Meteorological and agricultural droughts are inherently correlated, whereas the propagation mechanism between them remains unclear in Northwestern China. Investigating the linkages between these drought types and identifying the potential influencing factors is crucial for effective water resource management and drought mitigation. This study adopted the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Soil Moisture Index (SSMI) to characterize the meteorological and agricultural droughts from 1960 to 2018. The propagation time between these droughts was detected using the Pearson correlation analysis, and the cross-wavelet transform and wavelet cross-correlation were utilized to describe their linkages across the time–frequency scales. The grey relational analysis was applied to explore the potential factors influencing the propagation time. The results revealed that the agricultural drought typically lagged behind the meteorological drought by an average of 6 months in Northwestern China, with distinct seasonal and regional characteristics. The shortest propagation time occurred in the summer (3 months), followed by the autumn (4 months), and the propagation time was longer in the winter (8 months) and spring (9 months). Additionally, the average propagation time was longer in the plateau climate zone (8 months) than in the southeastern climate zone (6 months) and the westerly climate zone (4 months). There was a multi-timescale response between the meteorological and agricultural droughts, with a relatively stable and significant positive correlation over long timescales, whereas the correlation was less clear over short timescales. The key factors influencing the propagation time were soil moisture, elevation, precipitation, and potential evapotranspiration. Furthermore, the wavelet cross-correlation between agricultural and meteorological droughts was relatively high, with a lag of 0 to 3 months; as the timescale increased, the fluctuation period of their cross-correlation also increased.

Meteorological drought is a continuous spatiotemporal phenomenon that poses a serious threat to water resource security. Dynamic evolution and multivariable frequency analysis of meteorological drought are important for effective drought mitigation and risk management. Therefore, this study aims to analyze meteorological drought events in northwestern China between 1960 and 2018 based on the standardized precipitation evapotranspiration index (SPEI) through a three-dimensional identification method. This study investigates the meteorological drought dynamic evolution on different time and space scales and evaluates the frequency analysis considering the spatiotemporal variability based on Copula. The results show that SPEI presents an upward trend in Northwestern China. A trend towards increased humidity is observed in arid regions, contrasted by a trend towards aridification in semi-arid and semi-humid areas, indicating that the spatial distribution of drought in the study area tends towards homogenization. The possibility of high-intensity drought events occurring in the same area was relatively low, whereas low-intensity drought events were frequent. Additionally, this study analyzes the dynamic migration process of individual drought events from a three-dimensional perspective. Neglecting any one drought variable could significantly underestimate the occurring probability of severe drought events. Therefore, a multivariable frequency analysis considering the spatiotemporal variability plays a crucial role in the formulation of drought prevention and mitigation strategies, as well as drought forecasting.

The carbon cycle in terrestrial ecosystems is a crucial component of the global carbon cycle, and drought is increasingly recognized as a significant stressor impacting their carbon sink function. Net ecosystem productivity (NEP), which is a key indicator of carbon sink capacity, is closely related to vegetation Net Primary Productivity (NPP), derived using the Carnegie-Ames-Stanford Approach (CASA) model. However, there is limited research on desert grassland ecosystems, which offer unique insights due to their long-term data series. The relationship between NEP and drought is complex and can vary depending on the intensity, duration, and frequency of drought events. NEP is an indicator of carbon exchange between ecosystems and the atmosphere, and it is closely related to vegetation productivity and soil respiration. Drought is known to negatively affect vegetation growth, reducing its ability to sequester carbon, thus decreasing NEP. Prolonged drought conditions can lead to a decrease in vegetation NPP, which in turn affects the overall carbon balance of ecosystems. This study employs the improved CASA model, using remote sensing, climate, and land use data to estimate vegetation NPP in desert grasslands and then calculate NEP. The Standardized Precipitation Evapotranspiration Index (SPEI), based on precipitation and evapotranspiration data, was used to assess the wetness and dryness of the desert grassland ecosystem, allowing for an investigation of the relationship between vegetation productivity and drought. The results show that (1) from 1982 to 2022, the distribution pattern of NEP in the Inner Mongolia desert grassland ecosystem showed a gradual increase from southwest to northeast, with a multi-year average value of 29.41 gCm⁻². The carbon sink area (NEP > 0) accounted for 67.99%, and the overall regional growth rate was 0.2364 gcm⁻²yr⁻¹, In addition, the area with increasing NEP accounted for 35.40% of the total area (p < 0.05); (2) using the SPEI to characterize drought changes in the Inner Mongolia desert grassland ecosystems, the region as a whole was mainly affected by light drought. Spatially, the cumulative effect was primarily driven by short-term drought (1–2 months), covering 54.5% of the total area, with a relatively fast response rate; (3) analyzing the driving factors of NEP using the Geographical detector, the results showed that annual average precipitation had the greatest influence on NEP in the Inner Mongolian desert grassland ecosystem. Interaction analysis revealed that the combined effect of most factors was stronger than the effect of a single factor, and the interaction of two factors had a higher explanatory power for NEP. This study demonstrates that NEP in the desert grassland ecosystem has increased significantly from 1982 to 2022, and that drought, as characterized by the SPEI, has a clear influence on vegetation productivity, particularly in areas experiencing short-term drought. Future research could focus on extending this analysis to other desert ecosystems and incorporating additional environmental variables to further refine the understanding of carbon dynamics under drought conditions. This research is significant for improving our understanding of carbon cycling in desert grasslands, which are sensitive to climate variability and drought. The insights gained can help inform strategies for mitigating climate change and enhancing carbon sequestration in arid regions.

Agricultural drought poses significant challenges to food production and ecosystem sustainability. The evolution of drought and its recurrence period feature are important for drought mitigation and risk management. This study aims to evaluate agricultural drought using the Standardized Soil Moisture Index (SSMI) based on Global Land Data Assimilation System (GLDAS) products, and extract drought variables using a three-dimensional identification method in Northwestern China. Then, the spatiotemporal dynamics and recurrence characteristics of agricultural droughts were evaluated. The results showed that: (1) Study area experienced alternating phases of dry and wet, with intensification in the 1960s and 1990s, and significant humidification post-2000. All four seasons show a wetting trend, while spring exhibited notable humidification trends. (2) Drought intensity and frequency displayed regional variability, agricultural drought in the west part of the study area were high in frequency but low in intensity, while the opposite was true in the east. (3) Agricultural drought exhibited cyclical behavior with dominant periods of 3.5, 6.6, and 13.5 years, reflecting interannual and interdecadal fluctuations. (4) Multivariate joint recurrence periods highlighted significant correlations among drought characteristics, emphasizing the risk of underestimation when considering single variables. These results offer valuable insights for water resources allocation and drought mitigation.