poster - International Conference of Agricultural Engineering

2. Data and Methods
2.1. Methods
Irrigation vulnerability is determined by a quantitative balance between crop water
consumption and water resource availability. A vulnerability assessment model was
developed using two modules: simulation of water requirements in paddy fields and
calculation of hydrologically effective runoff. All processes were designed to be conducted
over a grid in order to make the process extendable to global scale-application, as
vulnerability does not need to be assessed only at country or regional levels such as
administrative or watershed boundaries (Naudé et al., 2011).
2.1.1. Simple water balance model
A simple water balance equation was formulated to simulate daily water balance at a location
(Eq. 1). The daily water requirement and ponding depth was simulated successively using
daily climate data and recommended water management practices.
PD(t) = PD(t-1) + PR(t) – AET(t) – DP (1)
where PD is ponding depth (mm) with an upper limit of 80 mm and the negative values of PD
trigger water deficit (WD), PR is the precipitation (mm/day) just in case of more than 5.0
mm/day, AET is actual crop evapotranspiration (mm/day) calculated by multiplying the
Penman-Monteith reference evapotranspiration by the 10-day crop coefficient (Table 1), DP
is a deep percolation of 4.0 mm/day (Lee, 1988), and t is time.
Irrigation requirements (IR) cannot be greater than the desired ponding depth by growth
stages (Table 2). Effective rainfall (ER) is the amount of rainfall below the upper limit of
ponding depth.
TABLE 1: Crop coefficients for use with the Penman-Monteith equation (Yoo et al., 2008)
Days after
transplanting
10 20 30 40 50 60 70 80 90 100 110 120
Crop coefficients 0.78 0.97 1.07 1.16 1.28 1.45 1.50 1.58 1.46 1.45 1.25 1.01
TABLE 2: Desired ponding depth by growth stages in paddy fields (Jang et al., 2004)
Days since transplanting 10 40 60 90 130
Growth stage On transplanting Tillering Elongation Heading Ripening
Ponding depth 0.78 0.97 1.07 1.16 1.28
2.1.2. Cell-based simple runoff model
Input parameters for the model were limited by a lack of quality data. Therefore, this study
examined a simplified runoff model using a curve number (CN) method at a cell unit.
2.1.3. Vulnerability indices
Vulnerability is a broad measure which is open to interpretation, and there are several
approaches to its measurement (Jun et al., 2011). Expression of vulnerability is complicated
by everything from the quality of the available data, to the selection and creation of indicators,