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.     

Direct relationships of discharges to the mean and standard deviation of the intervals between their exceedences

Abstract

This article paves a way for assessing flood risk by the use of two-parameter distributions, for the intervals between threshold exceedences rather than by the traditional exponential distribution. In a case study, the apparent properties of intervals between exceedences of runoff events differ from those anticipated for exponentially distributed series. A procedure is proposed to relate two statistical parameters of the intervals to threshold discharges. It considers partial duration series (PDS) with thresholds equal to all high enough observed discharges. To avoid unnecessary assumptions on the behaviour of those parameters and effects of dependence between parameters for different PDS, a non-parametric trend-free pre-whitened scheme is applied. It leads to power-law relationships between a discharge and the mean and standard deviation of the intervals between its exceedences. Predicted mean inter-exceedence intervals, for the highest observed discharges at the stations, are closer to the observational periods than those predicted by GEV distributions fitted to AMS, and by GP distributions to fitted PDS. In the present case, the latter predictions are longer than the observational periods whereas some of the predicted mean inter-exceedences are shorter than the corresponding observational periods and some others are longer.

Citation Ben-Zvi, A. & Azmon, B. (2010) Direct relationships of discharges to the mean and standard deviation of the intervals between their exceedences. Hydrol. Sci J. 55(4), 565–577.     

Analysis of streamflow droughts using fixed and variable thresholds

Hydrological drought analysis is very important in the design of hydrotechnical projects and water resources management and planning. In this study, a methodology is proposed for the analysis of streamflow droughts using the threshold level approach. The method has been applied to Yermasoyia semiarid basin in Cyprus based on 30‐year daily discharge data. Severity was defined as the accumulated water deficit volume occurring during a drought event, in respect with a target threshold. Fixed and variable thresholds (seasonal, monthly, and daily) were employed to derive the drought characteristics. The threshold levels were determined based on the Q₅₀ percentiles of flow extracted from the corresponding flow duration curves for each threshold. The aim is to investigate the sensitivity of these thresholds in the estimation of maximum drought severities for various return periods and the derivation of severity–duration–frequency curves. The block maxima and the peaks over threshold approaches were used to perform the extreme value analysis. Three pooling procedures (moving average, interevent time criterion, and interevent time and volume criterion) were employed to remove the dependent and minor droughts. The application showed that the interevent time and volume criterion is the most unbiased pooling method. Therefore, it was selected to estimate the drought characteristics. The results of this study indicate that monthly and daily variable thresholds are able to capture abnormal drought events that occur during the whole hydrological year whereas the other two, only the severe ones. They are also more sensitive in the estimation of maximum drought severities and the derivation of the curves because they incorporate better the effect of drought durations.     

MORPHOLOGICAL CHARACTERISTICS OF FREE BENDS

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Estimating Flood Quantiles on the Basis of Multi-Event Rainfall Simulation — Case Study

This paper presents an approach to estimating the probability distribution of annual discharges Q based on rainfall-runoff modelling using multiple rainfall events. The approach is based on the prior knowledge about the probability distribution of annual maximum daily totals of rainfall P in a natural catchment, random disaggregation of the totals into hourly values, and rainfall-runoff modelling. The presented Multi-Event Simulation of Extreme Flood method (MESEF) combines design event method based on single-rainfall event modelling, and continuous simulation method used for estimating the maximum discharges of a given exceedance probability using rainfall-runoff models. In the paper, the flood quantiles were estimated using the MESEF method, and then compared to the flood quantiles estimated using classical statistical method based on observed data.     

Streamflow drought time series forecasting

Drought is considered to be an extreme climatic event causing significant damage both in the natural environment and in human lives. Due to the important role of drought forecasting in water resources planning and management and the stochastic behavior of drought, a multiplicative seasonal autoregressive integrated moving average (SARIMA) model is applied to the monthly streamflow forecasting of the Zayandehrud River in western Isfahan province, Iran. After forecasting 12 leading month streamflow, four drought thresholds including streamflow mean, monthly streamflow mean, 2-, 5-, 10- and 20-year return period monthly drought and standardized streamflow index were chosen. Both observed and forecasted streamflow showed a drought period with different severity in the lead-time. This study also demonstrates the usefulness of SARIMA models in forecasting, water resources planning and management.     

Asymptotic Rayleigh instantaneous unit hydrograph

The instantaneous unit hydrograph for a channel network under general linear routing and conditioned on the network magnitude,N, tends asymptotically, asN grows large, to a Rayleigh probability density function. This behavior is identical to that of the width function of the network, and is proven under the assumption that the network link configuration is topologically random and the link hydraulic and geometric properties are independent and identically distributed random variables. The asymptotic distribution depends only on a scale factor, , where is a mean link wave travel time.     

Inter-catchment comparison of flow regime between the Hailiutu and Huangfuchuan rivers in the semi-arid Erdos Plateau,Northwest China

Abstract

Two river catchments, the Huangfuchuan and the Hailiutu, located in the same climate zone in the Erdos Plateau, China, have distinctly different flow regimes. This study systematically compared differences between the flow regimes of these two catchments using several statistical methods, and analysed the possible causes. The variations in yearly, monthly and daily mean discharges were found to be much greater in the Huangfuchuan catchment than in the Hailiutu catchment. Preliminary analysis indicated that these differences are not caused by changes in climate, but are instead attributable to differences in geology, geomorphology, hydrological processes and human interventions. In the Hailiutu catchment, the dominant groundwater contribution maintains stationary daily and monthly river discharges, while shifts in yearly mean discharges were closely associated with the expansion or reduction of crop area. In the Huangfuchuan catchment, the dominant direct rainfall–runoff process generates flashier daily and monthly river discharges, while the decrease of yearly mean discharges is caused mainly by the construction of check dams. These findings have significant implications for water resource management and the implementation of proper soil and water conservation measures in the middle reach of the Yellow River Basin of China.

Editor Z.W. Kundzewicz; Associate editor Y. Gyasi-Agyei     

Asymptotic Rayleigh instantaneous unit hydrograph

The instantaneous unit hydrograph for a channel network under general linear routing and conditioned on the network magnitude,N, tends asymptotically, asN grows large, to a Rayleigh probability density function. This behavior is identical to that of the width function of the network, and is proven under the assumption that the network link configuration is topologically random and the link hydraulic and geometric properties are independent and identically distributed random variables. The asymptotic distribution depends only on a scale factor, , where is a mean link wave travel time.     

Analysis of groundwater exchange for a large plains river in Colorado (USA)

Complete daily water budget information was assembled for a 105 km segment of the South Platte River in the plains region below Denver, CO, for the period 1983–1993. The data were used in testing the possibility that dependence of alluvial exchange mechanisms on stage height, as shown by models of alluvial exchange, allows alluvial exchange to be predicted continuously over a given reach through use of statistical information on river discharge. The study segment was divided into an upper and a lower reach; daily alluvial exchanges for each reach were estimated by the method of residuals. The two reaches show small (15%) but statistically significant annual differences in rates of exchange. For each reach, there is a seasonal pattern (2·5‐fold oscillation) in alluvial discharge to the channel, reflecting seasonality in recharge of the alluvium by irrigation. At discharges up to 40 m³/s (82nd percentile), alluvial discharge to the channel occurs at a rate independent of river discharge. Above 40 m³/s, net alluvial discharge into the channel is progressively reduced; at 60 m³/s (92nd percentile) there is no net alluvial exchange. At still higher river discharges, water is lost to the alluvium through bank storage at a rate that is linearly related to the logarithm of discharge. Annually, alluvial discharge accounts for 15–18% of water entering the study segment, and alluvial recharge through bank storage accounts for 2–4% of water leaving the segment. Alluvial recharge through bank storage at the highest discharges can, however, exceed low‐flow alluvial discharge rates by five‐fold over short intervals. Even though daily alluvial exchanges vary widely, they can be estimated at r² values above 80% on the basis of reach, season, and river discharge. Copyright © 2001 John Wiley & Sons, Ltd.     

Assessing possible changes in flood frequency due to climate change in mid‐sized watersheds in New York State,USA

The frequency of flooding is often presumed to increase with climate change because of projected increases in rainfall intensities. In this paper, using 50‐plus years of historical discharge and meteorological data from three watersheds in different physiographic regions of New York State, USA, we find that annual maximum stream discharges are associated with 20% or less of the annual maximum rainfall events. Instead of rainfall events, approximately 20% of annual maximum stream discharges are associated with annual maximum snowmelt events while 60% of annual maximum discharges are associated with moderate rainfall amounts and very wet soil conditions. To explore the potential for changes in future flood risk, we employed a compound frequency distribution that assumes annual maximum discharges can be modelled by combining the cumulative distribution functions of discharges resulting from annual maximum rainfall, annual maximum snowmelt, and occurrences of moderate rain on wet soils. Basing on a compound frequency distribution comprised of univariate general extreme value (GEV) and gamma distributions, we found that a hypothetical 20% increase in the magnitude of rainfall‐related stream discharge results in little change in 96th percentile annual maximum discharge. For the 99th percentile discharge, two waterbodies in our study had a 10% or less increase in annual maximum discharge when annual maximum rainfall‐related discharges increased 20% while the third waterbody had a 16% increase in annual maximum discharges. Additionally, in some cases, annual maximum discharges could be offset by a reduction in the discharge resulting from annual maximum snowmelt events. While only intended as a heuristic tool to explore the interaction among different flood‐causing mechanisms, use of a compound flood frequency distribution suggests a case can be made that not all waterbodies in humid, cold regions will see extensive changes in flooding due to increased rainfall intensities. Copyright © 2011 John Wiley & Sons, Ltd.     

Predicting unit plot soil loss in Sicily,south Italy

Predicting soil loss is necessary to establish soil conservation measures. Variability of soil and hydrological parameters complicates mathematical simulation of soil erosion processes. Methods for predicting unit plot soil loss in Sicily were developed by using 5 years of data from replicated plots. At first, the variability of the soil water content, runoff, and unit plot soil loss values collected at fixed dates or after an erosive event was investigated. The applicability of the Universal Soil Loss Equation (USLE) was then tested. Finally, a method to predict event soil loss was developed. Measurement variability decreased as the mean increased above a threshold value but it was low also for low values of the measured variable. The mean soil loss predicted by the USLE was lower than the measured value by 48%. The annual values of the soil erodibility factor varied by seven times whereas the mean monthly values varied between 1% and 244% of the mean annual value. The event unit plot soil loss was directly proportional to an erosivity index equal to , being Q_RR_e the runoff ratio times the single storm erosion index. It was concluded that a relatively low number of replicates of the variable of interest may be collected to estimate the mean for both high and particularly low values of the variable. The USLE with the mean annual soil erodibility factor may be applied to estimate the order of magnitude of the mean soil loss but it is not usable to estimate soil loss at shorter temporal scales. The relationship for estimating the event soil loss is a modified version of the USLE‐M, given that it includes an exponent for the Q_RR_e term. Copyright © 2007 John Wiley & Sons, Ltd.     

Estimation of regional meteorological and hydrological drought characteristics: a case study for Denmark

Information on regional drought characteristics provides critical information for adequate water resource management. This study introduces a method to calculate the probability of a specific area to be affected by a drought of a given severity and demonstrates its potential for calculating both meteorological and hydrological drought characteristics. The method is demonstrated using Denmark as a case study. The calculation procedure was applied to monthly precipitation and streamflow series separately, which were linearly transformed by the Empirical Orthogonal Functions (EOF) method. Denmark was divided into 260 grid-cells of 14×17 km, and the monthly mean and the EOF-weight coefficients were interpolated by kriging. The frequency distributions of the first two (streamflow) or three (precipitation) amplitude functions were then derived. By performing Monte Carlo simulations, amplitude functions corresponding to 1000 years of data were generated. Based on these simulated functions as well as interpolated mean and weight coefficients, long time series of precipitation and streamflow were simulated for each grid-cell. The probability distribution functions of the area covered by a drought and the drought deficit volumes were then derived and combined to produce drought severity-area-frequency curves. These curves allowed an estimation of the probability of an area of a certain extent to have a drought of a given severity, and thereby return periods could be assigned to historical drought events. A comparison of drought characteristics showed that streamflow droughts are less homogeneous over the region, less frequent and last for longer time periods than precipitation droughts.     

On the distribution of flood volume in partial duration series analysis of flood phenomena

A methodology based on the theory of stochastic processes is applied to the analysis of floods. The approach will be based on some results of the theory of extreme values over a threshold. In this paper, we focus on the estimation of the distribution of the flood volume in partial duration series analysis of flood phenomena, by using a bivariate exponential distribution of discharge exceedances and durations over a base level.     

On the distribution of flood volume in partial duration series analysis of flood phenomena

A methodology based on the theory of stochastic processes is applied to the analysis of floods. The approach will be based on some results of the theory of extreme values over a threshold. In this paper, we focus on the estimation of the distribution of the flood volume in partial duration series analysis of flood phenomena, by using a bivariate exponential distribution of discharge exceedances and durations over a base level.     

Space–time modelling of catchment scale drought characteristics

Drought may affect all components of the water cycle and covers commonly a large part of the catchment area. This paper examines drought propagation at the catchment scale using spatially aggregated drought characteristics and illustrates the importance of catchment processes in modifying the drought signal in both time and space. Analysis is conducted using monthly time series covering the period 1961–1997 for the Pang catchment, UK. The time series include observed rainfall and groundwater recharge, head and discharge simulated by physically-based soil water and groundwater models. Drought events derived separately for each unit area and variable are combined to yield catchment scale drought characteristics. The study reveals relatively large differences in the spatial and temporal characteristics of drought for the different variables. Meteorological droughts cover frequently the whole catchment; and they are more numerous and last for a short time (1–2 months). In comparison, droughts in recharge and hydraulic head cover typically a smaller area and last longer (4–5 months). Hydraulic head and groundwater discharge exhibit similar drought characteristics, which can be expected in a groundwater fed catchment. Deficit volume is considered a robust measure of the severity of a drought event over the catchment area for all variables; whereas, duration is less sensitive, particular for rainfall. Spatial variability in drought characteristics for groundwater recharge, head and discharge are primarily controlled by catchment properties. It is recommended not to use drought area separately as a measure of drought severity at the catchment scale, rather it should be used in combination with other drought characteristics like duration and deficit volume.     

Modelling streamflow trends for a watershed with limited data: case of the Litani basin,Lebanon

Abstract

Streamflow variability in the Upper and Lower Litani basin, Lebanon was modelled as there is a lack of long-term measured runoff data. To simulate runoff and streamflow, daily rainfall was derived using a stochastic rainfall generation model and monthly rainfall data. Two distinct synthetic rainfall models were developed based on a two-part probabilistic distribution approach. The rainfall occurrence was described by a Markov chain process, while the rainfall distribution on wet days was represented by two different distributions (i.e. gamma and mixed exponential distributions). Both distributions yielded similar results. The rainfall data were then processed using water balance and routing models to generate daily and monthly streamflow. Compared with measured data, the model results were generally reasonable (mean errors ranging from 0.1 to 0.8?m³/s at select locations). Finally, the simulated monthly streamflow data were used to investigate discharge trends in the Litani basin during the 20th century using the Mann-Kendall and Sen slope nonparametric trend detection methods. A significant drying trend of the basin was detected, reaching a streamflow reduction of 0.8 and 0.7 m³/s per decade in January for the Upper and Lower basin, respectively.

Editor D. Koutsoyiannis; Associate editor Sheng Yue

Citation Ramadan, H.H., Beighley, R.E., and Ramamurthy, A.S., 2012. Modelling streamflow trends for a watershed with limited data: case of the Litani basin, Lebanon. Hydrological Sciences Journal, 57 (8), 1516–1529.     

Application of a wind-driven hydrodynamic model for the quantification of transport in an open boundary canal-lakes system in sw Friesland,The Netherlands

The south western lake district is a part of the boezem, a system of interconnected lakes and canals in the province of Friesland. The lake district has open boundaries with the other part of the boezem system. However, discharges in the boundary canals are unknown. These discharges are needed for modelling the phosphorus dynamics in the study area. Incidental water flow measurements gave a good indication of the complex water transport in the study area, but continuous water flow recording was not possible. Consequently, discharges could not be measured directly. In order to quantify the discharges, the water transport in the area was modelled by the application of a detailed wind-driven hydrodynamic model. In the model hourly mean values of wind data and water levels at the boundary locations were used as forcing functions. Model tuning was done by comparing observed and computed water levels of three stations within the system. This approach is new in surface water systems in The Netherlands. Therefore, a sensitivity analysis was done and it was verified whether the model results were reliable.The sensitivity analysis showed that the sensitivity was low for modifications of the wind exponent value and rather high for the bottom roughness coefficient. Simulations with daily or weekly mean wind and water level data resulted in an undesirable loss of detail. The sensitivity for noise at the imposed water levels at the boundary locations was moderate. The calculated discharges were used as forcing functions for a chloride mass balance model. Calculated chloride concentrations coincided with measured concentrations in three lakes, during three periods. From this it was concluded that the discharges were reliable. The simulations also lead to the quantification of the water balance and water residence times in the lakes.     

Linking runoff response to burn severity after a wildfire

Extreme floods often follow wildfire in mountainous watersheds. However, a quantitative relation between the runoff response and burn severity at the watershed scale has not been established. Runoff response was measured as the runoff coefficient C, which is equal to the peak discharge per unit drainage area divided by the average maximum 30 min rainfall intensity during each rain storm. The magnitude of the burn severity was expressed as the change in the normalized burn ratio. A new burn severity variable, hydraulic functional connectivity Φ was developed and incorporates both the magnitude of the burn severity and the spatial sequence of the burn severity along hillslope flow paths. The runoff response and the burn severity were measured in seven subwatersheds (0·24 to 0·85 km²) in the upper part of Rendija Canyon burned by the 2000 Cerro Grande Fire near Los Alamos, New Mexico, USA. A rainfall–discharge relation was determined for four of the subwatersheds with nearly the same burn severity. The peak discharge per unit drainage area was a linear function of the maximum 30 min rainfall intensity I₃₀. This function predicted a rainfall intensity threshold of 8·5 mm h^?1 below which no runoff was generated. The runoff coefficient was a linear function of the mean hydraulic functional connectivity of the subwatersheds. Moreover, the variability of the mean hydraulic functional connectivity was related to the variability of the mean runoff coefficient, and this relation provides physical insight into why the runoff response from the same subwatershed can vary for different rainstorms with the same rainfall intensity. Copyright © 2007 John Wiley & Sons, Ltd.