Drought characteristics and dominant factors across China: Insights from high-resolution daily SPEI dataset between 1979 and 2018.

Drought, a complex phenomenon exacerbated by climate change, is influenced by various climate factors. The escalating global temperatures associated with climate change, impact precipitation patterns and water cycle processes, consequently intensifying the occurrence and severity of droughts. To effectively address and adapt to these challenges, it is crucial to identify the dominant climate factors driving drought events. In this study, we utilized the 1979-2018 Chinese meteorological forcing dataset to calculate the daily Standardized Precipitation Evapotranspiration Index (SPEI). The Theil-Sen and Mann-Kendall (M-K) tests were employed to analyze the spatial and temporal trends of drought severity and duration. Additionally, partial correlation analysis was conducted to examine the relationship between climate factors (precipitation and potential evapotranspiration (PET)) and drought characteristic (drought severity and duration). Through this comprehensive analysis, we aimed to identify the primary factors influencing drought severity and duration. The findings revealed the following key results: (1) Over the 40-year period from 1979 to 2018, drought trends in China and its seven climate divisions exhibited an increasing pattern. (2) During drought periods, most regions exhibited a positive correlation between PET and drought severity and duration, while precipitation demonstrated a negative correlation. However, certain areas experiencing severe drought displayed a negative correlation between PET and drought severity and duration, precipitation demonstrated a positive correlation with drought severity and duration. (3) PET emerged as the dominant climatic factor for meteorological drought in the majority of China. These findings contribute valuable insights for policymakers in the development of climate change adaptation and mitigation strategies. By understanding the dominant climate factors driving drought events, policymakers can implement effective measures to mitigate the adverse socioeconomic and environmental impacts associated with climate change.

Microwave-based soil moisture improves estimates of vegetation response to drought in China.

The increased frequency and severity of drought has heightened concerns over the risk of hydraulic vegetative stress and the premature mortality of ecosystems globally. Unfortunately, most land surface models (LSMs) continue to underestimate ecosystem resilience to drought - which degrades the credibility of model-predicted ecohydrological responses to climate change. This study investigates the response of vegetation gross productivity to water-stress conditions using microwave-based vegetation optical depth (VOD) and soil moisture retrievals. Based on the estimated isohydric/anisohydric spectrum, we find that vegetation at isohydric state exhibits a larger decrease in gross primary productivity and higher water use efficiency than anisohydric vegetation due to their more rigorous stomatal control and higher tolerance of carbon starvation risk. In addition, the introduction of microwave soil moisture improves the accuracy of isohydricity/anisohydricity estimates compared to those obtained using microwave VOD alone (i.e., increases their Spearman rank correlation versus the benchmark of Global Biodiversity Information Facility dataset from 0.12 to 0.63). Results of this study provide clear justification for the use of microwave-based soil moisture retrievals to enhance stomatal conductance parameterization within LSMs.

Emergy assessment of a wheat-maize rotation system with different water assignments in the north China plain.

Sustainable water use is seriously compromised in the North China Plain (NCP) due to the huge water requirements of agriculture, the largest use of water resources. An integrated approach which combines the ecosystem model with emergy analysis is presented to determine the optimum quantity of irrigation for sustainable development in irrigated cropping systems. Since the traditional emergy method pays little attention to the dynamic interaction among components of the ecological system and dynamic emergy accounting is in its infancy, it is hard to evaluate the cropping system in hypothetical situations or in response to specific changes. In order to solve this problem, an ecosystem model (Vegetation Interface Processes (VIP) model) is introduced for emergy analysis to describe the production processes. Some raw data, collected by investigating or observing in conventional emergy analysis, may be calculated by the VIP model in the new approach. To demonstrate the advantage of this new approach, we use it to assess the wheat-maize rotation cropping system at different irrigation levels and derive the optimum quantity of irrigation according to the index of ecosystem sustainable development in NCP. The results show, the optimum quantity of irrigation in this region should be 240-330 mm per year in the wheat system and no irrigation in the maize system, because with this quantity of irrigation the rotation crop system reveals: best efficiency in energy transformation (transformity = 6.05E + 4 sej/J); highest sustainability (renewability = 25%); lowest environmental impact (environmental loading ratio = 3.5) and the greatest sustainability index (Emergy Sustainability Index = 0.47) compared with the system in other irrigation amounts. This study demonstrates that application of the new approach is broader than the conventional emergy analysis and the new approach is helpful in optimizing resources allocation, resource-savings and maintaining agricultural sustainability.