Multiple time scale characteristics of rainfall and its impact on soil salinization in the typical easily salinized area in Huang-Huai-Hai Plain, China

On the basis of monthly rainfall data over 50?years, we analyzed temporal properties of annual and seasonal rainfall variability by using and comparing two kinds of continuous wavelet transforms. Furthermore, we deduced its impacts on soil salinization in the area of Huang-Huai-Hai Plain, China. Results showed that the annual rainfall collected by the studied area showed a decreasing trend during period 1960–2009 at a climatic tendency rate of 14.43?mm/10?years. The Morlet wavelet is better at capturing local feature of rainfall oscillatory behaviors at fine time scales, and the Mexican Hat wavelet is better at revealing global feature of rainfall period. Combining Wavelet transform with wavelet power spectrum and its confidence test, we found the 8-year dominant period of annual rainfall and the 5-, 6-, 10- and 12-year dominant periods of seasonal rainfall, respectively. The annual and seasonal rainfall trends in the near future and their impacts on soil salinization are deduced based on the rainfall dominant periods and the prominent correlation between rainfall and soil salinity changes. The annual rainfall will still be in a relatively low period in the subsequent year after 2009 and then revert to a relatively high period during 2011–2014. The subsequent summer variability of rainfall may be helpful for reducing the soil salinization, while the opposite trends of spring and autumn rainfall variability may aggravate the soil salinization. This suggests sustainable irrigation and drainage measures to prevent soil salinization in this area.     

Monsoonal precipitation variation in the East Asia since A.D. 1840

Three tree-ring rainfall reconstructions from China and Korea are used in this paper to investigate the East Asian summer monsoon-related precipitation variation over the past 160 years. Statistically, there is no linear correlation on a year-by-year basis between Chinese and Korean monsoon rainfall, but region-wide synchronous variation on a decadal-scale was observed. More rainfall intervals were 1860–1890, 1910–1925, and 1940–1960, and dry or even drought periods were 1890–1910, 1925–1940, and 1960–present. Reconstructions also display that the East Asian summer monsoon precipitation suddenly changed from more into less around mid-1920. These tree-ring precipitation records were also confirmed by Chinese historical dryness/wetness index and Korean historical rain gauge data.     

Multi-scale variability and trends of precipitation in North China

The issue of water shortage and related eco-environmental degradation in North China is one of the major emerging problems in China. Precipitation is the most key factor for water resources. Based on the historical flood/dryness grade dataset during the period of 1470–2000 obtained from 25 gauging stations in North China, the multi-scale variability and trends are analyzed by means of power spectral and continuous wavelet transform. It is found that the precipitation is characterized by obvious seasonal changes, quasi biennial oscillations, inter-annual 4–7 year component and inter-decadal 19-year periodicity. The MK test results showe that step changes occurred around 1914 and 1964 in the annual precipitation. As for the historical flood/dryness grade time series, it is characterized by 4∼5 year ENSO mode inter-annual oscillation, quasi-10 year inter-decadal variability, quasi-24 year component and 50–80 year centurial periodicity. However, the scales of these variations have decreased significantly since the 1970s. The trend for precipitation change in North China has been negative for last 30 years. Further research shows that North China will continue to become dryer until 2015 and may change to a wetter regime after 2020. These findings should be helpful for future decision-making to ensure sustainable water resource management in North China.     

Erythemal UV observations at Belsk,Poland, in the period 1976–2008: Data homogenization,climatology, and trends

Measurements of erythemal irradiance have been carried out continuously at Belsk since May 1975. We present a homogenization procedure of the UV time series for the period of 1976–2008. Long-term oscillations discovered in the homogenized data set agree with those extracted from the reconstructed UV data for all-sky and clear-sky conditions. The UV climatology was established and the UV variability was determined. Positive UV trends were found for the period of 1976-2008 in the annual mean (5.6±0.9% per decade), in the seasonal mean for the warm subperiod of the year (April–October, 5.5±1.0% per decade), and in monthly means (∼2–9% per decade). A satisfactory agreement between the trend extracted from the homogenized ground-based data and that found in satellite UV data for Belsk (1979–2008) supports the reliability of satellite trend analyses over wider areas during snowless periods.     

Climate-driven shifts in diatom assemblages recorded in annually laminated sediments of Sacrower See (NE Germany)

Sacrower See is a eutrophic lake with annually laminated sediments extending back to A.D. 1868. Analysis of annual layers revealed multi-decadal periods of distinct diatom assemblages at A.D. 1868–1875, 1876–1940, 1941–1978, and 1979–2000. Detrended correspondence analysis performed on individual seasonal sediment layers showed decadal-scale patterns of turnover in the diatom flora. The spring–summer layers showed higher sample scores until the early 1960s, after which the differences with the autumn–winter layers became smaller. Rates-of-change analysis revealed that the seasonal variability in diatom assemblages was higher than the annual changes. Summer diatom rates of change over the period A.D. 1894–1960 was on average higher than for winter, whereas between the 1960s and 1970s the winter rates of change became higher than the summer ones. Redundancy Analyses showed that seasonal temperatures and wind strength were significant explanatory variables for diatom assemblages in both annual and seasonal layers. These results suggest that meteorological changes indirectly affected diatom assemblages via the mixing regime of the lake. A comparison of the diatom rates of change with the amplitude of inter-annual climate change shows a statistically significant correlation for the spring-summer layers in the period of A.D. 1963–2000, showing that the sensitivity of diatom assemblages to meteorological changes has varied over the past century, with a stronger effect on diatoms registered during the past 40 years.     

Precipitation change and human impacts on hydrologic variables in Zhengshui River Basin, China

Climate change and anthropogenic impacts on hydrologic variables have received significant attention in recent years. We assessed stream flow and water level in the Zhengshui River basin, China, in the period 1960 to 2003 in response to precipitation variation and anthropogenic factors. Analyses of daily discharge and water level records, and derived annual, seasonal and monthly series, showed that Zhengshui River flows had a significant increasing trend, with an abrupt change point in 1990. There was a significant decreasing water level trend with an abrupt change point in 1995. Human activities and precipitation contributed 53 and 47%, respectively, to increase in stream flow during 1991–2003. Anthropogenic activities such as sand dredging, dominated the decrease in water level during 1994–2003. Human-induced land use change, soil erosion and sand excavation driven by rapid economic development have played a more important role than precipitation variation in hydrological changes in the Zhengshui River basin over the past 50 years.     

Hydrological response of a humid agroforestry catchment at different time scales

Using data collected at the Mero catchment during three hydrological years (2005/06–2007/08), an analysis of rainfall–runoff relationships was performed at annual, seasonal, monthly, and event scales. At annual scale, the catchment showed low runoff coefficients (23–35%), due to high water storage capacity soils as well as high runoff inter‐annual variability. Rainfall variability was the main responsible for the differences in the inter‐annual runoff. At seasonal and monthly scales, there was no simple relationship between rainfall and runoff. Seasonal dynamics of rainfall and potential evapotranspiration in conjunction with different rainfall distribution during the study years could be the key factors explaining the complex relationship between rainfall and runoff at monthly and seasonal scale. At the event scale, the results revealed that the hydrological response was highly dependent on initial conditions and, to a lesser extent, on rainfall amount. The shapes of the different hydrographs, regardless of the magnitude, presented similar characteristics: a moderate rise and a prolonged recession, suggesting that subsurface flow was the dominant process in direct runoff. Moreover, all rainfall–runoff events had a higher proportion of baseflow than of direct runoff. A cluster‐type analysis discriminated three types of events differentiated mainly by rainfall amount and antecedent rainfall conditions. The study highlights the role of the antecedent rainfall and the need for caution in extrapolating relationships between rainfall amount and hydrological response of the catchment. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

Non‐stationarity in rainfall and temperature in the Murray Darling Basin

Two analyses, one based on multiple regression and the other using the Holt–Winters algorithm, for investigating non‐stationarity in environmental time series are presented. They are applied to monthly rainfall and average maximum temperature time series of lengths between 38 and 108 years, from six stations in the Murray Darling Basin and four cities in eastern Australia. The first analysis focuses on the residuals after fitting regression models which allow for seasonal variation, the Pacific Decadal Oscillation (PDO) and the Southern Oscillation Index (SOI). The models provided evidence that rainfall is reduced during periods of negative SOI, and that the interaction between PDO and SOI pronounces this effect during periods of negative PDO. Following this, there was no evidence of any trend in either the PDO or SOI time series. The residuals from this regression were analysed with a cumulative sum (CUSUM) technique, and the statistical significance was assessed using a Monte Carlo method. The residuals were also analysed for volatility, autocorrelation, long‐range dependence and spatial correlation. For all ten rainfall and temperature time series, CUSUM plots of the residuals provided evidence of non‐stationarity for both temperature and rainfall, after removing seasonal effects and the effects of PDO and SOI. Rainfall was generally lower in the first half of the twentieth century and higher during the second half. However, it decreased again over the last 10 years. This pattern was highlighted with 5‐year moving average plots. The residuals for temperature showed a complementary pattern with increases in temperature corresponding to decreased rainfall. The second analysis decomposed the rainfall and temperature time series into random variation about an underlying level, trend and additive seasonal effects and changes in the level; trend and seasonal effects were tracked using a Holt–Winters algorithm. The results of this analysis were qualitatively similar to those of the regression analysis. Copyright © 2010 John Wiley & Sons, Ltd.     

Annual maxima and totals of seasonally varying processes

The solar cycle induces strong periodicity in processes underlying monthly rainfall totals. Seasonally varying parameters of rainfall distributions can be estimated with reasonable reliability from relatively few years of monthly data. The distribution of annual totals or maxima in terms of these varying parameters can thus be used to predict long term annual characteristics from quite short records. Specification of seasonal variation of parameters as a harmonic process simplifies the derivations. Ignoring seasonal variation in the rainfall process leads to incorrect estimates of long-term extreme rainfalls when using traditional methodology.     

Precipitation trend analysis using discrete wavelet transform at the Langat River Basin,Selangor, Malaysia

The main purpose of this study was to determine the most dominant periodic components that affect the annual and seasonal precipitation trends in each homogenous rainfall region in the Langat River Basin, Malaysia for the period 1982–2011. Performing this research could be essential because in the previous studies on detection of trend in Malaysia, the details of variations of different time scales and the periodic responsible for the observed trends were not investigated. Using discrete wavelet transform (DWT) coupled with Mann–Kendall at the regional scale for the first time particularly in the context of Malaysia is the contribution of this study. In order to form the homogenous rainfall regions, first the total annual and seasonal precipitation in each year was spatialized into 5 km × 5 km grids using the inverse distance weighting method. The obtained precipitation series for the grids were then grouped applying the Ward’s clustering method based on the similarity of precipitation time series. After allocating a cluster number to each grid, the boundary of the regions was formed in ArcGIS software. Following which, in each homogenous region the areal precipitation series were computed by the Thiessen polygon method. The Mann–Kendall (MK) test was used to detect trend and the DWT coupled with the MK test and the sequential MK analysis were then utilized in order to find out the time scale which affected the observed trend in each homogenous region. On annual scale, it was found that D₁ (plus approximation) component in regions Annual Cluster1 (AC1) and AC2 was the periodic mode responsible for trends. On seasonal scale, in regions Northeast monsoon Cluster 1 (NC1), NC3, SC1 and Southwest monsoon Cluster 2 (SC2), D₁ (with approximation), in regions NC4, Inter monsoon 1 Cluster 1 (I1C1), I1C2, Inter monsoon 2 Cluster 1 I2C1 and I2C2, Detail 2 (D₂) (plus approximation) and in region NC2, Detail 3 (D₃) (with approximation added) component were the most influential periodicity for trends.     

Segmentation-based approach for trend analysis and structural breaks in rainfall time series (1851–2006) over India

ABSTRACT

This study analysed long-term rainfall data (1851–2006) over seven climatic zones of India at seasonal and annual scales based on three techniques: (i) linear regression, (ii) multifractal detrended fluctuation analysis (MFDFA) and (iii) Bayesian algorithm. The linear regression technique was used for trend analysis of short-term (30 years) and long-term (156 years) rainfall data. The MFDFA revealed small- and large-scale fluctuations, whereas the Bayesian algorithm helped in quantifying the uncertainty in break-point detection from the rainfall time series. Major break points years identified through Bayesian algorithm were 1888, 1904 and 1976. The MFDFA technique identified that high fluctuation years were between 1871–1890, 1891–1910 and 1951–1970. Linear regression-based analysis revealed 1881–1910 and 1971–2006 as break-point periods in the North Mountainous Indian region. A similar analysis was carried out for India as a whole, as well as its seven climatic zones.     

Stochastic generation of hourly rainstorm events

Occurrence of rainstorm events can be characterized by the number of events, storm duration, rainfall depth, inter-event time and temporal variation of rainfall within a rainstorm event. This paper presents a Monte-Carlo based stochastic hourly rainfall generation model considering correlated non-normal random rainstorm characteristics, as well as dependence of various rainstorm patterns on rainfall depth, duration, and season. The proposed model was verified by comparing the derived rainfall depth–duration–frequency relations from the simulated rainfall sequences with those from observed annual maximum rainfalls based on the hourly rainfall data at the Hong Kong Observatory over the period of 1884–1990. Through numerical experiments, the proposed model was found to be capable of capturing the essential statistical features of rainstorm characteristics and those of annual extreme rainstorm events according to the available data.     

变化环境下近60年西江流域径流时空演变特征

气候变化叠加人类活动的双重影响下,西江流域的河川径流发生了不同程度的改变,重新认识和掌握变化环境下的径流时空演变规律对流域的科学管理具有重要意义。基于西江流域干支流7个控制性水文站近60年的日径流资料,综合极点对称模态分解法(ESMD)、Mann-Kendall检验、R/S分析、小波分析等方法,从年代、年、季和年内多个时间尺度对径流的时空演变特征进行分析,研究结果表明:年代尺度下,西江流域径流丰枯交替、变化悬殊,1970s与1990s径流丰沛,2010s径流偏枯,降雨影响着径流的丰枯变化,流域上、中游更易发生干旱与洪涝灾害;春、夏、秋、冬季径流振荡周期依次为2～7、15～20、28～29 a,3～5、7～10、20 a,2～3、6～8、12～15 a和3～8、12～15、20 a,均呈现年际与年代的双重周期特征,IMF1的年际振荡在径流变化中占主导地位;受降雨与水库调蓄作用的影响,年、夏、秋季径流呈下降趋势,预测下降变化具有持续性,春、冬季径流整体呈上升趋势。空间内上游的变化趋势更显著;年和季尺度径流在1980年后突变增多,尤其集中于2000—2010年间,人类活动与气候变化是造成西江...     

The Preferred Structure of the Interannual Indian Monsoon Variability

The leading empirical orthogonal function (EOF) of the June-Sept. mean, rotational horizontal wind at 850 hPa and 200 hPa (over the region 12.5°S–42.5°N, 50°E–100°E) from 56 years (1948–2003) of reanalysis (from the National Centers for Environmental Prediction) shows strong anti-cyclonic circulation at upper levels, strong Indian Ocean cross-equatorial flow and on-shore flow over western India at lower levels . The associated principal component (PC) is correlated at the 0.75 level with the seasonal mean observed Indian Monsoon rainfall (IMR). Composite differences of vertically integrated divergence (surface to 800 hPa) and vorticity (surface to 500 hPa) between ``strong' years (PC-1 exceeds one standard deviation σ) and ``weak' years (PC-1 less than − σ) suggest increased rising motion and storminess over the Bay of Bengal and central India. Composite difference maps of station rainfall from the India Meteorological Department (IMD) between strong years and normal years (weak years and normal years) are statistically significant over central India, with strong (weak) years associated with increased (decreased) precipitation. In both cases the maps of rainfall anomalies are of one sign throughout India. The correlation of PC-1 with global seasonal mean SST is strong and negative over the eastern equatorial Pacific, but positive in a surrounding horse-shoe like region. Significant negative correlation occurs in the northwestern Indian Ocean. The lag/lead correlation between the NINO3 SST index and PC-1 is similar to but stronger than the NINO3/IMR correlation. Modest (but significant) negative correlation is seen when NINO3 leads PC-1 (or IMR) by one-two months. Strong negative correlation is seen when PC-1 (or IMR) leads NINO3. The projections of running five-day means of horizontal rotational winds at 850 and 200 hPa onto EOF-1 (after removing the seasonal mean for each year) were pooled for strong, normal and weak years. The strong and normal year probability distribution functions (pdfs) are nearly indistinguishable, but the weak year pdf has more weight for moderate negative values and in both extreme tails and shows some hint of bi-modality.     

Periodic changes of stream flow in the last 40 years in Tarim River Basin,Xinjiang, China

Using the annual runoff series for the last 40 years from the Tarim River Basin, their periodic properties were analysed and their future trends predicted. Runoff data were collected at five hydrological gauging stations in the three main branches of the Tarim River. An extrapolation method and variance analysis were used to identify periods in annual runoff, and a trend superposition model to predict future changes. Results show that, there is a common period of 17 years in annual runoff changes for all three branches, with Hotan River showing an additional period of 10 years. Based on this trend, it is suggested that the annual runoff of the Tarim River should decrease in the period of 2006–2008, but increase in year 2009, and the flow may possibly begin to decrease significantly in year 2010. The long term trend of runoff in Tarim Basin has followed the global prediction of GCMs, i.e. began to increase in accordance with global increase of air temperature and precipitation in 1990. However, it has shown a local feature of uneven changes among the head streams in the same basin, which needs to be further investigated. Copyright © 2008 John Wiley & Sons, Ltd.     

Simulation of daily rainfall scenarios with interannual and multidecadal climate cycles for South Florida

Concerns about the potential effects of anthropogenic climate change have led to a closer examination of how climate varies in the long run, and how such variations may impact rainfall variations at daily to seasonal time scales. For South Florida in particular, the influences of the low-frequency climate phenomena, such as the El Nino Southern Oscillation (ENSO) and the Atlantic Multi-decadal Oscillation (AMO), have been identified with aggregate annual or seasonal rainfall variations. Since the combined effect of these variations is manifest as persistent multi-year variations in rainfall, the question of modeling these variations at the time and space scales relevant for use with the daily time step-driven hydrologic models in use by the South Florida Water Management District (SFWMD) has arisen. To address this problem, a general methodology for the hierarchical modeling of low- and high-frequency phenomenon at multiple rain gauge locations is developed and illustrated. The essential strategy is to use long-term proxies for regional climate to first develop stochastic scenarios for regional climate that include the low-frequency variations driving the regional rainfall process, and then to use these indicators to condition the concurrent simulation of daily rainfall at all rain gauges under consideration. A newly developed methodology, called Wavelet Autoregressive Modeling (WARM), is used in the first step after suitable climate proxies for regional rainfall are identified. These proxies typically have data available for a century to four centuries so that long-term quasi-periodic climate modes of interest can be identified more reliably. Correlation analyses with seasonal rainfall in the region are used to identify the specific proxies considered as candidates for subsequent conditioning of daily rainfall attributes using a Non-homogeneous hidden Markov model (NHMM). The combined strategy is illustrated for the May–June–July (MJJ) season. The details of the modeling methods and results for the MJJ season are presented in this study.     

Spatio-temporal changes of hydrological processes and underlying driving forces in Guizhou region, Southwest China

Understanding the changes in streamflow and associated driving forces is crucial for formulating a sustainable regional water resources management strategy in the environmentally fragile karst area of the southwest China. This study investigates the spatio-temporal changes in streamflow of the Guizhou region and their linkage with meteorological influences using the Mann–Kendall trend analysis, singular-spectrum analysis (SSA), Lepage test, and flow duration curves (FDCs). The results demonstrate that: (1) the streamflow in the flood-season (June–August) during 1956–2000 increased significantly (confidence level ≥95%) in most catchments, closely consistent with the distinct increasing trend of annual rainfall over wet-seasons. The timings of abrupt change for streamflow in most catchments are found to occur at 1986; (2) streamflow in the Guizhou region experiences significant seasonal changes prior/posterior to 1986, and in most catchments the coefficient of variation of monthly streamflow increases; (3) spatial changes in streamflow indicate that monthly streamflow in the north-west decreases but increases in other parts; (4) the spatial high- and low-flow map (Q ₅ and Q ₉₅) reveals an increase in the extremely large streamflow in the five eastern catchments but a decrease in the extremely low streamflow in the four eastern catchments and three western catchments during 1987–2000. An increase in streamflow, particularly extreme flows, during the flood season would increase the risk of extreme flood events, while a decrease in streamflow in the dry season is not beneficial to vegetation restoration in this ecologically fragile region.     

Correlation functions of rainfall field and their application in network design in the tropics

The study examines the correlation function of tropical monsoon rainfall on monthly, seasonal and annual time scales and obtains the relationship between this function and the distance. The area selected for study is Vidarbha with a fairly dense network of rain gauges. Vidarbha is a meteorological sub-division of the state of Maharashtra in India. Utilizing the relationship between the correlation function of the rainfall field and the distance, the errors of optimum interpolation of rainfall at a point have been computed by applying the method of optimum interpolation byGandin (1970). Relationships between the errors of interpolation and distance have been evaluated and from this the maximum spacing allowed between rain gauges for a specified tolerable error in interpolation has been estimated for each of the periods.