Simulating Crop Growth and Crop Water Use

On the other hand, many crop simulation models have been appeared in the last 20 years. Those models are able to estimate crop water-use and growth under any weather and cop management conditions. Those models, combined with downscaled GCM scenarios, can be a reliable approach to support decision-making under climate change conditions (Hoogenboom, 2000). Despite many models are available, Mechanistic models i.e. those based in the physical laws of the soil-water-plant-atmosphere continuum, are the most suitable to climate-change impact assessments (Eatherall, 1997), since the laws are, in principle, valid for al climatic conditions.

According to Tubiello and Ewert (2002), more than 40 assessments of climate-change impact on agriculture have been published up to now. They pointed out that generally models provided accurate results, compared to actual data. The most used models in such assessments are DSSAT (Jones et al., 2003) and those developed in Wageningen (Van Ittersum et al., 2003).

As pointed out above, modelling tools appeared in the eighties, due to computer availability, aimed to simulate crop growth and final yields. Numerous crop growth models have been developed since them. The models can use weather data input, such as short term weather forecast, a season's forecasted weather or climate scenarios to estimate potential or actual growth, development or yield. Historical-production records are useful for assessing the impacts of climate variability on crop yields, but cannot reveal crop response under alternative management strategies, which can be done through modelling simulations.

Bastiaansen et al. (2004) provided an update revision of the modelling applications to irrigation assessments. They pointed out the opportunities lying in such modelling approaches to irrigation and drainage assessments, with more than 40 examples. The simulation examples comprises assessing irrigation supply needs, as well as irrigation designing, scheduling, management and performance; salt-affected soils due to irrigation, groundwater recharge and estimating soil losses, among others.

Models have been usually classified as empirical, functional and mechanistics (Connolly, 1998; Bastiaansen et al., 2004). Mechanistic models, i.e. those based in the physical laws of the soil-water-plan-atmosphere are more suitable to assess climate-change effects on agriculture than empirical models (Eatherall, 1997; Hoogenboom, 2000), since the theoretical mechanistic-model backgrounds is still valid under these new conditions. According to

Bastiaansen et al. (2004), concerning suitability to describe irrigation and drainage processes, models can be classified as bucket, pseudo-dynamics, Richards-equation based, SVAT models, multidimensional and crop-production models. However, at the plot and field scale only the bucket, the crop-oriented models and those based on the Richards equation have been significantly used. The Richards equation describes the vertical movement of water within the soil profile and its solutions can, at least theoretically, provide the water distribution under certain initial and border conditions (Kutilek and Nielsen, 1994).

Therefore, concerning irrigation studies at field and plot scales, the most important mechanistic modelling approaches are those mainly aimed to simulate crop-growth and those addressed to physically-based simulation of soil-water movement, through numerical solutions of the Richards equation. These models have been called agrohydrological models, because they combine agricultural and hydrological issues (V an Dam, 2000).

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