Towards a Sustainable Agriculture Development Based on the Field Vulnerability Evaluation in Miandoab Region, Iran

Maryam Vaziri, S. Mahmoudi, F. Shahbazi, M. Masihabadi, H. Rezaei
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Abstract

Exploring the agro-ecological limits is necessary in sustainable agriculture development. Soil contamination and erosion are two main indices in land vulnerability evaluation. Raizal and Pantanal models within MicroLEIS DSS, the Ero&Con package, were established in identification of vulnerable areas due to erosion and contamination risks, respectively. This study was performed in Miandoab region under different land-use scenarios with approximately 5269 ha extension in the North-West of Iran (west Azarbaijan). The extracted morphological and analytical data from 62 soil profiles representative of the study area were used as basic information. A total of 17 land unites were then classified according to the Geopedologic approach. The benchmark soil profiles were categorized as Typic Torripsamments, Typic Haploxerepts, Typic Haplocambids and Typic Haplargids. The results taken by using the aforementioned models were presented as an attainable mode whereas the management practices were not mentioned. The application of Raizal model revealed that the water erosion has less impact than wind erosion on vulnerability classes whereas climate change will result extremely high vulnerable area in the future. In terms of soil contamination risks resulted by Pantanal model, phosphorous risks were classified in V2 (23%) and V4 (77%). Also, heavy metal and nitrogen as well as pesticide contamination vulnerability risks were classified as V3 and V4. Since there was no different in classes when cultivating maize and wheat, the attainable vulnerability classes are equal with the actual ones. Overall, this research demonstrates that application of models increase our understanding about the behavior of soil and landscape interactions.
基于田间脆弱性评价的伊朗Miandoab地区农业可持续发展
探索农业生态极限是农业可持续发展的必然要求。土壤污染和侵蚀是土地脆弱性评价的两个主要指标。MicroLEIS DSS (Ero&Con软件包)中的Raizal和Pantanal模型分别用于识别受侵蚀和污染风险影响的脆弱区域。这项研究是在Miandoab地区进行的,在不同的土地利用情景下,在伊朗西北部(Azarbaijan西部)扩展了大约5269公顷。提取了具有代表性的62个土壤剖面的形态和分析数据作为基本信息。然后根据地质方法对17个陆地单元进行了分类。基准土壤剖面分为典型Torripsamments、典型Haploxerepts、典型Haplocambids和典型Haplargids。使用上述模型所获得的结果作为可实现的模型提出,而没有提到管理实践。Raizal模型的应用表明,水蚀对脆弱性等级的影响小于风蚀,而气候变化将在未来造成极高的脆弱性等级。根据Pantanal模型得出的土壤污染风险,磷风险分为V2(23%)和V4(77%)。重金属、氮和农药污染脆弱性风险分别为V3和V4。由于种植玉米和小麦时不存在等级差异,因此可得脆弱性等级与实际脆弱性等级相等。总的来说,本研究表明,模型的应用增加了我们对土壤和景观相互作用行为的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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