Land Suitability Assessment in Climate Change Condition, Case Study: Canola Cultivation in West Azerbaijan Providence

Introduction
Today, with the increasing population and the need for strategic and industrial crops the farmers are simulated to grow these kinds of crops. Thus, this subject has now been caused the inappropriate use of land and natural resources. On the other hand, the natural environment resources have limited the ability to use its resources and the climate change intensifies this limit ability. Agriculture is one of the most sensitive parts of human activities to changes in climate parameters. The slightest shift in climatological factors of plant growth, the growth of plant processes affected these changes in the performance and quality of crops. In climate change condition, some natural environments with the most appropriate conditions and resources are provided for the development and optimal use of human and with the least appropriate condition the human manipulation can lead to damages to natural environment. Therefore, to any manipulate and development in environment, before planning to use it, we need to evaluate the potential of the environment. In addition to the potential of environments for the future, due to climate change, it is required to consider any planning. The aim of current study is to provide a land suitability assessment in the condition of climate change. Given the sensitivity of crops to climate change, one of the agricultural products as a sample product has been selected to implement the procedure.
One of the strategic and industrial products is Oil-seeds such as canola. Oil-seeds compose the second largest food resources of the world after cereals, and Canola is the third largest source of vegetable oil in the world. A variety of factors and parameters are effective in determination of suitability of any area of land for cultivation and in condition of climate change and changes in temperature and precipitation changes in suitability of lands may be occurred for cultivation of canola. In this study, a new method based on the Geographic Information System (GIS) and climate change model, has been developed for cultivation of canola in West Azerbaijan-Iran.
 
Material and Methods
In the first step, the effective criteria (canolaplant requirements) were recognized using library study. In this study, the GIS based on Artificial Neural Network (ANN), Network Analysis (ANP) and LARS-WG, for modeling the land suitably has been developed. Thus, for evaluating the lands suitability, the climatological data such as temperature, precipitation, growth degree day, relative humidity, freezing days, and sunshine hours were collected for the west Azerbaijan Province from synoptic stations data in 1987-2010 associated with the phonologic stages of canola growth. In addition to the climatological data, the earth resources like topographic layers, lands capability, soil depth and land uses were analyzed with focusing on the climatologic and ecological needs of canola.
All of canola plant requirements in base period (1987-2010) were simulated for three periods in the future. Therefore, the impact of climate change on temperature, precipitation, solar radiation and relative humidity were modeled using LARS-WG and ANN in the future climate condition. Also for simulating the data of future climate, the HADCAM3 of General Circulation Model and A1B and A2 scenarios were used. The importance of each criterion was completed by experts’ opinions. Due to the interaction of the criteria in the actual world, DEMATEL technique was used to recognize the relations among the criteria. ANP was used after completing the pairwise comparisons questionnaires by expert’s viewpoints.
 
Results and Dissection
In this study, the outputs of the minimum and maximum temperatures, the output rainfall and radiation of the model HADCM3, are used to estimate the relative humidity in the periods 2011-2030, 2046–2065 and 2081-2099. Based on the estimates through modelling in the artificial neural networks, the measures of relative humidity have been simulated. The results of the application of the introduced ANN structure for estimating the relative humidity in different modes of the functions and the number of neurons in the first and middle layers show that ANN have a good ability to estimate the relative humidity in the future periods. Results of ANP show that the most important canola plant requirement is elevation and after that are temperature and rainfall.
Implementation of the model shows that in the base period (1987-2010), 15% of lands in study area are in condition of very suitable and 31, 29 and 25% are in suitable, moderate suitable and unsuitable classes, respectively. Based on the results of HADCM3 model, in the second period (2011-2030) the very suitable class is 11% of the province and other classes are 38, 31 and 24 percent of the lands. Thus, in this period the suitable class compared with base period will increase. In the third period, with changes in temperature and rainfall, climate change will cause decrease of lands in condition of unsuitable and very suitable for canola cultivation and the percent of 2 and 3 classes will be increased. In the fourth period, following the changes in temperature and precipitation due to decreases in very suitable class, about 5% of lands and inappropriate lands (about 23 %) will cause decrease in suitable lands for cultivation of canola in West Azerbaijan.
 
Conclusion
The results indicate that the proposed method can well simulate the effects of climate change on Land Suitability Assessment to grow crops. Generally, changes in temperature and precipitation resulted in decreases in the areas of very suitable and suitable lands for cultivation of canola in West Azerbaijan providence. Additionally, the low limits lands will be increased significantly in comparison with the baseline period. As suitable lands for canola cultivation will be changed from 47% in the base period to 34% in the future periods.