Global projections of changing risks of floods and droughts in a changing climate

Abstract

Simulated daily discharge derived from a relatively high-resolution (approximately 1.1-degree) general circulation model was used to investigate future projections of extremes in river discharge under global warming. The frequency of floods was projected to increase over many regions, except those including North America and central to western Eurasia. The drought frequency was projected to increase globally, while regions such as northern high latitudes, eastern Australia, and eastern Eurasia showed a decrease or no significant changes. Changes in flood and drought are not explained simply by changes in annual precipitation, heavy precipitation, or differences between precipitation and evapotranspiration. Several regions were projected to have increases in both flood frequency and drought frequency. Such regions show a decrease in the number of precipitation days, but an increase in days with heavy rain. Several regions show shifts in the flood season from springtime snowmelt to the summer period of heavy precipitation.     

Development of an operational low-flow index for hydrological drought monitoring over Europe

Near real-time monitoring of hydrological drought requires the implementation of an index capable of capturing the dynamic nature of the phenomenon. Starting from a dataset of modelled daily streamflow data, a low-flow index was developed based on the total water deficit of the discharge values below a certain threshold. In order to account for a range of hydrological regimes, a daily 95th percentile threshold was adopted, which was computed by means of a 31-day moving window. The observed historical total water deficits were statistically fitted by means of the exponential distribution and the corresponding probability values were used as a measure of hydrological drought severity. This approach has the advantage that it directly exploits daily streamflow values, as well as allowing a near real-time update of the index at regular time steps (i.e. 10 days, or dekad). The proposed approach was implemented on discharge data simulated by the LISFLOOD model over Europe during the period 1995–2015; its reliability was tested on four case studies found within the European drought reference database, as well as against the most recent summer drought observed in Central Europe in 2015. These validations, even if only qualitative, highlighted the ability of the index to capture the timing (starting date and duration) of the main historical hydrological drought events, and its good performance in comparison with the commonly used standardized runoff index (SRI). Additionally, the spatial evolution of the most recent event was captured well in a simulated near real-time test case, suggesting the suitability of the index for operational implementation within the European Drought Observatory.     

Evaluating the performance of ground-based and remotely sensed near real-time rainfall fields from a hydrological perspective

Abstract

The South African Weather Service (SAWS) issues routine experimental, near real-time rainfall maps from daily raingauge networks, radar networks and satellite images, as well as merged rainfall fields. These products are potentially useful for near real-time forecasting, especially in areas of fast hydrological response, and also to simulate the “now state” of various hydrological state variables such as soil moisture content, streamflow, and reservoir inflows. The purpose of this paper is to evaluate their skill as inputs to hydrological simulations and, in particular, the skill of the merged field in terms of better hydrological results relative to the individual products. Rainfall fields derived from raingauge, radar, satellite, conditioned satellite and the merged (gauge/radar/satellite) were evaluated for two selected days with relatively high amounts of rainfall, as well as for a continuous period of 90 days in the Mgeni catchment, South Africa. Streamflows simulated with the ACRU model indicate that the use of raingauge as well as merged fields of satellite/raingauge and satellite/radars/raingauge provides relatively realistic rainfall results, without much difference in their hydrological outputs, whereas the radar and raw satellite information by themselves cannot be used in operational hydrological application in their current status.

Citation Ghile, Y., Schulze, R. & Brown, C. (2010) Evaluating the performance of ground-based and remotely sensed near real-time rainfall fields from a hydrological perspective. Hydrol. Sci. J. 55(4), 497–511.     

An integrated approach to the estimation of streamflow drought quantiles / Une méthode intégrée d’estimation des quantiles de sécheresse hydrologique

Abstract

Abstract An approach was developed for combining streamflow drought information from synthetic (generated) data with data reconstructed based on palaeoclimatic information (tree ring widths). The tree ring data were used to reconstruct streamflow in periods when no streamflow data were collected. The reconstructed data were then used as a source of historical data for estimating drought severity quantiles. The generated data were obtained using a nearest neighbour resampling method while the tree ring reconstruction was accomplished using a regression model. The application of the approach was to data from the Athabasca River in Alberta, Canada. The results demonstrate the feasibility and the utility of the approach for obtaining more accurate and precise estimates of extreme drought severity quantiles.     

Seasonal drought predictability in Portugal using statistical–dynamical techniques

Atmospheric forecasting and predictability are important to promote adaption and mitigation measures in order to minimize drought impacts. This study estimates hybrid (statistical–dynamical) long-range forecasts of the regional drought index SPI (3-months) over homogeneous regions from mainland Portugal, based on forecasts from the UKMO operational forecasting system, with lead-times up to 6 months. ERA-Interim reanalysis data is used for the purpose of building a set of SPI predictors integrating recent past information prior to the forecast launching. Then, the advantage of combining predictors with both dynamical and statistical background in the prediction of drought conditions at different lags is evaluated. A two-step hybridization procedure is performed, in which both forecasted and observed 500 hPa geopotential height fields are subjected to a PCA in order to use forecasted PCs and persistent PCs as predictors. A second hybridization step consists on a statistical/hybrid downscaling to the regional SPI, based on regression techniques, after the pre-selection of the statistically significant predictors. The SPI forecasts and the added value of combining dynamical and statistical methods are evaluated in cross-validation mode, using the R² and binary event scores. Results are obtained for the four seasons and it was found that winter is the most predictable season, and that most of the predictive power is on the large-scale fields from past observations. The hybridization improves the downscaling based on the forecasted PCs, since they provide complementary information (though modest) beyond that of persistent PCs. These findings provide clues about the predictability of the SPI, particularly in Portugal, and may contribute to the predictability of crops yields and to some guidance on users (such as farmers) decision making process.     

Microseismic Event Detection Kalman Filter: Derivation of the Noise Covariance Matrix and Automated First Break Determination for Accurate Source Location Estimation

Since 1972, Weir-Jones Engineering Consultants (WJEC) has been involved in the development and installation of microseismic monitoring systems for the mining, heavy construction and oil/gas industries. To be of practical value in an industrial environment, microseismic monitoring systems must produce information which is both reliable and timely. The most critical parameters obtained from a microseismic monitoring system are the real-time location and magnitude of the seismic events. Location and magnitude are derived using source location algorithms that typically utilize forward modeling and iterative optimal estimation techniques to determine the location of the global minimum of a predefined cost function in a three-dimensional solution space. Generally, this cost function is defined as the RMS difference between measured seismic time series information and synthetic measurements generated by assuming a velocity structure for the area under investigation (forward modeling). The seismic data typically used in the source location algorithm includes P- and S-wave arrival times, and raypath angles of incidence obtained from P-wave hodogram analysis and P-wave first break identification. In order to obtain accurate and timely source location estimates it is of paramount importance that the extraction of accurate P-wave and S-wave information from the recorded time series be automated—in this way consistent data can be made available with minimal delay. WJEC has invested considerable resources in the development of real-time digital filters to optimize extraction, and this paper outlines some of the enhancements made to existing Kalman Filter designs to facilitate the automation of P-wave first break identification.     

Ionospheric specification and forecasting based on observations from European ionosondes participating in DIAS project

There are two main objectives of the DIAS (European Digital Upper Atmosphere Server) project. First, it establishes a pan-European repository of raw and derived digital data describing the state of ionospheric part of the upper atmosphere, which is capable of ingesting real-time information and maintaining historical data collections provided by most operating ionospheric stations in Europe. Second, the DIAS system produces and distributes, based on the raw data collection, several operational products required by various user groups for ionospheric nowcasting, prediction and forecasting purposes. The project completed on May 2006 and the DIAS server operates since then continuously. The basic products that are delivered are real-time and historical ionograms from all DIAS-affiliated ionospheric stations, frequency plots and maps of the ionosphere over Europe based on the foF2, M(3000)F2, MUF and electron density parameters, as well as long term prediction and short term forecasting up to 24 hour ahead. The paper describes use of the ionospheric measurements in the DIAS modelling techniques for specification, predict-tion and forecasting of the ionosphere over the European region, and details the final products available to the DIAS user community.     

Assessment of drought trend and variability in India using wavelet transform

ABSTRACT

This paper presents an analysis of trends in six drought variables at 566 stations across India over the period 1901–2002. Six drought variables were computed using standardized precipitation index (SPI). The Mann-Kendall (MK) trend test and Sen’s slope estimator were used for trend analysis of drought variables. Discrete wavelet transform (DWT) was used to identify the dominant periodic components in trends, whereas the significance of periodic components was examined using continuous wavelet transform (CWT) based global wavelet spectrum (GWS). Our results show an increasing trend in droughts in eastern, northeastern and extreme southern regions, and a decreasing trend in the northern and southern regions of the country. The periodic component influencing the trend was 2–4 years in south, 4–8 years in west, east and northeast, 8–64 years in central parts and 32–128 years in the north; however, most of the periodic components were not statistically significant.     

Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin

Abstract

Remote sensing is considered the most effective tool for estimating evapotranspiration (ET) over large spatial scales. Global terrestrial ET estimates over vegetated land surfaces are now operationally produced at 1-km spatial resolution using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the MOD16 algorithm. To evaluate the accuracy of this product, ground-based measurements of energy fluxes obtained from eddy covariance sites installed in tropical biomes and from a hydrological model (MGB-IPH) were used to validate MOD16 products at local and regional scales. We examined the accuracy of the MOD16 algorithm at two sites in the Rio Grande basin, Brazil, one characterized by a sugar-cane plantation (USE), the other covered by natural savannah vegetation (PDG) for the year 2001. Inter-comparison between 8-day average MOD16 ET estimates and flux tower measurements yielded correlations of 0.78 to 0.81, with root mean square errors (RMSE) of 0.78 and 0.46 mm d^-1, at PDG and USE, respectively. At the PDG site, the annual ET estimate derived by the MOD16 algorithm was 19% higher than the measured amount. For the average annual ET at the basin-wide scale (over an area of 145 000 km²), MOD16 estimates were 21% lower than those from the hydrological model MGB-IPH. Misclassification of land use and land cover was identified as the largest contributor to the error from the MOD16 algorithm. These estimates improve significantly when results are integrated into monthly or annual time intervals, suggesting that the algorithm has a potential for spatial and temporal monitoring of the ET process, continuously and systematically, through the use of remote sensing data.

Editor D. Koutsoyiannis; Associate editor T. Wagener

Citation Ruhoff, A.L., Paz, A.R., Aragao, L.E.O.C., Mu, Q., Malhi, Y., Collischonn, W., Rocha, H.R., and Running, S.W., 2013. Assessment of the MODIS global evapotranspiration algorithm using eddy covariance measurements and hydrological modelling in the Rio Grande basin. Hydrological Sciences Journal, 58 (8), 1658–1676.     

A semi-empirical method for predicting hydrological drought magnitudes in the Canadian prairies

Abstract

A hydrological drought magnitude (M _T ) expressed in standardized terms is predicted on annual, monthly and weekly time scales for a sampling period of T years in streamflow data from the Canadian prairies. The drought episodes are considered to follow the Poisson law of probability and, when coupled with the gamma probability distribution function (pdf) of drought magnitude (M) in the extreme number theorem, culminate in a relationship capable of evaluating the expected value, E(M _T ). The parameters of the underlying pdf of M are determined based on the assumption that the drought intensity follows a truncated normal pdf. The E(M _T ) can be evaluated using only standard deviation (σ), lag-1 autocorrelation (ρ) of the standardized hydrological index (SHI) sequence, and a weighting parameter Φ (ranging from 0 to 1) to account for the extreme drought duration (L _T ), as well as the mean drought duration (L_m ), in a characteristic drought length (L_c ). The SHI is treated as standard normal variate, equivalent to the commonly-used standardized precipitation index. A closed-form relationship can be used for the estimation of first-order conditional probabilities, which can also be estimated from historical streamflow records. For all rivers, at the annual time scale, the value of Φ was found equal to 0.5, but it tends to vary (in the range 0 to 1) from river to river at monthly and weekly time scales. However, for a particular river, the Φ value was nearly constant at monthly and weekly time scales. The proposed method estimates E(M _T ) satisfactorily comparable to the observed counterpart. At the annual time scale, the assumption of a normal pdf for drought magnitude tends to yield results in close proximity to that of a gamma pdf. The M _T , when transformed into deficit-volume, can form a basis for designing water storage facilities and for planning water management strategies during drought periods.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Sharma, T.C. and Panu, U.S., 2013. A semi-empirical method for predicting hydrological drought magnitudes in the Canadian prairies. Hydrological Sciences Journal, 58 (3), 549–569.     

Intercomparison across scales between remotely-sensed land surface temperature and representative equilibrium temperature from a distributed energy water balance model

Abstract

Quantifying the reliability of distributed hydrological models is an important task in hydrology to understand their ability to estimate energy and water fluxes at the agricultural district scale as well the basin scale for water resources management in drought monitoring and flood forecasting. In this context, the paper presents an intercomparison of simulated representative equilibrium temperature (RET) derived from a distributed energy water balance model and remotely-sensed land surface temperature (LST) at spatial scales from the agricultural field to the river basin. The main objective of the study is to evaluate the use of LST retrieved from operational remote sensing data at different spatial and temporal resolutions for the internal validation of a distributed hydrological model to control its mass balance accuracy as a complementary method to traditional calibration with discharge measurements at control river cross-sections. Modelled and observed LST from different radiometric sensors located on the ground surface, on an aeroplane and a satellite are compared for a maize field in Landriano (Italy), the agricultural district of Barrax (Spain) and the Upper Po River basin (Italy). A good ability of the model in reproducing the observed LST values in terms of mean bias error, root mean square error, relative error and Nash-Sutcliffe index is shown.

Editor Z.W. Kundzewicz; Associate editor D. Gerten     

Spatio-temporal drought analysis in the Trakya region,Turkey

Abstract

Since droughts are natural phenomena, their occurrence cannot be predicted with certainty and thus it must be treated as a random variable. Once drought duration and magnitude have been found objectively, it is possible to plan for the transport of water in known quantities to drought-stricken areas either from alternative water resources or from water stored during wet periods. The summation of deficits over a particular period is referred to as the drought magnitude. Drought intensity is the ratio of drought magnitude to its duration. These drought properties at different truncation levels provide significant hydrological and hydrometeorological design quantities. In this study, the run analysis and z-score are used for determining drought properties of given hydrological series. In addition, kriging is used as a spatial drought analysis for mapping. This study is applied to precipitation records for Istanbul, Edirne, Tekirdag and Kirklareli in the Trakya region, Turkey and then the drought period, magnitude and standardized precipitation index (SPI) values are presented to depict the relationships between drought duration and magnitude.     

Mapping of drought for Sperchios River basin in central Greece

ABSTRACT

The estimation of drought at certain temporal and spatial scales is useful for research on climate change and global warming. Greece is often affected by droughts, which are widespread spatially and temporally due to the complex topography. Within the Greek territory, various complex microclimates are created, linked with the spatial variances in drought phenomena. In this paper an estimation of drought in the Sperchios River basin was conducted using the Aridity Index (AI). Additionally, a seasonal analysis of drought was performed. Meteorological data from the Hellenic National Meteorological Service (HNMS) were used as inputs for the AI equation. Spatial interpolation of AI for the Sperchios River basin was performed using a kriging method by the application of ArcGIS 9.3. In order to produce required input data, several models (EmPEst, RayMan) and techniques (linear regression, interpolation) were combined. Finally, the meteorological data series were randomly separated into two periods and AI was estimated for these sub-periods, in order to test the effectiveness of the drought index used. The results indicate that the conditions prevailing in the area are humid, mostly affected by increased rainfall occurring in the mountainous section of the basin. Broadly, the humid environment in the upstream of Sperchios River prevents drought occurring in the lowlands of Sperchios River valley. Nevertheless, some differentiation appeared during the summer period, to which special attention needs to be given in order to prevent drought conditions.

Editor Z. W. Kundzewicz Associate editor not assigned     

DIAS effective sunspot number as an indicator of the ionospheric activity level over Europe

DIAS (European Digital Upper Atmosphere Server) effective sunspot number — R12eff was recently introduced as a proxy of the ionospheric conditions over Europe for regional ionospheric mapping purposes. Although a pre-processing step for the real-time update of the Simplified Ionospheric Regional Model (SIRM) to real-time conditions, R12eff is available in real time by DIAS system (http://dias.space.noa.gr) for independent operational use. In this paper we discuss the efficiency of R12eff to specify ionospheric conditions over Europe. For this purpose, the diurnal R12eff’s reference pattern was determined on monthly basis and for different solar cycle phases. The deviation of the real-time R12eff estimates from the reference values, ΔR12eff was found to be highly correlated with the foF2 storm-time disturbances, especially during large scale effects indicating that DIAS-R12eff can provide a reliable estimator of the ionospheric activity level over a substantial part of Europe and a powerful tool for ionospheric specification applications.     

Comparison of drought projections using two UK weather generators

Abstract

Possible changes in drought under future climate scenarios may pose unprecedented challenges for water resources, as well as other environmental and societal issues, and need assessment to quantify their associated risk. Two weather generators, based upon (a) the Neyman-Scott Rectangular Pulses (NSRP) model as implemented by the United Kingdom Climate Projections 09 (UKCP09) study, and (b) the generalized linear model (GLM) approach, are used to investigate potential variations in drought conditions for six catchments in the UK under climate projections. The results show that both weather generators provide rainfall simulations having satisfactory monthly statistics. However, the rainfall series from the UKCP09 weather generators lack inter-annual variability, whereas the GLM simulations, which include non-stationary global circulation model (GCM) outputs as driving variables, seem to have a more appropriate representation of the observed drought conditions. For drought projections in the 2080s, the UKCP09 simulations provide repetitive patterns without much temporal variation, similar to the results in the control period. This study suggests that for the drought index considered here (a 3-month drought severity index) the GLM approach appears to be a more appropriate model for drought study on inter-annual scales in comparison with the UKCP09 weather generator.

Editor D. Koutsoyiannis

Citation Chun, K.P., Wheater, H.S., and Onof, C., 2013. Comparison of drought projections using two UK weather generators. Hydrological Sciences Journal, 58 (2), 295–309.     

Letters to the Editor

Abstract

This work investigates historical trends of meteorological drought in Taiwan by means of long-term precipitation records. Information on local climate change over the last century is also presented. Monthly and daily precipitation data for roughly 100 years, collected by 22 weather stations, were used as the study database. Meteorological droughts of different levels of severity are represented by the standardized precipitation index (SPI) at a three-monthly time scale. Additionally, change-point detection is used to identify meteorological drought trends in the SPI series. Results of the analysis indicate that the incidence of meteorological drought has decreased in northeastern Taiwan since around 1960, and increased in central and southern Taiwan. Long-term daily precipitation series show an increasing trend for dry days all over Taiwan. Finally, frequency analysis was performed to obtain further information on trends of return periods of drought characteristics.     

Teleconnections between oceanic–atmospheric indices and drought over Iran using quantile regressions

ABSTRACT

In this research, the Bayesian quantile regression model is applied to investigate the teleconnections between large oceanic–atmospheric indices and drought standardized precipitation index (SPI) in Iran. The 12-month SPI time series from 138 synoptic stations for 1952–2014 were selected as the drought index. Three oceanic–atmospheric indices, the North Atlantic Oscillation (NAO), the Southern Oscillation Index (SOI) and the Multivariate El Niño/Southern Oscillation Index (MEI), were selected as covariates. The results show that NAO has the weakest impact on drought in different quantiles and different regions in Iran. La Niña conditions amplified droughts through all SPI quantiles in western, Caspian Sea coastal regions and southern regions. The positive phase of MEI significantly modulates low SPI quantiles (i.e. drought conditions) throughout the Zagros region, Caspian Sea coastal regions and southern regions. The study shows that the effect of large oceanic–atmospheric indices have heterogeneous impacts on extreme dry and wet conditions.     

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.     

Large Scale Geostrophic Winds with a Full Representation of the Coriolis Force: Application to IR Observations of the Upper Jovian Troposphere

The diagnostics of large scale geostrophy in a stratified atmosphere are revisited in pressure coordinates using a full Coriolis force. This formulation of geostrophy includes the horizontal and vertical projections of the planetary rotation vector, is valid for shallow and deep atmospheres, accounts for the spherical geometry of the atmosphere, is not singular at the equator, and provides partial information about vertical velocities. The new expressions, although an improvement over the standard approach, are still only estimates because of the terms that are being neglected and because of the uncertainties in the observational data. The magnitudes of the errors are discussed. The accuracy of the standard hydrostatic approximation in the geostrophic regime is gauged and an alternative approach is discussed. The standard hydrostatic approximation predicts much smaller wind shears than those derived from the primitive equations. The observations are a set of global temperature maps of the upper Jovian troposphere at pressures, between 100 and 400 mbar, obtained from mid-infrared observations in June, 1996. Maps of the large-scale thermal winds show higher concentration of longitudinal structures and vertical velocities along two particular zonal bands at latitudes near 15°N and 15°S. Observational criteria are proposed to validate the standard versus the new diagnostic as well as the possible geostrophic regime of Jupiter's zonal jets.     

A drought outlook study in Korea

Abstract

Techniques are proposed for developing a monthly and weekly drought outlook and the drought outlook components are evaluated. A drought index, the surface water supply index (SWSI) was modified and used for the drought outlook. A water balance model (abcd) was successfully calibrated using a regional regression, including monthly and weekly factors, and was used to convert meteorology to hydrology. For the monthly drought outlook, an ensemble technique was applied, both with and without monthly industrial meteorology information (MIMI). For the weekly drought outlook, a deterministic forecasting technique was applied employing the Global Data Assimilation and Prediction System (GDAPS). The methodologies were applied to the Geum River basin in Korea. While only the weekly outlook using the GDAPS has sufficient forecasting capability to suggest it might be useful, the accuracy of the monthly drought outlook is expected to improve as the climate forecast accuracy increases.

Editor Z.W. Kundzewicz; Associate editor D. Hughes

Citation Kim, Y.-O., Lee, J.-K., and Palmer, R.N., 2012. A drought outlook study in Korea. Hydrological Sciences Journal, 57 (6), 1141–1153.