Palmer Index Research Articles

Characterization of Spatiotemporal Variations in Mert Stream Water Quality by Phytoplankton Community and Biological Indices

In order to determine the water quality of the Mert Stream, algal indicators and some biological indices (TDI, IDG, PTI, Palmer, DAIpo) based on phytoplankton species were used. Phytoplankton samples were performed monthly from six different sites at a depth of 0.5 meter using a one-litre water sampler between July 2011 and June 2012. After phytoplankton samples were placed in 250-mL dark bottles and fixed with Lugol’s solution until processed in the laboratory, they were identified and counted in the tubular plankton counting chambers using an inverted microscope according to Utermöhl method. Bacillariophyta members became the dominant division in the phytoplankton with an abundance rate of 83.3% and 71 taxa. Lindavia glomerata, Navicula cryptocephala, Cyclotella planctonica, and Navicula veneta were determined as the most dominant species among phytoplanktonic taxa of Mert Stream. Trophic diatom index (TDI) and Generic diatom index (IDG) based on planktonic diatoms were used to determine the trophic status of the Mert Stream. Pollution tolerance index (PTI), Diatom assemblage index (DAIPo) and Palmer index were also included to assess the organic load-based sabrobity level of the Mert Stream. According to the results of mean TDI and IDG (55 and 13, respectively), the trophic status of the Mert Stream is a mesotrophic structure with moderate nutrients and good water transparency. According to the average PTI result (2.7), Mert Stream is in the β-mesosaprobic class, which corresponds to moderate pollution. Considering DAIpo indice, the saprobity of Mert stream is α-oligosaprobic level and the stream is not exposed to a serious organic-based pollution. However, according to the Palmer index, all stations of the Mert Stream except the 6th station are under the threat of high organic pollution. In present study, it was seen that the best biological index that reflects the station-based trophic structure of the stream is IDG, and the best biological index that reflects the station-based organic pollution of the stream is PTI.

Evaluating ERA‐Interim, Agri4Cast, and E‐OBS gridded products in reproducing spatiotemporal characteristics of precipitation and drought over a data poor region: The Case of Greece

AbstractGridded climate datasets are among the most used datasets in the study of weather and climate. Given the large range of such products currently available, investigators must consider their strengths and weaknesses. This research evaluated the comparative performance of two reanalysis datasets (ERA‐Interim, and Agri4Cast [e.g. MARS‐STAT]) and one reprocessing dataset (E‐OBS) in replicating selected spatiotemporal characteristics of precipitation and drought at 20 wine production regions in Greece during 1981–2012. The results highlighted the abilities of E‐OBS and Agri4Cast, whose performance varied with season and the specific rainfall characteristic in question. The former product: (1) reproduced better the annual decreasing trends in spring, summer, and autumn, (2) captured a larger portion of the observed monthly variability in spring and summer, associated better and showed the lowest errors with observations, and (3) computed better or equal to Agri4Cast different skill scores applied on the daily time series, replicated better the probabilities of wet and dry days and equally well with Agri4Cast the extreme precipitation indices. Agri4Cast replicated better the monthly cycle of precipitation (underestimating though the station averages) and the increasing trend from SE to NW, on spatial basis. With regards to drought monitoring, frequency and detection of very and extremely wet and dry spells, SPI was superior to SC‐PDSI (the self‐calibrated version of Palmer's index), particularly when E‐OBS data was used. Agri4Cast and E‐OBS are the most appropriate products for use in climate/atmospheric‐related research over Greece.

Estimation and easy calculation of the Palmer Drought Severity Index from the meteorological data by using the advanced machine learning algorithms.

Drought, which has become one of the most severe environmental problems worldwide, has serious impacts on ecological, economic, and socially sustainable development. The drought monitoring process is essential in the management of drought risks, and drought index calculation is critical in the tracking of drought. The Palmer Drought Severity Index is one of the most widely used methods in drought calculation. The drought calculation according to Palmer is a time-consuming process. Such a troublesome can be made easier using advanced machine learning algorithms. Therefore, in this study, the advanced machine learning algorithms (LR, ANN, SVM, and DT) were employed to calculate and estimate the Palmer drought Z-index values from the meteorological data. Palmer Z-index values, which will be used as training data in the classification process, were obtained through a special-purpose software adopting the classical procedure. This special-purpose software was developed within the scope of the study. According to the classification results, the best R-value (0.98) was obtained in the ANN method. The correlation coefficient was 0.98, Mean Squared Error was 0.40, and Root Mean Squared Error was 0.56 in this success. Consequently, the findings showed that drought calculation and prediction according to the Palmer Index could be successfully carried out with advanced machine learning algorithms. Graphical Abstract.

Ecological diversity of species and its measurement in lentic ecosystem in Mysuru

The paper attempts to give an account of fresh water algae as an indicator of water quality. Eight lakes of Mysore have been studied. The Palmers Index IDSELS Diatom index and OMNIDA software, were used for calculated and analysed. The order of tolerance to organic pollution was calculated using the Garrett ranking techniques .According to Palmer index all the eight lakes were organically polluted. Bogadi lake was least polluted and Karanji lakes and mandakahalli lake were polluted. The present investigation compares the use of old and new techniques of detecting the water quality. It also enables us to understand whether the algae is imparting organic pollution of lake water. The species index indicated that Bogadi lake, Hadinarru lake, Karanji lake & Bilikere lake had low organic pollution. The diatom index showed that all lakes ranged between moderate and high organic pollution but the degradation levels in the water was also high. Dalvoi lake and Mandakahalli lake had the highest organic pollution. Species of Euglena and Scenedesmus were the most tolerant species found in organic polluted lakes. Algae were found to be highly resistant in Karanji lake, Dalvoi lake, Kukkarahalli lake and bilekere lake. These sites were found to be conducible for the growth of algae, while most of the other lakes had idiosynthcratic species. This study uses the advanced modern tools in determining levels of organic pollution in lake ecosystem.

Comparison of three different bio-inspired algorithms to improve ability of neuro fuzzy approach in prediction of agricultural drought, based on three different indexes

Monitoring agricultural drought utilizing the least variables can be useful at the areas with just rain gauge stations, especially in Iran, which is located in arid belt of the world. In this study, all of the stations having long duration data in Iran (31 stations with more than 59 years’ data), have been used to calculate three drought indices: (1) Palmer Drought Severity Index (PDSI); (2) Standardized Precipitation Index (SPI); (3) Multivariate Standardized Precipitation Index (MSPI). According to the recommendation of world meteorological organization (WMO), Palmer index has been defined as the reference index and SPI9 (9-month time window of SPI), SPI10, SPI11 & SPI12, and also MSPI9–12 (9–12 months’ time window), was evaluated by Palmer index. The results showed significant relation between SPI11 or SPI12 and PDSI in Iran’s climates. MSPI9–12 has a significant relation with PDSI too, and the correlation of MSPI with Palmer Index was found to be stronger than the SPI, in all stations. The relation between MSPI and PDSI is also stronger in extra-arid climates, and weaker in humid and per-humid areas. So, MSPI can be used for agricultural drought monitoring in the places where there are restrictions in meteorological dataset (when precipitation data are only available). In the second part, prediction of MSPI9–12 has been done using Adaptive Neuro-Fuzzy Inference System (ANFIS) merged with bio-inspired optimization algorithms. The meta-heuristic models implemented are ANFIS-ACO (ANFIS merged with Ant Colony Optimization), ANFIS-GA (ANFIS merged with Genetic Algorithm) and ANFIS-PSO (ANFIS merged with Particle Swarm Optimization). The models had their best predictions in arid, semi-arid and Mediterranean climates while humid climate provided the weakest predictions. Among the mentioned algorithms, the ACO and GA had the best performances to optimize ANFIS; they improved the ANFIS’s accuracy by 45.9% and 43.2%, respectively.

Drought dynamics in the East European Plain for the period 1980-2018

Drought is one of the most dangerous natural hazards that has a huge impact on the economy and population in the world and in Russia as well. A large number of studies speak of an increase in the number of droughts and low flow conditions, including Russia. In this work, an analysis was made of the conditions for droughts in the East European Plain over the past 38 years based on the data from the ERA-5 reanalysis. The atmospheric precipitation, air temperature over the seasons and the Palmer index (as a general indicator) for the study area were analyzed. Much attention was paid to the characteristics of the winter period, since the supposedly mild winters create favorable conditions for the formation of droughts in the summer period. It was found that the main factors affecting the drought formation of 2007-2018 was the lack of summer rainfall, and the remaining factors played a “preparatory” role in the process of the formation of large-scale drought.

Evaluation of Seasonal Changes in Temperature and Precipitation for Iran Five Provincial Centres during 1960-2017

Climate change is one of the key challenges of our era and it is a threat to sustainable development. Global warming has many meteorological consequences including rising air temperatures across the world. Undoubtedly, human activity has been one of the key factors to global warming followed by increased greenhouse gas emissions which will exacerbate changes in the Earth’s climate variables. So, any research work related to the climate around the world including Iran due to climate change may cause to better understand the cause and effect and make a better adaptation. This study investigates the regional warming in five meteorological stations in central provinces of Iran, based on seasonal changes in precipitation and temperatures over the period of 1960-2017 (study period). The seasonal drought severity based on Palmer index during 1960-2005 was used to monitor the drought intensity in the study areas which are in drought risk situation. The classification of drought severity using Palmer index shows the severe drought intensity in Arak, Qom, Semnan, Tehran and Isfahan respectively in all four seasons, especially during fall and summer. The slight changes in the coefficients of seasonal maximum, minimum and mean temperatures have been resulted. According to these results, the highest maximum (minimum) temperature rise has been calculated for Qom (Tehran) station during spring and winter (fall) seasons ~0.44°C (~0.67°C) in a decade during 1960-2017. However, the highest decrease in precipitation over Arak station has been calculated ~13.8 mm in a decade in winter during study period.

ASSOCIATION BETWEEN THE PRESENCE OF LACTOBACILLUS IN SALIVA AND DENTAL CARIES IN CHILDREN WITH PERMANENT DENTITION

Despite the scientific and technological evolution, dental caries is still one of the leading health concerns throughout the world that affects population groups from all ages, especially school children. There are numerous etiological factors for dental caries, from which most are confirmed etiological factors, but still many remain to be researched to their full extend. The purpose of this paper is to investigate whether there is a significant inverse association between the intensity of dental caries and the bacterial strains of Lactobacillus. Lactobacilli were the first microorganisms to be linked and mentioned as causes of dental caries. Numerous authors have suggested that the number of lactobacilli in saliva is a better criterion than that of Streptococcus mutans, although it is considered to be closely correlated with caries. The randomly selected children from the primary schools in the city of Stip were observed for the realization of the goals. In our examination we included 71 examiners from both genders at the age of 12 years (permanent dentition) of which 31 examiners were with DMFT = 0 (control group) and 40 examiners were with DMFT (study group). We selected an age group of 12 years following WHO recommendations that recommends that age for global dental caries monitoring and applies only to children with permanent dentition. In the study we used the generally accepted index of the presence or absence of a Klein - Palmer index caries process, designated as DMFT. According to the clinical trial data, we determined the intensity (presence / absence) of dental caries (WHO, Geneve, 1997). Lactobacilli in saliva were determined by diagnostic test CRT-bacteria (Vivadent, Schaan, Lihtenstein).Between the existence of Lactobacillus in the saliva and the existence of dental caries there is a significant correlation (p<0,01). The parameters which we included in the study can give a scientific contribution in the preparation of strategies for the individual assessment of the dental caries risk, from which the dentists can act on solving the problem with actions focused on the individual risk factors responsible for dental caries, while using methods which include assessment of the clinical criteria in the detection of the early phases of evolution of dental caries and designing protocols that can be used in dental caries preventive and interceptive measures based on the dental caries status which implies educative, chemical and minimally invasive procedures. We can conclude that most of the salivary parameters can be successfully used for caries screening and that they are the most appropriate means of providing good oral care that feeds thechildren to healty life.

A case study of phytoplankton used as a biological index for water quality assessment of Nhu Y river, Thua Thien - Hue

Studies of the composition and density of phytoplankton and the water quality of Nhu Y river were conducted over six months (March to August 2011). Phytoplankton samples were collected by filtration and immediately preserved in Lugol’s solution. The phytoplankton species composition recorded 117 species belonging to six divisions: Cyanobacteria (24 taxa), Bacillariophyta (14 taxa), Chlorophyta (45 taxa), Euglenophyta (31 taxa), Cryptophyta (2 taxa), and Dinophyta (1 taxa), of which Chlorophyta and Euglenophyta were dominant in terms of species numbers. The total phytoplankton density fluctuated from 110,146 to 5,964x103individuals/litre and Cyanophyta were dominant in terms of individual density. The algal genus pollution index (Palmer index) ranged from 30 to 41, indicating that the water was highly organically polluted, and the Shannon-Weiner index results of 0.66-2.92 showed moderately to heavily polluted water. With values for the Diatomeae index of more than 0.2, the quality of the eight sites during the period of the study showed that the aquatic environment was eutrophic. Phytoplankton and their indexes are useful tools for assessing water environment quality.

The economic cost of extreme and severe droughts in soybean production in Argentina

The objective of this study is to estimate the economic cost of droughts on soybean production in Argentina. By means of a linear model, extreme negative deviations in soybean yields during 1970-2016 are identified. It was found that in all cases extreme deviations in yields are related to severe and extreme droughts according to the palmer index. Constructing a counterfactual scenario and by means of the international soybean price, the economic loss is valued. It was found that in the aggregated sample the income loss due to drought events was of $8.046 million in dollars of 2016, equivalent to 22% of Argentinean international reserves of that year.

TRANSFORMING THE PALMER DROUGHT SEVERITY INDEX INTO A STANDARDIZED MULTI-SCALAR INDEX: ASSESSING THE NORMALITY ASSUMPTION UNDER SOUTH AMERICA TROPICAL-SUBTROPICAL CONDITIONS

SUMMARYTwo of the most common criticisms over the widely used Palmer Drought Severity Index (PDSI) is that it cannot be calculated at different time scales and it is not as spatially comparable as other Standardized Drought Indices (SDI), such as the Standardized Precipitation Index (SPI). Therefore, the hypothesis that the PDSI may be transformed into a multi-scalar index sharing the same normalized nature of others SDI has been proposed in the scientific literature. This hypothesis was extensively evaluated in this study by statistical methods largely used to assess and improve the performance of others standardized drought indices (e.g. SPI). In general terms, these methods evaluated the ability of the transformed/probability-based Palmer's Index to approach the standard normal distribution. The strategy of basing the selection of a distribution for calculating such an index on its performance within the range of typical drought and flood events was adopted. The testing region was the State of São Paulo, a tropical-subtropical region of Brazil. Time scales ranging from 1- to 12-month and Available Water Capacity equal to 50, 100 and 150 mm were also considered. A computational algorithm for calculating the new version of the Palmer's index is also provided. The Generalized Logistic distribution with parameters estimated by the maximum likelihood method is recommended to calculate the new index. The results of the normality tests are consistent with the above-mentioned strategy. From a scientific standpoint, the results support the hypothesis of this study. Therefore, we conclude that the new Standardized Palmer Drought Index (SPDI) is capable of meeting the normally assumption under tropical-subtropical climatic conditions of Brazil. In other words, the new SPDI has shown to be capable of representing floods and drought events in a similar probabilistic/normalized way. This conclusion holds true for time scales ranging from 1- to 12-month and Available Water Capacity equal to 50, 100 and 150 mm.

Ecological Assessment of the River Nile Status around Gizert El-Warrak using Phytoplankton and Macroinvertebrates Assemblages

Biological assessment is considered a useful tool for assessing the ecological status of the aquatic ecosystems. Therefore, the goal of the present study was to use phytoplankton and macroinvertebrates as biological tools for ecological assessment of the River Nile around Gizert El-Warrak. A total of 33 phytoplankton species identified in the studied stations; these include 16 species of Chlorophyta, 5 species of Cyanophyta and 12 species of Bacillariophyta. All investigated stations characterized by high organic pollution according to Palmer's index. Trophic state index showed a hyper-eutrophic status in stations S1, S2, S4, S6 and S8 and an eutrophic status in stations S3, S5 and S7. Gastropoda and Oligochaeta were the most dominant of macroinvertebrates taxa recorded 50.8 and 24.6%, respectively.

Spatio-temporal evaluation of the surface water quality in the middle Nile Delta using Palmer’s algal pollution index

This work aims to evaluate the spatio-temporal change in the surface water pollution in the middle Nile Delta using algal pollution index (Palmer Index). Water was sampled during winter and summer seasons from 18 stations distributed along the water pathways from south to north for two main irrigation canals (Qudaba and Mit-yazed canals) and two drains (El-Gharbia main drain and Janag drain). An algal analysis was carried out based on the species and genera that mentioned in Palmer Index (PI). High Palmer Index scores were noticed in most of the stations especially during summer, which might be related to various pollution supplies. Limited number of stations showed low palmer index scores indicating relatively clean water. In winter, the two irrigation canals showed similar spatial distribution patterns where PI values increased reaching its maximum at the middle of water pathways and then decreased. In summer, PI had no definite trend in Qudaba canal and decreasing trend in Mit-yazed canals along the water pathway to the northern direction. PI of El-Gharbia main drain showed increasing and decreasing trends in winter and summer, respectively. Janag drain had opposite patterns compared to that of El-Gharbia main.One of the major differences between irrigation canals and drainage water was the algal community structure where the drainage water was characterized by the abundance of Euglenophyta and Chlamydomonas spp. and rare occurrences of Bacillariophyta except the last station of El-Gharbia main drain, which was of estuary nature.

Phytoplankton as Pollution Indicator using Palmer Index of Chulband River, Gondia District. (MS), INDIA.

Phytoplankton as Pollution Indicator using Palmer Index of Chulband River, Gondia District. (MS), INDIA.

Environmental assessment of drainage water impacts on water quality and eutrophication level of Lake Idku, Egypt

Lake Idku, northern Egypt, receives large quantities of drainage water from four main discharging drains. Ecological and biological status of Lake Idku has been monitored during (autumn 2012 to summer 2013) to examine the lake water quality and eutrophication level in response to the quality as well as the source of the discharging water. Discrete water samples were collected from the lake body and the drains. Chemical analyses revealed an excessive nutrient load goes into the lake. A range of 1.4–10.6 mg nitrites/L was determined for drain waters, however a sudden increase was observed in lake and drain water samples of up to 84 and 74.5 mg/L, respectively. Reactive silicate ranged between 2.9 and 4.8 mg/L; while inorganic phosphate fluctuated between 0.2 and 0.43 mg/L. Transparency varied from 45 cm to 134 cm with better light conditions at drain sites. Biological results indicated a hyper-eutrophic status for the lake with a range of chlorophyll-a varied from a minimum of 39.9 μg/L (at Idku Drains) and a maximum of 104.2 μg/L (at El-Khairy drain). Phytoplankton community structure revealed higher abundance at lake sites compared with the drains. Maximum phytoplankton density was detected during summer with the dominance of Bacilariophyceae (e.g. Cyclotella meneghiniana, Cyclotella comate, Melosira varians) followed by Chlorophycean taxon (e.g. Scenedesmus dimorphus, S. bijuga and Crucigenia tetrapedia). Five indices were applied to evaluate the water quality of the lake. Diversity Index (DI) indicated slight to light pollution along all sites; while Sapropic Index (SI) indicated slight pollution with acceptable oxygen conditions and an availability of sensitive species. Palmer Index (PI) gave a strong evidence of high organic pollution at some sites in the lake, while Generic Diatom Index (GDI) revealed that levels of pollution varied from average to strong. Trophic Index (TI), suggest that there are an obvious signs of eutrophication in the lake.

Discharge variability in Romania using Palmer indices and a simple atmospheric index of large-scale circulation

ABSTRACTThe aim of this study is to analyse the seasonal characteristics of four Palmer indices calculated on the basis of data from 27 meteorological stations in Romania, and the impact of these indices on river discharges in the period 1931–1998. Our research also tests the influence of large-scale atmospheric circulation on these indices and on discharge. For each season, developments in the empirical orthogonal functions (EOF) and multivariate EOF (MEOF) are achieved. The MEOF representation highlights the overall characteristics of the four Palmer indices. It maximizes specific information for each season compared with individual information of each Palmer index. We then identify geographical areas with homogeneous distribution, taking into account both the discharge distribution and the rotated EOF components of each Palmer index. Finally, we analysed the impact of large-scale atmospheric circulation on hydro-climatic events in Romania by means of the Greenland-Balkan Oscillation Index (GBOI), which is shown to have a greater influence on southeastern Europe than the North Atlantic Oscillation Index (NAOI).

Variability and Trends in Precipitation, Temperature and Drought Indices in the State of California

This study presents a comprehensive assessment of the variability and trends of the precipitation and temperature along with the trends in drought indices over the State of California. The non-parametric Mann–Kendall trend test is applied with a trend-free pre-whitening procedure in trend identification. A dataset containing 120-year (water years 1896–2015) monthly precipitation, average temperature, maximum temperature, minimum temperature and the Palmer Index for seven climatic regions of the state is used for this purpose. The results confirm previous work indicating that no clear trends are observed in precipitation, while a distinct warming trend is evident in temperature over the state. New findings of this study include: (1) in general, the variability of annual, winter (December–February) and spring (March–May) precipitation shows an increasing tendency, implying intensified frequency of the occurrence of dry or wet extremes; (2) on the annual scale and in the summer, statewide meteorological, hydrological and agricultural drought indices all have decreasing trends, indicating the more frequent occurrence of drought events; and (3) among seven regions, the South Coast Drainage region generally has the most significant warming trend, as well as the most significant declining trends in drought indices. Overall, these findings are highly meaningful from both theoretical and practical perspectives, in the context of providing critical information in developing prediction models and guiding water resources management practices, respectively.

Evaluation of Palmer Drought Severity Index in Central Iran

The Palmer Drought Severity Index (PDSI), which uses hydrometeorological variables to solve a simple water balance equation in the soil and considers the drought or wet conditions as dynamic phenomena, is used for the assessment of drought conditions in many parts of the world. The main goal of this study was to assess the PDSI based on its original assumptions, its regionalized status, using the outputs of already calibrated and validated SWAT model in central regions of Iran. The PDSI was assessed through five methods: 1) original Palmer Index without calibration in which the climate coefficients and the severity equation were derived for Kansas and central Iowa; 2) original Palmer Index in which the coefficients of severity equations were adjusted; 3) the Palmer Index with the calibration of equations in central areas of Iran; 4) the Palmer Index using the soil moisture and potential evapotranspiration from SWAT model; and 5) the Palmer Index using the soil moisture, potential evapotranspiration and runoff from SWAT model. The evaluation was conducted for 17 major basins covering the entire country with a monthly time step for the period 19902002. Then, using all five methods, the severity of the drought for 160 sub basins located in central Iran was calculated and evaluated. The results of this study indicated that method 4 provides more acceptable results. Also, the results of this research showed these methods clearly demonstrated (1992) as the wettest year and (2001) as the driest year. The approach used in this study is applicable to regional calibration of Palmer Index and the outputs of other hydrological models.

Changes in precipitation pattern and risk of drought over India in the context of global warming

Precipitation pattern has changed over many regions in recent decades. There are evidences of increased heavy precipitation and decreased light precipitation in widespread parts of the globe due to global warming. Many studies over Indian region focus on heavy precipitation and risk of floods. But few works discuss the changes in light precipitation and risk of droughts. In this study, changes in total dry days, prolonged dry spells, light precipitation, and risk of drought as indicated by Modified Palmer Index (MPI) over India during six decades (1951–2010) are examined quantitatively in the context of global warming. It is found that there are increases of 49% ± 21% and 33% ± 17% in prolonged dry spells and total dry days, respectively, over India for each degree Kelvin (K) increase in global mean temperature. There is an increase of 51% ± 24% K−1 in drought index MPI (<= − 2.0). There is also a reduction of 31 ± 14% K−1in light precipitation days over India. These changes are more severe over northeastern and western part of India. Increases in prolonged dry spells, total dry days, and decreases in light precipitation relate well with the increases in drought index MPI (<= − 2.0). These results suggest that there is an increased risk of drought due to increased prolonged dry spells, total dry days, and decreased light precipitation days over India as a result of global warming.

Exploring the link between meteorological drought and streamflow: Effects of climate‐catchment interaction

AbstractIn this paper, we perform a detailed regional analysis of the link between meteorological drought indices and streamflow for a comprehensive Austrian data set of 47 small to medium‐size catchments in humid‐temperate climate. Four drought indices considering different components of the catchment water balance are tested. We assess the quality of the link using rank correlation analysis, and the probability of detecting low‐flow events by hit‐scores. Overall, correlations range between 0.4 and 0.8 and differ significantly between regions. A stratified analysis shows that the link is much stronger (i) for summer low flows and droughts than for anomalies in general, and (ii) for more humid than more arid conditions. Under more humid conditions streamflow droughts of small to medium‐size catchments are to a large extent generated by climate forcing and therefore well represented by a simple meteorological index. Under increasingly dry conditions, the climate signal gets less predictive, and storage properties of the underground become more important. A simple soil moisture accounting scheme (such as those of the Palmer index) can considerably improve the correlations. Overall, we conclude there is a significant link between meteorological drought and streamflow drought, except for catchments where groundwater storage and snow processes are important. The results are encouraging and provide a wealth of information which can profitably be used to set up statistical prediction models to estimate low flows from meteorological time series.