Drought Time-scales Research Articles

Understanding and seasonal forecasting of hydrological drought in the Anthropocene

Abstract. Hydrological drought is not only caused by natural hydroclimate variability but can also be directly altered by human interventions including reservoir operation, irrigation, groundwater exploitation, etc. Understanding and forecasting of hydrological drought in the Anthropocene are grand challenges due to complicated interactions among climate, hydrology and humans. In this paper, five decades (1961–2010) of naturalized and observed streamflow datasets are used to investigate hydrological drought characteristics in a heavily managed river basin, the Yellow River basin in north China. Human interventions decrease the correlation between hydrological and meteorological droughts, and make the hydrological drought respond to longer timescales of meteorological drought. Due to large water consumptions in the middle and lower reaches, there are 118–262 % increases in the hydrological drought frequency, up to 8-fold increases in the drought severity, 21–99 % increases in the drought duration and the drought onset is earlier. The non-stationarity due to anthropogenic climate change and human water use basically decreases the correlation between meteorological and hydrological droughts and reduces the effect of human interventions on hydrological drought frequency while increasing the effect on drought duration and severity. A set of 29-year (1982–2010) hindcasts from an established seasonal hydrological forecasting system are used to assess the forecast skill of hydrological drought. In the naturalized condition, the climate-model-based approach outperforms the climatology method in predicting the 2001 severe hydrological drought event. Based on the 29-year hindcasts, the former method has a Brier skill score of 11–26 % against the latter for the probabilistic hydrological drought forecasting. In the Anthropocene, the skill for both approaches increases due to the dominant influence of human interventions that have been implicitly incorporated by the hydrological post-processing, while the difference between the two predictions decreases. This suggests that human interventions can outweigh the climate variability for the hydrological drought forecasting in the Anthropocene, and the predictability for human interventions needs more attention.

Response of vegetation to different time-scales drought across China: Spatiotemporal patterns, causes and implications

Based on Normalized Difference Vegetation Index (NDVI) and Standardized Precipitation Evapotranspiration Index (SPEI), we investigated vegetation response to different time-scales drought across different vegetation types and homogeneous clusters in China, by annual maximum Pearson correlation (Rmax) and the corresponding time-scales of drought. Results showed that: (1) 8 subregions with homogeneous climate-vegetation conditions were identified using Fuzzy C-Means algorithm; (2) SPEI and NDVI's annual Rmax were in significantly positive correlation in most regions of China, indicating that vegetation biomass were influenced mainly by the spatiotemporal characteristics of the water availability. The southeastern Yangtze River basin and the lower Pearl River basin are dominated by abundant precipitation, and vegetation is not sensitive to droughts in these regions. The northeastern Heilongjiang province, the Changbai Mountains and western Sichuan province are characterized by weak NDVI versus SPEI relations, indicating a relatively small effect of drought on vegetation; (3) The effects of annual average water balance, annual average annual precipitation, annual average effective accumulative temperature, and annual average daily sunshine hours on the NDVI versus SPEI correlation show that the annual average water balance is the key factor behind the change of vegetation vigor. It can therefore be concluded that the change of water availability is the key factor behind the change of vegetation activity and biomass. Regional precipitation or water balance was significantly related to the correlation between SPEI and NDVI. Vegetation in the regions with longer sunshine hours is more sensitive to droughts. In general, the sensitivity of grassland to droughts is the largest, followed by the sensitivity of shrubs and forests to droughts.

Multi-time-scale analysis of hydrological drought forecasting using support vector regression (SVR) and artificial neural networks (ANN)

In this study, the preprocessing of the gamma test was used to select the appropriate input combination into two models including the support vector regression (SVR) model and artificial neural networks (ANNs) to predict the stream flow drought index (SDI) of different timescales (i.e., 3, 6, 9, 12, and 24 months) in Latian watershed, Iran, which is one of the most important sources of water for the large metropolitan Tehran. The variables used included SDIt, SDIt − 1, SDIt − 2, SDIt − 3, and SDIt − 4 monthly delays. Two variables including SDIt and SDIt − 1 with lower gamma values were identified as the most optimal combination of variables in all drought timescales. The results showed that the gamma test was able to correctly identify the right combination for the forecasting of 6, 9, and 12 months SDI using the ANN model. Also, the gamma test was considered in selecting the appropriate inputs for identifying the values of 9, 12, and 24 months SDI in SVR. The support vector machine approach showed a better efficiency in the forecast of long-term droughts compared to the artificial neural network. In total, among forecasts made for 30 scenarios, the support vector machine model only in scenario 3 of SDI3, scenario 1 of SDI6, and scenarios 2 and 3 of SDI24 represented poorer efficiency compared to the artificial neural network (MLP layer), but in other scenarios, the results of SVR had better efficiency.

Investigating event‐specific drought attribution using self‐organizing maps

AbstractPrevious studies evaluating anthropogenic influences on the meteorological drivers of drought have found mixed results owing to (1) the complex physical mechanisms which lead to the onset of drought, (2) differences in the characteristics and time scales of drought for different regions of the world, and (3) different approaches to the question of attribution. For a midlatitude, temperate climate like New Zealand, strongly modulated by oceanic influences, summer droughts last on the order of 3 months, and are less strongly linked to persistent temperature anomalies than continental climates. Here we demonstrate the utility of a novel approach for characterizing the meteorological conditions conducive to extreme drought over the North Island of New Zealand, using the January–March 2013 event as a case study. Specifically, we consider the use of self‐organizing map techniques in a multimember coupled climate model ensemble to capture changes in daily circulation, between two 41 year periods (1861–1901 and 1993–2033). Comparisons are made with seasonal pressure and precipitation indices. Our results demonstrate robust (>99% confidence) increases in the likelihood of observing circulation patterns like those of the 2013 drought in the recent‐climate simulations when compared with the early‐climate simulations. Best guess estimates of the fraction of attributable risk range from 0.2 to 0.4, depending on the metric used and threshold considered. Contributions to uncertainty in these attribution statements are discussed.

Drought in a human-modified world: reframing drought definitions, understanding, and analysis approaches

Abstract. In the current human-modified world, or Anthropocene, the state of water stores and fluxes has become dependent on human as well as natural processes. Water deficits (or droughts) are the result of a complex interaction between meteorological anomalies, land surface processes, and human inflows, outflows, and storage changes. Our current inability to adequately analyse and manage drought in many places points to gaps in our understanding and to inadequate data and tools. The Anthropocene requires a new framework for drought definitions and research. Drought definitions need to be revisited to explicitly include human processes driving and modifying soil moisture drought and hydrological drought development. We give recommendations for robust drought definitions to clarify timescales of drought and prevent confusion with related terms such as water scarcity and overexploitation. Additionally, our understanding and analysis of drought need to move from single driver to multiple drivers and from uni-directional to multi-directional. We identify research gaps and propose analysis approaches on (1) drivers, (2) modifiers, (3) impacts, (4) feedbacks, and (5) changing the baseline of drought in the Anthropocene. The most pressing research questions are related to the attribution of drought to its causes, to linking drought impacts to drought characteristics, and to societal adaptation and responses to drought. Example questions include (i) What are the dominant drivers of drought in different parts of the world? (ii) How do human modifications of drought enhance or alleviate drought severity? (iii) How do impacts of drought depend on the physical characteristics of drought vs. the vulnerability of people or the environment? (iv) To what extent are physical and human drought processes coupled, and can feedback loops be identified and altered to lessen or mitigate drought? (v) How should we adapt our drought analysis to accommodate changes in the normal situation (i.e. what are considered normal or reference conditions) over time? Answering these questions requires exploration of qualitative and quantitative data as well as mixed modelling approaches. The challenges related to drought research and management in the Anthropocene are not unique to drought, but do require urgent attention. We give recommendations drawn from the fields of flood research, ecology, water management, and water resources studies. The framework presented here provides a holistic view on drought in the Anthropocene, which will help improve management strategies for mitigating the severity and reducing the impacts of droughts in future.

Using multifractal and wavelet analyses to determine drought characteristics: a case study of Jilin province, China

Drought is a recurrent disaster that occurs in virtually all climatic zones of the world. However, drought characteristics vary substantially among different climatic regions. In this study, multifractal and wavelet analyses are used to characterize drought based on monthly precipitation. The rainfall data of 28 precipitation stations from 1958 to 2011 in Jilin province were collected to calculate the standardized precipitation index (SPI), and the negative monthly SPI time-series is used in a multiscaling approach to determine drought characteristics in Jilin province. Simple scaling and multiscaling analyses show significant variations in monthly droughts in the region. Morlet wavelet analysis also shows that significant cycles and multiple time-scales of drought exist in all stations. Cross wavelet analysis shows that drought occurrence in the region is mainly influenced by different climatic factor scales. However, different factors have different degrees of influence at different regions. The enduring influence of medium and long-term climatic patterns (such as El Nino events) may lead to the simple scaling behavior of drought for some regions.

Assessing the Added Value of Dynamical Downscaling Using the Standardized Precipitation Index

In this study, the Standardized Precipitation Index (SPI) is used to ascertain the added value of dynamical downscaling over the contiguous United States. WRF is used as a regional climate model (RCM) to dynamically downscale reanalysis fields to compare values of SPI over drought timescales that have implications for agriculture and water resources planning. The regional climate generated by WRF has the largest improvement over reanalysis for SPI correlation with observations as the drought timescale increases. This suggests that dynamically downscaled fields may be more reliable than larger-scale fields for water resource applications (e.g., water storage within reservoirs). WRF improves the timing and intensity of moderate to extreme wet and dry periods, even in regions with homogenous terrain. This study also examines changes in SPI from the extreme drought of 1988 and three “drought busting” tropical storms. Each of those events illustrates the importance of using downscaling to resolve the spatial extent of droughts. The analysis of the “drought busting” tropical storms demonstrates that while the impact of these storms on ending prolonged droughts is improved by the RCM relative to the reanalysis, it remains underestimated. These results illustrate the importance and some limitations of using RCMs to project drought.

Drought risk assessment in central Nepal: temporal and spatial analysis

This paper presents temporal and spatial pattern of drought phenomena in central Nepal using standardized precipitation index (SPI) at multiple time scales. The study is based on 32 years of monthly precipitation data from 40 meteorological stations from 1981 to 2012. Results indicate that, while there is no distinct trend in regional precipitation, interannual variation is large. Trend analysis of drought index shows that most stations are characterized by increases in both severity and frequency of drought and trend is stronger for longer drought time scales. Over the study period, the summer season of 2004, 2005, 2006, 2009 and winters 2006, 2008 and 2009 were the worst widespread droughts. These dry periods have a serious impact on agriculture–livestock production of central Nepal. Better understanding of these SPI dynamics could help in understanding the characteristics of droughts and also to develop effective mitigation strategies.

Contrasting impacts of continuous moderate drought and episodic severe droughts on the aboveground-biomass increment and litterfall of three coexisting Mediterranean woody species.

Climate change is predicted to increase the aridity in the Mediterranean Basin and severely affect forest productivity and composition. The responses of forests to different timescales of drought, however, are still poorly understood because extreme and persistent moderate droughts can produce nonlinear responses in plants. We conducted a rainfall-manipulation experiment in a Mediterranean forest dominated by Quercus ilex, Phillyrea latifolia, and Arbutus unedo in the Prades Mountains in southern Catalonia from 1999 to 2014. The experimental drought significantly decreased forest aboveground-biomass increment (ABI), tended to increase the litterfall, and decreased aboveground net primary production throughout the 15 years of the study. The responses to the experimental drought were highly species-specific. A. unedo suffered a significant reduction in ABI, Q. ilex experienced a decrease during the early experiment (1999-2003) and in the extreme droughts of 2005-2006 and 2011-2012, and P. latifolia was unaffected by the treatment. The drought treatment significantly increased branch litterfall, especially in the extremely dry year of 2011, and also increased overall leaf litterfall. The drought treatment reduced the fruit production of Q. ilex, which affected seedling recruitment. The ABIs of all species were highly correlated with SPEI in early spring, whereas the branch litterfalls were better correlated with summer SPEIs and the leaf and fruit litterfalls were better correlated with autumn SPEIs. These species-specific responses indicated that the dominant species (Q. ilex) could be partially replaced by the drought-resistant species (P. latifolia). However, the results of this long-term study also suggest that the effect of drought treatment has been dampened over time, probably due to a combination of demographic compensation, morphological and physiological acclimation, and epigenetic changes. However, the structure of community (e.g., species composition, dominance, and stand density) may be reordered when a certain drought threshold is reached.

Drought Response to Air Temperature Change over China on the Centennial Scale

Climate data from the Climatic Research Unit(CRU) for the period 1901–2013 are used to investigate the drought response to air temperature change over China on the centennial scale. Drought is observed to have increased evidently across China, except for some regions in eastern China. This increase is much stronger in northern China compared to southern China, especially in Northwest and North China. These change characteristics of drought are closely associated with air temperature change, with the severe droughts in the major drought episodes of the last century generally coinciding with higher temperatures. The significantly increasing trend of drought in China based on observations only appears when considering the effects of air temperature change,which can explain ~49% of droughts in observations and30%–65% of droughts in Coupled Model Intercomparison Project Phase 5(CMIP5) model simulations. Furthermore, the response of drought to air temperature change generally increases as the drought time scale increases.Furthermore, drought shows relatively high sensitivity in spring and early summer in China on the centennial scale.

Performance of the standardised precipitation evapotranspiration index at various lags for agricultural drought risk assessment in the Czech Republic

In this study we investigated the influence of drought on crop productivity and, in particular, the drought time-scales that affect the growth of eleven agricultural crops with growth cycles of different lengths in the Czech Republic. In addition, the performance of the standardised precipitation evapotranspiration index (SPEI) at various lags for the assessment of agricultural drought risks was determined. The SPEI was used to quantify the drought (wet) conditions for each month of the year and 24 accumulated lags for 304 climatological stations from 1961 to 2012. The temporal evolution of the standardised yield residuals series (SYRS) of 11 agricultural crops (spring wheat, winter wheat, spring barley, winter barley, winter rye, oats, oilseed rape, maize, sugar beet, potatoes, and grapevine) over a period of 52 years were conducted. To summarise the correlation analyses and compare the drought effect among crops, we found differences in the responses of agricultural crops to different lags of the SPEI. However, the monthly de-trended SPEI had a relatively strong association with SYRS at critical growth stages of the crops. The greatest yield-drought correlation was for cereals (r=0.52–0.60; May–June), and the least yield-drought correlation was for grapes (r=0.31; early flowering and berry growth). If one compares the frequency of drought between 1961–1980 and 2001–2012, it is evident that over the past 12 years, the drought risk in the April–June period has increased by more than one fold. Drought during the April–June period became a factor explaining a considerable proportion of the yield variability. We found that drought risk expressed in terms of the SPEI at 1-, 3-, and 6-month lags is an increasing problem during the early stages of root and tuber crops.

Meteorological Drought Characteristics Research of Western Jilin Province Based on Wavelet Analyses

Drought is a recurrent feature of the climate. It occurs in virtually all climatic zones, and its characteristics vary significantly among regions. The precipitation data are obtained from 6 fairly distributed stations across western Jilin province (in China) for the period from 1957 to 2010. The calculated monthly standardized precipitation index (SPI) is used as a drought index. SPI not only nicely reflects drought intensity and duration, but also has a multi-temporal scale application dimension. For the purpose of analyzing multiple meteorological drought time-scales, Morlet wavelet transforms of the station monthly SPI time-series are interpreted. The results show that some stations, such as Chang-Ling and Tong-Yu, have remarkably significant cycles in their respective wavelet power spectrum and variance. However, these significant cycles are not clearly noticeable in the other stations. Irrespective of the trend, time-scale and cycles generally influence drought characteristics in the study area.

Response of vegetation to drought time-scales across global land biomes.

We evaluated the response of the Earth land biomes to drought by correlating a drought index with three global indicators of vegetation activity and growth: vegetation indices from satellite imagery, tree-ring growth series, and Aboveground Net Primary Production (ANPP) records. Arid and humid biomes are both affected by drought, and we suggest that the persistence of the water deficit (i.e., the drought time-scale) could be playing a key role in determining the sensitivity of land biomes to drought. We found that arid biomes respond to drought at short time-scales; that is, there is a rapid vegetation reaction as soon as water deficits below normal conditions occur. This may be due to the fact that plant species of arid regions have mechanisms allowing them to rapidly adapt to changing water availability. Humid biomes also respond to drought at short time-scales, but in this case the physiological mechanisms likely differ from those operating in arid biomes, as plants usually have a poor adaptability to water shortage. On the contrary, semiarid and subhumid biomes respond to drought at long time-scales, probably because plants are able to withstand water deficits, but they lack the rapid response of arid biomes to drought. These results are consistent among three vegetation parameters analyzed and across different land biomes, showing that the response of vegetation to drought depends on characteristic drought time-scales for each biome. Understanding the dominant time-scales at which drought most influences vegetation might help assessing the resistance and resilience of vegetation and improving our knowledge of vegetation vulnerability to climate change.

A multiscalar global evaluation of the impact of ENSO on droughts

[1] In this study we analyzed the influence of the El Nino-Southern Oscillation (ENSO) phenomenon on drought severity at the global scale. A unique aspect of the analysis is that the ENSO influence was quantified using a multiscalar drought indicator, which allowed assessment of the role of the ENSO phases on drought types affecting various hydrological, agricultural and environmental systems. The study was based on ENSO composites corresponding to El Nino and La Nina phases, which were obtained from the winter El Nino 3.4 index for the period 1901–2006. Drought was identified in a multiscalar way using the Standardized Precipitation Evapotranspiration Index (SPEI) and the global SPEIbase data set. The study revealed the differing impacts of the El Nino and La Nina phases on drought severity, the time scales of droughts, and the period of the year when the ENSO phases explained drought variability worldwide. In large areas of America and eastern Europe the role of ENSO events were evident at the shortest time scales (1–3 months) at the beginning of events, but in areas of South Africa, Australia and Southeast Asia the effects were more obvious some months later, and at longer time scales. We also identified areas where severe drought conditions are associated with more than 70% of ENSO events. The persistence of the drought signal at longer time-scales (e.g., 6- or 12-months) is not directly determined by the atmospheric circulation response to the SST anomalies, since the SPEI anomalies will be caused by the cumulative dry conditions in some specific months. Knowledge of how these effects differ as a function of the El Nino and La Nina phases, and how they propagate throughout the drought time scales could aid in the prediction of the expected drought severity associated with the ENSO. Lags detected during the study may help forecasting of dry conditions in some regions up to one year before their occurrence.

Comment on “Characteristics and trends in various forms of the Palmer Drought Severity Index (PDSI) during 1900–2008” by Aiguo Dai

] Dai [2011] (henceforth D11) reported that the PalmerDrought Severity Index (PDSI) is superior to other statisti-cally based drought indices including the StandardizedPrecipitation Index (SPI) and the Standardized PrecipitationEvapotranspiration Index (SPEI). D11 argued that given thephysical character of the PDSI water balance model, theindex provides robust estimates of drought severity becauseit takes the preceding conditions into account, in contrast toother drought indices that are based purely on past statisticsof particular climate variable(s). However, D11 has over-estimated the ability of the PDSI to realistically simulate thedistributed soil water balance at large spatial scales, andignored the inherent complexity and multiscalar character ofdrought phenomena, which are related to more than themoisture conditions of the soil. In this comment we discussthe complex characteristics of droughts and the limitationsof the PDSI to quantify drought conditions in a variety ofhydrological systems. We describe the advantages of statis-tically based drought indices including the SPI and the SPEI.ThefactthattheSPIandtheSPEIarenot(anddonotintendtobe) physically based indices is more liberating than con-straining, especially when the physical basis of PDSI can beseriously questioned.[