Comparison of non-Gaussian multicomponent and periodic autoregressive models for river flow

The Non-Gaussian Multicomponent model for river flow (NGM) of Vandewiele and Dom is modified in order to facilitate maximum likelihood estimation. It is also generalized so that a wider variety of river flows at a diversity of time steps can be modeled. This model is applied to two basins in Belgium and France with very different areas, both at monthly and weekly time scale. Results on the quality of forecasting and simulation (especially simulation of low and high flow volumes) are compared with those of classical Periodic Autoregressive models (PAR). Results with NGM are always better, in most cases considerably better. This is due to the fact that NGM models explicitly take into consideration the presence of so called flow components, like baseflow and direct flow recession, which are phenomena well known to hydrologists.     

Decoupling the effects of deforestation and climate variability in the Tapajós river basin in the Brazilian Amazon

Tropical river basins are experiencing major hydrological alterations as a result of climate variability and deforestation. These drivers of flow changes are often difficult to isolate in large basins based on either observations or experiments; however, combining these methods with numerical models can help identify the contribution of climate and deforestation to hydrological alterations. This paper presents a study carried out in the Tapaj?s River (Brazil), a 477,000 km² basin in South‐eastern Amazonia, in which we analysed the role of annual land cover change on daily river flows. Analysis of observed spatial and temporal trends in rainfall, forest cover, and river flow metrics for 1976 to 2008 indicates a significant shortening of the wet season and reduction in river flows through most of the basin despite no significant trend in annual precipitation. Coincident with seasonal trends over the past 4 decades, over 35% of the original forest (140,000 out of 400,000 km²) was cleared. In order to determine the effects of land clearing and rainfall variability to trends in river flows, we conducted hindcast simulations with ED2 + R, a terrestrial biosphere model incorporating fine scale ecosystem heterogeneity arising from annual land‐use change and linked to a flow routing scheme. The simulations indicated basin‐wide increases in dry season flows caused by land cover transitions beginning in the early 1990s when forest cover dropped to 80% of its original extent. Simulations of historical potential vegetation in the absence of land cover transitions indicate that reduction in rainfall during the dry season (mean of ?9 mm per month) would have had an opposite and larger magnitude effect than deforestation (maximum of +4 mm/month), leading to the overall net negative trend in river flows. In light of the expected increase in future climate variability and water infrastructure development in the Amazon and other tropical basins, this study presents an approach for analysing how multiple drivers of change are altering regional hydrology and water resources management.     

Climate impacts on river flow: projections for the Medway catchment,UK, with UKCP09 and CATCHMOD

The potential impact of climate change on areas of strategic importance for water resources remains a concern. Here, river flow projections for the River Medway, above Teston in southeast England are presented, which is just such an area of strategic importance. The river flow projections use climate inputs from the Hadley Centre Regional Climate Model (HadRM3) for the time period 1960–2080 (a subset of the early release UKCP09 projections). River flow predictions are calculated using CATCHMOD, the main river flow prediction tool of the Environment Agency (EA) of England and Wales. In order to use this tool in the best way for climate change predictions, model setup and performance are analysed using sensitivity and uncertainty analysis. The model's representation of hydrological processes is discussed and the direct percolation and first linear storage constant parameters are found to strongly affect model results in a complex way, with the former more important for low flows and the latter for high flows. The uncertainty in predictions resulting from the hydrological model parameters is demonstrated and the projections of river flow under future climate are analysed. A clear climate change impact signal is evident in the results with a persistent lowering of mean daily river flows for all months and for all projection time slices. Results indicate that a projection of lower flows under future climate is valid even taking into account the uncertainties considered in this modelling chain exercise. The model parameter uncertainty becomes more significant under future climate as the river flows become lower. This has significant implications for those making policy decisions based on such modelling results. Copyright © 2010 John Wiley & Sons, Ltd.     

Modelling floodplain flows using a two-dimensional finite element model

A prototype two-dimensional finite element flow model for depth-averaged free surface flows was developed for floodplain environments. Limited refinement of the model's physical representation was undertaken and the enhanced scheme applied to an 11 km river channel/floodplain reach in the U.K. Preliminary model results indicate that this modelling approach can be used to identify dynamic variations in the flow field parameters over length scales of the order of 10-100 m. Potentially, such data have the ability to permit detailed analysis of short-term floodplain sedimentary dynamics.     

Incorporating Groundwater-Surface Water Interaction into River Management Models

Accurate representation of groundwater-surface water interactions is critical to modeling low river flows in the semi-arid southwestern United States. Although a number of groundwater-surface water models exist, they are seldom integrated with river operation/management models. A link between the object-oriented river and reservoir operations model, RiverWare, and the groundwater model, MODFLOW, was developed to incorporate groundwater-surface water interaction processes, such as river seepage/gains, riparian evapotranspiration, and irrigation return flows, into a rule-based water allocations model. An explicit approach is used in which the two models run in tandem, exchanging data once in each computational time step. Because the MODFLOW grid is typically at a finer resolution than RiverWare objects, the linked model employs spatial interpolation and summation for compatible communication of exchanged variables. The performance of the linked model is illustrated through two applications in the Middle Rio Grande Basin in New Mexico where overappropriation impacts endangered species habitats. In one application, the linked model results are compared with historical data; the other illustrates use of the linked model for determining management strategies needed to attain an in-stream flow target. The flows predicted by the linked model at gauge locations are reasonably accurate except during a few very low flow periods when discrepancies may be attributable to stream gaging uncertainties or inaccurate documentation of diversions. The linked model accounted for complex diversions, releases, groundwater pumpage, irrigation return flows, and seepage between the groundwater system and canals/drains to achieve a schedule of releases that satisfied the in-stream target flow.     

Modeling surface water–groundwater interaction in New Zealand: Model development and application

Most rivers worldwide have a strong interaction with groundwater when they leave the mountains and flow over alluvial plains before flowing into the seas or disappearing in the deserts, and in New Zealand, typically, rivers lose water to the groundwater in the upper plains and generally gain water from the groundwater in the lower plains. Aiming at simulating surface water–groundwater interaction nationally in New Zealand, we developed a conceptual groundwater module for the national hydrologic model TopNet to simulate surface water–groundwater interaction, groundwater flow, and intercatchment groundwater flow. The developed model was applied to the Pareora catchment in South Island of New Zealand, where there are concurrent spot gauged flows. Results show that the model simulations not only fit quite well to flow measurement but also to concurrent spot gauged flows, and compared to the original TopNet, it has a significant improvement in the low flows. Sensitivity analysis shows river flow is sensitive to the river losing/gaining rate instead of groundwater characteristic, while groundwater storage is sensitive to both river losing/gaining rate and groundwater characteristic. This indicates our conceptual approach is promising for nationwide modeling without the large amount of geology and aquifer data typically required by physically‐based modeling approaches.     

Simulation of river flow in Britain under climate change: Baseline performance and future seasonal changes

Climate change is likely to manifest in river flow changes across the globe, which could have wide-ranging consequences for society and the natural environment. A number of previous studies used the UK Climate Projections 2009 (UKCP09) to investigate the potential impacts on river flows in Britain, but these projections were recently updated by the release of UKCP18, thus there is a need to update flow studies. Here, the UKCP18 Regional (12 km) projections are applied using a national-scale grid-based hydrological model, to investigate potential future changes in seasonal mean river flows across Great Britain. Analysis of hydrological model performance using baseline climate model data (1980–2010) shows relatively good agreement with use of observation-based data, particularly after application of a monthly precipitation bias-correction. Analysis of seasonal mean flow changes for two future time-slices (2020–2050 and 2050–2080) suggests large decreases in summer flows across the country (median −45% by 2050–2080), but possible increases in winter flows (median 9% by 2050–2080), especially in the north and west. Information on the potential range of flow changes using the latest projections is necessary to develop appropriate adaptation strategies, and comparisons with previous projections can help update existing plans, although such comparisons are often not straightforward.     

Wavelet-ANFIS models for forecasting monsoon flows: Case study for the Gandak River (India)

WANFIS, a conjunction model of discreet wavelet transform (DWT) and adaptive neuro-fuzzy inference system (ANFIS) was developed for forecasting the current-day flow in a river when only available data are historical flows. Discreet wavelet transform decomposed the observed flow time series (OFTS) into wavelet components which captured useful information on three resolution levels. A smoothened flow time series (SFTS) was formed by filtering out the noise wavelet components and recombining the effective wavelet components. WANFIS model is essentially an ANFIS model with SFTS hydrograph as the input, while ANFIS and autoregression (AR) models, developed for comparison purpose, use OFTS hydrograph as input. For performance evaluation, the developed models were utilized for predicting daily monsoon flows for the Gandak River in Bihar state of India. During monsoon (June–October), this river carries large flows making the entire North Bihar unsafe for habitation or cultivation. Based on various performance indices, it was concluded that WANFIS models simulate the monsoon flows in the Gandak more reliably than ANFIS and AR models. The best performing WANFIS model, with four previous days’ flows as input, predicted the current-day Gandak flows with 80.7% accuracy while ANFIS and AR models predicted it with only 71.8 and 51.2% accuracies.     

Dissecting the effect of rainfall variability on the statistical structure of peak flows

This study examines the role of rainfall variability on the spatial scaling structure of peak flows using the Whitewater River basin in Kansas as an illustration. Specifically, we investigate the effect of rainfall on the scatter, the scale break and the power law (peak flows vs. upstream areas) regression exponent. We illustrate why considering individual hydrographs at the outlet of a basin can lead to misleading interpretations of the effects of rainfall variability. We begin with the simple scenario of a basin receiving spatially uniform rainfall of varying intensities and durations and subsequently investigate the role of storm advection velocity, storm variability characterized by variance, spatial correlation and intermittency. Finally, we use a realistic space–time rainfall field obtained from a popular rainfall model that combines the aforementioned features. For each of these scenarios, we employ a recent formulation of flow velocity for a network of channels, assume idealized conditions of runoff generation and flow dynamics and calculate peak flow scaling exponents, which are then compared to the scaling exponent of the width function maxima. Our results show that the peak flow scaling exponent is always larger than the width function scaling exponent. The simulation scenarios are used to identify the smaller scale basins, whose response is dominated by the rainfall variability and the larger scale basins, which are driven by rainfall volume, river network aggregation and flow dynamics. The rainfall variability has a greater impact on peak flows at smaller scales. The effect of rainfall variability is reduced for larger scale basins as the river network aggregates and smoothes out the storm variability. The results obtained from simple scenarios are used to make rigorous interpretations of the peak flow scaling structure that is obtained from rainfall generated with the space–time rainfall model and realistic rainfall fields derived from NEXRAD radar data.     

Modelling the effect of time‐dependent river dune evolution on bed roughness and stage

This paper presents an approach to incorporate time‐dependent dune evolution in the determination of bed roughness coefficients applied in hydraulic models. Dune roughness is calculated by using the process‐based dune evolution model of Paarlberg et al. ( 2009 ) and the empirical dune roughness predictor of Van Rijn ( 1984 ). The approach is illustrated by applying it to a river of simple geometry in the 1‐D hydraulic model SOBEK for two different flood wave shapes. Calculated dune heights clearly show a dependency on rate of change in discharge with time: dunes grow to larger heights for a flood wave with a smaller rate of change. Bed roughness coefficients computed using the new approach can be up to 10% higher than roughness coefficients based on calibration, with the largest differences at low flows. As a result of this larger bed roughness, computed water depths can be up to 15% larger at low flow. The new approach helps to reduce uncertainties in bed roughness coefficients of flow models, especially for river systems with strong variations in discharge with time. Copyright © 2010 John Wiley & Sons, Ltd.     

Fractal analysis of flow of the river Warta

A long time series (170 years) of daily flows of the river Warta (Poland) are subject to fractal analysis. A binary variable (renewal stream) illustrating excursions of the process of flow is examined. The raw series is subject to de-seasonalization and normalization. Fractal dimensions of crossings of Warta flows are determined using a novel variant of the box-counting method. Temporal variability of the flow process is studied by determination of fractal dimensions for shifted horizons of 10 or 30 years length. Spectral properties are compared between the time series of flows, and the fractional Brownian motion which describes both the fractal structure of the process and the Hurst phenomenon. The approach may be useful in further studies of non-stationary of the process of flow, analysis of extreme hydrological events and synthetic flow generation.     

Stream flow characterization and feature detection using a discrete wavelet transform

An exploration of the wavelet transform as applied to daily river discharge records demonstrates its strong potential for quantifying stream flow variability. Both periodic and non-periodic features are detected equally, and their locations in time preserved. Wavelet scalograms often reveal structures that are obscure in raw discharge data. Integration of transform magnitude vectors over time yields wavelet spectra that reflect the characteristic time-scales of a river's flow, which in turn are controlled by the hydroclimatic regime. For example, snowmelt rivers in Colorado possess maximum wavelet spectral energy at time-scales on the order of 4 months owing to sustained high summer flows; Hawaiian streams display high energies at time-scales of a few days, reflecting the domination of brief rainstorm events. Wavelet spectral analyses of daily discharge records for 91 rivers in the US and on tropical islands indicate that this is a simple and robust way to characterize stream flow variability. Wavelet spectral shape is controlled by the distribution of event time-scales, which in turn reflects the timing, variability and often the mechanism of water delivery to the river. Five hydroclimatic regions, listed here in order of decreasing seasonality and increasing pulsatory nature, are described from the wavelet spectral analysis: (a) western snowmelt, (b) north-eastern snowmelt, (c) mid-central humid, (d) south-western arid and (e) ‘rainstorm island’. Spectral shape is qualitatively diagnostic for three of these regions. While more work is needed to establish the use of wavelets for hydrograph analysis, our results suggest that river flows may be effectively classified into distinct hydroclimatic categories using this approach. © 1998 John Wiley & Sons, Ltd.     

On the Coupling Between Channel Level and Surface Ground-Water Flows

This paper is devoted to a mathematical analysis of some general models of mass transport and other coupled physical processes developed in simultaneous flows of surface, soil and ground waters. Such models are widely used for forecasting (numerical simulation) of a hydrological cycle for concrete territories. The mathematical models that proved a more realistic approach are obtained by combining several mathematical models for local processes. The water-exchange models take into account the following factors: Water flows in confined and unconfined aquifers, vertical moisture migration allowing earth surface evaporation, open-channel flow simulated by one-dimensional hydraulic equations, transport of contamination, etc. These models may have different levels of sophistication. We illustrate the type of mathematical singularities which may appear by considering a simple model on the coupling of a surface flow of surface and ground waters with the flow of a line channel or river.     

Impact assessment of reservoir operation in the context of climate change adaptation in the Chao Phraya River basin

Climate change adaptation has become the current focus of research due to the remarkable potential of climate change to alter the spatial and temporal distribution of global water availability. Although reservoir operation is a potential adaptation option, earlier studies explicitly demonstrated only its historical quantitative effects. Therefore, this article evaluated the possibility of reservoir operation from an adaptation viewpoint for regulating the future flow using the H08 global hydrological model with the Chao Phraya River basin as a case study. This basin is the largest river system in Thailand and has often been affected by extreme weather challenges in the past. Future climate scenarios were constructed from the bias-corrected outputs of three general circulation models from 2080 to 2099 under RCP4.5 and RCP8.5. The important conclusions that can be drawn from this study are as follows: (i) the operation of existing and hypothetical (i.e., construction under planning) reservoirs cannot reduce the future high flows below the channel carrying capacity, although it can increase low flows in the basin. This indicates that changes in the magnitude of future high flow due to climate change are likely to be larger than those achieved by reservoir operation and there is a need for other adaptation options. (ii) A combination of reservoir operation and afforestation was considered as an adaptation strategy, but the magnitude of the discharge reduction in the wet season was still smaller than the increase caused by warming. This further signifies the necessity of combining other structural, as well as non-structural, measures. Overall, this adaptation approach for assessing the effect of reservoir operation in reducing the climate change impacts using H08 model can be applied not only in the study area but also in other places where climate change signals are robust.     

Analysis of channel transmission losses in a dryland river reach in north‐eastern Brazil using streamflow series,groundwater level series and multi‐temporal satellite data

Scarcity of hydrological data, especially streamflow discharge and groundwater level series, restricts the understanding of channel transmission losses (TL) in drylands. Furthermore, the lack of information on spatial river dynamics encompasses high uncertainty on TL analysis in large rivers. The objective of this study was to combine the information from streamflow and groundwater level series with multi‐temporal satellite data to derive a hydrological concept of TL for a reach of the Middle Jaguaribe River (MJR) in semi‐arid north‐eastern Brazil. Based on this analysis, we proposed strategies for its modelling and simulation. TL take place in an alluvium, where river and groundwater can be considered to be hydraulically connected. Most losses certainly infiltrated only through streambed and levees and not through the flood plains, as could be shown by satellite image analysis. TL events whose input river flows were smaller than a threshold did not reach the outlet of the MJR. TL events whose input flows were higher than this threshold reached the outlet losing on average 30% of their input. During the dry seasons (DS) and at the beginning of rainy seasons (DS/BRS), no river flow is expected for pre‐events, and events have vertical infiltration into the alluvium. At the middle and the end of the rainy seasons (MRS/ERS), river flow sustained by base flow occurs before/after events, and lateral infiltration into the alluvium plays a major role. Thus, the MJR shifts from being a losing river at DS/BRS to become a losing/gaining (mostly losing) river at MRS/ERS. A model of this system has to include the coupling of river and groundwater flow processes linked by a leakage approach. Copyright © 2012 John Wiley & Sons, Ltd.     

Analytical study of the transverse distribution of along-channel and transverse residual flows in tidal estuaries

We present an analytical model to decompose complex along-channel and transverse residual flows into components induced by individual mechanisms. The model describes the transverse distribution of residual flows in tidally dominated estuaries. Scaling and perturbation techniques are used to obtain analytical solutions for residual flows over arbitrary across-channel bed profiles. The flows are induced by horizontal density gradients, tidal rectification processes, river discharge, wind, channel curvature and the earth's rotation. These rectification processes induce residual flows that are up-estuary to the right and down-estuary to the left of an estuarine channel (looking up-estuary in the northern hemisphere). The tidal rectification processes fundamentally change the transverse structure of along-channel residual flows in many tidal estuaries, as these processes cause the flows to be internally asymmetric about the mid-axis of the channel for relatively large tidal velocities, steep channels or narrow estuaries. In addition, velocity scales are derived from the analytical solutions to estimate the relative importance of the various residual flow mechanisms from estuarine parameters. A case study of a transect across the Upper Chesapeake Bay showed that important features of the residual flow observed in that transect are reproduced and explained by the analytical model. The velocity scales were able to identify the relevant residual flow mechanisms as well. The tidal rectification processes considered here result from advection of along-channel tidal momentum by Coriolis-induced transverse tidal currents.     

Teleconnection between low flows and large-scale climate indices in Texas River basins

Understanding low flow variability is critical for assessing water quality and health of riverine ecosystems in a river basin. Low flows are dependent on human water abstraction as well as the climate variability. This paper investigates the changing nature of low flows and their association with large-scale climate variability for different watersheds in the State of Texas, USA. For this purpose, we employed trend, wavelet analysis and linear as well as nonlinear correlations to identify important changes in low flow characteristics for three stream-gauging stations selected from different (i.e. Brazos, Colorado and Trinity) river basins located in Texas for the time period of 1916–1959 and 1960–2003. We also investigated the teleconnections between low flow variables and the large-scale climate indices (NINO 3.4, SOI and PDO) using cross wavelet analysis as well as their linear and non-linear correlation relationship. Our results indicated that the low flow magnitudes have shown considerable different characteristics for selected river basins during two separate time periods (1916–1959 and 1960–2003). Based on cross wavelet analysis, we identified that the low flows in selected stations of Colorado and Trinity River basins are likely to be influenced by all three large-scale climate indices. In addition to that, we identified that low flows are more nonlinearly associated with climate indices. Among the selected River basins, the stronger association between low flows and large scale climate indices are observed for Trinity River basin. The results from this study can help in better understanding of low flow hydrology and their potential relationship with large scale indices.     

Assessment of the flow regime alterations in the middle reach of the Yangtze River associated with dam construction: potential ecological implications

Hydrological regimes strongly influence the biotic diversity of river ecosystems by structuring physical habitat within river channels and on floodplains. Modification of hydrological regimes by dam construction can have important consequences for river ecosystems. This study examines the impacts of the construction of two dams, the Gezhouba Dam and the Three Gorges Dam, on the hydrological regime of the Yangtze River in China. Analysis of hydrological change before and after dam construction is investigated by evaluating changes in the medians and ranges of variability of 33 hydrological parameters. Results show that the hydrological impact of the Gezhouba Dam is relatively small, affecting mainly the medians and variability of low flows, the rate of rise, and the number of hydrological reversals. The closure of the Three Gorges Dam has substantially altered the downstream flow regime, affecting the seasonal distribution of flows, the variability of flows, the magnitude of minimum flows, low‐flow pulses, the rate of rise, and hydrological reversals. These changes in flow regime have greatly influenced the aquatic biodiversity and fish community structure within the Yangtze River. In particular, populations of migratory fish have been negatively impacted. The results help to identify the magnitudes of hydrological alteration associated with the construction of dams on this important large river and also provide useful information to guide strategies aimed at restoration of the river's ecosystems. Copyright © 2016 John Wiley & Sons, Ltd.     

Estimating daily streamflow in the Congo Basin using satellite-derived data and a semi-distributed hydrological model

ABSTRACT

The application of remotely-sensed data for hydrological modeling of the Congo Basin is presented. Satellite-derived data, including TRMM precipitation, are used as inputs to drive the USGS Geospatial Streamflow Model (GeoSFM) to estimate daily river discharge over the basin from 1998 to 2012. Physically-based parameterization was augmented with a spatially-distributed calibration that enables GeoSFM to simulate hydrological processes such as the slowing effect of the Cuvette Centrale. The resulting simulated long-term mean of daily flows and the observed flow at the Kinshasa gauge were comparable (40 631 and 40 638 m³/s respectively), in the 7-year validation period (2004–2010), with no significant bias and a Nash-Sutcliffe model efficiency coefficient of 0.70. Modeled daily flows and aggregated monthly river outflows (compared to historical averages) for additional sites confirm the model reliability in capturing flow timing and seasonality across the basin, but sometimes fails to accurately predict flow magnitude. The results of this model can be useful in research and decision-making contexts and validate the application of satellite-based hydrological models driven for large, data-scarce river systems such as the Congo.     

Integrated Catchment Modelling

The recent drought in the UK has focused attention on the requirement for more effective groundwater management practices in order to reduce the interference of groundwater abstraction on river flows to acceptable levels. Quantification of the impacts and the assessment of alternative management strategies requires the use of mathematical models. An Integrated Catchment Management Model is described which permits the direct assessment of alternative groundwater management practices on river flows. The model utilises a modified version of the Stanford Watershed Model for groundwater recharge estimation and for the computation of the surface and interflow components of runoff. The river system is incorporated implicitly in an integrated finite difference groundwater model. Groundwater flow to or from the river system is computed as a function of river level, which in turn is related to stage discharge characteristics of discrete reaches of the river system. The model has now been applied to a number of important groundwater systems in southern and eastern England. The calibration and verification results achieved in application to the River Allen catchment are presented. The approach maximises the use of readily available hydrological and hydrogeological information, and gives the water resources planner a sound framework and support for decision making.