The density difference and weighted RVA approaches for assessing hydrologic regime alteration

Sheikh, Vahedberdi; Sadoddin, Amir; Najafinejad, Ali; Zare, Arash; Hollisaz, Arashk; Siroosi, Hamid; Gholipouri, Mostafa; Sheikh, Javad

doi:10.1016/j.jhydrol.2022.128450

Cited by 6 publications

(10 citation statements)

References 57 publications

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“…where f pre,i (x) and f post,i (x) are the probability density functions of ith IHA in pre-and post-impact periods, respectively. Since the IHAs cover a variety of indicators such as flow, duration, number, and rate, Vahedberdi et al (2022) suggested applying Gaussian kernel function to simulate the density function of IHA based on the theory of Gaussian Kernel Density Estimation (KDE), which has well fitted the distribution of the indicators in practice (Wglarczyk, 2018). The Gaussian kernel function is given as follows (Sheather, 2004;Silverman, 1986):…”

Section: Density Difference Approach (Dda)mentioning

confidence: 99%

“…The root mean square (RMS) of IHAs can ultimately be used to characterize the overall or group alteration of hydrologic regime by following Equation 29 (Huang et al, 2017;Vahedberdi et al, 2022):…”

Section: Degree Of Hydrological Alterationmentioning

confidence: 99%

“…Although the histograms could roughly reflect the distribution of extreme values rather than RVA method, the fundamental principle of the RVA, HMA, and HCA methods remains the same. The alteration of indicators is defined by comparing frequency of samples within a finite number of classes in pre‐ and post‐impact periods, which still ignore the differences within any individual class and suffer from subjectivity in the division of classes in frequency histograms (Vahedberdi et al, 2022; Wglarczyk, 2018). Besides, as long as the finite classes are described in histograms, the sample points around the class boundaries will inevitably and severely influence the accuracy of alteration estimation (Kim & Billard, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Once the density curve in post-impact period significantly distinguishes with that in pre-impact period, the IHAs and hydrologic regime would undoubtedly suffer violent alterations. Vahedberdi et al (2022) proposed a Density Difference Approach (DDA) based on the difference of probability density functions in preand post-impact periods of IHAs, which was proven to be more accurate and comprehensive to estimate the alteration of hydrologic regime than the RVA, HMA, and HCA methods. The RRVA method focuses on the morphology of IHAs in time order, that is, how IHAs vary with time series.…”

mentioning

confidence: 99%

“…The annual average flow will not only have a direct influence on the hydrological flow indicators, but also indirectly influence the downstream hydrological regime through the decisionmaking of reservoir operation(Kangrang et al, 2017), especially when encountering consecutive dry (wet) hydrologic years or heavily dry (wet) hydrologic years. Since the probability density function is much accurate to describe the distribution and the DDA method performs much better than RVA, HMA, and HCA methods(Vahedberdi et al, 2022), the alteration of ith IHA in JPDDA (D JPDDA,i ) can be determined by Equations (21-22):…”

mentioning

confidence: 99%

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A novel Joint Probability Density Difference Approach for assessing the alteration of hydrologic regime

Zhong,

Guo,

Wang

et al. 2024

River Research & Apps

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The construction and operation of upstream reservoirs have significantly altered downstream hydrologic regime. Appropriate and quantifiable assessment method for the alteration of hydrologic regime is considerably vital and emergent for ecological protection and restoration. The Range of Variability Approach (RVA) and modified RVA methods have been widely used in practice to assess the hydrological alteration. However, these methods have failed to concurrently describe the distribution of indicator and morphological features in detail, which might inevitably lead to the misjudgment of alteration. This paper proposes a Joint Probability Density Difference Approach (JPDDA) method to address the major drawbacks of these previous methods with the introduction of Gaussian Kernel Density Estimation (KDE) and copula function. The annual average flow is selected as the reference variable to construct a proper joint probability density function between itself and other hydrological alteration indicators. The JPDDA method could describe the marginal distribution in detail through Gaussian KDE and also link the morphological features with copula function. Along with pervious methods, the hydrological alterations at Yichang hydrological station, Yangtze River are estimated based on the measured flow from 1949 to 2022. It is shown that the hydrologic regime has suffered from a moderate or even heavy alteration under the influence of massive upstream cascade reservoirs, and the JPDDA outperforms the other methods in terms of rationality and stability for practical assessments. Thus, the proposed JPDDA method is strongly advised to handle the hydrological alteration and could provide a reasonable reference for ecological operation.

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