Optimal land and water resources allocation policies for sustainable irrigated agriculture

Highlights

• A decision support system was developed for the land and water resources allocation.

• An LP model and a groundwater model were developed and incorporated in the DSS.

• The DSS was applied in a multi-purpose irrigation project in India.

• Conjunctive use of 87% surface and 13% groundwater was found the most feasible.

Abstract

Conjunctive use of surface water and groundwater is being practiced in many regions of the world to bring more areas under irrigation, increase agricultural production and productivity, and also maintain overall system balance. Successful agricultural water management policies put the physical, hydro-geological, and socio-economic constraints on these integrated water supplies. To sustain these constraints, a linear programming (LP) model has been developed for optimal land and water resources allocation in various sectors of the Hirakud Canal Command, a multi-purpose irrigation project on the river Mahanadi in eastern India. To enhance the decision-taking ability of the Hirakud command area development authority, a menu-driven and user-friendly software has been developed by Visual-Basic that incorporates model-base, data-base, knowledge-base subsystems along with the user-interface. The model-base subsystem includes LP, groundwater balance, and evapotranspiration models. The data-base subsystem includes the meteorological, crop, and water resources data. The knowledge-base subsystem was developed from the knowledge derived from the results of the aforementioned models. Sensitivity analysis of the LP model parameters was performed by varying the parameters that affect the optimal cropping pattern and groundwater allocation. The result indicates that conjunctive use of 87% surface water and 13% groundwater is the sustainable water allocation policy of the command area. The model results also indicate that a 20% deviation in existing cropping pattern is the best alternative as it considered socio-economic need and also meets the entire food demand of the study area.

Introduction

Agricultural production requirements of the burgeoning global population is expected to increase by about 50% in 2050 with the corresponding increase of 2.2 billion people by then (De Fraiture and Wichelns, 2010, Davies and Simonovic, 2011, Singh and Panda, 2012a, Singh and Panda, 2012b, Singh and Panda, 2012c, Singh, 2012a, United Nations, 2012). However, this task seems to be challenging in the backdrop of the shrinking land and water resources due to urbanization, contamination, and climate change impacts (Singh, 2014a). In many regions of the world, the surface water availability is just sufficient to meet the crop water demand during the short-span of monsoon season, while, during the non-monsoon season there is large water deficit. For instance, the lower Mahanadi river basin of Odisha State, India faces the problems of waterlogging during monsoon and water scarcity during non-monsoon season (Dash et al., 2010). The potential of fresh quality groundwater can be used to develop conjunctive use management plans for supplementing surface water supplies and to increase agricultural productivity (Khare et al., 2006). The objective of conjunctive use is to increase crop yield, reliability of supply, and general efficiency of a water resources system by combining two or more components of hydrologic cycle when a single source of water is inadequate to meet the demand with sustainability (Singh, 2012b, Singh, 2014b). Literature related to conjunctive use planning and management is plentiful and covers a broad spectrum regions (Castle and Lindeborg, 1960, Maknoon and Burges, 1978, Illangasekare et al., 1984, O’Mara, 1988, Onta et al., 1991, Reichard, 1995, Philbrick and Kitanidis, 1998, Watkins and McKinney, 1998, Karamouz et al., 2004, Vedula et al., 2005, Khare et al., 2007, Chiu et al., 2010, Gaur et al., 2011, Lu et al., 2011, Singh and Panda, 2012d).

Eastern India receives 92% of annual rainfall during four monsoon months (June–September). To capture this large quantity of water against flooding in the downstream and to generate hydro-electricity, surface reservoirs and/or barrages are constructed across the river system. But the stored water in surface reservoirs during monsoon season cannot be used productively because of relatively low irrigation water demand and fixed canal capacity. Whereas the entire groundwater reservoir is recharged during monsoon season, leading to waterlogging in some areas due to excess recharge against discharge and existing geological formations. During non-monsoon season, the stored groundwater is used to supplement surface water supplies as well as stabilize groundwater level within the permissible limit. Therefore, the need of mathematical modeling is very much imperative in the aforementioned complex water resources systems where some of the components are associated with uncertainties and cannot be predicted/measured accurately. As a result, various models and software are found to be effective and popular tools in the field of water resources management (Simonovic, 1996a, Simonovic, 1996b, Bharatia et al., 2008, Singh, 2013, Singh and Panda, 2013). One of the recent trends of solution of water resources management problems is to aggregate several models into an integrated software that focuses on interaction between the user and data, models and computers (Fredericks et al., 1998, Bouman et al., 2007).

Various researcher have developed models and associated software for application in drought management (Raman et al., 1992), irrigation water management (Prajamwong et al., 1997, Carvallo and Lasdon, 1998, Singh, 2014c), surface water planning in river basin (Ito et al., 2001), water quality management (Arnold and Orlob, 1989), flood warning (Ford, 2001), operation of reservoir systems (Arumugam and Mohan, 1997, Eschenbach et al., 2001, Fallah-Mehdipour et al., 2013), and for conjunctive use management of surface water and groundwater (Sethi et al., 2006, Marques et al., 2010, Singh, 2015).

Optimization models can often provide prescriptive results to water resources problems. Several researchers have applied a number of simulation and optimization models to derive planning and operating strategies for irrigation reservoir systems (Gorantiwar and Smout, 2003) and integrated floodplain management plan. In irrigated agriculture, where various crops are competing for a limited quantity of land and water resources, LP is one of the best tools for optimal allocation of land and water resources (Paudyal and Gupta, 1990, Peralta et al., 1995, Singh et al., 2001, Moradi-Jalal et al., 2007).

In this paper, a menu-driven user-friendly software for optimal land and water resources allocation and management policies has been developed under interseasonal and multicrop situations for the Hirakud canal irrigation system in Odisha State, eastern India so as to cater the need of surface water, groundwater, and agricultural authorities at the systems level. The developed model will enhance the decision-taking ability of the command area concerned. There is very clear interlinking between the three subsystems of the model. The typical phases of software development, i.e., analysis of its requirements, detailed specifications, design, programming, testing, and maintenance are relatively easier than many of the existing software. Particularly, the testing and application of this software is very user friendly.