Goal and assumptions

From Agri4castWiki
Revision as of 15:25, 21 June 2012 by Raymond (talk | contribs)
Jump to: navigation, search

The MCYFS uses the daily interpolated grid weather to simulate biomass accumulation and crop development. Besides regional monitoring of the crop condition, this MCYFS module issues alarm warnings in the case of abnormal conditions. The outcome of the crop monitoring module is also one of the inputs for the yield prediction (see Yield Forecasting).

Van Diepen and van der Wal (1995) described crop growth as a complex process which takes place on farms at field level. Crop yields vary among regions, farms, fields, and years. Many different factors influence the process. The cause of variation in crop yield may be sought in factors such as:

  • A-biotic: weather, soil type.
  • Farm management: soil tillage, planting density, sowing date, weeding intensity, fertiliser rates, crop protection against pests and diseases, harvest techniques, post harvest losses, degree of mechanisation.
  • Land development: field size, terracing, drainage, irrigation.
  • Socio-economic: distance to markets, population pressure, investments, costs of inputs, prices of outputs, education level, skills, infrastructure.

The crop simulation module of the MCYFS studies the influence of one factor, weather, assuming implicitly that the influence of all other omitted factors is constant. However, the results of the analysis cannot be conclusive, when yield is co-determined by factors kept outside the analysis. Furthermore, the influence of these factors may be completely overruled when the overall economic and political situation is not stable, or when crop-damaging catastrophes occur, such as warfare, flooding, earthquakes etc. Therefore in the final synthesis not only results of the CGMS are included but also other sources such as information derived from remote sensing images (see Remote Sensing). These images show the integrated effects of weather, soil moisture, management on crop growth but individual factors cannot be isolated.

Many of the omitted factors are important at local scale and may lead to variations in yields. The MCYFS assumes that at regional level the influence of these factors is compensated by each other (van Diepen and van der Wal, 1995). Additionally, the MCYFS assumes that effects of weather on yield is regardless the degree of fertilisation (Supit, 1999).

The majority of the relations between plant growth and agrometeorological growing conditions are non-linear. This non-linearity does not allow to first aggregate the input parameters to regional level and next simulate the crop growth at this regional level (Vossen, 1995a ????). Therefore crop growth simulation takes place at the detailed spatial level where distinct areas are more or less homogeneous regarding weather, soil, and crop management.

The MCYFS assumes that the cultivated area of each crop is evenly distributed over all suitable soils, which implies that the production volume increases linearly with planted area. Because complete information on crop areas is missing, the crop yield is estimated for all land that is considered suitable for this specific crop. In reality a given crop could be grown on marginal soils, for instance if the best soils are occupied with more profitable crops. And if the crop is grown on the most suitable soils the inter-annual fluctuation of crop acreage could involve only marginal soils. These assumptions should be kept in mind when calculating and studying production volumes which are the straight multiplication of crop yield and planted area.