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Mapping multi-year ground water salinity patterns in irrigation areas using time-series analysis of ground water salinity maps

机译:使用地下水盐度图的时间序列分析绘制灌溉区多年地下水盐度模式

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摘要

In irrigation areas, ground water salinity (GWS) levels may vary depending on the amount and quality of irrigation water applied and on the activity of the drainage system. GWS plays a vital role in irrigation systems by influencing whether the environment is suitable for plant growth. Hence, it is necessary to monitor changes in GWS both temporally and spatially. Maps are generally used to visualize this information. However, evaluation of temporal and spatial variations of GWS can be difficult because of the necessity of assessing many maps together to understand both temporal and spatial changes. In this study, a data assessment method that can be used for multi-year ground water salinity evaluations is presented. The method looks at the spatial and temporal relationships between the main salinity classes present in the study area, their typical locations (i.e. areas where the salinity classes are most frequently located), and the alternate salinity classes in those locations in any of the years of the time series. As a case study, the method was applied to multi-year (1990-2000) GWS observations in the Mustafakemalpasa irrigation project (19 370 ha) in the Marmara region of north-western Turkey.
机译:在灌溉区,地下水盐度(GWS)的水平可能会因灌溉水的用量和质量以及排水系统的活动而异。 GWS通过影响环境是否适合植物生长,在灌溉系统中发挥至关重要的作用。因此,有必要在时间和空间上监视GWS的变化。地图通常用于可视化此信息。但是,由于必须共同评估许多地图以了解时空变化,因此可能难以对GWS的时空变化进行评估。在这项研究中,提出了一种可用于多年地下水盐度评估的数据评估方法。该方法研究研究区域中存在的主要盐度类别,其典型位置(即盐度类别最常位于的区域)以及这些年份中任何年份中这些位置的替代盐度类别之间的时空关系。时间序列。作为案例研究,该方法被应用于土耳其西北部马尔马拉地区Mustafakemalpasa灌溉项目(19 370公顷)中的多年期(1990-2000年)全球观测系统观测。

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