Study loss of vegetative cover and increased land surface temperature through remote sensing strategies under the inter-annual climate variability in Jinhua-Quzhou basin, China.

The Jinhua-Quzhou basin in China is one of the most susceptible areas to drought. Due to the loss of vegetation and great fluctuations in rainfall and surface temperature, global warming occurs. Timely, accurate, and effective drought monitoring is crucial for protecting local vegetation and determining which vegetation is most vulnerable to increased LST during the period 1982-2019. It assumes a strong correlation between loss of vegetation cover, changes in monsoon climate, drought, and increases in land surface temperature (LST). Due to significantly increased in LST, low precipitation and vegetation cover, NDVI, TVDI, VCI, and NAP are useful in characterizing drought mitigation strategies. The temperature vegetation drought index (TVDI), normalized difference vegetation index (NDVI), vegetation condition index (VCI), and monthly precipitation anomaly percentage (NAP) can be helped to characterize drought reduction strategies. Monthly NDVI, NAP, VCI, TVDI, normalized vegetation supply water index (NVSWI), temperature condition index (TCI), vegetation health index (VHI), and heat map analysis indicate that the Jinhua-Quzhou basin experienced drought during 1984, 1993, 2000, and 2011. Seasonal SR, WVP, WS, NDVI, VCI, and NAP charts confirm that the Jinhua-Quzhou basin was affected by severe drought in 1984, which continued and led to severe droughts in 1993, 2000, and 2011. Regression analysis showed a significant positive correlation between NDVI, TVDI, VCI, and NAP values, while NVSWI, TVDI, and VHI showed positive signs of good drought monitoring strategies. The research results confirm the correlation between loss of vegetation cover and LST, which is one of the causes of global warming. The distribution of drought changed a trend indicating that compared with the Jinhua region; the Quzhou region has more droughts. The changing trend of drought has characteristics from 1982 to 2019, and there are significant differences in drought changing trends between different Jinhua-Quzhou basin areas. Overall, from 1982 to 2019, the frequency of drought showed a downward trend. We believe that these results will provide useful tools for drought management plans and play a relevant role in mitigating the effects of drought and protecting humanity from climate hazards.

The Role of Climate Change and Its Sensitivity on Long-Term Standardized Precipitation Evapotranspiration Index, Vegetation and Drought Changing Trends over East Asia.

Droughts have become more severe and frequent due to global warming. In this context, it is widely accepted that for drought assessments, both water supply (rainfall) and demand (standardized precipitation evapotranspiration index, SPEI) should be considered. Using SPEI, we explored the spatial-temporal patterns of dry and wet annual and seasonal changes in five sub-regions of East Asia during 1902-2018. These factors are linked to excess drought frequency and severity on the regional scale, and their effect on vegetation remains an important topic for climate change studies. Our results show that the SPEI significantly improved extreme drought and mostly affected the SPEI-06 and SPEI-12 growing seasons in East Asia during 1981-2018. The dry and wet annual SPEI trends mostly affect the five sub-regions of East Asia. The annual SPEI had two extremely dry spells during 1936-1947 and 1978-2018. Japan, South Korea, and North Korea are wet in the summer compared to other regions of East Asia, with drought frequency occurring at 51.4%, respectively. The mean drought frequencies in China and Mongolia are 57.4% and 54.6%. China and Mongolia are the driest regions in East Asia due to high drought frequency and duration. The spatial seasonal analysis of solar radiation (SR), water vapor pressure (WVP), wind speed (WS), vegetation condition index (VCI), temperature condition index (TCI), and vegetation health index (VHI) have confirmed that the East Asia region suffered from maximum drought events. The seasonal variation of SPEI shows no clear drying trends during summer and autumn seasons. During the winter and spring seasons, there was a dry trend in East Asia region. During 1902-1990, a seasonal SPEI presented diverse characteristics, with clear wet trends in Japan, Mongolia, and North Korea in four different growing seasons, with dry trends in China and South Korea. During 1991-2018, seasonal SPEI presented clear dry trends in Japan, Mongolia, and North Korea in different growing seasons, while China and South Korea showed a wet trend during the spring, autumn, and winter seasons. This ecological and climatic mechanism provides a good basis for the assessment of vegetation and drought-change variations within East Asia. An understandings of long-term vegetation trends and the effects of rainfall and SPEI on droughts of varying severity is essential for water resource management and climate change adaptation. Based on the results, water resources will increase under global warming, which may alleviate the water scarcity issue in the East Asia region.

MaxEnt model strategies to studying current and future potential land suitability dynamics of wheat, soybean and rice cultivation under climatic change scenarios in East Asia.

Climate change and variability are projected to alter the geographic suitability of lands for crops cultivation. Accurately predicting changes in the potential current and future land suitability distribution dynamics of wheat (Triticum aestivum), soybean (Glycine max) and rice (Oryza sativa) crops due to climate change scenarios is critical to adapting and mitigating the impacts of bioclimatic changes, and plays a significant role in securing food security in East Asia region. This study compiled large datasets of wheat, soybean and rice occurrence locations from GBIF and 19 bioclimatic variables obtained from the WorldClim database that affect crops growth. We recognized potential future suitable distribution regions for crops under the one socioeconomic pathway, (SSP585) for 2021-2040 and 2041-2060, using the MaxEnt model. The accuracy of the MaxEnt was highly significant with mean AUC values ranging from 0.833 to 0.882 for all models evaluated. The jackknife test revealed that for wheat, Bio4 and Bio12 contributed 17.6% and 12.6%, for soybean Bio10 and Bio12 contributed 15.6% and 49.5%, while for rice Bio12 and Bio14 contributed 12.9% and 36.0% to the MaxEnt model. In addition, cultivation aptitude for wheat, soybean, and rice increased in southeast China, North Korea, South Korea, and Japan, while decreasing in Mongolia and northwest China. Climate change is expected to increase the high land suitability for wheat, soybean, and rice in East Asia. Simulation results indicate an average decrease of unsuitable areas of -98.5%, -41.2% and -36.3% for wheat, soybean and rice from 2060 than that of current land suitability. In contrast, the high land suitable for wheat, soybean and rice cultivation is projected to increase by 75.1%, 68.5% and 81.9% from 2060 as compared with current. The findings of this study are of utmost importance in the East Asia region as they present an opportunity for policy makers to develop appropriate adaptation and mitigation strategies required to sustain crops distribution under future climates. Although the risks of wheat, soybean and rice cultivation may be significantly higher in the future because of high temperatures, heat waves, and droughts caused by climate change.

Improving drought mitigation strategies and disaster risk reduction through MODIS and TRMM-based data in relation to climate change over Pakistan.

Drought is an extreme climatic event that mostly occurs as a result of low rainfall, which leads to lack of water in various agro-ecological conditions of Pakistan. The condition could be further exacerbated by the prevailing dry weather. Therefore, accurate, timely, and efficient drought monitoring is crucial to ensure that its adverse effects are mitigated. In this study, Moderate Resolution Imaging Spectroradiometer (MODIS) and TRMM-based data were used together with remote sensing techniques to improve drought mitigation and disaster risk reduction strategies. In order to monitor drought mitigation and disaster risk reduction strategies in Pakistan, the crop water stress index (CWSI), vegetation condition index (VCI), normalized vegetation supply water index (NVSWI), vegetation health index (VHI), and temperature vegetation drought index (TVDI) were chosen as the instrument. Due to low rainfall and significantly low vegetation, CWSI, NDVI, TVDI, and VHI are useful in characterizing drought mitigation strategies in Pakistan. Monthly NDVI, NAP, NVSWI, TVDI, VCI, and VHI values and heat map analysis show that Pakistan suffered from drought in years 2001, 2002, and 2006. Seasonal CWSI, NDVI, VHI, and TVDI confirmed that Pakistan was affected by severe drought in 2001, which continued and led to severe drought in 2002 and 2006. We generate spatial correlation coefficients between NDVI and NVSWI, VCI, and VHI, and NVSWI and VCI and VHI, while the VCI and VHI values are significantly positively correlated. CWSI, NDVI, VHI, and TVDI show positive signs of effective climate change drought mitigation and disaster risk reduction strategies in Pakistan. Thus, these drought indices have been confirmed to be a complete drought monitoring indicator and reduce the risk of drought in Pakistan.

Impact assessment of drought monitoring events and vegetation dynamics based on multi-satellite remote sensing data over Pakistan.

Drought is a complex hazard caused by the disruption of rainwater balance, and it always has an impact on ecological, farming and socio-economic. In order to protect farming land in Pakistan, effective and timely drought monitoring is extremely essential. Therefore, a regular drought monitoring is required to study drought severity, its duration and spread, to ensure effective planning and to help reduce their possible adverse impacts. In this study, multi-satellite data were used for reliable drought monitoring. For monitoring changing trend of drought in Pakistan, the NVSWI, DSI, VCI, and NAP indices were chosen as a tool incorporated with Moderate Resolution Imaging Spectroradiometer (MODIS)-based NDVI and ET/PET. Due to the low vegetation and significantly high changing trend of drought, NDVI, DSI and TVDI are useful to characterize drought frequency in Pakistan. The yearly DSI index shows that Pakistan suffered of drought with low vegetation during 2001, 2002 and 2006 study years. The seasonal DSI, VCI, NAP, NDVI, and NVSWI values confirmed that 2001, 2002 and 2006 led to severe drought years in Pakistan. The regression analysis between VHI, VCI, NDVI and NVSWI values are significantly positively correlated. The NAP, DSI, and NVSWI showed the positive signs for good drought monitoring indices for agricultural regions of Pakistan. The trend of drought change from 2001 to 2017 also showed characteristics. The results showed that from 2001 to 2017, the drought trend of the whole region changed obviously, and the overall drought frequency showed a downward trend. The good performance of DSI, and NVSWI could, explicitly, contribute progressively towards improving specific drought mitigation strategies and disaster risk reduction at regional and national levels.