Faculty of Mining, Geology and Petroleum Engineering, University of Zagreb, Pierottijeva 6, 10000 Zagreb, Croatia.
Ground Water. 2010 Jul-Aug;48(4):598-603. doi: 10.1111/j.1745-6584.2009.00669.x. Epub 2010 Jan 20.
The fully automated objective-based method for master recession curve (MRC) separation was developed by using Microsoft Excel spreadsheet and Visual Basic for Applications (VBA) code. The core of the program code is used to construct an MRC by using the adapted matching strip method (Posavec et al. 2006). Criteria for separating the MRC into two or three segments are determined from the flow-duration curve and are represented as the probable range of percent of flow rate duration. Successive separations are performed automatically on two and three MRCs using sets of percent of flow rate duration from selected ranges and an optimal separation model scenario, having the highest average coefficient of determination R(2), is selected as the most appropriate one. The resulting separated master recession curves are presented graphically, whereas the statistics are presented numerically, all in separate sheets. Examples of field data obtained from two springs in Istria, Croatia, are used to illustrate its application. The freely available Excel spreadsheet and VBA program ensures the ease of use and applicability for larger data sets.
完全自动化的基于目标的主衰退曲线（MRC）分离方法是使用 Microsoft Excel 电子表格和应用程序的 Visual Basic（VBA）代码开发的。程序代码的核心用于使用适应匹配带方法（Posavec 等人，2006）构建 MRC。将 MRC 分离为两个或三个部分的标准是从流量持续时间曲线确定的，并表示为流量持续时间百分比的可能范围。使用选定范围和最佳分离模型场景的流量百分比的集合，在两个和三个 MRC 上自动执行连续分离，选择具有最高平均确定系数 R(2)的分离模型作为最合适的模型。分离后的主衰退曲线以图形方式呈现，而统计数据则以数字方式呈现，均在单独的工作表中呈现。来自克罗地亚伊斯特拉的两个泉的实地数据示例用于说明其应用。免费提供的 Excel 电子表格和 VBA 程序确保了更大数据集的易用性和适用性。
