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Drought is a natural disaster and its occurrence and development can be attributed to a range of driving factors, such as deficient precipitation, wind, temperature, land use/land cover changes, and so on. Therefore, attribution and monitoring of droughts are complicated and challenging. Standardized Precipitation Evapotranspiration Index (SPEI) has been widely used in meteorological drought monitoring. Nonstationarity has not been considered in SPEI-based drought monitoring. Here we propose a modified SPEI considering the nonstationarity of hydrometeorological processes, i.e. NSPEI hereafter. We observe nonstationarity SPEI in the Northeast, the Huang-Huai-Hai Plain, the Yangtze River Delta, and the Qinghai-Tibet Plateau. The goodness-of-fit can be determined for 76% of the total stations. Under the assumption of nonstationarity, the drought monitoring performance of the NSPEI is more robust than the traditional SPEI. Besides, we evaluate drought conditions across China under four shared socioeconomic pathways (SSPs), i.e. SSP126, SSP245, SSP370 and SSP585. We identify intensifying droughts in southwest China but a wetting tendency in northern China in winter under the SSP126 scenario; but a significant wetting tendency in southwest China and a drying tendency in northeast China under SSP245, SSP370 and SSP585 scenarios. This study provides a novel meteorological drought index and highlights a fresh picture of drought conditions across China under different SSPs. • A non-stationary SPEI index is developed. • The drought monitoring performance of the NSPEI is robust than the traditional SPEI. • We reevaluated drought conditions across China in future. [ABSTRACT FROM AUTHOR]

Monitoring of droughts is the first step into human adaptation and related management of drought hazards. Therefore, drought index is critical in drought monitoring practice. However, the standing drought indices include no information about agricultural irrigation. In this case, based on the Palmer Drought Severity Index (PDSI) and the Self-Calibrating Palmer Drought Severity Index (sc-PDSI), here we proposed the Modified Palmer Drought Severity Index (MPDSI) by considering agricultural irrigation such as irrigation quotas and soil water deficits. We compared changes of droughts monitored by MPDSI and other drought indices considered in this study, and found that MPDSI can well monitor drought conditions in irrigated regions. In this sense, MPDSI can monitor the actual drought conditions under human influences such as irrigation. Besides, we also found that MPDSI can well lessen overestimation of drought conditions by PDSI in terms of drought duration and drought intensity. Therefore, we can conclude that MPDSI can be accepted in drought monitoring practice across China. It should be noted here that the idea behind development of MPDSI and also the MDPSI proposed in this study can be well referenced in drought monitoring in other regions of the globe. • We improved the standing PDSI. • We found less sensitivity of Modified PDSI to warming climate than PDSI. • We found improved drought monitoring performance of modified PDSI than PDSI. [ABSTRACT FROM AUTHOR]

In this paper, we comprehensively evaluated the utility of integrated long-term satellite-based precipitation and evapotranspiration products for drought monitoring over mainland China. The latest Integrated Multi-satelliteE Retrievals for Global Precipitation Measurement V06 three Runs precipitation products, i.e., the near real-time Early Run (IMERG-E) and Late Run (IMERG-L) and the post-real time Final Run (IMERG-F), and the Global Land Evaporation Amsterdam Model V3.3a (GLEAM) potential evapotranspiration (PET) products from 2001 to 2017 were considered. The accuracy of IMERG precipitation and GLEAM PET products was first evaluated against observed precipitation and Penman-Monteith method estimated PET, respectively, based on dense meteorological station network. The Standard Precipitation Evapotranspiration Index (SPEI) calculated based on IMERG precipitation and GLEAM PET products (SPEIs, including SPEI E , SPEI L and SPEI F corresponding to IMERG-E, IMERG-L and IMERG-F, respectively) were then validated by using SPEI calculated based on meteorological data (SPEIm) at multiple temporal-spatial scales. Finally, four typical drought events were selected to analyse the ability of SPEIs to characterize the temporal-spatial evolution of drought situations. The results showed that the IMERG-F presents much better performance than IMERG-E and IMERG-L in terms of higher CC and smaller BIAS and RMSE values over mainland China. The GLEAM PET well simulated the change trend of reference PET, but generally underestimated reference PET in Northwest China (NW), Xinjiang (XJ) and Qinghai–Tibet plateau (TP). In general, the performances of SPEIs over eastern China and Southwest China (SW) were significantly superior to their performances in the NW, XJ, and TP regions. Even though the SPEI F performed the best, the SPEI E and SPEI L also performed reasonably well in some specific regions. SPEIs can well capture the temporal process and reasonably reflect the spatial characteristics for four typical drought events. It is thus highlighted that the latest IMERG precipitation (especially for IMERG-F) and GLEAM PET products could be used as alternative data sources for comprehensive drought monitoring, on account of the water balance principle over mainland China, particularly in eastern China and SW China. The outcomes of this study will provide valuable references for drought monitoring by integration of multi-source remote-sensing datasets in the GPM era. • The utility of integrated IMERG precipitation and GLEAM PET for drought monitoring was evaluated over mainland China. • SPEIs based on IMERG precipitation and GLEAM PET were validated at multiple spatial and temporal scales over mainland China. • IMERG precipitation and GLEAM PET show great potential for drought monitoring over eastern China and Southwest China. • SPEIs can well capture the temporal process and reasonably reflect the spatial characteristics for typical drought events. [ABSTRACT FROM AUTHOR]