17
CHAPTER 2
REVIEW OF LITERATURE
As water harvesting is a very old tradition and has been used for
years, several techniques have been developed so far. Extensive literature is
available on RWH with respect to various methods, its impacts on
groundwater quantity, quality and its modelling. Literature related to the
various methods of recharge estimation, applications of remote sensing and
GIS in artificial recharge, studies on groundwater modelling, RWH
implementation and its impact studies was collected and a critical review was
carried out, as shown in the following sections.
2.1 ESTIMATION OF GROUNDWATER RECHARGE
Chiew et al. (1992) estimated groundwater recharge by adopting an
integrated surface and groundwater modelling approach. The model was
calibrated against stream flow and potentiometric head data, with recharge
estimated as an output from the calibrated model. The model was applied to
the Campaspe River Basin in north-central Victoria and the results showed
that this modelling approach can satisfactorily quantify the spatial and
temporal distribution of regional recharge rates resulting from rainfall and
irrigation water. The simulations forcasted by the integrated model were
better than those forcasted when the surface and groundwater models were
used separately. Osterkamp et al. (1995) analysed the techniques of
groundwater recharge estimates in both arid and semi arid areas with examples
from Abu Dhabi.
18
Lee et al. (2001) estimated the groundwater recharge rate for the
fractured hard rock aquifer, Chojeong area, South Korea. Six different
methods were adopted to estimate groundwater recharge rate including Multi-
linear Regression analysis, SCS-CN method and aquifer modeling techniques.
Those results from various techniques have fallen in the large range from six
percent of annual recharge rate by groundwater modeling analysis to twenty
seven percent by simple flood formula. It was suggested that flood formula
and SCS-CN are more applicable to the top unconfined or alluvial aquifer and
when the aquifer composed of several layers, which had different hydraulic
conductivity including lower fractured hard-rock formation, recharge
estimation by aquifer modeling analysis could be more recommendable in
Korea. The recharge rates estimated from those statistical models turned out
more than twice than the value from aquifer model. It was concluded that
Groundwater Management Plan for Chojeong area was established based on
six percent of recharge rate by the aquifer modeling technique.
Segun et al. (2006) estimated the groundwater recharge in a part of
the Sokoto basin, Nigeria. Empirical, hydro chemical (chloride mass balance)
and climatic-hydrological methods were used. The empirical method showed
exaggerated values of recharge compared to other methods such as the
chloride and water balance methods. The chloride method showed average
recharge was on the order of 19.6 mm/yr based on an annual rainfall mean of
670 mm from 1916-1993 in the Sokoto area. In most of the study area, the
spatial variability of recharge was discovered to be more in wetter years than
in dry years. The results showed recharge around the Wurno and Goronyo
areas was <1 % of annual rainfall while for areas beyond this region recharge
was 3.2 % of annual rainfall. This sharp difference was linked to climate and
lithology. It was concluded that the chloride mass balance method was the
most suitable for estimating of recharge in most of the basin.
19
David Lorenz and Geoffrey Delin (2006) developed a Regional
Regression Recharge (RRR) Model to estimate regional groundwater recharge
in Minnesota. RRR model was based on a regression of basin-wide estimates
of recharge from surface water drainage basins, precipitation, growing degree
days (GDD) and average basin specific yield (SY). The model was applied to
state wide data in Minnesota, where precipitation was the least in the western
and north western parts of the state (50 to 65 cm/year), recharge calculated by
the RRR model also was the lowest (0 to 5 cm/year).
Rasoulzadeh and Moosavi (2007) studied the groundwater recharge
in the vicinity of Tashk lake area located in northeast of Shiraz using the CRD
method. It was focused on using both R-CRD and CRD methods to simulate,
and consequently predict transient water table fluctuations. A user-friendly
program named Groundwater Recharge Estimation Model (GREM), written
in VB language was used to reduce the variation between simulated and
observed water table elevations. The simulated water table revealed good
agreement with the observed water table (modelling efficiency = 0.933). The
percentage of the CRD(r), which resulted in a recharge from precipitation,
was estimated at 33.6. The results indicated that the natural recharge was not
adequate to balance the high volume of groundwater extraction in the study
area.
Bingguo Wang et al. (2008) estimated the groundwater recharge in
Hebei Plain, China under differing land use practices, using bromide and
tritium tracers. Mean recharge rates and recharge coefficient determined by
tritium and bromide tracing for different sites were 0.00-1.05 mm/d and 0.0-
42.5%, respectively. The results also revealed higher recharge for the initial
year of tracer travel than for the second. As total precipitation and irrigation
were greater in the first year than in the second, this might show temporal
variability of recharge.
20
2.2 RAINWATER HARVESTING STUDIES ALL OVER THE
WORLD
Rainwater harvesting is a very old practice that has been
increasingly receiving attention in the world, fueled by water shortages from
droughts, pollution and population growth (Nolde, 2007; Meera and Ahameed,
2006).
Runoff may be collected from roofs and ground surfaces as well
as from intermittent or ephemeral watercourses and thus water harvesting
falls into two groups. Water harvesting techniques which harvest runoff
from roofs called RWH and all systems which gathers discharges from
water courses named flood water harvesting (Critchley et al. 1991).
Gitte and Pendke (2002) conducted a study on the water
conservation practices, water table fluctuations and groundwater recharge
in watershed areas. The study revealed that the water conservation
measures were found to be effective for rising of water table in
observation wells, located in the middle and lower reach of the watershed.
The overall groundwater recharge due to corresponding rainfall was to the
tune of 3.76 to 8.85 cm in the influence of area of soil and water
conservation structure.
Mondal and Singh (2004) conducted a study of unconfined
aquifer response in terms of rise in water level due to rainfall; a rapid and
cost-effective procedure was developed in hard rock terrain. Cross
correlation of rise in water level and precipitation was established. The
entire area was divided into various zones depending on the difference in
21
coefficient of correlation. Thus, best zone for artificial recharge was
depicted with the help of correlation coefficients.
It has been said that rainwater harvesting can promote considerable
water saving in residences in different nations. In Germany, a study done by
Herrmann and Schmida (2008) showed that the potential of potable water
saving in a house might differ from 30% to 60%, depending on the need and
area of roof. In Brazil, a study performed by Ghisi et al. (2009) revealed the
potential water saving by using water harvesting in 62 cities ranged from 34%
to 92%, with an average potential for potable saving of 69%.
Sturm et.al (2009) described Rainwater Harvesting as an alternative
water resource in rural sites in Central Northern Namibia and presented the
results of the examinations of rainwater harvesting (RWH) in central northern
Namibia as a part of the trans-disciplinary research project CuveWaters
(Cuvelai-Etosha Basin in central-northern Namibia). On the basis of various
conditions, suitable solutions for RWH were developed, and evaluated. The
main aim was to analyse their technical and economical feasibility as well as
their affordability for future users. In detail, two small-scale RWH systems
were investigated i.e, roof catchments using corrugated iron roofs as rain
collection areas and ground catchments using treated ground surfaces.
2.3 RAINWATER HARVESTING STUDIES IN INDIA
Singh and Thapaliyal (1991) assessed the effect of watershed
programme on rain fed agriculture in Jhansi district at the state of Uttar
Pradesh and found that the underground water table in the area showed
a considerable increase, the average mean increase in the water table
being 3.7 meters. A change in the area from pulses to cereals and vice
versa was noted in Rabi and Kharif seasons, respectively.
22
Hazra (1997) in his study of crop yield performance in Tejpura
watershed reported that, because of water and soil conservation works
and water storage structures, the wells which earlier used to get water for
about 1-2 hours, got water for more than 8-10 hours due to the increased
groundwater table by 10 to 23 feet after the construction of water
storage structures.
Naik (2000) reported that the main reasons for non-adoption
of water harvesting structures in the state of Karnataka were the non-
availability of credit and high interest rates, (69% each) followed by long
gestation period (68%), high hiring charges of improved implements
(65%) and small holdings (61%) etc. in the non-watershed area.
Bisrat (2001) studied the economic analysis of watershed
treatment via groundwater recharge of Basavapura micro-watershed in
Kolar district of Karnataka and showed that the average output of bore well
increased from 1150 gallons per hour (GPH) to 1426 GPH (24 per cent
increase) after the construction of water harvesting structures.
Naidu (2001), in the study on Vanjuvankal watershed of Andhra
Pradesh, found that because of water harvesting structures and
percolation ponds, the groundwater level in watershed area showed a rise
by 2 to 3 meters.
Kadirvelu (2002) described the impact assessment of RWH in
Madras University-Marina campus. RWH structures were designed on the
basis of the in situ soil conditions. The frequent monitoring of three open
wells was carried out. The water levels during the pumping before and after
the implementation of RWH were recorded. The water levels and the water
quality were compared with the observation well which was situated near the
study area and maintained by TWAD. The benefit cost ratio was also
23
analysed on the basis of the construction cost of RWH and the population to
be served by the harvested rain. Finally, it was concluded from the results that
the quantity and quality improved. The benefit cost ratio was also arrived at
2.38. The impact of RWH was positive in the study area due to the
improvement in quantity, quality and benefit cost.
Rainfall analysis for the period of 1901-1990 for Amod,
Jambusar and Vagra was carried out (Khandelwal et al. 2002) to find
out the onset and withdrawal of effective monsoon, rainfall depth-
duration relationship, irrigation and surface drainage requirement, as well
as to develop design parameters for rainwater harvesting structures
on the unit catchment area basin in Gujarat, India. Water requirement and
irrigation schedule for cotton and pigeon pea under rain fed conditions
were also assessed using the CROPWAT model. Results showed that the
earliest and the latest probable date of onset of effective monsoon (OEM)
varied from 12-14 June to 15-16 July in the region. Mean date of
withdrawal of the monsoon was during 19-21 September. Correlation
between the 2-7 day annual maximum rainfall and 1-day annual
maximum rainfall showed that coefficient of determination and
correspondingly F ratio decreased with an increase in rainstorm duration
from 2 to 7 days. Surface drainage coefficient based on the maximum
moving rainfall of 7 consecutive days with a 7-day tolerance period varied
from 25.1 to 35.8 mm/d. Qualities of water requirement under rain fed
and 20% yield decrease condition for two (pigeon pea and cotton)
crops under irrigation were t h e same, which indicated that even under
non-irrigated conditions, 80% of the potential yield of both crops could be
achieved in an average normal rainfall year.
Ravikumar et al. (2003) described the roof top rainwater harvesting
in Chennai Airport using GIS. The estimation of surface runoff using SCS
24
method and design of rainwater harvesting structures in Chennai Airport
Terminal buildings was explained. Thematic maps were digitized in map Info
GIS software and roof drainage delineation was done in GIS environment.
Based on the topography and lithology of the airport, artificial recharge
structures like recharge shaft, recharge well and recharge pit were designed
and located.
Ramesh Chand et al. (2005) assessed the groundwater recharge via
neutron moisture probe in Hayatnagar micro-watershed, India. The soil
moisture values were calculated using neutron moisture probe from a total of
eight sites at Hayatnagar micro-watershed at regular intervals of time for two
hydrogeological cycles. The total volume of water (recharge) as a result of the
rise in water-level was estimated and it was found to vary from 0.22 to 0.37 m,
with an average of 0.30 m. The effective specific storativity component as a
result of increase in water level was estimated and it was found to change
from 6.9 to 10.6%, with an average value of 9.0%.
Sharda et al. (2006) assessed the groundwater recharge from water
storage structures in a semi-arid climate of India. Groundwater recharge was
calculated as 7.3% and 9.7% of the annual rainfall by Water Table Fluctuation
(WTF) method for the years from 2003 to 2004, respectively, while the
average recharge for two years, was estimated as 7.5% using Chloride Mass
Balance method. The study has further revealed that a minimum of 104.3 mm
cumulative rainfall was required to produce 1 mm of recharge from the water
storage structures. An empirical linear relationship was found to reasonably
connect the changes in the chloride concentration with the water table rise or
fall in the study area.
Venkatesh and Jose (2007) conducted a rainfall study on the
coastal and its nearby areas of Karnataka. The statistical analyses
conducted are cluster analysis and analysis of variance. The study
25
revealed that there existed three different zones of rainfall regimes in
the study area, namely, Transition Zone,Coastal zone, and Malanad
zone. It was found that the maximum rainfall occurred on the windward
side ahead of the geographical peak. Further, the average monthly rainfall
distribution over the zones had been shown to help agricultural planning in
the study area.
Sreekanth et al. (2009) used a prediction model to forecast
ground- water level at Maheshwaram watershed, Hyderabad, India. The
model’s efficiency were calculated based on the root mean square error
(RMSE) and coefficient of determination (R2). The model gave the best fit
and the predicted trend and also the observed data closely (RMSE = 4.50 and
R2 = 0.93).
Subash Chandra et al. (2011) developed lithologically Constrained
Rainfall (LCR) method for quantifying spatio-temporal recharge distribution
in crystalline rocks of Bairasagara watershed and Maheshwaram watershed of
India. The LCR method requires three input criteria i.e. vadose zone thickness,
soil resistivity, and precipitation. The average recharge at Bairasagara
watershed was found varying from 7.5% to 13.8% with a mean of 10.5%
during 1990-2002. The study concluded that the LCR was a generalized, least
cost method developed to quantify natural recharge spatially and temporally
from rainfall in hard rock terrain.
2.4 APPLICATION OF RS & GIS TO ARTIFICIAL RECHARGE
Remote Sensing (RS) and Geographic information system (GIS)
technology have shown novel ways in groundwater studies. The concept of
integrated remote sensing and GIS has shown to be an effective tool in
integrating urban planning and groundwater recharge studies. GIS is
beneficial to, analyze and represent spatial information and database of any
26
resource, which can be easily used for the planning of environmental
protection, resource development, and scientific researches and investigations.
Remote sensing is a very convenient tool in assessing, monitoring and
conserving groundwater resources. Satellite data provide instant and useful
baseline information on the criteria controlling the occurrence and movement
of groundwater like lithology/structural, soils, geomorphology, land
cover/land use, lineaments etc. Many literatures are available to know the
importance of RS and GIS in artificial recharge modeling.
Frank et al. (1996) used remote sensing and GIS to quantify
discharge and recharge fluxes for the Death Valley regional groundwater flow
system, USA.
Ramasamy and Anpazhagan (1997) integrated water level
fluctuation data, geological data, geomorphologic data and sub-surface
geological data for identifying suitable sites for artificial recharge in Ayyar
sub-basin in the Cauvery drainage basin of Tamil Nadu. Water level
fluctuation data, geologic data, geomorphologic data and sub-surface
hydrogeologic data were used for identifying the suitable areas of recharge.
Sites with all the four parameters favourable were classified as first priority
sites. Sites with any three parameters including water table fluctuation and
hydrogeology favourable for recharge were categorised as second priority
sites and water table fluctuation are favourable were classified as third
priority classes. Suitable site for various artificial recharge structures were
demarcated.
Saraf (2002) developed an integrated remote sensing and GIS
technique for groundwater recharge investigations in the hard rock terrain in
Silai watershed of West Bengal. The weighted overlay analysis and Boolean
logic method was discovered and it was very useful for delineation of
recharge suitable areas. The data used were IRS 1A LISS II and IRS 1C LISS
27
III false colour composites, SOI topographic sheets, thematic maps of geology,
geomorphology and soil from National Bureau of Soil Survey and Land Use
Planning. Water level data from 34 wells, collected by State Water
Investigation Directorate were also used for the study. Manual digitisation
was done by ILWIS Software. Remote sensing data were interpreted using
supervised classification technique. Arc View 3.1 was used for analysis and
processing.
Kshirish and Santhosh (2002) investigated suitable recharge zones
using remote sensing data and geographic information system for Rangareddy
District, A.P. Parameters such as surface contour, drainage, lineament and
groundwater depth are taken into consideration and converted into thematic
layers. Overlay of these thematic layers gave the final recharge zone map. The
area was categorised from excellent to poor zones. The result of the study has
given a clear picture about the recharge suitability of the areas.
Mbilinyi et al. (2007) used GIS-based decision support system
(DSS) for identifying suitable sites for rainwater harvesting in Tanzania. The
inputs into the DSS were maps of slope, rainfall, soil depth, soil texture,
drainage and land use/cover and the outputs were maps showing potential
sites of stone terraces, water storage systems, borders and bench terraces.
Ghayoumian et al. (2007) used GIS techniques to decide areas best
suited for artificial groundwater recharge in a coastal area in southern Iran.
Thematic layers for slope, depth to groundwater, infiltration rate, quality of
alluvial sediments and land use were prepared, categorized, weighted and
combined in a GIS environment by means of Boolean and Fuzzy logic. To
know the relationships between geomorphological units and the suitable sites
for groundwater artificial recharge, land-use and geomorphological maps
were used from satellite images. The results showed that about 12% of the
28
study area was suitable and 8% was moderately suitable sites for artificial
groundwater recharge.
Yu-Feng Lin et al. (2009) used PRO-GRADE GIS Toolkits for
groundwater recharge and discharge estimation. GRADE-GIS used a mass
balance method that needs only water table, hydraulic conductivity, and
bedrock elevation data for simulating two-dimensional steady-state
unconfined aquifers. PRO-GRADE was developed to assess the water
resources in Illinois and Wisconsin, in the United States. Maggirwar and
Umrikar (2009) identified the feasibility of artificial recharge in developed
miniwatersheds using a RS-GIS approach. The thematic layer of drainage
map, soil map,village map, geomorphology and land use maps were prepared.
The overlay analysis of drainage and geomorphology was done by
superimposing the geomorphology and drainage thematic layers for the
identification of suitable zones.
Sukumar and Sankar (2010) delineated the potential zones for
artificial recharge using GIS in Theni district, Tamilnadu, India. Various
thematic maps like soil depth, permeability, water holding capacity, drainage
intensity, and soil texture maps were prepared using National Bureau of Soil
Survey and Land use Planning map, Bangalore. GIS has been utilized for the
integration of various thematic maps to depict the suitable zones for artificial
recharge. Each theme was given a weightage depending on its effect on
groundwater recharge. Each unit or class in the map was given a knowledge-
based ranking from one to four depending on its importance in storage and
transmittance of groundwater. The final map was prepared stating high,
moderate and least favourable zone for artificial recharge.
Balachandar et al. (2010) used Remote Sensing and GIS for
Artificial Recharge Zone in Sivaganga District, Tamilnadu, India. Various
thematic maps were prepared which included Drainage density, Drainage,
29
Lineament density, Lineament, Geomorphology, Land use and Land cover
using Landsat data and used Digital Image processing, the supervised and
unsupervised Classification, Band ratioing, Filtering and Normalised
Difference Vegetation Index (NDVI) Techniques for updating the all thematic
maps. Weightages were given to all the thematic maps and were integrated for
identification of suitable site for artificial recharge.
Ismail Chenini et al. (2010) had done the groundwater Recharge
Zone Mapping using GIS-Based Multi-criteria Analysis for the Maknassy
Basin in Central Tunisia.
The advent of RS and GIS has opened new paths for groundwater
recharge studies. This is due to the fact that earth monitoring devices give
most latent, precise, unbiased and detailed spatial, spectral, and temporal
information on conditions of water resources. In order to execute artificial
groundwater recharge, it is important to delineate potential groundwater
recharge zones. Conventionally, remote sensing, photo geological,
hydrogeological and geophysical methods are deployed to select suitable sites
for implementing artificial recharge scheme. Further, the effectiveness of
recharge may be studied by monitoring the structures.
2.5 GROUNDWATER MODELLING
Most groundwater models used today are mathematical models.
Mathematical groundwater models are based on conservation of mass,
momentum, and energy, give cause and effect relations. A mathematical
model can be used as a design tool to determine the need for groundwater
artificial recharge. Many researchers around the world have tried to carry out
groundwater recharge modeling.
30
Gnanasundar and Elango (2000) carried out the groundwater flow
modeling of a coastal aquifer near Chennai, India using MODFLOW. The
model was calibrated under steady and transient conditions. The spatial
distribution of groundwater head and well hydrograph was compared with the
historical data. It was concluded that rapid urbanization would lead to further
reduction of water table at few locations along the northern coast of the
aquifer system and the model was sensitive even for 5% reduction in recharge.
Gogu et al. (2001) created GIS-based hydrogeological databases
and groundwater modelling of Belgium for the Walloon region. Data from a
total of five river basins, chosen for their different hydrogeological
characteristics, were included in the database. A "loose-coupling" tool was
developed between the spatial-database scheme and the groundwater
numerical model interface GMS (Groundwater Modelling System). The
hydrogeological data stored in the database could be easily used following
time and spatial queries within different groundwater numerical models. Ward
Sanford (2002) reviewed recharge and groundwater models.
Shammas and Jacks (2007) used the codes MODFLOW and
MT3DMS for solute transport to decide the flow of the freshwater/saltwater
interface. The study proposed the conservation of the groundwater in Salalah
plain aquifer in Oman from further encroachment by artificial recharge with
reclaimed water along the Salalah coastal agricultural strip.
Palma and Bentley (2007) simulated the groundwater flow in the
Leon-Chinandega aquifer in northwest Nicaragua by using MODFLOW
under transient and steady-state conditions for determining groundwater
availability for irrigation, without considering the effects of groundwater
development.
31
Joseph Zume and Aondover Tarhule (2008) simulated the effects of
groundwater pumping on stream-aquifer dynamics in semiarid northwestern
Oklahoma of USA using visual MODFLOW. Water need in semi-arid
northwestern Oklahoma was predicted to increase by 53% during the next
five decades, driven mostly by public water supply, irrigation, and
agricultural demand. Using MODFLOW's stream flow routing package,
pumping-induced changes in base flow and stream leakage were assessed to
find out streamflow depletion in the Beaver-North Canadian River system.
Results showed that groundwater pumping decreased base flow to streams by
29% and also increased stream leakage into the aquifer by 18% for a net
streamflow loss of 47%. The size and intensity of stream flow reduction
varied for different stream segments, ranging from 0 to 20,804 m3/d.
Szucs et al. (2009) investigated the recharge from open-surface-
water resources as a method for remediation of overproduced and polluted
aquifers. MODFLOW-2000 and MT3DMS simulation softwares were used
for the simulation of the best remediation approach to aquifer recharging from
surface waters.
Bhuiyan et al. (2009) modeled the groundwater recharge-potential
in the hard-rock Aravalli terrain of India. A GIS-based water table fluctuation
method was tried for quantitative modelling of groundwater recharge of the
hard-rock Aravalli terrain. This GIS-based model was used to estimate
recharge-potential of the area by integrated assessment of infiltration level,
normal rainfall and its frequency.
Taheri and Zare (2011) carried out the groundwater artificial
recharge modeling of Kangavar Basin, a semi-arid region in the western part
of Iran. MODFLOW was selected to simulate the aquifer. Calibration was
done for the water levels in the existing piezometers during the year 2003.
Groundwater fluctuations from the year 2004 to 2008 were predicted to
32
validate the model. The study revealed that the observed water level data were
good, adjusted to achieve a reasonable fit with the calculated data. Artificial
recharge impacts were evaluated in different positions. Groundwater level
mound of 3 m with recharged water volume of 3.42 MCM in two sites, and
upconing of 6 m in 3 sites with recharged water volume of 7 MCM were
obtained. The maximum radial effect of these artificial recharge sites was
found to be 1.5 km.
Groundwater modeling is a tool to understand the behaviour of
aquifer systems under different hydrological stresses, whether activated
naturally or by humans. From the various literatures, it is clearly known that
with the help of models and with various prediction scenarios, management
policy can be framed for the future protection of aquifers.
2.6 RWH IMPLEMENTATION
RWH is the technique of collection and storage of rainwater at
surface or in sub-surface aquifers before it is lost as surface run-off. The
harvested resource can be utilized at the time of need. Artificial recharge to
groundwater is a method by which the groundwater reservoir is augmented at
a rate exceeding that under natural conditions of replenishment. Methods of
groundwater recharge mainly in urban areas are roof top rainwater, storm
runoff harvesting through Recharge Trench, Recharge Pit, Recharge shaft and
Recharge well, whereas in rural areas, techniques of Contour Bund, Gully
Plug, Percolation tank, Nala Bund, Check Dam, Recharge shaft, Dug well
Recharge and Subsurface Dyke are used.
In Philippines, RWH was started in 1989 in Capiz Province with
the help of Canadian International Development Research Centre (CIDRC).
About 500 rainwater storage tanks were built using wire-framed ferro-cement,
with capacities varying from 2 to 10m3.
33
RWH has become an important choice for Gansu Province, China
to supply drinking water, promote rain-fed agriculture and improve the
ecosystem in dry areas. In 1995/96, the "121" Rainwater Catchment Project
implemented by the Gansu Provincial Government assisted farmers by
constructing one rainwater collection field, two water storage tanks and
giving one piece of land to grow cash crops. This had proved successful in
supplying drinking water for 1.3 million people and developed irrigated land
for a courtyard economy. As of 2000, a total of 2,183,000 rainwater tanks
were built with a total capacity of 73.1 Mm3 in Gansu Province, supplying
drinking water for 1.97 million people and supplementary irrigation for
2,36,400 ha of land.
A marginally larger RWH system exists in the Changi Airport,
Singapore. Rainfall from the runways and the surrounding green areas are
deflected to two impounding reservoirs. One of the reservoirs is devised to
balance the flows during the high runoffs and incoming tides and the other
reservoir is used to collect the runoff. The water is used mainly for non-
potable functions such fire-fighting drills and toilet flushing. Such collected
and treated water accounts for 28 to 33% of the total water used leading to
savings of approximately S$ 390,000 per annum.
Since May 2001, the Government of Tamil Nadu had promoted
awareness about RWH throughout the State. In view of deficit in demand-
supply, Tamil Nadu Government introduced a law in October 2002, followed
with an ordinance in June 2003, enforcing the implementation of RWH
systems compulsory in all existing buildings. Roof top rainwater harvesting
through existing and abandoned wells were executed in premises of all the
residences, government and private establishments. Awareness programmes
and regulatory options were conducted by State and Central agencies to
control the large scale unscientific extraction of the groundwater resources.
34
Central Groundwater Board (CGWB, 2007) had implemented a
number of pilot schemes for the popularization of cost-effective technologies
for artificial recharge of groundwater. Various structures like check dams,
recharge shafts, percolation ponds and subsurface dykes were built in
different hydrogeological settings. In Tamilnadu State, 7 percolation tanks
and a subsurface dyke were constructed.
2.7 IMPACT STUDIES ON RWH
Many researchers around the world have tried to study the impact
of RWH Systems. Gore et al. (1998) estimated the effects of RWH in 16
observation wells in Maharashtra State, by modelling groundwater coupled
with a water balance model, concluding that there was an overall increase in
groundwater from RWH recharge of 8 ha.m/year. Badiger et al. (2002)
monitored 42 wells in four micro catchments and the effect of recharge with
distance from the wells. It was inferred that recharge from RWH was about 3
-8% of rainfall.
Kun Zhua et al. (2004) focused mainly on the quality of rainwater
harvested from different catchment systems and stored at different periods of
time. By analysing the water samples, it was clear that rainwater quality could
be improved much by self-purification during the storage. The results showed
that roof-top catchments that included the "first flush'' usually gave safe
drinking water with low organic contents, even for rainwater collected
immediately after rainfall.
Deepak Khare et al. (2004) analysed the impact assessment of
RWH on groundwater quality at Indore and Dewas, India. The impact
assessment of roof top rainwater harvesting on groundwater was done with
the help of working tube wells to improve the quality and quantity of
groundwater. The roof top rainwater was sent to the ground using sand filter
35
for pre-treatment. Gontia and Sikarwar (2005) reported that groundwater
levels rose by 8 m in wells in the Saurashtra region of Gujarat and this rise
was believed to come from RWH, though no measurements were taken from
the structures themselves.
Sharda et al. (2006) quantified recharge from a number of RWH
structures in Gujarat, using the water balance method and the water table
fluctuation method. It was found that the structures had a limited capacity to
induce maximum recharge and that a cumulative rainfall of 104.3 mm was
required to induce 1mm of recharge.
Impact assessment of rainwater harvesting on the groundwater regime
was done by CGWB, India in Chennai City. The study showed that the water
level, which ranged from 1.75 to 6.96 m (below ground level: bgl) during May
1997, rose to 0.33 to 6.7 m (bgl) during May 2007. The percentage of wells
having water level less than 5m (bgl) had been increasing after RWH. The
wells, which were dry during the summer months (located in Aminjikarai,
Velachery, Gandhi Nagar, Thiyagarya Nagar and Besant Nagar areas within
Chennai City) prior to the year 2004, recorded rise in water levels.
Pachpute et al. (2009) evaluated the sustainability of RWH systems
in rural catchment of sub-Saharan Africa. A study was undertaken in
Makanya catchment of rural Tanzania to assess the sustainability of storage
type of RWH systems including micro dam, dug out pond, sub-surface runoff
harvesting tank and rooftop RWH system. It was found that higher crop
production was observed in 12 to 20 ha area near RWH type micro dams.
Sturm et al. (2009) described the results of investigations of RWH
in Namibia, on the basis of technical, hydrological, social and cultural
conditions. Suitable solutions for RWH were developed, discussed and
evaluated. The calculations indicated that it was economically reasonable to
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use decentral techniques of RWH in terms of the roof catchment systems.
Katrin Vohland and Boubacar Barry (2009) showed that in-situ RWH was a
promising practice to help sustainable development in sub-Saharan Africa
facing climate change impacts. It improved hydrological indicators, enriched
soil nutrients and increased biomass production.
Olanike and Omotayo (2010) evaluated the potential for RWH in
Abeokuta which had a average annual rainfall of 1,156 mm. 26-year rainfall
data were analyzed to obtain intra annual variability which lied between 0.7
and 1.0 while the inter annual variability was 0.2. Annually, 74 m3 of
rainwater could be harvested per household. Estimated annual need for
flushing, laundry and flushing were 21.6 and 29.4 m3 respectively. Harvested
rainwater in Abeokuta could meet the household monthly water demand for
WC flushing and laundry except for November, December, January and
February. The excess rainwater stored in the month of September and October
was enough to augment the shortfall in the dry months provided there was
adequate storage. Water savings potential is highest in June and September
which is the rainfall peak period in Southwest Nigeria.
Yong-chao Zhou et al. (2010) analyzed the RWH system for
domestic water supply in Zhoushan, China. A computer model was generated
to examine the performance of the DRHS (Domestic RWH system) with
different ratios of water demand/average annual collected runoff and storage
capacity/average annual collected runoff. The performance of DRHS was
analyzed by means of the model simulation.
Glendenning and Vervoort (2011) studied the hydrological effects
of RWH in a catchment of Arvari River, Rajasthan, India. This study analysed
a catchment-scale RWH impacts using a conceptual water balance model. The
simulation results revealed that RWH had a favorable effect on groundwater
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recharge and sustainability of irrigated agriculture, but decreased the stream
flow downstream.
2.8 STUDIES ON RAINFALL RUNOFF MODEL
USDA (1986) developed a simple empirical method called the U.S.
soil conservation Curve Number Method for estimating the amount of
rainwater available for runoff in a catchment. The method was developed by
the analysis of runoff volumes from small catchments in the US. The initial
abstraction values determined by the curve numbers were developed for
different soil types and Land-use practices.
Dunne and Leopold (1978) examined a number of environmental
factors that govern the rate at which water infiltrates into soil. These include;
the rate of rainfall, soil properties (including texture, soil porosity, organic
matter content, structure of soil aggregates, soil depth and moisture carrying
capacity of the soil), topography (slope), vegetation cover and type of land
use.
Schwab et al. (1981) stated that the term runoff can be applied to
stream or river discharge. It can be employed in reference to the gravitational
movement of a fraction of rainfall over the surface of land or as subsurface
flow from an area peripherally bound by a water divide, towards a water
body. Runoff is expressed in terms of volume per unit of time and its
generation largely depends on the amount of rain water that reaches the
earth’s surface.
Schwab et al. (1981) studied the infiltration rate which refers to the
rate at which water enters the soil during or after rainstorm. It plays a key role
in controlling the amount of water that will be available for surface runoff
after a rainfall event. It involves several processes acting together including
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gravitational forces pulling the water down, attractive forces between soil and
water molecules and the physical nature of soil particles and their aggregates.
Ward and Robinson (1990) studied that runoff in a catchment is
generated by the portion of rainfall that remains after satisfying both surface
and subsurface losses. Once these demands have been met, the remaining
rainwater follows a number of flow paths to enter a stream channel. The
course it follows depends on several factors including soil characteristics,
climatic, topographic and geological conditions of a catchment. Overland
flow or surface runoff is the main flow path of runoff that can largely be
influenced by human activities through catchment management practices. It is
also the flow path of rainwater that triggers the process of soil erosion
Beven (2000) stated that both the input and output variables of
stochastic runoff models were expressed in terms of a probability density
distribution. In a stochastic modeling approach, uncertainty or randomness in
the possible outcome of the model was permitted because of the uncertainty
that was introduced by the input variables of the model.
Rientjes (2004) explained that black box models involved the
simulation of empirical relations through the use of regression equations that
were developed after long-term field observations. The use of regression
coefficients was derived from observation rather than from the theoretical or
physical background of natural process.
2.9 SUMMARY
Rainwater harvesting is very important as pressure on
population and natural resources is increasing in India. Large numbers of
RWH models viz., water balance model, regression analysis, water table
fluctuation model, ground water recharge estimation model are available in
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the literature. They are specific to demand and site because RWH system
depends on the topography, land use, land cover, rainfall and demand pattern.
So an evaluation of each model is required for the analysis of hydrology,
topography and other elements like economics and site availability. However,
a common methodology could be evolved. The present study aims at
evaluating the effect of rainwater harvesting in Agastheeswaram taluk of
Kanyakumari District.