Stochastic Prediction of Drought Class Transitions

This paper aims at the stochastic characterization of droughts applying Markov chains modeling to drought class transitions derived from SPI time series. Several sites in Southern Portugal having updated data on precipitation available were considered. The drought class probabilities, the expected residence time in each class of severity, the expected time for the transition between drought classes and the drought severity class predictions 1, 2, or 3 months ahead have been obtained. Those predictions are then compared with observed drought classes for the recent drought periods of 2003–2006. In addition, the estimation of the cumulated precipitation deficits, amount of monthly precipitation needed to decrease drought severity, and foreseen SPI values depending on different precipitation scenarios are also presented as complementing the prediction of drought class transitions.     

Prediction of SPI Drought Class Transitions Using Markov Chains

Using the SPI relative to 67 years data sets, a Markov chains approach has been utilized for several locations in Alentejo, southern Portugal, to characterize the stochasticity of droughts, which allowed predicting the transition from a class of severity to another up to 3 months ahead. Markov models were applied using both the homogeneous and non-homogeneous formulations. The results of the application of the Markov models are presented and discussed, showing in particular the usefulness of adopting a non-homogeneous formulation, which allows to differentiate predictions in relation to the initial month considered, thus understanding the probable evolution of a drought as influenced by the climate and, in particular, the seasonality of rainfall. However, these results, which are promising in view of drought management, require further developments and to be associated with other predictive tools of stochastic or physical nature. Possible approaches on using predictions of drought class transitions in view of drought risk management are also discussed.     

Analysis of Impacts of Climate Change and Human Activities on Hydrological Drought: a Case Study in the Wei River Basin,China

Climate change and human activity are the two major drivers that can alter hydrological cycle processes and influence the characteristics of hydrological drought in river basins. The present study selects the Wei River Basin (WRB) as a case study region in which to assess the impacts of climate change and human activity on hydrological drought based on the Standardized Runoff Index (SRI) on different time scales. The Generalized Additive Models in Location, Scale and Shape (GAMLSS) are used to construct a time-dependent SRI (SRI_var) considering the non-stationarity of runoff series under changing environmental conditions. The results indicate that the SRI_var is more robust and reliable than the traditional SRI. We also determine that different driving factors can influence the hydrological drought evolution on different time scales. On shorter time scales, the effects of human activity on hydrological drought are stronger than those of climate change; on longer time scales, climate change is considered to be the dominant factor. The results presented in this study are beneficial for providing a reference for hydrological drought analysis by considering non-stationarity as well as investigating how hydrological drought responds to climate change and human activity on various time scales, thereby providing scientific information for drought forecasting and water resources management over different time scales under non-stationary conditions.     

不同季节气象干旱向水文干旱的传播及其动态变化

研究变化环境下气象干旱向水文干旱的传播与影响机制,有利于揭示水文干旱的形成过程与机理,从而建立基于气象干旱的水文干旱预警.为揭示不同季节气象干旱向水文干旱的传播动态变化及其驱动因素,本研究以无定河、窟野河和沁河流域为研究区域,采用标准化降水指数(SPI)和标准化径流指数(SRI)分别表征气象干旱和水文干旱,分析气象、水...     

Hydro-Climatological Drought Analyses and Projections Using Meteorological and Hydrological Drought Indices: A Case Study in Blue River Basin, Oklahoma

Understanding the characteristics of historical droughts will benefit water resource managers because it will reveal the possible impacts that future changes in climate may have on drought, and subsequently, the availability of water resources. The goal of this study was to reconstruct historical drought occurrences and assess future drought risk for the drought-prone Blue River Basin in Oklahoma, under a likely changing climate using three types of drought indices, i.e., Standardized Precipitation Index (SPI), Palmer Drought Severity Index (PDSI) and Standardized Runoff Index (SRI). No similar research has been conducted in this region previously. Monthly precipitation and temperature data from the observational period 1950?C1999 and over the projection period 2010?C2099 from 16 statistically downscaled Global Climate Models (GCM) were used to compute the duration, severity, and extent of meteorological droughts. Additionally, soil moisture, evapotranspiration (ET), and runoff data from the well-calibrated Thornthwaite Monthly Water Balance Model were used to examine drought from a hydrological perspective. The results show that the three indices captured the historical droughts for the past 50?years and suggest that more severe droughts of wider extent are very likely to occur over the next 90?years in the Blue River Basin, especially in the later part of the 21st century. In fact, all three indices display lower minimum values than those ever recorded in the past 50?years. This study also found that SRI and SPI (PDSI) had a correlation coefficient of 0.81 (0.78) with a 2-month (no appreciable) lag time over the 1950?C2099 time period across the basin. There was relatively lower correlation between SPI and PDSI over the same period. Although this study recommends that PDSI and SRI are the most suitable indices for assessing future drought risks under an increasingly warmer climate, more drought indices from ecological and socioeconomic perspectives should be investigated and compared to provide a complete picture of drought and its potential impacts on the dynamically coupled nature-human system.     

Utilization of the Bayesian Method to Improve Hydrological Drought Prediction Accuracy

This study established a hydrological drought forecasting system based on the Bayesian method and evaluated its utilization for South Korea. The regression result between Historical Runoff (HR) and Ensemble Streamflow Prediction Runoff (ESP_R) was used as prior information in the Bayesian method. Additionally Global seasonal forecast System 5 Runoff (GS5_R) produced using a dynamic prediction method was used in a likelihood function. Bayesian Runoff (BAY_R), as posterior information, was generated and compared with the ESP_R and GS5_R results for predictive ability evaluation. The Standardized Runoff Index (SRI) was selected for the drought prediction, and the BAY_SRI, GS5_SRI and ESP_SRI were computed using BAY_R, GS5_R and ESP_R, respectively. The Correlation Coefficient (CC), Nash-Sutcliffe Efficiency (NSE) and Receiver Operating Characteristic (ROC) score of BAY_SRI were the highest, and the Root Mean Square Error (RMSE) of BAY_SRI was the lowest among the methods. The Bayesian method improved the behavioral and quantitative error of drought prediction and the predictive ability of the occurrence of drought. In particular, the simulation accuracy was significantly improved during the flood season. Additionally, BAY_SRI represented past drought scenarios better than did the other two methods. Overall, we found that the Bayesian method could be applied for hydrological drought predictions for based on 1- and 2-month lead times.     

Comparison of Meteorological,Hydrological and Agricultural Drought Responses to Climate Change and Uncertainty Assessment

A comparison study of meteorological, hydrological and agricultural drought responses to climate change resulting from different General Circulation Models (GCMs), emission scenarios and hydrological models is presented. Drought variations from 1961–2000 to 2061–2100 in Huai River basin above Bengbu station in China are investigated. Meteorological drought is recognized by the Standardized Precipitation Index (SPI) while hydrological drought and agricultural drought are indexed with a similar standardized procedure by the Standardized Runoff Index (SRI) and Standardized Soil Water Index (SSWI). The results generally approve that hydrological and agricultural drought could still pose greater threats to local water resources management in the future, even with a more steady background to meteorological drought. However, the various drought responses to climate change indicate that uncertainty arises in the propagation of drought from meteorological to hydrological and agricultural systems with respect to alternative climates. The uncertainty in hydrological model structure, as well as the uncertainties in GCM and emission scenario, are aggregated to the results and lead to much wider variations in hydrological and agricultural drought characteristics. Our results also reveal that the selection of hydrological models can induce fundamental differences in drought simulations, and the role of hydrological model uncertainty may become dominating among the three uncertainty sources while recognizing frequency of extreme drought and maximum drought duration.     

Analysis of spatio-temporal evolution of droughts in Luanhe River Basin using different drought indices

Based on the monthly precipitation and air temperature from 1960 to 1989 in the Luanhe River Basin, the standardized precipitation evapotranspiration index(SPEI) and standardized precipitation index(SPI) at three- and six-month time scales and the self-calibrating Palmer drought severity index(sc-PDSI) were calculated to evaluate droughts in the study area. Temporal variations of the drought severity from 1960 to1989 were analyzed and compared based on the results of different drought indices, and some typical drought events were identified. Spatial distributions of the drought severity according to the indices were also plotted and investigated. The results reveal the following: the performances of different drought indices are closely associated with the drought duration and the dominant factors of droughts; the SPEI is more accurate than the SPI when both evaporation and precipitation play important roles in drought events; the drought severity shown by the sc-PDSI is generally milder than the actual drought severity from 1960 to 1989; and the evolution of the droughts is usually delayed according to the scPDSI. This study provides valuable references for building drought early warning and mitigation systems in the Luanhe River Basin.     

黄河流域气象干旱与水文干旱时空特征及其传递关系EI北大核心CSCD

基于标准化降水蒸散指数(SPEI)和标准化径流指数(SRI),比较了黄河流域气象干旱和水文干旱的时空分布差异,分析了二者时间尺度上的关联性,并选取典型干旱事件进一步探讨了两种干旱类型的传递关系。结果表明:两种干旱类型空间上有相似的趋势和频次,但在黄河源区和黄河中南部(渭河流域)差异显著,其干旱历时均有随年代延长的趋势,水文干旱历时增长尤为明显;在时间尺度上,SPEI与SRI在大部分区域基本一致,但在黄河源区和渭河流域差异较大,尤其是短时间尺度上差异更显著;气象干旱与水文干旱并非一一对应,多场短历时间断气象干旱受时滞效应、异常气象波动等影响,可能引发一场长历时连续水文干旱或多场短历时间断水文干旱,一场长历时连续气象干旱强度衰减可能引发多场短历时间断水文干旱。     

An Integration of Statistics Temporal Methods to Track the Effect of Drought in a Shallow Mediterranean Lake

During the last decades, a progressive decrease of water level in shallow Mediterranean lakes was recorded. This contribution tried to identify whether the rapid decrease of the Lake Doiran (N. Greece) water level was associated with drought phenomena. Drought characteristics over the study area were revealed by employing the Standardized Precipitation Index (SPI) in different time scales. Negative trends of the SPI drought index were recognized by using the Mann-Kendall non parametric test, which suggested that drought conditions were intensified through time. The impact of the intense drought phenomena to the lake??s water level became evident by employing the Pearson correlation coefficient. A year ahead forecast of future drought conditions was achieved by training a hybrid ARIMA/ANN model. The predicted results indicated that mild drought conditions should be anticipated in the future and the water level would further drop as well.     

A New Non-stationary Hydrological Drought Index Encompassing Climate Indices and Modified Reservoir Index as Covariates

Due to accelerating climate variability and intensified anthropogenic activities, the hypothesis of stationarity of data series is no longer applicable, questioning the reliability of the traditional drought index. Thus, it is critical to develop a non-stationary hydrological drought index that takes into account the joint impacts of climate and anthropogenic changes in a drought assessment framework. In this study, using the Generalized Additive Model for Location, Scale and Shape (GAMLSS), a new Non-stationary Standardized Runoff Index (NSRI) was developed combining climate indices (CI) and modified reservoir index (MRI) as explanatory variables. This novel index was applied to the hydrological drought assessment of the Hanjiang River basin (HRB) in China, and its reliability was assessed by comparing with the traditional Standardized Runoff Index (SRI). Results indicated that the optimal non-stationary model with CI and MRI as covariates performed better than did other models. Furthermore, NSRI was more robust in identifying extreme drought events and was more effective in the study region than the conventional SRI. In addition, based on the method of Breaks for Additive Seasonal and Trend (BFAST), it was found that there were two change points in 1981 and 2003 for the NSRI series at four hydrological stations in the HRB, which indicated that hydrological drought in the basin had a prominent non-stationary behavior. Our findings may provide significant information for regional drought assessment and water resources management from a changing environment perspective.

     

南盘江流域水文干旱对气象干旱的响应特征研究

选取南盘江流域3个站点40年(1970年-2009年)的逐月径流资料和20个站点同期逐月降水资料,计算标准化径流指数(SSFI)和不同时间尺度的标准化降水指数(SPI),从中选取水文干旱样本和同期的SPI进行统计分析,研究水文干旱对气象干旱的响应特征。结果表明:南盘江流域SSFI对SPI具有良好的响应关系;SSFI对SPI的响应关系随时间尺度的不同相关性不同;总体来看,流域内水文干旱对气象干旱的响应时间约为6个月。     

西南地区气象干旱向水文干旱传播的特征

为了解西南地区气象干旱向水文干旱传播的特征,采用西南地区1968—2017年101个气象站观测资料和8个水文站月径流资料,计算了标准化降雨蒸散发指数(SPEI)和标椎化径流指数(SRI),基于皮尔逊相关系数(PCC)确定了干旱响应时间并结合游程理论识别、融合和剔除干旱事件,构建了线性干旱传播模型并确定了西南地区部分流域气象干旱向水文干旱传播的触发阈值。结果表明：西南地区干旱响应时间为2～7月;水文干旱敏感度分布与气象干旱传播率分布较为一致;干旱烈度传播阈值较小的流域,水文干旱事件历时更长。     

滦河流域气象干旱向水文干旱传播特征及风险分析

干旱是一种复杂的自然灾害,气象干旱可能导致水文干旱等灾害,严重影响社会经济发展。探明气象干旱向水文干旱传播的特征及规律,可为减小干旱损失、保障流域供水用水安全提供技术支持。本文基于滦河山区1960—2017年的气象水文数据,应用游程原理识别气象水文干旱事件,甄别二者间的传播特征,并借助Copula模型评估气象干旱向水文干旱的风险和干旱传播的临界关系。结果表明：（1）在1960—2017年期间,与气象干旱事件相比,水文干旱事件具有频率低、历时长、峰值低的特点;（2）滦河地区气象干旱和水文干旱传播关系以单场气象干旱向单场水文干旱传播为主;（3）气象干旱向水文干旱的传播存在明显的滞后效应,从上游至下游地区干旱滞后时间依次增长;（4）Gumbel Copula函数能够更准确地评估该流域干旱传播风险,结果显示上游地区发生干旱传播的风险低于下游地区,上、下游地区气象干旱发展成水文干旱的临界历时分别为0.93个月和1.26个月,临界峰值强度分别为0.66和0.44。本研究可为评价不同干旱事件间的传播与演变关系,构建流域干旱风险评价模型提供新思路。     

A Water Balance Derived Drought Index for Pinios River Basin, Greece

This study estimates hydrological drought characteristics using a water balance derived drought index in Pinios river basin, Thessaly, Greece. The concept of hydrological management at subwatershed scale has been adopted because it encompasses the areal extent of a drought event. Fourteen (14) sub-watersheds of Pinios river basin were delineated according to the major tributaries of Pinios river using GIS. For the assessment of hydrological drought, because none of the sub-watersheds have flow gauge stations at their outlets, a six-parameter monthly conceptual water balance model (UTHBAL model), has been applied regionally to simulate runoff for the period October 1960?CSeptember 2002. The synthetic runoff was normalized through Box-Cox transformation and standardized to the mean runoff to produce the water balance derived drought index for hydrological drought assessment. The standardized precipitation index (SPI) at multiple time scales and four indices of the Palmer method (i.e. PDSI, WPLM, PHDI and the Palmer moisture anomaly Z-index) were also calculated to assess hydrological droughts. The results showed that the water balance derived drought index is a good indicator of hydrological drought in all sub-watersheds, since is capable to quantify drought severity and duration. Furthermore, the drought index provides guidance on the selection of an appropriate meteorological drought index for operational hydrological drought monitoring. Hence, SPI at 3- and 6-month timescales and the WPLM could be used along with the water balance derived drought index in risk and decision analyses at the study area.     

Drought forecasting using the Standardized Precipitation Index

Unlike other natural disasters, drought events evolve slowly in time and their impacts generally span a long period of time. Such features do make possible a more effective drought mitigation of the most adverse effects, provided a timely monitoring of an incoming drought is available. Among the several proposed drought monitoring indices, the Standardized Precipitation Index (SPI) has found widespread application for describing and comparing droughts among different time periods and regions with different climatic conditions. However, limited efforts have been made to analyze the role of the SPI for drought forecasting. The aim of the paper is to provide two methodologies for the seasonal forecasting of SPI, under the hypothesis of uncorrelated and normally distributed monthly precipitation aggregated at various time scales k. In the first methodology, the auto-covariance matrix of SPI values is analytically derived, as a function of the statistics of the underlying monthly precipitation process, in order to compute the transition probabilities from a current drought condition to another in the future. The proposed analytical approach appears particularly valuable from a practical stand point in light of the difficulties of applying a frequency approach due to the limited number of transitions generally observed even on relatively long SPI records. Also, an analysis of the applicability of a Markov chain model has revealed the inadequacy of such an approach, since it leads to significant errors in the transition probability as shown in the paper. In the second methodology, SPI forecasts at a generic time horizon M are analytically determined, in terms of conditional expectation, as a function of past values of monthly precipitation. Forecasting accuracy is estimated through an expression of the Mean Square Error, which allows one to derive confidence intervals of prediction. Validation of the derived expressions is carried out by comparing theoretical forecasts and observed SPI values by means of a moving window technique. Results seem to confirm the reliability of the proposed methodologies, which therefore can find useful application within a drought monitoring system.     

基于VIC模型的滦河流域综合干旱指数的构建与应用

干旱频发已成为严重制约社会经济可持续发展的重要因素,但由于干旱形成机理复杂,影响因素众多,目前尚无公认普遍适用的干旱指数,因此寻找并构建适用于研究区的综合干旱指数成为当前研究的热点和重点。本文以滦河流域为研究对象,选取1960-1979年为研究期,通过对降水距平百分数、相对湿润度和由VIC模型的中间变量-土壤含水量计算得到的土壤相对湿度指数进行主成分分析,构建了适用于该流域的综合干旱指数,对研究期的旱情进行了评价,并与标准化降水指数(SPI)、帕默尔指数(PDSI)的评价结果进行比较,验证其适用性。结果表明:基于VIC模型的综合干旱指数能较好地评价滦河流域历史旱情。该研究在提升海河流域干旱监测和评价能力方面具有一定的理论与实用价值,也为其它流域的干旱评价具有参考价值。     

人类活动影响下塔里木河流域气象干旱向水文干旱传播的规律

为了解人类活动影响下塔里木河流域气象干旱向水文干旱传播的规律,基于标准化降水指数(SPI)和径流干旱指数(SDI)分析了气象、水文干旱的变化特征,探讨了人类活动对气象干旱向水文干旱传播规律的影响。研究结果表明：源流区气象、水文干旱均呈减弱趋势,干流气象干旱呈减弱趋势,水文干旱与之相反;随时间尺度增大,干旱历时延长;源流区气象、水文干旱以及干流气象干旱的发生频率受人类活动影响后(1993年后)均降低,仅干流水文干旱的发生频率升高;受人类活动影响后,源流区不同季节气象干旱向水文干旱的传播时间均变长,干流干旱传播时间除春季外均缩短;源流区干旱传播时间延长与气候变化有关,而干流干旱传播时间缩短主要是受人类活动的影响。     

Drought Forecasting Using Neural Networks,Wavelet Neural Networks,and Stochastic Models: Case of the Algerois Basin in North Algeria

Drought forecasting is a major component of a drought preparedness and mitigation plan. This paper focuses on an investigation of artificial neural networks (ANN) models for drought forecasting in the algerois basin in Algeria in comparison with traditional stochastic models (ARIMA and SARIMA models). A wavelet pre-processing of input data (wavelet neural networks WANN) was used to improve the accuracy of ANN models for drought forecasting. The standard precipitation index (SPI), at three time scales (SPI-3, SPI-6 and SPI-12), was used as drought quantifying parameter for its multiple advantages. A number of different ANN and WANN models for all SPI have been tested. Moreover, the performance of WANN models was investigated using several mother wavelets including Haar wavelet (db1) and 16 daubechies wavelets (dbn, n varying between 2 and 17). The forecast results of all models were compared using three performance measures (NSE, RMSE and MAE). A comparison has been done between observed data and predictions, the results of this study indicate that the coupled wavelet neural network (WANN) models were the best models for drought forecasting for all SPI time series and over lead times varying between 1 and 6 months. The structure of the model was simplified in the WANN models, which makes them very convenient and parsimonious. The final forecasting models can be utilized for drought early warning.

     

A New Method for Joint Frequency Analysis of Modified Precipitation Anomaly Percentage and Streamflow Drought Index Based on the Conditional Density of Copula Functions

In this study, a new method was proposed to model the occurrence of related variables based on the conditional density of copula functions. The proposed method was adopted to investigate the dynamics of meteorological and hydrological droughts in the Zarinehroud basin, southeast of Lake Urmia, during the period 1994–2015. For this purpose, the modified precipitation anomaly percentage and streamflow drought indices were extracted. Finally, the joint frequency analysis of duration-duration and severity-severity characteristics of meteorological and hydrological droughts was analyzed. Analysis of 7 different copulas used to create the joint distribution in the Zarinehroud basin indicated that the Frank copula had the best performance in describing the relationship between the meteorological and hydrological drought severities and durations. By examining the results of the bivariate analysis of duration-duration of meteorological and hydrological droughts at different stations, the expected meteorological and hydrological drought durations were estimated in the years ahead. For example, at Chalkhmaz station, 4- to 7-month duration for the hydrological drought and 9- to 12-month duration for the meteorological drought is expected in the years ahead. The joint frequency analysis of drought characteristics allows to determine the meteorological and hydrological drought characteristics at a single station at the same time using joint probabilities. Also, the results indicated that by knowing the conditional density, the hydrological drought characteristics can be easily estimated for the given meteorological drought characteristics. This could provide users and researchers useful information about the probabilistic behavior of drought characteristics for optimal operation of surface water.