Analysis of long term meteorological trends in the middle and lower Indus Basin of Pakistan—A non-parametric statistical approach

Ahmad, Waqas; Fatima, Aamira; Awan, Usman Khalid; Anwar, Arif A.

doi:10.1016/j.gloplacha.2014.09.007

Cited by 53 publications

(32 citation statements)

References 24 publications

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“…Furthermore, an insignificant increasing trend for annual maximum temperature was found at other stations. An unexpected insignificant negative trend for annual average and maximum temperature was detected at Kakul, Lahore and Faisalabad; such an unexpected negative trend was explained by the massive rainfall from monsoons, specifically in the 1990's for Lahore and the nearby city of Faisalabad [16,18,43]. The results are verified by the region adjacent to Lahore in the Indian part of the Sutlej River basin, Himachal Pradesh, where Singh et al [44] found an insignificant negative trend for annual maximum temperature at Kasol and Sunni stations that explaineds the regional trend variation along the Pakistan-India boundary line.…”

Section: Resultsmentioning

confidence: 92%

“…The middle basin receives mean annual rainfall ranging from 300 to 800 mm, and annual mean air temperature ranges between 23 and 33 • C. The lower Indus River basin in Sindh province, including regions of Badin, Hyderabad, Nawabshah, Jacobabad, Khanpur and Karachi, is characterised by arid climate. The lower basin receives mean annual rainfall less than 200 mm, and annual mean temperature ranges between 17 and 28 • C [18]. The province of Balochistan, including regions of Sibi, Panjgur, Lasbela, Pasni, Quetta and Kalat, is characterised by an arid climate that receives the lowest rainfall and is prone to desertification [21].…”

Section: Profile Of the Study Areamentioning

confidence: 99%

“…However, Sadiq and Qureshi [16] found a maximum increment for annual mean temperature at Quetta (0.057 • C) and the lowest increment at Peshawar (0.019 • C), both greater than the global mean increment. Prolonged monsoon rains and especially rainfall during the 1990's caused a strange negative trend in maximum temperature at Lahore Ahmad, Fatima, Awan and Anwar [18]. Karachi is an urbanized and industrialized economic hub, and Sajjad, Hussain, Ahmed Khan, Raza, Zaman and Ahmed [15] found increasing mean maximum and mean annual temperature with extreme variability during 1976-2005 and no change in mean minimum temperature.…”

Section: Introductionmentioning

confidence: 99%

“…[17,18] observed obvious climatic changes and global warming with increasing trends in maximum and minimum temperature with no obvious precipitation trends in the upper middle and lower Indus River basin. Hussain et al [19] indicated an increasing trend in winter temperature for high and sub-mountains with warmer days and cooler nights in high mountains.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Contemporary Temperature Fluctuation in Urban Areas of Pakistan

Anjum

Tanoli

et al. 2017

Atmosphere

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Annual temperature data from thirty meteorological stations in Pakistan's major urban areas were selected to investigate trends in annual average and maximum temperature during . A combination of parametric and non-parametric tests including linear regression, the Mann-Kendall trend test and Sen's slope estimator was used for the analysis. Annual average and maximum temperature series showed an overall increasing trend for 90% of the stations and a decreasing trend for 10% of the stations in the study area. The highest significant increment of annual average temperature was observed at Gilgit, Hyderabad, Quetta and Lasbela stations at the rate of 0.49 • C per decade. The highest increment of annual maximum temperature was obtained at Chitral, Gilgit, Nawabshah and Quetta at the rate of 0.31 • C per decade. According to simple linear regression and the Mann-Kendall test, the annual average temperature showed a significant increasing trend for 43% of the stations (at a 0.001 level of significance) and 23% of the stations (at the 0.05 level). Annual maximum temperature showed a significant increasing trend for 26% of the stations (at the 0.001 level of significance) and 23% of the stations (at the 0.05 level). In general, the results showed increasing trends for the considered parameters, although annual average temperature showed a higher increasing rate than annual maximum temperature during the study period.

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Section: Resultsmentioning

confidence: 92%

Section: Profile Of the Study Areamentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Contemporary Temperature Fluctuation in Urban Areas of Pakistan

Anjum

Tanoli

et al. 2017

Atmosphere

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“…Different researchers [48,49] have used the non-parametric Mann-Kendall [50,51] and Sen's [52] slope estimator. Several researchers [53] prefer the use of the Mann-Kendall test because it provides the best alternative when the observed data is skewed either positively or negatively, or otherwise correlated cyclically or serially [54]. Therefore, to evaluate if there Remote Sens.…”

Section: Mann-kendall Test For Monotonic Trend In Temperaturementioning

confidence: 99%

Assessment of Irrigation Performance in Large River Basins under Data Scarce Environment—A Case of Kabul River Basin, Afghanistan

Akhtar

Awan²,

Tischbein

et al. 2018

Remote Sensing

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Abstract:The Kabul River basin (KRB) of Afghanistan, a lifeline of around 10 million people, has multiplicity of governance, management, and development-related challenges leading to inequity, inadequacy, and unreliability of irrigation water distribution. Prior to any uplifting intervention, there is a need to evaluate the performance of irrigation system on a long term basis to identify the existing bottlenecks. Although there are several indicators available for the performance evaluation of the irrigation schemes, we used the coefficient of variation (CV) of actual evapotranspiration (ET a ) in space (basin, sub-basin, and provincial level), relative evapotranspiration (RET), and temporal CV of RET, to assess the equity, adequacy, and reliability of water distribution, respectively, from 2003 to 2013. The ET a was estimated through a surface energy balance system (SEBS) algorithm and the ET a estimates were validated using the advection aridity (AA) method with a R 2 value of 0.81 and 0.77 at Nawabad and Sultanpur stations, respectively. The global land data assimilation system (GLDAS) and moderate-resolution imaging spectroradiometer (MODIS) products were used as main inputs to the SEBS. Results show that the mean seasonal sub-based RET values during summer (May-September) (0.37 ± 0.06) and winter (October-April) (0.40 ± 0.08) are below the target values (RET ≥ 0.75) during [2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013]. The CV of the mean ET a , within sub-basins and provinces for the entire study period, has an equitable distribution of water from October-January (0.09 ± 0.04), whereas the highest inequity (0.24 ± 0.08) in water distribution is during early summer. The range of the CV of the mean ET a (0.04-0.06) on a monthly and seasonal basis shows the unreliability of water supplies in several provinces or sub-basins. The analysis of the temporal CV of mean RET highlights the unreliable water supplies across the entire basin. The maximum ET a during the study period was estimated for the Shamal sub-basin (552 ± 43 mm) while among the provinces, Kunar experienced the highest ET a (544 ± 39 mm). This study highlights the dire need for interventions to improve the irrigation performance in time and space. The proposed methodology can be used as a framework for monitoring and implementing water distribution plans in future.

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Snowmelt and the hydrological interaction of forest-grassland ecosystems in Central Yakutia, eastern Siberia

et al. 2015

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Abstract:In the last two decades the major focus of study in forest water and carbon balances in eastern Siberia has been on the effect of rain during the growing season. Little attention has been paid to the contribution of snowmelt water. The results of the present study indicate that weather conditions during the snowmelt period as well as the soil moisture conditions carried from the previous year's growing season strongly determined the water availability for the forest ecosystem at the beginning of the next growing season. In the forest-grassland intermingled ecosystem of lowland Central Yakutia, gradual snowmelt water flow from the forest into the adjacent grassland depressions increased when soil moisture was high and air temperature was low, whereas low soil moisture and high air temperatures accelerated soil thawing and consequently snowmelt water infiltration into the forest soil. We found that snow depth did not determine the volume of snowmelt water moving to the grassland depression since the thermokarst lake water level in the adjacent grassland was about 25 cm lower in 2005 than in May 2006, even though maximum snow depth reached 57 cm and 43 cm in the winter of 2004-05 and 2005-06, respectively. The contribution of snowmelt water to forest growth as well as the flow of water from the forest to the grasslands showed a strong annual variability. We conclude that warmer springs and high variability in precipitation regimes as a result of climate change will result in more snowmelt water infiltration into the forest soil when the previous year's precipitation is low while more snowmelt water will flow into the thermokarst lake when the previous year's precipitation is high.

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Analysis of long term meteorological trends in the middle and lower Indus Basin of Pakistan—A non-parametric statistical approach

Cited by 53 publications

References 24 publications

Contemporary Temperature Fluctuation in Urban Areas of Pakistan

Contemporary Temperature Fluctuation in Urban Areas of Pakistan

Assessment of Irrigation Performance in Large River Basins under Data Scarce Environment—A Case of Kabul River Basin, Afghanistan

Snowmelt and the hydrological interaction of forest-grassland ecosystems in Central Yakutia, eastern Siberia

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