Multiscale Spatiotemporal Variation Analysis of Regional Water Use Efficiency Based on Multifractals DOI Creative Commons

Tong Zhao,

Yanan Wang,

Yulu Zhang

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(22), P. 4269 - 4269

Published: Nov. 16, 2024

Understanding the complex variations in water use efficiency (WUE) is critical for optimizing agricultural productivity and resource management. Traditional analytical methods often fail to capture nonlinear multiscale inherent WUE, where multifractal theory offers distinct advantages. Given its limited application WUE studies, this paper analyzes spatiotemporal characteristics influencing factors of Anhui Province from 2001 2022 using a multifractal, approach. The results indicated that exhibited significant interannual variation, peaking summer, especially August (2.4552 gC·mm−1·m−2), with monthly average showing an inverted “V” shape. Across different spatial temporal scales, displayed clear characteristics. Temporally, variation fractal features between years was not prominent, while inter-seasonal most during summer. Spatially, patterns were observed hilly mountainous areas, particularly regions brown soil distribution. Rainfall identified as primary natural driver regional changes. This study aims promote sustainable resources ensuring stability production within protected farmlands.

Language: Английский

Multifractal Applications in Hydro-Climatology: A Comprehensive Review of Modern Methods DOI Creative Commons

Shamseena Vahab,

S. Adarsh

Fractal and Fractional, Journal Year: 2025, Volume and Issue: 9(1), P. 27 - 27

Published: Jan. 6, 2025

Complexity evaluation of hydro-climatic datasets is a challenging but essential pre-requisite for accurate modeling and subsequent planning. Changes in climate anthropogenic interventions amplify the complexity time-series. Understanding persistence fractal features may help us to develop new robust frameworks which can work well under non-stationary non-linear environments. Classical hydrology, rooted statistical physics, has been developed since 1980s modern alternatives based on de-trending, complex network, time–frequency principles have 2002. More specifically, this review presents procedures Multifractal Detrended Fluctuation Analysis (MFDFA) Arbitrary Order Hilbert Spectral (AOHSA), along with their applications field hydro-climatology. Moreover, study proposes network-based analysis (CNFA) framework multifractal daily streamflows as an alternative. The case proves efficacy CNMFA shows that it flexibility be applied visibility inverted schemes, effective comprising both high- low-amplitude fluctuations. comprehensive showed more than 75% literature focuses characteristic time-series using MFDFA rather modeling. Among variables, about 70% studies focused analyzing fine-resolution streamflow rainfall datasets. This recommends use CNMF hydro-climatology advocates necessity knowledge integration from multiple fields enhance applications. further asserts transforming characterization into operational hydrology highly warranted.

Language: Английский

Citations

1
Optimal distribution modeling and multifractal analysis of wind speed in the complex terrain of Sichuan Province, China DOI Creative Commons

Cun Zhan,

Renjuan Wei, Lu Zhao

et al.

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Feb. 7, 2025

Increasing drought events have threaten electricity supply security in the predominantly hydropower-based Sichuan Province. Wind power has potential to complement hydropower, yet its complex fluctuations required a systematic assessment. Accordingly, we evaluated maximum likelihood estimation and three goodness-of-fit tests identify optimal distribution model of daily wind speed records during 1961-2017 across 156 weather stations Province among six commonly used probability density distributions. The study further analyzed spatiotemporal features persistence multifractality various landform types using multifractal detrended fluctuation analysis. principal outcomes our indicated that generalized extreme value served as for fitting speeds Province, outperforming Weibull distribution. Persistence was evident all series Hurst index exceeds 0.5, with strongest mountainous areas weakest plains. Multifractality confirmed by non-linear dependencies Generalized Exponent [h(q)] mass exponent [τ(q)] on q, well spectrum widths exceeding 0.05. Among types, plains exhibited multifractality, followed plateaus, mountains showing multifractality. Long-range correlations were identified primarily caused narrower both shuffled surrogate series, stronger narrowness series. width mountain shuffle which slightly exceeded 0.05, highlighted determinative influence long-range correlations. Considering these findings, southwestern region emerges area farm development, given stability (persistence) moderate complexity (multifractality), crucial effective resource utilization hydropower-dominated settings. Our provides novel approach assessing resources offers guidance placement terrain regions, supporting sustainable energy diversification

Language: Английский

Citations

0
Unveiling climate complexity: a multifractal approach to drought, temperature, and precipitation analysis DOI
Farhang Rahmani

Acta Geophysica, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 9, 2025

Language: Английский

Citations

0
Multiscale Spatiotemporal Variation Analysis of Regional Water Use Efficiency Based on Multifractals DOI Creative Commons

Tong Zhao,

Yanan Wang,

Yulu Zhang

et al.

Remote Sensing, Journal Year: 2024, Volume and Issue: 16(22), P. 4269 - 4269

Published: Nov. 16, 2024

Understanding the complex variations in water use efficiency (WUE) is critical for optimizing agricultural productivity and resource management. Traditional analytical methods often fail to capture nonlinear multiscale inherent WUE, where multifractal theory offers distinct advantages. Given its limited application WUE studies, this paper analyzes spatiotemporal characteristics influencing factors of Anhui Province from 2001 2022 using a multifractal, approach. The results indicated that exhibited significant interannual variation, peaking summer, especially August (2.4552 gC·mm−1·m−2), with monthly average showing an inverted “V” shape. Across different spatial temporal scales, displayed clear characteristics. Temporally, variation fractal features between years was not prominent, while inter-seasonal most during summer. Spatially, patterns were observed hilly mountainous areas, particularly regions brown soil distribution. Rainfall identified as primary natural driver regional changes. This study aims promote sustainable resources ensuring stability production within protected farmlands.

Language: Английский

Citations

0