Development of a short-term river flood forecasting method for snowmelt driven floods based on wavelet and cross-wavelet analysis

In this study, a new method of stand-alone short-term spring snowmelt river flood forecasting was developed based on wavelet and cross-wavelet analysis. Wavelet and cross-wavelet analysis were used to decompose flow and meteorological time series data and to develop wavelet based constituent components which were then used to forecast floods 1, 2, and 6 days ahead. The newly developed wavelet forecasting method (WT) was compared to multiple linear regression analysis (MLR), autoregressive integrated moving average analysis (ARIMA), and artificial neural network analysis (ANN) for forecasting daily stream flows with lead-times equal to 1, 2, and 6 days. This comparison was done using data from the Rideau River watershed in Ontario, Canada. Numerical analysis was performed on daily maximum stream flow data from the Rideau River station and on meteorological data (rainfall, snowfall, and snow on ground) from the Ottawa Airport weather station. Data from 1970 to 1997 were used to train the models while data from 1998 to 2001 were used to test the models. The most significant finding of this research was that it was demonstrated that the proposed wavelet based forecasting method can be used with great accuracy as a stand-alone forecasting method for 1 and 2 days lead-time river flood forecasting, assuming that there are no significant trends in the amplitude for the same Julian day year-to-year, and that there is a relatively stable phase shift between the flow and meteorological time series. The best forecasting model for 1 day lead-time was a wavelet analysis model. In testing, it had the lowest RMSE value (13.8229), the highest R² value (0.9753), and the highest EI value (0.9744). The best forecasting model for 2 days lead-time was also a wavelet analysis model. In testing, it had the lowest RMSE value (31.7985), the highest R² value (0.8461), and the second highest EI value (0.8410). It was also shown that the proposed wavelet based forecasting method is not particularly accurate for longer lead-time forecasting such as 6 days, with the ANN method providing more accurate results. The best forecasting model for 6 days lead-time was an ANN model, with the wavelet model not performing as well. In testing, the wavelet model had an RMSE of 57.6917, an R² of 0.4835, and an EI of 0.4366.     

Hydrological data assimilation with the ensemble Kalman filter: Use of streamflow observations to update states in a distributed hydrological model

This paper describes an application of the ensemble Kalman filter (EnKF) in which streamflow observations are used to update states in a distributed hydrological model. We demonstrate that the standard implementation of the EnKF is inappropriate because of non-linear relationships between model states and observations. Transforming streamflow into log space before computing error covariances improves filter performance. We also demonstrate that model simulations improve when we use a variant of the EnKF that does not require perturbed observations. Our attempt to propagate information to neighbouring basins was unsuccessful, largely due to inadequacies in modelling the spatial variability of hydrological processes. New methods are needed to produce ensemble simulations that both reflect total model error and adequately simulate the spatial variability of hydrological states and fluxes.     

The analysis of turbulence time series: Statistical and correlation approaches using the minitab package

The theoretical basis and use of statistical and correlation approaches for the analysis of turbulence time series are described. In particular, the analysis of data from high frequency current meter measurements using MINITAB is presented and the data files and analytical routines are included on the software disk.     

Relative effects of multi-decadal climatic variability and changes in the mean and variability of climate due to global warming: future streamflows in Britain

Climate change impact assessments conventionally assess just the implications of a change in mean climate due to global warming. This paper compares such effects of such changes with those due to natural multi-decadal variability, and also explores the effects of changing the year-to-year variability in climate as well as the mean. It estimates changes in mean monthly flows and a measure of low flow (the flow exceeded 95% of the time) in six catchments in Britain, using the UKCIP98 climate change scenarios and a calibrated hydrological model. Human-induced climate change has a different seasonal effect on flows than natural multi-decadal variability (an increase in winter and decrease in summer), and by the 2050s the climate change signal is apparent in winter and, in lowland Britain, in summer. Superimposing natural multi-decadal variability onto the human-induced climate change increases substantially the range in possible future streamflows (in some instances counteracting the climate change signal), with important implications for the development of adaptation strategies. Increased year-to-year variability in climate leads to slight increases in mean monthly flows (relative to changes due just to changes in mean climate), and slightly greater decreases in low flows. The greatest effect on low flows occurs in upland catchments.     

Singular spectrum analysis and forecasting of hydrological time series

The singular spectrum analysis (SSA) technique is applied to some hydrological univariate time series to assess its ability to uncover important information from those series, and also its forecast skill. The SSA is carried out on annual precipitation, monthly runoff, and hourly water temperature time series. Information is obtained by extracting important components or, when possible, the whole signal from the time series. The extracted components are then subject to forecast by the SSA algorithm. It is illustrated the SSA ability to extract a slowly varying component (i.e. the trend) from the precipitation time series, the trend and oscillatory components from the runoff time series, and the whole signal from the water temperature time series. The SSA was also able to accurately forecast the extracted components of these time series.     

Temporal variability of the physical and chemical water characteristics at a coastal monitoring observatory: Station ENSENADA

The temporal variability of the physical and chemical conditions of coastal waters off Ensenada, Baja California (Mexico) was characterized. A historical analysis was made based on 11 years (1998–2008) of temperature and salinity data records measured quarterly by IMECOCAL, along a transect perpendicular to the coast (CalCOFI line 100). Moreover, the physical and chemical conditions at a coastal monitoring observatory called station ENSENADA were described using a 2-year data series (October 2006–November 2008) obtained with improved temporal resolution. The historical analysis of line 100 showed marked seasonal variability in the thermohaline conditions associated with fluctuations in the flow of the equatorward California Current and the poleward California Undercurrent, as well as with coastal upwelling events whose magnitude and frequency increase towards spring–summer. Interannual variability was also observed, related to warm and/or cold ENSO phases that modify the characteristics of the water column in this coastal region. The most striking characteristics of the interannual variability at station ENSENADA were La Niña conditions recorded from summer 2007 to mid 2008. During this cold ENSO phase, temperature, salinity, dissolved oxygen, density, and dissolved inorganic carbon data revealed the anomalous presence of subsurface water at the surface layers in spring 2008. Results suggest that the coastal observatory is sensitive to the temporal variability of hydrographic conditions on shelf coastal waters (<50 km) off Ensenada in the northern BC region. Consequently, station ENSENADA would be a good location to high-frequency monitors the oceanographic conditions of the transitional region between tropical/subtropical and subarctic systems of the California Current System.     

Hydrological dynamics of snowmelt induced streamflow in a high mountain catchment of the Pyrenees under contrasting snow accumulation and duration years

Snowmelt drives a large portion of streamflow in many mountain areas of the world. However, the water paths from snowmelt to the arrival of the water in the streams are still largely unknown. This work analyzes for first time the influence of snowmelt on spring streamflow with different snow accumulation and duration, in an alpine catchment of the central Spanish Pyrenees. This study presents the water balance of the main melting months (May and June). Piezometric values, water temperature, electrical conductivity and isotope data (δ¹⁸O) allow a better understanding of the hydrological functioning of the basin during these months. Results of the water balance calculations showed that snow represented on average 73% of the water available for streamflow in May and June while precipitation during these months accounted for only 27%. However, rainfall during the melting period was important to determine the shape of the spring hydrographs. On average, 78% of the sum of both the snow water equivalent (SWE) accumulated at the beginning of May and the precipitation in May and June converted into runoff during the May–June melting period. The average evaporation-sublimation during the 2 months corresponded to 8.4% of the accumulated SWE and rainfall, so that only a small part of the water input was ultimately available for soil and groundwater storage. When snow cover disappeared from the catchment, soil water storage and streamflow showed a sharp decline. Consequently, streamflow electrical conductivity, temperature and δ¹⁸O showed a marked tipping point towards higher values. The fast hydrological response of the catchment to snow and meteorological fluctuations, as well as the marked diel fluctuations of streamflow δ¹⁸O during the melting period, strongly suggests short meltwater transit times. As a consequence of this hydrological behaviour, independently of the amount of snow accumulated and of melting date, summer streamflow remained always low, with only small runoff peaks driven by rainfall events.     

What drives high flow events in the Swiss Alps? Recent developments in wavelet spectral analysis and their application to hydrology

Extreme hydrological events are often triggered by exceptional co-variations of the relevant hydrometeorological processes and in particular by exceptional co-oscillations at various temporal scales. Wavelet and cross wavelet spectral analysis offers promising time-scale resolved analysis methods to detect and analyze such exceptional co-oscillations. This paper presents the state-of-the-art methods of wavelet spectral analysis, discusses related subtleties, potential pitfalls and recently developed solutions to overcome them and shows how wavelet spectral analysis, if combined to a rigorous significance test, can lead to reliable new insights into hydrometeorological processes for real-world applications. The presented methods are applied to detect potentially flood triggering situations in a high Alpine catchment for which a recent re-estimation of design floods encountered significant problems simulating the observed high flows. For this case study, wavelet spectral analysis of precipitation, temperature and discharge offers a powerful tool to help detecting potentially flood producing meteorological situations and to distinguish between different types of floods with respect to the prevailing critical hydrometeorological conditions. This opens very new perspectives for the analysis of model performances focusing on the occurrence and non-occurrence of different types of high flow events. Based on the obtained results, the paper summarizes important recommendations for future applications of wavelet spectral analysis in hydrology.     

低频检波器频谱补偿算法建模及仿真

采用数值仿真的方法建立了动圈式检波器的仿真模型,推导检波器传递函数,通过对实际动圈式检波器频率特性的测试,验证了动圈式检波器数值仿真模型的正确性,分析动圈检波器频率响应特性,分别对动圈式检波器的自然频率、灵敏度、阻尼比进行仿真,对不同自然频率、灵敏度、阻尼比对检波器输出频率特性的影响进行了分析,使用二阶二次型反馈补偿方法,设计检波器低频补偿结构,结果表明：数值仿真模型与实际检波器的频率响应一致,补偿结构使检波器自然频率由2 Hz降低至0.2 Hz.

     

Assimilation of streamflow and in situ soil moisture data into operational distributed hydrologic models: Effects of uncertainties in the data and initial model soil moisture states

We assess the potential of updating soil moisture states of a distributed hydrologic model by assimilating streamflow and in situ soil moisture data for high-resolution analysis and prediction of streamflow and soil moisture. The model used is the gridded Sacramento (SAC) and kinematic-wave routing models of the National Weather Service (NWS) Hydrology Laboratory’s Research Distributed Hydrologic Model (HL-RDHM) operating at an hourly time step. The data assimilation (DA) technique used is variational assimilation (VAR). Assimilating streamflow and soil moisture data into distributed hydrologic models is new and particularly challenging due to the large degrees of freedom associated with the inverse problem. This paper reports findings from the first phase of the research in which we assume, among others, perfectly known hydrometeorological forcing. The motivation for the simplification is to reduce the complexity of the problem in favour of improved understanding and easier interpretation even if it may compromise the goodness of the results. To assess the potential, two types of experiments, synthetic and real-world, were carried out for Eldon (ELDO2), a 795-km² headwater catchment located near the Oklahoma (OK) and Arkansas (AR) border in the U.S. The synthetic experiment assesses the upper bound of the performance of the assimilation procedure under the idealized conditions of no structural or parametric errors in the models, a full dynamic range and no microscale variability in the in situ observations of soil moisture, and perfectly known univariate statistics of the observational errors. The results show that assimilating in situ soil moisture data in addition to streamflow data significantly improves analysis and prediction of soil moisture and streamflow, and that assimilating streamflow observations at interior locations in addition to those at the outlet improves analysis and prediction of soil moisture within the drainage areas of the interior stream gauges and of streamflow at downstream cells along the channel network. To assess performance under more realistic conditions, but still under the assumption of perfectly known hydrometeorological forcing to allow comparisons with the synthetic experiment, an exploratory real-world experiment was carried out in which all other assumptions were lifted. The results show that, expectedly, assimilating interior flows in addition to outlet flow improves analysis as well as prediction of streamflow at stream gauge locations, but that assimilating in situ soil moisture data in addition to streamflow data provides little improvement in streamflow analysis and prediction though it reduces systematic biases in soil moisture simulation.     

南极半岛地区GPS坐标时间序列噪声分析及形变模式初探

有色噪声广泛存在于各种连续GPS站坐标时间序列,对GPS时间序列分析有重要影响.利用GAMIT/GLOBK软件解算了南极半岛地区8个GPS测站2010—2014年的实测数据,对坐标时间序列使用主分量分析法(PCA)进行了空间滤波,利用CATS软件估计了不同噪声模型下和空间滤波前后的噪声量级、站坐标时间序列参数及其不确定度,最后对南极半岛地区水平和垂向的形变模式进行了分析和讨论.结果表明,南极半岛地区GPS时间序列不仅存在白噪声,还存在较大量级的闪烁噪声,部分测站E方向在滤波前可能存在随机游走噪声;空间滤波能够有效降低这三种噪声的量级,从而有效减小线性项和周期项估计的不确定度;南极半岛地区在水平方向主要表现为板块运动,还可能存在局部性构造运动;在垂直方向上由冰川均衡调整(Glacial Isostatic Adjustment, GIA)因素引起的抬升较小,主要表现为现今冰雪质量损失引起的弹性抬升运动.     

Determining the amplitude and timing of streamflow discontinuities: A cross wavelet analysis approach

Records of natural processes, such as gradual streamflow fluctuations, are commonly interrupted by long or short disruptions from natural non‐linear responses to gradual changes, such as from river‐ice break‐ups, freezing as a result of annual solar cycles, or human causes, such as flow blocking by dams and other means, instrument calibrations and failure. The resulting abrupt or gradual shifts and missing data are considered to be discontinuities with respect to the normal signal. They differ from random noise as they do not follow any fixed distribution over time and, hence, cannot be eliminated by filtering. The multi‐scale resolution features of continuous wavelet analysis and cross wavelet analysis were used in this study to determine the amplitude and timing of such streamflow discontinuities for specific wavebands. The cross wavelet based method was able to detect the strength and timing of abrupt shifts to new streamflow levels, gaps in data records longer than the waveband of interest and a sinusoidal discontinuity curve following an underlying modeled annual signal at ±0.5 year uncertainty. Parameter testing of the time‐frequency resolution demonstrated that high temporal resolution using narrow analysis windows is favorable to high‐frequency resolution for detection of waveband‐related discontinuities. Discontinuity analysis on observed daily streamflow records from Canadian rivers showed the following: (i) that there is at least one discontinuity/year related to the annual spring flood in each record studied, and (ii) neighboring streamflows have similar discontinuity patterns. In addition, the discontinuity density of the Canadian streamflows studied in this paper exhibit 11‐year cycles that are inversely correlated with the solar intensity cycle. This suggests that more streamflow discontinuities, such as through fast freezing, snowmelt, or ice break‐up, may occur during years with slightly lowered solar insolation. Copyright © 2013 John Wiley & Sons, Ltd.     

Hydroclimatology of the Volta River Basin in West Africa: Trends and variability from 1901 to 2002

Long-term historical records of rainfall (P), runoff (Q) and other climatic factors were used to investigate hydrological variability and trends in the Volta River Basin over the period 1901-2002. Potential (E_p) and actual evaporation (E), rainfall variability index (δ), Budyko’s aridity index (I_A), evaporation ratio (C_E) and runoff ratio (C_Q) were estimated from the available hydroclimatological records. Mann-Kendall trend analysis and non-parametric Sen’s slope estimates were performed on the respective time series variables to detect monotonic trend direction and magnitude of change over time.Rainfall variability index showed that 1968 was the wettest year (δ = +1.75) while 1983 was the driest (δ = −3.03), with the last three decades being drier than any other comparable period in the hydrological history of the Volta. An increase of 0.2 mm/yr² (P < 0.05) was observed in E_p for the 1901-1969 sub-series while an increased of 1.8 mm/yr² (P < 0.01) was recorded since 1970. Rainfall increased at the rate of 0.7 mm/yr² or 49 mm/yr between 1901 and 1969, whereas a decrease of 0.2 mm/yr² (6 mm/yr) was estimated for 1970-2002 sub-series. Runoff increased significantly at the rate of 0.8 mm/yr (23 mm/yr) since 1970. Runoff before dam construction was higher (87.5 mm/yr) and more varied (CV = 41.5%) than the post-dam period with value of 73.5 mm/yr (CV = 23.9%). A 10% relative decrease in P resulted in a 16% decrease in Q between 1936 and 1998. Since 1970, all the months showed increasing runoff trends with significant slopes (P < 0.05) in 9 out of the 12 months. Possible causes, such as climate change and land cover change, on the detected changes in hydroclimatology are briefly discussed.     

Quantitative assessment of the contribution of climate variability and human activity to streamflow alteration in Dongting Lake,China

Climate variability and human activity were regarded as two contributors to streamflow alteration. However, the contributions of the two factors were still unclear in Dongting Lake. Therefore, it was crucial to quantify the relative impact of climate variability and human activity on streamflow alteration. The time series (1961–2010) was divided into three periods, namely, natural period (1961–1980), change period I (1981–2002) and change period II (2003–2010). Sensitivity analysis based on Budyko‐type equations was applied to reveal the contributions of climate variability and human activity in those two change periods, respectively. The results showed that during the change period I, climate variability was the main factor responsible for streamflow alteration in most parts of Dongting Lake, accounting for 60.07–67.27%. However, the impact of climate variability was slightly smaller than that of human activity in West Dongting Lake (the former accounting for 43.20% while the latter accounting for 56.80%). For the change period II, human activity was the dominate factor for streamflow alteration, accounting for 58.89–78.33%. The impact of climate variability gradually decreased while the impact of human activity gradually increased. Along with the intensification of the human activity, the impact of it became more dominant. The results could provide a reference for water resources planning and management decisions. Under the condition of uncontrollable climatic factor, effective measures should be put forward in controlling human activity, such as reservoir/dam operation, closed management of protected area and so on. Besides, it is essential to study the impact of climate variability on future water resources and water resource management under different climate change scenarios. Copyright © 2016 John Wiley & Sons, Ltd.     

The contrasted evolution of high and low flows and precipitation indices in the Duero basin (Spain)

Abstract

Trends in high and low flows are valuable indicators of hydrological change because they highlight changes in various parts of the frequency distribution of streamflow series. This enables improved assessment of water availability in regions with high seasonal and inter-annual variability. There has been a substantial reduction in water resources in the Duero basin (Iberian Peninsula, Spain) and other areas of the Mediterranean region during the last 50 years, and this is likely to continue because of climate change. In this study, we investigated the evolution and trends in high and low flows in the Spanish part of the Duero basin, and in equivalent or closely-related precipitation indices for the period 1961–2005. The results showed a general trend of decrease in the frequency and magnitude of high flows throughout most of the basin. Moreover, the number of days with low flows significantly increased over this period. No clear relationship was evident between the evolution of high/low flows and changes in the distribution frequencies of the precipitation series. In contrast to what was expected, the number of days with heavy precipitation and the mean annual precipitation did not show significant trends across the basin, and the number of days without rainfall decreased slightly. The divergence between precipitation and runoff evolution was more accentuated in spring and summer. In the absence of trends in precipitation, it is possible that reforestation processes in the region, and increasing temperatures in recent decades, could be related to the decreasing frequency of high flows and the increasing frequency of low flows.

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

Citation Morán-Tejeda, E., López-Moreno, J.I., Vicente-Serrano, S.M., Lorenzo-Lacruz, J. and Ceballos-Barbancho, A., 2012. The contrasted evolution of high and low flows and precipitation indices in the Duero basin (Spain). Hydrological Sciences Journal, 57 (4), 591–611.     

Spatio-temporal variability of streamflow in the Yellow River: possible causes and implications

Abstract

The water shortage in the Yellow River, China, has been aggravated by rapid population growth and global climate changes. To identify the characteristics of streamflow change in the Yellow River, approximately 50 years of natural and observed streamflow data from 23 hydrological stations were examined. The Mann-Kendall and Pettitt tests were used to detect trends and abrupt change points. The results show that both the natural and the observed streamflow in the Yellow River basin present downward trends from 1956 to 2008, and the decreasing rate of observed streamflow is generally faster than that of the natural streamflow. Larger drainage areas have higher declining rates, and the declining trends are intensified downstream within the mainstream. The possibility of abrupt changes in observed streamflow is higher than in natural streamflow, and streamflow series in the mainstream are more likely to change abruptly than those in the tributaries. In the mainstream, all the significant abrupt changes appear in the middle and latter half of the 1980s, but the abrupt changes occur somewhat earlier for observed streamflow than for natural streamflow. The significant abrupt change for the observed streamflow in the tributaries is almost isochronous with the natural streamflow and occurs from the 1970s to 1990s. It is implied that the slight reduction in precipitation is not the only direct reason for the streamflow variation. Other than the effects of climate change, land-use and land-cover changes are the main reasons for the natural streamflow change. Therefore, the increasing net water diversion by humans is responsible for the observed streamflow change. It is estimated that the influence of human activity on the declining streamflow is enhanced over time.

Editor Z.W. Kundzewicz

Citation Miao, C.Y., Shi, W., Chen, X.H., and Yang, L., 2012 Miao, C.Y., Yang, L. and Chen, X.H. 2012. The vegetation cover dynamics (1982–2006) in different erosion regions of the Yellow River basin, China. Land Degradation and Development, 23(1): 62–71. [Crossref], [Web of Science ®] , [Google Scholar]. Spatio-temporal variability of streamflow in the Yellow River: possible causes and implications. Hydrological Sciences Journal, 57 (7), 1355–1367.     

用EOF分析方法研究强震前中国大陆水平位移场时空分布特征

利用大气科学常用的经验正交函数(EOF)分解方法, 对中国大陆连续观测的基准站的水平位移每周解时间序列进行分析。 首先对时间序列中不连续的数据进行内插处理, 并通过线性拟合从时间序列中去掉长期滑动速率的影响。 结合震例研究强震前水平位移场在NS向和EW向的时间和空间的分布特征。     

Use of time series analysis for the identification of tidal effect on groundwater in the coastal area of Kimje, Korea

The purpose of this study is to apply time series analysis to investigate whether the groundwater quality in the coastal area is affected by the tide. Continuous and regular in situ monitoring data of electrical conductivity (EC) and groundwater level, and tidal level data measured by the National Oceanographic Research Institute were used for the time series analysis. Through the time series analysis, it is known that EC and groundwater level conspicuously fluctuate with two periodicities (15.4 and 0.52-day), which is very similar to those of the tide. Also the behaviors of their fluctuations vary in accordance with the tidal period. These indicate that the groundwater quality has been mainly controlled by the tidal level, and the strength of tidal effect on the groundwater quality is different according to the tidal period.