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Hydrologic Alteration Analysis

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Methodologies

The statistical methods in this study include the non-parametric Mann-Kendall rank statistic method for trend analysis; the Pettitt-Mann-Whitney change-point statistics (Pettitt, 1979, 1980) to identify the hydrologic change points; and the Indicators of Hydrologic Alterations (IHA) program (Richter et al., 1996, 1998) to evaluate hydrologic alterations of flow and stage data in periods before and after change points.
Hydrologic Alteration Analysis
The analysis in this study adopted the IHA and Eco-flow statistical analysis. IHA statistics is the most commonly used method for hydrologic alteration analysis due to its simplicity in application. However, the eco-flow statistics have been proved to be more efficient to avoid redundancy …show more content…

The area below the pre-change point FDC and above the post-change point FDC represents the amount of water now unavailable to the river due to flow alteration. Eco-deficit is then defined as the ratio of this area over the total area under the pre-change point FDC. This ratio represents the fraction of stream flow no longer available to the river during that period. Conversely, eco-surplus is the area above the pre-change point FDC and below the post-change point FDC divided by the total area under the pre-change point FDC. In another sense, the eco-deficit and eco-surplus are merely the relative change of accumulated flow volume between post- and pre-change periods. The transition point (TP) in the figure indicates the transition from eco-surplus to eco-deficit or vice …show more content…

The DHRAM scores are subjective by assigning different impact scores based on the defined threshold absolute percentage change of mean and the coefficient of variation (CV). In this study, the Fuzzy Comprehensive Evaluation (FCE) method was used to objectively rank the overall degree of hydrologic alteration evaluated either by the IHA method or by the eco-statistical method. Details of this application will be discussed in a subsequent paper. In this study, the FCE method was used to calculate fuzzy vectors from the RVA of each IHA parameter, the indices of seasonal eco-surplus and eco-deficit, and from the seasonal indices showing only eco-surplus. A higher value of the fuzzy vector represents greater overall hydrological

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