1. FLOOD PROGNOSTICS OF YERRAKALAVA RIVER BASIN USING HEC-HMS EVENT MODEL
P. Lakshminarayana Asst. Professor, Department of Water Resources and Irrigation Engineering Madawalabu University, Bale Robe, Ethiopia and Dr. B. Venkateswara Rao Professor, Center for Water Resources, IST Jawaharlal Nehru Technological University Hyderabad

3. Statement of the Problem
The Yerrakalava River Basin is experiencing the flood submergence at the lower part of the Basin.
To study this flooding, a viable and operational flood model is not available.
Therefore, a hydrological model is developed to Yerrakalava River Basin and also prepared certain flood prognostics.

4. HYDROLOGICAL MODEL SET-UP

5. PREPARATION AND ANALYSIS OF SPATIAL DATABASE
RAINFALL ANALYSIS
The rainfall is the very important parameter in HEC-HMS hydrological modeling is supplied by daily time step.
The study area is covered with 14 rain gauge stations (mandal headquarters) namely Aswaraopeta, Buttayagudem, Chintalapudi, Devarapalli, Dommapeta, Dwaraka Tirumala, Gopalapuram, Jangareddigudem, Jilugumilli, Kamavarapukota, Koyyalagudem, Nallagerla, Nidadavolu and T. Narasapuram.
The daily rainfall data is recording at mandal headquarters was collected from Directorate of Economics and Statistics (DES), Govt. of Andhra Pradesh.
The point data used in the rainfall analysis is from

6. Spatial distribution of average annual rainfall of Yerrakalava River basin

7. Average monthly rainfall (mm) of different rain gauges in Yerrakalava River Basin
Name of the
Mandal
Height (m)
A.M.S.L.
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
DEC
YEAR
Aswaraopeta
180
8.6
5.6
12.3
15.4
72.3
136.2
270.1
284.1
162.3
110.6
37.4
12.4
1127.4
Buttayagudem
135
5.8
9.3
14.8
13.2
61.3
151.7
290.4
310.9
188.3
141.0
39.2
12.2
1237.9
Chintalapudi
139
12.7
7.9
20.3
23.8
62.7
136.0
256.0
274.0
165.4
141.6
39.5
12.0
1152.0
Devarapalli 58
4.2
15.3
10.0
45.6
103.6
197.0
196.0
159.7
133.5
40.1
14.3
924.9
Dommapeta
214
8.7
14.1
23.7
78.1
152.4
303.7
314.6
199.6
119.1
53.2
11.3
1288.4
D. Tirumala
100
7.8
26.4
11.7
60.6
120.4
225.0
236.3
180.8
126.3
45.5
13.1
1059.6
Gopalapuram 55
10.5
6.7
15.9
11.9
61.5
134.3
229.8
210.6
180.0
32.6
16.0
1045.9
Jangareddi-
gudem 96
7.0
19.2
18.3
56.0
152.7
257.5
252.0
189.6
140.3
44.1
1154.3
Jilugumilli
157
8.3
6.8
17.2
57.3
135.0
254.0
279.1
165.7
116.5
38.4
10.2
1104.5
Kamavarapu-
kota
113
7.6
8.0
24.2
10.6
65.1
122.1
223.6
256.5
183.4
121.7
36.9
9.7
1069.4
Koyyalagudem 92
9.6
15.7
141.2
259.4
259.0
200.3
143.5
43.2
1155.4
Nallagerla 51
8.1
13.0
11.8
60.2
115.4
208.6
231.3
174.4
142.4
40.0
1024.2
Nidadavolu 24
7.3
5.7
21.1
69.7
127.5
207.2
226.2
174.7
155.1
63.3
1081.4
T.Narasapuram
122
7.5
8.2
15.0
18.1
58.6
121.5
230.7
254.6
141.8
114.4
35.2
10.8
1016.5
AVERAGE
7.2
16.8
61.6
132.1
243.8
256.1
176.1
131.6
42.0
1103.0
MIN
MAX

8. The soil type is very important parameter in generation of curve number.
The soil map is collected from National Bureau of Soil Survey and Land Use Planning (NBSS and LUP).
Soil map of the Yerrakalava River Basin

9. Moderately steep to steep sloping 111.5 4.6 > 35 Very steep sloping
The slope is one of the essential input parameter in hydrological modeling of a river basin.
The elevation data for slope map preparation is collected from the Shuttle Radar Topography Mission (SRTM) satellite.
Slope (%)
Slope category
Area,
km2
Area, %
0-1
Nearly level
515.5
21.5
1-3
Very gently sloping
1247.9
52.0
3-5
Gently sloping
331.5
13.8
5-10
Moderately sloping
107.9
4.5
10-15
Strongly sloping
52.9
2.2
15-35
Moderately steep to steep sloping
111.5
4.6
> 35
Very steep sloping 35
1.5
Slope map of the Yerrakalava River Basin

10. Drainage map and stream ordering of the Yerrakalava River Basin
The Yerrakalava river basin consists of nearly 500 surface water bodies. In which the very small ( ha) tanks are 269, small (2.5-5 ha) tanks are 106, medium (5-10 ha) tanks are 69 and large tanks (> 10 ha) are 56.
The topo sheet derived drainage is compared with the DEM derived drainage to check the accuracy of the DEM.
Visual analysis indicates that the DEM derived streams are well matching with the topo sheet derived streams.
Drainage map and stream ordering of the Yerrakalava River Basin

11. Geological map of the Yerrakalava River Basin
Geology
Area,
km2
Area, %
Kota sand stone
860.98
36.02
Gollapalli sandstone
91.15
3.81
Khondalites
429.80
17.98
Raghavapuram shale
26.09
1.09
Gangapur sandstone
245.55
10.27
Barakar sandstone
25.05
1.05
Tirupathi sandstone
222.34
9.30
Granite gneisses
18.45
0.77
Alluvium
162.38
6.79
Basalts
13.85
0.58
Kamthi sandstone
152.97
6.40
Qurtzite
13.78
Rajamundry sandstone
137.04
5.73
Talchir formation
2.56
0.11
Geological map of the Yerrakalava River Basin

12. Geomorphology map of the Yerrakalava River Basin
The geomorphological information derived in this study area is not directly used in the hydrological modeling but it is useful to assess the recharge and discharge areas and also impervious areas in the study area.
The study area is broadly divided in to 21 geomorphic units.
The geomorphic units include Bajada (BJ), Flood plain (FP), Pediplain deeply weathered (PPD), Pediplain moderately weathered (PPM), Pediplain shallow weathered (PPS), Inter- montane valley (IV), Valley Fill (VF), Valley (V), Pediment (PD), Pediment structural Dome Complex (PSDC), Pediment Inselberg Complex (PIC), Slightly Dissected Plateau (SDP), Undissected Plateau (UDP), Inselberg (I), Linear Ridge (LR), Structural Dome (SD), Denudational Hill (DH), Residual Hill (RH), Residual Mound (RM), Structural Hill (SH) and Cuesta (CU).
Geomorphology
Area,
km2
Area, %
PPD
51.75 VF
3.56
0.15
PPM
543.10
22.61 BJ
3.50 SH
207.63
8.64 PD
2.92
0.12
PPS
167.67
6.98 LR
2.78 FP
162.38
6.76 IV
2.10
0.09
SDP
13.85
0.58
PIC
2.08 SD
13.05
0.54 CU
1.29
0.05 RH
10.86
0.45 V
0.19
0.01
PSDC
9.99
0.42
UDP
0.18 DH
7.21
0.30 RM
0.001 I
4.51
Geomorphology map of the Yerrakalava River Basin

13. Land use/land cover map of the Yerrakalava River Basin
The Land use / land cover information plays a crucial role in In the present study, IRS P6 LISS – III Sensor images pertaining to Kharif ( and ) and Rabi season ( and ) were used in preparation of land use / land cover.
In the present study, Level-II land use/ land cover classification is done using the guidelines of NRSC, Govt. of India.
Using the on screen visual interpretation techniques and field visits, a total 14 land use/land cover classes were delineated.
Land use/land cover
Area, km2
Area, %
Crop land
54.51
Plantation
320.69
13.70
Deciduous forest
290.31
12.41
Forest plantation
114.67
4.90
Fallow land
113.06
4.83
Water bodies
57.07
2.44
Rural area
56.84
2.43
Scrub land
54.18
2.32
Evergreen /Semi evergreen forest
22.89
0.98
River/Stream/Canals
19.11
0.82
Scrub Forest
12.33
0.53
Gullied / Ravinous land
2.73
0.12
Grass/Grazing
0.49
0.02
Barren Rocky area
0.07
0.003
Land use/land cover map of the Yerrakalava River Basin

14. Generation of drainage and sub-basins using the HEC-GeoHMS
HEC-HMS Model Setup
Generation of drainage and sub-basins using the HEC-GeoHMS

15. Modeled sub-basins and drainage of the study area.

16. Curve number map of the study area
The study area is occupied by two soil groups namely B (moderate infiltration rates) and D (very low infiltration rates).
The Soil Group B is located in northern part of the study area and Soil Group D is located in the rest of the area
Soil Conservation Service (SCS) developed a method of combining the effects of soils, watershed characteristics, and land use into a single parameter called curve number (CN).
SCS curve number (CN) is internationally used in various water resources projects. In particular, it is widely used for operational flood modeling in Mediterranean countries (Brocca et al., 2009; Tramblay et al., 2010).
The curve number estimates the precipitation excess as a function of cumulative precipitation, soil cover, land use and Antecedent Moisture Condition (AMC).
In the basin model, the SCS loss method, SCS transform method, recession base flow methods were used.
In the SCS loss method, the used parameters are initial abstraction, curve number and impervious areas.
The initial abstraction (loss) as 0.2 times the potential retention which is calculated from the curve number .
Curve number map of the study area

17. Sub-basin parameters of the study area
Area, km2
Basin slope (%)
Curve number(CN)
Impervious area, %
Lag time, minutes
w1010
181.2
1.29
72.7
8.1
930.2
w1050
177.7
1.11
67.3
8.3
1077.5
w1210
211.8
8.23
73.4
10.4
508.4
w1260
145.8
2.67
69.8
9.9
655.4
w1350
241.0
1.76
72.0
8.9
736.9
w1360
196.9
1.90
14.1
751.3
w1400
121.1
1.22
54.9
6.8
1099.5
w1410
134.5
1.68
66.9
8.0
741.3
w560
358.0
2.74
48.3
6.2
1534.4
w570
171.2
5.71
72.5
8.8
480.7
w670
134.1
2.79
53.1
7.9
940.0
w700
329.0
2.82
60.5
8.2
902.5

18. Stream parameters of the study area
Stream Name
Slope (%)
Elev UP(m)
ElevDS(m)
River
Length(m)
Stream
Name
ElevUP(m)
R10
0.0037
188.00
161.00
R340
0.0008
57.00
56.00
R20
0.0022
129.00
R360
0.0007
49.00
46.00
R30
0.0034
147.00
R370
0.0012
R40
0.0026
190.00
R380
0.0029
63.00
R50
0.0068
277.00
111.00
R390
0.0030
85.00
68.00
R60
0.0038
125.00
R400
0.0027
91.00
R70
0.0024
96.00
R410
29.00
25.00
R80
R420
0.0019
71.00
R90
0.0236
95.00
42.43
R460
0.0020
R100
0.0018
104.00
R470
0.0010
14.00
13.00
R110
116.00
112.00
R480
0.0005
23.00
R120
0.0039
174.00
R490
15.00
R130
115.00
84.00
R450
0.0000
84.85
R140
93.00
R1030
0.0011
R150
0.0016
R440
R160
0.0036
151.00
110.00
R1080
R170
79.00
R1130
0.0082
404.00
54.00
R180
0.0021
R1170
0.0046
53.00
51.00
434.56
R190
99.00
R310
531.84
R200
0.0084
101.00
238.49
R290
0.0167
52.00
120.00
R210
0.0009
R1230
312.43
R220
80.00
74.00
R1270
55.00
169.71
R230
118.00
R300
0.0023
852.43
R240
0.0013
114.00
R350
60.00
R250
R1330
R260
0.0015
121.00
R1370
R270
0.0032
58.00
930.62
R320
R280
R430
37.00
R330
R1430
Where ElevUP: Upstream elevation; ElevDS: Downstream elevation

19. Yerrakalava River Basin in HEC-HMS model
The map is showing the connectivity of the sub-basins (w560, w1360…...), reaches (R150, R180….), junctions (J244, J265….) and sink.
Yerrakalava River Basin in HEC-HMS model

20. HEC-HMS model Contd.
The recession method was selected because of its successful application in various river basins with varying physiographic and climatic characteristics (Ali et al., 2008; Du et al., 2012; Young et al.,2015; Verma et al., 2010).
The model is applied both at the start of the simulation of the rain event and later at the delayed sub-surface flow reaching the channels.
In this model, the required parameters are Initial discharge, recession constant and ratio to peak (threshold ratio).
The initial discharge is considered as the initial base flow. The other two parameters are estimated through calibration.

21. HEC-HMS model Contd.
In the present study, Muskingum Routing model is used.
The Muskingum method is a hydrologic river routing technique based on the equation of continuity and uses a simple conservation of mass approach to route flow through the stream reach.
The model requires two parameters namely Muskingum K and Muskingum X in HEC- HMS model.
The Muskingum K is the travel time through the reach. It can be estimated from knowledge of the cross-section properties and flow properties or it can be estimated through calibration.
The Muskingum X is the weighting between inflow and outflows; it ranges from 0.0 to In practical application, a value of 0.0 results in maximum attenuation and 0.5 results in no attenuation.
In the present study Muskingum K and X both are taken as calibration parameters.

22. Thiessen polygons of the study area

23. HEC-HMS model Contd.
The model also requires the information on Evapotranspiration (ET) but it is negligible for event-based models (Kneb et al., 2004; McColl and Agget, 2007; Ali et al., 2011) those applied for flood simulation.
The model requires all the timing information such as starting date and ending date of simulation, starting time and time step of each simulation.
In the present study, the available data on rainfall and discharge are at daily time step (24 hours).
The model is simulated for different rainfall events scattered between and 2010 under daily time step.
The starting time of the simulation is 8 AM.
The simulation is done for five events (two for calibration and three for validation).

24. HEC-HMS model Contd.
Time series data on rainfall, discharge, and stage at the river gauge for the corresponding simulation are essential inputs supplied through time series data in HEC-HMS model.
The discharge data is available for two locations in the study area which are Yerrakalava Reservoir and Anantapalli gauge on Yerrakalava river are added to the discharge gages in HEC-HMS model.
The events are selected in such a way that they produce peak runoff of more than 250 m3/s.
The selected events have different peak magnitudes ranging between minimum flood and maximum flood.

25. HEC-HMS model Contd.
The maximum release of the reservoir is m3/s. The total storage capacity of the reservoir is 151×106 m3. These two parameters are constant throughout the modeling process.
The initial elevation of the reservoir is varied from time to time so that it is changing from simulation to simulation.
The river gauge located near the Anantapalli Road Bridge is considered for present model calibration and validation due to availability of stream discharge for different rainfall events.

26. CALIBRATION OF HEC-HMS MODEL
Model calibration is a systematic process of adjusting model parameters until model results match acceptably with the observed data.
The objective of the model calibration is to match simulated daily runoff with the observed data with different meteorological and land cover conditions (Du et al. 2012).
The selected parameters considered to model calibration are recession constant, base flow threshold ratio, Muskingum travel time (K) and weighing factor (X).
The model is calibrated for two rainfall events: “Oct. 2 to Oct. 10, 2007” and “Aug. 4 to Aug. 17, 2007”.

27. Daily rainfall (mm) of the study area during Oct. 2 to Oct. 10, 2007
Day
ASPE
BUGU
CHPU
DEPA
DOPE
DWTI
GOPU
JAGU
JIMI
KAKO
KOGU
NAGE
NIVO
TNPU
Oct. 2, 2007
0.0
8.2
7.0
1.8
2.0
3.2
1.4
20.0
Oct. 3, 2007
12.4
2.2
4.0
21.0
3.0
1.2
15.8
12.6
6.0
19.2
23.2
Oct. 4, 2007
7.8
7.4
8.0
4.6
15.6
1.6
16.2
7.2
18.4
16.8
Oct. 5, 2007
49.4
65.2
40.2
60.0
38.0
80.0
81.4
91.6
52.8
45.6
68.0
56.4
89.4
51.4
Oct. 6, 2007
38.2
54.6
16.0
21.4
23.0
77.6
59.8
40.8
36.2
78.6
50.2
27.8
Oct. 7, 2007
Oct. 8, 2007
Oct. 9, 2007
Oct.10,2007

28. Observed streamflow (m3/s) at Anantapalli river gauge during Oct
Observed streamflow (m3/s) at Anantapalli river gauge during Oct. 2 to Oct. 10, 2007
Date
Observed streamflow, m3/s
Oct. 2, 2007
9.7
Oct. 3, 2007
5.0
Oct. 4, 2007
Oct. 5, 2007
43.4
Oct. 6, 2007
291.9
Oct. 7, 2007
50.5
Oct. 8, 2007
23.9
Oct. 9, 2007
15.7
Oct. 10, 2007

29. CALIBRATION OF THE HEC-HMS MODEL Contd.
These parameters first adopted from the similar studies conducted in Pakistan (Ali et al., 2011) and China (Chen et al., 2009; Du et al., 2012) and later modified using calibration.
After adding the all model parameters, the model is simulated for the Oct event and the results are verified with observed streamflow.
This process is repeated by changing the parameters of base flow and routing techniques until model results are matching with the observed results.
The calibration is made using the both optimized method and manual method. The local calibration method is adopted in the present study.

30. Calibrated parameters of the HEC-HMS model of different rain events
Sub-basin
Recession constant
Base flow Threshold ratio
Reach
Element
Muskingum K
Muskingum X
Oct. 2 to Oct. 10, 2007
Aug. 4 to Aug. 17, 2008
W1210
0.3068
0.3900
0.2539
0.27
R1430
2.6172
2.5166
0.4597
0.4376
W1260
0.3571
0.4399
0.2460
R150
4.8201
4.8394
0.4365
0.4197
W1350
0.4938
0.2395
R180
5.0101
5.0162
0.4604
0.4424
W1360
0.5081
0.5940
0.2640
0.15
R320
6.1335
6.0383
0.4784
0.4631
W1410
0.2712
0.3248
0.2472
0.24
Reach-11
5.1554
5.1599
0.4808
0.4463
W560
0.5291
0.6019
0.2764
0.16
W570
0.4083
0.4687
0.2787
W670
0.8106
0.8180
0.2810
W700
0.5821
0.6167
0.2831

31. HEC-HMS model global summary of the Yerrakalava River Basin
Hydrologic element
Area (km2)
Peak Discharge(m3/s)
Time of peak
Volume ×103 m3
W560
358.0
17.0
Oct. 6, 2007, 08:00
4693.0
W570
171.2
52.1
9327.6
J265
529.1
69.1
R180
63.0
W700
329.0
27.3
6242.1
W670
134.1
13.5
3480.1
J244
463.1
40.8
9722.2
R150
40.4
9793.1
W1360
196.9
57.2
Inflow observation
1189.0
160.5
Reach-11
148.8
Reservoir
14.2
Oct. 9, 2007, 08:00
4078.1
R320
16.3
4057.2
W1350
241.0
86.7
W1210
211.8
70.7
W1260
145.8
75.8
J282
1787.6
233.7
R1430
240.2
W1410
134.5
51.9
9930.2
Anantapalli River gauge
1922.1
292.1
 Oct. 6, 2007, 08:00
Reach-8
279.4
W1010
181.2
69.8
W1400
121.1
44.6
J259
2224.5
393.8
R480
358.4
W1050
177.7
51.6
Outlet_ek
2402.1
410.0

32. CALIBRATION OF THE HEC-HMS MODEL Contd.
The simulated and observed hydrograph during rainfall event of “Oct. 2 to Oct. 10, 2007” is showing the model simulated hydrograph is excellently matched with the observed hydrograph.
Observed and simulated hydrographs of rainfall during Oct. 2 to Oct. 10, 2007

33. The simulated and observed hydrographs of another rain event occurred during Aug (Aug. 4 to Aug. 16, 2008).
Observed and simulated hydrographs of rainfall event during Aug. 4 to Aug. 16, 2007

34. CALIBRATION OF THE HEC-HMS MODEL Contd.
Further, the model performance is assessed using the four evaluation criteria namely Nash-Sutcliffe Model Efficiency (NSE), deviation of runoff volumes (Dv), The deviation of peak discharge (Dp) and Absolute error of time to peak ( △𝑇 ) (Chen et al., 2009; Ali et al., 2011).
Model performance during calibration
Event
Observed Volume(mm)
Observed peak (m3/s)
Statistics
NSE
Dp, %
Dv, % △𝑇
Oct. 2 to
Oct. 10, 2007
20.2
292.1
0.98
-0.82
12.12
0.00
Aug. 4 to
Aug. 17,2008
124.2
637.5
0.75
-4.31
6.16

35. VALIDATION OF THE HEC-HMS MODEL
The model is validated for three rainfall events which occurred during 2010.
The rainfall events of “Jul. 25 to Aug. 6, 2010”, “Sep. 2 to Sep. 9, 2010” and “Sep. 25 to Oct. 3, 2010” are taken for validation of the model.
The parameters finalized during calibration of the model are considered as input to the validation of the HEC-HMS model.

36. Observed and simulated hydrographs of rainfall event
Contd…
Observed and simulated hydrographs of rainfall event
during Jul. 25 to Aug. 6, 2010
Observed and simulated hydrographs of rainfall event during Sep. 25 to Oct. 3, 2010
Model performance during Validation
Event
Observed peak (m3/s)
Statistics
NSE
Dp, %
Dv, % △𝑇
Jul. 25 to
Aug. 6, 2010
354.1
0.97
-3.98
3.08
0.00
Sep. 2 to
Sep. 9, 2010
308.5
0.64
-29.62
20.41
Sep. 25 to
Oct. 3, 2010
609.6
0.87
-2.72
10.1
Observed and simulated hydrographs of rainfall event during Sep. 2 to Sep. 9, 2010

37. SENSITIVITY OF THE HEC-HMS HYDROLOGICAL MODEL Contd.
Total seven parameters are considered for sensitivity analysis. These parameters include Initial abstraction, curve number, impervious area, Lag time, Recession constant, base flow threshold ratio and Muskingum K.
The curve number is the most influencing parameter in the present model.
it is observed that, with increase in CN, the peak discharge increases exponentially and the slope of the curve is steeper.
In the presence of a maximum CN i.e. 30% increase in present curve number, the potentiality of watershed to generate runoff drastically increases.

38. SENSITIVITY OF THE HEC-HMS MODEL Contd.
Event model sensitivity on the curve number
The Model is sensitive to Curve
Number. The curve number in turn
depends, soils, antecedent
moisture condition and Land Use
Land Cover
Land Use Land Cover are changing
While soils are permanent.

39. FLOOD PROGNOSTICS
The prediction of an accurate flood inundation area is an essential part of a flood forecasting system.
The available flood submergence maps for the years 2005, 2008, 2010 and 2012 are collected from NRSC website (Bhuvan Website) and are used in the mapping of the flood submergence area of Yerrakalava River Basin.

40. Flood inundation occurred on Sep. 23, 2005
Simulated streamflow of Sep. 19 to Sep. 26, 2005 at Anantapalli Gauge
The model simulated information suggests that the maximum peak discharge of 700 m3/s has occurred on Sep. 20, 2005.
The flood submergence map on Sep. 23, 2005 suggest that the flood inundation area is 6897 acres.
Flood inundation occurred on Sep. 23, 2005

41. Simulated streamflow of Aug. 4 to
The model simulated peak flood on Aug. 5, 2008 is m3/s and the corresponding satellite image on Aug. 7, 2008 is showing the flood inundation area of 3543 acres.
Flood inundation occurred on Aug. 7, 2008

42. Simulated streamflow of Aug. 4 to
The simulated peak discharge on Aug. 10, 2008 is showing the value of 897 m3/s.
The satellite image on Aug. 13, 2008 is showing the flood submergence area of acres .
Flood inundation occurred on Aug. 13, 2008

43. Simulated streamflow of Jul. 24 to
Aug. 7, 2010
The simulated maximum peak discharge m3/s is identified on Jul. 29, 2010.
The satellite image of Jul. 30, 2010 is showing the flood inundation of about 3050 acres.
Flood inundation occurred on Jul. 30, 2010

44. Simulated streamflow of Sep. 2 to
On Sep. 4, 2010 the simulated peak discharge is 402 m3/s and on Sep. 7, 2010 the peak discharge is 303 m3/s.
The flood submergence area is delineated from the satellite image of Sep. 8, 2010 is showing an area of acres.
Flood inundation occurred on Sep. 8, 2010

45. Flood inundation occurred on Nov. 6, 2012
Simulated streamflow of Nov.1 to Nov.9, 2012
The simulated streamflow shows that the peak discharge of 597 m3/s occurs on Nov. 4, 2012.
The satellite image of Nov. 6, is showing that the flood submergence area is 4160 acres.
Flood inundation occurred on Nov. 6, 2012

46. CORRELATION OF PEAK DISCHARGE AND FLOOD SUBMERGENCE
Since the flood submergence area is almost flat and slope is less than 1%, it is assumed that the peak flood is directly proportional to flood inundation area.
Hence, a relation is made between the peak flood and flood inundation area.
The simulated peak discharge of different rainfall events has been correlated with the corresponding flood inundated areas derived from satellite images.

47. Simulated Peak Discharge(m3/s)
Simulated peak discharge and flood submergence area
Date of
Flood map
Simulated Peak Discharge(m3/s)
Area
Submerged(Acres)
22-Sep-05
700.0
6897.0
7-Aug-08
360.6
3543.4
13-Aug-08
897.1
30-Jul-10
387.1
3050.4
8-Sep-10
303.8
2834.2
6-Nov-12
597.0
4159.5
The regression equation developed during correlation has been given as:
Y = X- 1433
Where Y= Area of submergence in lower sub-
basin near the Nandamuru Aqueduct;
X= Peak discharge at the Anantapalli
River Gauge.
Threshold Value is m3/s
Relation between the peak discharge and area of inundation

48. SUB-BASIN RAINFALL CHARACTERISTICS AND TRENDS Contd.
The maximum rainfall of more than 1150 mm is observed in sub-basins w570, w1210 and w1260.
These three sub-basins are located in a northeastern part of the study area.
The minimum rainfall of less than 1020 mm is observed at sub-basins w1050, w1010 and w1400.
These three sub-basins are located at southern side after the Anantapalli river gauge at the outlet of Yerrakalava River Basin.
Average rainfall and rainy days of different sub-basins
Sub-basin
Rainfall, mm
Rainy days
w560
1143.8
72.1
w570
1222.7
67.0
w670
1094.6
68.1
w700
1091.9
66.0
w1010
1014.0
68.3
w1050
941.2
65.9
w1210
1207.9
w1260
1168.3
69.1
w1350
1089.8
70.2
w1360
1083.1
71.3
w1400
1017.5
67.3
w1410
1064.7
From table it is observed that, the high rainfall sub-basins have less rainy days.

49. SUB-BASIN RAINFALL CHARACTERISTICS AND TRENDS Contd.
The increased rainfall in upper basin and increased rainfall intensity in lower basin makes the study area more vulnerable than previous years.
Sub-basin annual trends of rainfall and rainy days
Sub-basin
Rainfall Trend
Rainy days Trend
w560
Increasing
More or less same
w570
w670
w700
w1010
Decreasing
w1050
w1210
w1260
w1350
w1360
w1400
w1410

50. Simulated stream flow for different scenarios of rainfall

51. FUTURE PREDICTIONS OF FLOOD SUBMERGENCE Contd.
The peak discharge of the baseline hydrograph is m3/s for which the baseline inundation area is acres as per the equation developed.
The peak discharges for three scenarios of 10%, 20% and 30% incremental rainfalls are m3/s, m3/s, and m3/s respectively.
With 10% increase in rainfall makes flood submergence of acres which is 9.6% more area than the baseline inundation area.
Similarly, for 20% and 30% increase in rainfall, the flood submergence is acres and acres. This indicates 19.6 % and 28.8% increase of flood submergence over baseline inundation area of acres.

52. Satellite image with aggregate flood inundation and
elevation contour

53. SUB-BASIN RUNOFF ANALYSIS Contd.
In the upper basin, there is reservoir control which reduces some part of flood from upper sub-basins. Therefore, their affect is some what less on submergence area.
The sub-basins in northeastern side just below the Yerrakalava Reservoir are w1210 and w1260 which are producing the maximum peak floods most of the time and does not have any flood controlling structures consequently flood from them is directly reaching the inundated area and makes the submergence in sub-basin w1050.
May be these two sub-basins have to be considered for water harvesting structures to reduce flood damages in the study area.

54. Runoff During the Rainfall Event of Jul. 24 to Aug. 7, 2010

55. LOCATION OF WATER STORAGE STRUCTURE
To identify the possible locations of water storage structures, a methodology developed by Lakshminarayana and Rao (2014) and Kumar et al., (2009) are used.
Kumar et al., (2009) used the methodology of weight assignment of different thematic layers such as Land use/Land cover, geomorphology, lineaments, lithology, road and settlement, and drainage.
Finally, they have integrated these layers in GIS environment.
The sites were classified as good recharge to bad recharge.
As the main aim of the present study is to control water flow from upper parts during the high runoff periods. therefore, the sites were selected for storage purpose and not for recharge purpose.

56. LOCATION OF WATER STORAGE STRUCTURE Contd.
Though many sites are possible to construct the water harvesting structures in the lower Yerrakalava river basin as per the above methodology, only one site is recommended which is controlling most of the water.
The reservoir has been proposed at the confluence point of Yerrakalava, Baineru and Turpukalava as shown in the Fig.
This site is selected because of its geographical location and other physiographical conditions.
The reservoir site located is non settlement area, slope is less than 3%, confluence of three major streams and hard sandstone terrain.
Before going for construction, it is recommended to go for detailed ground survey like site possibility and geological constraints, and inundation area.

57. Proposed reservoir to control flood

58. LOCATION OF WATER STORAGE STRUCTURE Contd.
Apart from this, many water harvesting structures like check dams, nulla bunds, percolation tanks, contour bunds, contour trenches are also useful to arrest some of the water from upper parts and lower parts of the basin.
The Yerrakalava reservoir, in upper basin is constructed to control flood and to irrigating the area.
Most of the time, the reservoir water releases and lower basin runoff are at the same time. This is aggravating the flood situation in lower part of the basin.
Many tanks available in the study area are silted as per the data shown in the satellite image and are reducing the water storing capacity (DST Report, 2010).
Desiltation of these structure may also improve the flood control measures.

59. CONCLUSIONS
The estimated spatial average annual rainfall of the basin is 1103 mm. July and August months are showing the highest average monthly rainfall of more than 240 mm. During these two months some parts of the northern basin is experiencing the rainfall of more than 300 mm. It has been observed that high elevated areas have high rainfall than low elevated regions.
The soil analysis indicates, the study area is having two soil groups namely soils with moderate infiltration (red loamy soils) and soils with very low infiltration (red clay soils).

60. CONCLUSIONS Contd.
Slope analysis indicates that, most of the area is under very gently sloping and nearly level constituting an area of more than 70% of the basin. Moderately steep to very steep sloping areas correspond to the denudational and structural hills normally found in the North Eastern Ghats hilly region of Andhra Pradesh.
The drainage analysis indicates that, the River Yerrakalava is originated in Eastern Ghats of Kottagudem mandal in Khammam district of Telangana state. The Yerrakalava river is the seventh order stream. The drainage density is varying between 0.1 and 6.3 km/km2 with high drainage density in north eastern side and very less drainage density in north-west and south eastern sides. The SRTM DEM derived drainage is well matching with the topo sheet derived streams. Hence, it is recommended for future work also.

61. CONCLUSIONS Contd.
The study area is occupied with a total of 14 rock types, in which three are Archean type and remaining are sandstone and alluvial type of formations. Overall geological analysis is suggesting that, the highest occupied rock is Kota Sandstone with an areal extent of %. Khondalitic suite of rocks is occupying an area of % and Alluvial formation occupies an area of 6.79 %.
The geomorphological analysis indicates Pediplain deeply weathered and Pediplain shallow weathered areas are occupying an area of more than 70%. Structural hill is the next highest area occupied geomorphic unit. The least occupied geomorphic unit is Residual mound.

62. CONCLUSIONS Contd.
A total of 14 land use/land cover classes are delineated in Yerrakalava Basin. The Crop land is occupying the highest area of 54.51% followed by Plantation (13.70%).
A Total 12 sub-basins have been delineated and the corresponding stream network and their parameters are successfully generated using GIS and HEC-GeoHMS tool.
The HEC-HMS model is successfully built to the Yerrakalava River Basin.
The HEC-HMS model is well calibrated and validated for Yerrakalava River Basin. The Nash-Sutcliffe Model efficiency is more than 0.82.

63. CONCLUSIONS Contd.
It is identified that, the HEC-HMS model is giving good results with SCS loss, SCS transform, recession base flow method, Muskingum routing method, thiessen polygon routing method with daily time step. Hence, this model can be applied for similar type of river basins with same modelling options.
The model is more sensitive to Curve Number. With 30% change in Curve Number the runoff is changing more than 50%.
The regression equation is developed between peak discharge and corresponding area of submergence which is given as:
Y = X- 1433
Where Y= Area of submergence in lower sub-basin near the Nandamuru Aqueduct; X= Peak discharge at the Anantapalli River Gauge.

64. CONCLUSIONS Contd.
It is identified that the flood submergence in the lower sub-basin starts if the peak discharge at the Anantapalli river gauge is more than the value of m3/s. This value has been considered as the Threshold value to generate the flood in lower parts of the basin.
The present trends in annual rainfall of different sub-basins indicate that out of 12 sub-basins, the rainfall shows increasing trends in 9 sub-basins indicating more floods in the future.
The increased rainfall of 30% creates the maximum flood inundation of acres of cropland which is more than the baseline flood inundation area of acres.

65. CONCLUSIONS Contd.
From the sub-basin runoff analysis, it is concluded that, the flood is contributing more from upper parts of the Yerrakalava River Basin. The sub-basins namely w1210 and w1260 in northeastern side just below the Yerrakalava Reservoir are producing the maximum peak floods most of the time and does not have any flood controlling structures.
To control flood from upper basin one location has been proposed at the confluence point of Yerrakalava, Baineru and Turpukalava for reservoir construction based on the thematic maps generated.

66. LIMITATIONS OF THE STUDY
Since, the model is calibrated only for two rainfall events and validated only for three events, the model still may not be robust.
As the model is built with daily rainfall data, hourly forecasting is not possible with this model.

67. RECOMMENDATIONS FOR FUTURE RESEARCH WORK
The HEC-HMS model is simulated for daily rainfall time step. It is recommended to run the model for hourly. This will give exact time (hour) of peak flood.
Since, the model is more sensitive to curve number, it is recommended to run the HEC-HMS model for different land use /land cover of past to generate future scenarios using the methods like Cellular Automta-Markov model.
For future flood prognostics, it is recommended to run the HEC- HMS model of the present Yerrakalava River Basin with the downscaled rainfall of the future climate change.

68. RECOMMENDATIONS FOR FUTURE RESEARCH WORK Contd.
The back water inundation due to recommended flood storage structure has to be studied with reservoir simulation models.
To assess the exact flood sub-mergence at lower parts, it is recommended to use river hydraulic models like HEC-RAS to the future work.
In the present study, HEC-HMS model is simulated for only selected flood events. In future, it is recommended to do continuous HEC-HMS hydrological modeling which gives exact water resources of the Yerrakalava River Basin.

69. Thank You