Investigating the Spatial and Temporal Variability of Precipitation using Entropy Theory

Atieh, Maya; Rudra, R. P.; Gharabaghi, Bahram; Lubitz, David

doi:10.14796/jwmm.c420

Cited by 4 publications

(5 citation statements)

References 58 publications

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“…Similarly, the iso-information redundancy maps of TCs in the Middle Vaal was determined and analysed for WR90, WR2005 and WR2012. There is no universal rule to define entropic zone values; hence they are usually determined arbitrarily as far as entropy related studies are concerned [ 5 , 13 , 44 ]. For that, the range of RCE ( R ) was arbitrarily divided into intervals to define zones of the same information transmission (information redundancy).…”

Section: Methodsmentioning

confidence: 99%

Shannon Entropy for Measuring Spatial Complexity Associated with Mean Annual Runoff of Tertiary Catchments of the Middle Vaal Basin in South Africa

Ilunga

2019

Entropy

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This study evaluates essentially mean annual runoff (MAR) information gain/loss for tertiary catchments (TCs) in the Middle Vaal basin. Data sets from surface water resources (WR) of South Africa 1990 (WR90), 2005 (WR2005) and 2012 (WR2012) referred in this study as hydrological phases, are used in this evaluation. The spatial complexity level or information redundancy associated with MAR of TCs is derived as well as the relative change in entropy of TCs between hydrological phases. Redundancy and relative change in entropy are shown to coincide under specific conditions. Finally, the spatial distributions of MAR iso-information transmission (i.e., gain or loss) and MAR iso-information redundancy are established for the Middle Vaal basin.

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Section: Methodsmentioning

confidence: 99%

Shannon Entropy for Measuring Spatial Complexity Associated with Mean Annual Runoff of Tertiary Catchments of the Middle Vaal Basin in South Africa

Ilunga

2019

Entropy

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“…The precipitation variability can be quantitatively measured based on entropy theory using different precipitation time series (Atieh et al ., 2017; Roushangar and Alizadeh, 2018; Zhou and Lei, 2020). In this study, we investigated the seasonal variability in the distribution of the number of precipitation days and amounts among the different months within a year.…”

Section: Methodsmentioning

confidence: 99%

“…Basically, a higher entropy is assigned to more random and complicated precipitation regimes and vice versa. The highest entropy reflects a white noise process that is completely random and unpredictable (Atieh et al ., 2017; Wang et al ., 2018). A disorder index (DI) can be used to evaluate the difference between a case of evenly distributed precipitation and the observed precipitation series (Mishra et al ., 2009; Atieh et al ., 2017).…”

Section: Introductionmentioning

confidence: 99%

Seasonal precipitation variability in mainland China based on entropy theory

Qin

Huang

et al. 2021

Intl Journal of Climatology

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Precipitation plays a fundamental role in terrestrial modelling and is extremely vulnerable to climate change. It is particularly challenging to describe precipitation due to its intermittency and fluctuation at nearly all temporal and spatial scales. Precipitation variability represents the degree of unevenness in its distribution or its lack of uniformity over different scales. This study examined the seasonal variability of meteorological station precipitation observations during 1961–2018 over mainland China using entropy theory. The intensity disorder index (IDI) and apportionment disorder index (ADI) were used to characterize the distribution unevenness, including the number of precipitation days, and precipitation amounts. Six special regions were selected according to their geographical location and climate conditions to show the regional differences of the disorder indices. At the daily scale, the regional mean IDI was 0.4081 for the eastern Tibetan Plateau and the regional mean ADI was 0.9984 for north China, which were the largest value among the six regions investigated. The regional mean IDI was 0.1128 and the regional mean ADI was 0.4071 both for the Yangtze River Basin, which were the smallest value among the six regions investigated. Temporal variations of the DIs were also detected. The IDI have decreased not significantly in most regions, except increasing by 0.0223/decade and 0.0129/decade in southwest China during nighttime and daytime, respectively. The ADI decreased by −0.0191, −0.0275, −0.0229, and −0.0203/decade and passed the significant test at .05 level for northwest, northeast, north China, and eastern Tibetan Plateau at the daily scale, respectively. The results quantify the precipitation unevenness over mainland China, which can be treated as a reference for water resources management and land surface model evaluation.

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“…The entropy theory presented by Shannon in the late 1940s [6] and the principle of maximum entropy presented by Jaynes in the late 1950s [7,8] have been applied in various research fields. Among them, there are many valuable hydrological applications of entropy theory (e.g., [9][10][11][12][13][14][15][16][17][18][19][20][21]). The aspects we want to address in this study include: (1) the detection of the spatial region and temporal year for high disorder features; (2) the identification of a monthly time series, which dominates the seasonal precipitation in Hexi corridor, and the identification of a seasonal time series, which dominates the annual precipitation in the corridor; (3) the correlations between drought-induced crop reduction and precipitation variability.…”

Section: Methodsmentioning

confidence: 99%

Entropy-Based Investigation on the Precipitation Variability over the Hexi Corridor in China

Cheng

Niu

Liao

2017

Entropy

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Abstract:The spatial and temporal variability of precipitation time series were investigated for the Hexi Corridor, in Northwest China, by analyzing the entropy information. The examinations were performed on monthly, seasonal, and annual timescales based on 29 meteorological stations for the period of 1961-2015. The apportionment entropy and intensity entropy were used to analyze the regional precipitation characteristics, including the intra-annual and decadal distribution of monthly and annual precipitation amounts, as well as the number of precipitation days within a year and a decade. The regions with high precipitation variability are found in the western part of the Hexi corridor and with less precipitation, and may have a high possibility of drought occurrence. The variability of the number of precipitation days decreased from the west to the east of the corridor. Higher variability, in terms of both of precipitation amount and intensity during crop-growing season, has been found in the recent decade. In addition, the correlation between entropy-based precipitation variability and the crop yield is also compared, and the crop yield in historical periods is found to be correlated with the precipitation intensity disorder index in the middle reaches of the Hexi corridor.

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Investigating the Spatial and Temporal Variability of Precipitation using Entropy Theory

Cited by 4 publications

References 58 publications

Shannon Entropy for Measuring Spatial Complexity Associated with Mean Annual Runoff of Tertiary Catchments of the Middle Vaal Basin in South Africa

Shannon Entropy for Measuring Spatial Complexity Associated with Mean Annual Runoff of Tertiary Catchments of the Middle Vaal Basin in South Africa

Seasonal precipitation variability in mainland China based on entropy theory

Entropy-Based Investigation on the Precipitation Variability over the Hexi Corridor in China

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