Search

• The most suitable ecological streamflow was calculated via kernel density estimation method. • Ecological drought was identified using the variable threshold method based on ecological streamflow. • Impacts of climate variability and human activities on ecological drought were quantified. • Human activities are the dominant factor aggravating the ecological drought in the Weihe River Basin. Although various studies have investigated the impacts of climate variability and human activities on drought, researches specifically analysing the impact on ecological drought are still limited. A deep understanding of the climatic and anthropogenic effects on ecological drought processes is crucial for ecological regulation and management in the changing environments. In the present study, an integrated approach for comprehensive understanding and quantification of ecological drought in rivers was proposed which first applied the nonparametric kernel density estimation (KDE) method to calculate the most suitable ecological streamflow (MSES) for a river ecosystem. Then, the variable threshold level method based on the MSES for each month and the run theory method were applied to identify the ecological drought duration and deficit volumes. Finally, a quantification approach based on hydrological model simulation was proposed to attribute the impacts of climate variability and human activities on ecological drought. The proposed approach was applied on two catchments, Xianyang (XY) and Huaxian (HX) within the Weihe River Basin (WRB) in northern China. Comparison results obtained using the two empirical methods revealed that the MSES calculated using the KDE method was reasonable and can be used for ecological drought identification. The identification results showed that both the median and upper quartile values of the drought duration and deficit volumes during the disturbed period (1991–2017) were greater than those during the undisturbed period (1961–1990). Quantification results showed that human activities were the dominant factor aggravating ecological drought in the WRB after 1990. The contribution rates of climate variability and human activities toward ecological drought variations were 25.6% and 74.4%, respectively, for the XY station and 42.7% and 57.3%, respectively, for the HX station. Although the WRB was selected as a case study, the proposed approach can also be applied to other regions to provide scientific guidance for regional ecological management. [ABSTRACT FROM AUTHOR]

• An observation-based natural and human-impacted catchment comparison method is proposed. • Human influence are quantified based on gridded socio-economic and land use data. • Climatic and anthropogenic influences on drought propagation are investigated. • Climate change accelerates the response of hydrological drought to meteorological drought. • Human activities delay the propagation from meteorological to hydrological drought. It is crucial to investigate how a precipitation deficit is transformed into hydrological drought and how climate change and human activities affect this transformation process, which is helpful to gain a deep understanding of drought propagation process in this changing environment. This study proposed an observation-based natural and human-impacted catchment comparison method to assess the impacts of climate change and human activities on propagation from meteorological drought to hydrological drought. The method mainly consists of the following three steps: (1) selection of natural catchments through analysis of trends and change points of hydro-meteorological data, as well as statistics analysis of human influence based on land use and socio-economic indicators data sets; (2) calculation of drought propagation characteristics (e.g., drought severity, duration, and propagation time) based on run theory and the Pearson correlation coefficient; and (3) comparison of drought propagation characteristics of natural catchments between undisturbed and disturbed periods to identify the impacts of climate change on drought propagation, and comparison of the propagation characteristics between natural and human-impacted catchments during the disturbed period to investigate human influence on drought propagation. The Laohahe basin (with eleven sub-catchments), located in northern China, was evaluated via the proposed procedure, and standardized precipitation index (SPI) and standardized runoff index (SRI) were used to characterize meteorological and hydrological droughts, respectively. The results demonstrate that the proposed method is suitable tool for distinguishing natural and human-impacted catchments, and separating the impacts of climate change and human activities on drought propagation. Furthermore, the comparison results of different schemes show that climate change accelerates the propagation from meteorological drought to hydrological drought in the Laohahe basin, shortening it by approximately 3 months. Human activities, however, disturb and then delay the natural propagation from meteorological drought to hydrological drought, retarding it by 11–12 months. Although the Laohahe basin was selected as a case study in this paper, the proposed method can be applied in other regions as well to improve drought prediction and water resources management. [ABSTRACT FROM AUTHOR]

• A comprehensive approach for identifying drought termination characteristics is proposed. • Natural and human-influenced hydrological drought termination characteristics are identified. • Human activities significantly aggravate the drought termination duration, deficit and rate. • Human activities lead to shifts in drought termination seasonality. Although many previous studies have analysed the impacts of human activities on hydrological drought, studies that analysed these impacts from the perspective of drought termination, a critical re-wetting phase of hydrological drought, are limited. A deeper understanding on how human alter hydrological drought termination phase is essential for improving drought recovery prediction and performance of the drought early warning system. In this study, a comprehensive approach for identifying hydrological drought termination characteristics and quantifying the impact of human activities on drought termination was proposed. This approach, which combines the concept of drought termination (DT), an 'observed–simulated' comparison approach, and the variable threshold level method (TLM v), consists of the following steps: (1) reconstruction of natural streamflow using a hydrological model, (2) identification of hydrological drought termination characteristics using TLM v method and the concept of drought termination, and (3) quantification of human influence by comparison of the hydrological drought termination characteristics of human-influenced (observed) series and those of natural (simulated) series. The Laohahe basin, consists of four catchments (Xiquan, Xiaochengzi, Dianzi, and Taipingzhuang) in northern China, was evaluated using the proposed procedure. The study demonstrated that the proposed approach is efficient in quantifying human influence on hydrological drought termination phase. The results revealed that human activities have significant impacts on the hydrological drought termination phase in the Xiaochengzi, Dianzi, and Taipingzhuang catchments. All the average drought termination duration (DT dur), deficit (DT def), and rate (DT rate) in the human-influenced series of the three catchments (Xiaochengzi, Dianzi, and Taipingzhuang) increased in comparison to those in the natural series, with maximum increases of 230%, 865%, and 35%, respectively. The seasonality of the drought termination phase starts (DT start) and ends (DT end) for the three catchments exhibited obvious shifts due to human influence. The preferred seasons for DT start and DT end were shifted to summer and autumn, respectively. The proposed approach and findings of this study may help to gain a deeper understanding of how human activities alter hydrological drought termination severity (drought termination duration, deficit, and rate) and time (drought termination starts or ends). [ABSTRACT FROM AUTHOR]

[Display omitted] • A cascade model chain suitable for the risk of future DWAA events is proposed. • Evolution characteristics of DWAA in the future period of YRB are revealed. • Severity of DWAA events in far-future is greater than that in the near-future. • Extreme precipitation events have strong synchronization with DWAA events. At present, many studies have investigated the evolution characteristics, frequency estimation techniques, and prediction of droughts and floods, but a comprehensive understanding of the spatiotemporal evolution law and joint risk of these two composite extreme events is still lacking. The synergistic effect of dry and wet abrupt alternation (DWAA) events has more significant consequences than a single drought and flood event, and these events have a considerable impact on agriculture, ecology, and economy. Furthermore, owing to the intensification of global warming and climate change, the potential synchronisation between DWAA events and extreme precipitation in the future requires special attention. Therefore, it is necessary to establish a reliable framework to analyse the evolution characteristics and risks of composite extreme events (DWAA). In this study, a cascade modelling chain comprising climate model downscaling, non-uniform bias-correction technique, and model integration was developed to study the spatiotemporal evolution characteristics and combined risk impact of DWAA events. The proposed methodology was applied to the Yellow River Basin (YRB) in the historical period (1960–2014, Hist) and the future period (2021–2060, FUT1; and 2061–2100, FUT2) under the Shared Socioeconomic Pathway (SSP) 3–7.0 and 5–8.5 scenarios. The results show that: (1) The constructed cascade modelling chain has high simulation accuracy for precipitation, and can be used to analyse future DWAA events. (2) Considering the precipitation characteristics under SSP3-7.0 and SSP5-8.5 scenarios, the precipitation increases slightly in the near future FUT1 (about 5–10%), and increases significantly in the far future FUT2 (about 10–70%). (3) Following either scenario, the frequency of DWAA events is expected to decrease in the future compared to that in the Hist, but the average intensity is expected to increase compared to that in the Hist. (4) The joint risk of the impact area and intensity of future DWAA events of FUT2 is greater than that of FUT1. [ABSTRACT FROM AUTHOR]

In this study, a comprehensive evaluation of the reliability of seventeen satellite-, reanalysis-, and gauge-based precipitation products (i.e., IMERG-F, GSMaP-G, TMPA 3B42, CMORPH-CRT, PERSIANN-CDR, CHIRPS, IMERG-E, IMERG-L, GSMaP-RT, TMPA-RT, PERSIANN-RT, ERA5, ERA-Interim, MERRA2, GPCC, CPC, and CRU) was conducted for drought monitoring from June 2000 to December 2019 over mainland China. The girded China monthly Precipitation Analysis Product (CPAP) with a dense station network was used as the benchmark observed precipitation data. The Standardized Precipitation Index (SPI) was used as a drought monitoring tool. The comprehensive evaluation procedures were implemented by a monthly precipitation evaluation, various timescales SPI verification, and typical drought event analysis. The results indicated that the performance of per precipitation product is in accordance with the generally higher monthly accuracy in eastern China than that in western China. The post-process satellite precipitation products, particularly bias-adjusted GPM-based products, i.e., the IMERG-F and GSMaP-G, are significantly better at detecting the monthly precipitation than the reanalysis (ERA5 and ERA-Interim), and near real-time satellite precipitation datasets. The best performances are observed for MERRA2 from reanalysis-based precipitation datasets, and GPCC from gauge-based precipitation products, for both precipitation estimation and drought monitoring. Regarding drought monitoring, the performance ranking of most precipitation products is basically consistent with monthly precipitation estimation. The SPI behaviors based on the bias-adjusted GPM-based products have inferior performance than those in MERRA2 and GPCC at the continental scale. Nevertheless, some discrepancies exist in the reliability level of drought detection in sub-regions and multi-timescales. Integrally, the IMERG-F is evaluated to be the most ideal precipitation data among the seventeen precipitation products for drought monitoring in eastern and southwest China. However, in comparison to the GPCC performance, the accuracy of satellite precipitation products should be further improved in the Xinjiang and Tibet Plateau regions. The outcomes of this study will provide valuable insights into the drought monitoring by using multi-sources open access precipitation products across mainland China. • 17 precipitation products reliability were analyzed over mainland China. • Reanalysis- and gauge-based datasets were used to reveal the performance level of satellite-estimated drought. • IMERG-F is the most suitable dataset for drought research in eastern and southwest China [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]

This study evaluated the suitability of the latest retrospective Integrated Multi-satellitE Retrievals for Global Precipitation Measurement V06 (IMERG) Final Run product with a relatively long period (beginning from June 2000) for drought monitoring over mainland China. First, the accuracy of IMERG was evaluated by using observed precipitation data from 807 meteorological stations at multiple temporal (daily, monthly, and yearly) and spatial (pointed and regional) scales. Second, the IMERG-based standardized precipitation index (SPI) was validated and analyzed through statistical indicators. Third, a light–extreme–light drought-event process was adopted as the case study to dissect the latent performance of IMERG-based SPI in capturing the spatiotemporal variation of drought events. Our results demonstrated a sufficient consistency and small error of the IMERG precipitation data against the gauge observations with the regional mean correlation coefficient (CC) at the daily (0.7), monthly (0.93), and annual (0.86) scales for mainland China. The IMERG possessed a strong capacity for estimating intra-annual precipitation changes; especially, it performed well at the monthly scale. There was a strong agreement between the IMERG-based SPI values and gauge-based SPI values for drought monitoring in most regions in China (with CCs above 0.8). In contrast, there was a comparatively poorer capability and notably higher heterogeneity in the Xinjiang and Qinghai-Tibet Plateau regions with more widely varying statistical metrics. The IMERG featured the advantage of satisfactory spatiotemporal accuracy in terms of depicting the onset and extinction of representative drought disasters for specific consecutive months. Furthermore, the IMERG has obvious drought monitoring abilities, which was also complemented when compared with the Precipitation Estimation from the Remotely Sensed Information using Artificial Neural Networks Climate Data Record (PERSIANN-CDR), Climate Hazards Group Infrared Precipitation with Stations (CHIRPS), and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) 3B42V7. The outcomes of this study demonstrate that the retrospective IMERG can provide a more competent data source and potential opportunity for better drought monitoring utility across mainland China, particularly for eastern China. [ABSTRACT FROM AUTHOR]

The multi-satellite retrieved soil moisture products released from Europe Space Agency's Climate Change Initiative (ESA CCI) program have been widely used in plenty of fields including drought monitoring. In this study, Cumulative Distribution Function (CDF) is applied to match the simulated soil moisture from the Variable Infiltration Capacity (VIC) model for filling the missing records of ESA CCI soil moisture (ESA CCI SM). The weekly Standard Soil Moisture Index (SSI) calculated from ESA CCI SM dataset (ESA CCI SSI) is conducted to monitor the agricultural drought over the Yellow River Basin (YRB) during 2000~2012. The performance of ESA CCI SSI is compared with the Standard Precipitation Index (SPI), the Standard Precipitation Evapotranspiration Index (SPEI), the self-calibrating Palmer Drought Severity Index based on VIC model (VIC_scPDSI) and the anomaly of Normalized Difference Vegetation Index (NDVI). The results show that the interpolated ESA CCI SM is significant (p<0.05) correlated with the observed soil moisture and more than 84% of the girds in the YRB display good correlations with the global reanalysis soil moisture. In terms of drought monitoring (i.e. drought area and drought intensity), ESA CCI SSI presents a similar spatiotemporal pattern with VIC_scPDSI, while exhibits a delayed response to SPI and SPEI significantly. Analysis of the typical drought event in 2002 indicates that ESA CCI SSI could effectively capture the emerge and development process of this event and the drought severity detected by ESA CCI SSI is higher than that of SPI and SPEI. Besides, it is found that spatial characteristics of ESA CCI SSI and the anomaly of NDVI are consistent in some areas of the basin. [ABSTRACT FROM AUTHOR]