An investigation of trends in precipitation volume for the last three decades in different regions of Fars province, Iran

Ahani, Hossein; Kherad, Mehrzad; Kousari, Mohammad Reza; Rezaeianzadeh, Mehdi; Karampour, Mohammad Amin; Ejraee, Faezeh; Kamali, Saeedeh

doi:10.1007/s00704-011-0572-z

Cited by 35 publications

(18 citation statements)

References 30 publications

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Section: Methodsmentioning

confidence: 99%

“…Spatial distribution analysis was completed by interpolating the extreme rainfall magnitudes throughout the state. Inverse distance weighting was used in ArcGIS 10.2 to create the mapped surfaces (Golian et al, 2010;Ahani et al, 2012). In addition to the analysis of annual maximum daily rainfall extreme events, daily amounts were summed to calculate monthly precipitation totals.…”

Section: Methodsmentioning

confidence: 99%

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Analysis of frequency and magnitude of extreme rainfall events with potential impacts on flooding: a case study from the central United States

Rahmani

Hutchinson

Harrington

et al. 2015

Intl Journal of Climatology

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Climate variability and change can impact rainfall by varying time, location, magnitude, and frequency of precipitation events. Fluctuations in heavy rainfall events can impact flooding and drought events and water management systems. This research addresses temporal and spatial distributions of extreme daily and monthly rainfall in Kansas using daily rainfall data from 23 stations for the period 1890–2013. The Mann–Kendall non‐parametric method was used in trend analysis. Results indicate an increasing trend in the annual daily maximum rainfall, and an increase in the annual number of rainfall events above the 90th, 95th, and 99th percentile thresholds at a majority of stations since 1890. The most recent 30‐year climate normal period (1981–2010) was selected to assess contemporary change compared to the entire period (1890–2013). Most stations have a steeper positive slope for all extreme rainfall parameters for 1981–2010. Generally, western Kansas receives smaller and fewer extreme storms than eastern Kansas with respect to both magnitude and frequency. Since 1890, June has been the month that receives the greatest amount of rain in each year at a majority of stations (18 of 23). Stations in eastern Kansas tend to experience earlier maximum rainfall on a monthly basis than central and western stations. Earlier annual maximum monthly rains can affect soil moisture and runoff generation. Timely maintenance and improvement in water, soil, and flood management systems are necessary in order to increase preparedness of the society to flash floods and protect them from water management systems failures.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Analysis of frequency and magnitude of extreme rainfall events with potential impacts on flooding: a case study from the central United States

Rahmani

Hutchinson

Harrington

et al. 2015

Intl Journal of Climatology

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“…2 The row dataset is shown in a and its dendogram from the hierarchical clustering is illustrated in b, where the dashed lines present different partitioning at different levels of similarity Stoch Environ Res Risk Assess clusters is completely independent from the type of data (Iván et al 2010). In addition, a proper intuitive feel of quality of clustering is provided by the absolute values by using this coefficient (Aggarwal 2015). For a given point i in a cluster A, the silhouette, s(i), is defined as follows:…”

Section: Silhouette Coefficientmentioning

confidence: 99%

“…In reviewing the recent literature, the most common methods to detect trends were the bootstrap analysis (Douglas et al 2000;Yue and Hashino 2003;Bonaccorso et al 2005;Cannarozzo et al 2006;Burn et al 2010), regression analysis (Cheung et al 2008;Tabari and Talaee 2011;Miao et al 2012); and the non-parametric methods (Becker et al 2006;Cannarozzo et al 2006;Modarres and da Silva 2007;Basistha et al 2009;de Lima et al 2010;Bari Abarghouei et al 2011;Ahani et al 2012;Tabari et al 2015a). It was found from the literature, that the nonparametric Mann-Kendall test is the most extensively applied method in the detection of trends (Hamed 2008).…”

Section: Introductionmentioning

confidence: 97%

Precipitation trend analysis using discrete wavelet transform at the Langat River Basin, Selangor, Malaysia

Palizdan

Falamarzi

Huang

et al. 2016

Stoch Environ Res Risk Assess

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The main purpose of this study was to determine the most dominant periodic components that affect the annual and seasonal precipitation trends in each homogenous rainfall region in the Langat River Basin, Malaysia for the period 1982-2011. Performing this research could be essential because in the previous studies on detection of trend in Malaysia, the details of variations of different time scales and the periodic responsible for the observed trends were not investigated. Using discrete wavelet transform (DWT) coupled with Mann-Kendall at the regional scale for the first time particularly in the context of Malaysia is the contribution of this study. In order to form the homogenous rainfall regions, first the total annual and seasonal precipitation in each year was spatialized into 5 km 9 5 km grids using the inverse distance weighting method. The obtained precipitation series for the grids were then grouped applying the Ward's clustering method based on the similarity of precipitation time series. After allocating a cluster number to each grid, the boundary of the regions was formed in ArcGIS software. Following which, in each homogenous region the areal precipitation series were computed by the Thiessen polygon method. The Mann-Kendall (MK) test was used to detect trend and the DWT coupled with the MK test and the sequential MK analysis were then utilized in order to find out the time scale which affected the observed trend in each homogenous region. On annual scale, it was found that D 1 (plus approximation) component in regions Annual Cluster1 (AC1) and AC2 was the periodic mode responsible for trends. On seasonal scale, in regions Northeast monsoon Cluster 1 (NC1), NC3, SC1 and Southwest monsoon Cluster 2 (SC2), D 1 (with approximation), in regions NC4, Inter monsoon 1 Cluster 1 (I1C1), I1C2, Inter monsoon 2 Cluster 1 I2C1 and I2C2, Detail 2 (D 2 ) (plus approximation) and in region NC2, Detail 3 (D 3 ) (with approximation added) component were the most influential periodicity for trends.

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“…Due to the sparsity of weather station networks across Iran, only a few studies were undertaken on regional variability analysis of precipitation over the country [3][4][5][6][7][8][9][10][11][12]. Dinpashoh et al [3] applied the principal component analysis (PCA) in association with cluster analysis (CA) to 12 chosen variables recorded by 77 stations in Iran, and classified the country into seven homogeneous rainfall sub-regions.…”

Section: Introductionmentioning

confidence: 99%

Modeling the Spatial and Temporal Variability of Precipitation in Northwest Iran

Amiri

Mesgari

2017

Atmosphere

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Spatial and temporal variability analysis of precipitation is an important task in water resources planning and management. This study aims to analyze the spatial and temporal variability of precipitation in the northeastern corner of Iran using data from 24 well-distributed weather stations between 1991 and 2015. The mean annual rainfall, precipitation concentration index (PCI), and their coefficients of variation were mapped to examine the spatial variability of rainfall. An artificial neural network (ANN) in association with the inverse distance weighted (IDW) method was proposed as a hybrid interpolation method to map the spatial distribution of the detected trends of mean annual rainfall and PCI over the study region. In addition, principal component analysis (PCA) was applied to annual precipitation time series in order to verify the results of the analysis using the mean annual rainfall and PCI data sets. Results show high variation in inter-annual precipitation in the west, and a moderate to high intra-annual variability over the whole region. Irregular year-to-year precipitation concentration is also observed in the northeastern and northwestern parts. All in all, the highest variations in inter-annual and intra-annual precipitation occurred over the western and northern parts, while the lowest variability was observed in the eastern part (i.e., the coastal region).

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An investigation of trends in precipitation volume for the last three decades in different regions of Fars province, Iran

Cited by 35 publications

References 30 publications

Analysis of frequency and magnitude of extreme rainfall events with potential impacts on flooding: a case study from the central United States

Analysis of frequency and magnitude of extreme rainfall events with potential impacts on flooding: a case study from the central United States

Precipitation trend analysis using discrete wavelet transform at the Langat River Basin, Selangor, Malaysia

Modeling the Spatial and Temporal Variability of Precipitation in Northwest Iran

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