Drought is a costly natural hazard with far-reaching impacts on agriculture, ecosystem, water supply, and socio-economy. While propagating through the water cycle, drought evolves into different ...types and affects the natural system and human society. Despite much progress made in recent decades, a synthesis of the characteristics, approaches, processes, and controlling factors of drought propagation is still lacking. We bridge this gap by reviewing the recent progress of drought propagation and discussing challenges and future directions. We first introduce drought propagation characteristics (e.g., response time scale, lag time), followed by different approaches, including statistical analysis and hydrological modeling. The recent progress in the propagation from meteorological drought to different types of drought (agricultural drought, hydrological drought, and ecological drought) is then synthesized, including the basic process, commonly used indicators, data sources, and main findings of drought propagation characteristics. Different controlling factors of drought propagations, including climate (e.g., aridity, seasonality, and anomalies of meteorological variables), catchment properties (e.g., slope, elevation, land cover, aquifer, baseflow), and human activities (e.g., reservoir operation and water diversion, irrigation, and groundwater abstraction), are then summarized. Challenges in drought propagation include the discrepancy in drought indicators (and approaches) and difficulty in characterizing the full propagation process and isolating influencing factors. Future analysis of drought propagation should shift from single indicators to multiple indicators, from individual drivers to combined drivers, from uni-directional analysis to feedbacks, from hazards to impacts, and from stationary to nonstationary assumptions. This review is expected to be useful for drought prediction and management across different regions under global warming.
Display omitted
•Drought propagation characteristics include response time scale, lag time, propagation rate, and spatial propagation•Correlation analysis, run theory, and response functions are statistical approaches for drought propagation analysis•Impacts of climate, catchments, and human activities on drought propagation were synthesized•Difficulties in modeling full propagation processes and isolating influences factors are prevailing challenges•Future directions of drought propagation analysis were discussed
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
We present a quantitative approach for measuring hydrological drought occurrence and severity based on terrestrial water storage observations from NASA's Gravity Recovery and Climate Experiment ...(GRACE) satellite mission. GRACE measurements are applied by calculating the magnitude of the deviation of regional, monthly terrestrial water storage anomalies from the time series' monthly climatology, where negative deviations represent storage deficits. Monthly deficits explicitly quantify the volume of water required to return to normal water storage conditions. We combine storage deficits with event duration to calculate drought severity. Drought databases are referenced to identify meteorological drought events in the Amazon and Zambezi River basins and the southeastern United States and Texas regions. This storage deficit method clearly identifies hydrological drought onset, end, and duration; quantifies instantaneous severity and peak drought magnitude; and compares well with the meteorological drought databases. It also reveals information about the hydrological effects of meteorological drought on regional water storage.
Key Point
GRACE‐based drought severity using water storage rather than just precipitation explicitly quantifies the volume of water needed to return to normal conditions and identifies hydrological drought onset, peak magnitude, duration, and severity
Full text
Available for:
FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SAZU, SBCE, SBMB, UL, UM, UPUK
Drought propagation describes the changes in a drought signal as it moves from one major type of drought to another. It is important to investigate the propagation among meteorological, agricultural ...and hydrological drought, as well as their major impacting factors, to improve understanding of the drought propagation relationship, monitor agricultural drought and reduce crop losses. This study presents the first exploration of the interplay between multiple droughts among different climate zones and seasons in China. The standardized precipitation evapotranspiration index (SPEI), standardized runoff index (SRI) and self-calibrating Palmer drought severity index (scPDSI) were used to represent meteorological, agricultural and hydrological drought, respectively. The Pearson correlation coefficient was used to analyze the propagation relationships among different droughts and identify the most sensitive season for drought propagation. The Lindeman–Merenda–Gold (LMG) method was used to quantify the relative importance of PRE (precipitation), PET (potential evapotranspiration) and SM (soil moisture) to hydrological and agricultural drought. The propagation from meteorological to agricultural drought was prominent in different seasons at the annual scale over China. In general, the propagation relationship from agricultural to hydrological drought was weaker than that from meteorological to agricultural drought. In Northern China (arid and semi-arid areas), there was a stronger propagation relationship from agricultural to hydrological drought in summer and autumn than in spring. There was also stronger propagation from agricultural to hydrological drought in eastern China than in western China. Different climate regions had different major factors driving hydrological drought because of the different climate characteristics. However, SM was generally the most important driving factor for agricultural drought in all climate regions. Mulching plastic film might be an effective and feasible method to reduce PET from soil evaporation in sub-regions that apply high irrigation levels. These findings may also be applied to strengthen the study of artificial regulation of water resources, which could be an approach to reducing crop losses from drought.
•The propagation between different drought types was strongest in summer.•Propagation from meteorological to agricultural drought was strongest in western China.•SM and PET were the main drivers of hydrological drought in arid and semi-arid areas.•SM was more important than PRE and PET in hydrological and agricultural drought.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
What the extent of meteorological drought could trigger the corresponding hydrological drought with different levels? This question is an important topic in the field of drought propagation, which ...however has not been resolved. Therefore, a novel model based on a Bayesian network was proposed to address this issue in this study. In this model, the drought pooling and excluding methods were applied to eliminate minor drought events. A drought matching approach based on drought propagation time was proposed to achieve the one by one matching between different types of drought. Moreover, based on the matched drought events and the copula-based conditional probability model, the drought propagation thresholds of meteorological drought for triggering hydrological drought at various levels were determined. In addition, the interval conditional probability was calculated to further explore the sensitivity of hydrological drought response to different meteorological drought conditions. Furthermore, the propagation ratio was proposed to characterize the differences of drought propagation threshold among various regions. The Wei River Basin was selected as a case study. Results indicated that the results of drought propagation threshold were reliable and accurate. The increase of interval conditional probability showed a typical S-curve, which can intuitively obtain the probability of hydrological drought occurrence at different levels under specific meteorological drought condition, so as to effectively guide drought preparedness and mitigation. The propagation ratio can describe the overall resistance of the basin to meteorological drought, and it mainly depended on the meteorological and underlying surface conditions as well as groundwater supply.
Display omitted
•A novel framework is proposed to calculate the propagation threshold between different types of drought.•The sensitivity of hydrological drought to different meteorological drought conditions is fully revealed.•Drought propagation threshold is associated with meteorological conditions and underlying surface characteristics.•The propagation ratio Pr could represent the drought resistance of the whole basin.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Hydrological drought usually lags behind meteorological drought. Obtaining the propagation threshold (PT) from meteorological drought to hydrological drought is important for providing early warnings ...of hydrological drought. Previous studies have only used single timescales to characterize PT; however, a single timescale cannot accurately describe the propagation attributes from meteorological to hydrological drought because drought has multi-timescale features. In addition, several methods can be used to obtain PT, such as run theory, correlation analysis, and non-linear response methods. However, these methods might produce different estimates of PT. Here, multi-timescale drought indices, namely the Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI), were used to represent meteorological drought and hydrological drought. PT estimates at multiple timescales (e.g., 1-month, 3-month, and 12-month) obtained from run theory, correlation analysis, and non-linear response methods were compared, and the possible reasons for differences in the PT estimates are discussed. We conducted a case study of three sub-basins (Xinfengjiang River, Qiuxiangjiang River, and Andunshui River) with low levels of human activity in the Dongjiang River Basin, which is located in a humid region in southern China. We found that estimates of PT differed at different timescales of drought indices and with different methods at the same timescales. Longer timescales of hydrological drought corresponded to larger PT and vice versa. The major cause of this pattern was the fact that different timescales of drought indices showed different response sensitivities to drought events. The PT obtained from run theory was the shortest; thus, run theory can provide conservative warnings to aid drought prevention and mitigation. Our findings can help drought managers select effective tools to manage the early stages of hydrological drought based on meteorological forecasts and thus minimize the negative impacts of hazards posed by drought.
Display omitted
•Propagation thresholds from meteorological to hydrological drought were determined.•Three methods were used to calculate propagation thresholds at different timescales.•Propagation thresholds at the same timescale derived from different methods differed.•Longer timescales of hydrological drought led to larger propagation thresholds.•The average propagation threshold derived from the run theory method was the smallest.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Understanding the multi-scale variation of drought is essentially important in drought assessment. Now, a comprehensive assessment is still lacking on the meteorological, ecological and hydrological ...drought perspectives. In order to better investigate multi-scale droughts, we carried out a comprehensive analysis of their long-term variation based on the two drought indices and observation data in Xinjiang, China, from 1961 to 2015. The two indices are the Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI). The results show that the SPI and SPEI are highly consistent for most stations and time scales in Xinjiang. Based on multi-scale and considered evaporative demand, the SPEI from 1961 to 2015 showed a wetting trend followed by a drying trend (as of 1997), giving an overall slight drying trend (−0.0122±0.0043 per year) for the 54-year period. We assessed the sensitivity of the two drought indices to precipitation (P) and potential evapotranspiration (PET) and found that the SPEI shows different sensitivity to P and PET. In arid regions characterized by high PET, drought severity is mostly determined by changes in PET. The intensified warming and diminished precipitation in Xinjiang that have been observed over the past two decades have resulted in SPEI-drought severity. These changes also amplify the risk of ecological drought. However, the hydrological drought was highly complex and not entirely comparable to the SPEI and SPI droughts. Hydrological records indicate that runoff in most rivers in the Tianshan Mountains has increased, whereas runoff in the Kunlun Mountains is either stable or has slightly decreased over the past 20years. A moderately high and statistically significant correlation between the runoff anomaly and the SPEI and SPI was revealed for four major rivers in the region. This implies that the accelerated river runoff in Xinjiang is a function of both precipitation and increasing glacier melt.
Display omitted
•Aggravated drought based on the SPEI in Xinjiang, China•Intensified warming and diminished precipitation increase the severity of the drought.•Increased ET0 amplifies the risk of ecological drought.•Hydrological drought is not entirely comparable to SPEI and SPI drought.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
•Non-stationary approach to examine the impact of environmental factors on drought.•A non-linear method is proposed for detection of change point in streamflow.•Drought is modeled by employing ...non-stationary GAMLSS algorithm.•The impact of climate variation on drought is larger than human activity.
Climate variation and human activities are two prime drivers influencing the hydrological cycle and the stationarity of hydrologic systems. Hydrological drought is caused by significant negative variation from normal hydrologic conditions, influenced by climate variation and human activities. Traditional methods employed for quantifying the impacts of climate change and human activities are based on the assumption of stationarity, which is no longer valid under the current changing environment. In this study, a heuristic segmentation method was used to identify the change point in streamflow time series by considering its non-linearity, and trend analysis was performed on hydro-meteorological variables before and after the change point. A non-stationary Standardized Runoff Index (SRINS) was constructed using Generalized Additive Models in Location, Scale, and Shape (GAMLSS). Finally, the influences of climate change and human activities on hydrological drought were quantified at various time scales. The results reveal change points in the streamflow time series after the 1990s. Significant decreases in precipitation and streamflow were also observed after the change points in all study watersheds, whereas the trend of potential evapotranspiration increased at a higher rate after the change points. The impact of climate change on the seasonal (three-month) time scale was greater in the winter and spring seasons, whereas the impact of human activities was significantly higher in the summer and autumn seasons. The influence of climate change on hydrological drought was dominant at longer (6- and 12-month) time scales, whereas human activities accounted for 25.6% and 20% of the changes in watersheds #1018 and #1019 on the 12-month time scale, respectively.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Hydrological extremes are changing under the impacts of environmental change, i.e., climate variation and human activity, which can substantially influence ecosystems and the living environment of ...humans in affected region. This study investigates the impacts of environmental change on hydrological drought in the middle reaches of the Yangtze River in China based on hydrological modelling. Change points for streamflow into two major lakes and a reservoir in the study area were detected in the late 1980s using the Mann-Kendall test. Streamflow simulation by a water balance model was performed, and the resulting Kling-Gupta efficiency value was >0.90. Hydrological drought events were identified based on the simulated streamflow under different scenarios. The results show that the hydrological drought occurrence was increased by precipitation, whereas the drought peak value was increased by potential evapotranspiration. The impacts of precipitation and potential evapotranspiration on drought severity and duration varied in the study area. However, hydrological drought was intensified by the influence of human activity, which increased the severity, duration and peak value of droughts. The dominant factor for hydrological drought severity is precipitation, followed by potential evapotranspiration and human activity. The impacts of climate variation and human activity on drought severity are larger than on drought duration. In addition, environmental change is shown to have an “accumulation effect” on hydrological drought, demonstrating that the indirect impacts of environmental change on hydrological drought are much larger than the direct impacts on streamflow. This study improves our understanding of the responses of hydrological extremes to environmental change, which is useful for the management of water resources and the prediction of hydrological disasters.
Display omitted
•An approach is proposed to study the impacts of environmental change on droughts.•The impact of climate variation on drought is larger than that of human activity.•Drought is intensified by human activity.•The impacts of environmental change on drought are larger than on streamflow.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
Long-term (over 30a) satellite-based quantitative rainfall estimate (SRE) products provide an ideal data source for hydrological drought monitoring. This study mainly explores the suitability of the ...two long-term SREs, the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) and the Climate Hazards Group (CHG) Infrared Precipitation with Stations (CHIRPS), for hydrological drought monitoring. A hydrological drought index called the standardized streamflow index (SSI) was used as an example and the Grid-based Xinanjiang (GXAJ) hydrological model was used for streamflow generation of the SREs. A middle size basin in the humid region of south China was selected as case study. The obtained results show that both SREs present acceptable performances for hydrological modeling, and CHIRPS outperformed PERSIANN-CDR. SSIs calculated by the SRE simulations generally fit well with the trend of observation-based on SSI but apparent deviations in drought intensity were also found. In contrast to hydrological modeling, performance of the SRE-based SSI showed almost no change after model recalibration. Both SREs generally present acceptable classification accuracy but tended to underestimate the levels of drought types. Both SREs accurately captured the beginning, end, and duration of this drought event; however, several deviations were found in severity and intensity estimation of the drought event. In general, both SREs are suitable for hydrological drought monitoring. Although the CHIRPS generally presented better performance, the PERSIANN-CDR is still adequate for hydrological drought monitoring.
Display omitted
•Hydrological drought monitoring utility of the Long-term QPEs is evaluated.•Hydrological model is an effective tool for QPE-based SSI calculation.•Both PERSIANN-CDR and CHIRPS could temporally capture the drought events.•Both the QPEs are useful for hydrological drought in ungauged basins.
Full text
Available for:
GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK, ZRSKP
PDF
