High‐frequency streamflow acquisition and bed level/flow angle estimates in a mountainous river using shallow‐water acoustic tomography

The acquisition of reliable discharge estimates is crucial in hydrological studies. This study demonstrates a promising acoustic method for measuring streamflow at high sampling rate for a long period using the fluvial acoustic tomography system (FATS). The FATS recently emerged as an innovative technique for continuous measurements of streamflow. In contrast to the traditional point/transect measurements of discharge, the FATS enables the depth‐averaged and range‐averaged flow velocity along the ray path to be measured in a fraction of a second. The field test was conducted in a shallow gravel‐bed river (0.9 m deep under low‐flow conditions, 115 m wide) for 1 month. The parameters (stream direction and bottom elevation) required for calculating the streamflow were deduced by a nonlinear regression to the discharge data from the well‐established rating curve. The cross‐sectional average velocities were automatically calculated from the acoustic data, which were collected on both riverbanks every 30 s. The FATS was connected to the internet so that the real‐time flow data could be obtained. The FATS captured discharge variations at a cut‐off frequency of approximately 70 day^?1. The stream exhibited temporal discharge changes at multiple time scales ranging from a few tens of minutes to days. Copyright © 2016 John Wiley & Sons, Ltd.     

Modelling rating curves using remotely sensed LiDAR data

Accurate stream discharge measurements are important for many hydrological studies. In remote locations, however, it is often difficult to obtain stream flow information because of the difficulty in making the discharge measurements necessary to define stage‐discharge relationships (rating curves). This study investigates the feasibility of defining rating curves by using a fluid mechanics‐based model constrained with topographic data from an airborne LiDAR scanning. The study was carried out for an 8m‐wide channel in the boreal landscape of northern Sweden. LiDAR data were used to define channel geometry above a low flow water surface along the 90‐m surveyed reach. The channel topography below the water surface was estimated using the simple assumption of a flat streambed. The roughness for the modelled reach was back calculated from a single measurment of discharge. The topographic and roughness information was then used to model a rating curve. To isolate the potential influence of the flat bed assumption, a ‘hybrid model’ rating curve was developed on the basis of data combined from the LiDAR scan and a detailed ground survey. Whereas this hybrid model rating curve was in agreement with the direct measurements of discharge, the LiDAR model rating curve was equally in agreement with the medium and high flow measurements based on confidence intervals calculated from the direct measurements. The discrepancy between the LiDAR model rating curve and the low flow measurements was likely due to reduced roughness associated with unresolved submerged bed topography. Scanning during periods of low flow can help minimize this deficiency. These results suggest that combined ground surveys and LiDAR scans or multifrequency LiDAR scans that see ‘below’ the water surface (bathymetric LiDAR) could be useful in generating data needed to run such a fluid mechanics‐based model. This opens a realm of possibility to remotely sense and monitor stream flows in channels in remote locations. Copyright © 2012 John Wiley & Sons, Ltd.     

Daily suspended sediment modelling using a fuzzy differential evolution approach / Modélisation journalière des matières en suspension par une approche d’évolution différentielle floue

Abstract

Abstract Correct estimation of the sediment volume carried by a river is important with respect to pollution, channel navigability, reservoir filling, hydroelectric equipment longevity, fish habitat, river aesthetics and scientific interests. However, conventional sediment rating curves are not able to provide sufficiently accurate results. In this study, models incorporating fuzzy logic are developed as a superior alternative to the sediment rating curve technique for determining the daily suspended sediment concentration for a given river cross-section. This study provides forecasting benchmarks for sediment concentration prediction in the form of a numerical and graphical comparison between fuzzy and rating curve models. Benchmarking was based on a five-year period of continuous streamflow and sediment concentration data from the Quebrada Blanca Station operated by the United States Geological Survey (USGS). Nine different fuzzy models were developed to estimate sediment concentration from streamflow. Each fuzzy model has a different number of membership functions. The parameters of the membership functions were found using a differential evolution algorithm. The benchmark results showed that the fuzzy models were able to produce much better results than rating curve models for the same data inputs.     

Assessment of a lumped coupled flow‐isotope model in data scarce Boreal catchments

Quantifying streamflow sources within remote, data scarce, Boreal catchments remains a significant challenge because of limited accessibility and complex, flat topography. The coupled use of hydrometric and isotopic data has previously been shown to facilitate quantification of streamflow sources, but application has generally been limited to small basins and short time scales. A lumped flow‐isotope model was used to estimate contributing streamflow sources (soil, ground, and wetland water) over a four‐year period in two large nested headwater catchments (Sapochi and Odei Rivers) in northern Manitoba, Canada. On average, the primary streamflow source was estimated as soil water (60%) in the Sapochi River, and groundwater (54%) in the Odei River. A strong seasonal influence was observed: soil water was the primary streamflow source in summer, changing to groundwater and wetlands during the winter. Interannual variability in streamflow sources was strongly linked to the presence or absence of late summer rainfall. The greatest uncertainties in source quantification were identified during the spring freshets and high precipitation events, and hence, simulations may be improved through explicit representation of the soil freeze/thaw process and data collection during this period. Assessment of primary streamflow components and qualitative uncertainty estimation using coupled isotope‐flow modelling is an effective method for first‐order identification of streamflow sources in data sparse remote headwaters. Copyright © 2016 John Wiley & Sons, Ltd.     

Suspended sediment estimation using neuro-fuzzy and neural network approaches/Estimation des matières en suspension par des approches neurofloues et à base de réseau de neurones

Abstract

The abilities of neuro-fuzzy (NF) and neural network (NN) approaches to model the streamflow–suspended sediment relationship are investigated. The NF and NN models are established for estimating current suspended sediment values using the streamflow and antecedent sediment data. The sediment rating curve and multi-linear regression are also applied to the same data. Statistic measures were used to evaluate the performance of the models. The daily streamflow and suspended sediment data for two stations—Quebrada Blanca station and Rio Valenciano station—operated by the US Geological Survey were used as case studies. Based on comparison of the results, it is found that the NF model gives better estimates than the other techniques.     

Modelling daily suspended sediment of rivers in Turkey using several data-driven techniques / Modélisation de la charge journalière en matières en suspension dans des rivières turques à l'aide de plusieurs techniques empiriques

Abstract

The transport of sediment load in rivers is important with respect to pollution, channel navigability, reservoir filling, longevity of hydroelectric equipment, fish habitat, river aesthetics and scientific interest. However, conventional sediment rating curves cannot estimate sediment load accurately. An adaptive neuro-fuzzy technique is investigated for its ability to improve the accuracy of the streamflow—suspended sediment rating curve for daily suspended sediment estimation. The daily streamflow and suspended sediment data for four stations in the Black Sea region of Turkey are used as case studies. A comparison is made between the estimates provided by the neuro-fuzzy model and those of the following models: radial basis neural network (RBNN), feed-forward neural network (FFNN), generalized regression neural network (GRNN), multi-linear regression (MLR) and sediment rating curve (SRC). Comparison of results reveals that the neuro-fuzzy model, in general, gives better estimates than the other techniques. Among the neural network techniques, the RBNN is found to perform better than the FFNN and GRNN.     

Seeing through porous media: An experimental study for unveiling interstitial flows

We describe a novel inexpensive method, utilizing particle image velocimetry (PIV) and refractive index‐matching (RIM) for visualizing and quantifying the flow field within bio‐amended porous media. To date, this technique has been limited to idealized particles, whose refractive index does not match that of fresh water and thus requires specialized and often toxic or hazardous fluids. Here, we use irregularly shaped grains made of hydrogel as the solid matrix and water as the fluid. The advantage of using water is that it provides, for the first time, the opportunity to study both hydraulic and biological processes, which typically occur in soils and streambeds. By using RIM coupled with PIV (RIM‐PIV), we measured the interstitial flow field within a cell packed with granular material consisting of hydrogel grains in a size range of 1–8 mm, both in the presence and in the absence of Sinorhizobium meliloti bacteria (strain Rm8530). We also performed experiments with fluorescent tracer (fluorescein) and fluorescent microbes (Shewanella GPF MR‐1) to test the capability of visualizing solute transport and microbial movements. Results showed that the RIM‐PIV can measure the flow field for both biofilm‐free and biofilm‐covered hydrogel grains. The fluorescent tracer injection showed the ability to visualize both physical (concave surfaces and eddies) and biological (biofilms) transient storage zones, whereas the fluorescent microbe treatment showed the ability to track microbial movements within fluids. We conclude that the proposed methodology is a promising tool to visualize and quantify biofilm attachment, growth, and detachment in a system closer to natural conditions than a 2D flow cell experiment.     

River suspended sediment modelling using a fuzzy logic approach

Correct estimation of sediment volume carried by a river is very important for many water resources projects. Conventional sediment rating curves, however, are not able to provide sufficiently accurate results. In this paper, a fuzzy logic approach is proposed to estimate suspended sediment concentration from streamflow. This study provides forecasting benchmarks for sediment concentration prediction in the form of a numerical and graphical comparison between fuzzy and rating‐curve models. Benchmarking was based on a 5‐year period of continuous streamflow and sediment concentration data of Quebrada Blanca Station operated by the United States Geological Survey. The benchmark results showed that the fuzzy model was able to produce much better results than rating‐curve models. The fuzzy model proposed in the study is site specific and does not simulate the hysteresis effects. Copyright © 2006 John Wiley & Sons, Ltd.     

Long term high frequency sediment observatory in an alpine catchment: The Arc-Isère rivers,France

We present a dataset on to the Arc-Isère long-term environmental research observatory, which is part of the Rhône Basin Long Term Environmental Research Observatory. This alpine catchment located in the French Alps is characterized by high Suspended Particulate Matter (SPM) in anthropogenized valleys. Suspended Sediment Concentrations (SSC) naturally observed in the river are very high, ranging from a few tens of milligrams per litre at low flow to tens of grams per litre during major natural hydrological events (floods, debris flows) or river dam hydraulic flushes. One research objective related to this site is to better understanding the SSC dynamics along the river using a system of nested catchments (Arvan, Arc, and Isère) in order to assess both temporal and spatial dynamics. The data allow the quantification of fine sediment yields and also the evaluation of possible morphological changes due to fine sediment deposition or resuspension. Additionally, the observatory database support studies on contaminants (either dissolved or particulate contaminants). Our monitoring includes six stations with high frequency (2–30 min) streamflow, SSC measurement using turbidity sensors, and associated automatic sampling. Discharge is measured via water level measurements and a rating curve. The oldest station (Grenoble-campus) started recording discharge and concentration data from April 2006 while others stations were built between 2009 and 2011. Data are available in an online data website called ‘Base de Données des Observatoires en Hydrologie’ (Hydrological observatory database, https://bdoh.irstea.fr/ARC-ISERE/ ) with a DOI reference for the dataset. The hydrological and sediment transport time series are stored, managed and made available to a wide community with unfettered access in order to be used at their full extent. This database is used as a data exchange tool for both scientists and operational end-users and there is an associated online tool to compute integrated fluxes.     

A technique for deriving an average event unit hydrograph from streamflow—only data for ephemeral quick-flow-dominant catchments

A technique is presented for empirical and parametric estimation of an average event unit hydrograph response curve solely from measured streamflow data for use in rainfall-runoff models with a focus on modelling flow for natural resource management. As the technique does not require rainfall data, the unit hydrograph can be derived solely from streamflow data at a temporal resolution appropriate for the response of the catchment. The response curves derived for a number of stations show a power law relationship of decay in flow after peak that can be described using a three-parameter function. The approach is best suited to ephemeral streamflow regimes dominated by surface and near-surface runoff (quick-flow component) where flow events are well-separated and largely independent of each other. Analysis of the derived unit hydrograph for 28 quick-flow-dominated catchments illustrates the range of parameter values obtained in fitting the power law.     

Changes in event-based streamflow magnitude and timing after suburban development with infiltration-based stormwater management

Green stormwater infrastructure implementation in urban watersheds has outpaced our understanding of practice effectiveness on streamflow response to precipitation events. Long-term monitoring of experimental suburban watersheds in Clarksburg, Maryland, USA, provided an opportunity to examine changes in event-based streamflow metrics in two treatment watersheds that transitioned from agriculture to suburban development with a high density of infiltration-focused stormwater control measures (SCMs). Urban Treatment 1 has predominantly single family detached housing with 33% impervious cover and 126 SCMs. Urban Treatment 2 has a mix of single family detached and attached housing with 44% impervious cover and 219 SCMs. Differences in streamflow-event magnitude and timing were assessed using a before-after-control-reference-impact design to compare urban treatment watersheds with a forested control and an urban control with detention-focused SCMs. Streamflow and precipitation events were identified from 14 years of sub-daily monitoring data with an automated approach to characterize peak streamflow, runoff yield, runoff ratio, streamflow duration, time to peak, rise rate, and precipitation depth for each event. Results indicated that streamflow magnitude and timing were altered by urbanization in the urban treatment watersheds, even with SCMs treating 100% of the impervious area. The largest hydrologic changes were observed in streamflow magnitude metrics, with greater hydrologic change in Urban Treatment 2 compared with Urban Treatment 1. Although streamflow changes were observed in both urban treatment watersheds, SCMs were able to mitigate peak flows and runoff volumes compared with the urban control. The urban control had similar impervious cover to Urban Treatment 2, but Urban Treatment 2 had more than twice the precipitation depth needed to initiate a flow response and lower median peak flow and runoff yield for events less than 20 mm. Differences in impervious cover between the Urban Treatment watersheds appeared to be a large driver of differences in streamflow response, rather than SCM density. Overall, use of infiltration-focused SCMs implemented at a watershed-scale did provide enhanced attenuation of peak flow and runoff volumes compared to centralized-detention SCMs.     

A multi‐temporal analysis of AMSR‐E data for flood and discharge monitoring during the 2008 flood in Iowa

The objective of this work is to demonstrate the potential of using passive microwave data to monitor flood and discharge conditions and to infer watershed hydraulic and hydrologic parameters. The case study is the major flood in Iowa in summer 2008. A new Polarisation Ratio Variation Index (PRVI) was developed based on a multi‐temporal analysis of 37 GHz satellite imagery from the Advanced Microwave Scanning Radiometer (AMSR‐E) to calculate and detect anomalies in soil moisture and/or inundated areas. The Robust Satellite Technique (RST) which is a change detection approach based on the analysis of historical satellite records was adopted. A rating curve has been developed to assess the relationship between PRVI values and discharge observations downstream. A time‐lag term has been introduced and adjusted to account for the changing delay between PRVI and streamflow. Moreover, the Kalman filter has been used to update the rating curve parameters in near real time. The temporal variability of the b exponent in the rating curve formula shows that it converges toward a constant value. A consistent 21‐day time lag, very close to an estimate of the time of concentration, was obtained. The agreement between observed discharge downstream and estimated discharge with and without parameters adjustment was 65 and 95%, respectively. This demonstrates the interesting role that passive microwave can play in monitoring flooding and wetness conditions and estimating key hydrologic parameters. Copyright © 2011 John Wiley & Sons, Ltd.     

Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean catchments

Abstract

The SWAT model was tested to simulate the streamflow of two small Mediterranean catchments (the Vène and the Pallas) in southern France. Model calibration and prediction uncertainty were assessed simultaneously by using three different techniques (SUFI-2, GLUE and ParaSol). Initially, a sensitivity analysis was conducted using the LH-OAT method. Subsequent sensitive parameter calibration and SWAT prediction uncertainty were analysed by considering, firstly, deterministic discharge data (assuming no uncertainty in discharge data) and secondly, uncertainty in discharge data through the development of a methodology that accounts explicitly for error in the rating curve (the stage?discharge relationship). To efficiently compare the different uncertainty methods and the effect of the uncertainty of the rating curve on model prediction uncertainty, common criteria were set for the likelihood function, the threshold value and the number of simulations. The results show that model prediction uncertainty is not only case-study specific, but also depends on the selected uncertainty analysis technique. It was also found that the 95% model prediction uncertainty interval is wider and more successful at encompassing the observations when uncertainty in the discharge data is considered explicitly. The latter source of uncertainty adds additional uncertainty to the total model prediction uncertainty.

Editor D. Koutsoyiannis; Associate editor D. Gerten

Citation Sellami, H., La Jeunesse, I., Benabdallah, S., and Vanclooster, M., 2013. Parameter and rating curve uncertainty propagation analysis of the SWAT model for two small Mediterranean watersheds. Hydrological Sciences Journal, 58 (8), 1635?1657.     

An example of application: The ecological “natural flow regime” paradigm in hydroclimatology

According to the concept of “natural flow regime,” introduced and developed in the 1990's in aquatic ecology, streamflow can be described using five basic characteristics: magnitude, frequency, duration, period of occurrence and variability. A sixth could be added to these, namely, distribution curve. Our study, which focused exclusively on the temporal variability of these six characteristics, had these objectives: (1) to compare their stationarity, (2) to determine the links among these characteristics and (3) to analyze, for the first time, their relationship to six climatic indices (Atlantic Multidecadal Oscillation, Artic Oscillation, North Atlantic Oscillation, Niño3.4, Pacific decadal Oscillation and Southern Oscillation Index). To do this, we used the Vermillon River (2670 km²) as an example, analyzing the streamflow of heavy spring floods (equal to or greater than the annual flood streamflow), as measured between 1934 and 2000.     

最大准则优化技术在贴体网格中的应用

贴体网格在地质数值模拟中具有广阔的应用前景,为解决贴体网格生成时边界离散问题,提出了最大长度准则和最大面积准则,把曲线逼近和曲面网格优化问题转化为数学优化问题,为求解该问题,提出了改进的单粒子优化算法.试验表明,最大长度准则和最大面积准则的优化效果好于常规方法;以改进的单粒子优化算法求解该问题时,计算效率是智能单粒子优化算法的30倍左右（节点量为200）,从而实现最大长度准则和最大面积准则在贴体网格生成中的应用.针对最大面积准则优化曲面网格不能控制网格步长的情况,提出了限定步长的网格优化算法,使网格步长合理化,并通过实例验证了该算法的有效性.研究成果提供了生成贴体网格时边界优化准则和求解方法,对今后复杂边界的贴体网格生成具有重要意义.     

Trends and shifts in streamflow in Hawai‘i, 1913–2008

This study addresses a need to document changes in streamflow and base flow (groundwater discharge to streams) in Hawai‘i during the past century. Statistically significant long‐term (1913–2008) downward trends were detected (using the nonparametric Mann–Kendall test) in low‐streamflow and base‐flow records. These long‐term downward trends are likely related to a statistically significant downward shift around 1943 detected (using the nonparametric Pettitt test) in index records of streamflow and base flow. The downward shift corresponds to a decrease of 22% in median streamflow and a decrease of 23% in median base flow between the periods 1913–1943 and 1943–2008. The shift coincides with other local and regional factors, including a change from a positive to a negative phase in the Pacific Decadal Oscillation, shifts in the direction of the trade winds over Hawai‘i, and a reforestation programme. The detected shift and long‐term trends reflect region‐wide changes in climatic and land‐cover factors. A weak pattern of downward trends in base flows during the period 1943–2008 may indicate a continued decrease in base flows after the 1943 shift. Downward trends were detected more commonly in base‐flow records than in high‐streamflow, peak‐flow, and rainfall records. The decrease in base flow is likely related to a decrease in groundwater storage and recharge and therefore is a valuable indicator of decreasing water availability and watershed vulnerability to hydrologic changes. Whether the downward trends will continue is largely uncertain given the uncertainty in climate‐change projections and watershed responses to changes. Copyright © 2012 John Wiley & Sons, Ltd.     

Mediating stream baseflow response to climate change: The role of basin storage

Inter‐basin differences in streamflow response to changes in regional hydroclimatology may reflect variations in storage characteristics that control the retention and release of water inputs. These aspects of storage could mediate a basin's sensitivity to climate change. The hypothesis that temporal trends in stream baseflow exhibit a more muted reaction to changes in precipitation and evapotranspiration for basins with greater storage was tested on the Oak Ridges Moraine (ORM) in Southern Ontario, Canada. Long‐term (>25 years) baseflow trends for 16 basins were compared to corresponding trends in precipitation amount and type and in potential evapotranspiration as well as shorter trends in groundwater levels for monitoring wells on the ORM. Inter‐basin differences in storage properties were characterized using physiographic, hydrogeologic, land use/land cover, and streamflow metrics. The latter included the slope of the basin's flow duration curve and basin dynamic storage. Most basins showed temporal increases in baseflow, consistent with limited evidence of increases and decreases in regional precipitation and snowfall: precipitation ratio, respectively, and recent increases in groundwater recharge along the crest of the ORM. Baseflow trend magnitude was uncorrelated to basin physiographic, hydrogeologic, land use/land cover, or flow duration curve characteristics. However, it was positively related to a basin's dynamic storage, particularly for basins with limited coverage of open water and wetlands. The dynamic storage approach assumes that a basin behaves as a first‐order dynamical system, and extensive open water and wetland areas in a basin may invalidate this assumption. Previous work suggested that smaller dynamic storage was linked to greater damping of temporal variations in water inputs and reduced interannual variability in streamflow regime. Storage and release of water inputs to a basin may assist in mediating baseflow response to temporal changes in regional hydroclimatology and may partly account for inter‐basin differences in that response. Such storage characteristics should be considered when forecasting the impacts of climate change on regional streamflow.     

Effect of forest recovery on summer streamflow in small forested watersheds,Northeastern China

The hydrological effect of forest recovery is receiving renewed interest globally because information on forest carbon–water relationship is critically needed to support carbon management through reforestation and sustainable water management. In Northeastern China, summer (June to August) streamflow accounts for about 50% of total annual streamflow and is vital to water supply and management in the region. Understanding how forest recovery may affect streamflow is important to both reforestation campaign and long‐term water sustainability. In this study, we analysed 33 years of summer hydrologic data (1970–2002) from two comparable small‐scale watersheds located in the Xiaoxing'anling, Northeastern China. Time series analysis and two graphic methods (double mass curve and flow duration curve) with statistical testing as well as long‐term data on forest cover changes and climate were used. Our results show that the significant streamflow reduction as a result of reforestation occurred when forest cover reached 70% or 10 years after planting. After forest cover reached 85%, water reduction became stabilized. The accumulative streamflow reduction in 2002 reached 8·61% of the total accumulative streamflow. Among those water reduced, high flows (from 5 to 25 percentiles) were mostly affected, demonstrating that northeastern forests have an important role in reducing high flows. Implications of these results are discussed in the context of climate change, reforestation and water resource management. Copyright © 2011 John Wiley & Sons, Ltd.     

Estimation of river discharge from non-trapezoidal open channel using QuickBird-2 satellite imagery/Utilisation des images satellites de Quickbird-2 pour le calcul des débits fluviaux en chenaux ouverts non-trapézoïdaux

Abstract

Abstract River discharge is traditionally acquired by measuring water stage and then converting the water stage to discharge by using a stage–discharge rating curve. The possibility of monitoring river discharge by satellite has not been adequately studied hitherto, because of the difficulty in making sufficiently precise measurements of the water surface. Since the successful launch of commercial satellites with very-high-resolution sensors, it has become possible to derive ground information from satellite data. To determine river discharge in a non-trapezoidal open channel, an efficient approach has been developed that uses mainly satellite data. The method, which focuses on the measurement of surface water width coupled with river width–stage and ?remote? stage–discharge rating curves, was applied to the Yangtze River (Changjiang) and an accurate estimate of river discharge was obtained. The method can be regarded as ancillary to traditional field measurement methods or other remote sensing methods.