Australian rainfall trends and their relation to the southern oscillation index

Rainfall is the key climate variable that governs the spatial and temporal availability of water. In this study we identified monthly rainfall trends and their relation to the southern oscillation index (SOI) at ten rainfall stations across Australia covering all state capital cities. The nonparametric Mann–Kendall (MK) test was used for identifying significant trends. The trend free pre‐whitening approach (TFPW) was used to remove the effects of serial correlation in the dataset. The trend beginning year was approximated using the cumulative summation (CUSUM) technique and the influence of the SOI was identified using graphical representations of the wavelet power spectrum (WPS). Decreasing trends of rainfall depth were observed at two stations, namely Perth airport for June and July rainfall starting in the 1970s and Sydney Observatory Hill for July rainfall starting in the 1930s. No significant trends were found in the Melbourne, Alice Springs and Townsville rainfall data. The remaining five stations showed increasing trends of monthly rainfall depth. The SOI was found to explain the increasing trends for the Adelaide (June) and Cairns (April) rainfall data and the decreasing trends for Sydney (July) rainfall. Other possible climatic factors affecting Australian rainfall are also discussed. Copyright © 2009 John Wiley & Sons, Ltd.     

Trend assessment of annual instantaneous maximum flows in Turkey

A comprehensive evaluation of trends in annual instantaneous maximum flows (AIMF) from 153 gauge stations located in 26 river basins in Turkey is presented. Two traditional non-parametric trend tests, the Mann-Kendall (MK) and Spearman’s rho (SR), are used to quantify the significance of trends, while Sen’s slope method is applied to determine the magnitude of trends. The traditional tests indicate that the AIMF records of 57 stations showed statistically decreasing trends, while those of six stations showed an increasing trend. Sen’s trend method, which provides more detailed assessment of the trends in different clusters (low, medium and high), was applied to the AIMF series and the results were compared with traditional tests. Sen’s trend method indicated that all flow clusters at nine stations have increasing or decreasing trends, although no significant trend was detected by the MK and SR tests.     

Effect of autocorrelation on temporal trends in rainfall in a valley region at the foothills of Indian Himalayas

This study examines the effect of autocorrelation on step and monotonic trends in seasonal and annual rainfall. Initially, for step change, modified-Pettitt test is applied in two ways. First, using the corrected and unbiased trend-free-pre-whitening (TFPWcu) approach. Second, using a new approach in which time series is modelled by intervention analysis for modified Pettitt test. Subsequently, for monotonic trends, Mann–Kendall (MK) and six approaches of modified Mann–Kendall (MMK) test are applied to NCDC data for period 1901–2012 and its sub-periods. Approaches of MMK include pre-whitening (PW), trend-free-pre-whitening (TFPW), TFPWcu, two Variance Correction Approaches (VCAs) based on empirical formula (VCA:CF1) and Monte-Carlo-Simulations (VCA:CF2) and long term persistence (MK-LTP). A single change point is identified in 1970 for annual and monsoon rainfall from original and modified-Pettitt’s test using TFPWcu, while time series modelling approach has not exhibited any change point. Process shift in rainfall series is also studied using CUSUM and multiple change points are identified using Segment-Neighbourhood method. Outcomes of MMK show that TFPWcu is able to efficiently limit the effect of autocorrelation and may be preferred over PW and TFPW. The VCA:CF2 is not dependent on whole autocorrelation structure and corrects variance of all data series using lag-1 autocorrelation and may be preferred over VCA:CF1. MK-LTP considers long term persistence and it has exhibited presence of weaker trends than exhibited by other approaches. VCA:CF2 and MK-LTP are used to study trends of rainfall in Dehradun.     

Analysis of the rainfall variability and change in the Republic of Benin (West Africa)

ABSTRACT

The temporal variation and trends of annual rainfall distribution in Benin were examined using data from 1940 to 2015 at six meteorological stations and three raingauges stationed throughout the country. The nonparametric modified Mann-Kendal (MK) and Levene tests were applied to detect trends and heteroscedasticity, respectively. For six of the time series, no significant trends were detected. A Bayesian multiple change points detection approach was applied to the rainfall time series, and most (six of nine) exhibited abrupt change points, corresponding to the alternation between wet (before 1968 and after 1990) and dry (1969–1990) periods. No significant trends or breakpoints and changes in the variance were observed for the spatial average rainfall time series. Seven modified MK trend tests were applied; the trends are affected by the selected MK method and rainfall statistics. Oceanic and/or atmospheric influences on the rainfall in Benin were examined by investigating the correlation between the precipitation time series and several indices. Negative seasonal correlations were determined for the North Atlantic Oscillation, Pacific Decadal Oscillation and Niño3, while positive seasonal correlations were observed for the Southern Oscillation, Antarctic Oscillation and Dipole Mode Index.     

Analysis of long-term rainfall trends in India

Abstract

The study of precipitation trends is critically important for a country like India whose food security and economy are dependent on the timely availability of water. In this work, monthly, seasonal and annual trends of rainfall have been studied using monthly data series of 135 years (1871–2005) for 30 sub-divisions (sub-regions) in India. Half of the sub-divisions showed an increasing trend in annual rainfall, but for only three (Haryana, Punjab and Coastal Karnataka), this trend was statistically significant. Similarly, only one sub-division (Chattisgarh) indicated a significant decreasing trend out of the 15 sub-divisions showing decreasing trend in annual rainfall. In India, the monsoon months of June to September account for more than 80% of the annual rainfall. During June and July, the number of sub-divisions showing increasing rainfall is almost equal to those showing decreasing rainfall. In August, the number of sub-divisions showing an increasing trend exceeds those showing a decreasing trend, whereas in September, the situation is the opposite. The majority of sub-divisions showed very little change in rainfall in non-monsoon months. The five main regions of India showed no significant trend in annual, seasonal and monthly rainfall in most of the months. For the whole of India, no significant trend was detected for annual, seasonal, or monthly rainfall. Annual and monsoon rainfall decreased, while pre-monsoon, post-monsoon and winter rainfall increased at the national scale. Rainfall in June, July and September decreased, whereas in August it increased, at the national scale.

Citation Kumar, V., Jain, S. K. & Singh, Y. (2010) Analysis of long-term rainfall trends in India. Hydrol. Sci. J. 55(4), 484–496.     

Inconsistent linear trends in Senegalese rainfall indices from 1950 to 2007

Abstract

Daily precipitation data from 31 Senegalese stations spanning the period from 1950 to 2007 were used to examine the inter-annual variations of seven rainfall indices: the annual mean precipitation (MEAN); the annual standard deviation of daily precipitation (STD); the frequency of wet days (Prcp1); the maximum number of consecutive dry days (CDD); the maximum 3-day rainfall total (R3D); the wet day precipitation intensity (SDII); and the 90th percentile of rain-day precipitation (Prec90p). The indices were spatially averaged over three agro-climatic regions in Senegal. Trends in the time series of the averaged indices were assessed using both visual examination and a modified version of the Mann-Kendall (MM-K) test. Initially negative significant trends in all seven indices suggest gradually drier conditions over the three agro-climatic regions between 1950 and 1980. In contrast, no significant trends, or even positive significant trends, were observed from the mid-1980s to 2007. The MM-K test was applied to all available data (1950–2007) and the period from 1971 to 2000. While several indices were found to have significant trends towards drier conditions for the 1950–2007 period, only PRCP1 showed a positive significant trend for the 1971–2000 period. The MM-K test did not detect a significant trend for the other indices. It was found that the rainfall deficit and therefore drought is no longer intensifying, and that the region may even become wetter. However, the period covered by the observations is still too short to resolve the question of whether there is now a trend towards wetter conditions.

Editor Z.W. Kundzewicz; Associate editor K. Hamed     

Analysis of trends in reference evapotranspiration data in a humid climate

Abstract

Statistically significant FAO-56 Penman-Monteith (FAO-56 PM) and adjusted Hargreaves (AHARG) reference evapotranspiration (ET₀) trends at monthly, seasonal and annual time scales were analysed by using linear regression, Mann-Kendall and Spearman’s Rho tests at the 1 and 5% significance levels. Meteorological data were used from 12 meteorological stations in Serbia, which has a humid climate, for the period 1980–2010. Web-based software for conducting the trend analyses was developed. All of the trends significant at the 1 and 5% significance levels were increasing. The FAO-56 PM ET₀ trends were almost similar to the AHARG trends. On the seasonal time scale, for the majority of stations significant increasing trends occurred in summer, while no significant positive or negative trends were detected by the trend tests in autumn for the AHARG series. Moreover, 70% of the stations were characterized by significant increasing trends for both annual ET₀ series.

Editor Z.W. Kundzewicz; Associate editor S. Grimaldi

Citation Gocic, M. and Trajkovic, S., 2013. Analysis of trends in reference evapotranspiration data in a humid climate. Hydrological Sciences Journal, 59 (1), 165–180.     

Estimates of changes in design rainfall values for Canada

Annual maximum rainfall data from 51 stations in Canada were analyzed for trends and changes by using the Mann–Kendall trend test and a bootstrap resampling approach, respectively. Rainfall data were analyzed for nine durations ranging from 5 min to 24 h. The data analyzed are typically used in the development of intensity‐duration‐frequency (IDF) curves, which are used for estimating design rainfall values that form an input for the design of critical water infrastructure. The results reveal more increasing than decreasing trends and changes in the data with more increasing changes and larger changes, noted for the longer rainfall durations. The results also indicate that a traditional trend test may not be sufficient when the interest is in identifying changes in design rainfall quantiles. Copyright © 2012 John Wiley & Sons, Ltd.     

Trends in hydrological and climatic variables affected by four variations of the Mann-Kendall approach in Urmia Lake basin,Iran

ABSTRACT

The trends in hydrological and climatic time series data of Urmia Lake basin in Iran were examined using the four different versions of the Mann-Kendall (MK) approach: (i) the original MK test; (ii) the MK test considering the effect of lag-1 autocorrelation; (iii) the MK test considering the effect of all autocorrelation or sample size; and (iv) the MK test considering the Hurst coefficient. Identification of hydrological and climatic data trends was carried out at monthly and annual time scales for 25 temperature, 35 precipitation and 35 streamflow gauging stations selected from the Urmia Lake basin. Mann-Kendall and Pearson tests were also applied to explore the relationships between temperature, precipitation and streamflow trends. The results show statistically significant upward and downward trends in the annual and monthly hydrological and climatic variables. The upward trends in temperature, unlike streamflow, are much more pronounced than the downward trends, but for precipitation the behaviour of trend is different on monthly and annual time scales. Furthermore, the trend results were affected by the different approaches. Specifically, the number of stations showing trends in hydrological and climatic variables decreased significantly (up to 50%) when the fourth test was considered instead of the first and the absolute value of the Z statistic for most of the time series was reduced. The results of correlations between streamflow and climatic variables showed that the streamflow in Urmia Lake basin is more sensitive to changes in temperature than those of precipitation. The observed decreases in streamflow and increases in temperature in the Urmia Lake basin in recent decades may thus have serious implications for water resources management under the warming climate with the expected population growth and increased freshwater consumption in this region.

Editor Z. W. Kundzewicz; Associate editor Q. Zhang     

Spatial modelling of rainfall trends using satellite datasets and geographic information system

This study developed a standard methodology for identifying spatial trends using satellite-based raster datasets. It involves the novelty of exploring the capabilities of a geographic information system in implementing the procedures of three trend tests, the Spearman rank order correlation (SROC) test, the Kendall rank correlation (KRC) test and the Mann-Kendall (MK) test, on raster datasets of the Tropical Rainfall Measuring Mission at 0.25° × 0.25° resolution. Comparative evaluation of the three tests revealed fair agreement of a major part of the test results for pre-, post- and non-monsoon and one-day maximum rainfall. Also, similar results from KRC and MK tests were obtained over a considerable area for annual, monsoon and monthly maximum rainfall. These findings suggest the importance of selecting the appropriate test depending on rainfall magnitudes at the chosen time scale and emphasize the robustness of the KRC and MK tests.     

Entropy theory for analysing water resources in northeastern region of Brazil

Using the Shannon entropy, the space–time variability of rainfall and streamflow was assessed for daily rainfall and streamflow data for a 10-year period from 189 stations in the northeastern region of Brazil. Mean values of marginal entropy were computed for all observation stations and entropy maps were then constructed for delineating annual and seasonal characteristics of rainfall and streamflow. The Mann-Kendall test was used to evaluate the long-term trend in marginal entropy as well as relative entropy for two sample stations. The marginal entropy values of rainfall and streamflow were higher for locations and periods with the highest amounts of rainfall. The entropy values were higher where rainfall was higher. This was because the probability distributions of rainfall and the resulting streamflow were more uniform and less skewed. The Shannon entropy produced spatial patterns which led to a better understanding of rainfall and streamflow characteristics throughout the northeastern region of Brazil. The total relative entropy indicated that rainfall and streamflow carried the same information content at annual and rainy season time scales.     

Assessment of drought trend and variability in India using wavelet transform

ABSTRACT

This paper presents an analysis of trends in six drought variables at 566 stations across India over the period 1901–2002. Six drought variables were computed using standardized precipitation index (SPI). The Mann-Kendall (MK) trend test and Sen’s slope estimator were used for trend analysis of drought variables. Discrete wavelet transform (DWT) was used to identify the dominant periodic components in trends, whereas the significance of periodic components was examined using continuous wavelet transform (CWT) based global wavelet spectrum (GWS). Our results show an increasing trend in droughts in eastern, northeastern and extreme southern regions, and a decreasing trend in the northern and southern regions of the country. The periodic component influencing the trend was 2–4 years in south, 4–8 years in west, east and northeast, 8–64 years in central parts and 32–128 years in the north; however, most of the periodic components were not statistically significant.     

The nature of rainfall in the main drainage sub-basins of Uganda

Abstract

A study of rainfall trends and temporal variations within seven sub-basins of Uganda spanning from 1940 to 2009 has been made. Rainfall climatologies are constructed from observational data, using 36 station records which reflect hydroclimatic conditions. Long-term changes in rainfall characteristics were determined by non-parametric tests (Mann-Kendall and Sen’s T tests), coefficient of variation (CV), precipitation concentration index and drought severity index. Magnitude of change was estimated by applying Sen’s estimator of slope. Decadal variability of rainfall with marked seasonal cycles is evident. Temporal variability of drought patterns is detected. Variations in annual rainfall are low with no significant trends observed in the main drainage sub-basins. Significant trends occur in October, November, December and January. A noticeable decrease in the annual total rainfall was observed mostly in northwestern and southwestern sub-basins. Rainfall trend in the second normal of June–July–August (JJA) was decreasing in all the main drainage sub-basins.

Editor Z.W. Kundzewicz; Associate editor S. Yue

Citation Nsubuga, F.W.N., Botai, O.J., Olwoch, J.M., Rautenbach, C.J.deW., Bevis, Y., and Adetunji, A.O., 2014. The nature of rainfall in the main drainage sub-basins of Uganda. Hydrological Sciences Journal, 59 (2), 278–299.     

Multi-decadal variations in annual maximum peak flows in semi-arid and temperate regions of Chile

Abstract

In determining the possible influence of climate change, it is important to understand the temporal and spatial variability in streamflow response for diverse climate zones. Thus, the aim of this study was to determine the presence of changes in annual maximum peak flow for two climate zones in Chile over the past few decades. A general analysis, a flood frequency analysis and a trend analysis were used to study such changes between 1975 and 2008 for a semi-arid (29°S–32°S) and a temperate (36°S–38°S) climatic zone. The historic annual maxima, minima and mean flows, as well as decadal mean peak flow, were compared over the period of record. The Gumbel distribution was selected to compare the 30-year flood values of two ±15-year intervals, which showed that streamflow decreased by an average of 19.5% in the semi-arid stations and increased by an average of 22.6% in the temperate stations. The Mann-Kendall test was used to investigate the temporal changes in streamflows, with negative trends being observed in 87% of the stations analysed in the semi-arid zone, and positive trends in 57% of those analysed in the temperate zone. These differences in streamflow response between climate zones could be related to recent documented increases in altitude of the zero-degree isotherm in the Andes Mountains of Chile, since most of the significant positive and negative changes were detected in first-order rivers located closer to this mountain range.

Editor D. Koutsoyiannis; Associate editor H. Lins

Citation Pizarro, R., Vera, M., Valdés, R., Helwig, B., and Olivares, C., 2013. Multi-decadal variations in annual maximum peak flows in semi-arid and temperate regions of Chile. Hydrological Sciences Journal, 59 (2), 300–311.     

Characteristics of intense rainfall over Gujarat State (India) based on percentile criteria

The study focuses on the spatial and temporal variations of intense/extreme rainfall events over Gujarat State (India) during the period 1970–2014. Average monsoon rainfall for the state shows a significant increasing trend, with an increase of 48 mm/decade. Some of the stations in the Saurashtra region show a statistically significant increasing trend but none of the stations in the state show a decreasing trend. The increasing trend in monsoon rainfall is very significant for the past three decades, with an increase of 167 mm/decade. Instead of fixed absolute threshold values, relative threshold values of rainfall corresponding to the 95th, 98th, 99th and 99.5th percentiles for each station have been proposed to represent heavy, very heavy, intense and extreme rainfall, which varied between 70–120, 105–160, 130–210 and 165–280 mm, respectively. Significant increasing trends are observed for the frequency of heavy and very heavy rainfall events over the state.     

Climate-driven trends in mean and high flows from a network of reference stations in Ireland

Abstract

This paper introduces a reference hydrometric network for Ireland and examines the derived flow archive for evidence of climate-driven trends in mean and high river flows. The Mann-Kendall and Theil-Sen tests are applied to eight hydroclimatic indicators for fixed and variable (start and end date) records. Spatial coherence and similarities of trends with rainfall suggest they are climate driven; however, large temporal variability makes it difficult to discern widely-expected anthropogenic climate change signals at this point in time. Trends in summer mean flows and recent winter means are at odds with those expected for anthropogenic climate change. High-flow indicators show strong and persistent positive trends, are less affected by variability and may provide earlier climate change signals than mean flows. The results highlight the caution required in using fixed periods of record for trend analysis, recognizing the trade-off between record length, network density and geographic coverage.

Editor Z.W. Kundzewicz; Associate editor H. Lins

Citation Murphy, C., Harrigan, S., Hall, J., and Wilby, R.L., 2013. Climate-driven trends in mean and high flows from a network of reference stations in Ireland. Hydrological Sciences Journal, 58 (4), 755–772.     

Rainfall trend and its implications for water resource management within the Yarra River catchment,Australia

Rainfall is the key climatic variable that governs the regional hydrologic cycle and availability of water resources. Recent studies have analysed the changes in rainfall patterns at global as well as regional scales in Australia. Recent studies have also suggested that any analysis of hydroclimatic variables should be performed at the local scale rather than at a large or global scale because the trends and their effects may be different from one location to the other. Because no studies were found specific to the Yarra River catchment, which is an important catchment in Victoria, Australia, this study performs a spatiotemporal trend analysis on long‐term rainfall records at 15 measuring stations within the catchment. The Mann–Kendall test was used to detect trends, and Sen's slope estimator was used to calculate the slopes in both monthly and annual rainfall. Moreover, a cumulative summation technique was used to identify the trend beginning year, and prewhitening criteria were tested to check for autocorrelation in the data. The results showed that the monthly rainfall has generally decreasing trends except in January and June. Significant decreasing rainfall trends were observed in May (among the autumn months of March, April and May) at most stations and also in some other months at several stations. A decreasing trend was also observed in the annual rainfall at all stations. This study indicates that there has been a consistent reduction in rainfall over the catchment, both spatially and temporally over the past 50 years, which will have important implications for the future management of water resources. Copyright © 2012 John Wiley & Sons, Ltd.     

On trend detection

A main obstacle to trend detection in time series occurs when they are autocorrelated. By reducing the effective sample size of a series, autocorrelation leads to decreased trend significance. Numerous recipes attempt to mitigate the effect of autocorrelation, either by adjusting for the reduced effective sample size or by removing the autocorrelated components of a series. This short note deals with the latter, also called prewhitening (PW). It is known that removal of autocorrelation also removes part of the trend, which may affect the signal‐to‐noise ratio. Two popular methods have dealt with this problem, the trend‐free prewhitening (TFPW) and the iterative prewhitening. Although it is generally accepted that both methods reduce the adverse effects of PW on the trend magnitude, corresponding effects on statistical significance have not been clearly stated for TFPW. Using a Monte Carlo approach, it is demonstrated that both methods entail quite different Type‐I error rates. The iterative prewhitening produces rates that are generally close to the nominal significance level. The TFPW, however, shows very high Type‐I error rates with increasing autocorrelation. The corresponding rate of false trend detections is unacceptable for applications, so that published trends based on TFPW need to be reassessed.     

Streamflow trends in Nepal

Abstract

This study presents the first comprehensive nationwide trend detection of streamflow in Nepal, a country that has been historically understudied despite its critical location as the southern pathway for most of the Himalayan snowpack melt and torrential seasonal monsoon rains. We applied Mann-Kendall and Sen's trend tests using trend-free pre-whitening and bootstrap approaches to two streamflow data sets to deal with serial and cross-correlation. The two data sets comprised 23–33 hydrometric stations with 31 years and more than 20 years of published data, respectively. The test on the 33 stations data set showed that 23% of the streamflow variables studied had statistically significant trends, evenly divided between upward and downward trends. Similarly, in the second, relatively smaller data set, 24% of variables exhibited trends, of which 41% were downward and 59% upward. The higher percentage of observed upward trends in pre-monsoon and winter seasonal average flow is noteworthy given the potential snowmelt contribution in many of the studied sites. Trends were mostly absent in stations draining the larger basins. However, some spatial patterns were seen in the observed trend directions, specifically, a downward trend in the Karnali-Mahakali River basin and an upward trend in the West Rapti River basin, as well as a nationwide absence of trend in the post-monsoon season.

Editor Z.W. Kundzewicz

Citation Gautam, M.R. and Acharya, K., 2011. Streamflow trends in Nepal. Hydrological Sciences Journal, 57 (2), 344–357.