Bavishi, Himanshu

Bhagat, N. K.

English

Rainfall Runoff Co-Relationship done by many approaches such as software, mathematical, empirical, hydrograph. Models of different types provide a means of quantitative extrapolation or prediction that will helpful in decision making. In present paper focused on empirical methods for rainfall runoff co-relationship. Rainfall data for the important rain gauging site was considered for flood years (1991, 1994, 1996, 1997, 1998, 2005, 2006, 2007). INGLIS AND DE SOUZA'S, LACEY'S, PARKER'S BRITISH AND USA, AND TAPI BASIN Formula use for corelationship. Utilizing all formula, a rainfall runoff co-relationship was obtained using the regression equation.</p

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The University of Manchester ResearchRainfall runoff co-relationship using empirical methods forLower Mahi Basin, IndiaDocument VersionFinal published versionLink to publication record in Manchester Research ExplorerCitation for published version (APA):Bavishi, H., & Bhagat, N. K. (2017). Rainfall runoff co-relationship using empirical methods for Lower Mahi Basin,India. International Journal of Civil Engineering and Technology, 8(3), 575-581.Published in:International Journal of Civil Engineering and TechnologyCiting this paperPlease note that where the full-text provided on Manchester Research Explorer is the Author Accepted Manuscriptor Proof version this may differ from the final Published version. 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Jun. 2022http://www.iaeme.com/IJCIET/index.asp 575 editor@iaeme.com International Journal of Civil Engineering and Technology (IJCIET) Volume 8, Issue 3, March 2017, pp. 575–581 Article ID: IJCIET_08_03_056 Available online at http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=8&IType=3 ISSN Print: 0976-6308 and ISSN Online: 0976-6316  © IAEME Publication Scopus Indexed  RAINFALL RUNOFF CO-RELATIONSHIP USING EMPIRICAL METHODS FOR LOWER MAHI BASIN, INDIA Himanshu Bavishi  U.G Student, Department of Civil Engineering, Indus University, Ahmedabad, India Bhagat N.K Assistant Professor, Department of Civil Engineering, Indus University, Ahmedabad, India ABSTRACT Rainfall Runoff Co-Relationship done by many approaches such as software, mathematical, empirical, hydrograph. Models of different types provide a means of quantitative extrapolation or prediction that will helpful in decision making. In present paper focused on empirical methods for rainfall runoff co-relationship. Rainfall data for the important rain gauging site was considered for flood years (1991, 1994, 1996, 1997, 1998, 2005, 2006, 2007). INGLIS AND DE SOUZA’S, LACEY’S, PARKER’S BRITISH AND USA, AND TAPI BASIN Formula use for co-relationship. Utilizing all formula, a rainfall runoff co-relationship was obtained using the regression equation. Key words: Rainfall, Runoff, Empirical Methods. Cite this Article: Himanshu Bavishi and Bhagat N.K, Rainfall Runoff Co-Relationship Using Empirical Methods for Lower Mahi Basin, India. International Journal of Civil Engineering and Technology, 8(3), 2017, pp. 575–581. http://www.iaeme.com/IJCIET/issues.asp?JType=IJCIET&VType=8&IType=3 1. INTRODUCTION Rainfall is the result of water vapour condensing and precipitating, forming droplets that fall from clouds due to gravity. It is an important part of the water cycle. Runoff means the draining or flowing off of rainfall from a catchment area through a surface channel. The relationship between rainfall in a period and the corresponding runoff is quite complex and is influenced by a host of factors relating to the catchment and climate. Further, there is the problem of paucity of data which forces one to adopt simple correlations for adequate estimation of runoff. Commonly adopted method is to fit a linear regression line between Runoff and Rainfall and to accept the result if the correlation coefficient is nearer unity. Several empirical formulae have been developed by various investigations. These formulae the annual precipitation (p). There are generally of two forms: (I) R = aP + b (II)      R = c Pn  Rainfall Runoff Co-Relationship Using Empirical Methods for Lower Mahi Basin, India http://www.iaeme.com/IJCIET/index.asp 576 editor@iaeme.com Where a, b, c and n are the catchment constants. There is large number of empirical formula available in literature. These formulae are applicable for the catchment for which they had been derived. However, these are also used for other catchment with similar characteristics. Some of the most commonly formulae are given below:  INGLIS AND DE SOUZA’S  LACEY’S  PARKER’S BRITISH AND USA  TAPI BASIN In this study, an attempt has been made to obtain a rainfall runoff relationship for Lower Mahi Basin, India using Empirical equations. Since the data collection is very expensive and time consuming, the rainfall data was collected only for important rain gauge station for period of 20 years. Using the rainfall data, runoff calculated from empirical methods. Observed and calculated runoff co-relation was obtained using regression question. 2. DIFFERENT EMPERICAL METHODS 2.1. INGLIS and DE SOUZA’S formulae Inglis and De Souza studies the yield of catchments in Western Ghat mountains and Palins of Maharashtra (India) and gave two separate formulae for the ghat areas and plain areas.   (a) Ghat areas   R = 0.85P – 30.5  (b) Plain areas    R = (P – 17.8) P          254 Where R is the daily runoff (cm) and P is the daily rainfall (cm) over the entire catchment. 2.2. Lacey’s Formulae Lacey gave the following formula for the catchment in the Indo-Gangetic plains.     R =  P       1 + 304.8F       PS  Where F is the monsoon duration factor, whose value is equal to 1.0 for the normal monsoon duration. For very short duration and very long duration, the value of F is, 0.50 and 1.50. S is the catchment factor. The value of S for A, B, C, D and E types of catchments are respectively, 0.25, 0.60, 1.00, 1.70 and 3.45 where types of catchments are as per Barlow’s Classification ( Table 1 ). Alternatively, the value of (F/S) for different types of catchments for different monsoon duration factor can be taken from Table 2. Table 1 Barlow’s catchment classification Class of  catchment   Description of catchment A Flat, cultivated, absorbent soil B Flat, partly cultivated, stiff soil  C Average catchment D Hills and plains with little cultivation E Very hilly and steep, with little or no cultivation  Himanshu Bavishi and Bhagat N.K http://www.iaeme.com/IJCIET/index.asp 577 editor@iaeme.com Table 2 Value of (F/S) for the catchment of type Duration of monsoon Values of (F/S) for the catchment of type A B C D E Very short 2 0.83 0.5 0.29 0.14 Standard duration 4 1.67 1 0.58 0.28 Very long 6 2.5 1.5 0.88 0.43 2.3. Parker’s formulae Parker gave the following formulae for different countries.       (a)  British Isles           R = 0.94P – 35.6  (b)  Germany               R = 0.94P – 40.6  (c)  U.S.A                    R = 0.80P – 41.9 Where R and P in centimetre. 2.4. Tapi basin (Gujarat) This formula has been developed for Tapi basin Gujarat, India.                                     R = 0.435P – 17.2 Where R  and P in centimetre. 3. STUDY AREA Mahi River is one of the major west flowing interstate river of India, draining into the Gulf of Khambhat. The Mahi basin is comprised of two sub-basins: - Mahi upper sub basin of (65.11% of total basin area) consisting of41 watersheds and Mahi lower sub basin (34.89% of total basin area) consisting of 22 watersheds. It lies between720 15‟00” E to 780 15‟00” E and 220 N to 22040‟ 00” N respectively. The basin map is shown in Fig 1.Only the lower Mahi Basin is considered for the present study. Rain gauging stations was considered Table 3 shows the details of the rain gauging station considered for study.  Figure 1 Mahi Basin Rainfall Runoff Co-Relationship Using Empirical Methods for Lower Mahi Basin, India http://www.iaeme.com/IJCIET/index.asp 578 editor@iaeme.com Table 3 Details of rainfall gauge station Station NAME Latitude Longitude Ref. Topo. No PILOL 22˚24'39" 22˚24'39" 46F03 SANSOLI 22˚24'39" 22˚24'39" 46F06 SAVLI 22˚24'39" 22˚24'39" 00F46 WANAK BORI 22˚24'39" 22˚24'39" 46F05 KALOL 22˚24'39" 22˚24'39" 46F06 4. ANALYSIS  4.1. INGLIS and DE SOUZA’S formulae Table 4 Inglis and De Souza’s Formula Analysis YEAR CALCULATED OBSERVED 1991 12476.10 10293 1994 16742.62 14592 1996 8723.64 7403 1997 12695.85 11956 1998 6893.15 5750.6 2005 2158.36 1674.52 2006 24331.42 31061.91 2007 11111.53 9000.16                Figure 2 Inglis and De Souza’s formula Co-Relation 4.2. Lacey’s Formulae Table 5: Lacey’s Formula Analysis         YEAR CALCULATED OBSERVED 1991 12442.41 10293 1994 16744.09 14592 1996 8506.82 7403 1997 12547.41 11956 1998 6859.80 5750.6 2005 2160.54 1674.52 2006 24307.82 31061.91 2007 11114.01 9000.16 y = 1.2832x - 3792.3R² = 0.9328050001000015000200000.00 10000.00 20000.00 30000.00ObservedCalculatedOBSERVEDLinear (OBSERVED)Himanshu Bavishi and Bhagat N.K http://www.iaeme.com/IJCIET/index.asp 579 editor@iaeme.com             Figure 3 Lacey’s formula co-Relation 4.3. Parker’s formulae 4.3.1. British lsles Table 6 Parker’s British formula Analysis                       Figure 4 Parker’s British formula Co-Relation 4.3.2. U.S.A Table 7 Parker’s USA formula Analisis YEAR CALCULATED OBSERVED 1991 12465.86 10293 1994 16692.93 14592 1996 8587.19 7403 1997 12630.45 11956 1998 6903.50 5750.6 2005 2130.71 1674.52 2006 24347.66 31061.914 2007 11072.82 9000.16 YEAR CALCULATED OBSERVED 1991 12524.38 10293 1994 16727.51 14592 1996 8679.87 7403 1997 12718.09 11956 1998 6966.78 5750.6 2005 2169.91 1674.52 2006 24408.56 31061.91 2007 11093.82 9000.16 y = 1.281x - 3699.R² = 0.932050001000015000200000.00 10000.0020000.0030000.00ObservedCalculatedOBSERVEDLinear (OBSERVED)y = 1.281x - 3799.R² = 0.934050001000015000200000.00 10000.0020000.0030000.00ObservedCalculatedOBSERVEDLinear (OBSERVED)Rainfall Runoff Co-Relationship Using Empirical Methods for Lower Mahi Basin, India http://www.iaeme.com/IJCIET/index.asp 580 editor@iaeme.com             Figure 5 Parker’s USA formula Co-Relation 4.4. TAPI BASIN Table 8 Tapi Basin formula Analisis YEAR CALCULATED OBSERVED 1991 12436.66 10293 1994 16726.15 14592 1996 8468.94 7403 1997 12525.33 11956 1998 6861.90 5750.6 2005 2151.88 1674.52 2006 24312.26 31061.914 2007 11100.32 9000.16              Figure 6 Tapi Basin Formula Co-Relation 5. CONCLUSION This study is ab attempt to define a Rainfall-Runoff Co-relationship for Lower Mahi Basin, India. Graphical regressions were made relating to rainfall and runoff was determined considering all the important catchment characteristics using the empirical methods. It was found that considerably good results were obtained by correlating rainfall versus run off. The regressions were affected to some extent by the quality of the data from which they were derived. Runoff data was considered fairly well, as it does not take into account the infiltration in the catchment. The infiltration is the start of the event is different when the storm ends and this effects the run off from the catchment. When the “R2” value approaches y = 1.281 x - 3678.R² = 0.933050001000015000200000.00 10000.0020000.0030000.00ObservedCalculatedOBSERVEDLinear (OBSERVED)y = 1.281 x - 3724.R² = 0.934050001000015000200000.00 10000.0020000.0030000.00ObservedCalculatedOBSERVEDLinear (OBSERVED)Himanshu Bavishi and Bhagat N.K http://www.iaeme.com/IJCIET/index.asp 581 editor@iaeme.com to 1, it means the river receives a regular rainfall every year and the flow is actually proportional to it. The co relation “R” for the basin is nearing the unity and such a correlation is said to be very good, which shows the catchment is more responsive to the rainfall it is receiving. The method presented in this study provides a tool for estimating runoff from a rainfall event. For all this different empirical equations, the regression value was nearing unity. Parker’s USA analysis gave the value of R2 as 0.934. So, it is most effective method for runoff calculation for lower Mahi Basin.  REFERNCES [1] Bhagat N. K.(2016) Rainfall - Runoff Co-Relationship for Lower Mahi [2] Basin, India. “ PARIPEX - INDIAN JOURNAL OF RESEARCH”, Volume : 5, Issue : 12, December-2016 Keith Beven Lancaster University, UK “Rainfall-Runoff Modelling” Second edition WIELY-BLACWELL publication [3] K. Subramanya “Engineering hydrology” Third Edition TataMcGraw-Hill publication [4] Dr. K.R. Arora “IRRIGATION, WATER POWER AND WATER RESOURCES ENGINEERING” Standard Publisher distributors. [5] R.K.Suryawanshi., S.S.Gedam and R.N.Sankhua., (2012),”Comparative Analysis of Spatial Rainfall and Runoff estimation using Geospatial Tools, ANN and Empirical approach”. International Journal of Emerging Technology and Advanced Engineering, ISSN: 2250-2459, Volume-2, Issue-10, PP 295-299. [6] H.L. Tiwari, Ankit Balvanshi and Deepak Chouhan, Simulation of Rainfall Runoff of Shipra River Basin. International Journal of Civil Engineering and Technology, 7(6), 2016, pp.364–370. [7] Akali Ngaywa Moses, Spatial Variation of Rainfall Runoff Erosivity (R) Factor for River Nzoia Basin, Western Kenya. International Journal of Civil Engineering and Technology, 8(2), 2017, pp. 418–422 

Rainfall runoff co-relationship using empirical methods for Lower Mahi Basin, India

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Rainfall runoff co-relationship using empirical methods for Lower Mahi Basin, India

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