Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study

Chiaudani, Alessandro; Curzio, Diego Di; Palmucci, William; Pasculli, Antonio; Polemio, M.; Rusi, Sergio

doi:10.3390/w9110850

Cited by 39 publications

(28 citation statements)

References 74 publications

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“…Four of these monitoring points were the same ones that we have analyzed. Similarly, the time-frequency analysis of rainfall, river level and groundwater level by Chiaudani et al (2017), combined with hydrogeological knowledge, revealed the conceptual hydrodynamic model of an alluvial aquifer in central Italy.…”

Section: Ngwaorgmentioning

confidence: 95%

“…Mathematical methods applying time series analysis are increasingly being used to improve the understanding of surface water/groundwater interactions (Kaplan et al 2010;Aguilera et al 2013;Acworth et al 2015;Chiaudani et al 2017;Oh et al 2017;Haaf and Barthel 2018;Trásy et al 2018). Acworth et al (2015) successfully used Fourier analysis on daily and sub-daily scales to identify responses to evapotranspiration in hydraulic head fluctuations.…”

Section: Ngwaorgmentioning

confidence: 99%

“…Time series decomposition is another approach used to characterize hydrological patterns (Machiwal and Jha 2006;Von Asmuth et al 2008;Peterson and Western 2014;Wang et al 2015;Chiaudani et al 2017;Haaf and Barthel 2018). Concerning this method, there is a new flexible additive model developed by Facebook (Prophet) that considers non-periodic changes in trends as well as customizable seasonal periodic components in a Bayesian framework as easily interpretable parameters (Taylor and Letham 2018a).…”

Section: Ngwaorgmentioning

confidence: 99%

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Unraveling the Hydrological Behavior of a Coastal Pond in Doñana National Park (Southwest Spain)

Fernández-Ayuso¹,

Aguilera²,

Guardiola‐Albert³

et al. 2019

Groundwater

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Time series analysis methods have been used to detect behavioral patterns in a set of nine time series. These series contained information in a 3‐h time step about meteorological, hydrological and tidal data of a sand dune pond area located in Doñana National Park in the southwest of Spain. The methods used, such as wavelet analysis and additive seasonal decomposition, had never been applied before in the types of ecosystems studied. These approaches have improved the current knowledge of the conceptual model of the Santa Olalla pond system, the only system with a permanent hydroperiod located in this protected area. In addition, complex surface water‐groundwater interactions, not visible through descriptive methods, have been distinguished to have a strong seasonal component. Finally, we evaluated the effect of pumping activity in a nearby coastal resort on the water supply of the Santa Olalla pond system. Although direct damage to this sand dune pond has not yet been identified, special attention must be paid in order to maintain groundwater inputs that are integral to maintaining its current status.

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Section: Ngwaorgmentioning

confidence: 95%

Section: Ngwaorgmentioning

confidence: 99%

Section: Ngwaorgmentioning

confidence: 99%

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Unraveling the Hydrological Behavior of a Coastal Pond in Doñana National Park (Southwest Spain)

Fernández-Ayuso¹,

Aguilera²,

Guardiola‐Albert³

et al. 2019

Groundwater

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“…The memory effect of the time series is usually estimated until the autocorrelation function falls below the significance threshold for the first time. Many studies adopted 0.2 as the significance threshold to measure the memory effect of hydrological time series because time series with lower autocorrelation function can be considered quasi‐independent (Chiaudani et al, ; Delbart et al, ; Mangin, ). The function value of 0.2 was adopted as the predefined evaluating value in this study.…”

Section: Methodsmentioning

confidence: 99%

Statistical analyses of the effect of a drainage tunnel on landslide hydrogeological characteristics

Wang

et al. 2020

Hydrological Processes

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A high groundwater level is highly relevant to the slope instability. Drainage tunnel is an effective method for groundwater level control, but its effect on landslide hydrogeological characteristics is rarely discussed. This study analysed the changes of the landslide hydrogeological characteristics under the effect of a drainage tunnel by real-time monitoring of rainfall, groundwater level, and surface displacement. The trend and mutation of groundwater level are analysed by the Mann-Kendall test and the Mann-Kendall mutation test. The memory effect of groundwater in the landslide area was analysed using autocorrelation analysis. The response characteristics of groundwater level to rainfall were evaluated using cross-correlation analysis and mutual information theory. Variations of groundwater levels were further investigated based on hydrograph analysis. Results showed that the groundwater level had a downward trend from 2016 to 2017. The significant downward trend of groundwater levels began in August 2016. The memory effect of groundwater levels was longer under the effect of the drainage tunnel. Before the construction of the drainage tunnel, the response time of groundwater to rainfall was less than 3 hr and rainfall can generate dramatic groundwater level variations. After the drainage tunnel was completed, time lags can be observed in the groundwater response, and the variation of groundwater levels was smaller than before. A strong correlation was found between groundwater levels and the landslide movement. This study demonstrated that the drainage tunnel had effectively controlled the groundwater level in the landslide and ensured the stability of the landslide.

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“…Many approaches have been proposed to analyze the relations between the rainfall time series over the recharge area and the spring outflow [5]. These models, for example, are based on continuous and discrete wavelet analysis [6,7], cross-correlation analysis [8,9,10], or machine learning models [11]. Other studies, concerning karst springs, have employed time-series analysis studying transfer function between rainfall and spring discharge, obtained by black-box models [12] or artificial neural network [12].…”

Section: Introductionmentioning

confidence: 99%

Karst Spring Discharge Evaluation Using a Rainfall-Input Model: The Case Study of Capodacqua di Spigno Spring (Central Italy)

Sappa¹,

Fm²,

Iacurto³

et al. 2019

Preprint

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The increasing occurrence of widespread drought phenomena is a global environmental emergency, especially for the effects of ongoing climate change on groundwater availability. Dry years and extreme temperatures are common drivers of current climate impacts all over the world, including, for example, freshwater supply for drinking and agriculture purposes, ecosystems, forestry, health, etc.. In this frame, to ensure temporal water availability in water-stressed areas, a sustainable groundwater management is an increasing challenge. Most of groundwater in the South-East Latium Region, Central Italy, as in the whole Apennine Mountains chain, is stored in karst aquifers. In this area important water resources are present, but even here in the last decades they are affected by groundwater depletion as a consequence of occurring drought events, the upward trend in the globally average temperature and the increasing of anthropogenic activities. Due to the lack of flow rates data of springs in many areas of Italy, the spring response modeling could be a useful tool for supporting a proper water resource management. Several research studies proposed methods based on relationships between spring discharges and rainfall data. The goal of this paper is to propose a model, based on rainfall-discharges cross correlations, in order to assess the spring flow rate patterns of Capodacqua di Spigno Spring, which is the main one in the study area. The results obtained using the developed model has been compared to an existing method that uses the SPI index for the estimation of the minimum annual spring discharge.

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Statistical and Fractal Approaches on Long Time-Series to Surface-Water/Groundwater Relationship Assessment: A Central Italy Alluvial Plain Case Study

Cited by 39 publications

References 74 publications

Unraveling the Hydrological Behavior of a Coastal Pond in Doñana National Park (Southwest Spain)

Unraveling the Hydrological Behavior of a Coastal Pond in Doñana National Park (Southwest Spain)

Statistical analyses of the effect of a drainage tunnel on landslide hydrogeological characteristics

Karst Spring Discharge Evaluation Using a Rainfall-Input Model: The Case Study of Capodacqua di Spigno Spring (Central Italy)

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