首页> 外文会议>Annual National Conference of the American Society of Mining and Reclamation >A SYSTEM TO EVALUATE PRIME FARMLAND RECLAMATION SUCCESS BASED ON SPATIAL SOIL PROPERTIES
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A SYSTEM TO EVALUATE PRIME FARMLAND RECLAMATION SUCCESS BASED ON SPATIAL SOIL PROPERTIES

机译:基于空间土壤性质评估粉体耕地回收成功的制度

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Since the passage of Public Law 95-87, the Surface Mining Control and Reclamation Act (SMCRA) in 1977, reclamation success of prime farmland after coal mining has been determined by long-term crop yield testing. States such as Illinois and Indiana require that reclamation success be based on crop production of mined land. This process often can continue for many years, especially for lands failing to meet production standards in a specified time period. Needs have been expressed by landowners, mine operators, and regulators for methods to expediate this process. A soil property based model could relieve this burden and ensure the most efficient process for returning the soil resource to the landowner. The objective of our work was to develop a soil-based model to replace the current crop yield-based system and to evaluate mined- land for diagnostic purposes. Geo-referenced corn (Zea mays L.), soybean [Glycine max (L.) Merr.], and wheat (Triticum aestivum L.) yield, cone penetrometer test (CPT), VIS-NIR spectrophotometer, apparent electrical conductivity (ECa), elevation and terrain derivatives, fertility, and other site characteristic data were collected on fields at the Lewis Mine site in southwestern IN, the Cedar Creek Mine site in western IL, and the Wildcat Hills Mine site in southern IL. Soil-based productivity models were developed using regression and multivariate techniques to assign probabilities of meeting crop yield standards at the partial-field level. Our research indicates that soil compaction and water availability primarily influence a field's ability to meet crop yield standards across time. Model validation between fields and among sites has been encouraging, thus we propose modeling soil variability as a diagnostic tool to identify problematic field areas and to complement yield-based requirements.
机译:自公法95-87的通过以来,1977年表面采矿控制和填海法(SMCRA),煤炭矿业后粉煤后的填海成功由长期作物产量检测确定。伊利诺伊州和印第安纳等各国要求填海层成功基于作物生产的土地。此过程通常可以持续多年,特别是对于未能在指定时间段内未能满足生产标准的土地。需要由土地所有者,矿山运营商和监管机构表达,以便加快此过程的方法。基于土壤属性的模型可以减轻这种负担,并确保将土壤资源返回土地所有者的最有效过程。我们工作的目的是开发一种基于土壤的模型,以取代当前的作物产量为基础的系统,并评估诊断目的的开采。地理参考玉米(Zea Mays L.),大豆[甘氨酸Max(L.)Merr。],小麦(Triticum aestivum L.)产率,锥形渗透分光光度计,视觉电导率(ECA) ),在西南雪松河矿场地区的刘易斯矿场地区的刘易斯矿场地区的田地,生育和地形衍生物,生育和其他场地特征数据以及南伊尼尔南部的野猫山矿场。利用回归和多变量技术开发了土壤基生产率模型,以分配在局部场级别满足作物产量标准的概率。我们的研究表明,土壤压实和水可用性主要影响领域跨时达到作物产量标准的能力。场之间以及站点之间进行模型验证一直鼓励,为此,我们建议模拟土壤变异作为诊断工具,以确定有问题的场区和补充基于产量的要求。

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