Floods and droughts research progress and its contributions toward sustainability.

In 2015, the United Nations General Assembly launched seventeen Sustainable Development Goals (SDGs), aimed at being achieved by 2030. The SDGs 6 (clean water & sanitation) and 13 (climate actions) are two critically important goals concerning water resources that need to be addressed. This study used the Scopus database to explore climate extremes, specifically droughts and floods, in East Asia and highlight the region's efforts and contributions towards achieving SDGs 6 and 13. We found that even before the implementation of SDGs, the topics related to solving the problems of water resources, water quality, and treatment of wastewater using different conceptual models and methodologies were the main concerns in the region. The adoption of SDGs has led to a heightened focus on water and climate sustainability in East Asia, with the considerable surge in climate-related studies after 2019. Under SDG 13, all countries have contributed substantially to climate action research. Keyword analysis indicates that climate change, water management, water treatment, water quality, and adsorption remain prominent. SDGs 6 and 13 have emerged as crucial areas of focus for research and initiatives as the global community grapples with escalating water resources and climate challenges. Under specific keywords search, China has 2nd place in the search with climate and water during the SDGs period, accounting for 21 % of the entire publication from 2015 to 2023. Japan and South Korea account for of 4 % and 3 %, respectively. The research on floods and droughts has garnered significant attention, with half of the ten highly co-cited literature examining the changing pattern of drought, the influence of extreme events on crop yield, and other related topics. Despite the positive contribution of the East Asia region towards SDGs 6 and 13, there is still an urgent need for a more robust framework to improve the complex interconnections between climate actions, clean water, and sanitation for a sustainable soil-water-plant-atmosphere ecosystem.

Measurement and analysis of the resilience characteristics for a regional agricultural soil-water resource composite system.

Resilience is a significant attribute used to measure the sustainable development of the environment, and research on optimal measurement models is very important. This study took 15 farms in the Jiansanjiang Administration of Heilongjiang Province in China as the research object and constructed a resilience evaluation indicator system containing 31 indicators for the regional agricultural soil-water resource composite system (ASWRS). The combined weight (BFCM-CRITIC) and entropy weight (EW) combined with the variable fuzzy assessment (VFA) model and the improved technique for order preference by similarity to an ideal solution (TOPSIS) model were used to calculate the resilience exponent and to analyse the characteristics of space-time variation. The stability and reliability of the two models under different weights were verified by the Spearman correlation coefficient and discrimination theory to determine the optimal resilience exponent diagnosis method. The results show that according to the BFCM-CRITIC-VFA model, the levels of resilience were the highest at the Nongjiang, Hongwei and Erdaohe farms, and the resilience levels were strong and scattered. The resilience of the Jiansanjiang Administration has been increasing over time, and the spatial distribution has generally decreased from north to south and from the Heilong River and Wusuli River basins inland. A comparison of the reliability and stability of the two models for different weights indicates that the VFA model optimized based on combined weights was superior to the other methods in terms of stability and reliability, which verifies that the BFCM-CRITIC-VFA model is the most suitable for measuring the resilience exponent.

Assessment of the response of climate variability and price anomalies to grain yield and land use in Northeast China.

Evidence revealed that climate change has a significant impact on grain production in China. Northeast China has abundant agricultural resources which can make the maximum contribution to national food security. This study examines the effects of climate variability and price anomalies on grain yield and land use in Northeast China. The analysis showed that different climate variability phase combinations based on Pacific Decadal Oscillation and North Atlantic Oscillation present variations in signals and different magnitude of effects over the study area. The results revealed that land use by total grain crop negatively responds to the increase in price anomalies in Heilongjiang and Jilin Provinces. To assess the impact of climate change on crop yield model, the yield models under dynamically downscaled regional climate models revealed that climate variables significantly contribute to total grain yields. In the near future, minimum temperature (- 0.26 °C under CanESM2-4.5, - 4.42 °C under HadGEM2-ES), maximum temperature (- 2.82 °C under CanESM2-4.5, - 0.84 under HadGEM2-ES), and precipitation (ranged from 3.59 to 11.10%) positively contribute to total grain yields under both models. Overall, analysis showed that climate change has a significant contribution to grain production. In conclusion, the implications for future research and policymakers have been addressed. Particularly, the importance of considering regional differences in adaptation planning in agricultural regions was also considered.