Assessment of Air Temperature Trends in the Source Region of Yellow River and Its Sub-Basins, China

Iqbal, Mujahid; Wen, Jun; Wang, Xin; Yong-chao, Lan; Tian, Hui; Anjum, Muhammad Naveed; Adnan, Muhammad

doi:10.1007/s13143-017-0064-x

Cited by 16 publications

(14 citation statements)

References 42 publications

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“…Double mass curves for all the stations revealed almost straight lines and no apparent breakpoints were found in the time series, which confirms that all deployed datasets are reliable. Such results are also confirmed by previous studies in the SRYR (Hu et al, 2012;Iqbal et al, 2018). Thiessen (1911) polygon method can get more accurate results than those obtained by the simple arithmetic average by the use of weighting factors when the areal distribution of station in the catchment is uneven.…”

Section: Methodssupporting

confidence: 87%

Variations of precipitation characteristics during the period 1960–2014 in the Source Region of the Yellow River, China

et al. 2018

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Precipitation, a natural feature of weather systems in the Earth, is vitally important for the environment of any region. Under global climate change condition, the characteristics of precipitation have changed as a consequence of enhanced global hydrological cycle. The source region of the Yellow River (SRYR), locating within the Qinghai-Tibet Plateau, is sensitive to the global climate change due to its complex orography and fragile ecosystem. To understand the precipitation characteristics and its impacts on the environment in the region, we studied the characteristics of rainy days and precipitation amount of different precipitation classes, such as light (0-5 and 5-10 mm), moderate (10-15, 15-20 and 20-25 mm) and heavy (≥25 mm) rains by analyzing the precipitation data of typical meteorological stations in the SRYR during the period 1961-2014, as well as the trends of persistent rainfall events and drought events. Results showed that annual average precipitation in this area had a non-significant (P>0.05) increasing trend, and 82.5% of the precipitation occurred from May to September. Rainy days of the 0-5 mm precipitation class significantly decreased, whereas the rainy days of 5-10, 10-15, and 20-25 mm precipitation classes increased and that of ≥25 mm precipitation class decreased insignificantly. The persistent rainfall events of 1-or 2-day and more than 2-day showed an increasing trend, with the 1-or 2-day events being more frequent. Meanwhile, the number of short drought periods (≤10 days) increased while long drought periods (>10 days) decreased. Since the 0-5 mm precipitation class had a huge impact on the grasslands productivity; the 5-10, 10-15, and 20-25 mm precipitation classes had positive effects on vegetation which rely on the deep soil water through moving nutrients and water into the root zone of these vegetation or through the plant-microbe interactions; the ≥25 mm precipitation class contributed to the floods; and more persistent rainfall events and fewer long drought events inferred positive effects on agriculture. Thus, these results indicate grassland degradation, less risk of floods, and the upgrading impact of climate change on agriculture. This study may provide scientific knowledge for policymakers to sustain the eco-environmental resources in the SYSR.

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Section: Methodssupporting

confidence: 87%

Variations of precipitation characteristics during the period 1960–2014 in the Source Region of the Yellow River, China

et al. 2018

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“…The annual average temperature increase over the past several years was mainly caused by the increase in the average annual minimum temperature [47]. Related studies have also confirmed that the climate in the SRYR is warming [26,47,48]. The temperature changes in the region over the past 19 years were consistent with those throughout China [49], and all regions showed increasing temperatures.…”

Section: Discussionsupporting

confidence: 54%

“…The temperature and precipitation decrease from the southeast to the northwest. The annual average rainfall is approximately 530 mm yr −1 [26]. From the southeast to the northwest, the annual average daily temperature varies between 2 • C and −4 • C [27].…”

Section: Study Areamentioning

confidence: 99%

Spatiotemporal Variation of NDVI in the Vegetation Growing Season in the Source Region of the Yellow River, China

Wang

et al. 2020

IJGI

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Research on vegetation variation is an important aspect of global warming studies. The quantification of the relationship between vegetation change and climate change has become a central topic and challenge in current global change studies. The source region of the Yellow River (SRYR) is an appropriate area to study global change because of its unique natural conditions and vulnerable terrestrial ecosystem. Therefore, we chose the SRYR for a case study to determine the driving forces behind vegetation variation under global warming. Using the Normalized Difference Vegetation Index (NDVI) and climate data, we investigated the NDVI variation in the growing season in the region from 1998 to 2016 and its response to climate change based on trend analysis, the Mann–Kendall trend test and partial correlation analysis. Finally, an NDVI–climate mathematical model was built to predict the NDVI trends from 2020 to 2038. The results indicated the following: (1) over the past 19 years, the NDVI showed an increasing trend, with a growth rate of 0.00204/a. There was an upward trend in NDVI over 71.40% of the region. (2) Both the precipitation and temperature in the growing season showed upward trends over the last 19 years. NDVI was positively correlated with precipitation and temperature. The areas with significant relationships with precipitation covered 31.01% of the region, while those with significant relationships with temperature covered 56.40%. The sensitivity of the NDVI to temperature was higher than that to precipitation. Over half (56.58%) of the areas were found to exhibit negative impacts of human activities on the NDVI. (3) According to the simulation, the NDVI will increase slightly over the next 19 years, with a linear tendency of 0.00096/a. From the perspective of spatiotemporal changes, we combined the past and future variations in vegetation, which could adequately reflect the long-term vegetation trends. The results provide a theoretical basis and reference for the sustainable development of the natural environment and a response to vegetation change under the background of climate change in the study area.

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“…For the accuracy of the recorded datasets, the prime concern was exploring the missing values and finding suitable replacements. Ergo, to verify the quality of the data [74], missing values were identified and then fixed by using Jupyter Notebook 6.0.3 of the Anaconda Navigator script. Its method was based on checking the monthly records and then taking the average values of the upper and lower years of similar months for a period [75].…”

Section: Resultsmentioning

confidence: 99%

Assessment of Climate Variability among Seasonal Trends Using In Situ Measurements: A Case Study of Punjab, Pakistan

et al. 2021

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This research assessed the changes in spatial patterns and the seasonal trends in temperature, precipitation, and relative humidity over 36 years (1979–2014) using Climate Forecast System Reanalysis (CFSR) datasets. The evaluation of climate deviations was the prime objective of this research. The augmented Dickey–Fuller Test (ADF) was used to scrutinize whether the data was either stationary or non-stationary. The results of the ADF test showed that all the datasets were found to be stationary at lag order 3. To observe undulations in the time series data, trend analyses were done using Sen’s slope (SS), Mann–Kendall (MK), and Cox and Stuart (CS) tests. For all the statistical analyses, we considered the 5% significance level (α = 0.05) and p < 0.05 to be statistically significant. We observed significant (p < 0.05) trends in spring (MAM) and autumn (SON) for minimum temperature (Tmin) in Punjab. We also noted a significant (p < 0.05) trend in precipitation during autumn (SON). Annually, all the variables showed a non-significant (p > 0.05) trend for Punjab, Pakistan, during the period 1979–2014. Climate variability, such as a decrease in precipitation, higher temperature, and relative humidity fluctuations, were the reasons for the imbalance in the sustainability of Punjab, Pakistan.

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Assessment of Air Temperature Trends in the Source Region of Yellow River and Its Sub-Basins, China

Cited by 16 publications

References 42 publications

Variations of precipitation characteristics during the period 1960–2014 in the Source Region of the Yellow River, China

Variations of precipitation characteristics during the period 1960–2014 in the Source Region of the Yellow River, China

Spatiotemporal Variation of NDVI in the Vegetation Growing Season in the Source Region of the Yellow River, China

Assessment of Climate Variability among Seasonal Trends Using In Situ Measurements: A Case Study of Punjab, Pakistan

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