Food security is a burning issue these days across the world and especially in developing countries including Pakistan where more than 70 per cent population is directly or indirectly engaged with agriculture sector. Among all agricultural products wheat is the most preferring commodity as it is staple food around almost whole parts of the country so it is an important factor in determination of food security. Wheat yield in Pakistan has experienced extreme fluctuations due to the threatening scenario of changing climate. Climate is getting changed due to change in rainfall pattern, dry spells, droughts and floods.

Crop Modeling is an artistic tool for risk management in Agriculture. Crop models are being used as tool for sustaining food security in changing climate as they are used to develop innovative crop management system. Crop growth and development is described by crop models based on equations and there is in general information about these processes. For example, there might be information about the thermal time to flowering, which comes from controlled environment experiments, or information about maximum rate of rootelongation from specific experiments on this aspect of crop growth. The main objective of crop models is to predict the timing, growth rate, partitioning of assimilates into economic yield, requirement of essential water and nitrogen resources.

The backbone of model is temperature and phasic development, growing degree days and heat units. Crop growth simulation models are used to determine optimum sowing time for crops. As wheat is most important crop of Pakistan being staple food so its sowing time is important. Delayed sowing could reduce wheat yield at the rate of 42kg per hectare per day as last optimum sowing period (SAARC Report, 2013).

Various models are being used in the whole world for yield forecasting in different climatic conditions. Similar scenario is in Pakistan but there is a need to test the scope and limitations of different crop models according to the area. Different models have been used for rice and wheat in Asia like CERES Rice and CERES wheat model to investigate a range of issues from management to yield gap analysisof wheat and rice in changing climate.

In Pakistan, there is a need to stabilize production of wheat in order to sustain food security, the main crop models used for wheat in our country are APSIM, DSSAT, SWAT, CROPWAT, Random Walk with Drift, Linear Trend, Simple Exponential Smoothing, ARIMAand IFSM. APSIM and DSSAT are also being used for yield forecasting of rice and wheat. Different experiments were carried out to check the result of different crop models, as APSIM and DSSAT on different verities of wheat in Potohar region.

The focus of comparison of both models was based on crop, soil and climate data, techniques and outcomes of models. Models were carried out on experimental fields of 155 farmers from five districts of Punjab. Due to changing climate, there is a reduction in rice yield differently with 30 per cent, 20 per cent, 13 per cent, 7 per cent and 6 per cent (mean 15.2 per cent) by DSSAT, and APSIM decreased yield 19 per cent, 14 per cent, 16 per cent, 15 per cent and 18 per cent (mean 17.2 per cent) using five GCMs GFDL, MPI-ESM, CCSM4, MICROC5 and Had-GEM respectively. If the current production system prevails in future, there would be about 69 to 82.6 per cent losers for DSSAT and 72 to 76 per cent losers in case of APSIM due to changing climate.

Poverty rate in changing climate would be between 33 to 38 per cent in DSSAT and from 35 to 37 per cent in the case of APSIM. Quantification of climate change impact on future agricultural production systems depicted that there would be 57 to 70 per cent losers in case of DSSAT and 60 to 71 per cent losers for APSIM and poverty would be from 16.6 to 19 per cent for DSSAT and 18 to19.2 per cent for APSIM.

APSIM model was used to study the impact of climate change on wheat yield in rain-fed areas of Pakistan under changing climate. APSIM model was tested at Potohar region. Parameters including sowing time, biological yield, nitrogen application and grain yield were estimated in this study. This study was taken under different rates of nitrogen in order to investigate the impact of different rates of nitrogen on days after sowing, biological yield, grain yield and grain total nitrogen.

Results showed that nitrogen rates and application methods influenced days after sowing significantly and there was a close association between simulated and actual maturity days (days after sowing). APSIM was parameterized to simulate biomass production under varying rates and methods of nitrogen application, simulated and actual biomass nitrogen contents were very close at three phonological stages. A direct relation with nitrogen fertilizing rates calculated in simulating biological yield and grain yield by APSIM model. Observed and simulated biological yield and grain yield were close to each other (, 2012).

Advanced strategies should be adopted in order to increase yield of wheat in rainfed regions of Pakistan under climatic variations. Traditional practices of agriculture must be replaced by new technologies. Crop modeling and simulation helps like APSIM (Agricultural Production Systems Simulator) which is software that allows dynamic simulation of crop production to enhance productivity of crops under limited resources, residue management, soil water and nutrient flow under different timing and methods of fertilizer application.

To achieve high productivity and meet the need of growing population, it would be required to increase the sowing density up to 15 per cent for rice and fertilizer use up to 15 per cent is considered as one of the adaptation strategy to make up the soil fertility status and high fertilizer requirement of new varieties (A. Ahmad, 2014). Research has showed that APSIM module predicted wheat crop yield through different parameters more accurately as compared to DSSAT. So it is more accurate and appropriate and can be used to simulate crop growth under changing climatic situations to select suitable genotype, sowing time, cropping pattern, fertilizers and weed management strategies that make crops capable to cope with environmental stress and hence increasing yield and to ensure food security.

The author is associated with the Department of Agronomy, Faculty of Crop and Food Science, PMAS-Arid Agriculture University, Rawalpindi. He can be reached at <>

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