Shannon information entropy for assessing space–time variability of rainfall and streamflow in semiarid region

Silva, Vicente de P. Rodrigues da; Filho, Adelgcio F. Belo; Almeida, Rafaela Silveira Rodrigues; Holanda, Romildo Morant de; Campos, João Hugo Baracuy da Cunha

doi:10.1016/j.scitotenv.2015.11.082

Cited by 38 publications

(8 citation statements)

References 36 publications

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“…The concept of entropy created by Clausius [ 56 ], which is a measurement of disorder degree of the system, derives from thermodynamics. While the concept of information entropy proposed by Shannon in 1948 [ 57 ] describes the discrete degree of some index data. The bigger the discrete degree, the greater the influence of the indicator on evaluation results, and the bigger the index weight [ 58 ].…”

Section: Index Weights Calculation Methodsmentioning

confidence: 99%

Multi-Index Evaluation for Flood Disaster from Sustainable Perspective: A Case Study of Xinjiang in China

Dou

Xue

Zhao

et al. 2018

IJERPH

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The floods have undermined the sustainable construction of cities because of their sudden and destruction. To reduce the losses caused by floods, it is necessary to make a reasonable evaluation for historical floods and provide scientific guidance for future precaution. Previous research mainly used subjective/objective weights or barely made static analysis without considering the uncertainty and ambiguity of floods. Therefore, this study proposed a variable fuzzy recognition model, based on combined weights, to evaluate floods, including the determination of index weights and the choice of evaluation model. To make the index weights reflect both subjective experience and objective data, the combined weights were proposed and calculated based on the principle of minimum identification information. Then, the relative membership degree matrix and evaluation results can be worked out by the variable fuzzy recognition model. Conclusions indicated that the combined weights were more convincing than simply subjective or objective weights. Moreover, the variable fuzzy recognition model, by changing model parameters, got stable evaluation results of the sample data. Therefore, the model can improve the credibility of evaluation and the conclusions can provide reasonable suggestions for management departments.

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Section: Index Weights Calculation Methodsmentioning

confidence: 99%

Multi-Index Evaluation for Flood Disaster from Sustainable Perspective: A Case Study of Xinjiang in China

Dou

Xue

Zhao

et al. 2018

IJERPH

View full text Add to dashboard Cite

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“…Entropy is closely related to the partition of equivalent relations in finite networks, and we use it to describe the structure and complexity of networks. An appropriately defined probability distribution, Shannon entropy is a numerical expression of network structure 18 .…”

Section: Methodsmentioning

confidence: 99%

Analysis and evaluation of the entropy indices of a static network structure

Cai

Cui

Stanley

2017

Sci Rep

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Although degree distribution entropy (DDE), SD structure entropy (SDSE), Wu structure entropy (WSE) and FB structure entropy (FBSE) are four static network structure entropy indices widely used to quantify the heterogeneity of a complex network, previous studies have paid little attention to their differing abilities to describe network structure. We calculate these four structure entropies for four benchmark networks and compare the results by measuring the ability of each index to characterize network heterogeneity. We find that SDSE and FBSE more accurately characterize network heterogeneity than WSE and DDE. We also find that existing benchmark networks fail to distinguish SDSE and FBSE because they cannot discriminate local and global network heterogeneity. We solve this problem by proposing an evolving caveman network that reveals the differences between structure entropy indices by comparing the sensitivities during the network evolutionary process. Mathematical analysis and computational simulation both indicate that FBSE describes the global topology variation in the evolutionary process of a caveman network, and that the other three structure entropy indices reflect only local network heterogeneity. Our study offers an expansive view of the structural complexity of networks and expands our understanding of complex network behavior.

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“…Based on the annual CMORPH and ED global rainfall erosivity maps for specific years in the period from 1998-2019, the Mann-Kendall trend test was also calculated for each grid cell. The Mann-Kendall test is one of the most widely applied tests for detection of changes in the environmental data (Burn and Hag Elnur, 2002;Rodrigues da Silva et al, 2016 (Burn and Hag Elnur, 2002;Hamed, 2008;McLeod, 2011).…”

Section: Trendsmentioning

confidence: 99%

Exploring the possible role of satellite-based rainfall data to estimate inter‐ and intra‐annual global rainfall erosivity

Bezak

Borrelli

Panagos

2021

Preprint

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Abstract. Despite recent developments in modelling global soil erosion by water, to date no substantial progress has been made towards more dynamic inter- and intra-annual assessments. In this regard, the main challenge is still represented by the limited availability of high temporal resolution rainfall data needed to estimate rainstorms rainfall erosivity. As this data scarcity is likely to characterize the upcoming years, the suitability of alternative approaches to estimate global rainfall erosivity using satellite-based rainfall data was explored. For this purpose, the high spatial and temporal resolution global precipitation estimates obtained with the NOAA CDR Climate Prediction Center MORPHing technique (CMORPH) were used. Alternatively, the erosivity density (ED) concept was used to estimate global rainfall erosivity as well. The obtained global estimates of rainfall erosivity were validated against the pluviograph data included in the Global Rainfall Erosivity Database (GloREDa). Overall, results indicated that the CMORPH estimates have a marked tendency to underestimate rainfall erosivity when compared to the GloREDa estimates. The most substantial underestimations were observed in areas with the highest rainfall erosivity values. At continental level, the best agreement between annual CMORPH and interpolated GloREDa rainfall erosivity map was observed in Europe. Worse agreement was detected for Africa and South America. Further analyses conducted at monthly scale for Europe revealed seasonal misalignments, with the occurrence of underestimation of the CMORPH estimates in the summer period and overestimation in the winter period compared to GloREDa. The best agreement between the two approaches to estimate rainfall erosivity was found for autumn, especially in Central and Eastern Europe. Conducted analysis suggested that satellite-based approaches for estimation of rainfall erosivity appear to be more suitable for low-erosivity regions, while in high erosivity regions and seasons (> 1,000–2,000 MJ mm ha−1 h−1 yr−1), the agreement with estimates obtained from pluviograph data such as GloREDa is lower. Concerning the ED estimates, this second approach to estimate rainfall erosivity yielded better agreement with GloREDa estimates compared to CMORPH. The application of a simple-linear function correction of the CMORPH data was applied to provide better fit to the GloREDa and correct systematic underestimation. This correction improved the performance of the CMORPH but in areas with the highest rainfall erosivity rates the underestimation was still observed. A preliminary trend analysis of the CMORPH rainfall erosivity estimates was also performed for the 1998–2019 period. According to this trend analysis, increasing and statistically significant trend was more frequently observed than decreasing trend.

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Shannon information entropy for assessing space–time variability of rainfall and streamflow in semiarid region

Cited by 38 publications

References 36 publications

Multi-Index Evaluation for Flood Disaster from Sustainable Perspective: A Case Study of Xinjiang in China

Multi-Index Evaluation for Flood Disaster from Sustainable Perspective: A Case Study of Xinjiang in China

Analysis and evaluation of the entropy indices of a static network structure

Exploring the possible role of satellite-based rainfall data to estimate inter‐ and intra‐annual global rainfall erosivity

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