habitually borrow our engineering common-sense from the advanced countries rather than developing it individually here, I want to once again stress this point in this series.

As I mentioned in my last post in this series [^]:

“Evaporation is a really bad factor in hot climates like India. At the level of large-scale dams and even for check dams, there is precious little that can be done about it.”

There is a technological reason behind it: You can’t sprinkle some powder or so to cover the surface of a water body, and thereby arrest or slow down the evaporation losses, without also polluting water body in the process.

These days, you often see a layer of water hyacinth in dams/rivers. Thought the plant contiguously covers the water body, contrary to the naive expectation, it in fact accelerates evaporation. The plant sucks water from below and perspires it out via leaves. This rate of perspiration happens to be higher than that of the plain evaporation. Further, water hyacinth has big leaves. The total surface area of the leaves is many times greater than the area of the water body that the plant covers.

But, yes, the simple-minded idea is right, in a way. If instead of the water-sucking water-hyacinth, something else—something chemically inert and opaque—were to cover the water body, then it would cut down on the evaporation losses. People have tried finding such a material, but without success. Any suggested solutions are either not scalable, not economical, or both. That’s why, evaporation is a fact that we must simply learn to live with.

Let me continue quoting from my aforementioned post:

“Evaporation maps for Maharashtra show losses as high as 1.5 m to even 2.5 m per year. Thus, if you build a check-dam with a 3 m high wall, expect to lose more than half of the [stored] water to evaporation alone.

For the same reason of evaporation, most nallah-bunding and contour-trenching works [such as] those typically undertaken under the socialist programs like MNREGA don’t translate to anything at all for storage, or for that matter, even for seepage. Typically, the bunds are less than 1 m tall, and theoretically, water in them is expected to plain evaporate out right before December. Practically, that anyway is the observation! […] It is a waste of money and effort.”

That’s what I had said, about a year ago. It needs to be repeated.

Most people currently enthusiastic about water conservation simply don’t seem to have any appreciation as to how huge (and how hugely relevant) this factor of evaporation is. Hence this post.

To repeat: In Maharashtra, the range of evaporation losses is as high as 1.5–2.5 m. That is, about 5–8 feet, in terms of the height of water lost.

Thus, if you build or repair a nullah-bund that is about 10 feet tall (which is the typical height of a house), then you should expect to lose about 75% of the stored water to evaporation alone. Perhaps even 90% or more. After all, nullahs and rivers typically have a progressively smaller width as we go deeper, and so, the volume of the water body remaining at the bottom after evaporation is even smaller than what a simple height-based calculation tells you.

Coming back to the Khans and Bhatkals, and Patekars and Anaspures: If the small check-dam or Kolhapur-type of bund/weir you are repairing this summer is, say, 7–8 feet high, then what you should expect to see in the next March or April is: a dry river-bed with a few puddles of water perhaps still lingering here and there. Picture a stray dog trying to satisfy his thirst from a puddle that is relatively cleaner from among them, but with a vast patch of a darkish brown, rocky or parched land filling the rest of your visual field. In no case should you picture a large body of clean water extending a couple of kilometers or more upstream of the bund. The fallen rain-water would have got blocked by that bund, sure, but if your bund is only 7–8 feet tall, then all of it would have disappeared [literally] in the thin air through evaporation alone, by the time the summer arrives. [We are not even counting seepage here. And realize, not all seepage goes towards meaningful groundwater recharge. More on it, may be, later.]

Now, the fact of the matter is, many, many KT weirs and bunds, as built in Maharashtra, are hardly even 5–6 feet tall. (Some are as low as just 3–4 feet tall.) They are, thus, not even one (Marathi/Sanskrit word) “puruSh” deep. …

The next time you go for an outing, keep an eye for the bunds. For instance, if you are in Pune, take an excursion in the nearby Purandar taluka, and check out the series of the bunds built by the PWD/Irrigation department on the Neera river. Most of them are just 3–5 feet tall. None is as big as a “puruSh” tall. None ever shows any water left after December. [But don’t therefore go and talk to the PWD/Irrigation engineers about it. These engineers are smart. They will tell you that those are flood-control structures, not water-storage structures. You will thus come back non-plussed. You are warned.]

… In case you didn’t know what “puruSh” means: Well, it’s a traditionally used unit of depth/height in India. It is defined as the uppermost reach of a man when he stands upright and stretches his arms up. Thus, one “puruSh” is about 7–8 feet. Typically, in earlier times, the unit would be used for measuring the depth of a well. [During my childhood, I would often hear people using it. People in the rural areas still continue using it.]

So keep the following capsule in mind.

In most parts of Maharashtra, expect the evaporation losses to be about one “puruSh” deep.

If the water-body at a nallah-bund/check-dam/farm-pond is one “puruSh” deep during the monsoon, then expect its water body to completely dry up by the time the summer arrives the next year.

Therefore, an urgent word of advice:

If you are building farm-ponds or undertaking repairs of any bunds or KT weirs structures this year, then drop from your planning all those sites whose walls are not at least 2.0 “puruSh” tall. [If a wall is 2.0 purush tall, the water body will be about 1.5 purush deep.] Evaporation losses will make sure that your social-work/activity would be a complete waste of money. The successive governments—not just politicians but also social workers, planners, bureaucrats and engineers—have already wasted money on them. Let the wastage stop at least now. Focus from now on only on the viable sites—the sites where the depth of the water-body would be at least 12–15 feet or so.

If the nullah is not naturally deep, and if the local soil type is right, then you may think of deepening it (to a sufficient minimum depth), perhaps with machinery and all.

But in any case, keep the factor of evaporation in mind.

As pointed out in my earlier posts in this series, given the geological type of the top layers in most parts of Maharashtra, seepage is not a favorable option for water conservation planning.

The only exception is the patch that runs across Dhule, Jalgaon through Wardha, Nagpur. There, the top-layer is sufficiently sandy (as in Rajasthan.) Mr. Suresh Khanapurkar has done a lot of seepage-related work in this patch, and groundwater recharge indeed is a viable option there.

But remember: seepage is not viable for most of the remaining parts of Maharashtra (and in fact, it also is not, over very large patches of India). So, if your idea is to build shallower bunds with the expectation that it would help improve groundwater levels via seepage during and soon after monsoon (i.e., before evaporation kicks in the months following the monsoon), then that idea is not so much on the target, as far as Maharashtra is concerned. Engineering for seepage can be viable only if the local geology favors it.

For the general-purpose water conservation, in most parts of Maharashtra, we have to look for storage, not seepage. Therefore, evaporation becomes a more important factor. So, avoid all shallower sites.

In particular, when it comes to farm-ponds, don’t build the shallower ones even if government gives you subsidy for building them (including for the blue plastic sheet which they use in the farm-ponds to prevent the wasteful seepage). If your pond is shallow, it would once again be a waste of money, pure and simple. Evaporation would make sure of that.

That’s all for now, folks.

Yes, I have been repetitive. I don’t mind. I want to be repetitive, until the time that social workers and engineers begin to show a better understanding of the engineering issues involved in water conservation, esp. the factor of evaporation. Currently, an appreciation of this factor seems to be non-existent.

My blogging in the upcoming weeks will be sparser, because I have to re-write my CFD course notes and research related notes, simulation programs, etc. I lost them all during my last HDD crash. I want to complete that part first. So excuse me even if I don’t come back for some 3–4 weeks or more for now. I will try to post a brief note or two even if not a blog post, but no promises. [And, yes, I have now begun my weekly backups, and am strictly following the policy—the notifications from the operating system.]

Bye for now.

[May be one more editing pass, later today or tomorrow… Done.]

[E&OE]

/

# Summer, boredom, city skyline, etc.

Boredom. That’s what my life has become of late. … Boredom. … Pure boredom.

Life is boring.

Nothing interests me. Don’t feel like writing anything.

No, it’s not called a writer’s block. To have a writer’s block, first you need to be a writer. And my problem is that I don’t even want to be a writer. Not even just a plain reader. Both are boring propositions.

Life, somehow, has become boring to that great an extent.

Summers always do that to me.

While at IIT Madras, we (a few friends of mine and I) had begun using a special term for that: (Sanskrit) “glaani.”

Usage pattern:

“Did you work out those lab calculations?”

“Ajit, did you complete those lab calculations?”

“Machchaa…”

The fellow turns around, lethargically. [He, too, doesn’t have much energy left to pursue anything; the heat has been that bad…] … Begins to drag his feet back to his room.

“glaani.” [One attempts some answer, some explanation.]

The fellow does not even care to look back.

The use-case scenario is over.

Currently, it’s summer time, and this year in particular, I am finding it even more lethargy-inducing and boring than it usually is…

Here is an idea I had. I wanted to expand it in a blog post. But since everything has become so summer-ly boring, I am not going to do that. Instead, I will just mention the idea, and let it go at that.

How do you visually estimate the water requirements of a human settlement, say, a city? Say a city with skyscrapers, like Mumbai? (Skyscrapers? In Mumbai? OK, let’s agree to call them that.)

Start with a decent estimate of per capita water requirement. Something like, say, 135 liters/day/person. That is, $1.35 \times 10^2 \times 10^{-3} = 1.35 \times 10^{-1}$ cubic meters. For one year, it translates to $0.135 \times 365 = 49.275 \approx 50$ cubic meters.

An average room in an average apartment is about 10 feet X 12 feet. With a standard height of 10 feet, its volume, in cubic meters, is: $3.048 \times 3.6576 \times 3.048 = 33.98 \approx 35$ cubic meters.

Of course, 135 liters/day is an estimate on a slightly higher side; if what I recall is right, the planning estimates range from even as low as 50 liters/day/person. So, taking a somewhat lower estimate for the daily per capita requirement (figure out exactly how much), you basically arrive at this neat nugget:

Think of one apartment room, full of water. That much volume each person needs, for the entire year.

If one person lives in one room (or if a family of four people lives in a 2BHK apartment), then the volume of that apartment is their yearly water requirement.

Hardly surprising. In the traditional water-harvesting in Rajasthan, they would have single-storied houses, and roughly the same volume for an underground reservoir of water. Last year, I blogged quite a bit about water resources and water conservation; check out tags like “water resources” [^].

So, the next time you look at a city skyline, mentally invert it: imagine a dam-valley that is just as deep as the skyline’s height, containing water for that skyline. That would be the residential water requirement of that city.

Of course, if the population density is greater, if one apartment room accommodates 2, 3 (or even more number of) people (as is the common in Mumbai), then the visualization fails. I mean to say: You then have to imagine a deeper (or wider) dam valley.

… I used to be skeptical of residential water harvesting schemes. I used to think that it was a typical NGO type of day-dreaming, not backed up by hard data. I used to think that even if every 3-story apartment building covered its entire plot area (and not just the built-up area) with a 1 to 2 story-deep tank beneath it, it wouldn’t last for even a couple of months. But when I did the actual calculations (as above), I became convinced of the utility of the residential water harvesting schemes—if the storage is big enough.

Of course, as one often hears these days, if common people are going to look after everything from electricity (portable gen-sets, batteries and inverters), water (residential water harvesting), garbage (composting in the house/terrace garden), even security (gated communities with privately paid watchmen), then what the hell is the government for?

If your anger has subsided, realize that only the last (security) falls under the proper functions of government; the rest should actually be services rendered by private businesses. And if government gets out of every thing but the defense, the police and the courts, the economic progress would so humongous that none would bother reading or writing blog posts on residential water conservation schemes—there would be very competent businesses with private dams and private canals to deliver you clean water very cheaply (also via private trains, if the need be)… But then, I am not going to write about it.  Writing is boring. Life is boring. …. So, just look up Ayn Rand if you want, OK?

… Yawns. Life is boring.

BTW, did you notice that boring also means digging, and I was somehow talking about inverting the skyline, i.e., imagining wells and valleys. Kindaa double meaning, the word “boring” happens to have, and I happen to have used it in both senses, haven’t I?

Oh well. But really, really speaking, I meant it only in the simplest, most basic sense.

Life is boring. … Yawns….

[E&OE]

# Blogging some crap…

I had taken a vow not to blog very frequently any more—certainly not any more at least right this month, in April.

But then, I am known to break my own rules.

Still, guess I really am coming to a point where quite a few threads on which I wanted to blog are, somehow, sort of coming to an end, and fresh topics are still too fresh to write anything about.

So, the only things to blog about would be crap. Thus the title of this post.

Anyway, here is an update of my interests, and the reason why it actually is, and also would be, difficult for me to blog very regularly in the near future of months, may be even a year or so. [I am being serious.]

1. About micro-level water resources engineering:

Recently, I blogged a lot about it. Now, I think I have more or less completed my preliminary studies, and pursuing anything further would take a definitely targeted and detailed research—something that only can be pursued once I have a master’s or PhD student to guide. Which will only happen once I have a job. Which will only happen in July (when the next academic term of the University of Mumbai begins).

There is only one idea that I might mention for now.

I have installed QGIS, and worked through the relevant exercises to familiarize myself with it. Ujaval Gandhi’s tutorials are absolutely great in this respect.

The idea I can blog about right away is this. As I mentioned earlier, DEM maps with 5 m resolution are impossible to find. I asked my father to see if he had any detailed map at sub-talukaa level. He gave me an old official map from GSI; it is on a 1:50000 scale, with contours at 20 m. Pretty detailed, but still, since we are looking for check-dams of heights up to 10 m, not so helpful. So, I thought of interpolating contours, and the best way to do it would be through some automatic algorithms. The map anyway has to be digitized first.

That means, scan it at a high enough resolution, and then perform a raster to vector conversion so that DEM heightfields could be viewed in QGIS.

The trouble is, the contour lines are too faint. That means, automatic image processing to extract the existing contours would be of limited help. So, I thought of an idea: why not lay a tracing paper on top, and trace out only the contours using black pen, and then, separately scan it? It was this idea that was already mentioned in an official Marathi document by the irrigation department.

Of course, they didn’t mean to go further and do the raster-to-vector conversion and all.  I would want to adapt/create algorithms that could simulate rainfall run-offs after high intensity sporadic rains, possibly leading also to flooding. I also wanted to build algorithms that would allow estimates of volumes of water in a check dam before and after evaporation and seepage. (Seepage calculations would be done, as a first step, after homogenizing the local geology; the local geology could enter the computations at a more advanced stage of the research.) A PhD student at IIT Bombay has done some work in this direction, and I wanted to independently probe these issues. I could always use raster algorithms, but since the size of the map would be huge, I thought that the vector format would be more efficient for some of these algorithms. Thus, I had to pursue the raster-to-vector conversion.

So I did some search in this respect, and found some papers and even open source software. For instance, Peter Selinger’s POTrace, and the further off-shoots from it.

I then realized that since the contour lines in the scanned image (whether original or traced) wouldn’t be just one-pixel wide, I would have to run some kind of a line thinning algorithm.

Suitable ready made solutions are absent and building one from the scratch would be too time consuming—it can possibly be a good topic for a master’s project in the CS/Mech departments, in the computer graphics field. Here is one idea I saw implemented somewhere. To fix our imagination, launch MS Paint (or GIMP on Ubuntu), and manually draw a curve in a thick brush, or type a letter in a huge font like 48 points or so, and save the BMP file. Our objective is to make a single pixel-thick line drawing out of this thick diagram. The CS folks apparently call it the centerlining algorithm. The idea I saw implemented was something like this: (i) Do edge detection to get single pixel wide boundaries. The “filled” letter in the BMP file would now become “hollow;” it would have only the outlines that are single pixel wide. (ii) Do raster-to-vector conversion, say using POTrace, on this hollow letter. You would thus have a polygon representation for the letter. (iii) Run a meshing software (e.g. Jonathan Schewchuk’s Triangle, or something in the CGAL library) to fill the interior parts of this hollow polygon with a single layer of triangles. (iv) Find the centroids of all these triangles, and connect them together. This will get us the line running through the central portions of each arm of the letter diagram. Keep this line and delete the triangles. What you have now got is a single pixel-wide vector representation of what once was a thick letter—or a contour line in the scanned image.

Sine this algorithm seemed too complicated, I thought whether it won’t be possible to simply apply a suitable diffusion algorithm to simply erode away the thickness of the line. For instance, think that the thick-walled letter is initially made uniformly cold, and then it is placed in uniformly heated surroundings. Since the heat enters from boundaries, the outer portions become hotter than the interior. As the temperature goes on increasing, imagine the thick line to begin to melt. As soon as a pixel melts, check whether there is any solid pixel still left in its neighbourhood or not. If yes, remove the molten pixel from the thick line. In the end, you would get a raster representation one pixel thick. You can easily convert it to the vector representation. This is a simplified version of the algorithm I had implemented for my paper on the melting snowman, with that check for neighbouring solid pixels now being thrown in.

Pursuing either would be too much work for the time being; I could either offload it to a student for his project, or work on it at a later date.

Thus ended my present thinking line on the micro-level water-resources engineering.

2. Quantum mechanics:

You knew that I was fooling you when I had noted in my post dated the first of April this year, that:

“in the course of attempting to build a computer simulation, I have now come to notice a certain set of factors which indicate that there is a scope to formulate a rigorous theorem to the effect that it will always be logically impossible to remove all the mysteries of quantum mechanics.”

Guess people know me too well—none fell for it.

Well, though I haven’t quite built a simulation, I have been toying with certain ideas about simulating quantum phenomena using what seems to be a new fluid dynamical model. (I think I had mentioned about using CFD to do QM, on my blog here a little while ago).

I pursued this idea, and found that it indeed should reproduce all the supposed weirdities of QM. But then I also found that this model looks a bit too contrived for my own liking. It’s just not simple enough. So, I have to think more about it, before allocating any specific or concrete research activities about it.

That is another dead-end, as far as blogging is concerned.

However, in the meanwhile, if you must have something interesting related to QM, check out David Hestenes’ work. Pretty good, if you ask me.

OK. Physicists, go away.

3. Homeopathy:

I had ideas about computational modelling for the homeopathic effect. By homeopathy, I mean: the hypothesis that water is capable of storing an “imprint” or “memory” of a foreign substance via structuring of its dipole molecules.

I have blogged about this topic before. I had ideas of doing some molecular dynamics kind of modelling. However, I now realize that given the current computational power, any MD modelling would be for far too short time periods. I am not sure how useful that would be, if some good scheme (say a variational scheme) for coarse-graining or coupling coarse-grained simulation with the fine-grained MD simulation isn’t available.

Anyway, I didn’t have much time available to look into these aspects. And so, there goes another line of research; I don’t have much to do blogging about it.

4. CFD:

This is one more line of research/work for me. Indeed, as far as my professional (academic research) activities go, this one is probably the most important line.

Here, too, there isn’t much left to blog about, even if I have been pursuing some definite work about it.

I would like to model some rheological flows as they occur in ceramics processing, starting with ceramic injection moulding. A friend of mine at IIT Bombay has been working in this area, and I should have easy access to the available experimental data. The phenomenon, of course, is much too complex; I doubt whether an institute with relatively modest means like an IIT could possibly conduct experimentation to all the required level of accuracy or sophistication. Accurate instrumentation means money. In India, money is always much more limited, as compared to, say, in the USA—the place where neither money nor dumbness is ever in short supply.

But the problem is very interesting to a computational engineer like me. Here goes a brief description, suitably simplified (but hopefully not too dumbed down (even if I do have American readers on this blog)).

Take a little bit of wax in a small pot, melt it, and mix some fine sand into it. The paste should have the consistency of a toothpaste (the limestone version, not the gel version). Just like you pinch on the toothpaste tube and pops out the paste—technically this is called an extrusion process—similarly, you have a cylinder and ram arrangement that holds this (molten wax+sand) paste and injects it into a mould cavity. The mould is metallic; aluminium alloys are often used in research because making a precision die in aluminium is less expensive. The hot molten wax+ceramic paste is pushed into the mould cavity under pressure, and fills it. Since the mould is cold, it takes out the heat from the paste, and so the paste solidifies. You then open the mould, take out the part, and sinter it. During sintering, the wax melts and evaporates, and then the sand (ceramic) gets bound together by various sintering mechanism. Materials engineers focus on the entire process from a processing viewpoint. As a computational engineer, my focus is only up to the point that the paste solidifies. So many interesting things happen up to that point that it already makes my plate too full. Here is an indication.

The paste is a rheological material. Its flow is non-Newtonian. (There sinks in his chair your friendly computational fluid dynamicist—his typical software cannot handle non-Newtonian fluids.) If you want to know, this wax+sand paste shows a shear-thinning behaviour (which is in contrast to the shear-thickening behaviour shown by, say, corn syrup).

Further, the flow of the paste involves moving boundaries, with pronounced surface effects, as well as coalescence or merging of boundaries when streams progressing on different arms of the cavity eventually come together during the filling process. (Imagine the simplest mould cavity in the shape of an O-ring. The paste is introduced from one side, say from the dash placed on the left hand side of the cavity, as shown here: “-O”. First, after entering the cavity, the paste has to diverge into the upper and lower arms, and as the cavity filling progresses, the two arms then come together on the rightmost parts of the “O” cavity.)

Modelling moving boundaries is a challenge. No textbook on CFD would even hint at how to handle it right, because all of them are based on rocket science (i.e. the aerodynamics research that NASA and others did from fifties onwards). It’s a curious fact that aeroplanes always fly in air. They never fly at the boundary of air and vacuum. So, an aeronautical engineer never has to worry about a moving fluid boundary problem. Naval engineers have a completely different approach; they have to model a fluid flow that is only near a surface—they can afford to ignore what happens to the fluid that lies any deeper than a few characteristic lengths of their ships. Handling both moving boundaries and interiors of fluids at the same time with sufficient accuracy, therefore, is a pretty good challenge. Ask any people doing CFD research in casting simulation.

But simulation of the flow of the molten iron in gravity sand-casting is, relatively, a less complex problem. Do dimensional analysis and verify that molten iron has the same fluid dynamical characteristics as that of the plain water. In other words, you can always look at how water flows inside a cavity, and the flow pattern would remain exactly the same also for molten iron, even if the metal is so heavy. Implication, surface tension effects are OK to handle for the flow of molten iron. Also, pressures are negligibly small in gravity casting.

But rheological paste being too thick, and it flowing under pressure, handling the surface tensions effect right should be even bigger a challenge. Especially at those points where multiple streams join together, under pressure.

Then, there is also heat transfer. You can’t get away doing only momentum equations; you have to couple in the energy equations too. And, the heat transfer obviously isn’t steady-state; it’s necessarily transient—the whole process of cavity filling and paste solidification gets over within a few seconds, sometimes within even a fraction of a second.

And then, there is this phase change from the liquid state to the solid state too. Yet another complication for the computational engineer.

Why should he address the problem in the first place?

If the die design isn’t right, the two arms of the fluid paste lose heat and become sluggish, even part solidify at the boundary, before joining together. The whole idea behind doing computational modelling is to help the die designer improve his design, by allowing him to try out many different die designs and their variations on a computer, before throwing money into making an actual die. Trying out die designs on computer takes time and money too, but the expense would be relatively much much smaller as compared to actually making a die and trying it. Precision machining is too expensive, and taking a manufacturing trial takes too much time—it blocks an entire engineering team and a production machine into just trials.

So, the idea is that the computational engineer could help by telling in advance whether, given a die design and process parameters, defects like cold-joins are likely to occur.

The trouble is, the computational modelling techniques happen to be at their weakest exactly at those spots where important defects like cold-joins are most likely. These are the places where all the armies of the devil come together: non-Newtonian fluid with temperature dependent properties, moving and coalescing boundaries, transient heat transfer, phase change, variable surface tension and wall friction, pressure and rapidity (transience would be too mild a word) of the overall process.

So, that’s what the problem to model itself looks like.

Obviously, ready made software aren’t yet sophisticated enough. The best available are those that do some ad-hoc tweaking to the existing software for the plastic injection moulding. But the material and process parameters differ, and it shows in the results. And, that way, validation of these tweaks still is an on-going activity in the research community.

Obviously, more research is needed! [I told you the reason: Economics!]

Given the granular nature of the material, and the rapidity of the process, some people thought that SPH (smoothed particle hydrodynamics) should be suitable. They have tried, but I don’t know the extent of the sophistication thus far.

Some people have also tried finite-differences based approaches, with some success. But FDM has its limitations—fluxes aren’t conserved, and in a complex process like this, it would be next to impossible to tell whether a predicted result is a feature of the physical process or an artefact of the numerical modelling.

FVM should do better because it conserves fluxes better. But the existing FVM software is too complex to try out the required material and process specific variations. Try introducing just one change to a material model in OpenFOAM, and simulating the entire filling process with it. Forget it. First, try just mould filling with coupled heat transfer. Forget it. First, try just mould filling with OpenFOAM. Forget it. First, try just debug-stepping through a steady-state simulation. Forget it. First, try just compiling it from the sources, successfully.

I did!

Hence, the natural thing to do is to first write some simple FVM code, initially only in 2D, and then go on adding the process-specific complications to it.

Now this is something about I have got going, but by its nature, it also is something about you can’t blog a lot. It will be at least a few months or so before even a preliminary version 0.1 code would become available, at which point some blogging could be done about it—and, hopefully, also some bragging.

Thus, in the meanwhile, that line of thought, too comes to an end, as far as blogging is concerned.

Thus, I don’t (and won’t) have much to blog about, even if I remain (and plan to remain) busy (to very busy).

So allow me to blog only sparsely in the coming weeks and months. Guess I could bring in the comments I made at other blogs once in a while to keep this blog somehow going, but that’s about it.

In short, nothing new. And so, it all is (and is going to be) crap.

More of it, later—much later, may be a few weeks later or so. I will blog, but much more infrequently, that’s the takeaway point.

* * * * *   * * * * *   * * * * *

(Marathi) “madhu maagashee maajhyaa sakhyaa pari…”
Lyrics: B. R. Tambe
Singer: Lata Mangeshkar
Music: Vasant Prabhu

[I just finished writing the first cut; an editing pass or two is still due.]

[E&OE]

# Micro-level water-resources engineering—5

See near the end of this post.

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Today is (Sanskrit) “akshay tritiya.” In the Khandesh area of North Maharashtra (in which the Shirpur town of the famous Shirpur pattern falls), in the local lingo, the day is known as “aakhaaji.” In Khandesh, it is a festival of women visiting their (Marathi) “maaher” (i.e. their parents’ home, or the home before marriage). There are traditional songs in the local “AhiraNi” dialect, and dance of the Gujarathi garbaa style, but played only by women. When I was a school-boy in that region, the dance would be done with “Tipri”s, but as far as I remember, without any dhols (i.e. drums), loud-speakers, or any large-scale organization, even if all the streets of the town would overflow with women playing “Tipri”s. I don’t know what the situation is like today.

Festivals mark days of relief. But otherwise, summer is a time of gruelling hard work for rural women. Maharashtra’s population is already 11.4 crores. Even if you take only 20% population as drought-affected, that makes it about 2 crores. (In the 2013 drought, the estimates were about 3 crores.) That means about 1 crore drought-affected women. So, as a rough estimate, there must be at least about 50–75 lakh women facing water-scarcity in a normal year—e.g., right now! Imagine, some tens of lakhs of women having to daily carry pots on their heads for several kilometers a day, just for fetching water—often only poor quality and soily/brackish water, but something that allows them at least cooking food for their families for their barest sustenance. What can we do to spare them the hardship? Obvious.

Find out cost-effective water resources strategies and solutions that can be within their means, without remaining dependent either on government or even on charity.

* * * * *   * * * * *   * * * * *

I have been browsing a lot of material, but have found that in this area, even some of the simplest questions are so hard to answer.

For instance, the data about the local geology. Or, even the data about local morphology—I mean, maps with contour lines having 1, 2, or even 5 m resolution, and not 20 or 30 m resolution. Digital DEMs with say 5 m resolution are impossible to find, and so, some creative solutions have to be found out. Here, I first thought of an idea, and later on found a part of it mentioned in a Marathi official document for irrigation department that my father gave me. I will write about it, and address many such questions some time later in this series.

In this post, instead, let me touch upon another simple question.

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How much of the fallen rainwater really runs off the ground to the rivers? Why don’t some of the dams fill up every monsoon?

In Maharashtra, Marathwada is the region of the lowest rainfall (about 65 cm/annum). The river Godavari flows through this region. There is a big dam called the Jayakwadi project [^]; the reservoir is called “Naath Saagar;” it is named after the great Marathi poet-saint Eknath Maharaj.

The simple question is this: Why does the Naath Saagar reservoir does not fill up to its full capacity every rainy season?

An easy answer would be to say: “Because the rainfall is deficient.”

Let us see whether, starting from some simple basic assumptions, this answer turns out to make any sense or not. Let’s try to do a quick, back-of-the-envelop estimate for how much water should flow into the Jayakwadi dam every year. (My objective behind working out this simple exercise was to get some kind of a datum for the small check dams.)

The basic source of water is the rainfall. To estimate the total water received via rainfall, we have to know the watershed area of the dam. The Wiki page on the Jayakwadi dam [^] notes the catchment area as 21,750 square km. Referring to the rainfall for the upstream catchment area of this dam [I used the map in the book River Basins of India (p. 66)], I estimate the average rainfall for this region as about 65 cm (which also is the figure quoted by P. R. Pisharoty as noted in an earlier post in this series). So, the total annual water received via rainfall in the Jayakawadi watershed is about 1.41375E10 cubic m. Raghunath’s text on hydrology [^] on page 5 notes that for India’s total annual rainfall water of 370 million ha-m, the total runoff into all the rivers is 167 million ha-m. Thus, the runoff to the biggest river in a basin should be about 45% of the total water received from the skies. Assuming that a similar figure applies here, I get the runoff calculations as the following Python code shows:
 # Assumed data dRainfall = 0.65 # meter, assumed dRunoffCoefficient = 0.45 # for all India dCatchmentArea = 21750.0*1000*1000 # meters # Calculations dRainwaterVolume = dRainfall*dCatchmentArea dEvaporationLoss = dRainwaterVolume/3.0 dRunoff = dRunoffCoefficient*dRainwaterVolume dSeepageIntoSubsoil = dRainwaterVolume - dEvaporationLoss - dRunoff print ("Total Volume: %E, Runoff: %E, Evaporation Loss: %E Seepage: %E" % (dRainwaterVolume, dRunoff, dEvaporationLoss, dSeepageIntoSubsoil)) 

On Ubuntu, open a terminal, type “python” in it, and at the Python prompt (say >>>) copy-paste the above lines, and hit enter. (On Windows, you will have to install a suitable Python environment first.) Or, use the online interactive Python terminal here [^].

Thus, the total quantity of water rushing into the Jayakawadi dam every year should be 6.36E9 m^3 (i.e. cubic meters). The Wiki page on the Jayakwadi dam notes that the total capacity of the dam is just 2.91E9 m^3.

Thus, the total quantity of water flowing into the dam should be about 2.1 times the dam reservoir capacity. The dam should more than overflow every year.

Yet, the dam doesn’t even fully fill up every year—it does so only about 2–3 times in a decade.

Even if we take a lower runoff coefficient, say as low as 0.35 (e.g., to factor in the presence of the relatively smaller dams upstream, and also an increased forest cover—which must be a very unrealistic assumption), and even if we take the annual rainfall in the watershed region to be as drastically low as just 40 cm (i.e. the worst drought situation, because they declare a drought if the rainfall is 20% lower [^], and the average for the catchment area of Jayakawadi is above 65 cm), you should still get some 3.045E9 m^3 of water into the Jayakawadi reservoir—more than enough to fill it up fully.

Indeed, there is a further irony. This dam has already gathered a lot of silt (because it is situated in a relatively flatter region, with more loose soil), and the live storage has gone down by 14% (as per Wiki).

[Incidentally, there has been some criticism that the project was moved 100 km upstream. Chances are, the reservoir then would have covered even a flatter area of loose topsoil.]

All of which means that the Naath Saagar reservoir should fill up and overflow even in the worst drought-hit years.

In practice, it doesn’t.

What gives? Any idea? I have no clue.

There must be something the wrong with the way the run-off calculations are performed—they are going off the mark by some 250%. That is too big an error. Has anyone looked into this aspect more carefully?

Exercise: Undertake the same exercise for the Ujjani dam. It is supposed to supply water to another severely drought-prone region in Maharashtra, viz. that of the Solapur district and the nearby areas. It too doesn’t fill up every year.

Realize that big dams like Jayakwadi and Ujjani have comparatively huge catchment areas. For a check dam, the catchment area (or the watershed area) is very small—and therefore, subject to even wider fluctuations from year to year. This is one sobering point we must keep in mind in our enthusiasm for the micro-level projects.

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The Evaporation Loss, the High Intensity Rains, and Seepage vs. Storage:

As Raghunath’s book [^] shows on page 5, the water balance equation is:

total rainfall = evaporation loss + runoff + seepage into sub-soil.

The item of seepage into subsoil is further split into two parts: (i) a slightly bigger part (53%) of the contribution to moisture (which is the part that is used by the shrubs and the trees in their life-processes; this is the part that is ultimately released to the atmosphere via transpiration), and (ii) a smaller part (47%) of the recharge into groundwater.

Thus, the biggest items here are (1) runoff and (2) evaporation.

This primary importance of the runoff quantity in the overall quantitative scheme was the reason why I decided to check whether the simple runoff factors or calculations are realistic or not. If they were to be OK, I could use them as they are, in my detailed calculations concerning computational watershed modelling.  But as the above example of the Jayakwadi dam showed, at least at a gross scale, the runoff factors are not reliable. Now, even if there are some more detailed (say GIS based) models and micro-models for computing runoffs, I am not sure how reliable they would be. And, if the runoff factor itself is wrong, we are basically regressing back to the stage of empirical data collecting and validation, and so, coarsening out of the micro-models to macro-models (even if using GIS) would be an even more distant a step … Anyway, to proceed further….

For India, the runoff figure is several times higher than the total groundwater recharge.

Further, in the Deccan trap basalt region of Maharashtra, the seepage mechanism is not as efficient as it is in the alluvial soils (for instance, of Aravali region of Rajasthan, or in the Tapi and Purna basins of Maharashtra (the area of the Shirpur pattern)).

Recall Pisharoty’s paper I quoted in my last post in this series [^]. In Maharashtra, half of the annual rainfall occurs within only 15 to 20 high-intensity hours, which occur sometime over only 35–45 days of any actual rainfall.

Thus, in the Deccan trap region of Maharashtra, first there is an overall inefficiency of seepage. It is further compounded worse due to the infrequent high intensity bursts of rains. If the same amount of rainfall were to occur as a slow drizzle over a long period of time, say a continuous stretch of weeks, then such a rainfall pattern would be better conducive to seepage. On the other hand, a sporadic high intensity pattern implies less seepage and more runoff.

Hence, in the Deccan trap regions of Maharashtra, it is the surface storage strategy which is likely to prove better than the underground seepage strategy.

For the above reasons, our solutions should be able to handle arresting the high intensity runoff, for storage.

Next, in India in general, evaporation also is several times higher than the groundwater recharge.

Evaporation is a really bad factor in hot climates like India. At the level of large-scale dams and even for check dams, there is precious little that can be done about it. (Solutions have been sought, e.g., spreading some chemicals on top of the water, but their side effects is a worry.)

Realize that evaporation is a surface phenomenon. Dams with a shallow and wide-spread reservoir (e.g. Jayakwadi) tend to have a relatively higher percentage of evaporation losses, as compared to the deeper dams. Ditto, also for check dams. (That is the reason why the nallah-deepening aspect of the Shirpur pattern makes good sense—provided the cost of excavation is low enough. For the time being, let’s focus on evaporation.)

Evaporation maps for Maharashtra show losses as high as 1.5 m to even 2.5 m per year. Thus, if you build a check-dam with a 3 m high wall, expect to lose more than half of the water to evaporation alone. (The famous bund of the bund-garden in the Pune city used to be actually shallow; it would hold a nice expanse of water simply because the bigger Khadakvasla dam upstream would periodically release water into the river.)

For the same reason of evaporation, most nallah-bunding and contour-trenching works, such as those by Anna Hazaare in Ralegan Siddhi, or those typically undertaken under the socialist programs like MNREGA, don’t translate to anything at all for storage, or for that matter even seepage. Typically, the bunds are less than 1 m tall, and theoretically, water in them is expected to plain evaporate out right before December. Practically, that anyway is the observation! No matter what Anna Hazare might tell you, it is a waste of money and effort.

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Farm Ponds:

Before closing, let me mention farm ponds as an effective storage strategy, apart from check-dams.

One big advantage with check dams as compared to conventional dams is that there is no cost incurred in the acquisition of land, and for rehabilitation of the displaced people. Speaking purely costs-wise, I read somewhere (or heard in Suresh Khanapurkar’s interviews) that about half of the cost of the conventional dams is on just these two counts.

However, in the case of check dams, if the natural depth of the river gorge is not sufficient (try the small software I wrote earlier in this series), then in order to reduce the percentage loss due to evaporation and thus to make the project economical, some extra expenditure may become necessary in deepening the nallahs.

Now, in the Deccan trap region of Maharashtra, since small rivers and nallahs tend to run through regions of hard rocks (the top soil layer can be as thin as just 0.5 to 1 m or even zero, in them), the excavation work to deepen the nallahs can easily prove to be too costly—this is a factor going against the Shirpur pattern. (More on the economics of excavation in check dams, and of farm ponds, in a later post.)

An advantage with the farm ponds, when compared to check dams, is that since they are built in the field, i.e. in a deeper layer of soft soil, deepening the ditch turns out to be much more economical.

On the downside, as compared to check dams, the storage capacity of farm ponds is much smaller. They also eat up what otherwise could have been a productive farm land.

But, as we saw, a deeper water body means lower percentage of evaporation losses.

Thus, overall, costs-wise, there are many oppositely directed factors, and it’s not possible to draw general conclusions. It’s the cost balance that really determines whether a farm pond makes sense in a given location or not, or is it a check dam for storage, or a check dam for seepage. (I will write another post covering the economics of check dams vs. farm ponds vs. conventional dams).

Second, as far as evaporation is concerned, there is an incredibly creative solution which I ran into only today. It suggests that if you cover a farm pond with a floating layer of the used plastic bottles, then the evaporation loss (at least for very small experimental ponds) can be cut by up to 40%! [(1.7 MB .PDF file) ^]. The work has been done at the well-known Vigyaan Aashram at PaabaL near Pune; guess they also have some kind of collaboration with COEP and MIT (USA). Anyway, coming back to evaporation losses, this is a huge, huge advantage at a throw-away price! The suggestion right now is only at a preliminary stage. I think it should be seriously taken up for studies on a larger scale of a realistic pond. But yes, as an engineer, I simply marvel at this idea—it again takes a perceived problem (“Gee, even Indians have started buying bottled water, huh?” and “Now how do we deal with this mess of all this plastic waste!”), turns it around on its head, and provides a cost-effective solution to another pressing problem. Neat!

BTW, the farm ponds need not always get only“naturally” filled, i.e., with the surface-running rain-water falling from the sky on the same field. Sometimes a combination of a lift-irrigation scheme + a farm pond can also be cost-effective.

Further, as has been practically demonstrated at many sites (e.g. in the Ahmednagar district, by actually practising farmers) a farm pond can also be very easily used for farming fish, as a side business (read side income)! Farming for fish requires relatively little labour—mostly, only some aeration (if at all required) and throwing food into the pond regularly (like twice/thrice a week or so), that’s all. Fish is not only very tasty food, it also is a very high quality and easily digested protein.

The side-walls of the farm-ponds can be also be planted with the kind of trees that give lush green shadow while making do with less water demand. A welcome sight, and a welcome spot for rest, on a hot summer afternoon.

Finally, talking of water bodies, trees, and how beautiful and (literally) cool a surroundings they can go on to make, and of side-businesses, and of creativity, here is yet another creative side-business that has come out of a bigger farm pond; check out the Saguna Baug in Neral near Mumbai [^].

* * * * *   * * * * *   * * * * *

Python scripts for predicting the extent to which the Jayakwadi and Ujjani dams should fill, at a given rainfall level. Also, analysis of results, and some comments:

Since writing this post yesterday, I studied more closely the topic of the rainfall–runoff relationships in standard textbooks on hydrology.

There are quite a few models that allow you to calculate the expected runoff volume from the rainfall extent. These are specific to soil types, gradients, type of surface, etc. For Maharashtra, there is a well-known model by Inglis and De Souza (1929); e.g. see p. 180 here [^]. This is an empirical (curve-fitted) model that gives you two separate equations.

For the ghat region:
$R = 0.85P - 30.5$

and for the Deccan plateau:
$R = \dfrac{1}{254} P \left( P - 17.8\right)$

where $R$ is the annual runoff and $P$ is the annual rainfall, both in cm.

Since the formulae seemed to give far lower values for the runoff coefficient, and hence the runoff volume even for the average rains, I decided to write a Python script to find out the extent to which the Jayakwadi (and later, also Ujjani) dam would fill up, given different levels of rainfall.

Here is a link to a zip containing the Python script files and their outputs, in the CSV format [^]. In my code, I calculate the $R$ parameter using both the above equations and take their average. Effectively, I assume that half of the watershed region is of the ghat region, and the other half is of the Deccan plateau. Though the zip file doesn’t show it, there aren’t very glaring differences in the values of $R$ as estimated via the two equations.

The files make it clear that at the average rainfall level of 65 cm in the watershed (i.e. the catchment) region, the Jayakwadi dam is expected to fill only to 89.6%. If there is a drought year and so the watershed region receives some 45 cm rains, this dam would fill only to 21%!! For this dam to fill 100%, an above average rainfall of 67–68 cm would be necessary. Little wonder that the dam has filled only rarely.

The figures for the Ujjani dam are not much different, only slightly different. For instance, it would take 77–78 cm rain in its catchment area for it to fill up. The catchment area of the Ujjani dam does receive a somewhat higher rain, and so, let’s say the normal rainfall there is 70 cm. At this level, the Ujjani dam is expected to fill only to 73% of its full capacity!

There are other methods to estimate runoff too. But given the informal general knowledge about these dams, Inglis and De Souza’s correlations would seem to hold well.

I am no expert in dams design. To my lay engineer’s eyes, these are decidedly wasteful designs. After all, bigger-than-necessary designs imply greater-than-necessary expenditures, too. The Wiki page informs us that Jayakwadi project has cost more than Rs. 10,000 crores by now. … What portion of this huge amount are wasteful?

Among the Maharashtrian “intellectual,” “chattering” etc. classes  (and also among the NRI community, esp. that settled in the USA, esp. in California), it has become a fashion to blame politicians for every conceivable ill concerning water scarcity in Maharashtra.

Do you think that these civil engineering designs were done by politicians? Do you think that, for instance, say Vasantrao Naik, would have knowingly ordered a deliberately bigger and costlier dam, just to score some political high point for himself or his party? (I mention him because the Wiki informs us that the Jayakwadi dam design was finalized when he was the CM. Similarly, the Ujjani dam got designed when he was the CM.)

If you think such things are possible—things like increasing a dam size just to score some political high point for oneself or one’s party—then I would say that you just don’t know the way a typical politician thinks and operates. Yes, even in a mixed economy.

Yes, it’s important for a typical politician in a mixed economy (regardless of the party to which he belongs) to show that he is doing something meaningful, whether something actually meaningful gets done or not; yes, it is possible that given a choice, he would always pick up that choice which benefits his own constituency; yes, it is possible that he might even bring a bit of pressure on the officers to tweak solutions so that his constituency benefits. (They even publicly admit if not boast about such things.)

But a deliberate increase of size of a dam for absolutely no conceivable benefit to anyone? No way. No politician even in a mixed economy—and esp. in reference to a country like India—ever operates that way.

Here, if you say that an increased dam size means an increased budget, and therefore greater bribes to him/his party-men, then I would say, you just don’t understand the system. Even if I grant you the premise that every politician is always on principle on the look-out for kickbacks and bribes, granted that, a typical politician still wouldn’t want to increase a dam’s size, because—and get this right—he doesn’t have to. He can easily use the same amount of the additional (wasteful) budget on some other project without ever affecting the total quantum of his bribe, so why should he insist on making just one dam/project bigger than necessary, at the expense of all other possible dams/projects? If he can build two dams in the same budget—note, the amount of bribe has stayed the same—since he stands to get double the publicity with the same budget-money, he would rather go in for that.

Thus, all this “logic” is simply the smart “white-collared” Indian’s way of saving the “behind” of his own—or of groups of people he regards similar to him—nothing else.

Are bureaucrats and even engineers ever going to admit there might have been some mistakes here? More importantly, how many Indians of the “intellectual” kind are going to be willing to even think of such a possibility? (Even Anna Hazaare’s all-water-vaporizing nallah-bunds seem almost innocuous by comparison; they must have involved relatively smaller amounts, say of a mere few hundreds of crores. In contrast, wasteful big projects like these would involve thousands of crores.)

And, even more importantly, is there anyone willing to have an honest second look about the socialistic nature of the system that produces costly errors of this kind? (Not just costs. Since a wrong datum for the capacity of the dam has been established, now there also are fights: Marathwada people think that if the Jayakwadi dam doesn’t fill up fully, the reason must be that the smaller dams upstream have been criminally diverting water that is rightfully theirs… Think of the bigger and bigger mess it all gets into.)

…Anyway, since I can’t do anything about it, let me wind down on that topic, and instead, let me focus on what I can do.

What this exercise means is that I can use some of these even simple text-book methods to build computational models for the check dams/farm ponds with acceptable enough accuracy; they would be accurate at least to a first-order. (After all, Inglis and De Souza’s second equation shows that a quadratic dependence of the runoff on the rainfall. Also, the other rainfall-runoff models show different kinds of nonlinear relations. So, they should be accurate at least to the first order in further usage.)

One more point before we close. Let me note a couple of good links on the topic of farm ponds. Here they are:

“Farm Ponds: A Climate Resilient Technology for Rainfed Agriculture: Planning, Design and Construction” [(13.1 MB PDF) ^]

“Rainwater Harvesting and Reuse through Farm Ponds: Experiences, Issues and Strategies” [(5.4 MB PDF) ^]

Also, a useful reference on the topic of evaporation: “Potential Evapotranspiration Estimation for Indian Conditions: Improving accuracy through calibration coefficients” [(3.8 MB PDF) ^]

* * * * *   * * * * *   * * * * *

A Song I Like:

[I recently randomly stumbled on a listing of this song, and then listened to it after a long, long time—long enough that reading only through the words, I was not able to place the song; I had to listen to it to “get” it back…  A relaxed tempo, and a beautiful melody by SD. … I don’t know if RD assisted SD for this song or not (this one is from 1963), but going by the orchestration, there is at least a hint of the young RD here, esp. in those interludes of the sax and guitar. I doubt if Dada Burman, in 1963, could have given that much of a freedom to Manohari Singh (an assistant and the probable sax player) sans RD’s presence. The tune, of course, is unmistakably SD’s own. … It’s the kind of a tune which you inadvertently catch yourself humming aloud sometime later, perhaps even a few days later, and it still surprises you, and it still makes you want to re-listen to the song…  Shailendra is at his lyrical best… And yes, it’s Suman Kalyanpur, not Lata.  Enjoy the brilliant simplicity of SD (possibly with a small assistance coming from RD)…]

(Hindi) “ye kis ne geet chheDaa…”
Music: S. D. Burman
Singers: Mukesh, Suman Kalyanpur
Lyrics: Shailendra

[PS: Though the content will not change much, tomorrow, I might come back and add just a few links to some good documents on design/experience/economics of farm ponds that I have downloaded. Done. Also added Python scripts for computing the percentage of dam capacity to which the Jayakwadi and Ujjani dams would fill up, at various levels of rainfall in their respective catchment areas.]

/

# Micro-level water-resources engineering—4

Further Update on 2015.04.13: The debugged version is online.

Here is the zip file for the debugged version [^]. I have updated the link in the main text below, too. The bug consisted of a single change: In the file CCheckDamsSeries.cpp, line 228, it should be dEX1 = dX2 - dEWaterLength; in place of dEX1 = dX2 - dWaterLength;. That’s all. (Copy-pasting codes always introduces errors of this sort.)

What I have now uploaded is only the (corrected) first version, not the entirely rewritten second version (as mentioned in the first update below). Two reasons for that: (i) The first version itself is good enough to get some overall idea of the benefits of check dams, and (ii) I have decided to try Python for the more elaborate and completely rewritten version. The reason for that, in turn, is that I just got tired of compiling the binaries on two different platforms.

That way, I am new to Python, and so, it will take a while before you get the expanded and rewritten version. I am learning it the hard way [^].  May be a couple of weeks or so for the next version… Bye for now.

Important Update on 2015.04.12: The software is buggy.

I have noticed (at least one) bug in the software I wrote (see details below). It came to my notice today, once I began completely rewriting the code with a view to study how the economics would work out at different gradients of the river (keeping all the other variables constant, that is). The bug concerns the calculation of the water volume after evaporation, in each dam.

Please give me a few days’ time, at the most a week, and I will upload a (hopefully) correct and a much better written code.

In the meanwhile, I am keeping the current buggy code at the link provided below just in case you want to debug it or play with it, in the meanwhile. Once the new code is ready, I will remove the current buggy code and replace it with the new code.

* * * * *   * * * * *   * * * * *

The last time, I had suggested an exercise to you. I had not actually undertaken that exercise myself, before writing about it on the blog.

Once I began calculating manually, I realized that the calculations were highly repetitive. I therefore decided to write a quick-and-dirty C++ program about it.

It takes a few input parameters concerning the geometrical dimensions of the highly simplified model river, generates a series of check dams, and calculates the volumes of water that would get stored.

The program also takes into consideration a thumb-rule for the evaporation losses. However, the seepage losses are not considered. That will be quite a different game.

The program also calculates the number of people whose daily personal water needs would be fully satisfied by the available water storage (after deducting the loss due to evaporation, though not by the seepage).

Finally, I also threw in a very rough-and-ready calculation for estimating the costs of building the system of check-dams, and the one-time per-capita cost (for the supported population) for the round the year availability of water (assuming that all the dams do get fully filled up during the monsoon each year).

Let me hasten to emphasize that the cost calculations here are too simplistic. Don’t rely on them; take them as just rough, preliminary and merely indicative estimates.

The cost calculations also do not include any maintenance aspects—which, IMO, is an even more serious drawback for this software. I believe that dam-maintenance must be factored in right at the stage of design—including periodic maintenance for the mechanized removal of the accumulated silt.

Further, costs for lift-irrigation or pumping of water are not included in this program.

Despite these limitations, it has turned out to be an interesting toy to play with!

I am sharing a link to a zip file (stored on Google Docs) containing the source code as well as the pre-compiled binaries for both Windows 7 and Ubuntu 14.04.01 LTS (both 64 bit), here [ (.zip, < 40 kB) ^]. Enjoy!

Things you could check out:

After altering some of the input parameters, I found that the total amount of water available (and hence the population that can be supported, and hence the per-capita expense) is highly sensitive to the depth of the river gorge at the mouth (i.e. at the extreme downstream end, where it joins a bigger river). Realize that this is a very simple model: the volume of the pyramid is directly proportional to the area of the base rectangle, and the fact of the slope restricts the possible storage volume in such a way that the depth of the river bed at the mouth then perhaps becomes the most important parameter in this model.

If you spot some other peculiarities, I would love to hear from you.

* * * * *   * * * * *   * * * * *

These days, I have been discussing these ideas with my father a bit. Not much, but I just passingly mentioned to him that I had written a blog post and that I mentioned about what he had told me about the geology of the Shirpur region.

Next day, he dug out from somewhere the proceedings of an all India seminar he had attended. Here are the details of the seminar: “Modern techniques of rain water harvesting, water conservation and artificial recharge for drinking water, afforestation, horticulture and agriculture,” jointly organized by the Rural Development Department of Government of Maharashtra and the Directorate of Ground Water Surveys and Development Agency, in Pune, on 19–21 November, 1990!

Wow! 1990! The proceedings are by now some 25 years old!

Yet, browsing through it, it first seemed to be how little things had changed. The contents of that seminar a generation ago are almost entirely relevant even today!

… Of course, there must have been some changes. What I got here was only a compilation of the abstracts and not the complete proceedings of all the full length papers. It is difficult to make out the progress (or its absence) looking only at abstracts. … I notice that a lot (even majority) of the papers are mostly of the sort: “This thing needs to be looked into” or “We have begun this study,” or “this approach seems to be promising.” Concrete, quantitative results are rare in the book. May be that’s the reason why the material looks very “modern” even today.

Other noticeable points: Only one or two papers make reference to GIS or material generated by GIS, or to the satellite imaging/remote sensing technologies. None provides any kind of a computational modelling. All the diagrams are drawn on paper—not computer generated. The book itself was printed, not produced via desktop publishing.

There was a participant from a foreign country—a lone foreign participant, I think. His affiliation was with the Cornell University, USA.

The title of this paper was “Optimization techniques to study the impact of economic and technical measures in recovering aquifers polluted by farming activities” (italics mine).

Even in the abstract, the author felt it important to highlight this part: “the importance of a government body which assumes a key regulatory role in managing the quality of the aquifers cannot be understated” (italics mine).

Immediately later, he also simply added, as if it were an unquestionable kind of a statement: “Both economic and technical measures are at the disposal of the government” (italics, once again, mine).

The author had grandly concluded his abstract thusly: “A theoretical model is developed that may assist the government in determining proper policies under various conditions of economic priorities as well as under different scenarios for relative price ratios between inputs and agricultural production” (italics emphatically are only mine).

The more things change the more…

BTW, any one for the idea that participation from Ivy League schools uplifts the quality of Indian conferences?

It’s a 140 pages book, and I haven’t finished even browsing all through it. My father gave it to me only yesterday noon, and, as you know, I have been writing this program since yesterday afternoon, and so didn’t find much time for this book.

However, I did notice one very neat abstract. So neat, that I must share it fully with you. It forms the content of the next section.

* * * * *  * * * * *   * * * * *

“Indian Rainfall and Water Conservation,” by P. R. Pisharoty, Professor Emeritus at Physical Research Laboratory, Ahmedabad.

Abstract

The average annual rainfall over the plains of India is 117 cm. The average for all the lands of the World put together is only 70 cm. per year.

In Maharashtra, 80% to 95% of the annual rainfall occurs during the monsoon period June to September. And that occurs in 85 days over the Konkan and in 35–45 days over the rest of Maharashtra. The monsoon rainfall over Konkan is 270 cm., Vidarbha 95 cm., Madhya Maharashtra 77 cm., and Marathwada 65 cm. Half of this amount (outside Konkan) falls in 15 Hours to 20 hours distributed within those 35–45 days. Being of high intensity, 3–5 cms. per hour, this half amount of total monsoon rainfall runs off the ground causing floods and much soil erosion.

This is our problem—particularly in the non-coastal Maharashtra. Only 35–45 days of any significant rain in the whole year, that too confined to the period June to September, half of the rain coming down with great intensity and running off the ground causing flood and much erosion.

We need innovative water conservation methods. We have to draw on our ancient wisdom. The characteristics of the rainfall in the European Countries and in north America are different. Their rainfall is distributed throughout the year and their intensities are not as high as those of Indian rainfall.

Construction of a very large number of water ponds, each a hectare or so in area and about 10 metres deep is one such method. It can be supplemented by check dams, underground check dams, etc. There are other water harvesting methods adopted in areas where annual rainfall is 20–30 cm. or less. Maharashtra is not that bad.

* * * * *  * * * * *   * * * * *

[In the above reproduction, I have kept the typos (15 Hours to 20 hours), the mistaken convention for writing physical units (cm. instead of cm) and the italics emphasis exactly as in the original.]

Honestly, which one of the two abstracts you liked better? Why? What kind of epistemological issues seem to be at work?

* * * * *  * * * * *   * * * * *

A Song I Like:
(Hindi) “ni sultaanaa re…”
Music: R. D. Burman
Lyrics: Majrooh Sultanpuri

[E&OE]

# Micro-level water-resources engineering—3

The deccan trap basalt as the most widespread feature of the geology of Maharashtra:

The geological map for India shows a large uniform portion for the deccan plateau. It consists the hard basalt rock, and not soft or sandy alluvial soils. The deccan trap basalt portion goes over Maharashtra, MP, Karnataka, and the adjacent areas from other states. (To my surprise, it seems that the geologists do not include the south Karnataka region in the same deccan trap basalt region.)

As far as regions of water-scarcity go, there is a very wide continuous band in India. Take India’s map, and mark two slanted lines: the top one going across Rajasthan, MP, Orissa, and the bottom one going across Gujarat, Maharashtra, Karnataka, Telangana and AP, even Tamil Nadu. Statistically speaking, the greatest number of the most severe droughts seem to occur in the regions falling in between these two lines.

The area of my interest is in Maharashtra. The worst drought-prone regions of Marathwada, South Maharashtra and parts of Vidarbha and Western Maharashtra all fall in between those two lines.

If Maharashtra is seen at a large, national, scale [say, 1 cm:100 km], the topmost geological layer is comprised mostly of the deccan trap basalt.

The water-seepage characteristics of the deccan trap basalt:

Speaking in general terms, if you take, say, a 10 cm X 10 cm X 10 cm cube of basalt, you will find it to be a hard, impermeable rock. You might therefore conclude that it is not very easily conducive to groundwater seepage.

However, when viewed at a larger scale, even a top-layer of basalt is not uniform either in composition or in shape (i.e. in terms of its surface morphology). First of all, there are inhomogeneities introduced and fissures formed right at the time of formation of these geological layers aeons ago. Then, there are earth-quakes, introducing cracks and fissures. Further, there also are some very slow processes that nevertheless make their effects felt over the geologically long time-scale of tens, even hundreds of thousands of years.

Due to the inhomogeneity of their composition and morphology, the daily thermal expansions and contractions experienced by the surface layers of rocks are inhomogenous. These inhomogeneities lead to thermally induced mechanical stresses. Over the geological time-scale, the repeated thermal stresses result in local fractures, especially near the surface (where the temperature gradients are the greatest). Further, the mechanical effects of erosion due to water flow leads to deposition of sand; it also serves to erode the fissure openings. The chemical action of dissolved minerals and chemicals lead to enlargement of fissures and opening of cavities at surface as well as deeper layers. Even in a nominally hard rock like basalt.

Thus, due to fracturing and weathering at the surface layers, if you consider relatively bigger patches, say those at the scale of, 10 m to a few hundreds of m (or bigger), even a top layer of a nominally hard rock like the basalt, can begin to act like the more permeable alluvial layer.

Since the cracks are highly irregular and elongated, percolation from a surface water body into the deeper underground layers is highly inhomogeneous and anisoptropic.

In the above discussion, we have considered the seepage from the surface layers. As far as the underground flow through aquifers goes, there is a presence of local sub-layering within an overall top layer of basalt. Further, fissuring and cavitation also has occurred deeper underground. Therefore, local underground aquifers are observed to exist even within an overall basalt layer. Such aquifers often are quite directional, and not too criss-cross. Hence, anisotropy (or directionality) to the local underground flow is only to be expected.

As an example of a locally restricted fracturing/fissuring, observe the groundwater falling over the passing trains and buses in the tunnels of the Khandala ghat on the Mumbai–Pune routes. (BTW, in case you have ever wondered whether these fissures/fractures pose risk, don’t worry!  Their presence is already factored in, while designing for tunnels—fracture mechanics, by now, is a fairly well understood technique.)

One notable reference here is by Prof. Deolankar of Uni. of Pune: Deolankar, S. B. (1980) “The deccan basalts of Maharashtra, India—their potential as aquifers,” Ground Water, vol. 18, no. 5, September–October 1980, pp. 434–437 [(.PDF) ^]. Note the comparisons to the basalt layers elsewhere, and the quantitative estimates for parameters such as porosity, yield, transmissivity and specific capacity.

To conclude, (i) a top layer of basalt layer also allows for seepage of water, even if (ii) the effect varies greatly from place to place (due to the inhomogeneity of fracturing) and the flow is directional (due to anisotropy).

Therefore, groundwater seepage, and therefore artificial groundwater recharge work, appears feasible even in the deccan trap region of Maharashtra. However, it is only to be expected that the seepage aspect won’t be as pronounced as in the regions having a sandy alluvial top layer.

The importance of the local geology:

Due to the local inhomogeneity and anisotropy, there also arise certain difficulties or challenges.

The main difficulty is that unless a detailed geological study of the local hydro-geology is carefully conducted, it would be impossible to tell whether any underground water recharge work would at all be feasible in a given village or not.

Artificial groundwater recharge work may lead to very impressive results in some village or a cluster of villages, but it may not at all give economical returns even in some nearby  villages—even if all of them fall under the same governmental administrative unit of a taluka (or even a block). [The same Collector; the same Block Development Officer! … Two results! (LOL!)]

Thus, in Maharashtra (and similar regions), it becomes crucially important to know what kind of local geology there is—the surface geology, as well as the geology and morphology of the underground strata.  The depth to which these features should be known would vary from place to place; it may range from 10 m to even hundreds of meters.

Unfortunately, the geological surveys in the past were conducted only at much grosser scales. The relevant geological data at the micro-level of villages (i.e. covering just 5 km X 5 km areas) are simply not available.

If experts (say GSA) are asked to conduct such surveys at the micro-level for the entire country, it would be a very time-consuming and costly process.

However, realize that what you need for the water-conservation work is not the most elaborate kinds of surveys. You don’t need surveys of the kind that GSA or the mining engineers make. You aren’t really interested in things like detailed rock-compositions, percentages of minerals, etc. Your main interest is things such as: what kind of strata run where underground, what kind of intermediate layers occur in between the layers of hard rocks and at what depths, the depth and the direction at/in which the local fissures and aquifers run, whether a given fissure extends up to surface or not, etc.

Some of this data (concerning the local geological strata) can be gathered simply by observing the traditional wells! Often-times, the wells are either not at all covered with walls, or even if there is a masonry work, it does not extend beyond a certain depth, and so, the underground layers stand adequately exposed at the traditional wells. Other data can be had by observing the exposed surfaces of nallahs, rivers, hill-sides, etc.

And, of course, data about the local underground strata can always be had by drilling observation bore-wells (though it would be a costlier method).

The economic relevance of computational modelling:

In places like Maharashtra, since the groundwater seepage, flow, and water-holding characteristics crucially involve local variations and directionality, 3D computational models should prove to be of definite use.

Use of 3D computational models would not only streamline the collection of data, it would also lead to far more accurate predictions concerning economic feasibility of projects—ahead of spending any money on them.

A case in point, here, is that of a small check-dam built at the initiative of the IIT Bombay alumni. More details can be found at the CTARA Web site. As a measure of the difficulty in making predictions for underground water flow, notice that in spite of certain geological studies (of conductivity measurements etc.) conducted by the IIT Bombay experts prior to building of this check dam, it still has not resulted in any enhanced ground-water seepage downstream. Chances are, if a 3D model were to be built by drilling observation bore-wells, either a significant amount of money could have been saved, or deployed at a more suitable location.

An apparent counter-case in point is that of the success of the Shirpur pattern, at its original location, viz., near Shirpur (where else?). No detailed micro-level 3D computational modelling was conducted for it. Still, it was successful. How come?

The local geology of the Shirpur region as not being representative of the entire state of Maharashtra:

As it so happens, my father, a retired irrigation engineer, had worked in the Shirpur area. (I thus happened to have had a considerable stint of my school education in and around Shirpur.) I had discussed the issue with my father quite a few years ago. From whatever I now recollected, he had mentioned that the local geology there indeed was more conducive to underground seepage. There were sandy soils at the top level, and some hard rock well underneath. Both these factors lead to better seepage characteristics. The strategy of deepening and widening of the nallahs, as followed in the Shirpur pattern, therefore is a good strategy. As to the rest of Maharashtra, the local geological characteristics differed, he had mentioned it.

[I guess we had this conversation some time in 2007 or 2008. I have been having this idea of not getting discouraged if there is no water at a bore-well location, but instead turn the situation on its head and use the out-coming data regarding the underlying geological strata, to build better predictive computer models at a very fine level of granularity. I have been having this idea since at least 2008, and so, our conversation must be that old. As to the appreciation of having to carefully build 3D models, I owe it to my training in materials engineering, in particular, stereology.]

Anyway, in the recent weeks, I therefore checked the local geology for the Shirpur region, consulting some of the references listed in my earlier post in this series. It turns out that the depth to the water level near Shirpur is at roughly 20–30 m bgl (i.e. below ground level); see ref. here: Aquifer Systems of India, Central Ground Water Board, Plate XXVII on page 58 [(34 MB) pdf ^]. Now, this is a region through which Taapi, a major river, flows. As any school-boy in Shirpur would know, the river has enriched the top layers with a rich black soil. What is the official geological nature of this top layer? Turns out that it is “alluvial.” The black soil does not have the best permeability. However, in the Shirpur region, the alluvial deposits also are sandy in nature, esp. as you go below a certain depth (of 1 m to a few meters). Next, check out the distinctive yellow patch of the alluvial region in this map, standing in sharp contrast to the green patch for the basalt layer for the major parts of Maharashtra [(370 kB pdf) ^].

A top layer of alluvial soil, esp. if deeper than 10 m, if it is then also supported underneath by a highly impervious layer (e.g. basalt in Maharashtra), then the approaches that seek to enhance ground-water seepage do make good sense.

In contrast, if there is a top layer of basalt itself, then, in general, it is less conducive to groundwater seepage; it is more conducive to construction of check-dams for water storage (as in contrast to water percolation/seepage), or for the Kolhapur-type weirs for both storage and redistribution, etc.

As an inevitable conclusion, the local geology holds very important implications for selection of effective water conservation strategies.

Naturally, you can’t just go ahead and apply the Shirpur pattern everywhere in Maharashtra.

“Give me the funds for a few Poclains per taalukaa, and I will make everything green,” is a statement therefore strongly reminiscent of “Give me a place to stand and with a lever I will move the whole world.” The point is not that the whole world won’t be moved; the point is the natural difficulty in providing the guy with a place to stand (complete with air to breathe etc.), not to mention the engineering difficulty of supplying him with a strong enough, and long enough, a lever. And, of course, the difficulty of arranging a place to keep the fulcrum of that lever.

Dramatic statements, both!

I will go ahead, stick my neck out, and say that the Shirpur pattern—inasmuch as it incorporates the seepage mechanism as a strategy—is not likely to be the most optimum solution at any places other than in the Tapi and the Purna river regions! Check out the map if you have not done so already [(370 kB pdf) ^]!

The idea of small dams as storage—and not seepage—devices:

Come to think of it, then, with all the due qualifications—i.e., speaking only in general terms, and only for most parts of Maharashtra (not all), and ignoring any fracturing present in the local geology—the idea of small-dams or check-dams as storage devices, rather than as a seepage devices (or as a groundwater recharge devices), has begun to make much better sense to me. …

[… Yes, the famous government-funded Poclains, and the government-funded work to be contracted out to some of the local parties, and the government funds to be timely released only to some of those parties…. The whole she-bang does stand to be applied also here; more on it, later, if at all necessary. …]

…For the time being, here is an exercise for you.

Exercise:

Take a smallish river (or a bigger nallah), say, 50 km (or 10 km) long. Build an enormously simplified geometrical model of the river, by assuming a rectangular pyramid for its water-carrying volume.

Thus, ignore all the bends in the course of the river and instead assume that the river looks like a long, acicular triangle in the plan (i.e. in the top view). Further, assume that the vertical cross-section of the river remains rectangular throughout; it goes on linearly increasing in area from zero at the origin of the river to a certain value at the end of the river.

Assume typical figures for the dimensions of the river/nallah: how about a vertical cross section that is 50 m wide and 2–3 m deep at the mid-length of the river (i.e. 25 km downstream from the origin)? Assume also a suitable slope for the river, so that water does indeed flow downstream: how about a fall in the height of the ground level of, say, 50 to 100 m, over its 50 km length?

Now, if a series of check dams were to be built on this “river” such that they would submerge some 75% of the total river area present in the plan view into water-holding areas, calculate how much total volume of water would be made available. Compare this volume to the storage capacity of a single conventional dam known to you. …

[While making your calculations, realize (i) that the max. height of the dam cannot exceed the depth of the river bed (because only the river area would go under water), (ii) that the bottom of the river slopes down, and therefore (iii) that the depth of river bed below the water surface goes on decreasing as you go upstream from the check dam location, coming to zero at some location upstream. The third factor severely delimits the total volume of water that can be held via the series of check dams.]

To put the water volume in context, assume that the per-capita consumption for daily individual consumption is some 135–150 liters. Using this assumption, determine the size of the town/city whose needs could be met by this series of check dams. (Note, this figure does not include demand for agriculture and industrial usages.)

Then, consult a practising civil engineer and find out the current cost of construction of all these check dams. Compare this cost with that of a single conventional dam.

Think about any advantages the series of check dams may have; consider water distribution, flood control, and sedimentation and maintenance aspects.

Include the costs of canal construction in the conventional approach. Include the costs of lift-irrigation schemes in the check-dams approach.

Include the fact that since check-dams won’t have a great height (say 2–4 m), the evaporation losses (estimated at about 20–30% in the conventional dams) may even lead to this circumstance: all the water in a check dam plain evaporates in the thin air even before the next summer season approaches. Realize here that, as a rule of thumb, evaporation losses over the eight non-monsoon months are as high as about 1.67 m of height loss per square m of the average of top and bottom surface areas in the plan. [To help put this figure in some kind of a context, the average annual rainfall in Maharashtra is about 110 cm—if no rainwater were to be lost to seepage, runoff or evaporation, and if all of it could be collected, a tank with a square meter of bottom surface area would hold a water body 1.1 m tall.]

Include the economics of maintenance and mechanization in the regions where there is no traditional “Rajasthan culture” of water conservation, but instead people expect government to bring them everything wherever they are.

* * * * *   * * * * *   * * * * *

I will come back later with some further notes and observations (including those on software) on this topic of micro-level water-resources engineering. In particular, I want to make a few notings related to the GIS software. However, I belong to those old-fashioned kind of engineers who, in their practical life (as in contrast to their avatars in blogosphere, for instance) always first do a quick back-of-the-envelop calculation before they switch on a computer to do any computational modelling. If you are like me, you should finish the above exercise first, so that the exploration of software is better grounded in reality.

* * * * *   * * * * *   * * * * *

A Song I Like:
(Marathi) “gangaa aali re, angaNi”
Music: Datta Davajekar
Singers: Jayawant Kulkarni, Sharad Jambhekar, Govind Powale, H. Vasant, Aparna Mayekar

[Minor updates done right on 2015.04.08 after posting the very first version. Guess I will not make any significant revisions to this post any further. May come back and correct typos and grammatical streamlining; that’s all—no new points.]

[E&OE]

# Micro-level water-resources engineering—2

As mentioned in my last blog post, I have been browsing material on the title subject.

In this post, let me note down a few informative links that I have (only) browsed (but not completely read through) thus far. I will come back to my own notes and observations (based on them) in the subsequent posts. BTW, I intend to keep this post as a catch-all thing: whenever I find a new interesting link, I will come back and note it here, without separately mentioning update dates and all. (I think I will also consider converting this post into a separate page of this blog or my personal Web site.)

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Portals:

India Water Portal [^] (Web sites like these are, IMO, better than novels in English 🙂 )
Rainwater Harvesting [^]

Government and Public Sector Portals/Sites:

IMD: [^]

IITM: [^]

Central Groundwater Board:  [^]. This is a big site/portal. So, let me note down the links to some specifically relevant parts of it:  Downloads [^], Watershed [^], Aquifer Systems of India (and a few states) [^], Groundwater Yearbooks [^], Groundwater Scenario in India [^].

The World Bank funded projects in India, phase I and II: [^][^]

A popularization kind of a book on Rajasthan’s water culture: [^]. Incidentally, it is through this book that I came to place Rajendra Singh’s work in a better context. The last time I had wondered why Singh didn’t go 400 km West. This book clarified the matter to me.

US Dept of Agriculture Report: Technical Guide to Managing Ground Water Resources [(.PDF) ^]

Groundwater Manual [^]

A book at the US GS site: [^]

A research group at CTARA, IIT Bombay: [^]. Reports and Course Materials at [^],  [^],  and [^]

A research group at IISc Bangalore: [^]. An example of a project they are carrying out: [^]

A private research cum consulting group from Pune (with many academic projects conducted with the Geology Dept. of S. P. University of Pune, too): [^]

CP Kumar’s links on hydrology [^] and on hydrology resources [^]. He works at the National Institute of Hydrology: [^]. There is a learning package for hydrology for the beginners, too: [^]

Indian Association of Hydrologists [^]

Software:

Hydrology Software:

Lists of software maintained at the USGS site, in general [^], and for groundwater in particular [^].

A proprietory software developed for use by the government agencies in India [^]:

Open-source GIS software:

Wiki list [^].

The following two seem to be more general purpose and/or leading; they also are multi-platform: QGIS (I think IIT Bombay people use it) [^], and GRASS [^].

An open-source GIS software on Windows (.NET) platform: [^]. US EPA uses it: [^]. I installed and tried it, but the documentation seems to be lagging behind the software.

ParFlow: [^]

List at the GIS Lounge: [^]

Rainfall and Its Measurement:

Annual rainfall animation [^]. Check out the animated GIF [^]. A surprise: check out the low rainfall area which the animation shows for the Konkan region. That is because while creating the animation, they coarse-grained the data. There are unexpectedly low-rainfall region even in Konkan, but these are rather isolated. Once again highlights the importance of the local data. But, it’s entertaining anyway.

Another royal entertainment (reduce your computer’s volume before hitting the link): [^]. Then, to see the actual action, hit the “Play the whole sequence” button. (This is one of the rare times that you would wish you had an Intel 386.)

Just in case you want to keep a record of the rainfall in your area, in India, we follow these specs  [(.PDF) ^].

In case you didn’t know, 1 mm of rainfall at a point means “A 0.001 m3, or 1 litre of water to each square metre of the field” [^]. … 1 cm of rainfall is ten times that number.

Exercise:

On the Internet, look up the area of a state, district, taluka, or city; look up its average annual rainfall; then find the total quantity of water (in litres) it receives via rainfall in a typical year.

Then, also do searches and find out data about its total water demand. Also, find out its current water availability, and the short-fall in the supply.

Trivia:

The average annual rainfall for India is about 70 cm in monsoon alone, and about 110 cm for the entire year (including the non-monsoon rains, snow-fall, etc.) (Source: [^]. Also see: [^]).

Floods and droughts still visit India every year.

The average annual rainfall in Jaisalmer is just 16.4 cm (less than one-fifth of that at Delhi), and all of it is received over only 10 days. (Yes, statistically speaking, as many as 355 days in a year go completely dry there.) The water-table depth there is really bad; it ranges between about 40 to 80 m (i.e., about 125 to 250 feet) [^].

Jaisalmer nevertheless has a huge lake that would supply water to the city [^] all through the year—the lake would not go dry even in summer! This lake: Image [^], video [^].

No, that lake doesn’t get its water supply from a river or groundwater sources; there is in fact no mountainous or hilly region around it. The only source of water for this lake is: an ingenious scheme for rainwater harvesting. A scheme that is almost 7 centuries old.

Now, go, figure how wasteful—and flood-hit—and water-scarce—the rest of us manage to remain even today.

* * * * *   * * * * *   * * * * *

A Song I Like:
(Marathi) “ye re ghanaa ye re ghanaa…”
Music: Hridaynath Mangeshkar
Lyrics: Aarati Prabhu
Singer: Asha Bhosale

[E&OE]

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