Standardized Streamflow Index Research Articles

Monitoring the Meteorological and Hydrological Droughts in the Largest River Basin (Mahaweli River) in Sri Lanka

This study assessed the meteorological and hydrological droughts and their relationship over 30 years from 1985 to 2015 in the largest river basin (Mahaweli River Basin (MRB)) in Sri Lanka. Data from 14 rainfall, 5 temperature, and 5 streamflow stations in and near the MRB were used in the present study. Universal drought indices including Standardized Precipitation Index (SPI) and Standardized Precipitation–Evapotranspiration Index (SPEI) were used to assess meteorological droughts. The Standardized Streamflow Index (SSI) was used in investigating hydrological droughts. Correlations between meteorological and hydrological droughts were obtained, annual variations were observed (in terms of SPI, SPEI, and SSI), and the spatial distributions of selected drought events were analyzed. Our results revealed that the highest correlation was found in long-term dry conditions in the wet zone. In addition, some negative correlations found showed the opposite behavior of correlations. Furthermore, in annual variations of droughts, extreme droughts were recorded in the dry zone as maximum values, while results were more prominent in the wet zone. In addition, the spatial distribution performed using SPI, SPEI, and SSI showed an extremely dry condition in 2004. Our findings are beneficial for policymaking and for the decision-makers in assessing meteorological and hydrological drought risks in the future.

Low Flow Trends in Texas Stream Segments Serving Unique Hydrologic Functions

In recognition of the unique hydrologic functions they serve, certain stream segments in Texas have been designated as ecologically significant. In this study, we evaluated low flow trends in seven hydrologically unique stream segments spanning three climatic divisions in Texas from 1970 to 2019. Despite increasing mean annual temperatures, there are no trends in low flows or other hydrologic variables in the East Fork of the San Jacinto River in the Upper Coast climatic division, likely due to local moisture surplus effects from the Gulf of Mexico. In the Edwards Plateau climatic division, annual low flows and annual baseflows are decreasing in the South Fork of the Guadalupe River, the Sabinal River and the Frio River. While increasing mean annual temperatures appear to have a role in the drying of all three of these stream segments, increasing annual potential evapotranspiration may be an additional driver in the Sabinal and Frio Rivers. Analysis of the Standardized Streamflow Index indicates that all seven stream segments experienced their worst streamflow droughts in the 2010s. As such, the watersheds draining to the gages on these stream segments have minimal anthropogenic impacts, suggesting the influence of climate on the observed stream drying.

Anthropogenic drought in the Yellow River basin: Multifaceted and weakening connections between meteorological and hydrological droughts

Connections between meteorological and hydrological droughts (CMHDs) have changed due to increasingly intensified human activities. Understanding such changes from an anthropogenic perspective is, therefore, of critical importance for drought monitoring, early warning, and adaptation. As the second-longest river system in China, the Yellow River basin (YRB) has been seriously impacted by humans and has a high risk of drought due to its dry climate, dense population and massive water demand. However, the effects of human activities on CMHDs in the YRB are still unclear. We thus used the standardized precipitation evapotranspiration index (SPEI) and the standardized streamflow index (SSI) to indicate meteorological drought (MD) and hydrological drought (HD), respectively, and analysed CMHDs with multiple indicators including trends, correlation, difference, and drought propagation characteristics. Our results highlighted the heterogeneity of CMHDs in terms of subregions and indicators and showed that this heterogeneity was impacted by humans by quantifying the effects of human activities (mainly referring to water abstraction and regulation) on CMHDs in each subregion. We found that 1) human activities aggravated the disconnections between MD and HD by sharpening the downward trend in the SSI and weakening the correlation (amplifying the difference) between the SPEI and SSI, and 2) human activities reduced the drought propagation rate from MD to HD, manifested by a decreased number of HD but a lengthening of the HD duration. In addition to the abovementioned effects that were consistent for most of the YRB, there were also some effects, for example, on HD intensity and drought propagation time, that differed among subregions, and these kinds of diverse responses of CMHDs might be related to the various human activities in terms of intensities, types, and regions. By analysing human effects on CMHDs, this study may be helpful in understanding drought and drought propagation in the Anthropocene, which is beneficial to watershed management.

Review of In-Situ and Remote Sensing-Based Indices and Their Applicability for Integrated Drought Monitoring in South Africa

The devastating socioeconomic impacts of recent droughts have intensified the need for improved drought monitoring in South Africa (SA). This study has shown that not all indices can be universally applicable at all regions worldwide, and there is no single index that can represent all aspects of droughts. The aim of this study was to review the performance and applicability of the Palmer drought severity index (PDSI), surface water supply index (SWSI), vegetation condition index (VCI), standardised precipitation index (SPI), standardised precipitation evapotranspiration index (SPEI), standardised streamflow index (SSI), standardised groundwater index (SGI), and GRACE (Gravity Recovery and Climate Experiment)-based drought indices in SA and provide guidelines for selecting feasible candidates for integrated drought monitoring. The review is based on the ‘2016 World Meteorological Organisation (WMO) Handbook of Drought Indicators and Indices’ guidelines. The PDSI and SWSI are not feasible in SA, mainly because they are relatively complex to compute and interpret and cannot use readily available and accessible data. Combining the SPI, SPEI, VCI, SSI, and SGI using multi-index or hybrid methods is recommended. Hence, with best fitting probability distribution functions (PDFs) used, and with an informed choice between parametric and non-parametric approaches, this combination has the potential for integrated drought monitoring. Due to the scarcity of groundwater data, investigations on the use of GRACE-based groundwater drought indices must be carried out. These findings may contribute to improved drought early warning and monitoring in SA.

Dynamic Characteristics and Possible Causes for the Propagation from Meteorological to Hydrological Drought over a Temperate Typical Steppe

Abstract Knowledge gain in the characteristics and mechanisms of drought propagation is indispensable for timely drought early warning and risk reduction over the grassland eco-region. This study focused on the Xilin River basin, which is a typical inland river basin located in the Inner Mongolia temperate steppe, China. The characteristics of meteorological and hydrological drought were assessed by applying the standardized precipitation index and standardized streamflow index. The propagation relationship between meteorological and hydrological droughts was then investigated from both static and dynamic perspectives, and the possible reasons for its temporal dynamics were discussed by considering environmental factors. Our results showed that the Xilin River basin has suffered from more serious meteorological drought than hydrological drought during the past 60 years, with a stationary evolution of meteorological drought but an overall drying trend in hydrological drought. The propagation from meteorological to hydrological droughts exhibited obvious seasonality, characterized by stronger intensity and shorter response time in the wet season. Nonstationary behaviors were identified for the temporal patterns of drought propagation time, especially showing a significant trend in April, May, and August. The dynamic changes in propagation time affected by regional forces were principally ruled by the precipitation variation positively and strongly, and they were moderately controlled by temperature, vegetation cover, and deep-layer soil moisture, with season-dependent effects. The effects of low-frequency atmospheric anomalies on drought propagation will be further investigated in future studies, which are expected to provide a better understanding of the physical mechanism of the large-scale climate forcing on local drought condition. Significance Statement A new research approach was proposed to assess the propagation relationship between meteorological and hydrological drought from both static and dynamic perspectives, and the possible reasons for the temporal dynamics were discussed by considering environmental factors. Focusing on an inland river basin over the Inner Mongolia typical steppe, the propagation from meteorological to hydrological droughts showed obvious seasonality. Nonstationary behaviors were identified for the temporal patterns of drought propagation time, which could be explained by the regional hydrometeorological conditions. The advanced understanding of drought propagation provides a scientific base for water resources planning and drought management within a grassland region.

Relating drought indices to impacts reported in newspaper articles

AbstractRelating drought indicators and real‐world impacts is fundamental for understanding and addressing drought vulnerability. We link drought indices and impacts from newspapers compiled in the Irish Drought Impacts Database (IDID) for the period 1900–2016. For three catchment clusters across the island of Ireland we link the Standardized Precipitation Index (SPI) with land‐based impacts and the Standardized Streamflow Index (SSI) with water‐based impacts by matching total reported articles per month with concurrent drought indices. Using logistic regression we find SPI‐3 links best with land‐based impact reports, whereas SSI‐2 links best with water‐based impact reports. Catchments in the east/southeast display the highest sensitivity to land‐ and water‐based impacts; however, in summer months at low deficits northwestern catchments show a higher likelihood of impact reports. In winter months the likelihood of water‐based impacts is considerably greater than the land‐based equivalent, particularly in east/southeastern catchments. Moreover, the likelihood of news‐worthy drought impacts has changed over the 117 year period. More severe deficits are required to induce a high likelihood (0.6) of land‐ and water‐based impacts in east/southeastern and southwestern catchments during 1961–2016 compared with 1900–1960. Largest changes emerge in the southwest with SPI‐3 values of −2.51 (<−3.00) required to reach the high impact likelihood threshold in the pre (post) 1961 period. Even greater reductions are found for water‐based impacts in the southwest with SSI‐2 values associated with high impact likelihoods changing from −2.04 to −2.58. Conversely, for catchments in the northwest more moderate drought deficits result in high impact likelihoods for both land‐based (from <−3.00 to −2.32 SPI‐3) and water‐based impacts (from <−3.00 to −2.29 SSI‐2) for the 1961–2016 period. These findings show the value of newspaper archives for understanding regional sensitivities to drought plus their potential for underpinning a near real‐time, drought monitoring and warning system in Ireland.

Time series analysis for droughts characteristics response to propagation

AbstractUnderstanding and exploring hydrological (H) or soil moisture (SM) drought due to meteorological (M) drought under changing climate is crucial for drought early warning. Previously, different methods were used to calculate drought propagation from one state (M to another [H or SM]). However, each method has its pros and cons and thus cannot describe appropriate propagation attributes. In this study, a time series analysis is carried out to explore the propagation process in the Yellow River Basin (YRB) and Hai River Basin (HRB) of China. Standardized Streamflow Index (SSI), Standardized SM Index (SSMI), and Standardized Precipitation Index (SPI) 1‐month time series were calculated using streamflow, satellite‐based SM, and precipitation from 1979 to 2016. The time series framework identifies the average drought propagation as 3.4–8.3 months (M–H) and 2.3–5 months (M–SM) in YRB, while 2.8–7.7 months (M–H) and 2.3–8.5 months (M–SM) in HRB. Cross‐wavelet analysis indicated that periodic characteristics of M drought are responsible for these droughts. Overall, the findings of this study may help to minimize the drought hazards posed by M droughts.

Simulating dissolved organic carbon during dryness/wetness periods based on hydrological characteristics under multiple timescales

Understanding and simulating dissolved organic carbon (DOC) concentrations is a challenge with important implications for water quality projections and carbon balance estimates, particularly at the event-scale. Hydrological dryness/wetness represents water shortage/surplus in surface water. Previous studies have analyzed the dynamic patterns of DOC concentrations during either dryness or wetness (or rewetting) periods. However, the dynamic patterns of DOC concentrations and corresponding simulations during both dryness and wetness events, based on their characteristics (i.e., duration and severity), remain to be fully understood, particularly under multiple timescales. This study proposed a framework to help overcome this limitation. The standardized streamflow index (SSI) combined with run theory was used to describe the dryness/wetness characteristics at the monthly, seasonal, and annual scales. Simulation models were constructed and validated based on the multivariable linear regression model and cross-validation method. Three evaluation indicators, namely, the coefficient of determination (R2), Nash-Sutcliffe efficiency (NSE), and mean absolute percentage error (MAPE, %), were employed to determine the optimal model. This model was then applied to additional basins based on the correction coefficient method. Three nearby basins (HP3a, HP4, and HP6), with different catchment areas (9.28 to 122.80 ha) and long-term (41 years) daily streamflow and weekly (or biweekly) DOC measurements in the Harp Lake catchment, south-central Ontario, Canada, were used to demonstrate the usefulness of the framework. Data from HP3a was used to construct and validate the simulation model, and the model was applied to the HP4 and HP6 basins. Results show that the average DOC concentration during the dryness events is lower than that in the wetness events at the monthly, seasonal, and annual scales. The average, maximum, and minimum DOC concentrations during the dryness events increased with the dryness/wetness index timescales, but decreased during the wetness events. The optimal model was able to accurately simulate the DOC concentrations (R2 ≥ 0.90, NSE ≥ 0.90, and MAPE ≤ 10 %) at the monthly, seasonal, and annual scales based on the hydrological characteristics during the dryness and wetness periods, respectively, and the application results exhibit a good performance. The proposed framework can help improve the forecasting of DOC concentrations and the corresponding ecological coping strategies at the event-scale under changing environments.

Meteorological and hydrological drought hazard, frequency and propagation analysis: A case study in southeast Australia

Study regionSoutheast Australia. Study focusWe investigated meteorological and hydrological drought characteristics using Standardized Precipitation Index (SPI), Standardized Streamflow Index (SSFI) and Effective Drought Index (EDI). Drought Hazard Index (DHI) was derived based on the probability of drought occurrence and Thiessen polygons using SPI/EDI, whereas Drought Frequency Index (DFI) was derived based on number of drought events, and data length using SPI, EDI, and SSFI. The modified Mann-Kendall test was applied to detect trends in streamflow data and hydrological droughts. Furthermore, correlation between meteorological and hydrological drought indices for different timesteps was assessed through Pearson’s and Spearman’s rank correlation analysis. Finally, the drought propagation time (DPT) from meteorological to hydrological drought was estimated by ‘theory of run.’ New hydrological insights for the regionOur major findings include: (i) The spatial coverage of DHI and DFI, based on SPI/EDI, illustrate that mainly south and coastal regions of the study area are the most ‘drought-prone’ (ii) A considerable proportion of streamflow stations shows a significant trend of decrease in annual streamflow, with the most dominant year of abrupt change is 1996; (iii) Hydrological droughts are increasing in the study area; (iv) Performance of EDI with SSFI is found to be better than SPI at 3-month timestep; and (v) DPT can be found using ‘theory of run’ however, defined DPT cannot be directly applied to other regions.

Hydrological Response to Meteorological Droughts in the Guadalquivir River Basin, Southern Iberian Peninsula

Drought is an extreme phenomenon that will likely increase in frequency and severity in the current context of climate change. As such, it must be studied to improve the decision-making process in affected areas. As a semi-arid zone, the Guadalquivir River basin, located in the southern Iberian Peninsula, is an interesting area to perform this study. The relationship between meteorological and hydrological droughts is studied using drought indices with data from 1980 to 2012. The chosen indices are the Standardized Streamflow Index (SSI) and the Standardized Precipitation Evapotranspiration Index (SPEI). Their correlations are calculated, based on SPEI accumulation periods, and these values are analyzed with a principal component analysis to find spatial patterns in drought behavior inside the basin. This analysis was performed for the continuous series and also for monthly series, to account for seasonal changes. It has been found that the relationship of drought types occurs at different time scales depending mainly on orography and catchment area. Two main patterns were found. Generally, for low altitudes and small catchment areas, accumulation periods are shorter indicating that hydrological system in this area respond rapidly to meteorological conditions. In mountainous parts of the basin, longer accumulation periods have a stronger influence due to effects such as snowmelt.

Study on the propagation probability characteristics and prediction model of meteorological drought to hydrological drought in basin based on copula function

Studying the probability characteristics of meteorological drought transmission to hydrological drought can help alleviate drought and optimize the allocation of water resources. This study takes the Yiluo River as the research object, and Standardized Precipitation Index (SPI) and Standardized Streamflow Index (SSI) were used to represent meteorological and hydrological drought, respectively. First, the stability of the precipitation and stream flow sequence is tested by using the heuristic segmentation algorithm. The correlation between meteorological and hydrological watershed was analyzed using cross wavelet transform and lag correlation to study the transmission time of meteorological drought to hydrological drought. Second, the characteristics of drought such as drought duration, drought intensity, and drought intensity are discussed by using the run theory. Finally, the joint distribution of the SPI and SSI sequence is constructed using Copula function. From the perspective of conditional probability, the propagation probability and propagation threshold from different levels of meteorological drought to hydrological drought are calculated. A hydrological drought prediction model based on the SPI—P(SSI|SPI) relation curve is proposed. The model is also validated based on the historical data. The results show that the model is suitable for light and middle hydrological drought prediction.

Monitoring drought in ungauged areas using satellite altimetry: The Standardized River Stage Index

The lack of in-situ hydrological observations, especially in remote and developing areas, is one of the main challenges of drought monitoring. This paper proposes a novel drought index, the Standardized River Stage Index (SRSI), based on data retrieved from satellite altimetry missions. The novelties of the SRSI are that it can quantitatively monitor drought of river water deficits at multiple timescales and that it does not require in-situ observations. The Mekong River is used as the case study to demonstrate and validate the SRSI calculated from the multi-mission satellite altimetry data (Envisat and Jason-2/3). The log-logistic distribution is best fitted for SRSI calculation for the highest goodness-of-fit for river stages for the Mekong River. The comparison with the Standardized Streamflow Index (SSI) from the in-situ discharge observations shows that the SRSI can reasonably capture the drought of river water deficit. It is effective in identifying the timing and intensity of severe drought events, such as the 2019 Thailand drought. The SRSI is also compared with the Standardized Precipitation Evapotranspiration Index and the GRACE Drought Index in revealing drought features such that the river water deficit of Mekong River has time lags of 2 to 3 months for precipitation deficits and water storage deficits. Hence, the SRSI is more suitable for monitoring drought of river water deficit, because it directly links to the streamflow via physical stage-discharge relationship. Overall, the SRSI provides an effective indicator of drought of river water deficit when in-situ observations are unavailable. It can serve in the real-time drought early warning in remote and developing areas.

Streamflow droughts in Sweden: Spatiotemporal patterns emerging from six decades of observations

Study RegionSwedenStudy focus:Although Sweden has historically been a country abundant with water, observed changes in temperature and precipitation patterns during the past century have perturbed regional hydrologic regimes, including the severity, frequency and duration of streamflow droughts. This study utilizes the standardized streamflow index (SSI) and the threshold-level method to provide an unprecedented overview of spatiotemporal patterns of streamflow droughts in 50 Swedish catchments over the past six decades. The study catchments were categorized into five clusters, of which each was analyzed for changes in various drought characteristics over the period 1961–2020. New hydrological insights for the regionMultiple severe streamflow drought events were detected over the past 60 years. Remarkably, droughts in 1976 and 1996 were identified as the most extreme and wide-spread events, also compared to the latest 2018 drought. Southern catchments were generally more often and more severely affected than northern catchments. Our results suggest a wetting tendency over the past six decades across the entire country. This occurs in conjunction with less severe, shorter and less frequent droughts, especially during colder winter months. Only in the southernmost regions, a slight drying trend in spring and summer was found. Thus, we argue that a better understanding and regional management of streamflow droughts is essential to secure the needs of the environment, society and economy now and in the future.

Hydrological Retrospective and Historical Drought Analysis in a Brazilian Savanna Basin

Analyzing historical droughts is essential to improve the assessment of future hydrological risks and to understand the effects of climate variability on streamflow. However, prolonged and consistent hydrological time series are scarce in the Brazilian savanna region. This study aimed to analyze the performance of climate reanalysis products in precipitation estimation, hydrological modeling, and historical drought analysis in a Brazilian savanna basin. For this purpose, precipitation data from the twentieth-century atmospheric model ensemble (ERA-20CM) and the land component of the fifth generation of European ReAnalysis (ERA5-Land) with bias correction were used. The weather variables were obtained from the Climatic Research Unit (CRU) and the hydrological modeling was performed using the Soil and Water Assessment Tool (SWAT). The Standardized Streamflow Index (SSI) was used to calculate hydrological drought in the basin. Overall, ERA5-Land performed satisfactorily in precipitation estimation, mainly on the monthly time scale, hydrological modeling, and drought prediction. Since ERA-20CM showed unsatisfactory values for the performance statistics in all analyses, the hydrologic drought (1950 to 2018) was performed with ERA5-Land. The results showed both an increase in the number of dry months and a decrease in wet months in recent decades.

Observed Changes in Crop Yield Associated with Droughts Propagation via Natural and Human-Disturbed Agro-Ecological Zones of Pakistan

Pakistan’s agriculture and food production account for 27% of its overall gross domestic product (GDP). Despite ongoing advances in technology and crop varieties, an imbalance between water availability and demand, combined with robust shifts in drought propagation has negatively affected the agro-ecosystem and environmental conditions. In this study, we examined hydro-meteorological drought propagation and its associated impacts on crop yield across natural and human-disturbed agro-ecological zones (AEZs) in Pakistan. Multisource datasets (i.e., ground observations, reanalysis, and satellites) were used to characterize the most extensive, intense drought episodes from 1981 to 2018 based on the standardized precipitation evaporation index (SPEI), standardized streamflow index (SSFI), standardized surface water storage index (SSWSI), and standardized groundwater storage index (SGWI). The most common and intense drought episodes characterized by SPEI, SSFI, SSWSI, and SGWI were observed in years 1981–1983, 2000–2003, 2005, and 2018. SPEI yielded the maximum number of drought months (90) followed by SSFI (85), SSWSI (75), and SGWI (35). Droughts were frequently longer and had a slower termination rate in the human-disturbed AEZs (e.g., North Irrigated Plain and South Irrigated Plain) compared to natural zones (e.g., Wet Mountains and Northern Dry Mountains). The historical droughts are likely caused by the anomalous large-scale patterns of geopotential height, near-surface air temperature, total precipitation, and prevailing soil moisture conditions. The negative values (<−2) of standardized drought severity index (DSI) observed during the drought episodes (1988, 2000, and 2002) indicated a decline in vegetation growth and yield of major crops such as sugarcane, maize, wheat, cotton, and rice. A large number of low-yield years (SYRI ≤ −1.5) were recorded for sugarcane and maize (10 years), followed by rice (9 years), wheat (8 years), and cotton (6 years). Maximum crop yield reductions relative to the historic mean (1981–2017) were recorded in 1983 (38% for cotton), 1985 (51% for maize), 1999 (15% for wheat), 2000 (29% for cotton), 2001 (37% for rice), 2002 (21% for rice), and 2004 (32% for maize). The percentage yield losses associated with shifts in SSFI and SSWSI were greater than those in SPEI, likely due to longer drought termination duration and a slower termination rate in the human-disturbed AEZs. The study’s findings will assist policymakers to adopt sustainable agricultural and water management practices, and make climate change adaptation plans to mitigate drought impacts in the study region.

Systematic assessment of the development and recovery characteristics of hydrological drought in a semi-arid area

Studies have documented the significant effect of various factors on hydrological drought events. However, few studies have quantified drought's development and recovery process under environmental changes. This study focused on identifying hydrological drought's development and recovery characteristics and their potential causes in a typical semi-arid area. The Standardized Streamflow Index (SSI) was used as a metric for hydrological droughts, while the run theory was applied to identify the development and recovery processes of droughts. Changes in observed (human disturbed scenario) and simulated (natural scenario) droughts by employing the SWAT (Soil and Water Assessment Tool) model were also investigated from 1970 to 2016. The “simulated-observed” approach was used to assess the impacts of human regulations on hydrological drought development and recovery characteristics. Results showed that hydrological droughts occurred mainly during 1980–1990 and 2000–2016. In the natural condition, drought duration and intensity were higher, while lower severity in the drought recovery stage than development stage was observed. The drainage characteristics of the basin played the most critical role in the development and recovery characteristics of drought, which were also influenced by climatic conditions. Human activities had exacerbated recent natural hydrological drought. When considering the contribution of human activities, the reservoir operation was the dominant anthropic factor affected the development and recovery process of drought in the study area. Under the effects of reservoir regulation, long-duration hydrological droughts became rare. Moreover, the recovery ability of drought had been weakened. The effects of the reservoir were progressively crucial gradually. Although the water got from the river by the reservoir had been reduced, the negative impact on aggravating drought remains stronger than the reservoir was initially constructed. The results of our study will help improve the optimal management of reservoirs in semi-arid areas and enhance drought early warning and forecasting system.

Drought impact links to meteorological drought indicators and predictability in Spain

Abstract. Drought affects many regions worldwide, and future climate projections imply that drought severity and frequency will increase. Hence, the impacts of drought on the environment and society will also increase considerably. Monitoring and early warning systems for drought rely on several indicators; however, assessments of how these indicators are linked to impacts are still lacking. Here, we explore the links between different drought indicators and drought impacts within six sub-regions in Spain. We used impact data from the European Drought Impact Report Inventory database and provide a new case study to evaluate these links. We provide evidence that a region with a small sample size of impact data can still provide useful insights regarding indicator–impact links. As meteorological drought indicators, we use the Standardised Precipitation Index and the Standardised Precipitation Evapotranspiration Index; as agricultural and hydrological drought indicators, we use a Standardised Soil Water Content Index and a Standardised Streamflow Index and a Standardised Reservoir Storage Index. We also explore the links between drought impacts and teleconnection patterns and surface temperature by conducting a correlation analysis, and then we test the predictability of drought impacts using a random forest model. Our results show that meteorological indices are best linked to impact occurrences overall and at long timescales between 15 and 33 months. However, we also find robust links for agricultural and hydrological drought indices, depending on the sub-region. The Arctic Oscillation, Western Mediterranean Oscillation, and the North Atlantic Oscillation at long accumulation periods (15 to 48 months) are top predictors of impacts in the northwestern and northeastern regions, the community of Madrid, and the southern regions of Spain, respectively. We also find links between temperature and drought impacts. The random forest model produces skilful models for most sub-regions. When assessed using a cross-validation analysis, the models in all regions show precision, recall, or R2 values higher than 0.97, 0.62, and 0.68, respectively. Thus, our random forest models are skilful in predicting drought impacts and could potentially be used as part of an early warning system.

Assessment of drought time-frequency relationships with local atmospheric-land conditions and large-scale climatic factors in a tropical Andean basin

This study analyzed in the Tomebamba subbasin the relationships between droughts, the condition of the vegetation, global scale climatic indices and local atmospheric variables. The variability of monthly meteorological and hydrological droughts, as well as the condition of the vegetation, were characterized using the standardized precipitation index (SPI), the standardized streamflow index (SSI), and the vegetation condition index (VCI). The wavelet coherence method was used to establish time-frequency relationships. The results indicate that the vegetation in good condition reduces the impact of hydrological drought events when there are no sudden precipitation impacts. The atmospheric variables at the local scale with the highest significant correlation are cloud cover, relative humidity, specific humidity, temperature and specific rainwater content between 500 and 750 hPa. The Multivariate ENSO Index (MEI), ENSO 3, the Southern Oscillation Index (SOI), the Pacific Decadal Oscillation (PDO), and the Pacific North American Index (PNA) are strongly linked to SPI and the ENSO 4 index to SSI. Vegetation does not show strong relationships with any climate indices, obtaining the best relationship with the PNA. The results provide a basis for the analysis of variability and propagation of the droughts in Andean basins, their relationships with local and large-scale factors, and the influence of drought on vegetation.

The Development of a Nonstationary Standardised Streamflow Index Using Climate and Reservoir Indices as Covariates

Under current global change, the driving force of evolution of drought has gradually transitioned from a single natural factor to a combination of natural and anthropogenic factors. Therefore, widely used standardised drought indices based on assumption of stationarity are challenged and may not accurately assess characteristics of drought processes. In this study, a nonstationary standardised streamflow index (NSSI) that incorporates climate and reservoir indices as external covariates was developed to access nonstationary hydrological drought. The first step of the proposed approach is to apply methods of trend and change point analysis to assess the nonstationarity of streamflow series to determine type of streamflow regime, that is, the natural and altered regime. Then, different nonstationary models were constructed to calculate the NSSI by selecting climate indices as covariates for streamflow series with natural regime, and climate and reservoir indices as covariate for streamflow series with altered regime. Four stations in the upper reaches of the Huaihe River basin, China, were selected to examine the performance of the proposed NSSI. The results indicated that Dapoling (DPL), Changtaiguan (CTG), and Xixian (XX) stations had natural streamflow regimes, while the Nanwan (NW) station had an altered regime. The global deviances of the optimal nonstationary models were 17 (2.2%), 18 (2.9%), 26 (4.0%), and 22 (3.5%) less than those of stationary models for DPL, CTG, NW, and XX stations, respectively. Especially, for the NW station influenced by reservoir regulations, the frequency of slight drought and moderate drought of NSSI was 12.8% lower than and 13.1% greater than those of SSI, respectively. Overall, the NSSI that incorporates the influence of climate variability and reservoir regulations provided more reliable assessment of hydrological drought than the traditional SSI.

Assessing the characteristics of recent drought events in South Korea using WRF-Hydro

Drought is a complex and slow-moving disaster that is difficult to monitor and define. This study, therefore, aims to demonstrate the characteristics of recent droughts occurring from 2008 to 2015 over South Korea using a process-based land and hydrologic model, Weather Research and Forecasting-Hydro modeling system (WRF-Hydro). To drive the standalone WRF-Hydro, gridded meteorological data (5 km) were generated using station-based observations and the Parameter-elevation Regressions on Independent Slopes Model (PRISM). The model was calibrated and evaluated using inflow observations at four locations with dams; for 2008–2010 (calibration) and 2011–2015 (evaluation), it demonstrated average R2 values of 0.80 and 0.75, respectively. While Standardized Precipitation Index is used for calculating meteorological drought using precipitation from PRISM, Standardized Soil Moisture Index and Standardized Streamflow Index, at different timescales, are used to calculate agricultural and hydrological droughts, respectively, with WRF-Hydro simulations. The correlation coefficients between SPI and both SSFI and SSMI were calculated to detect their response times. The hydrological and agricultural droughts showed response times 0.5–1 month later than meteorological drought. In 2008–2015, agricultural and hydrological drought events occurred 1.6 times per year on average in South Korea, whereas meteorological droughts occurred 4.3 times per year on average. Agricultural and hydrological droughts lagged behind meteorological droughts by up to 53, 65, and 83 days, when using 1-, 3-, and 6-month SPI, respectively. Moreover, hydrological droughts were less severe than meteorological droughts due to the propagation of drought by attenuation. This study demonstrates that WRF-Hydro can be used to quantitatively determine the different types of drought events and their propagation, which could help policy makers manage drought risks.