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Exploring the Variations and Interplay of Drought and Heatwaves: Uncovering the Associated Mechanisms and Impacts

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Ecological Remote Sensing".

Deadline for manuscript submissions: closed (31 July 2024) | Viewed by 16975

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Dr. Jinping Liu

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1. College of Surveying and Geo-Informatics, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
2. Hydraulics and Geotechnics Section, KU Leuven, Kasteelpark Arenberg 40, BE-3001 Leuven, Belgium
Interests: extreme climatic events; climate change and human health impacts; hydrology modeling; water resources; vegetation remote sensing
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Prof. Dr. Zengyun Hu

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Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Interests: climate change; extreme climate; climate model; arid and semiarid climate; geography; water resource; nonlinear time series analysis; impact of the climate change on human health
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Dr. Hongquan Sun

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Flood and Drought Hazards Research Center, National Institute of Natural Hazards, Ministry of Emergency Management of China, Beijing 100085, China
Interests: drought and flood disasters projection and forecast; risk assessment; monitoring and early warning based on statistical methods; physical models; remote sensing technology
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Dr. Hui Tao

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Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
Interests: detection of extreme climate events; impact of anthropogenic climate change and human activities on water resources; hydroclimatic change and risk assessment
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Dr. Arfan Arshad

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Guest Editor

Department of Biosystems and Agricultural Engineering, Oklahoma State University, Stillwater, OK 74075, USA
Interests: Transboundary water governance; food security; remote sensing; climate change; earth system predictability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Increasing surface temperatures associated with global climate change are projected to cause heatwaves and droughts to become more frequent and extreme in many parts of the world. Moreover, there exists a potential interplay between drought and heatwave events, which means that drought can exacerbate the severity of heatwave events, and vice versa. These extreme events have had a significant impact on the environmental ecosystem and socioeconomic activities, which is expected to worsen in the future, especially with the compounded effects of drought and heatwave (CDHW) episodes. Although some effort has been made to investigate the temporal and spatial variations of drought and heatwaves, the knowledge regarding their interplay and associated mechanisms is still limited. Therefore, this Special Issue focuses on exploring the variations and interplay of drought and heatwaves and uncovering the associated mechanisms and impacts. In this regard, review, application, or methodological contributions to this Special Issue may include, but are not limited to:

Identification and variation analysis of regional drought and heatwave events;
The interplay between climate variability and drought and heatwaves;
Exploring the implication or impacts of drought and heatwaves;
Projecting the variations of drought and heatwaves in different climate scenarios;
Compound drought and heatwave (CDHW) events;
Uncovering the interactions between drought and heatwaves at different scales;
Remote sensing and early warning systems for drought and heatwaves;
Clarifying the mechanisms behind drought and heatwaves;
Adaptation strategies for drought and heatwaves.

Dr. Jinping Liu
Prof. Dr. Zengyun Hu
Dr. Hongquan Sun
Dr. Hui Tao
Dr. Arfan Arshad
Guest Editors

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Keywords

heatwave and drought
spatio-temporal variations
mechanisms
potential impacts
compound events
interplay
projection
adaptation strategies

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Related Special Issue

Exploring the Variations and Interplay of Drought and Heatwaves: Uncovering the Associated Mechanisms and Impacts (2nd Edition) in Remote Sensing (1 article)

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Research

19 pages, 7145 KiB

Open AccessArticle

Impact of Long-Term Drought on Surface Water and Water Balance Variations in Iran: Insights from Highland and Lowland Regions

by Mohammad Kazemi Garajeh, Nastaran Abdoli, Ebrahim Seyedebrahimi, Amin Naboureh, Iman Kurdpour, Amir Reza Bakhshi Lomer, Amin Sadeqi and Saham Mirzaei

Remote Sens. 2024, 16(19), 3636; https://doi.org/10.3390/rs16193636 - 29 Sep 2024

Cited by 1 | Viewed by 1350

Abstract

Droughts have a significant impact on surface water resources, especially in arid and semi-arid regions. Computational and data handling limitations have constrained previous time-series analyses. However, advances in cloud computing services and remote sensing technology allow for a more detailed examination. This study integrates multi-source satellite-derived data with a cloud computing platform to assess the impact of long-term drought on surface water and water balance in Iran from 2000 to 2021. Given the varying effects of drought on highlands and lowlands, the analysis was conducted at three levels: the entire country, the highlands, and the lowlands. The results of this study reveal imbalances between water balance from 2000 to 2021, with notable disparities observed during 2000–2007, 2009–2014, and 2016–2019. The results also show varying drought trends (e.g., −1.22 in 2000 and −0.73 in 2021), with severe conditions captured in 2008 (SPI: −1.92). Additionally, our analysis illustrated that lowlands were more impacted by droughts compared to highlands. Long-term drought and permanent surface water had correlation values of 0.33 across the country, 0.33 in the highlands, and 0.31 in the lowlands. For seasonal surface water, coefficients were 0.18 for the entire country, 0.16 for the highlands, and 0.18 for the lowlands. Overall, long-term drought had minimal effect on reducing surface water. These findings show that drought is only part of the explanation for the decrease in surface water resources. Full article

(This article belongs to the Special Issue Exploring the Variations and Interplay of Drought and Heatwaves: Uncovering the Associated Mechanisms and Impacts)

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26 pages, 12204 KiB

Open AccessArticle

The Impact of Meteorological Drought at Different Time Scales from 1986 to 2020 on Vegetation Changes in the Shendong Mining Area

by Zhichao Chen, He Qin, Xufei Zhang, Huazhu Xue, Shidong Wang and Hebing Zhang

Remote Sens. 2024, 16(15), 2843; https://doi.org/10.3390/rs16152843 - 2 Aug 2024

Viewed by 1073

Abstract

The Shendong Mining Area, being the largest coal base in the world, has significant challenges in the intensive development and utilization of coal resources, as well as the impact of a dry climate, which can have serious negative effects on the growth of flora in the region. Investigating the spatial and temporal patterns of how meteorological drought affects vegetation in the Shendong Mining Area at various time scales can offer a scientific foundation for promoting sustainable development and ecological restoration in the region. This study utilizes the Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI) data from 1986 to 2020 in the Shendong Mining Area. It employs Slope trend analysis, a Mann–Kendall test, a Geographic Detector, and other methods to examine the spatiotemporal distribution characteristics of meteorological drought at various time scales. Additionally, the study investigates the influence of these drought patterns on vegetation growth in the Shendong Mining Area. Across the mining area, there was a general decrease in the monthly average SPEI on an annual basis. However, on a seasonal, semi-annual, and annual basis, there was a gradual increase in the annual average SPEI, with a higher rate of increase in the southern region compared to the northern region. When considering the spatial variation trend in different seasons, both positive and negative trends were observed in winter and summer. The negative trend was mainly observed in the western part of the mining area, while the positive trend was observed in the eastern part. In spring, the mining area generally experienced drought, while in autumn, it generally experienced more precipitation. The mining area exhibits a prevailing distribution of vegetation, with a greater extent in the southeast and a lesser extent in the northwest. The vegetation coverage near the mine is insufficient, resulting in a low NDVI value, which makes the area prone to drought. Over the past few years, the mining area has experienced a significant increase in vegetation coverage, indicating successful ecological restoration efforts. Various forms of land use exhibit distinct responses to drought, with forests displaying the most positive correlation and barren land displaying the strongest negative correlation. Various types of landforms exhibit varying responses to drought. Loess ridge and hill landforms demonstrate the most pronounced positive association with monthly-scale SPEI values, whereas alluvial and floodplain landforms display the poorest positive correlation with yearly scale SPEI values. The general findings of this research can be summarized as follows: (1) The mining area exhibits a general pattern of increased humidity, with the pace of humidity increase having intensified in recent times. Seasonal variations exhibit consistent cyclic patterns. (2) There are distinct regional disparities in NDVI values, with a notable peak in the southeast and a decline in the northwest. The majority of the mining area exhibits a positive trend in vegetation recovery. (3) Regional meteorological drought is a significant element that influences changes in vegetation coverage in the Shendong Mining Area. Nevertheless, it displays complexity and is more obviously impacted by other factors at a small scale. (4) It should be noted that forests and barren land exert a more significant influence on SPEI values, despite their relatively lesser spatial coverage. The predominant land use type in most locations is grasslands; however, they have a relatively minor influence on SPEI. (5) A shorter time period, higher elevation, and steeper slope gradient all contribute to a larger correlation with drought. Full article

(This article belongs to the Special Issue Exploring the Variations and Interplay of Drought and Heatwaves: Uncovering the Associated Mechanisms and Impacts)

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25 pages, 24658 KiB

Open AccessArticle

Propagation of Meteorological Drought to Agricultural and Hydrological Droughts in the Tropical Lancang–Mekong River Basin

by Ganlin Feng, Yaoliang Chen, Lamin R. Mansaray, Hongfeng Xu, Aoni Shi and Yanling Chen

Remote Sens. 2023, 15(24), 5678; https://doi.org/10.3390/rs15245678 - 9 Dec 2023

Cited by 11 | Viewed by 3201

Abstract

In the past several decades, drought events have occurred frequently around the world. However, research on the propagation of drought events has not been adequately explored. This study investigated the drought propagation process from meteorological drought to agricultural drought (PMAD) and from meteorological drought to hydrological drought (PMHD) using a 72-year reanalysis dataset in the tropical Lancang–Mekong River Basin. Firstly, we used a new method—Standardized Drought Analysis Toolbox—to construct drought indices. Then, a linear method (Pearson correlation analysis) and a nonlinear method (mutual information) were used to investigate the drought propagation process. Cross-wavelet analysis and wavelet coherence analysis were employed to explore the statistical relationship among the three drought types. Finally, the random forest method was applied to quantify the major factors in drought response time (DRT). The results revealed the following: (1) both linear and nonlinear methods exhibited strong temporal and spatial consistency for both PMAD and PMHD, with linear relationships being stronger than nonlinear ones. (2) The DRTs of PMAD and PMHD were around 1–2 months and 3–5 months, respectively. Significant differences existed in the DRT between the dry season and the rainy season. (3) A divergent spatial pattern of the proportion of DRT was observed between PMAD and PMHD. (4) Significant statistical correlations between meteorological drought and agricultural drought and between meteorological drought and hydrological drought were observed in specific periods for each sub-region; (5) Hydrometeorological factors contributed the most to DRT, followed by terrain factors and the land cover types. The findings of this study deepened our understanding of the spatial–temporal relationship of multiple drought propagation types in this transboundary river basin. Full article

(This article belongs to the Special Issue Exploring the Variations and Interplay of Drought and Heatwaves: Uncovering the Associated Mechanisms and Impacts)

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21 pages, 9371 KiB

Open AccessArticle

Actual Evapotranspiration Dominates Drought in Central Asia

by Zhuoyi Zhao, Xingming Hao, Xue Fan, Jingjing Zhang, Sen Zhang and Xuewei Li

Remote Sens. 2023, 15(18), 4557; https://doi.org/10.3390/rs15184557 - 16 Sep 2023

Cited by 12 | Viewed by 2342

Abstract

Central Asia is a drought-prone region that is sensitive to global climate change. The increased actual evapotranspiration intensifies the drought impacts in this area. However, little is known about the similarities and differences between various types of drought in Central Asia, as well as the relative importance of water income and consumption processes during drought events. Therefore, this study evaluates the trends and characteristics of meteorological, agricultural, and hydrological droughts in Central Asia using precipitation, soil moisture, and terrestrial water storage as indicators; explores the temporal correlation of and spatial similarity between various types of drought; and quantitatively assesses the contribution of water balance variables to drought intensity. The results indicate that drought has intensified in Central Asia, and the trends of precipitation, soil moisture, and terrestrial water storage in this region were −0.75 mm·yr⁻¹ (p = 0.36), −0.0003 m³·m⁻³ yr⁻¹ (p < 0.01), and −0.3742 cm·yr⁻¹ (p < 0.001), respectively. Severe droughts are typically short in duration and high in intensity. Three various types of drought have low temporal correlation and spatial similarity. Furthermore, agricultural and hydrological droughts were primarily driven by actual evapotranspiration, accounting for relative contributions of 64.38% and 51.04% to these drought types, respectively. Moreover, the extent of increased actual evapotranspiration expanded to cover 49.88% of the region, exacerbating agricultural and hydrological droughts in 23.88% and 35.14% of the total study area, respectively. The study findings demonstrate that actual evapotranspiration plays a critical role in causing droughts. This study establishes a theoretical foundation to carry out drought assessment, the construction of multivariate drought indices, and water resource management in Central Asia. Full article

(This article belongs to the Special Issue Exploring the Variations and Interplay of Drought and Heatwaves: Uncovering the Associated Mechanisms and Impacts)

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34 pages, 10148 KiB

Open AccessArticle

Research on Soil Moisture Inversion Method for Canal Slope of the Middle Route Project of the South to North Water Transfer Based on GNSS-R and Deep Learning

by Qingfeng Hu, Yifan Li, Wenkai Liu, Weiqiang Lu, Hongxin Hai, Peipei He, Xianlin Liu, Kaifeng Ma, Dantong Zhu, Peng Wang and Yingchao Kou

Remote Sens. 2023, 15(17), 4340; https://doi.org/10.3390/rs15174340 - 3 Sep 2023

Cited by 2 | Viewed by 2007

Abstract

The soil moisture from the South-to-North Water Diversion Middle Route Project is assessed in this study. Complex and variable geological conditions complicate the prediction of soil moisture in the study area. To achieve this aim, we carried out research on soil moisture inversion methods for channel slopes in the study area using massive monitoring data from multiple GNSS observatories on channel slopes, incorporating GNSS-R techniques and deep learning algorithms. To address the issue of low accuracy in linear inversion when using a single satellite, this study proposes a multi-satellite and multi-frequency data fusion technique. Furthermore, three soil moisture inversion models, namely, the linear model, BP neural network model, and GA-BP neural network model, are established by incorporating deep learning techniques. In comparison with single-satellite data inversion, with the data fusion technique proposed in this study, the correlation is improved by 12.7%, the root mean square error is reduced by 0.217, the mean square error is decreased by 0.884, and the mean absolute error is decreased by 0.243 with the linear model. With the BP neural network model, the correlation is increased by 15.4%, the root mean square error is decreased by 0.395, the mean square error is decreased by 0.465, and the mean absolute error is reduced by 0.353. Moreover, with the GA-BP neural network model, the correlation is improved by 6.3%, the root mean square error is decreased by 1.207, the mean square error is decreased by 0.196, and the mean absolute error is reduced by 0.155. The results indicate that performing data fusion by using multiple satellites and multi-frequency bands is a feasible approach for improving the accuracy of soil moisture inversion. These research findings provide new technical means for the risk analysis of deformation disasters in the expansive soil channel slopes of the South-to-North Water Diversion Middle Route Project. Full article

(This article belongs to the Special Issue Exploring the Variations and Interplay of Drought and Heatwaves: Uncovering the Associated Mechanisms and Impacts)

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19 pages, 17167 KiB

Open AccessArticle

Spatiotemporal Variation and Factors Influencing Water Yield Services in the Hengduan Mountains, China

by Qiufang Shao, Longbin Han, Lingfeng Lv, Huaiyong Shao and Jiaguo Qi

Remote Sens. 2023, 15(16), 4087; https://doi.org/10.3390/rs15164087 - 19 Aug 2023

Cited by 5 | Viewed by 1983

Abstract

Conducting a quantitative assessment of water yield in mountainous areas is crucial for the management, development, and sustainable utilization of water resources. The Hengduan Mountains Region (HDMR) is a significant water-supporting area characterized by complex topography and climate changes. To analyze the spatial and temporal variations of water yield in the HDMR from 2001 to 2020, we employed the InVEST model and examined the influencing factors in conjunction with the elevation gradient. Our results indicate that: (1) The water yield in the Hengduan Mountains decreases from southeast to northwest, with the southwestern and eastern regions having high water yield values, and the high-altitude areas in the northwestern part having low water yield values. (2) The water yield in the Hengduan Mountains exhibits a decreasing trend followed by an increasing trend from 2001 to 2020, with the lowest level in 2011 and higher levels in 2004, 2018, and 2020. (3) Pixel-based trend analysis demonstrates a decreasing trend in water yield in the central and western parts of the study area, while the eastern part shows an increasing trend. (4) The climatic components, particularly precipitation, predominantly influence the spatial and temporal variations of water yield in the Transverse Mountain region. In most areas, evapotranspiration and land surface temperature have a negative impact on water yield. (5) Water yield tends to decrease and then increase on the altitudinal gradient, with precipitation and actual evapotranspiration being the factors directly affecting water yield, and land surface temperature and the proportion of forested areas having a significant indirect effect on water yield. Our study provides a scientific basis for water resources management and sustainable development in the Hengduan Mountains. Full article

(This article belongs to the Special Issue Exploring the Variations and Interplay of Drought and Heatwaves: Uncovering the Associated Mechanisms and Impacts)

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19 pages, 9985 KiB

Open AccessArticle

Ecosystem Resistance and Resilience after Dry and Wet Events across Central Asia Based on Remote Sensing Data

by Jie Zou, Jianli Ding, Shuai Huang and Bohua Liu

Remote Sens. 2023, 15(12), 3165; https://doi.org/10.3390/rs15123165 - 18 Jun 2023

Cited by 9 | Viewed by 2826

Abstract

Climate change forecasts indicate that the frequency and intensity of extreme climate events will increase in the future; these changes will have important effects on ecosystem stability and function. An important arid region of the world, Central Asia has ecosystems that are extremely vulnerable to extreme weather events. However, few studies have investigated the resistance and resilience of this region’s ecosystems to extreme weather events. In this study, first, the extreme drought/wet threshold was calculated based on the 113-year (1901–2013) standardized precipitation–evapotranspiration index (SPEI); second, moderate resolution imaging spectroradiometer (MODIS) remote sensing data were applied to calculate ecosystem water use efficiency (WUE) and quantify ecosystem resistance and resilience after different extreme climate events; and finally, differences in the changes of various ecosystem types before and after climate events were assessed. The results showed the following: (1) The average SPEI was 0.073, and the thresholds of extreme wetness and drought were 0.91 and −0.67, respectively. Central Asia experienced extreme wet periods in 2002 and 2003 and a drought period in 2008. (2) Suitable wetness levels can increase the resistance of an ecosystem; however, continuous wetness reduces ecosystem resistance, as does drought. Wet areas had strong resilience after wet events, and arid areas had strong resilience after drought events. (3) During both wet and drought years, the transition between shrubland and grassland caused changes in ecosystem resistance and resilience. These findings are important for understanding the impact of future climate change on ecosystem stability. Full article

(This article belongs to the Special Issue Exploring the Variations and Interplay of Drought and Heatwaves: Uncovering the Associated Mechanisms and Impacts)

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