Tailoring information about climate change and its impacts

Resultaten van onderzoek naar klimaatverandering en de mogelijke effecten zijn vaak niet beschikbaar in een vorm waarin ze direct door anderen gebruikt kunnen worden. Gebruikers van klimaat- en impactinformatie hebben vaak ook geen goed overzicht over de beschikbare gegevens van alle sectoren en resultaten zijn soms inconsistent

Integration of remote sensing and simulation of crop growth, soil water and solute transport at regional scale

Water productivities (WP) are defined for different scales that can be considered in an agricultural area, such as the crop, the field and the regional scale

Analysis of crop growth

SWAP / WOFOST was used for a balanced estimation of yield and evapotranspiration, and to include interactions between soil-water and solute transport and crop development. The model was calibrated for wheat, rice and cotton in Sirs

Uncertainties in input-output coefficients for land use optimization studies: an illustration with fertilizer use efficiency.

The problem of uncertainties in input-output coefficients is examined, using the uncertainty in estimating the fertilizer use efficiency as an illustration. An example of uncertainty due to lack of knowledge on processes involved is the use of different approaches for estimating fertilizer use efficiency in two land use optimization studies. A further problem is uncertainty due to lack of data; this is illustrated with an example from the Atlantic Zone of Costa Rica. Very few data are available to determine fertilizer use efficiency and data from regions with similar soil and climate type are not available. Data from non-similar regions may not give a correct assessment of the possibilities in the region. Different concepts and sources of information result in different estimates of coefficients, which might in turn greatly influence the results of the linear programming model. It is therefore concluded that, rather than using one fixed value for a particular input-output coefficient, the effect of uncertainty in coefficients on the final results of the model should be examined

Which crop and which drop, and the scope for improvement of water productivity

The information provided in publications on water-related agronomic trials and irrigation interventions is often too limited to compare values of water productivity (WP), i.e. the ratio between produced plant biomass and the amount of water used for that production, from different years, regions, etc. in a meaningful way. In this article, we show with the help of simulation models how WP-values are affected by different definitions of the numerator and denominator, environmental circumstances, such as climate, year and sowing date, and crop characteristics. In many cases, this resulted in 10-25% change in the WP-values, and sometimes even more. A minimum dataset is formulated that will make normalization and comparison of different WP-values easier. Most of these data are known by those who execute experiments, and we recommend strongly that these are reported in the future. Simulation models are excellent tools to explore the limitations and opportunities for increasing WP, provided they are well calibrated and validated for biomass, soil water availability, and ET. Such a balanced estimation of the 'crop' and the 'drop' requires an improved cooperation between hydrologists and agronomists. Comparison of actual WP(E)T and simulated maximum WP(E)T for the same environmental conditions does show the scope for increasing WP(E)T and other WP-values. Since WP-values are ratios, the production level on a hectare basis should be given besides WP. When we try to find an optimum combination of production per hectare and production per m3 irrigation water, we will be able to produce 'more food with less water'

Integration of remote sensing and simulation of crop growth, soil water and solute transport at regional scale

Water productivities (WP) are defined for different scales that can be considered in an agricultural area, such as the crop, the field and the regional scale