Rainfall trends in arid and semi-arid regions of Iran

Modarres, Reza; Silva, Vicente de Paulo Rodrigues da

doi:10.1016/j.jaridenv.2006.12.024

Cited by 413 publications

(200 citation statements)

References 23 publications

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“…For detecting trends and shifts in trends in hydrometeorological variables, various statistical methods have been developed and used over the years [45][46][47][48][49][50]. Of the two methods most commonly used, the parametric and nonparametric methods, the latter has been favored over the former [49].…”

Section: Discussionmentioning

confidence: 99%

“…Of the two methods most commonly used, the parametric and nonparametric methods, the latter has been favored over the former [49]. Among the nonparametric methods, the Mann-Kendall (MK) statistical test [51,52] has been frequently used to quantify the significance of trends in time series [1,23,[45][46][47][48][49][50][53][54][55][56][57][58][59][60]. It is also widely used in environmental science because it is simple, robust, and can cope with missing values and values below a detection limit.…”

Section: Discussionmentioning

confidence: 99%

“…An extension of the MK method, called the Sequential Mann-Kendall (SQMK) test, is widely used to detect the time (year) when a trend shows a shift (change in regime trend turning point) [1,20,47,49,56,58,60]. SQMK consists of sequential forward (u(t i )) and backward (u'(t i )) analyses of the MK test.…”

Section: Discussionmentioning

confidence: 99%

“…SQMK consists of sequential forward (u(t i )) and backward (u'(t i )) analyses of the MK test. If the two time series cross each other, the year of crossing indicates the year of trend change [47]. If, after crossing, the two series diverge from each other for a long period of time, the year when the divergence began indicates an abrupt trend change [58].…”

Section: Discussionmentioning

confidence: 99%

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Precipitation Trends over Slovakia in the Period 1981–2013

Zeleňáková

Vido

Portela

et al. 2017

Water

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Abstract:The objective of this paper was to analyze the temporal and spatial trends in annual and seasonal precipitation in Slovakia utilizing 487 gauging station data collected statewide in the period from 1981 to 2013. The nonparametric Mann-Kendall (MK) statistical test, which has been widely used to assess the significance of trends in hydrological time series, was applied to detect the significant trends. The Theil-Sen (TS) approach was applied to quantify the trend magnitude, and the Sequential Mann-Kendall (SQMK) test was used to detect abrupt temporal trend shifts. In general, precipitation data in the study area have not changed during the last 33 years, and there are no big gaps. However, predominantly increasing trends in precipitation time series were found at most of the gauging stations in Slovakia. The results corroborate previous climatic studies in the area of central Europe. In Slovakia, there is evidence of different rain distribution from the monthly point of view. Decreasing trends were detected in December in the northern part of Slovakia, while the central and southern parts revealed increasing trends. Most of the stations showed increasing summer precipitation trends, especially in July. It is expected that the findings of this comprehensive study of precipitation trends over Slovakia will produce more insights for the understanding of the regional hydrological behavior in Slovakia over the last several decades.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Precipitation Trends over Slovakia in the Period 1981–2013

Zeleňáková

Vido

Portela

et al. 2017

Water

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“…e MK test is a nonparametric rank-based statistical test used for detecting monotonic trends in time-series data. In comparison with other nonparametric procedures, such as Spearman's rho test [50], the power of the Mann-Kendal test is robust and similar to the extent of giving indistinguishable results in practice [51]. e MK statistic (S mk ) is calculated theoretically using the following equation:…”

Section: Seasonal Scale Analysismentioning

confidence: 99%

Evaluation of CMIP5 Global Climate Models over the Volta Basin: Precipitation

Agyekum

Annor

Lamptey

et al. 2018

Advances in Meteorology

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A selected number of global climate models (GCMs) from the fifth Coupled Model Intercomparison Project (CMIP5) were evaluated over the Volta Basin for precipitation. Biases in models were computed by taking the differences between the averages over the period of the models and the observation, normalized by the average of the observed for the annual and seasonal timescales. e Community Earth System Model, version 1-Biogeochemistry (CESM1-BGC), the Community Climate System Model Version 4 (CCSM4), the Max Planck Institute Earth System Model, Medium Range (MPI-ESM-MR), the Norwegian Earth System Model (NorESM1-M), and the multimodel ensemble mean were able to simulate the observed climatological mean of the annual total precipitation well (average biases of 1.9% to 7.5%) and hence were selected for the seasonal and monthly timescales. Overall, all the models (CESM1-BGC, CCSM4, MPI-ESM-MR, and NorESM1-M) scored relatively low for correlation (<0.5) but simulated the observed temporal variability differently ranging from 1.0 to 3.0 for the seasonal total. For the annual cycle of the monthly total, the CESM1-BGC, the MPI-ESM-MR, and the NorESM1-M were able to simulate the peak of the observed rainy season well in the Soudano-Sahel, the Sahel, and the entire basin, respectively, while all the models had difficulty in simulating the bimodal pattern of the Guinea Coast. e ensemble mean shows high performance compared to the individual models in various timescales.

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Impacts of recent climate change on trends in baseflow and stormflow in United States watersheds

Ficklin

Robeson

Knouft

2016

Geophysical Research Letters

102

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Characterizing the impacts of climatic change on hydrologic processes is critical for managing freshwater systems. Specifically, there is a need to evaluate how the two major components of streamflow, baseflow and stormflow, have responded to recent trends in climate. We derive baseflow and stormflow for 674 sites throughout the United States from 1980 to 2010 to examine their associations with precipitation, potential evapotranspiration, and maximum/minimum temperature. The northeastern (NE) and southwestern (SW) United States display consistent trends in baseflow and stormflow: increasing during fall and winter in the NE and decreasing during all seasons in the SW. Trends elsewhere and at other times of the year are more variable but still associated with changes in climate. Counter to expectations, baseflow and stormflow trends throughout the United States tend to change concurrently. These trends are primarily associated with precipitation trends, but increases in PET are influential and likely to become important in the future.

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Rainfall trends in arid and semi-arid regions of Iran

Cited by 413 publications

References 23 publications

Precipitation Trends over Slovakia in the Period 1981–2013

Precipitation Trends over Slovakia in the Period 1981–2013

Evaluation of CMIP5 Global Climate Models over the Volta Basin: Precipitation

Impacts of recent climate change on trends in baseflow and stormflow in United States watersheds

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