Spatial distribution and temporal trends in daily and monthly precipitation concentration indices in the upper reaches of the Huai River, China

Understanding precipitation variations on various timescales and their correlations is important for assessment of flood risk and utilization of water resources. In this study, the spatial and temporal patterns of precipitation concentration in the upper reaches of the Huai River, China, were investigated using two indices: the precipitation concentration index (PCI) and the concentration index (CI) for measuring seasonality and daily heterogeneity using monthly and daily precipitation series, respectively. In particular, the trends of PCI and CI were tested by the Mann–Kendall method, and relationship among PCI, CI and percentage of precipitation contributed by the rainiest days was analyzed by the linear correlation analysis. The results show a significant seasonality of the rainfall distribution and very in homogeneous temporal distribution of the daily rainfall in the south part of the study area, especially in the three reservoirs. Positive trends in the PCI and CI were found at most stations, although none of the PCI trends were statistically significant. Daily heterogeneity of the rainfall in a year is highly correlated with the heavy rainfall amount of the 15 % rainiest days, and seasonality in rainfall distribution over a year can be partly explained by the daily rainfall heterogeneity.     

Spatial and temporal characteristics of rainfall in a data-scarce region: case of Kinshasa and Bas-Congo in Democratic Republic of Congo

ABSTRACT

The aim of the present paper was to improve understanding of the rainfall dynamics in Bas-Congo and Kinshasa provinces, in Democratic Republic of Congo (DRC). The first objective of the study was achieved by analysing the spatial correlations of monthly, seasonal, annual and individual monthly rainfall amounts of Kinshasa and Bas-Congo. The second objective was achieved through investigating and quantifying the temporal trends and their spatial variations. The results demonstrated notably high average inter-station correlation of +0.63 for dry season series, followed by monthly rainfall series with an average inter-station correlation of +0.58. However, there was no station with a stable monthly rainfall regime, i.e. with mean precipitation concentration index lower than 10% (it varies between 14.2 and 21.9%). Moreover, Kinshasa experienced an increase of rainfall with an average annual rate of change of +4.59 mm/year for the period 1961–2006. The results will be helpful for efficient water resources management and for mitigating the adverse impacts of future extreme drought or flood occurrences.

Editor M.C. Acreman Associate editor N. Verhoest     

Study of indices for drought characterization in KBK districts in Orissa (India)

Drought is a temporary, random and regional climatic phenomenon, originating due to lack of precipitation leading to water deficit and causing economic loss. Success in drought alleviation depends on how well droughts are defined and their severity quantified. A quantitative definition identifies the beginning, end, spatial extent and the severity of drought. Among the available indices, no single index is capable of fully describing all the physical characteristics of drought. Therefore, in most cases it is useful and necessary to consider several indices, examine their sensitivity and accuracy, and investigate for correlation among them. In this study, the geographical information system‐based Spatial and Time Series Information Modeling (SPATSIM) and Daily Water Resources Assessment Modeling (DWRAM) software were used for drought analysis on monthly and daily bases respectively and its spatial distribution in both dry and wet years. SPATSIM utilizes standardized precipitation index (SPI), effective drought index (EDI), deciles index and departure from long‐term mean and median; and DWRAM employs only EDI. The analysis of data from the Kalahandi and Nuapada districts of Orissa (India) revealed that (a) droughts in this region occurred with a frequency of once in every 3 to 4 years, (b) droughts occurred in the year when the ratio of annual rainfall to potential evapotranspiration (Pae/PET) was less than 0·6, (c) EDI better represented the droughts in the area than any other index; (d) all SPI, EDI and annual deviation from the mean showed a similar trend of drought severity. The comparison of all indices and results of analysis led to several useful and pragmatic inferences in understanding the drought attributes of the study area. Copyright © 2007 John Wiley & Sons, Ltd.     

Temporal and spatial variability of annual and seasonal rainfall over Ethiopia

Abstract

Characterization of the seasonal and inter-annual spatial and temporal variability of rainfall in a changing climate is vital to assess climate-induced changes and suggest adequate future water resources management strategies. Trends in annual, seasonal and maximum 30-day extreme rainfall over Ethiopia are investigated using 0.5° latitude?×?0.5° longitude gridded monthly precipitation data. The spatial coherence of annual rainfall among contiguous rainfall grid points is also assessed for possible spatial similarity across the country. The correlation between temporally coinciding North Atlantic Multidecadal Oscillation (AMO) index and annual rainfall variability is examined to understand the underlying coherence. In total 381 precipitation grid points covering the whole of Ethiopia with five decades (1951–2000) of precipitation data are analysed using the Mann-Kendall test and Moran spatial autocorrelation method. Summer (July–September) seasonal and annual rainfall data exhibit significant decreasing trends in northern, northwestern and western parts of the country, whereas a few grid points in eastern areas show increasing annual rainfall trends. Most other parts of the country exhibit statistically insignificant trends. Regions with high annual and seasonal rainfall distribution exhibit high temporal and spatial correlation indices. Finally, the country is sub-divided into four zones based on annual rainfall similarity. The association of the AMO index with annual rainfall is modestly good for northern and northeastern parts of the country; however, it is weak over the southern region.

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

Citation Wagesho, N., Goel, N.K., and Jain, M.K. 2013. Temporal and spatial variability of annual and seasonal rainfall over Ethiopia. Hydrological Sciences Journal, 58 (2), 354–373.     

A hybrid stochastic-weather-generation method for temporal disaggregation of precipitation with consideration of seasonality and within-month variations

Linking atmospheric and hydrological models is challenging because of a mismatch of spatial and temporal resolutions in which the models operate: dynamic hydrological models need input at relatively fine temporal (daily) scale, but the outputs from general circulation models are usually not realistic at the same scale, even though fine scale outputs are available. Temporal dimension downscaling methods called disaggregation are designed to produce finer temporal-scale data from reliable larger temporal-scale data. Here, we investigate a hybrid stochastic weather-generation method to simulate a high-frequency (daily) precipitation sequence based on lower frequency (monthly) amounts. To deal with many small precipitation amounts and capture large amounts, we divide the precipitation amounts on rainy days (with non-zero precipitation amounts) into two states (named moist and wet states, respectively) by a pre-defined threshold and propose a multi-state Markov chain model for the occurrences of different states (also including non-rain days called dry state). The truncated Gamma and censored extended Burr XII distributions are then employed to model the precipitation amounts in the moist and wet states, respectively. This approach avoids the need to deal with discontinuity in the distribution, and ensures that the states (dry, moist and wet) and corresponding amounts in rainy days are well matched. The method also considers seasonality by constructing individual models for different months, and monthly variation by incorporating the low-frequency amounts as a model predictor. The proposed method is compared with existing models using typical catchment data in Australia with different climate conditions (non-seasonal rainfall, summer rainfall and winter rainfall patterns) and demonstrates better performances under several evaluation criteria which are important in hydrological studies.     

Spatial distribution and temporal trends of rainfall and erosivity in the Eastern Africa region

Soil erosion by water is one of the main environmental concerns in the drought‐prone Eastern Africa region. Understanding factors such as rainfall and erosivity is therefore of utmost importance for soil erosion risk assessment and soil and water conservation planning. In this study, we evaluated the spatial distribution and temporal trends of rainfall and erosivity for the Eastern Africa region during the period 1981–2016. The precipitation concentration index, seasonality index, and modified Fournier index have been analysed using 5 × 5‐km resolution multisource rainfall product (Climate Hazards Group InfraRed Precipitation with Stations). The mean annual rainfall of the region was 810 mm ranging from less than 300 mm in the lowland areas to over 1,200 mm in the highlands being influenced by orography of the Eastern Africa region. The precipitation concentration index and seasonality index revealed a spatial pattern of rainfall seasonality dependent on latitude, with a more pronounced seasonality as we go far from the equator. The modified Fournier index showed high spatial variability with about 55% of the region subject to high to very high rainfall erosivity. The mean annual R‐factor in the study region was calculated at 3,246 ± 1,895 MJ mm ha^?1 h^?1 yr^?1, implying a potentially high water erosion risk in the region. Moreover, both increasing and decreasing trends of annual rainfall and erosivity were observed but spatial variability of these trends was high. This study offers useful information for better soil erosion prediction as well as can support policy development to achieve sustainable regional environmental planning and management of soil and water resources.     

A new standardized Palmer drought index for hydro‐meteorological use

Accepting the concept of standardization introduced by the standardized precipitation index, similar methodologies have been developed to construct some other standardized drought indices such as the standardized precipitation evapotranspiration index (SPEI). In this study, the authors provided deep insight into the SPEI and recognized potential deficiencies/limitations in relating to the climatic water balance it used. By coupling another well‐known Palmer drought severity index (PDSI), we proposed a new standardized Palmer drought index (SPDI) through a moisture departure probabilistic approach, which allows multi‐scalar calculation for accurate temporal and spatial comparison of the hydro‐meteorological conditions of different locations. Using datasets of monthly precipitation, temperature and soil available water capacity, the moisture deficit/surplus was calculated at multiple temporal scales, and a couple of techniques were adopted to adjust corresponding time series to a generalized extreme value distribution out of several candidates. Results of the historical records (1900–2012) for diverse climates by multiple indices showed that the SPDI was highly consistent and correlated with the SPEI and self‐calibrated PDSI at most analysed time scales. Furthermore, a simple experiment of hypothetical temperature and/or precipitation change scenarios also verified the effectiveness of this newly derived SPDI in response to climate change impacts. Being more robust and preferable in spatial consistency and comparability as well as combining the simplicity of calculation with sufficient accounting of the physical nature of water supply and demand relating to droughts, the SPDI is promising to serve as a competent reference and an alternative for drought assessment and monitoring. Copyright © 2013 John Wiley & Sons, Ltd.     

A drought climatology for Mauritius using the standardized precipitation index

This study presents a high-resolution and multi-temporal drought climatology for Mauritius based on calculated standardized precipitation index (SPI) using mean monthly rainfall for the period 1953–2007. A monthly mean SPI varying from +3.4 to ?2.7 indicates the occurrence of extremely wet and dry conditions, and collocated SPI indicates more frequent mild drought conditions. Spatial maps of rainfall trends and SPI show mostly neutral to severely dry conditions, but sparse regions of extremely wet and dry conditions are also observed. An increase in the frequency of dry years after the 1990s is noted, while most of the extreme wet conditions are found to have occurred between 1972 and 1988. More frequent short-duration wet events are observed on the 3- and 6-month time scales compared to dry events. On the 12- and 24-month time scales the frequency of both dry and wet periods is almost the same, with the dry events lasting longer.     

Drought assessment in a south Mediterranean transboundary catchment

ABSTRACT

Predicting the impacts of climate change on water resources remains a challenging task and requires a good understanding of the dynamics of the forcing terms in the past. In this study, the variability of precipitation and drought patterns is studied over the Mediterranean catchment of the Medjerda in Tunisia based on an observed rainfall dataset collected at 41 raingauges during the period 1973–2012. The standardized precipitation index and the aridity index were used to characterize drought variability. Multivariate and geostatistical techniques were further employed to identify the spatial variability of annual rainfall. The results show that the Medjerda is marked by a significant spatio-temporal variability of drought, with varying extreme wet and dry events. Four regions with distinct rainfall regimes are identified by utilizing the K-means cluster analysis. A principal component analysis identifies the variables that are responsible for the relationships between precipitation and drought variability.     

Temporal change of spatial heterogeneity and its effect on regional trend of annual precipitation heterogeneity indices

A statistical test on climate and hydrological series from different spatial resolution could obtain different regional trend due to spatial heterogeneity and its temporal variability. In this study, annual series of the precipitation heterogeneity indices of concentration index (CI) and the number of wet days (NW) along with annual total amount of precipitation were calculated based on at‐site daily precipitation series during 1962–2011 in the headwater basin of the Huaihe River, China. The regional trends of the indices were first detected based on at‐site series by using the aligned and intrablock methods, and field significance tests that consider spatial heterogeneity over sites. The detected trends were then compared with the trends of the regional index series derived from daily areal average precipitation (DAAP), which averages at‐site differences and thus neglects spatial heterogeneity. It was found that the at‐site‐based regional test shows increasing trends of CI and NW in the basin, which follows the test on individual sites that most of sites were characterized by increasing CI and NW. However, the DAAP‐derived regional series of CI and NW were tested to show a decreasing trend. The disparity of the regional trend test on at‐site‐based regional series and the DAAP‐derived regional series arises from a temporal change of the spatial heterogeneity, which was quantified by the generalized additive models for location, scale, and shape. This study highlights that compared with averaging indices, averaging at‐site daily precipitation could lead to an error in the regional trend inference on annual precipitation heterogeneity indices. More attention should be paid to temporal variability in spatial heterogeneity when data at large scales are used for regional trend detection on hydro‐meteorological events associated with intra‐annual heterogeneity.     

全球植被叶面积指数对温度和降水的响应研究

利用一套新的遥感信息反演的叶面积指数(LAI)数据和生物气候数据,建立了全球尺度的LAI与降水及温度的总体相关和距平相关,用以揭示全球尺度的植被季节和年际的变化对气候变化的响应特征.结果发现,全球尺度植被与气候因子的季节和年际变化随不同的生态系统差异明显.植被LAI与温度的总体正相关的最大值出现在北半球的中高纬度地区;LAI与降水的总体正相关高值(＞0.8)出现在亚洲东部、北美洲北部腹地和热带非洲北部的Sahel地区;最大的LAI与温度的正距平相关(0.4-0.6)出现在东南亚南部、非洲Sahel地区的南部和巴西东部等热带地区;而从LAI与降水的距平相关来看,最明显的特征是出现在西伯利亚、亚洲北部和北美西北部的强的负距平相关.本文进一步阐明了出现相关特征差异的陆-气过程物理机制.     

基于MODIS数据的干旱遥感监测研究

干旱是影响社会发展和农业生产的重要因素之一。本文基于EOS/MODIS卫星遥感资料,选取江西省2001-2006年的NDVI时间序列数据,分析了NDVI对干旱的响应规律。计算了NDVI与气温、降水之间的关系。并提取植被状态指数(VCI),分析VCI与气温距平、降水距平的空间分布规律。结果表明:2003年江西夏季旱灾以高温少雨天气为主。这一时期的NDVI数值明显低于其他年份同一时期的NDVI值。气温温度越高,NDVI值越大;日照时数时间越长,NDVI值越大;降水量越高,NDVI值越大;降水距平百分率越高,VCI值越高;平均温度距平越小,VCI值越高。说明气候因素对NDVI指数和VCI指数有很大影响。研究表明,基于MODIS的植被指数可以反映旱灾的时空分布规律。     

Scenarios of global municipal water-use demand projections over the 21st century

Abstract

A comparison study is presented of three methods for evaluating trends in drought frequency: the standardized precipitation index (SPI), the Palmer drought severity index (PDSI), and a new method for estimation of dry spells (DS), which is based on average daily temperature and precipitation, and takes into account the length of a spell. The methods were applied to climate data from 450 stations in the Elbe River basin for the period 1951–2003, as well as data from several stations with longer observed time series. Statistical methods were used to calculate trend lines and evaluate the significance of detected trends. The dry spells estimated with the new method show significant trends in the whole lowland part of the Elbe basin during the last 53 years, and at the 10% level almost everywhere in the German part of the basin excluding mountains and the area around the river mouth. The SPI and PDSI methods also revealed significant trends, but for smaller areas in the lowland. The new DS method provides a useful supplement to other drought indices for the detection of trends in drought frequency. Furthermore, the DS method was able to detect statistically significant trends in areas where the other two methods failed to find significant trends, e.g. in the loess region in the southwest of the German part of the basin, where small insignificant changes in climate can lead to significant changes in water fluxes. This is important, because the loess region is the area within the basin having the highest crop yields. Therefore, additional research has to be done to investigate possible impacts of detected trends on water resources availability, and possible future trends in drought frequency under climate change.     

Trends in precipitation extremes over the Yellow River basin in North China: Changing properties and causes

The Mann–Kendall test, composite analysis, and 68 high‐quality meteorological stations were used to explore the spatiotemporal variations and causes of precipitation extremes over the Yellow River basin (YRB) during the period of 1960–2011. Results showed that (a) the YRB is characterized by decreases of most precipitation indices, excluding the simple daily intensity index, which has increasing trends in most locations, suggesting that the intensity of rainfall and the probability of occurrence of droughts have increased during the last decades. (b) Trends of extreme precipitation show mixed patterns in the lower reach of the YRB, where drought–flood disasters have increased. The increases in heavy rainfall and decreases in consecutive wet days in recent years over the northwestern portions of the YRB indicate that the intensity and frequency of above‐normal precipitation have been trending upward in domains. In the central‐south YRB, the maximum 1‐day precipitation (RX1day) and precipitation on extremely wet days (R99p) have significantly increased, whereas the number of consecutive dry days has declined; these trends suggest that the intensity of precipitation extremes has increased in those regions, although the frequency of extreme and total rainfall has decreased. (c) The spatial distributions of seasonal trends in RX1day and maximum 5‐day precipitation (RX5day) exhibited less spatial coherence, and winter is becoming the wettest season regionwide, particularly over the central‐south YRB. (d) There were multiple and overlapping cycles of variability for most precipitation indices, indicating variations of time and frequency. (e) Elevation is intimately correlated with precipitation indices, and a weakening East Asian summer monsoon during 1986–2011 compared to that in 1960–1985 may have played an important role in the declines in most indices over the YRB. Therefore, the combined effects from local and teleconnection forcing factors have collectively influenced the variations in precipitation extremes across the YRB. This study may provide valuable evidence for the effective management of water resources and the conduct of agricultural activities at the basin scale.     

A two steps disaggregation method for highly seasonal monthly rainfall

 The need for high resolution rainfall data at temporal scales varying from daily to hourly or even minutes is a very important problem in hydrology. For many locations of the world, rainfall data quality is very poor and reliable measurements are only available at a coarse time resolution such as monthly. The purpose of this work is to apply a stochastic disaggregation method of monthly to daily precipitation in two steps: 1. Initialization of the daily rainfall series by using the truncated normal model as a reference distribution. 2.␣Restructuring of the series according to various time series statistics (autocorrelation function, scaling properties, seasonality) by using a Markov chain Monte Carlo based algorithm. The method was applied to a data set from a rainfall network of the central plains of Venezuela, in where rainfall is highly seasonal and data availability at a daily time scale or even higher temporal resolution is very limited. A detailed analysis was carried out to study the seasonal and spatial variability of many properties of the daily rainfall as scaling properties and autocorrelation function in order to incorporate the selected statistics and their annual cycle into an objective function to be minimized in the simulation procedure. Comparisons between the observed and simulated data suggest the adequacy of the technique in providing rainfall sequences with consistent statistical properties at a daily time scale given the monthly totals. The methodology, although highly computationally intensive, needs a moderate number of statistical properties of the daily rainfall. Regionalization of these statistical properties is an important next step for the application of this technique to regions in where daily data is not available.     

Spatial and temporal variation of extreme precipitation indices in the Yangtze River basin, China

Regional characteristics of extreme precipitation indices (EPI) of precipitation magnitude, intensity and persistence were analyzed based on a daily rainfall dataset of 135 stations during the period of 1961–2010 in the Yangtze River basin, China. The spatial distribution of temporal trends of the selected indices was regionally mapped and investigated by using non-parametric test method. Future projections of EPI changes derived from the output of general circulation model (HadCM3) under the SRES A2 and B2 emission scenarios were downscaled and analyzed. The results show that: (a) there is not a general significant increasing or decreasing trend in EPI for the Yangtze River basin based on historical recorded data; (b) the automated statistical downscaling method-based precipitation captures some spatial distribution of the EPI and the bias correction can improve the simulation results; (c) a mixed pattern of positive and negative changes is observed in most of the nine indices under both scenarios in the first half of twenty-first century, and they increase continuously in the second half of twenty-first century; and (d) the concurrent increase in the heavy rain and drought indices indicates the possibility of the sudden change from drought to water logging in the lower region of Yangtze River basin.     

青海湖流域近六百年来的气候变化与湖水位下降原因

根据青海湖流域及其邻近地区树木年轮资料重建的历史时期气候资料序列,给出了流域近六百年来的主要冷、暖、干、湿期,并对器测时期的气候变化趋势作了分析。指出,近百年来气候暖干化是造成湖水位下降的主要原因;对于湖水位年际变化与前期降水影响系统、不同气候类型以及地面气象要素的关系作了统计分析。     

Multi-scale analysis of meteorological drought risks based on a Bayesian interpolation approach in Huai River basin,China

A scheme for meteorological drought analysis at various temporal and spatial scales based on a spatial Bayesian interpolation of drought severity derived from Standardized Precipitation Index (SPI) values at observed stations is presented and applied to the Huai River basin of China in this paper, using monthly precipitation record from 1961 to 2006 in 30 meteorological stations across the basin. After dividing the study area into regular grids, drought condition in gauged sites are classified into extreme, severe, moderate and non drought according to SPIs at month, seasonal and annual time scales respectively while that in ungauged grids are explained as risks of various drought severities instead of single state by a Bayesian interpolation. Subsequently, temporal and spatial patterns of drought risks are investigated statistically. Main conclusions of the research are as follows: (1) drought at seasonal scale was more threatening than the other two time scales with a larger number of observed drought events and more notable variation; (2) results of the Mann–Kendall test revealed an upward trend of drought risk in April and September; (3) there were larger risks of extreme and severe drought in southern and northwestern parts of the basin while the northeastern areas tended to face larger risks of moderate drought. The case study in Huai River basin suggests that the proposed approach is a viable and flexible tool for monitoring meteorological drought at multiple scales with a more specific insight into drought characteristics at each severity level.     

Spatial mapping of drought in Zambia using regional frequency analysis

Regional frequency analysis based on L-moments was applied to assess the spatial extent of meteorological droughts in tandem with their return periods in Zambia. Weather station monthly rainfall data were screened to form homogeneous sub-regions-, validated by a homogeneity criterion and fitted by a generalized extreme value distribution using goodness-of-fit test statistics. Predictor equations at regional scale for L-moment ratios and mean annual precipitation were developed to generate spatial maps of meteorological drought recurrences. The 80% of normal rainfall level and two thresholds of 60% and 70% were synonymous with moderate and severe droughts, respectively. Droughts were more severe in the south than in the north of Zambia. The return periods for severe and moderate droughts showed an overlapping pattern in their occurrence at many locations, indicating that in certain years droughts can affect the entire country. The extreme south of Zambia is the most prone to drought.     

Characterizing the changing behaviours of precipitation concentration in the Yangtze River Basin,China

The statistical characteristics of precipitation on the daily resolution play an important role not only in the risk assessment of floods and droughts but also in the land use management. In this study, spatial and temporal patterns of the precipitation concentration in the Yangtze River Basin are investigated by using three indices, i.e. precipitation concentration index (CI), precipitation concentration degree (PCD) and precipitation concentration period (PCP). Based on meteorological data of 147 stations for the period of 1960–2008, non‐parametric trend analysis and wavelet transformation analysis are employed to detect the temporal variation of these indices. Spatial variability of precipitation concentration indices and their trends are analysed and demonstrated with the help of GIS tools. The results indicate the following: (i) The high precipitation CI values mainly distribute in the middle region of the Yangtze River Basin, whereas the lower and lowest CI values are found in the lower and upper regions, respectively. A roughly east–west gradient for PCD value and PCP value varies from 0.26 to 0.77 and from 123 to 197, respectively. (ii) The analysis results of precipitation CI trends for different periods (i.e. recent 40, 30 and 20 years) show that the middle region of the Yangtze River Basin experienced a transition from decreasing precipitation CI to increasing precipitation CI during the last two decades, although the decreasing long‐term trends in the precipitation CI are not significant in most areas during the period of 1960–2008. (iii) The upper basin, middle basin and lower basin are, respectively, dominated by the significant decreasing, increasing and no significant trends in PCD. A dominance of insignificant PCP trends is observed in the entire basin during 1960–2008 despite that a few areas in the upper region are characterized by significant decreasing trends. (iv) Interdecadal oscillations can be found for three precipitation indices, but with no constant periodicity. Furthermore, good positive correlations have been detected between precipitation CI and PCD, whereas insignificant correlation coefficients of PCP with precipitation are common in the basin. The results can provide beneficial reference to water resource and eco‐environment and mitigation to flood or drought hazards in the Yangtze River Basin for policymakers and stakeholders. Copyright © 2012 John Wiley & Sons, Ltd.