Spatial and temporal Hurst exponent variability of rainfall series based on the climatological distribution in a semiarid region in Mexico

López-Lambraño, Álvaro Alberto; Fuentes, Carlos; Mata, J.; López-Lambraño, Mariangela

doi:10.20937/atm.2018.31.03.02

Cited by 26 publications

(16 citation statements)

References 53 publications

(56 reference statements)

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“…The rescaled range analysis (R/S analysis) Hurst exponent, based on auto-covariance (a function of lag [38] that gives the covariance of the process with itself at pairs of time points), can be applied as a parameter to spot the consistency of time series data of a natural phenomenon [22]. This parameter has widely been used in several fields like geology [39], hydrology [40], economics [41], and climatology [42]. The auto-covariance function can capture long-term memory effects that decay exponentially with a spectral density that tends to infinity [22].…”

Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Vegetation Dynamic and Persistence under Climatic and Anthropogenic Factors

et al. 2020

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Land degradation reflected by vegetation is a commonly used practice to monitor desertification. To retrieve important information for ecosystem management accurate assessment of desertification is necessary. The major factors that drive vegetation dynamics in arid and semi-arid regions are climate and anthropogenic activities. Progression of desertification is expected to exacerbate under future climate change scenarios, through precipitation variability, increased drought frequency and persistence of dry conditions. This study examined spatiotemporal vegetation dynamics in arid regions of Sindh, Pakistan, using annual and growing season Normalized Difference Vegetation Index (NDVI) data from 2000 to 2017, and explored the climatic and anthropogenic effects on vegetation. Results showed an overall upward trend (annual 86.71% and growing season 82.7%) and partial downward trend (annual 13.28% and growing season 17.3%) in the study area. NDVI showed the highest significant increase in cropland region during annual, whereas during growing season the highest significant increase was observed in savannas. Overall high consistency in future vegetation trends in arid regions of Sindh province is observed. Stable and steady development region (annual 48.45% and growing 42.80%) dominates the future vegetation trends. Based on the Hurst exponent and vegetation dynamics of the past, improvement in vegetation cover is predicted for a large area (annual 44.49% and growing 30.77%), and a small area is predicted to have decline in vegetation activity (annual 0.09% and growing 3.04%). Results revealed that vegetation growth in the study area is a combined result of climatic and anthropogenic factors; however, in the future multi-controls are expected to have a slightly larger impact on annual positive development than climate whereas positive development in growing season is more likely to continue in future under the control of climate variability.

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Section: Introductionmentioning

confidence: 99%

Spatio-Temporal Vegetation Dynamic and Persistence under Climatic and Anthropogenic Factors

et al. 2020

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“…These results constitute a starting point for risk management and flood resilience. These results can also be complemented by a detailed analysis of the rainfall time series for the State of Baja California [35].…”

Section: Resultsmentioning

confidence: 99%

Rainfall Intensity-Duration-Frequency Relationship. Case Study: Depth-Duration Ratio in a Semi-Arid Zone in Mexico

et al. 2020

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Intensity–Duration–Frequency (IDF) curves describe the relationship between rainfall intensity, rainfall duration, and return period. They are commonly used in the design, planning and operation of hydrologic, hydraulic, and water resource systems. Considering the intense rainfall presence with flooding occurrences, limited data used to develop IDF curves, and importance to improve the IDF design for the Ensenada City in Baja California, this research study aims to investigate the use and combinations of pluviograph and daily records, to assess rain behavior around the city, and select a suitable method that provides the best results of IDF relationship, consequently updating the IDF relationship for the city for return periods of 10, 25, 50, and 100 years. The IDF relationship is determined through frequency analysis of rainfall observations. Also, annual maximum rainfall intensity for several duration and return periods has been analyzed according to the statistical distribution of Gumbel Extreme Value (GEV). Thus, Chen’s method was evaluated based on the depth-duration ratio (R) from the zone, and the development of the IDF relationship for the rain gauges stations was focused on estimating the most suitable (R) ratio; chosen from testing several methods and analyzing the rain in the region from California and Baja California. The determined values of the rain for one hour and return period of 2 years obtained were compared to the values of some cities in California and Baja California, with a range between 10 and 16.61 mm, and the values of the (R) ratio are in a range between 0.35 and 0.44; this range is close to the (R) ratio of 0.44 for one station in Tijuana, a city 100 km far from Ensenada. The values found here correspond to the rainfall characteristics of the zone; therefore, the method used in this study can be replicated to other semi-arid zones with the same rain characteristics. Finally, it is suggested that these results of the IDF relationship should be incorporated on the Norm of the State of Baja California as the recurrence update requires it upon recommendation. This study is the starting point to other studies that imply the calculation of a peak flow and evaluation of hydraulic structures as an input to help improve flood resilience in the city of Ensenada.

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“…The Hurst exponent is known to be a quantitative measure of memory for time and spatial series [ 13 , 22 , 23 ]. At H = 0.5, a series is random and the previous, current, and subsequent values are not related.…”

Section: Resultsmentioning

confidence: 99%

Memory Effect in the Spatial Series Based on Diamond and Graphite Crystals

et al. 2020

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To study the relation between the structure of a compound and its properties is one of the fundamental trends in chemistry and materials science. A classic example is the well-known influence of the structures of diamond and graphite on their physicochemical properties, in particular, hardness. However, some other properties of these allotropic modifications of carbon, e.g., fractal properties, are poorly understood. In this work, the spatial series (interatomic distance histograms) calculated using the crystal structures of diamond and graphite are investigated. Hurst exponents H are estimated using detrended fluctuation analysis and power spectral density. The values of H are found to be 0.27–0.32 and 0.37–0.42 for diamond and graphite, respectively. The calculated data suggest that the spatial series have long memory with a negative correlation between the terms of the series; that is, they are antipersistent.

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Spatial and temporal Hurst exponent variability of rainfall series based on the climatological distribution in a semiarid region in Mexico

Cited by 26 publications

References 53 publications

Spatio-Temporal Vegetation Dynamic and Persistence under Climatic and Anthropogenic Factors

Spatio-Temporal Vegetation Dynamic and Persistence under Climatic and Anthropogenic Factors

Rainfall Intensity-Duration-Frequency Relationship. Case Study: Depth-Duration Ratio in a Semi-Arid Zone in Mexico

Memory Effect in the Spatial Series Based on Diamond and Graphite Crystals

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