1 00:00:05,710 --> 00:00:11,090 Welcome! My name is Hubert Savenije and I am a hydrologist. 2 00:00:11,090 --> 00:00:17,140 We have seen that the hydrological cycle has no start and no end, but generally we say 3 00:00:17,140 --> 00:00:21,140 that the terrestrial cycle starts with the precipitation 4 00:00:21,960 --> 00:00:26,300 There are many different types of precipitation, besides rainfall 5 00:00:26,310 --> 00:00:31,530 There is of course snow and hail, which is the frozen form of rainfall 6 00:00:31,720 --> 00:00:37,760 Dew is formed by cooling (generally at night as a result of outgoing long wave radiation) 7 00:00:38,899 --> 00:00:42,039 While white frost is frozen dew 8 00:00:42,039 --> 00:00:48,620 But there is also glaze ice (or simply glaze), which is undercooled rain that turns into 9 00:00:48,620 --> 00:00:51,539 ice as it hits a cold surface. 10 00:00:51,539 --> 00:00:58,249 I remember that as a child I could skate on the road. 11 00:00:58,249 --> 00:01:04,260 Dew and white frost find their origin in the near ground humidity of the air, 12 00:01:04,260 --> 00:01:09,520 It is formed when the Earth’s surface cools until the dew point. 13 00:01:09,520 --> 00:01:15,030 Just like we saw in the saturation vapor pressure curve in the previous section. 14 00:01:15,030 --> 00:01:21,659 But rainfall, snow and hail (as everybody knows) fall from the clouds. 15 00:01:21,659 --> 00:01:25,500 How is this process triggered? 16 00:01:25,500 --> 00:01:31,960 As in the case of dew, droplet formation is governed by the saturation pressure curve 17 00:01:31,960 --> 00:01:36,689 Clouds are formed by super-saturation, which happens when moisture is cooled below the 18 00:01:36,689 --> 00:01:39,289 dew point 19 00:01:39,289 --> 00:01:42,759 Cooling is causes by the lifting of air: 20 00:01:42,759 --> 00:01:48,109 As a volume of air is lifted, the pressure drops, and hence the temperature. 21 00:01:48,109 --> 00:01:53,990 The average lapse rate is 6.4°C/km elevation. 22 00:01:53,990 --> 00:01:59,730 Condensation requires little crystals or dust particles for nucleation. 23 00:01:59,730 --> 00:02:08,270 Turbulence causes the droplets to grow, as drops move up and down, and collide with other droplets 24 00:02:08,560 --> 00:02:16,520 until they are too heavy to be sustained by turbulence (or uplift) and drop to the ground 25 00:02:17,700 --> 00:02:19,940 So we see that cooling is essential, 26 00:02:19,940 --> 00:02:26,040 And we also noticed that clouds are formed by rising air. 27 00:02:26,040 --> 00:02:28,410 What can be the causes of rising air? 28 00:02:28,410 --> 00:02:35,160 There can be several; and all of them have different characteristics: 29 00:02:35,160 --> 00:02:39,560 Convection by thunderstorms …….. 30 00:02:42,320 --> 00:02:47,580 Orographic effects near mountain ranges ………. 31 00:02:51,290 --> 00:02:57,650 and then we have Tropical cyclones, hurricanes or typhoons 32 00:02:57,650 --> 00:03:02,380 Do you know what the difference is between them? 33 00:03:02,380 --> 00:03:06,760 There is no difference. It is just that their names are linked to the different oceans that 34 00:03:06,760 --> 00:03:08,310 generate them: 35 00:03:08,310 --> 00:03:15,310 the Indian Ocean has cyclones, the Pacific has typhoons, and the Atlantic has hurricanes. 36 00:03:16,020 --> 00:03:23,020 Here you see a movie of the Hurricane Katrina, which caused havoc in New Orleans. 37 00:03:23,810 --> 00:03:27,830 And then there are the monsoons, governed by the difference in cooling between land 38 00:03:27,830 --> 00:03:34,560 and ocean in the Tropics, causing sea breezes that carry moist air inland 39 00:03:34,560 --> 00:03:41,080 In temperate areas there are depressions that cause cold and warm fronts to rotate over land 40 00:03:42,230 --> 00:03:48,250 Because cold air is heavier than warm air, a cold front forces itself under warm (and 41 00:03:48,250 --> 00:03:54,840 moist) air, causing an uplift, which can trigger heavy thunderstorms. 42 00:03:54,840 --> 00:04:01,640 A warm front generally moves over the colder air and triggers less intensive rainfall 43 00:04:01,640 --> 00:04:07,950 As a result, we see very different amounts of precipitation distributed over the world. 44 00:04:07,950 --> 00:04:14,950 From very large amounts in Cherrapoongee, at the foot of the Himalayas, and fed by monsoons, 45 00:04:15,180 --> 00:04:21,329 to very small amounts in the arid zones of the Arabian Peninsula. 46 00:04:21,329 --> 00:04:24,020 It is fun to look at the world records of precipitation. 47 00:04:24,020 --> 00:04:32,620 Here we plot the maximum depths of precipitation recorded in the world as a function of their duration. 48 00:04:33,490 --> 00:04:37,870 We see that the orographic lifting in the foothills of the Himalayas, under the influence 49 00:04:37,870 --> 00:04:44,080 of the monsoons triggers the highest amounts of long duration rainfall. 50 00:04:44,080 --> 00:04:52,280 A maximum of about 20 m/yr in Cherrapoongee. Just try to imagine how much rainfall that is. 51 00:04:53,919 --> 00:05:00,919 The tropical cyclones cause the largest amounts on a daily time scale. In La Reunion (Indian 52 00:05:01,160 --> 00:05:10,300 Ocean) we recorded about 2m/day . You could drown by just standing in the rain on a flat terrain! 53 00:05:11,539 --> 00:05:18,050 At shorter time scales, we go to the thunderstorms. We have a world record of about 200 mm/10 54 00:05:18,050 --> 00:05:26,150 min in South Germany and on Jamaica. Imagine that a bucket standing in the rain would fill 55 00:05:26,150 --> 00:05:29,180 up with water in 10 minutes. 56 00:05:29,180 --> 00:05:36,050 Of course not all places in the world can have these records. The second line corresponds 57 00:05:36,050 --> 00:05:39,860 with the records of UK rainfall 58 00:05:39,860 --> 00:05:45,620 And in The Netherlands , where I am from, we have very modest amounts of rainfall compared 59 00:05:45,620 --> 00:05:53,680 to other places in the world, (indicated by the stars) yet I have the feeling that it 60 00:05:53,689 --> 00:06:00,689 rains a lot here in The Netherlands: we have 180 raindays per year ! 61 00:06:02,099 --> 00:06:04,370 How do we measure precipitation? 62 00:06:04,370 --> 00:06:06,080 There are many devices. 63 00:06:06,080 --> 00:06:11,550 The most traditional is the regular funnel shaped tube which you empty once per day. 64 00:06:11,550 --> 00:06:17,370 You read the volume, divide it by the surface areas and record the amount of rainfall per day. 65 00:06:18,379 --> 00:06:25,379 Other devices make use of weighing, optics, acoustics or a tipping device 66 00:06:26,120 --> 00:06:33,620 This is such a tipping device. When on side is full, it tips and then the other side fills, etc. 67 00:06:34,319 --> 00:06:43,799 Be aware, a lot can go wrong. I once had a hornet’s nest in it, which blocked the tipping device. 68 00:06:44,259 --> 00:06:50,759 But this applies to all the devices mentioned. A lot of things can go wrong, sometimes because 69 00:06:50,759 --> 00:06:56,809 they brake down, sometimes because the reader does not know what to do, or sometimes because 70 00:06:56,809 --> 00:07:01,650 they are positioned under a tree or in the shade of a house. 71 00:07:01,650 --> 00:07:08,009 Moreover, All these instruments provide point observations in space and we have to be aware 72 00:07:08,009 --> 00:07:11,550 that rainfall can vary considerably in space. 73 00:07:11,550 --> 00:07:18,270 This is an example of the many new remote sensing products that are becoming available. 74 00:07:18,270 --> 00:07:24,129 They measure rainfall on the basis of radar, micro-wave and the temperature of clouds. 75 00:07:24,129 --> 00:07:30,849 This picture shows how variable the rainfall is and that point observation can give a wrong 76 00:07:30,849 --> 00:07:37,150 impression of the average precipitation that fell over a region 77 00:07:37,150 --> 00:07:41,349 There are other new and innovative ways of precipitation measurement: 78 00:07:41,349 --> 00:07:43,449 Such as land-based radar, 79 00:07:43,449 --> 00:07:47,009 information from GSM booster stations, 80 00:07:47,009 --> 00:07:53,559 and using the speed of cars as a function of the weather, or the speed of screen wipers, 81 00:07:53,559 --> 00:08:00,559 There is still a lot of information around that we can use ! 82 00:08:01,349 --> 00:08:05,620 Precipitation has a number of characteristics that we have to distinguish very well. 83 00:08:05,620 --> 00:08:09,409 Watch out, because not everybody does this. 84 00:08:09,409 --> 00:08:16,199 Firstly there is the intensity. Precipitation being a flux, the intensity is the measure 85 00:08:16,199 --> 00:08:21,539 of the flux, but it depends on the duration of the rainfall. 86 00:08:21,539 --> 00:08:26,819 In general we can say that if the duration is longer, the intensity is lower 87 00:08:26,820 --> 00:08:29,400 (we'll come back to that) 88 00:08:29,400 --> 00:08:35,560 Second is the depth. This is the integral of the intensity over a certain duration t. 89 00:08:35,560 --> 00:08:40,650 It is expressed as a length (e.g. in mm) 90 00:08:40,650 --> 00:08:47,090 But be aware, this integral is meaningless without the duration, because precipitation 91 00:08:47,090 --> 00:08:51,220 is and remains a flux. 92 00:08:51,220 --> 00:08:56,220 Many people (even meteorological offices) make mistakes in this regard. For instance 93 00:08:56,220 --> 00:08:59,880 they say that the rainfall was 100 mm. 94 00:08:59,880 --> 00:09:06,880 But this is meaningless if you don’t mention the time over which this 100 mm was accumulated. 95 00:09:07,450 --> 00:09:13,380 So always present precipitation as a flux: P=d/t 96 00:09:13,380 --> 00:09:20,380 Then there is the frequency, or the probability of occurrence. A rainfall event always has 97 00:09:20,380 --> 00:09:27,380 a probability of occurrence. This is the more important when we speak of extreme precipitation. 98 00:09:28,830 --> 00:09:35,700 Finally there is the areal extent of the event. This is extremely important if we want to 99 00:09:35,700 --> 00:09:40,250 interpret a point observation of precipitation 100 00:09:40,250 --> 00:09:46,730 The hyetograph is the Greek word to describe the graph of the rainfall intensity as a function of time. 101 00:09:47,410 --> 00:09:52,710 The mass curve is the integral of this curve. And the precipitation over a duration t is 102 00:09:52,710 --> 00:09:59,090 found by connecting two points on the curve a distance t apart 103 00:09:59,090 --> 00:10:05,650 The maximum intensity corresponds with the steepest slope of the mass curve 104 00:10:05,650 --> 00:10:10,340 The areal extent of an event is described by the Areal Reduction curve. 105 00:10:10,340 --> 00:10:16,380 If we look at a very extreme precipitation event observed at a certain spot, then we 106 00:10:16,380 --> 00:10:21,950 may assume that around it the event was less extreme 107 00:10:21,950 --> 00:10:28,950 Generally it reduces according to some Gaussian distribution, reflecting the size of the event. 108 00:10:29,060 --> 00:10:36,940 It can be described by a Gauss-like equation of the maximum intensity Pmax , the area A, 109 00:10:36,950 --> 00:10:41,290 and two parameters k and n 110 00:10:41,290 --> 00:10:46,650 Here I show some of these curves derived by an engineering consultant company for Bangkok 111 00:10:46,650 --> 00:10:47,810 and Jakarta. 112 00:10:47,810 --> 00:10:56,450 We can see that the distribution is flatter for longer duration events (which seems logical 113 00:10:56,450 --> 00:11:00,310 because these are larger systems) 114 00:11:00,310 --> 00:11:07,310 Finally we briefly mention four engineering tools used to average precipitation in space. 115 00:11:07,540 --> 00:11:15,220 Most common is the Thiessen network (a way to visualise the nearest neighbour) but another 116 00:11:15,220 --> 00:11:19,420 way to favour the nearest neighbour is by inverse distance 117 00:11:19,420 --> 00:11:26,900 A more accurate, but more elaborate, way is using the isohyets (the lines of equal rainfall amounts). 118 00:11:27,600 --> 00:11:34,600 But more advanced is the use of geo-statistics. The so-called Kriging method 119 00:11:36,370 --> 00:11:39,080 Here we see some isohyets for Thailand 120 00:11:39,080 --> 00:11:43,140 and a Thiessen Network for the city of Bangkok 121 00:11:43,140 --> 00:11:49,540 In the exercise you can see how these methods are applied in practice. 122 00:11:49,540 --> 00:11:54,670 If you have many point observation data, then it is sometimes hard to assess the consistency 123 00:11:54,670 --> 00:11:56,190 of the data 124 00:11:56,190 --> 00:12:01,670 As I said, many things can go wrong in the measurement and the processing 125 00:12:01,670 --> 00:12:04,570 of precipitation data. 126 00:12:04,570 --> 00:12:11,570 A simple way of identifying stations with problems is to plot double mass curves. 127 00:12:12,560 --> 00:12:18,440 In this example on the horizontal axis we see the accumulated means of a number of stations, 128 00:12:18,440 --> 00:12:23,570 plotted against the accumulated values of a single station. 129 00:12:23,570 --> 00:12:29,850 If something is wrong with that station it may show a haphazard pattern or a kink in 130 00:12:29,850 --> 00:12:35,110 the line when something changed around that station 131 00:12:35,110 --> 00:12:38,250 Here you see a few double mass plots of Bangkok again. 132 00:12:38,250 --> 00:12:45,250 They look reliable, although the right one had some deviations around 1978 133 00:12:47,660 --> 00:12:54,660 For engineering practises, we need to be able to relate precipitation intensity to its duration 134 00:12:54,670 --> 00:12:57,030 and frequency, 135 00:12:57,030 --> 00:13:01,290 for instance to determine the pumping capacity of a polder, 136 00:13:01,290 --> 00:13:06,920 or to find a critical precipitation event to design a bridge or a culvert, 137 00:13:06,920 --> 00:13:09,570 For that we follow the following procedure 138 00:13:09,570 --> 00:13:13,340 We have to start with looking at a record of daily rainfall. 139 00:13:13,340 --> 00:13:23,320 Assume we have 50 years of records, totaling 365*50=18262 daily values. 140 00:13:23,920 --> 00:13:30,630 We then count the number of days with more than 0, 10, 20, 30, etc. mm depth 141 00:13:30,630 --> 00:13:37,160 (you can also take smaller classes depending on the purpose) 142 00:13:37,160 --> 00:13:43,540 You do the same for amounts fallen in two days, 5 days and 10 days. 143 00:13:43,540 --> 00:13:47,570 This results for instance in this Table 144 00:13:47,570 --> 00:13:54,570 We see that only once in 50 years the daily intensity exceeds 40 mm/d, 145 00:13:55,060 --> 00:14:00,500 a probability of 2% on a annual scale. 146 00:14:00,760 --> 00:14:09,480 Similarly an intensity of 30 mm/d is exceeded 5/50 years, whereby T=10; 147 00:14:10,390 --> 00:14:18,010 For the 2 days precipitation 60 mm is exceeded 2 times during 50 years: T=25; 148 00:14:18,990 --> 00:14:22,730 We can plot these data in a graph. 149 00:14:22,730 --> 00:14:28,630 On the vertical axis I plotted the logarithm of the Return Period T and horizontally the 150 00:14:28,630 --> 00:14:31,360 depth in mm. 151 00:14:31,360 --> 00:14:38,110 In the black squares we see the points where an event of 40 mm/d has a return period of 152 00:14:38,110 --> 00:14:45,850 50 years and an event of 30 mm/d a return period of 10 years 153 00:14:46,560 --> 00:14:54,300 similarly we see the point where 60mm/2days has a return period of 25 years; 154 00:14:55,870 --> 00:14:59,680 We can rework these curves in the following graphs; 155 00:14:59,680 --> 00:15:06,680 We can plot the depth against the duration for different return period, on a normal scale 156 00:15:06,690 --> 00:15:12,750 scale (left) or on a log scale (right) 157 00:15:12,750 --> 00:15:18,550 Or we can plot the intensity against the duration for different return periods, also on a normal 158 00:15:18,550 --> 00:15:23,440 scale (left) or on a log scale (right) 159 00:15:23,440 --> 00:15:28,650 Such graphs are extremely useful to design the drainage of parking lots, pumping capacities 160 00:15:28,650 --> 00:15:33,910 of polders, or design discharge for culverts or bridges. 161 00:15:34,180 --> 00:15:39,180 Here is a graph for Bangkok, which was used to design the drainage of the city on the 162 00:15:39,180 --> 00:15:41,320 right bank of the Chao Phya. 163 00:15:42,180 --> 00:15:47,220 Now that we have looked into the characteristics of evaporation and precipitation, 164 00:15:47,230 --> 00:15:52,520 it is time that we start to look at the third component of the water balance: the runoff. 165 00:15:52,520 --> 00:15:54,560 See you later!