scholarly journals Spatiotemporal Assessment of Temperature Data Products for the Detection of Warming Trends and Abrupt Transitions over the Largest Irrigated Area of Pakistan

2020 ◽  
Vol 2020 ◽  
pp. 1-19 ◽  
Author(s):  
Zain Nawaz ◽  
Xin Li ◽  
Yingying Chen ◽  
Xufeng Wang ◽  
Kun Zhang ◽  
...  
Keyword(s):  
Abrupt Change ◽  
Reference Data ◽  
Temperature Data ◽  
Trend Detection ◽  
Preliminary Evaluation ◽  
Change Analysis ◽  
Study Region ◽  
Data Products ◽  
Abrupt Change Analysis ◽  
Temperature Indices

Reliable and accurate temperature data acquisition is not only important for hydroclimate research but also crucial for the management of water resources and agriculture. Gridded data products (GDPs) offer an opportunity to estimate and monitor temperature indices at a range of spatiotemporal resolutions; however, their reliability must be quantified by spatiotemporal comparison against in situ records. Here, we present spatial and temporal assessments of temperature indices (Tmax, Tmin, Tmean, and DTR) products against the reference data during the period of 1979–2015 over Punjab Province, Pakistan. This region is considered as a center for agriculture and irrigated farming. Our study is the first spatiotemporal statistical evaluation of the performance and selection of potential GDPs over the study region and is based on statistical indicators, trend detection, and abrupt change analysis. Results revealed that the CRU temperature indices (Tmax, Tmin, Tmean, and DTR) outperformed the other GDPs as indicated by their higher CC and R2 but lower bias and RMSE. Furthermore, trend and abrupt change analysis indicated the superior performances of the CRU Tmin and Tmean products. However, the Tmax and DTR products were less accurate for detecting trends and abrupt transitions in temperature. The tested GDPs as well as the reference data series indicate significant warming during the period of 1997–2001 over the study region. Differences between GDPs revealed discrepancies of 1-2°C when compared with different products within the same category and with reference data. The accuracy of all GDPs was particularly poor in the northern Punjab, where underestimates were greatest. This preliminary evaluation of the different GDPs will be useful for assessing inconsistencies and the capabilities of the products prior to their reliable utilization in hydrological and meteorological applications particularly over arid and semiarid regions.

scholarly journals Effects of Climate and Land Use changes on Vegetation Dynamics in the Yangtze River Delta, China Based on Abrupt Change Analysis

2020 ◽  
Vol 12 (5) ◽  
pp. 1955
Author(s):  
Lei Wan ◽  
Huiyu Liu ◽  
Haibo Gong ◽  
Yujia Ren
Keyword(s):  
Land Use ◽  
Vegetation Dynamics ◽  
Abrupt Change ◽  
Land Use Changes ◽  
Yangtze River Delta ◽  
Change Analysis ◽  
Land Use Types ◽  
Natural Land ◽  
Abrupt Change Analysis ◽  
Relationship Of

Vegetation dynamics is thought to be affected by climate and land use changes. However, how the effects vary after abrupt vegetation changes remains unclear. Based on the Mann-Kendall trend and abrupt change analysis, we monitored vegetation dynamics and its abrupt change in the Yangtze River delta during 1982–2016. With the correlation analysis, we revealed the relationship of vegetation dynamics with climate changes (temperature and precipitation) pixel-by-pixel and then with land use changes analysis we studied the effects of land use changes (unchanged or changed land use) on their relationship. Results showed that: (1) the Normalized Vegetation Index (NDVI) during growing season that is represented as GSN (growing season NDVI) showed an overall increasing trend and had an abrupt change in 2000. After then, the area percentages with decreasing GSN trend increased in cropland and built-up land, mainly located in the eastern, while those with increasing GSN trend increased in woodland and grassland, mainly located in the southern. Changed land use, except the land conversions from/to built-up land, is more favor for vegetation greening than unchanged land use (2) after abrupt change, the significant positive correlation between precipitation and GSN increased in all unchanged land use types, especially for woodland and grassland (natural land use) and changed land use except built-up land conversion. Meanwhile, the insignificant positive correlation between temperature and GSN increased in woodland, while decreased in the cropland and built-up land in the northwest (3) after abrupt change, precipitation became more important and favor, especially for natural land use. However, temperature became less important and favor for all land use types, especially for built-up land. This research indicates that abrupt change analysis will help to effectively monitor vegetation trend and to accurately assess the relationship of vegetation dynamics with climate and land use changes.

Trend and abrupt change analysis in water quality of Urmia Lake in comparison with changes in lake water level

2020 ◽  
Vol 192 (10) ◽  
Author(s):  
Mohammad Taghi Sattari ◽  
Rasoul Mirabbasi ◽  
Salar Jarhan ◽  
Fatemeh Shaker Sureh ◽  
Sajjad Ahmad
Keyword(s):  
Water Quality ◽  
Water Level ◽  
Lake Water ◽  
Abrupt Change ◽  
Urmia Lake ◽  
Change Analysis ◽  
Lake Water Level ◽  
Abrupt Change Analysis

scholarly journals Spatiotemporal trend and abrupt change analysis of temperature in Iran

2017 ◽  
Vol 25 (2) ◽  
pp. 314-321 ◽  
Author(s):  
Farshad Ahmadi ◽  
Mohammad Nazeri Tahroudi ◽  
Rasoul Mirabbasi ◽  
Keivan Khalili ◽  
Deepak Jhajharia
Keyword(s):  
Abrupt Change ◽  
Change Analysis ◽  
Abrupt Change Analysis

scholarly journals Spatiotemporal Variation and Abrupt Change Analysis of Temperature from 1960 to 2012 in the Huang-Huai-Hai Plain, China

2015 ◽  
Vol 2015 ◽  
pp. 1-11 ◽  
Author(s):  
Yanyu Yin ◽  
Hui Liu ◽  
Xiangsheng Yi ◽  
Weidong Liu
Keyword(s):  
Climate Warming ◽  
Abrupt Change ◽  
Hydrological Cycle ◽  
Spline Interpolation ◽  
Regional Climate ◽  
Kendall Test ◽  
Spatiotemporal Variation ◽  
Seasonal Temperature ◽  
Change Analysis ◽  
Abrupt Change Analysis

Based on a monthly dataset of temperature time series (1960–2012) in the Huang-Huai-Hai Plain of China (HHHPC), spatiotemporal variation and abrupt change analysis of temperature were examined by moving average, linear regression, spline interpolation, Mann-Kendall test, and movingt-test. Major conclusions were listed as follows. (1) Annual and seasonal temperature increased with different rates on the process of fluctuating changes during 1960~2012. The upward trend was 0.22°C 10a−1for annual temperature, while it was very significant in winter (0.34°C 10a−1) and spring (0.31°C 10a−1), moderately significant in autumn (0.21°C 10a−1), and nonsignificant in summer (0.05°C 10a−1). (2) The spatial changes of annual and seasonal temperature were similar. The temperature increased significantly in Beijing and its adjacent regions, while it was nonsignificant in the central and southern regions. (3) The spring, autumn, winter, and annual temperature had warm abrupt change. The abrupt change time for winter temperature was in the late 1970s, while it was in the late 1980s and early 1990s for spring, autumn, and annual temperature. (4) Macroscopic effects of global and regional climate warming and human activities were probably responsible for the temperature changes. The climate warming would influence the hydrological cycle and agricultural crops in the study area.

scholarly journals Spatiotemporal dynamics of glacial lakes (1990–2018) in the Kashmir Himalayas, India using Remote Sensing and GIS

2021 ◽  
Vol 1 (1) ◽  
Author(s):  
Rayees Ahmed ◽  
Gowhar Farooq Wani ◽  
Syed Towseef Ahmad ◽  
Riyaz Ahmad Mir ◽  
Mansour Almazroui ◽  
...  
Keyword(s):  
Growth Rate ◽  
Field Studies ◽  
Rapid Expansion ◽  
Spatial Extent ◽  
Glacial Lakes ◽  
Landsat Images ◽  
Change Analysis ◽  
Study Region ◽  
Kashmir Himalayas ◽  
Maximum Temperatures

AbstractThis study is perhaps the first attempt to use satellite data (1990–2018) to analyze spatiotemporal changes in glacial lakes over the Kashmir Himalayas supplemented by field studies. Landsat images were used to delineate the spatial extent of glacial lakes at four-time points, i.e., 1990, 2000, 2010 and 2018. The total count of lakes as well as their spatial extent showed a discernible increase. The number increased from 253 in 1990 to 324 in 2018, with a growth rate of 21.4%. The area has increased from 18.84 ± 0.1 km2 in 1990 to 22.13 ± 0.12 km2 in 2018 with a growth rate of 14.7%. The newly formed glacial lakes, including supraglacial lakes, were greater in number than the lakes that disappeared over the study period. All glacial lakes are situated at elevations of 2700 m asl and 4500 m asl. More than 78% of lake expansion in the study region is largely due to the growth of existing glacial lakes. Through area change analysis, our findings reveal that certain lakes show rapid expansion needing immediate monitoring and observation. The analysis of the meteorological variables reveals that minimum and maximum temperatures in the Jhelum basin have shown an increasing trend. Tmax showed an increase of 1.25 °C, whereas Tmin increased to 0.7 °C from 1980 to 2020. On the other hand, precipitation has shown a decreasing trend, which can be attributed to one of the major causes of glacier recession and the expansion of glacial lakes in the Upper Jhelum basin. Consequently, this study could play a significant role in devising a comprehensive risk assessment plan for potential Glacial Lake Outburst Floods (GLOFs) and developing a mechanism for continuous monitoring and management of lakes in the study region.

scholarly journals Spatial variability of mean daily estimates of actual evaporation from remotely sensed imagery and surface reference data

2019 ◽  
Vol 23 (12) ◽  
pp. 4891-4907 ◽  
Author(s):  
Robert N. Armstrong ◽  
John W. Pomeroy ◽  
Lawrence W. Martz
Keyword(s):  
Remote Sensing ◽  
Spatial Variability ◽  
Land Surface ◽  
Management Practices ◽  
Reference Data ◽  
Meteorological Data ◽  
Net Radiation ◽  
Study Region ◽  
Evaporation Model ◽  
Actual Evaporation

Abstract. Land surface evaporation has considerable spatial variability that is not captured by point-scale estimates calculated from meteorological data alone. Knowing how evaporation varies spatially remains an important issue for improving parameterisations of land surface schemes and hydrological models and various land management practices. Satellite-based and aerial remote sensing has been crucial for capturing moderate- to larger-scale surface variables to indirectly estimate evaporative fluxes. However, more recent advances for field research via unmanned aerial vehicles (UAVs) now allow for the acquisition of more highly detailed surface data. Integrating models that can estimate “actual” evaporation from higher-resolution imagery and surface reference data would be valuable to better examine potential impacts of local variations in evaporation on upscaled estimates. This study introduces a novel approach for computing a normalised ratiometric index from surface variables that can be used to obtain more-realistic distributed estimates of actual evaporation. For demonstration purposes the Granger–Gray evaporation model (Granger and Gray, 1989) was applied at a rolling prairie agricultural site in central Saskatchewan, Canada. Visible and thermal images and meteorological reference data required to parameterise the model were obtained at midday. Ratiometric indexes were computed for the key surface variables albedo and net radiation at midday. This allowed point observations of albedo and mean daily net radiation to be scaled across high-resolution images over a large study region. Albedo and net radiation estimates were within 5 %–10 % of measured values. A daily evaporation estimate for a grassed surface was 0.5 mm (23 %) larger than eddy covariance measurements. Spatial variations in key factors driving evaporation and their impacts on upscaled evaporation estimates are also discussed. The methods applied have two key advantages for estimating evaporation over previous remote-sensing approaches: (1) detailed daily estimates of actual evaporation can be directly obtained using a physically based evaporation model, and (2) analysis of more-detailed and more-reliable evaporation estimates may lead to improved methods for upscaling evaporative fluxes to larger areas.

scholarly journals Rainfall Trends over the Past Century for Tropical Climatic Region in Western India

10.29007/szsv ◽  
2018 ◽  
Author(s):  
Priyank Sharma ◽  
Prem Lal Patel
Keyword(s):  
Rainfall Intensity ◽  
Trend Detection ◽  
Annual Rainfall ◽  
Past Century ◽  
Western India ◽  
Study Region ◽  
Maximum Rainfall ◽  
Increasing Trend ◽  
Lower Tapi Basin ◽  
Tapi Basin

Present study examines the applications of different trend detection methodologies for investigation of trend in long-term rainfall over Lower Tapi basin, India using daily gridded rainfall data for the period 1901 – 2013 at 0.25  0.25 resolution. The trends in rainfall indices, viz. total annual rainfall (TAR), annual maximum rainfall (AMR) and average annual rainfall intensity (AAI) have been detected using non-parametric and graphical methods. The results show increasing trends in TAR across all the 9 grids in the study region, with significant increasing trend over Grids-8 and 9. Further, AMR exhibited increasing trend over 7 out of 9 grids, with significant increasing trend over Grid-8 (ZMMK = 2.478;  = 0.356 mm/year) and Grid-9 (ZMMK = 2.278;  = 0.257 mm/year). The Innovative Trend Analysis plots reveal overall increasing trend in AMR across all the grids. The AAI exhibited significant increasing trend over 5 grids including Grids-8 and 9. The Grids 8 and 9 encompass the urban areas of the Surat city, located in the Lower Tapi basin. The urbanization in the Surat city and proximity to the Arabian Sea areas may be the possible reasons for significant increase in the extreme rainfall and rainfall intensity over Grids-8 and 9.

scholarly journals Spatio-temporal dynamics of glacial lakes (1990-2018) in the Kashmir Himalayas, India using remote sensing and GIS

2021 ◽  
Author(s):  
Rayees Ahmed ◽  
Gowhar Farooq Wani ◽  
Syed Towseef Ahmad ◽  
Riyaz Ahmad Mir ◽  
Mansour Almazroui ◽  
...  
Keyword(s):  
Growth Rate ◽  
Temporal Dynamics ◽  
Field Studies ◽  
Rapid Expansion ◽  
Spatial Extent ◽  
Glacial Lakes ◽  
Landsat Images ◽  
Change Analysis ◽  
Study Region ◽  
Kashmir Himalayas

Abstract This study is perhaps the first attempt to use satellite data (1990–2018) to analyze spatiotemporal changes in glacial lakes over the Kashmir Himalayas supplemented by field studies. Landsat images were used to delineate the spatial extent of glacial lakes at four time points, i.e., 1990, 2000, 2010 and 2018. The total count of lakes as well as their spatial extent showed a discernible increase. The number increased from 253 in 1990 to 322 in 2018, with a growth rate of 21.4%. The area has increased from 18.84 Km2 in 1990 to 22.11 Km2 in 2018 with a growth rate of 14.7 percent. The newly formed glacial lakes, including supra glacial lakes, were greater in number than the lakes that disappeared over the study period. All glacial lakes are situated at elevations of 2700 m asl and 4500 m asl. More than 78% of lake expansion in the study region is largely due to the growth of existing glacial lakes. Through area change analysis, our findings reveal that certain lakes show rapid expansion needing immediate monitoring and observation. The analysis of the meteorological variables reveals that minimum and maximum temperatures in the Jhelum basin have shown an increasing trend. Tmax showed an increase of 1.1°C, whereas Tmin increased to 0.7°C from 1990 to 2018. On the other hand, precipitation has shown a decreasing trend, which can be attributed to one of the major causes of glacier recession and the expansion of glacial lakes in the Upper Jhelum basin. Consequently, this study could play a significant role in devising a comprehensive risk assessment plan for potential GLOFs and developing a mechanism for continuous monitoring and management of lakes in the study region.

Sign in / Sign up

Export Citation Format

Share Document