Rainfed two levels, seasonal and intra-seasonal competition for

Rainfed regions in India account for 94 million ha,
which is 65% of the net sown area. About 95% of coarse cereals, 86% of pulses
and 81% of oilseeds areas of the country are produced in rainfed areas.
Parthasarathy Committee Report (2006) says, “It is the rainfed parts of Indian
agriculture that have been the weakest, they are also the ones that contain the
greatest unutilized potential for growth, and need to be developed if food
security demands of 2020 are to be met.” The major constraint in increasing
production from rainfed areas is to increase sources of irrigation. In eastern
India, the rainfed agriculture is over 67% of the net sown area. The region
receives mean annual rainfall of 1500 mm, which seems to be sufficient to grow
two crops in sequence provided the rainfall events are uniformly distributed in
space and time throughout the total cropping seasons, whereas it is associated
with random phenomena. South-west monsoon in India is responsible for growing
rainy/monsoon season (kharif) crops
and its onset, withdrawal, and intra-seasonal distribution are erratic in
nature. Rao et
al. (1990) addressed the problem
of water allocation of a limited water supply for irrigation of several crops
grown in the same season using a dynamic framework by decomposition to two
levels, seasonal and intra-seasonal competition for water. Moreover,
uneven distribution of monsoon rain in rainfed areas causes crop failure due to
shortage of soil moisture in the root zone during its critical growth period. During monsoon season,
the maximum rainfall received between June to September is nearly 1200 mm with
some high intensity of rainfall that contains nearly 60% of annual rainfall (Pisharoty, 1990). For such high intensity
rainfall causes excess runoff and soil erosion from the crop field.

The on-farm reservoir (OFR) is a small
storage structure constructed for collecting surface runoff from the field. The
design of the OFR consists of finding a suitable combination of surface area,
depth of storage and a permissible side slope for a given storage volume. A
good number of works has been done on the performance evaluation of the OFR for
irrigation purposes using different crops in different part of the country. Roy et al. (2009) developed user-friendly
software, using Visual Basic 6.0 program to find out the optimal size of the
OFR in terms of percentage of field area by simulating the water balance model
parameters of the crop field and the OFR. The user has to specify the crops to
be grown in the fields, irrigation management practices of the crops, types of
OFR (lined or unlined), side slope, depth of OFR, and field sizes.
Panigrahi et al.
(2001) developed a daily
simulation model to determine the size of OFR that enables the farmers to
provide supplemental irrigation to rice. Irrigation for rice is provided during
the critical growth stages only and the rest of the period is rainfed.
The major challenge in enhancing food grain production in eastern India comes
from its rainfed uplands. The on-farm reservoir (OFR) designed for harvesting
and recycling of rainwater for rice based cropping pattern in rainfed lowlands (Srivastava, 2001; Islam et al., 1998) and uplands
(Panigrahi et al., 2007) appears to be a
full proof technology for enhancing rice production during drought years. But
the technology is not sound enough to guarantee optimum yield from winter
crops. Because, a rice crop cultivated at the upstream of the reservoir
obstructs a large amount of runoff to maintain its depth of ponding requirement
and also requires equally enough water as supplemental irrigation during its
critical growth stage. This is the reason why the reservoir lacks adequate
storage for meeting the irrigation requirement of winter crops. In this
context, expecting an optimum yield of winter crops is seldom achieved.  Out of 44 million ha of total rice area in the
country, the upland rice occupies 7 million ha of which 75% is from eastern
India only (Kar et al., 2004). The average
yield of rice from this area is very low because of uneven distribution
rainfall in crop growing season. Due to sandy loam type of soil in this area,
it is impossible to maintain standing water in the crop field but for rice it
is imperative to maintain even saturation condition throughout its growing
season.  Also
the scope of growing a second crop after withdrawal of monsoon is also very
much limited due to quick depletion of soil moisture. The average yield of
cereals, oilseeds and pulses from the region are lagging behind the other
regions of the country (NAAS, 1998). On the
other hand, rice dominant cropping practice resulted in lowering the cropping
intensity in rainfed uplands but also contributed to bringing down the
productivity. Panigrahi and Panda (2003) developed a model for
the prediction of optimal size of an on-farm reservoir (OFR) so as to provide
supplemental irrigation to rice in monsoon season and pre-sowing irrigation to
mustard in winter for a rainfed farming system of eastern India. Mahendrarajah et al. (1992) analyzed the
optimization of monsoonal water storage tank for supplemental irrigation under
double rice cropping in Sri Lanka. The inter-seasonal irrigation allocation of
storage was solved by deterministic dynamic programming using simulated crop
response function. Panigrahi et al. (2005) documented
that construction of the on-farm reservoir (OFR) is an alternative for the
storage of excess rainwater from the diked rice field during monsoon season
followed by its reuse as supplemental irrigation to the rice in the same season
and pre-sowing irrigation to mustard in the winter season. Mehta and Goto (1992) developed an irrigation pond
model for the determination of minimum storage capacity at a desired
reliability level with a given intake, operating rule to meet the fluctuating
water demands under various cropping patterns and hourly irrigation demands. For
this purpose, a soil water balance model is developed to determine the actual
evapotranspiration, followed by formulating a dated production function
relating evapotranspiration and crop yield, which is included in the objective
function of the dynamic programing model to obtain the optimal irrigation
decisions. Prasad et
al. (2011) formulated a weekly
irrigation planning linear programming model for determining the optimal
cropping pattern and reservoir water allocation for an existing storage based
irrigation system in India. Vedula and Mujumdar
(1992) formulated a model to obtain a steady state optimal reservoir
operating policy for irrigation of multiple crops with stochastic inflows by
first using dynamic programming (DP) to optimally allocate the available water
among all crops within a given period, and then evaluated the system
performance using stochastic dynamic programming (SDP) to optimize the benefits
over a full year. Umamahesh and Sreenivasulu (1997)
developed a two-phase stochastic dynamic programming model for optimal
operation of irrigation reservoirs under a multicrop environment. The proposed
model integrates reservoir release decisions with water allocation decisions.
The water requirements of crops vary from period to period and are determined
from the soil moisture balance equation taking into consideration the
contribution of soil moisture and rainfall for the water requirements of the
crops. The main objective of the present study is to determine the
optimum size of the OFR using dynamic programming.

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