Application of planning models in the agri-food supply chain: A review

An overview of the optimization modelling applications

Conjunctive use of water resources for sustainable irrigated agriculture

Proper planning and management of irrigation is vital in achieving food security for the burgeoning global population and sustaining livelihoods. Because irrigated agriculture is expected to provide more food, if managed properly. The comprehensive reviews on the use of various programming techniques used for planning and management of irrigation have been provided in this paper. The literature review revealed that the management models used in the past mainly considered the objectives of maximization of net farm income, minimization of waterlogging, and minimization of groundwater depletion. These objectives were achieved by optimizing the allocation of available land and water resources. The past reviews are grouped into four sections based on the programming techniques adopted. The sections include: linear programming, nonlinear programming, dynamic programming, and genetic algorithms. This review provides the basis for the selection of appropriate methodology for the planning and management of irrigation.

Irrigation Planning and Management Through Optimization Modelling

Optimal resources allocation strategies for a canal command in the semiarid region of Indian Punjab are developed in a stochastic regime, considering the competition of the crops in a season, both for irrigation water and area of cultivation. The proposed strategies are divided into two modules using a multilevel approach. The first module determines the optimal seasonal allocation of water as well as optimal cropping pattern. This module is subdivided into two stages. The first stage is a single crop intraseasonal model that employs a stochastic dynamic programming algorithm. The stochastic variables are weekly canal releases and evapotranspiration of the crop that are fitted to different probability distribution functions to determine the expected values at various risk levels. The second stage is a deterministic dynamic programming model that takes into account the multicrop situation. An exponential seasonal crop-water production function is used in this stage. The second module is a single crop stochastic dynamic programming intraseasonal model that takes the output of the first module and gives the optimal weekly irrigation allocations for each crop by considering the stress sensitivity factors of crops.

Optimal Irrigation Allocation: A Multilevel Approach

Optimal seasonal multicrop irrigation water allocation and optimal stochastic intraseasonal (daily) irrigation scheduling are carried out using a two-stage decomposition approach based on a stochastic dynamic programming methodology. In the first stage the optimal seasonal water and acreage allocation among several crops or fields is defined using deterministic dynamic programming with the objective of maximizing total benefits from all the crops. The optimization is based on seasonal crop production functions. Seasonal crop production functions are obtained using single-crop stochastic dynamic programming, which incorporates the physics of soil moisture depletion and the stochastic properties of precipitation. In the second stage optimal intraseasonal irrigation scheduling is performed using a single-crop stochastic dynamic programming algorithm, conditional on the optimal seasonal water allocation of stage one. Optimal daily irrigation decision functions are obtained as a function of root-zone soil moisture content and the currently available irrigation water. The methodology is applied to a case study characterized by four crops in which both the optimal irrigation applications and the optimal acreage for each crop are determined.

Judith D. Sunantara

Papers

Optimal Stochastic Multicrop Seasonal and Intraseasonal Irrigation Control