International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

HYDROLOGICAL MODELING OF CATCHMENT AREA USING HEC-HMS

NAVKIRAN SINGH PG Scholar, Department of Civil Engineering, PEC Technology of University, Chandigarh, India MOHIT KUMAR Assistant Professor, Department of Civil Engineering, PEC Technology of University, Chandigarh, India AKSHAY KUMAR Research Scholar, Department of Civil Engineering, PEC Technology of University, Chandigarh, India

ABSTRACT The magnitude of high runoff volume and velocity have been captured the attention of many researchers in the field of hydrology since the last decade. The appropriate selection of rainfall-runoff model is necessary in order to ensure water management and planning for a given watershed in developing country like India. The rainfall- runoff modeling was carried out in this study using HEC-HMS, HEC-GeoHMS, Remote sensing and ArcGIS10.5 techniques in the Ravi river catchment area upto Ranjit sagar dam using monsoon period(2015-2018). The hydrological parameters like basin slope, sub-basin area basin slope, basin parameters etc. have been delineated using HEC-GeoHMS , an extension tool of ArcGIS 10.5 and the area of catchment was found to be 6114 km2. The input file of HEC-GeoHMS was then imported to HEC-HMS for simulation of rainfall events to compute the optimized parameters, mean absolute error(MAE), Root mean square error (RMSE) and Nash- sutcliffe efficiency. Keywords : HEC-HMS, Rainfall, Catchment area, Parameters.

INTRODUCTION Hydrological models for rainfall runoff modeling have been developed across the world to study the hydrological and meteorological behaviour of catchment due to precipitation. The number of factors like industrial growth, urbanization, deforestation , land use and land cover with climate change are responsible for this significant changes. To ensure proper utilization of available water resources in a watershed, it is necessary to adopt the suitable model for a catchment as various hydrological models are available. In this study, rainfall runoff modeling of Ravi river catchment upto Ranjit sagar dam as outlet point was done using HEC-HMS, HEC-GeoHMS an extension of ArcGIS and Remote sensing techniques. In the past, Hydrological parameters were averaged over large catchment for the modeling[11], but in this study for more detailed representation of catchment, grid system and spatial data were utilised. In HEC-GeoHMS number of files like basin model file, meteorological model file and grid cell parameter file were created which were then used for hydrological modeling[4]. The attribute tables created by HEC-GeoHMS gives details of sub basin area, basin slope, longest flow path and other physical parameters. With the help of HEC-GeoHMS tool one can perform terrain pre-processing in stepwise. While performing the tool stepwise , one can identify the different commands which is to be used in Terrain pre-processing like flow direction, flow accumulation, stream definition, stream segmentation, catchment grid delineation, drainage line processing etc. as mentioned in methodology[4]. After terrain preprocessing has been completed basin

30 NAVKIRAN SINGH, MOHIT KUMAR, AKSHAY KUMAR

International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

processing is to be done. In basin preprocessing , the sub basin delineation has been done in which one can merge the sub basin or split the sub basin by maximum area. The objective of this study was to estimate and simulate the hydrological response of Ravi River basin due to Precipitation using HEC-HMS software, to calibrate the hydrological model at outlet point based on observed data, to validate the calibrated model with optimized parameters. The Digital Elevation Model which was downloaded from the website https://gdex.cr.usgs.gov/gdex/ for the Ravi river catchment was used.

STUDY AREA The present study has been undertaken on Ravi river catchment area in the district of Punjab, India upto Ranjit Sagar Dam which was selected as the outlet point. Total catchment area of dam reservoir is about 6114 km2. The latitude and longitude of the watershed area is 32.139° N to 33.133° N and from 75.527° E to 77.527° E respectively. The river Ravi originates from Himalyas in the Chamba district of Himachal Pradesh and flows along the India-Pakistan border. Ranjit Sagar Dam is the highest earth filled dam in India. The reservoir area is 87.00 km2, the top level of the dam is at the elevation of 540.0 m and gross storage capacity is 3280 million m3. The normal reservoir level is 527.91m. The study of catchment is shown in Figure.1

Outlet point (Ranjit

Sagar Dam)

Fig 1: Study area.

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International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

METHODOLOGY In the present study, to delineate the watershed and different hydrological parameters, Arc-GIS10.5 software with its extension tool i.e HEC-GeoHMS was used and step by step procedure in the form of flow chart is shown below in Figure 2.

Fig 2: Flow chart of HEC-GeoHMS process.

Firstly Digital elevation model (DEM) of the area was downloaded from https://gdex.cr.usgs.gov as shown in Figure 3.

Fig 3: Digital elevation model (DEM) of Ravi river catchment. Terrain pre-processing- Terrain pre-processing is the first step for the development of HEC-GeoHMS and used to find the direction and accumulation of flow, stream segmentation, catchment grid delineation and drainage line. The step by step process in the form of flow chart is shown in Figure 4. 32 NAVKIRAN SINGH, MOHIT KUMAR, AKSHAY KUMAR

International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

Fig 4: Flow chart for Terrain pre-processing Project setup- In the new project tool the control point i.e. outlet point was specified and then new project was generated at Generate project tool. Basin Processing- In basin processing, small basins were merged by using the Basin Merge tool. The basins were merged according to the purpose and characteristics of the basin( mainly shape). Characteristics-For extracting the topographic characteristics of different streams and sub basins and for estimating hydrological parameters, the characteristics tool has been used. These physical characteristics which were extracted by using characteristics tool are shown in Figure 5.

Fig 5: Flow chart for extracting topographic characteristics Parameters- After the extraction of physical characteristics of streams and sub basins, the parameters tool was used which is helpful to know the particular name of rivers and sub basins by using the commands as mentioned below in Figure 6.

Fig 6: Flow chart for extracting hydrological parameters

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International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

Hydrologic Modeling System - The number of hydrologic inputs like background shape files, basin model file, grid-cell parameter file, and meteorologic model files were developed for HEC-HMS. Further this tool was used for generating the HEC-HMS model files. The stepwise procedure is mentioned below in Figure 7. which was used to generate the model files.

Fig 7: Flow chart to generate model files. HEC-HMS The HEC-HMS software has been used for hydrological modeling to simulate rainfall runoff relationship by using different parameters according to the availability of data. The input files of HEC-GeoHMS was then imported to HEC-HMS for the purpose of hydrological modeling. The number of methods like loss, transformation, routing method etc. are available. If the data such as soil type, land use, land cover is not available so simplest model for least parameters were selected. Loss Method During the rainfall, water is continuously infiltrate in the soil and also intercepted by trees, plants, roofs etc. Evaporation also occurs. These losses should be incorporate in the model but in HEC-HMS either all precipitation contributes in runoff with no other losses or whole precipitation counts into loss in surface is pervious[2]. The methods available for calculation of losses are Deficit and Constant method, Green and Ampt method, Soil Moisture Accounting method and SCS Curve Number method. Out of these methods the SCS Curve Number (CN) method was selected to estimate the loss. The equations used in this method are shown below: (P  Ia)2 Pa  (1) (P  Ia  S) Where Pa= excess accumulated precipitation in time t, P= rainfall depth accumulated in time t, Ia= Initial abstraction and S= Potential maximum retention. Ia and S are calculated from following equations: Ia = 0.2S (2)  25400  S    254  (3)  CN  Transform Method To transform the excess precipitation into point runoff, the methods available in HEC-HMS are Clark Unit Hydrograph method, Kinematic Wave method, Snyder Unit Hydrograph method and SCS Unit Hydrograph

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International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

method[9]. For the present study SCS Unit Hydrograph method was used. The parameter used for this method is lag time. Lag time is different for the different subbasin. Routing Method In HEC-HMS similar to transform method, number of routing methods are also available like Lag, Muskingum, Modified Puls, Kinematic Wave, Muskingum Cunge method. In this study Muskingum method was used. This method is based on conservation of mass approach to route the flow through the stream reach. The routing method evaluates the X and K parameters where, K parameter is time taken by the wave in particular length of a reach and parameter X is constant[5]. In this study initially K and X were taken as 2 hours and 0.2 respectively. The calibration was done to estimate the correct value of K for different reach and X was same i.e 0.2 for natural river. Model Calibration For the model calibration, the initial guess values of parameters were entered to obtain the simulated hydrograph. some parameters were measured while some were estimated by trial and error method. Trial parameters were selected , model were exercised and error was computed. If the error is unacceptable, the program changes the trial parameters and reiterates. Two different search algorithms are there i.e Nelder and Mead search algorithm and Univariate Gradient search algorithm in HEC-HMS, which estimates the final best value from initial estimated values. The Univariate Gradient search algorithm has been selected for this study. This algorithm evaluates and adjusts one parameter and holding other parameters constant.

RESULTS AND DISCUSSION After importing the DEM of the area to Arc-GIS and performing the above methodology following results were observed:

Fig 7: Fill Sink Fig 8: Flow Direction

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International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

Fig 9: Catchment Grid Fig 10: Subbasin

Fig 11: River and Longest flow path Fig 12: Sub-basin

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International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

Table 1: Sub-basin Area, Basin Slope, Basin Perimeter Basin Sub-basin Area Basin Perimeter Sub basin Slope (km2) (Km)

W590 2841.69 1397 291

W740 1901.52 975 236

W770 916.80 640 171

W800 3304.69 968 225

W950 2396.92 878 197

W1010 4088.65 1256 267

The HEC-Geo HMS results are shown from figure 7 to 12. After performing the methodology as mentioned above , we got the results which were again used in HEC-HMS. From the above results model file was developed which was imported to HEC- HMS as shown below in Figure 13.

Fig13: Basin model with River and Sub-basin shape file After model file was imported, the rainfall events were selected as shown in Table 2. and corresponding discharge data was used as observed flow. Then calibration was done on this event by using different parameters as mentioned in the methodology. The optimization of parameters was conducted in calibration process. From the optimization, different results were computed like optimized parameters, mean absolute error (MAE), root mean square error (RMSE) and Nash-sutcliffe efficiency. Further optimization can be done according to the required results. These results can be used for verification purposes by using the another rainfall events.

Table 2: Events selected for calibration part

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International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

Event No. Date of Event Duration of Event Total Rainfall (days) (mm) 1 01/07/15 -31/07/15 31 347.11 2 01/08/15 -31/08/15 31 279.16 3 01/09/15 -30/09/15 30 179.46 4 01/07/16 -31/07/16 31 338.20 5 01/08/16 -31/08/16 31 327.56 6 01/09/16 -30/09/16 30 54.69 The Figure 14 below considered one of the event which shows the comparison of hydrograph between observed and computed discharge. The data for this optimization was the inflow data at Ranjit sagar dam of September 2016 and corresponding daily rainfall of 7 rain gauges in the watershed was taken. For the calibration, different parameters were taken as mentioned in methodology. The optimized parameters are shown in Table 3.

450

400

350

300 /sec) 3 250

200 Discharge (m 150

100

50

0 28-ऑग.-16 02-सप्टᴂ.-16 07-सप्टᴂ.-16 12-सप्टᴂ.-16 17-सप्टᴂ.-16 22-सप्टᴂ.-16 27-सप्टᴂ.-16 02-ऑक्टो.-16 Time (days) Observed Computed

Fig 14:Comparison of observed and computed discharge for 2nd event.

Table 3: Optimized Parameters

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International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

Elements Parameters Units Initial Value values after before optimization optimization

W1010 SCS-Curve-Number 63 63 W590 SCS-Curve-Number 63 35.39 W740 SCS-Curve-Number 63 60.5 W770 SCS-Curve-Number 63 37.04 W800 SCS-Curve-Number 63 63 W950 SCS-Curve-Number 63 60.5 R180 Muskingum-K HR 2 3.01 R230 Muskingum-K HR 2 3.01 R240 Muskingum-K HR 2 2.02 R270 Muskingum-K HR 2 2.02 R280 Muskingum-K HR 2 2.02 R310 Muskingum-K HR 2 2.02 R360 Muskingum-K HR 2 2.02 R380 Muskingum-K HR 2 2.02 R420 Muskingum-K HR 2 2.02 R430 Muskingum-K HR 2 2.02 R440 Muskingum-K HR 2 2.02 R460 Muskingum-K HR 2 2.02 R470 Muskingum-K HR 2 2.02 R490 Muskingum-K HR 2 2.02 R550 Muskingum-K HR 2 2.02 W1010 SCS Unit Hydrograph-Lag Time MIN 300 300 W590 SCS Unit Hydrograph-Lag Time MIN 240 240 W740 SCS Unit Hydrograph-Lag Time MIN 120 120 W770 SCS Unit Hydrograph-Lag Time MIN 60 60 W800 SCS Unit Hydrograph-Lag Time MIN 240 240 W950 SCS Unit Hydrograph-Lag Time MIN 180 180 These optimized parameter were used for validation purpose and the events selected for validation are shown in Table 4. Table 4: Events selected for Validation part 39 NAVKIRAN SINGH, MOHIT KUMAR, AKSHAY KUMAR

International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

Event No. Date of Event Duration of Event Total Rainfall (days) (mm) 7 01/07/17 -31/07/17 31 314.70 8 01/08/17 -31/08/17 31 161.72 9 01/09/17 -30/09/17 30 70.00 10 01/07/18 -31/07/18 31 266.60 11 01/08/18 -31/08/18 31 438.84 12 01/09/18 -30/09/18 30 255.07 One of the result of selected event i.e of September 2017 for validation part is shown below in the Figure 15. It is found that for this 9th event the MAE, RMSE and Nash-sutcliffe efficiency is 14.40, 17.69, 0.95 respectively. 500

450

400

350

/sec) 300 3 250

200

Discharge(m 150

100

50

0 28-ऑग.-17 02-सप्टᴂ.-17 07-सप्टᴂ.-17 12-सप्टᴂ.-17 17-सप्टᴂ.-17 22-सप्टᴂ.-17 27-सप्टᴂ.-17 02-ऑक्टो.-17 Time (days) Observed Computed

Fig 15: Comparison of observed and computed discharge for 9th event. In the similar way further calibration and validation of events can be done by using the appropriate methods according to the availability of data or characteristics of the study area

CONCLUSION In the present study, HEC-HMS model was used for simulation of runoff hydrograph in Ravi River basin. It is observed from the validation results that computed value of the performance evaluation parameters like E, MAE and RMSE were ranging from 0.781-0.951, 14.4-68.79 and 17.69-86.64 respectively. These ranges of performance evaluation parameters are not much better but it’s acceptable for the rainfall-runoff simulation of the present study. It is recommended that the HEC-HMS model may be used for Ravi river watershed and other basins to simulate rainfall-runoff with some approximation and availability of data. REFERENCES

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International Journal of Engineering Technology Science and Research IJETSR www.ijetsr.com ISSN 2394 – 3386 Volume 6, Issue 7, July 2019

[1] Al-Hamdan, O.Z., 2009. Sensitivity Analysis of HEC-HMS Hydrologic Model to the Number of Sub-Basins: Case Study. In World Environmental and Water Resources Congress, Great Rivers (pp. 1-9). [2] Bennett, T.H. and Peters, J.C., 2000. Continuous Soil Moisture Accounting in the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS). In Building Partnerships (pp. 1-10). [3] Boughton, W. and Droop, O., 2003. Continuous simulation for design flood estimation- a review. Environmental Modelling & Software, 18(4), pp.309-318. [4] U.S. Army Corps of Engineers, 2008, Hydrologic Modeling System (HEC-HMS) Applications Guide: Version 3.1.0. Institute for Water Resources, Hydrologic Engineering Center, Davis, CA. [5] Chatterjee, M., De, R., Roy, D., Das, S. and Mazumdar, A., 2014. Hydrological modeling studies with HEC-HMS for Damodar Basin, India. World Appl Sci J, 31(12), pp.2148-2154. [6] Choudhari, K., Panigrahi, B. and Paul, J.C., 2014. Simulation of rainfall-runoff process using HEC-HMS model for Balijore Nala watershed, Odisha, India. International Journal of Geomatics and Geosciences, 5(2), p.253. [7] Chow V.T, Maidment D.R. and Mays L.W. 1988. “Applied Hydrology, McGraw-Hill Publishing Company ISBN: 0071001743.” [8] Chu, X. and Steinman, A., 2009. Event and continuous hydrologic modeling with HEC-HMS. Journal of Irrigation and Drainage Engineering, 135(1), pp.119-124. [9] Halwatura, D. and Najim, M.M.M., 2013. Application of the HEC-HMS model for runoff simulation in a tropical catchment. Environmental modelling & software, 46, pp.155-162. [10] De Silva, M.M.G.T., Weerakoon, S.B. and Herath, S., 2013. Modeling of Event and Continuous Flow Hydrographs with HEC–HMS: Case Study in the Kelani River Basin, Sri Lanka. Journal of Hydrologic Engineering, 19(4), pp.800- 806. [11] Verma, A.K., Jha, M.K. and Mahana, R.K., 2010. Evaluation of HEC-HMS and WEPP for simulating watershed runoff using remote sensing and geographical information system. Paddy and Water Environment, 8(2), pp.131-144

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