Most soil/water/crop growth models are based on the 1-D conceptualization paradigm and lack the spatio-temporal dimensions advocated in recent times. The literature abounds with agricultural systems models that are based on point scale or paddock scale soil water balance coupled to a crop growth process. Some of these models were adapted to represent lumped characterization of spatial processes. They are ideal for simulating crop development on a relatively homogeneous area such as a paddock. To account for spatial heterogeneity over a larger area such as an irrigation district or a river basin, new techniques are required. The spatial dimension of agricultural production systems makes geographic information system (GIS) software a powerful tool for developing sustainable management solutions. GIS technology provides a mechanism for spatial data input/storage and display with intervening soil water and crop growth engine. A prototype model has been developed to link SWAGMAN-Destiny (Soil Water and Groundwater Management) model to a component based development framework provided by Arc-GIS engine. SWAGMAN Destiny is a point scale soil water balance and crop growth simulation model with crop growth affected by water, salt and aeration stress. The model represents a point in the landscape, and uses capacity concepts to describe the principle processes that determine the fluxes of water and salt into and through a soil profile. Ability to compute a reasonable water and salt balance over time is used to check for integrity of the calculations. The generic crop growth model simulates canopy development using intercepted radiant energy and ambient temperature as the major drivers. Growth, and ultimately yield, is modified from a nominated potential by invoking daily stress factors induced by water deficit, aeration stress, salt stress and nitrogen deficit. Partitioning of growth between shoots and roots and the distribution of roots in the layered soil profile is also influenced by the limiting stress factors.The development of this model attempts to encapsulate our best understanding of the major controlling processes in this complex irrigated production system and allow us to examine the consequences of a range of management options aimed at influencing both productivity, and soil, salt and water management. The model is able to quantify year-to-year variation in yield using longterm weather data and thus may be used for risk assessment. In addition, the model is able to determine the leaching fraction expressed as a percentage of total infiltration at different levels of the soil profile.
|Title of host publication||Land, Water & Environmental Management|
|Subtitle of host publication||Integrated Systems for Sustainability|
|Editors||Les Oxley, Don Kulasiri|
|Place of Publication||Christchurch, New Zealand|
|Publisher||Modelling and Simulation Society of Australia and New Zealand|
|Number of pages||6|
|Publication status||Published - 2007|
|Event||International Congress on Modelling and Simulation (MODSIM) - Christchurch, New Zealand|
Duration: 10 Dec 2007 → 13 Dec 2007
|Conference||International Congress on Modelling and Simulation (MODSIM)|
|Period||10/12/07 → 13/12/07|
Khan, S., & Xevi, E. (2007). Integrating GIS and Modelling Soil Water and Crop Production. In L. Oxley, & D. Kulasiri (Eds.), Land, Water & Environmental Management: Integrated Systems for Sustainability (pp. 1314-1319). Modelling and Simulation Society of Australia and New Zealand.