Impact of Climate Change on Vegetation and Water Scarcity using Remote Sensing

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Biosphere/Hydrosphere/Land–Atmosphere Interactions".

Deadline for manuscript submissions: closed (19 July 2022) | Viewed by 14478

Special Issue Editors

School of Hydrology and Water Resources, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: drought; flood; water scarcity; hydrological modeling; evapotranspiration; hydro-meteorological disasters; climate change impact; climate extremes
Department of Management Sciences university of haripur, Haripur, Khyber Pakhtunkhwa 22620, Pakistan
Interests: drought; hazard risk assessment; precipitation extremes; climate change impact; weather and climate extremes.
School of Atmospheric Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: hydro-meteorological droughts; heatwaves; water resources; water scarcity; hydrological modeling; climate change impacts.
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Special Issue Information

Dear Colleagues,

Under the influence of changing climate, population growth, urbanization, land use changes and poor water management, water scarcity has become crucial worldwide especially in arid, semi-arid and subtropical regions. Future projections estimated that by the year 2025, every one in four individuals on Earth might be suffering from water scarcity. Moreover, extreme weather events such as heat waves, agricultural and hydrological droughts, and precipitation extremes affected global water demand, limiting rain-fed and irrigated vegetation potential. The impact of such water scarcity is amplified by inefficient irrigation practices, especially since irrigation consumes more than 70% of the available water in these regions. Besides, crop water stress can be detected by the in-situ measurements are generally expensive, time consuming, and not available over extended areas. In such circumstances, remote sensing provides an alternative and cost-effective method for mapping and monitoring broad areas and can be used to assess crop water stress and changes in vegetation cover through retrieving different biophysical crop variables from a multi-sensor.

Furthermore, extreme climatic events are predicted to increase both in the frequency and magnitude due to global warming, but their ecological effects are poorly understood particularly in forest ecosystems. Remote sensing data’s accessibility, diversity, quality, and computing capacity provide new opportunities to understand the impact of extreme climatic and disturbance events on vegetation. In the last several decades, long-term and synchronous remote sensing observations have allowed an improved understanding of ecosystems dynamics affected by extreme climatic and disturbance events globally. This will provide a better understanding of vegetation’s role in the Earth system and its resilience to environmental threats.

In this Special Issue, we are looking for original scientific contributions on assessment of water scarcity, identification of water stressed hotspots, decrease in vegetation cover, crop water stress, impact of agriculture drought, control of climate change impacts, remote sensing of climate extremes, statistical indices addressing drought recovery, and its spatiotemporal patterns using different Remote Sensing datasets, are highly encouraged.

Prof. Dr. Xieyao Ma
Prof. Dr. Xiefei Zhi
Prof. Dr. Kamran Azam
Dr. Irfan Ullah
Guest Editors

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Keywords

  • Water scarcity
  • Evapotranspiration
  • Agriculture drought
  • Crops and vegetation
  • Climate change impact
  • Deforestation
  • Climate extremes
  • Impacts and role of large-scale atmospheric circulation and climate indices on agriculture drought
  • Socioeconomic and public health

Published Papers (6 papers)

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Research

13 pages, 6835 KiB  
Article
Preliminary Application of a Multi-Physical Ensemble Transform Kalman Filter in Cloud and Precipitation Forecasts
by Qin Mei, Jia Wang, Xiefei Zhi, Hanbin Zhang, Ya Gao, Chuanxiang Yi and Yang Yang
Atmosphere 2022, 13(9), 1359; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13091359 - 25 Aug 2022
Viewed by 1583
Abstract
In this study, based on the retrieval data from the Fengyun geostationary meteorological satellite and the Tropical Rainfall Measuring Mission satellite, a large-scale precipitation case in eastern China is selected to address the systematic deviations of deterministic forecasts for clouds and precipitation. A [...] Read more.
In this study, based on the retrieval data from the Fengyun geostationary meteorological satellite and the Tropical Rainfall Measuring Mission satellite, a large-scale precipitation case in eastern China is selected to address the systematic deviations of deterministic forecasts for clouds and precipitation. A multi-physical ensemble transform Kalman filter (ETKF) is constructed in this research based on the Weather Research and Forecast model version 3.6, and its forecasting ability in terms of cloud-top height and temperature, hydrometeors, and precipitation is evaluated by quantitatively comparing three microphysical parameterization schemes (Lin, Morrison, and CAM5.1 schemes) and their corresponding multi-physical ensemble mean. The results show that the Lin, Morrison, and CAM5.1 schemes all underestimate the range of cloud systems and have different advantages and disadvantages in forecasting different elements, while the forecasting improvement of the multi-physical ensemble mean is limited. However, the multi-physical ETKF can effectively improve the forecast accuracy of the cloud system range. In addition, the multi-physical ETKF has the advantages of different physical parameterization schemes, which can dramatically improve the forecast accuracy of cloud hydrometeors, reduce precipitation forecast errors, and improve threat scores. Full article
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15 pages, 4723 KiB  
Article
Impact of Climate and Land-Use Change on Groundwater Resources, Study of Faisalabad District, Pakistan
by Meer Muhammad Sajjad, Juanle Wang, Haider Abbas, Irfan Ullah, Rehan Khan and Furman Ali
Atmosphere 2022, 13(7), 1097; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13071097 - 13 Jul 2022
Cited by 24 | Viewed by 2508
Abstract
Groundwater depletion has become a major concern all over the world. Recently, the rapid population growth and need for water and food have placed a massive strain on land and water resources. In this study, groundwater depletion resulting from land-use and climate change [...] Read more.
Groundwater depletion has become a major concern all over the world. Recently, the rapid population growth and need for water and food have placed a massive strain on land and water resources. In this study, groundwater depletion resulting from land-use and climate change was investigated in the Faisalabad district, Pakistan, from 2000 to 2015. A Pearson correlation analysis between climatic parameters and land-use indices with groundwater was conducted to explore the major influencing factors. Interpolation maps of groundwater were generated using the inverse distance weighting interpolation (IDW) method. The Normalized Difference Built-up Index (NDBI) of five-year intervals demonstrated a strong increasing trend, whereas the Normalized Difference Vegetation Index (NDVI) presented a declining trend. The results also indicated a significant declining trend in groundwater levels in the region, with the annual average groundwater level decreasing at a rate of approximately 0.11 m/year. Climatic parameters (i.e., precipitation and temperature) further reveal an insignificant increasing trend estimated using the Mann–Kendall test and Sens’s slope. Overall, spatial analysis results showed a statistically significant positive trend in the groundwater level of the Faisalabad district, where the NDBI ratio is high and the NDVI is low, owing to the extensive extraction of groundwater for domestic and industrial use. These findings may be useful for a better understanding of groundwater depletion in densely populated areas and could also aid in devising safety procedures for sustainable groundwater management. Full article
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16 pages, 3788 KiB  
Article
Future Climate Projections Using SDSM and LARS-WG Downscaling Methods for CMIP5 GCMs over the Transboundary Jhelum River Basin of the Himalayas Region
by Saira Munawar, Ghani Rahman, Muhammad Farhan Ul Moazzam, Muhammad Miandad, Kashif Ullah, Nadhir Al-Ansari and Nguyen Thi Thuy Linh
Atmosphere 2022, 13(6), 898; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13060898 - 01 Jun 2022
Cited by 16 | Viewed by 2498
Abstract
Climate change is one of the leading issues affecting river basins due to its direct impacts on the cryosphere and hydrosphere. General circulation models (GCMs) are widely applied tools to assess climate change but the coarse spatial resolution of GCMs limit their direct [...] Read more.
Climate change is one of the leading issues affecting river basins due to its direct impacts on the cryosphere and hydrosphere. General circulation models (GCMs) are widely applied tools to assess climate change but the coarse spatial resolution of GCMs limit their direct application for local studies. This study selected five CMIP5 GCMs (CCSM4, HadCM3, GFDL-CM3, MRI-CGCM3 and CanESM2) for performance evaluation ranked by Nash–Sutcliffe coefficient (NSE) and Kling–Gupta Efficiency (KGE). CCSM4 and HadCM3 large-scale predictors were favored based on ranks (0.71 and 0.68, respectively) for statistical downscaling techniques to downscale the climatic indicators Tmax, Tmin and precipitation. The performance of two downscaling techniques, Statistical Downscaling Methods (SDSM) and Long Ashton Research Station Weather Generator (LARS-WG), were examined using the Mean Absolute Error (MAE), Root Mean Square Error (RMSE), bias, NSE and KGE with weights (Wi) for the validation period. The results of statistical measures proved SDSM more efficient (0.67) in comparison to the LARS-WG (0.51) for the validation time for the Jhelum River basin. The findings revealed that the SDSM simulation for Tmax and Tmin are more comparable to the reference data for the validation period except simulation of extreme events by precipitation. The 21st century climatic projections exhibited a significant rise in Tmax (2.37–4.66 °C), Tmin (2.47–4.52 °C) and precipitation (7.4–11.54%) for RCP-4.5 and RCP-8.5, respectively. Overall, the results depicted that winter and pre-monsoon seasons were potentially most affected in terms of warming and precipitation, which has the potential to alter the cryosphere and runoff of the Jhelum River basin. Full article
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16 pages, 7898 KiB  
Article
Possible Relationships between the Interdecadal Anomalies of Heavy Rainfall under Northeastern China Cold Vortexes and the Sea Surface Temperature (SST)
by Dan Zhu, Xiefei Zhi, Zin Mie Mie Sein, Yan Ji, Xiao Tian and Mengting Pan
Atmosphere 2022, 13(2), 354; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13020354 - 19 Feb 2022
Cited by 4 | Viewed by 2032
Abstract
As an important component of the East Asian monsoon system, the northeast cold vortex (NECV) exerts a significant impact on weather and climate, especially in Northeast China. This study investigated the interdecadal spatiotemporal variability of heavy rainfall under the cold vortex of Northeast [...] Read more.
As an important component of the East Asian monsoon system, the northeast cold vortex (NECV) exerts a significant impact on weather and climate, especially in Northeast China. This study investigated the interdecadal spatiotemporal variability of heavy rainfall under the cold vortex of Northeast China (NECVHR) and its relationship with sea surface temperature (SST) during 1961–2019 over Northeast China. To investigate the dominant factors affecting variability in the heavy rainfall between May and September, an empirical orthogonal function (EOF) analysis was performed. To detect the trends and changes, a Mann-Kendall (MK) test was used. The sliding t-test was used to identify the change points and the significance. Pearson correlation analysis was used to analyze the relationship between SST and NECVHR, and the t-test was used to verify the significance. The results showed that the total amount of cold vortex heavy rainfall during May–September ranged from 153 to 12,509 mm for 1961–2019. An abrupt interdecadal change was seen after 2014 in Northeast China. The EOF analyses revealed that the first, second, and third EOFs explain 76%, 12.1%, and 5.5% of the total variance, respectively. The EOF followed the heavy rainfall pattern, with increases in the south (southeast) and decreases in the north (northwest) over Northeast China. Heavy rainfall over Northeast China positively correlated with the Atlantic multidecadal oscillation (AMO) index. The heavier rainfall under cold vortex (MCVHR) years revealed that the equipotential height was obviously located over the Sea of Japan, west of Northeast China and the Qinghai Tibet plateau. The cyclonic circulation over the East China Sea and north (northeasterly) wind prevails over Northeast China during less heavy rainfall under cold vortex (LCVHR) years. A high anticyclonic circulation over the Qinghai Tibet plateau resulted in stronger cold advection over Northeast China. The anticyclonic circulations over the East China Sea and the Sea of Japan (east), and the western (southwesterly) winds prevail over Northeast China, with a relatively shallow cold trough over the Qinghai Tibet plateau. The findings in this paper provided a better understanding of the interdecadal variability of NECVHR over Northeast China. The findings can be helpful for several stakeholders regarding agricultural production, water resource management, and natural habitat conversation in Northeast China. Full article
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25 pages, 6156 KiB  
Article
Spatiotemporal Rainfall Variability and Drought Assessment during Past Five Decades in South Korea Using SPI and SPEI
by Muhammad Farhan Ul Moazzam, Ghani Rahman, Saira Munawar, Nasir Farid and Byung Gul Lee
Atmosphere 2022, 13(2), 292; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos13020292 - 09 Feb 2022
Cited by 22 | Viewed by 2961
Abstract
About 41% of the earth is drought-affected, which has impacted nearly 2 billion people, and it is expected that more than 90% of terrestrial areas will be degraded by 2050. To evade and mitigate the harmful impacts of drought, it is necessary to [...] Read more.
About 41% of the earth is drought-affected, which has impacted nearly 2 billion people, and it is expected that more than 90% of terrestrial areas will be degraded by 2050. To evade and mitigate the harmful impacts of drought, it is necessary to study the rainfall variability and assess the drought trend at a global and regional level. This study utilized 70 meteorological stations in South Korea to evaluate the rainfall variability, drought, and its trend during the past five decades using the standardized precipitation evapotranspiration index (SPEI) and the standardized precipitation index (SPI). Rainfall data normality was assessed with mean, standard deviation, skewness, and kurtosis. The highest amount of rainfall was observed in the months of June, July, and August. The SPI and SPEI 12-month results revealed that 1982, 1988, 2008, 2015, and 2017 were dry years throughout the country, while from 2013 to 2017 mixed drought events were observed for the 6-month time series. The Mann-Kendall trend test was applied to the 1- and 12-month time series, and the results revealed that the months of January, March, April, May, June, and August had a significant negative trend, which means drought is increasing in these months, while the months of September, October, and December had a significant positive trend, which means wetter conditions prevailed in these months during the study period. It was observed in the 12-month time series that only two met stations had a significant negative trend, while only one had a significant positive trend. It was found that January and March were the driest months, and October was the wettest month. The detected drought events in this research are consistent with ENSO events. We have observed differences in drought characteristics (duration and frequency) for both indices. Climatic data revealed that South Korea has faced drought conditions (rainfall deficit) due to a shortened monsoon season. This study can provide guidance on water management strategies under the changing pattern of drought in South Korea. Full article
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14 pages, 7495 KiB  
Article
Distinct Evolution of Sea Surface Temperature over the Cold Tongue Region in South China Sea during Various El Niño Events
by Min Wu and Li Qi
Atmosphere 2021, 12(12), 1689; https://0-doi-org.brum.beds.ac.uk/10.3390/atmos12121689 - 16 Dec 2021
Viewed by 1992
Abstract
This study investigates the evolution of the sea surface temperature (SST) over the cold tongue (CT) region in the central South China Sea (SCS) during various El Niño events. A significant and distinct double-peak warming evolution can occur during EP El Niño and [...] Read more.
This study investigates the evolution of the sea surface temperature (SST) over the cold tongue (CT) region in the central South China Sea (SCS) during various El Niño events. A significant and distinct double-peak warming evolution can occur during EP El Niño and CP El Niño events, with the former being more remarkable and robust than the latter. Further analyses show that the weak and insignificant CT SST anomaly in CP El Niño events is influenced by some CP El Niño events in which the warm sea surface temperature anomaly (SSTA) is located west of 175° E (WCP El Niño). The response of CT SSTA mainly depends on the warm SSTA location of CP El Niño. The different corresponding mechanisms in winter, spring and summer are discussed respectively in this work. Further analysis reveals that the weak and insignificant SST anomaly over the CT region in CP El Niño events is caused by the faint SSTA response during the WCP El Niño events. The results of this study call attention to the response of the SCS climate in both atmosphere and ocean to the diversity of ENSO, especially the CP El Niño. Full article
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