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Assessment of rainfall recharge using rainfall

infiltration factor method and empirical

equations

Manti Patil1, Arnab Saha2, Sateesh Karwariya3, Santosh M Pingale4, Vikash

Chandra Goyal5, Devendra Singh Rathore6, Nihar Behera7

1. RMO Division, National Institute of Hydrology, Roorkee, India, Email: [email protected]






7. RMO Division, National Institute of Hydrology, Roorkee, India

Corresponding author:

Manti Patil

Email: [email protected]

National Institute of Hydrology,

RMO Division, NIH Road, Roorkee, Uttarakhand, India, 247 667

Phone: +91 7987457158

Article History

Received: 30 September 2018

Accepted: 09 November 2018

Published: January 2019

Citation

Manti Patil, Arnab Saha, Sateesh Karwariya, Santosh M Pingale, Vikash Chandra Goyal, Devendra Singh Rathore, Nihar Behera.

Assessment of rainfall recharge using rainfall infiltration factor method and empirical equations. Discovery Nature, 2019, 13, 1-8

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REPORT Volume 13, 2019

Nature ISSN 2319–5703

EISSN 2319–5711

Discovery


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ABSTRACT

The rainfall recharges of subsurface and ground water is through the artificial application and natural geology. The rainfall recharge

occurring through geology features is natural which is mainly based on the process of infiltration where infiltrated water percolates

from the surface and subsurface to the bed of the aquifer. Recharge plays a vital role in rabi and zaid season, especially for

agricultural purposes. The average annual rainfall of Chhattisgarh is higher than India’s annual rainfall, but most of the regions have

drought condition during off monsoon. In this study, an attempt has been made to assess the recharge from rainfall in Mandri river

watershed, Kanker district, Chhattisgarh, India. Rainfall recharge calculated using four different methods such as Rainfall Infiltration

Factor (RIF) method, Chaturvedi equation, Water level fluctuation method and an empirical equation developed by National

Geophysics Research Institute (NGPRI). The above methods were mostly used in recharge by rainfall. The RIF method and NGPRI

equation is based on geological classification. Rainfall recharge is computed by all the four methods and compared at study area of

Kanker district in Chhattisgarh. It was found that RIF and NGPRI methods gave well-defined and closed results to the water table

fluctuation method as compared to empirical equation. Also, it can be concluded that the equation should be region specified,

based on the specific infiltration factor of that region-specific rock. Rainfall recharge is significant in those areas where geology

strata are Vesicular, Jointed Basalt, Semi- consolidated sandstone, Weathered Granite etc. The ten-year average recharge value using

RIF method is 890.22 ha-m, whereas using NGPRI method is 1036.25 ha-m, Water level fluctuation method gives 1079.ha-mand

Chaturvedi equation was found to yield the highest value i.e. 1349.38 ha-m.

Keywords: Rainfall infiltration factor, Geology, Rainfall recharge, Empirical equations

1. INTRODUCTION

Groundwater is considered to be an only major source for long-term water availability. Due to the alarming increase in the rate of

population, the pumping rate from ground water is far more than recharge. Groundwater recharge contributed through the

subsurface flow below the water table. Rainfall is an only a major source of groundwater recharge. Recharge occurring through

geology features is natural which is mainly based on the process of infiltration, where infiltrated water percolates from the surface

and subsurface to the bed of the aquifer (Healy et al., 2010). The humid region has a high potential of groundwater recharge due to

heavy rainfall, permeable ground surface, average temperature, and minimum evapotranspiration losses. The rainfall recharge of

subsurface and groundwater is done both by artificial and natural geology (Mukherjee et al., 2016). For sustainable development of

the groundwater resources, its quantitative estimation is imperative (Thomas et al., 2008). The natural recharge can occur in a

mannered fashion only if the natural process of recharging is not disturbed due to anthropogenic activities. However, due to

urbanization the forest cover and vegetative cover has significantly decreased at an alarming rate, and increasing population and

decreasing agriculture land the rainfall recharge is a very serious issue to focus. Rainfall recharge is one of the huge sources to save

water and increase the water level in drought areas (Saha et al., 2017). It is most effective in areas which come under Indo-Gangetic

plains and inland areas, East coast and west coast (GEC-1997; Chandan Kumar Singh and Yashwant B Katpatal, 2015). Rainfall

recharge is significant in areas, which have geology strata like Vesicular and Jointed Basalt, Semi-consolidated sandstone, Weathered

Granite etc., but in India, some of the areas do not possess significant rocks to recharge by rainfall due to less infiltration rate. In that

case, artificial recharge is key factors to enhance water level of such areas (Oke et al., 2015; Jyh-Woei Lin, 2015). Reliable Streamflow

forecast can allocate water efficiency for competing water user’s like agricultural and domestic for maintenance of environmental

flows (Patil et al., 2016). Therefore, in the present study, the rainfall recharge has been carried out using rainfall infiltration factor

method and some empirical equations. The groundwater recharge from rainfall infiltration factor methods was used mainly in

command and non-command area during the non-monsoon season and the poor groundwater quality area in both seasons (Sinha

et al., 2016).

2. STUDY AREA

The study area considered here is located at Mandri river watershed (Figure 1) of river Mahanadi, Kanker district, Chhattisgarh, India.

The Mahanadi is a major river in East Central India. This watershed lies in the Kanker block of Kanker district in Chhattisgarh, India. It

is located between 20.1990° N latitude and 81.0755° E longitude, having a total geographical area of 66.6 km2. The altitude of the


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terrain varies from 330 m at plains and 711 m towards the Ghats. The major types of soil found in this region are sand, sandy loam

clay loam, sandy clay, and rock types include Gneiss and Granite. The basin receives most of its rain from the South-West monsoon

during June to September and average annual rainfall in the region is approximately 1,297 mm. The temperature in the watershed

varies from 12°C in the winter season to 45°C in the summer season. Agriculture and horticulture activities include paddy cropping,

maize, kulthi, gram and urd and during monsoon, kodo, sunflower, cowpea, other pulses and oil seeds (Sharma et al. 2014).

Figure 1 Study area map of Mandri river watershed

3. DATA USED

The rainfall recharge was mainly based on the geology of the study area. In the present work geology data collected from State

Level Nodal Agency (SLNA) and rest of the data was available from various government websites and literatures. The water level

data (2006-2007 to 2015-2016) used in this study was collected from CGWB website (http://cgwb.gov.in/).

4. METHODOLOGY

The groundwater recharge was quantified based on the linear relationship between rainfall and recharge. There are two basic

methods applied to estimate the ground water recharge which is widely followed by most of the researchers (Hashemi et al., 2013).

In addition to this approach, some empirical equations have been derived to area-specific rainfall recharge (Adeleke et al., 2015).

4.1. Rainfall infiltration factor method (RIF)

Rainfall recharge by rainfall infiltration factor method is based on the geology of the particular areas. Infiltration factor is defined by

the Ground water Estimation Committee (GEC) for various rock types of India (Rajagopalan et al., 1998). Rainfall recharge in hectare

meters (ha-m) can be computed as the product of the following three parameters (Table 1):

i) RIF, fraction

ii) Quantum of normal rainfall, m

iii) The area of the sub-unit under consideration, ha


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Table 1 Parameters used in this study

S. No. Rainfall Infiltration

factor method

Water table fluctuation

method

NGRI

method

Chaturvedi

equation

1 Geology Water level difference Rainfall Rainfall

2 Infiltration factor Specific yield Constant constant

3 area area Area area

The rainfall recharge is considered to be a linear function of only the quantum of rainfall during that season. The distribution of

rainfall within the season is therefore ignored. The rainfall recharge during the non-monsoon season is considered to be nil if the

normal non-monsoon season rainfall is less than or equal to 10% of the normal annual rainfall, and is calculated only if that

percentage value is greater than 10 (GEC, 1997). The methodology used in this work is presented in figure 2.

Figure 2 Flowchart of methodology adopted in the present study

The geology classification of the study area is shown in Table 2. There are four rock types that exist in the study area based on

which the infiltration factor is assigned to a particular rock (Table 2).

Inputs

1. Rainfall

2. Geology

3. Rainfall Infiltration Factor

4. Water level

5. Difference in water level

6. Specific yield

7. Area

Rainfall Infiltration

Factor Method Water Level

Fluctuation Method Empirical Equations

Methods used

Rainfall

Recharge

ha-m


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Figure 3 Indicates that around 90% of the area comes under granite which has infiltration factor of 0.11.

Table 2 Rainfall infiltration factors of Mandri watershed (Adopted from GEC 2015)

4.2. Water table fluctuation method:

4.2.1 Shallow water table: This area shows the quick response of rainfall recharge due to the shallow water table. Therefore, at a

shallow groundwater depth, the total recharge from a single rainfall event is calculated by multiplying the water table rise with the

specific yield (Zhang et al., 1984).

4.2.2 Moderate water table: In case of moderate water table single rainfall, the event is not much significant to recharge the water

table. In those cases, the cumulative sum of effective rainfall is useful to raise the water table and increase recharge. (Mukherjee et

al., 2014)

4.2.3 Deep water table: Rainfall recharge in the deep water table is mainly based on the intensity, duration, and frequency of

rainfall events and infiltration rate of geology. The recharge rate is small in case of the deep water table. The difference in water level

in pre-monsoon and post- monsoon indicates the total quantity of water withdrawal from the groundwater storage. The change in

storage is computed using the following equation (Bhattacharya et at., 2008)

ΔS = Δh *A* Sy

Where, ΔS= Change in storage;A = Area influence by well; Δh = Difference in water level;Sy =Specific yield

S. No. Rock type

Rainfall infiltration

factor

1 Epidiorite

0.11

2 Granite

0.08

3 Granite, gneiss and schist with low clay

0.11

4 Thick Bedded massive

0.06


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4.3. NGPRI equation method

The National Geophysical Research Institute conducted a large number of natural recharge measurements covering four rock types,

namely, granites, basalts, sedimentary and alluvium across 36 basins distributed all over India (Athavale et al., 2003). A regression

equation developed by (Athavale et al., 2003) for four rock type is given below

Rr =0.174*(P)-62

Where, Rr = rainfall recharge in mm; P= rainfall in mm

4.4. Chaturvedi equation method

In India, one of the earliest natural groundwater recharge estimates were developed by Chaturvedi et al., 1973, who derived an

empirical relationship between rainfall and recharge (when rainfall exceeded 400 mm):

R= 2*(P-15)*0.4

Where, R= Recharge in inches’= Rainfall in inch

5. RESULTS AND DISCUSSION

Rainfall recharge has been estimated using various methods that were mainly focused according to maximum storm possible in

India. Four different methods were adopted to calculate rainfall recharge from the year 2006-2007 to 2015-2016 for duration of 10

years (Figure 4). Rainfall recharge depends on several hydrological and natural phenomenons like, Rainfall intensity, duration,

frequency, infiltration capacity of the soil, temperature and evaporation rate of the study. The results indicate that rainfall infiltration

factor method has minimum recharge as compared to the other methods. While Chaturvedi equation indicated maximum recharge

in the study area. The rock formation and its fracture zone is a key sources of natural recharge, so that the average trend of ten years

have maximum value in Chaturvedi equation (1349 )and minimum valve I RIF methods (890.22).

Figure 1 Comparison of Rainfall recharge by different methods

Figure 5 Comparison of Chaturvedi and NGPRI equation


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Figure 6 Comparison of Rainfall infiltration factor and Water table fluctuation method

In absence of the geological data, some empirical equations are already developed to estimate rainfall recharge. The NGRI has

conducted an experimental study and developed an empirical equation. NGRI equation and Chaturvedi equation were compared in

Figure 5, which indicates higher values of recharge as compared to rest of the approaches. The most popular approaches which are

widely used to estimate the recharge are rainfall infiltration factor method and water table fluctuation method (Figure 6), which

indicates that there is not much deviation in values except for the year 2009-2010 and 2015-2016.

6. CONCLUSION

In this study, the first two methods of rainfall recharge is based on the geologic classification of rocks, which plays a major role in

rainfall recharge. The Chaturvedi formula is mainly based on the direct relation of rainfall and recharge, hence the recharge values

are found to be higher as compared to the other three methods used in this study. The dominant rock type found in the Mandri

watershed was Granite and hence, the number of litholog classes was found to be four. In most of the empirical equations, which are

previously being used have a linear relation of rainfall and recharge; hence the value of recharge is slightly higher as compared to

rainfall infiltration method. In order to minimize the variations in the outputs, empirical equations should be based on rainfall-runoff

relationship, geology, and area specific. In the future, this recharge relationship can be integrated with runoff and local evaporation

from open water bodies.

Acknowledgment

Authors thank National Institute of Hydrology for allowing us to use its facilities, SLNA’s of Chhattisgarh for parting with data for this

study

Author Contributions

Arnab Saha: contributed to all sections. Manti Patil: contributed to all sections. Sateesh Karwariya: contributed to introduction and

discussion sections. SM Pingale: contributed to results and discussion sections. VC Goyal: contributed to introduction and results

sections. DS Rathore: contributed to introduction and results sections. Nihar Behera: contributed to introduction section. The author

read and approved the final manuscript.

Conflicts of Interest

The authors declare that they have no competing interests

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REPORT ARTICLE Volume 13, 2019 Nature Discoverydiscoveryjournals.org/nature/current_issue/2019/A1.pdf · plains and inland areas, East coast and west coast (GEC-1997; Chandan Kumar