Temporal precipitation estimation from nearby radar reflectivity using dynamic factor analysis in the mountainous watershed – a case during Typhoon Morakot

The radar reflectivity (Z)–rain intensity (R) relationship fluctuates in both temporal and spatial scales. The dynamic factor analysis (DFA) and min/max autocorrelation factor analysis (MAFA) was specifically designed for considering various space–time integrations of gauge rainfall and radar reflectivity. We detect representative radar reflectivity observed around rainfall stations that were most responsible for rainfall intensity and identify the crucial patterns of the radar reflectivity in the Kaoping River watershed during Typhoon Morakot. Result shows that the MAFA and DFA can reduce the uncertainty of the dynamic Z‐R relationship effectively. The MAFA separates an entire area into two subareas (southern and northern areas) according to the relationships between the radar reflectivity and min/max autocorrelation factor (MAF) axes. For both areas, the different extents of temporal rainfall correlated with the radar reflectivity were determined using DFA. Especially in the northern area, the radar reflectivity was significantly related to the rainfall intensity for most stations without mountain blockage. Mountain blockages associated with the presence of terrain and wind direction were inferred the major factors that affected the relationship between radar reflectivity and rainfall intensity in the mountainous watershed. Further study can consider the terrain effect and meteorological information, such as wind speed and direction in the DFA model, with the dominant radar reflectivity to estimate the temporal rainfall patterns. Copyright © 2012 John Wiley & Sons, Ltd.     

Dynamic factor analysis and artificial neural network for estimating pan evaporation at multiple stations in northern Taiwan

Abstract

Evaporation is an important reference for managers of water resources. This study proposes a hybrid model (BD) that combines back-propagation neural networks (BPNN) and dynamic factor analysis (DFA) to simultaneously precisely estimate pan evaporation at multiple meteorological stations in northern Taiwan through incorporating a large number of meteorological data sets into the estimation process. The DFA is first used to extract key meteorological factors that are highly related to pan evaporation and to establish the common trend of pan evaporation among meteorological stations. The BPNN is then trained to estimate pan evaporation with the inputs of the key meteorological factors and evaporation estimates given by the DFA. The BD model successfully inherits the advantages from the DFA and BPNN, and effectively enhances its generalization ability and estimation accuracy. The results demonstrate that the proposed BD model has good reliability and applicability in simultaneously estimating pan evaporation for multiple meteorological stations.

Citation Chang, F.J., Sun, W., and Chung, C.H., 2013. Dynamic factor analysis and artificial neural network for estimating pan evaporation at multiple stations in northern Taiwan. Hydrological Sciences Journal, 58 (4), 813–825.     

Space–time rainfall variability in the Paute basin,Ecuadorian Andes

Despite the importance of mountain ranges as water providers, knowledge of their climate variability is still limited, mostly due to a combination of data scarcity and heterogeneous orography. The tropical Andes share many of the main features of mountain ranges in general, and are subject to several climatic influences that have an effect on rainfall variability. Although studies have addressed the large-scale variation, the basin scale has received little attention. Thus, the purpose of this study was to obtain a better understanding of rainfall variability in the tropical Andes at the basin scal, utilizing the Paute River basin of southern Ecuador as a case study. Analysis of 23 rainfall stations revealed a high spatial variability in terms of: (i) large variations of mean annual precipitation in the range 660–3400 mm; (ii) the presence of a non-monotonic relation between annual precipitation and elevation; and (iii) the existence of four, sometimes contrasting, rainfall regimes. Data from seven stations for the period 1964–1998 was used to study seasonality and trends in annual, seasonal and monthly precipitation. Seasonality is less pronounced at higher elevations, confirming that in the páramo region, the main water source for Andean basins, rainfall is well distributed year round. Additionally, during the period of record, no station has experienced extreme concentrations of annual rainfall during the wet season, which supports the concept of mountains as reliable water providers. Although no regional or basin-wide trends are found for annual precipitation, positive (negative) trends during the wet (dry) season found at four stations raises the likelihood of both water shortages and the risk of precipitation-triggered disasters. The study demonstrates how variable the precipitation patterns of the Andean mountain range are, and illustrates the need for improved monitoring. Copyright © 2007 John Wiley & Sons, Ltd.     

Trends and discontinuities in regional rainfall of West and Central Africa: 1951–1989

Abstract

Standardized regional mean annual rainfall series are analysed over the period 1951–1989 from a data set of 891 rainfall stations which covers 23 countries of West and Central Africa. Missing values are estimated by using regionalized indexes computed on the basis of a morpho-climatic delimitation of 44 homogeneous climatic units. Searches for statistical discontinuities in rainfall series show no discontinuity for most units of Central Africa. For several units of West Africa the first discontinuity occurs at the end of the 1950s. The main discontinuity period occurs between 1968 and 1970, followed by a second one at the beginning of the 1980s. Rainfall deficit is greater north of 10°N, and is also important in the Guinean Mountains and on the northern coast of the Gulf of Guinea, west of the Atakora Mountains. Regions leeward of mountainous areas experienced moderate rainfall decrease.     

Entropy,consistency in rainfall distribution and potential water resource availability in Australia

Understanding the variability in monthly rainfall amounts is important for the management of water resources. We use entropy, a measure of variability, to quantify the rainfall variability in Australia. We define the entropy of stable rainfall (ESR) to measure the long‐term average rainfall variability across the months of the year. The stations in northern Australia observe substantially more variability in rainfall distributions and stations in southern Australia observe less variability in rainfall distribution across the months of the year. We also define the consistency index (CI) to compare the distribution of the monthly rainfall for a given year with the long‐term average monthly rainfall distribution. Higher value of the CI indicates the rainfall in the year is consistent with the overall long‐term average rainfall distribution. Areas close to the coastline in northern, southern and eastern Australia observe more consistent rainfall distribution in individual years with the long‐term average rainfall distribution. For the studied stations, we categorize the years into different potential water resource availability on the basis of annual rainfall amount and CI. For almost all Australian rainfall stations, El Niño years have a greater risk of having below median and relatively inconsistent rainfall distribution than La Niña years. The results may be helpful for developing area‐specific water usage strategies. Copyright © 2011 John Wiley & Sons, Ltd.     

Analysis of long-term fluctuations in stream flow time series: An application to Litani River, Lebanon

Litani River is the largest river in Lebanon and has been affected by several physical and anthropogenic factors that influenced its flow dynamics. By means of the Singular Spectrum Analysis (SSA), the time dynamics of the stream flow of seven sites along the course of Litani River was investigated, extracting for each site the long-term trend. A clear decreasing trend characterizes all the long-term trends of the stream flow. Furthermore, several peaks were identified, consistent with the rainfall rate and snow cover variability.     

Temporal trends of hydro-climatic variables and their relevance in water resource management

Identification of temporal changes in hydrological regimes of river basins is an important topic in contemporary hydrology because of the potential impacts of climate change on river flow regimes.For this purpose,long-term historical records of rainfall(P),runoff(Q)and other climatic factors were used to investigate hydrological variability and trends in the Tajan River Basin over the period 1969e1998.Actual evaporation(E),rainfall variability index(d),evaporation ratio(CE)and runoff ratio(CQ)were estimated from the available hydroclimatological records.Mann-Kendall trend analysis and nonparametric Sen's slope estimates were performed on the respective time series variables to detect monotonic trend direction and magnitude of change over time.Rainfall variability index showed that 1973 was the wettest year(δ=+2.039)while 1985 was the driest(δ=-1.584).Also,decades 69e78 and 89e98 were recognized as the wettest and driest decades respectively.The gradient of variation of climatological parameters showed that during the study period,all three parameters of rainfall,evaporation and runoff have decreased and the variations of rainfall and evaporation were significant at the 95%level.Investigation of hydrological changes due of dam construction(1999)showed that the amount and annual distribution of discharge were completely different pre and post-dam construction.Discharge decreased in high water months and increased in low water months to meet water supply demands,especially for agriculture.The relationship between temperature and rainfall trends is compared for three stations in Mazandaran Province(Gorgan,Babolsar and Ramsar)from 1956 to 2003 and nine other stations with different statistical periods of 19e36 years,relating trends to northern hemisphere and global trends.Decreases in temperature were accompanied by decreases in rainfall,and vice versa.These trends were not observed in northern hemisphere and world scales,where temperature increases are accompanied by decreases in rainfall.These variations of hydroclimatological parameters show undesirable water resources situations during the statistical periods if the trend continues severe water resource crises.     

Geodetic evidence on segmentation of Cascadia subduction zone based on episodic tremors and slips using multivariate harmonic analysis of GPS time series

Episodic tremor and slip (ETS) events with different recurrence intervals have been observed in abundance all along the Cascadia subduction zone margin. Analysis of seismic records as well as Global Positioning System (GPS) time series of the Pacific Northwest Geodetic Array (PANGA) has suggested three distinct coherent zones for the occurrence of these events. In this paper multivariate harmonic estimation has been deployed for further analysis of the segmentation in this area. Raw time series of 43 permanent GPS stations have been used for this purpose. The GPS stations have been geographically divided into three distinct groups including those in the northern, middle and southern parts of the study area. After the reduction of time series for the linear trend as well as annual and semiannual effects, the data series of each group has been analyzed using the multivariate harmonic estimation technique. Subsequently, different combinations of GPS stations including the stations located in the southern, northern and middle zones have been analyzed. Furthermore, the northern and middle, southern and middle as well as the northern and southern zone pair combinations have also been analyzed. The statistical measure devised for identifying the significant frequencies suggests common periods that are consistent with the recurrence intervals of the ETS events already reported for each of the above three geographic zones. Moreover, the method can provide geodetic evidence, in addition to geophysical ones, on the segmentation of ETSs, provided that the adopted time series are of a sufficient length. The geodetic evidence obtained in this research is consistent with the recurrence intervals as well as the boundaries obtained by the analysis of seismic records. Contrary to univariate harmonic estimation, multivariate approach using spatio-temporal correlation of the GPS time series is capable to detect those ETSs whose impacts on the time series are weak.     

The relationship between runoff rate and lag time and the effects of surface treatments at the plot scale

Abstract

The manner in which both the seasonal and regional variations in storm duration, intensity and inter-storm period manifest in the runoff response of agricultural water supply catchments is investigated. High-resolution rainfall data were analysed for a network of 17 raingauges located across the semiarid (200–500 mm year^?1) agricultural districts of southwest Western Australia. Seasonal variations in mean storm duration, mean rainfall intensity and mean inter-storm period were modelled using simple periodic functions whose parameters were then also regressed with geographic and climatic indices to create spatial fields for each of these statistics. Based on these mean values, a continuous rainfall time series can be synthesized for any location within the region, with the rainfall depth within each storm being downscaled to 5-min time steps using a bounded random cascade model. Runoff from six different catchment surface treatments (“engineered” catchments) was simulated using a conceptual water-balance model, validated using rainfall—runoff data from an experimental field site. The expected yield of the various catchment types at any other location within the study region is then simulated using the above rainfall—runoff model and synthetic rainfall and potential evaporation time series under a range of climatic settings representative of regional climate variation. The resulting coupled model can be used to estimate the catchment area required to yield an acceptable volume of runoff for any location and dam capacity, at a specified reliability level, thus providing a tool for water resource managers to design engineered catchments for water supply. Although the model presented is specific for Western Australia's southwest region, the methodology itself is applicable to other locations.     

Detection of trends in the 7-day sustained low-flow time series of Irish rivers

A combination of statistical hypothesis testing methods (Mann-Whitney, Mann-Kendall and Spearman’s rho) and visual exploratory analysis were used to investigate trends in Irish 7-day sustained low-flow (7SLF) series possibly driven by changes in summer rainfall patterns. River flow data from 33 gauging stations covering most major Irish rivers were analysed, after excluding catchments where low flows are influenced by significant human interventions. A statistically significant increasing trend in the 7SLF series was identified by all three tests at eight gauging stations; in contrast, a statistically significant decreasing trend was identified by all three tests at four stations. The stations with increasing trends are mainly located within the western half of the country, while there is no particular spatial clustering of the stations showing a decreasing trend. Further analysis suggests that the increasing trend in the 7SLF time series persists regardless of the starting year of analysis. However, the decreasing trend occurs only when years prior to 1970 are included in the analysis, and disappears, or is reversed, if only the data from 1970 and onwards are considered. There is strong evidence that the direction of the trends in the 7SLF series is determined mainly by trends in total summer rainfall amounts, i.e. is linked to weather.

EDITOR Z.W. Kundzewicz

ASSOCIATE EDITOR not assigned     

Estimation and spatial interpolation of rainfall intensity distribution from the effective rate of precipitation

Great emphasis is being placed on the use of rainfall intensity data at short time intervals to accurately model the dynamics of modern cropping systems, runoff, erosion and pollutant transport. However, rainfall data are often readily available at more aggregated level of time scale and measurements of rainfall intensity at higher resolution are available only at limited stations. A distribution approach is a good compromise between fine-scale (e.g. sub-daily) models and coarse-scale (e.g. daily) rainfall data, because the use of rainfall intensity distribution could substantially improve hydrological models. In the distribution approach, the cumulative distribution function of rainfall intensity is employed to represent the effect of the within-day temporal variability of rainfall and a disaggregation model (i.e. a model disaggregates time series into sets of higher solution) is used to estimate distribution parameters from the daily average effective precipitation. Scaling problems in hydrologic applications often occur at both space and time dimensions and temporal scaling effects on hydrologic responses may exhibit great spatial variability. Transferring disaggregation model parameter values from one station to an arbitrary position is prone to error, thus a satisfactory alternative is to employ spatial interpolation between stations. This study investigates the spatial interpolation of the probability-based disaggregation model. Rainfall intensity observations are represented as a two-parameter lognormal distribution and methods are developed to estimate distribution parameters from either high-resolution rainfall data or coarse-scale precipitation information such as effective intensity rates. Model parameters are spatially interpolated by kriging to obtain the rainfall intensity distribution when only daily totals are available. The method was applied to 56 pluviometer stations in Western Australia. Two goodness-of-fit statistics were used to evaluate the skill—daily and quantile coefficient of efficiency between simulations and observations. Simulations based on cross-validation show that kriging performed better than other two spatial interpolation approaches (B-splines and thin-plate splines).     

Characterizing rainfall–groundwater dynamics in a hard‐rock aquifer system using time series,geographic information system and geostatistical modelling

The aim of this study was to investigate rainfall–groundwater dynamics over space and annual time scales in a hard‐rock aquifer system of India by employing time series, geographic information system and geostatistical modelling techniques. Trends in 43‐year (1965–2007) annual rainfall time series of ten rainfall stations and 16‐year (1991–2006) pre‐monsoon and post‐monsoon groundwater levels of 140 sites were identified by using Mann–Kendall, Spearman rank order correlation and Kendall rank correlation tests. Trends were quantified by Kendall slope method. Furthermore, the study involves novelty of examining homogeneity of pre‐monsoon and post‐monsoon groundwater levels, for the first time, by applying seven tests. Regression analysis between rainfall and post‐monsoon groundwater levels was performed. The pre‐monsoon and post‐monsoon groundwater levels for four periods – 1991–1994, 1995–1998, 1999–2002 and 2003–2006 – were subjected to geographic information system‐based geostatistical modelling. The rainfall showed considerable spatiotemporal variations, with a declining trend at the Mavli rainfall station (p‐value < 0.05). The Levene's tests revealed spatial homogeneity of rainfall at α = 0.05. Regression analyses indicated significant relationships (r² > 0.5) between groundwater level and rainfall for eight rainfall stations. Non‐homogeneity and declining trends in the groundwater level, attributed to anthropogenic and hydrologic factors, were found at 5–61 more sites in pre‐monsoon compared with post‐monsoon season. The groundwater declining rates in phyllite–schist, gneiss, schist and granite formations were found to be 0.18, 0.26, 0.21 and 0.14 m year^?1 and 0.13, 0.19, 0.16 and 0.02 m year^?1 during the pre‐monsoon and post‐monsoon seasons, respectively. The geostatistical analyses for four time periods revealed linkages between the rainfall and groundwater levels. Copyright © 2013 John Wiley & Sons, Ltd.     

Fractal analysis of rainfall observed in two different climatic regions

Abstract

The importance of high-resolution rainfall data to understand the intricacies of the dynamics of hydrological processes and describe them in a sophisticated and accurate way has been increasingly realized. The present study investigates the general suitability of fractal (or scaling) theory for understanding the rainfall behaviour and transforming rainfall data from one time scale to another. The study, employing a multi-fractal approach, follows the research undertaken earlier by the author (Sivakumar, 2000) employing a mono-fractal approach in which some preliminary indication as to the possibility of existence of (multi-) fractals was obtained. Rainfall data of three different resolutions, six-hourly, daily, and weekly, observed over a period of 25 years in two different climatic regions: a subtropical climatic region (Leaf River basin, Mississippi, USA); and an equatorial climatic region (Singapore) are analysed. The existence of multi-fractal behaviour in the rainfall data is investigated using (a) the power spectrum method; (b) the empirical probability distribution function (PDF) method; (c) the statistical moment scaling method; and (d) the probability distribution multiple scaling (PDMS) method. The results achieved from all these methods for the six different rainfall data sets considered indicate the existence of multi-fractal behaviour of rainfall observed in Leaf River basin and Singapore, providing further support to the results obtained using the mono-fractal approach (Sivakumar, 2000). The suitability of a multi-fractal framework to characterize the behaviour of rainfall observed in the above two significantly different climatic regions, subtropical and equatorial, seems to suggest the general suitability of the fractal theory for transforming rainfall from one time scale to another. Investigations with rainfall data from several other climatic regions are underway with a view to strengthening the above conclusions.     

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.     

Some aspects of the monsoon circulation and monsoon rainfall

Summary The south Asian summer monsoon from June to September accounts for the greater part of the annual rainfall over most of India and southeast Asia. The evolution of the summer and winter monsoon circulations over India is examined on the basis of the surface and upper air data of stations across India. The salient features of the seasonal reversals of temperature and pressure gradients and winds and the seasonal and synoptic fluctuations of atmospheric humidity are discussed. The space-time variations of rainfall are considered with the help of climatic pentad rainfall charts and diagrams. The rainfall of several north and central Indian stations shows a minimum around mid-August and a maximum around mid-February which seem to be connected with the extreme summer and winter positions of the ITCZ and the associated north-south shifts in the seasonal circulation patterns. Attention is drawn to the characteristic features of the monsoon rainfall that emerge from a study of daily and hourly rainfall of selected stations. Diurnal variations of temperature, pressure, wind and rainfall over the monsoon belt are briefly treated.     

中国东部夏季持续性降水日变化在淮河南北的差异分析

本文利用1961-2006年我国285站观测的逐时降水数据,分析了中国东部不同地区夏季平均降水日变化随降水持续时间的变化特征. 虽然整个东部地区都表现为短时降水峰值较一致地出现在下午17时左右,持续较长时间降水在清晨前后发生峰值降水,但持续性降水日变化的平均峰值时间以淮河为界存在显著南北差异. 北部地区的持续性降水峰值主要出现在02-06时前后;南部地区的持续性降水峰值时间出现在06-10时. 无论是降水强度或频次的日变化峰值的南北差异均较明显,但降水强度差异更为突出,且主要表现在持续性强降水中. 进一步分析发现：一方面北部地区持续性强降水开始时间较南部地区更早;另一方面,北部地区降水从开始到峰值经历的时间更短. 最后,对持续性强降水峰值时间南北差异的可能原因进行了初步讨论.     

Joint probability distribution of annual maximum storm peaks and amounts as represented by daily rainfalls

Abstract

A procedure is presented for using the bivariate normal distribution to describe the joint distribution of storm peaks (maximum rainfall intensities) and amounts which are mutually correlated. The Box-Cox transformation method is used to normalize original marginal distributions of storm peaks and amounts regardless of the original forms of these distributions. The transformation parameter is estimated using the maximum likelihood method. The joint cumulative distribution function, the conditional cumulative distribution function, and the associated return periods can be readily obtained based on the bivariate normal distribution. The method is tested and validated using two rainfall data sets from two meteorological stations that are located in different climatic regions of Japan. The theoretical distributions show a good fit to observed ones.     

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.     

Caractérisation de la Variabilité Spatiale et Temporelle des Précipitations Annuelles sur le Bassin du Lac Tchad au Cours du 20ème Siècle/Spatial and Temporal Variability of Annual Rainfall in the Lake Chad Basin During the 20th Century

Abstract

The study of changes in annual rainfall in the Lake Chad basin during the 20th century is based on the analysis of 47 stations, i.e. a total of about 1600 station-years for the time series with more than 25 years of data. As previously observed in western and Sahelian Africa, robust tests of shift in time series identify a significant change in mean from the beginning of the 1960s between the latitudes 11 and 13°N, and a little later in this decade for the northern stations. The analysis of decadal rainfall shows that the 1950s decade was very humid and the next three decades were drier. These dry conditions were more and more severe until the 1980s. Data available after 1990 do not show any inversion in the trend. The annual rainfall decreases from south to north, and the regional gradient has changed from 1.5 mm km^?1 in the 1950s to 1.2 mm km^?1 in the 1980s between the latitudes 10 and 14°N.     

Trends in extreme rainfall in the state of New South Wales,Australia

The trends in annual maximum rainfall (AMR) intensity data in New South Wales, Australia, were examined. Data from 60 stations were used covering three study periods, 1955–2010, 1965–2010 and 1978–2010. Mann-Kendall (MK) and Spearman’s rho (SR) tests were applied to assess trends at local stations. Pre-whitening (PW), trend-free pre-whitening (TFPW) and the variance correction (VC) tests were used to assess the effects of serial correlation on trend results. For regional trend analysis, the regional MK test was employed. The impacts of climatic variability modes on the observed trends in AMR intensity and seasonal maximum rainfall data were investigated. It was found that positive trends were more frequent than the negative ones. The PW, TFPW and VC tests resulted in a slight reduction in the count of stations exhibiting significant positive trends. The number of stations exhibiting significant trends decreased when the impact of climate variability modes was considered.