Calibration of weather radar using region probability matching method (RPMM)

In this paper, spatiotemporal variability of drought in Xilingol grassland during pasture growing season (from April to September) was investigated, using 52 years (1961–2012) of precipitation data recorded at 14 rain gauge stations in the study area. The Standardized Precipitation Index was used to compute the severity of drought. The Mann-Kendall test, the linear trend, and the sequential Mann-Kendall test were applied to standardized precipitation index (SPI) time series. The results indicate that drought has become increasingly serious on the region scale during pasture growing season, and the rate of SPI decreases ranged from ?0.112 to ?0.013 per decade. As for the MK test, most of the stations, the Z value range is from ?1.081 to ?0.005 and Kendall’s τ varies from ?0.104 to ?0.024. Meanwhile, drought is increased obviously from the northwest to the southeast region. Meanwhile, the occurrence probability of each severity class, times for reaching different drought class from any drought severity state, and residence times in each drought class have been obtained with Markov chain. Furthermore, the drought severities during pasture growing season in 2013–2016 are predicted depending on the weighted Markov chain. The results may provide a scientific basis for preventing and mitigating drought disaster.     

Separation of the impact of climate change and human activity on streamflow in the upper and middle reaches of the Taoer River,northeastern China

The Taoer River, a representative ecologically sensitive area in Northeast China, has undergone great climate changes and rapid social developments since 1961. Subsequently, a substantial alteration of the streamflow regime was observed and severe eco-environmental problems were becoming prominent. To provide decision makers the scientific basis for effective resource management and sound future planning, it is crucial to understand and assess the impacts of the climate variability and human activities on streamflow in this region. In this study, we combined an observation-based statistical analysis and physical modeling experiments to address this broad question. The Mann–Kendall and Sen’s slope were used to examine the trends and the moving t test was used to identify change points for the streamflow, precipitation, and potential evapotranspiration datasets. A statistically significant upward trend (α?=?5 %) was found for annual streamflow. An abrupt change point was identified in 1985 for the basin outlet station at Taonan. Accordingly, the streamflow was divided into baseline and changed period for attribution analysis. To investigate the impacts of climate change and human activities on annual streamflow, we applied a distributed hydrological model and six Budyko-type functions during the two periods. The results indicated that climate change and human activities accounted for about 45 and 55 % of the changes in streamflow, respectively.     

Streamflow trend analysis by considering autocorrelation structure,long-term persistence,and Hurst coefficient in a semi-arid region of Iran

Due to the substantial decrease of water resources as well as the increase in demand and climate change phenomenon, analyzing the trend of hydrological parameters is of paramount importance. In the present study, investigations were carried out to identify the trends in streamflow at 20 hydrometric stations and 11 rainfall gauging stations located in Karkheh River Basin (KRB), Iran, in monthly, seasonal, and annual time scales during the last 38 years from 1974 to 2011. This study has been conducted using two versions of Mann–Kendall tests, including (i) Mann–Kendall test by considering all the significant autocorrelation structure (MK3) and (ii) Mann–Kendall test by considering LTP and Hurst coefficient (MK4). The results indicate that the KRB streamflow trend (using both test versions) has decreased in all three time scales. There is a significant decreasing trend in 78 and 73 % of the monthly cases using the MK3 and MK4 tests, respectively, while these percentages changed to 80 and 70 % on seasonal and annual time scales, respectively. Investigation of the trend line slope using Theil–Sen’s estimator showed a negative trend in all three time scales. The use of MK4 test instead of the MK3 test has caused a decrease in the significance level of Mann–Kendall Z-statistic values. The results of the precipitation trends indicate both increasing and decreasing trends. Also, the correlation between the area average streamflow and precipitation shows a strong correlation in annual time scale in the KRB.     

Recent trends in annual snowline variations in the northern wet outer tropics: case studies from southern Cordillera Blanca,Peru

TL-moments approach has been used in an analysis to identify the best-fitting distributions to represent the annual series of maximum streamflow data over seven stations in Johor, Malaysia. The TL-moments with different trimming values are used to estimate the parameter of the selected distributions namely: Three-parameter lognormal (LN3) and Pearson Type III (P3) distribution. The main objective of this study is to derive the TL-moments (t ₁,0), t ₁?=?1,2,3,4 methods for LN3 and P3 distributions. The performance of TL-moments (t ₁,0), t ₁?=?1,2,3,4 was compared with L-moments through Monte Carlo simulation and streamflow data over a station in Johor, Malaysia. The absolute error is used to test the influence of TL-moments methods on estimated probability distribution functions. From the cases in this study, the results show that TL-moments with four trimmed smallest values from the conceptual sample (TL-moments [4, 0]) of LN3 distribution was the most appropriate in most of the stations of the annual maximum streamflow series in Johor, Malaysia.     

On the link between extreme floods and excess monsoon epochs in South Asia

This paper provides a synoptic view of extreme monsoon floods on all the nine large rivers of South Asia and their association with the excess (above-normal) monsoon rainfall periods. Annual maximum flood series for 18 gauging stations spread over four countries (India, Pakistan, Bangladesh and Nepal) and long-term monsoon rainfall data were analyzed to ascertain whether the extreme floods were clustered in time and whether they coincided with multi-decade excess monsoon rainfall epochs at the basin level. Simple techniques, such as the Cramer’s t-test, regression and Mann–Kendall (MK) tests and Hurst method were used to evaluate the trends and patterns of the flood and rainfall series. MK test reveals absence of any long-term tendency in all the series. However, the Cramer’s t test and Hurst-Mandelbrot rescaled range statistic provide evidence that both rainfall and flood time series are persistent. Using the Cramer’s t-test the excess monsoon epochs for each basin were identified. The excess monsoon periods for different basins were found to be highly asynchronous with respect to duration as well as the beginning and end. Three main conclusions readily emerge from the analyses. Extreme floods (>90th percentile) in South Asia show a tendency to cluster in time. About three-fourth of the extreme floods have occurred during the excess monsoon periods between ~1840 and 2000 AD, implying a noteworthy link between the two. The frequency of large floods was higher during the post-1940 period in general and during three decades (1940s, 1950s and 1980s) in particular.     

Spatiotemporal variations of potential evapotranspiration and aridity index in relation to influencing factors over Southwest China during 1960–2013

This study investigated the spatial–temporal patterns and trends of potential evapotranspiration (ET₀) and aridity index (AI) over Southwest China during 1960–2013 based on daily temperature, precipitation, wind speed, sunshine duration, total solar radiation, and relative humidity data from 108 meteorological stations. The Penman–Monteith model, Mann–Kendall (M–K) test, moving t test, and Morlet wavelet method were used. The results indicated that ET₀ and AI across the region displayed decreasing trends, but the former was significant. After 2000, regionally average trends in ET₀ and AI increased rapidly, indicating that droughts increased over Southwest China in recent years. Spatially, the changes of ET₀ and AI were dissimilar and not clustered, either. Temporally, both ET₀ and AI displayed obvious abrupt change points over different timescales and that of AI was during the winter monsoon period. Significant periodic variations with periods of 27, 13, and 5 years were found in ET₀, but only of 13 and 5 years existed in AI. Correlation analysis revealed that the sunshine duration and wind speed were the dominant factors affecting ET₀ and that AI showed strong negative correlation with precipitation. The findings of this study enhance the understanding of the relationship between climate change and drought in Southwest China, while the mechanism controlling the variation in drought requires further study.     

Long-term trend and variability of precipitation in Chhattisgarh State,India

Spatial and temporal precipitation variability in Chhattisgarh State in India was examined by using monthly precipitation data for 102 years (1901–2002) from 16 stations. The homogeneity of precipitation data was evaluated by the double-mass curve approach and the presence of serial correlation by lag-1 autocorrelation coefficient. Linear regression analysis, the conventional Mann–Kendall (MK) test, and Spearman’s rho were employed to identify trends and Sen’s slope to estimate the slope of trend line. The coefficient of variation (CV) was used to analyze precipitation variability. Spatial interpolation was done by a Kriging process using ArcGIS 9.3. Results of both parametric and non-parametric tests and trend tests showed that at 5 % significance level, annual precipitation exhibited a decreasing trend at all stations except Bilaspur and Dantewada. For both annual and monsoon precipitation, Sen’s test showed a decreasing trend for all stations, except Bilaspur and Dantewada. The highest percentage of variability was observed in winter precipitation (88.75 %) and minimum percentage variability in annual series (14.01 %) over the 102-year periods.     

Change point detection of the Persian Gulf sea surface temperature

In this study, the Student’s t parametric and Mann-Whitney nonparametric change point models (CPMs) were applied to detect change point in the annual Persian Gulf sea surface temperature anomalies (PGSSTA) time series for the period 1951–2013. The PGSSTA time series, which were serially correlated, were transformed to produce an uncorrelated pre-whitened time series. The pre-whitened PGSSTA time series were utilized as the input file of change point models. Both the applied parametric and nonparametric CPMs estimated the change point in the PGSSTA in 1992. The PGSSTA follow the normal distribution up to 1992 and thereafter, but with a different mean value after year 1992. The estimated slope of linear trend in PGSSTA time series for the period 1951–1992 was negative; however, that was positive after the detected change point. Unlike the PGSSTA, the applied CPMs suggested no change point in the Niño3.4SSTA time series.     

Effects of climate change on annual streamflow using climate elasticity in Poyang Lake Basin, China

Hydrological processes depend directly on climate conditions [e.g., precipitation, potential evapotranspiration (PE)] based on the water balance. This paper examines streamflow datasets at four hydrological stations and meteorological observations at 79 weather stations to reveal the streamflow changes and underlying drivers in four typical watersheds (Meigang, Saitang, Gaosha, and Xiashan) within Poyang Lake Basin from 1961 to 2000. Most of the less than 90th percentile of daily streamflow in each watershed increases significantly at different rates. As an important indicator of the seasonal changes in the streamflow, CT (the timing of the mass center of the streamflow) in each watershed shows a negligible change. The annual streamflow in each watershed increases at different rates, with a statistically significant trend (at the 5 % level) of 9.87 and 7.72 mm year^?1, respectively, in Meigang and Gaosha watersheds. Given the existence of interactions between precipitation and PE, the original climate elasticity of streamflow can not reflect the relationship of streamflow with precipitation and PE effectively. We modify this method and find the modified climate elasticity to be more accurate and reasonable using the correlation analysis. The analyses from the modified climate elasticity in the four watersheds show that a 10 % increase (decrease) in precipitation will increase (decrease) the annual streamflow by 14.1–16.3 %, while a 10 % increase (decrease) in PE will decrease (increase) the annual streamflow by ?10.2 to ?2.1 %. In addition, the modified climate elasticity is applied to estimate the contribution of annual precipitation and PE to the increasing annual streamflow in each watershed over the past 40 years. Our result suggests that the percentage attribution of the increasing precipitation is more than 59 % and the decreasing in PE is less than 41 %, indicating that the increasing precipitation is the major driving factor for the annual streamflow increase for each watershed.     

Analysis of changes in the relationship between precipitation and streamflow in the Yiluo River, China

The Yiluo River is the largest tributary of the middle and lower Yellow River below the Sanmenxia Dam. Hydro-climatic variables have changed in the Yiluo River during the last half century. In this study, the trends in the annual precipitation and streamflow were analyzed in the Yiluo River during 1960–2006. The results indicated that both the annual precipitation and streamflow decreased significantly (P?<?0.05) from 1960 to 2006. Pettitt’s test shows that there was a change point for annual streamflow series around the year 1986 (P?<?0.05), while there was no change point identified for the annual precipitation series from 1960 to 2006. Annual streamflow decreased more significantly than annual precipitation since 1986. The relationship between the annual precipitation and streamflow presented a non-stationary state since 1986. This non-stationary relationship was mainly influenced by human activities. The average annual amount of water diversion from the Yiluo River increased significantly since the mid-1980s, accounting for 31.3 % of the total streamflow decrease from 1986 to 2006. In addition, land use/cover change (LUCC) contributed to 27.1–29.8 % of the decrease in streamflow. Human activities, including water diversion and LUCC, together contributed to 58.4–61.1 % of the decrease in streamflow and led to the non-stationary relationship between the annual precipitation and streamflow from 1986 to 2006. This study detected the changes in the precipitation–streamflow relationship and investigated the possible causes in the Yiluo River, which will be helpful for the understanding of the changes in streamflow in the Yellow River Basin.     

Falling Lake Victoria water levels: Is climate a contributing factor?

Recently, and perhaps most threatening, Lake Victoria water level has been receding at an alarming rate. A recent study suggested the possibility of the expanded hydroelectric power station in Uganda. However, since the lake receives 80% of its refill through direct rainfall and only 20% from the basin discharge, climatic contributions cannot be ignored, since the 80% water is directly dependant on it. It is therefore necessary to investigate climatic contribution to the declining Lake Victoria water level observed over a long period, i.e., 30 years. This contribution uses 30 years period anomalies for rainfall, river discharge and lake level changes of stations within Lake Victoria basin to analyse linear and cyclic trends of climate indicators in relation to Lake levels. Linear trend analysis using the Student’s t test indicate a decreasing pattern in rainfall anomalies, with the slope being statistically similar to those of water levels at both Kisumu, Maziba and Jinja stations for the same period of time (1976–1999), thus showing a strong correlation. On the other hand, cyclic trend analysis using Discrete Fourier Transform (DFT) shows cyclic period of water level to coincide with those of droughts and rainfall. The strong relationship between climatic indicators of drought and rainfall on one-hand and lake levels on the other hand signifies the need to incorporate climate information in predicting, monitoring and managing lake level changes.     

Probabilistic assessment of flood risks using trivariate copulas

In this paper, a copula-based methodology is presented for probabilistic assessment of flood risks and investigated the performance of trivariate copulas in modeling dependence structure of flood properties. The flood is a multi-attribute natural hazard and is characterized by mutually correlated flood properties peak flow, volume, and duration of flood hydrograph. For assessing flood risk, many studies have used bivariate analysis, but a more effective assessment can be possible considering all three mutually correlated flood properties simultaneously. This study adopts trivariate copulas for multivariate analysis of flood risks, and applied to a case study of flood flows of Delaware River basin at Port Jervis, NY, USA. On evaluation of various probability distributions for representation of flood variables, it is found that the flood peak flow and volumes can be best represented by Fréchet distribution, whereas flood duration by log-normal distribution. The joint distribution is modeled using four trivariate copulas, namely, three fully nested form of Archimedean copulas: Clayton, Gumbel–Hougaard, Frank copulas; and one elliptical copula: Student’s t copula. Based on distance-based performance measures, graphical tests, and tail-dependence measures, it is found that the Student’s t copula best representing the trivariate dependence structure of flood properties as compared to the other copulas. Similar results are found for bivariate copula modeling of flood variables pairs, where Student’s t copula performed better than the other copulas. The obtained copula-based joint distributions are used for multivariate analysis of flood risks, in terms of primary and secondary return periods. The resultant trivariate return periods are compared with univariate and bivariate return periods, and addressed the necessity of multivariate flood risk analysis. The study concludes that the trivariate copula-based methodology is a viable choice for effective risk assessment of floods.     

Spatial–temporal variations of spring drought based on spring-composite index values for the Songnen Plain,Northeast China

A spring-composite index (s-CI) is proposed in this study that involves slightly altering the use of the accumulated precipitation from the composite index (CI) comparing the value with other three commonly used indices (standardized precipitation index, SPI; self-calibrated Palmer drought severity index, sc-PDSI; and CI). In addition, the spatial–temporal variation of the s-CI in the Songnen Plain (SNP) was investigated using the Mann–Kendall test and empirical orthogonal function (EOF) methods. The results indicated that the proposed s-CI could identify most drought events in 1990s and 2000s and performed relatively better than SPI, sc-PDSI, and CI in this region. Compared with the other three indices, the s-CI had a higher correlation with relative soil moisture in April and May. The recent spring droughts (2000s) were the most severe in April or May. The weather was drier in May compared with April in the 1980s, whereas the weather was wetter in May than in April in the 1960s and 1970s. Moreover, the spatial patterns of the first EOFs for both April and May indicated an obviously east–west gradient in the SNP, whereas the second EOFs displayed north–south drought patterns. The proposed index is particularly suitable for detecting, monitoring, and exploring spring droughts in the Songnen Plain under global warming.     

The changing pattern of droughts in the Lancang River Basin during 1960–2005

Drought is one of the most costly natural disasters in the world. Understanding the drought characteristics in space and time will help deepen our apprehension of the drought formation and evolution mechanisms. It can also contribute to design monitoring system for drought warning and mitigation. In this study, we analyzed meteorological droughts, using the Standardized Precipitation Index, for Lancang River Basin, Southwest China. The 46-year (1960–2005) daily precipitation observations from 35 meteorological stations in the basin were used to derive the drought index. Spatial patterns and temporal patterns of the drought characteristics at multiple scales were investigated. The results utilizing the Principal Component Analysis and K-means clustering methods suggest that the study area can be divided into four sub-regions geographically with each sub-region having its own distinctive temporal evolution patterns of droughts. The temporal variability of droughts was investigated using the Empirical Mode Decomposition (EMD) analysis and the wavelet method. The EMD analysis showed that more than 60 % of the variance of the drought is associated with intra-decadal fluctuations in precipitation, except for one sub region, represented by the Changdu station. The wavelet transform showed an evolution of the main cycle near 3–7 years for most parts of the study area.     

A 400-year tree-ring record of the Puelo River summer–fall streamflow in the Valdivian Rainforest eco-region, Chile

The Puelo River is a watershed shared between Chile and Argentina with a mean annual streamflow of 644 m³ s^?1. It has a high ecologic and economic importance, including introduced farmed salmon, tourism, sports fishing and projected hydroelectricity. Using Austrocedrus chilensis and Pilgerodendron uviferum tree-ring records we reconstructed summer–fall (December–May) Puelo River streamflow, which is the first of such reconstructions developed in the Pacific domain of South America. The reconstruction goes back to 1599 and has an adjusted r ² of 0.42. Spectral analysis of the reconstructed streamflow shows a dominant 84-year cycle which explains 25.1% of the total temporal variability. The Puelo River summer–fall streamflow shows a significant correlation (P?>?0.95, 1943–2002) with hydrological records throughout a vast geographic range within the Valdivian eco-region (35 to 46°S). Seasonal Puelo River interannual streamflow variability is related to large-scale oceanic and atmospheric circulation features. Summer–fall streamflows showed a significant negative correlation with the Antarctic Oscillation (AAO), whereas winter–spring anomalies appear to be positively connected with sea surface temperature variations in the tropical Pacific. In general, above- and below-average discharges in winter–spring are related to El Niño and La Niña events, respectively. The temporal patterns of the observed and reconstructed records of the Puelo River streamflow show a general decreasing trend in the 1943–1999 period. Projected circulation changes for the next decades in the Southern Hemisphere would decrease summer–fall Puelo River streamflows with significant impacts on salmon production, tourism and hydropower generation.     

Low Frequency Streamflow Regimes over the Central United States: 1939–1998

Intra- to multi-decadal (6–30 year) streamflow regimes over the central United States during the late 20th century are identified and investigated here through a two-stage analysis. The first stage ranks mean annual flow rates during 1939–1998, calculates Mann–Whitney Ustatistics from samples of those rankings over running time windows, and then tests those U statistics for significance. This analysis of the records of 42 Hydro-Climatic Data Network stations over the Great Plains and Midwest reveals consistent patterns of highly ranked annual streamflow during time windows at the end of the century, with most beginning during the late 1960s and early 1970s and ending in either 1997 or 1998. Many of these stations are located in a critical agricultural region known as the Corn Belt. The second stage of analysis compares both the duration of abnormal flow periods and the frequency of hydrological surplus and drought conditions during the high flow years indicated by the first stage, relative to the remaining years of 1939–1998. Among gage stations in the climatologically drier western Corn Belt during the 1980s and 1990s there is a clear tendency toward extended periods of above normal flow, which results in more than a doubling in the average annual frequency of hydrological surplus days relative to previous years. These stations also show more than a 50% reduction in the average annual frequency of hydrological drought days relative to previous years. Similar but less pronounced shifts in hydrological regime are evident in the central and eastern Corn Belt, and in the Mississippi River at Vicksburg during 1973–1998. These results indicate that many areas of the central United States have shifted toward a climate regime of relative hydrological surplus during the closing decades of the 20th century.     

Quantile regression and clustering analysis of standardized precipitation index in the Tarim River Basin,Xinjiang, China

Because drought is a very common and widespread natural disaster, it has attracted a great deal of academic interest. Based on 12-month time scale standardized precipitation indices (SPI12) calculated from precipitation data recorded between 1960 and 2015 at 22 weather stations in the Tarim River Basin (TRB), this study aims to identify the trends of SPI and drought duration, severity, and frequency at various quantiles and to perform cluster analysis of drought events in the TRB. The results indicated that (1) both precipitation and temperature at most stations in the TRB exhibited significant positive trends during 1960–2015; (2) multiple scales of SPIs changed significantly around 1986; (3) based on quantile regression analysis of temporal drought changes, the positive SPI slopes indicated less severe and less frequent droughts at lower quantiles, but clear variation was detected in the drought frequency; and (4) significantly different trends were found in drought frequency probably between severe droughts and drought frequency.     

Spatiotemporal variability of four precipitation-based drought indices in Xinjiang,China

Global increases in duration and prevalence of droughts require detailed drought characterization at various spatial and temporal scales. In this study, drought severity in Xinjiang, China was investigated between 1961 and 2012. Using meteorological data from 55 weather stations, the UNEP (1993) index (I _A), Erinç’s aridity index (I _m), and Sahin’s aridity index (I _sh) were calculated at the monthly and annual timescales and compared to the Penman-Monteith based standard precipitation evapotranspiration index (SPEI_PM). Drought spatiotemporal variability was analyzed for north (NX), south (SX), and entire Xinjiang (EX). I _m could not be calculated at 51 stations in winter as T _max was below 0. At the monthly timescale, I _A, I _m, and I _sh correlated poorly to SPEI_PM because of seasonality and temporal variability, but annual I _A, I _m, and I _sh correlated well with SPEI_PM. Annual I _A, I _m, and I _sh showed strong spatial variability. The 15 extreme droughts denoted by monthly SPEI_PM occurred in NX but out of phase in SX. Annual precipitation, maximum temperature, and relative and specific humidity increased, while air pressure and potential evapotranspiration decreased over 1961–2012. The resulting increases in the four drought indices indicated that drought severity in Xinjiang decreased, because the local climate became warmer and wetter.

     

基于SPEI干旱指数的凉山州干旱特征分析

本文采用凉山州17个国家气象站1971~2017年的气象资料,利用基于Penman-Monteith模型的标准化降水蒸散指数SPEI,分析月、季、年不同时间尺度下凉山州SPEI干旱指数的时空分布状况,并以西昌气象站为代表进行了SPEI干旱指数的突变性M-K检验。结果表明:(1)标准化降水蒸散指数能较好地反映凉山州干旱发生程度;(2)凉山州干旱的年代际变化明显,20世纪70年代、80年代和21世纪10年代总体偏旱,20世纪90年代和21世纪00年代则相对较为湿润;(3)凉山州干旱发生频率空间分布不均,中部干旱发生频率高于北部和南部地区;(4)西昌市近30年来干旱总体偏轻,最近一次干湿突变发生于1987年;⑤各季节最近一次由干转湿的突变点,冬季在1999年、春季在1996年、夏季在1994年、秋季在1991年,呈逐季提前的趋势。      

Multivariate drought frequency estimation using copula method in Southwest China

This study reveals the impacts of climatic variable trends on drought severity in Xinjiang, China. Four drought indices, including the self-calibrating Palmer drought severity index (sc-PDSI), Erinç’s index (I _m), Sahin’s index (I _sh), and UNEP aridity index (AI), were used to compare drought severity. The ensemble empirical mode decomposition and the modified Mann-Kendall trend test were applied to analyze the nonlinear components and trends of the climatic variable and drought indices. Four and six climatic scenarios were generated in sc-PDSI, I _m, I _sh, and AI with different combinations of the observed and detrended climatic variables, respectively. In Xinjiang, generally increasing trends in minimal, average, and maximal air temperature (T _min, T _ave, T _max) and precipitation (P) were found, whereas a decreasing trend in wind speed at 2 m height (U ₂) was observed. There were significantly increasing trends in all of the four studied drought indices. Drought relief was more obvious in northern Xinjiang than in southern Xinjiang. The strong influences of increased P on drought relief and the weak influences of increased T _min, T _ave, and T _max on drought aggravation were shown by comparing four drought indices under different climate scenarios. Decreased U ₂ had a weak influence on drought, as shown by the AI in different climate scenarios. The weak influences of T and U ₂ were considered to be masked by the strong influences of P on droughts. Droughts were expected to be more severe if P did not increase, but were likely milder without an increase in air temperature and with a decrease in U ₂.