Determination of the drainage structure of a watershed using a digital elevation model and a digital river and lake network

Distributed hydrological models require a detailed definition of a watershed's internal drainage structure. The conventional approach to obtain this drainage structure is to use an eight flow direction matrix (D8) which is derived from a raster digital elevation model (DEM). However, this approach leads to a rather coarse drainage structure when monitoring or gauging stations need to be accurately located within a watershed. This is largely due to limitations of the D8 approach and the lack of information over flat areas and pits. The D8 approach alone is also unable to differentiate lakes from plain areas.

To avoid these problems a new approach, using a digital river and lake network (DRLN) as input in addition to the DEM, has been developed. This new approach allows for an accurate fit between the DRLN and the modelled drainage structure, which is represented by a flow direction matrix and a modelled watercourse network. More importantly, the identification of lakes within the modelled network is now possible. The proposed approach, which is largely rooted in the D8 approach, uses the DRLN to correct modelled flow directions and network calculations. For DEM cells overlapped by the DRLN, flow directions are determined using DRLN connections only. The flow directions of the other DEM cells are evaluated with the D8 approach which uses a DEM that has been modified as a function of distance to the DRLN.

The proposed approach has been tested on the Chaudière River watershed in southern Québec, Canada. The modelled watershed drainage structure showed a high level of coherence with the DRLN. A comparison between the results obtained with the D8 approach and those obtained by the proposed approach clearly demonstrated an improvement over the conventionally modelled drainage structure. The proposed approach will benefit hydrological models which require data such as a flow direction matrix, a river and lake network and sub-watersheds for drainage structure information.     

A comparison of two stochastic inverse methods in a field-scale application

Inverse modeling is a useful tool in ground water flow modeling studies. The most frequent difficulties encountered when using this technique are the lack of conditioning information (e.g., heads and transmissivities), the uncertainty in available data, and the nonuniqueness of the solution. These problems can be addressed and quantified through a stochastic Monte Carlo approach. The aim of this work was to compare the applicability of two stochastic inverse modeling approaches in a field-scale application. The multi-scaling (MS) approach uses a downscaling parameterization procedure that is not based on geostatistics. The pilot point (PP) approach uses geostatistical random fields as initial transmissivity values and an experimental variogram to condition the calibration. The studied area (375 km2) is part of a regional aquifer, northwest of Montreal in the St. Lawrence lowlands (southern Québec). It is located in limestone, dolomite, and sandstone formations, and is mostly a fractured porous medium. The MS approach generated small errors on heads, but the calibrated transmissivity fields did not reproduce the variogram of observed transmissivities. The PP approach generated larger errors on heads but better reproduced the spatial structure of observed transmissivities. The PP approach was also less sensitive to uncertainty in head measurements. If reliable heads are available but no transmissivities are measured, the MS approach provides useful results. If reliable transmissivities with a well inferred spatial structure are available, then the PP approach is a better alternative. This approach however must be used with caution if measured transmissivities are not reliable.     

Inverse problems of gravimetry as retrieval of reliable information under uncertainty

The guaranteed approach to the solution of inverse problems of gravimetry, which is fundamentally different from the common solution, is presented. Instead of providing single (optimum) estimates of the model parameters, whose quality is, generally, random, the interpretation in the suggested approach yields that volume of reliable information on disturbing objects, which is contained in the field measurements, together with the a priori constraints. The method of solving the inverse problem of gravimetry is developed within this approach, where, in contrast to the conventional approach, both the geometrical parameters of the geological bodies and the densities of their composing rocks are treated as unknowns. The generalized assembly algorithm suggested by V.N. Strakhov is proposed as a basic working tool to implement this approach. The results of testing this algorithm and the guaranteed approach itself on the model and practical examples are discussed.     

Radionuclide transport during glacial cycles: Comparison of two approaches for representing flow transients

The effect of future, transient ice sheet movement and permafrost development on transport of radionuclides from a proposed repository site is investigated using numerical groundwater flow and radionuclide transport modelling. Two different transport approaches are compared, both utilizing groundwater flow simulations of future climate conditions. The first transport approach uses steady-state particle trajectories representing temperate climate conditions, but modifies the transport velocity along the trajectories according to the changing climate. The second approach is pseudo-transient by performing particle tracking in each individual flow field representing a given time epoch.Two different climate sequences are analyzed. First, a simplified sequence is assessed in order to understand if the two different transport approaches yield significantly different breakthrough characteristics. Second, a sequence representing conditions relevant for real safety assessment applications is considered.Results indicate that the transport approach using fixed trajectories tends to significantly over predict breakthrough during permafrost conditions relative to the pseudo-transient approach. The major difference between the two approaches is related to discharge locations. The fixed trajectory approach yields discharge locations constant in time whereas the pseudo-transient approach is characterized by discharge centres moving in time according to the different climate conditions.     

Seismic reliability analysis of urban water distribution network

An approach to analyze the seismic reliability of water distribution networks by combining a hydraulic analysis with a first-order reliability method （FORM）, is proposed in this paper. The hydraulic analysis method for normal conditions is modified to accommodate the special conditions necessary to perform a seismic hydraulic analysis. In order to calculate the leakage area and leaking flow of the pipelines in the hydraulic analysis method, a new leakage model established from the seismic response analysis of buried pipelines is presented. To validate the proposed approach, a network with 17 nodes and 24 pipelines is investigated in detail. The approach is also applied to an actual project consisting of 463 nodes and 767 pipelines. The results show that the proposed approach achieves satisfactory results in analyzing the seismic reliability of large-scale water distribution networks.     

Group-based estimation of missing hydrological data: I. Approach and general methodology

Abstract

In this first paper in a set of two, the problem of estimating missing segments in streamflow records is described. The group approach, different from the traditional single-valued approach, is proposed and explained. The approach perceives the hydrological data as sequence of groups rather than single-valued observations. The techniques suggested to handle the group approach are regression, time series analysis, partitioning modelling, and artificial neural networks. Pertinent literature is reviewed and background material is used to support the group approach. Implementation and comparisons of models' performance are deferred to the second paper.     

Correction of Discretization Errors Simulated at Supply Wells

Many hydrogeology problems require predictions of hydraulic heads in a supply well. In most cases, the regional hydraulic response to groundwater withdrawal is best approximated using a numerical model; however, simulated hydraulic heads at supply wells are subject to errors associated with model discretization and well loss. An approach for correcting the simulated head at a pumping node is described here. The approach corrects for errors associated with model discretization and can incorporate the user's knowledge of well loss. The approach is model independent, can be applied to finite difference or finite element models, and allows the numerical model to remain somewhat coarsely discretized and therefore numerically efficient. Because the correction is implemented external to the numerical model, one important benefit of this approach is that a response matrix, reduced model approach can be supported even when nonlinear well loss is considered.     

Assessing entrainment of bed material in a debris‐flow event: a theoretical approach incorporating Monte Carlo method

Entrainment of underlying bed sediment by a debris flow can significantly increase the debris‐flow magnitude. To study this phenomenon, a theoretical approach to assessing bed‐sediment entrainment is presented. The approach is based on a static approximation that bed‐sediment entrainment occurs when the shearing stress of the flow is sufficiently high to overcome the basal resistance of the bed sediment. In order to delineate erodible zones in a channel, we analyze the critical condition of this static equilibrium model, and subsequently propose a new concept of a critical line to detect the entrainment reaches in a channel. Considering the spatial and temporal uncertainties of the input parameter, the approach is further incorporated within a Monte Carlo method, and the distribution of entrainment zones and post‐entrainment volumes can be analyzed. This approach is illustrated by back‐analysis of the 2010 Yohutagawa debris‐flow event, Japan. Results from 10 000 trials of Monte Carlo simulation are compared with the in situ surveys. It is shown that the present approach can be satisfactorily used to delineate erodible zones and estimate possible entrainment volume of the event. Discussion regarding the sensitivities and limitations of the approach concludes the paper. Copyright © 2015 John Wiley & Sons, Ltd.     

Thermodynamically constrained averaging theory approach for modeling flow and transport phenomena in porous medium systems: 3. Single-fluid-phase flow

This work is the third in a series of papers on the thermodynamically constrained averaging theory (TCAT) approach to modeling flow and transport phenomena in multiscale porous medium systems. Building upon the general TCAT framework and the mathematical foundation presented in previous works in this series, we demonstrate the TCAT approach for the case of single-fluid-phase flow. The formulated model is based upon conservation equations for mass, momentum, and energy and a general entropy inequality constraint, which is developed to guide model closure. A specific example of a closed model is derived under limiting assumptions using a linearization approach and these results are compared and contrasted with the traditional single-phase-flow model. Potential extensions to this work are discussed. Specific advancements in this work beyond previous averaging theory approaches to single-phase flow include use of macroscale thermodynamics that is averaged from the microscale, the use of derived equilibrium conditions to guide a flux–force pair approach to simplification, use of a general Lagrange multiplier approach to connect conservation equation constraints to the entropy inequality, and a focus on producing complete, closed models that are solvable.     

Analytical approach for sheet flow transport in purely acceleration-skewed oscillatory flow

An instantaneous analytical approach is developed to predict sheet flow transport in purely acceleration-skewed oscillatory flow. The approach is derived from exponential approximations of velocity and concentration profiles above a mobile seabed, and it particularly considers factors of phase lead; phase lag (i.e. phase residual and phase shift); acceleration modification; and asymmetries in shear stress, roughness height, and boundary layer development. The approach can predict net boundary layer flow above a mobile seabed, and can revert to the classical bedload model. Instantaneous and net sediment transport rates are studied using the approach. The instantaneous sediment transport rate in an onshore flow stage can be approximated by a power function of velocity in which the exponent is confirmed to range between 1 and 5 with a decrease in the phase residual. The net sediment transport rate predicted using the approach is validated using a considerable amount of measured data, and compared with existing instantaneous and half-period type models that consider the phase lag or acceleration modification. For the net sediment transport rate in purely acceleration-skewed oscillatory flow, the phase residual is less important than the acceleration-skewed boundary layer difference between onshore and offshore acceleration stages.     

Mode acceleration-based response spectrum approach for nonclassically damped structures

The paper describes the development of a mode accleration-based response spectrum approach for calculating the seismic design response of the nonclassically damped structures. The response is divided into a pseudo-static part and a dynamic part. The pseudo-static part is calculated by a simple static analysis of the structure for the inertial forces, induced by a unit ground acceleration, applied statically. The dynamic part, of course, pends upon the dynamic characteritics of the structure which are defined in terms of the complex-valued modal characteristics. The correlation between the pseudo-static and dynamic components is properly considered. The design ground input in this approach is defined in terms of the relative acceleration and relative velocity response spectra. The proposed approach has the desired attribute of the mode acceleration approach as the response can be accurately calculated even if only a first few modes are used in the analysis. The approach is computationally more efficient than the convenionally used mode displacement approach. The applicability of the approach is verified by numerical simulation results.     

A statistical approach to crowdsourced smartphone-based earthquake early warning systems

The Earthquake Network research project implements a crowdsourced earthquake early warning system based on smartphones. Smartphones, which are made available by the global population, exploit the Internet connection to report a signal to a central server every time a vibration is detected by the on-board accelerometer sensor. This paper introduces a statistical approach for the detection of earthquakes from the data coming from the network of smartphones. The approach allows to handle a dynamic network in which the number of active nodes constantly changes and where nodes are heterogeneous in terms of sensor sensibility and transmission delay. Additionally, the approach allows to keep the probability of false alarm under control. The statistical approach is applied to the data collected by three subnetworks related to the cities of Santiago (Chile), Iquique (Chile) and Kathmandu (Nepal). The detection capabilities of the approach are discussed in terms of earthquake magnitude and detection delay. A simulation study is carried out in order to link the probability of detection and the detection delay to the behaviour of the network under an earthquake event.     

Construction of design hyetographs for locations without observed data

A design hyetograph which represents the time distribution of design rainfall depth corresponding to a duration and a return period is essential in hydrologic design. However, for locations without observed data (ungauged sites), construction of design hyetographs is a difficult task because of the lack of data. Hence, an approach based on self‐organizing map (SOM) is proposed in this paper to construct design hyetographs at ungauged sites. SOM, which is a special kind of artificial neural networks (ANNs), is a powerful technique for extracting and visualizing salient features of data and for solving classification problems. The proposed approach is composed of three steps: classification, assignment and construction. First, the SOM‐based classification is performed to analyse gauged sites' design hyetographs. Second, based on the concept of indicator kriging, a method is developed to assign an ungauged site of interest to a certain cluster. Third, based on the spatial information, the clustering results, and the design hyetographs of gauged sites, the design hyetograph at the site of interest is constructed using the reciprocal‐distance‐squared method. An application is conducted to assess the advantages of the proposed approach over the conventional approaches. Moreover, cross‐validation tests are applied to evaluate the performance of the accuracy and the robustness of the proposed approach. The results confirm the improvement in performance by using the proposed approach instead of conventional approaches. The proposed approach is useful for constructing design hyetographs at ungauged sites. Copyright © 2009 John Wiley & Sons, Ltd.     

An integrated approach for modeling solute transport in streams and canals with applications

A new modeling approach for solute transport in streams and canals was developed to simulate solute dissolution, transport, and decay with continuously migrating sources. The new approach can efficiently handle complicated solute source feeding schemes and initial conditions. Incorporating the finite volume method (FVM) and the ULTIMATE QUICKEST numerical scheme, the new approach is capable of predicting fate and transport of solute that is added to small streams or canals, typically in a continuous fashion. The approach was tested successfully using a hypothetical case, and then applied to an actual field experiment, where linear anionic polyacrylamide (LA-PAM) was applied to an earthen canal. The field experiment was simulated first as a fixed boundary problem using measured concentration data as the boundary condition to test model parameters and sensitivities. The approach was then applied to a moving boundary problem, which included subsequent LA-PAM dissolution, settling to the canal bottom and transport with the flowing canal water. Simulation results showed that the modeling approach developed in this study performed satisfactorily and can be used to simulate a variety of transport problems in streams and canals.     

Assessing uncertainty in refraction seismic traveltime inversion using a global inversion strategy

To analyse and invert refraction seismic travel time data, different approaches and techniques have been proposed. One common approach is to invert first‐break travel times employing local optimization approaches. However, these approaches result in a single velocity model, and it is difficult to assess the quality and to quantify uncertainties and non‐uniqueness of the found solution. To address these problems, we propose an inversion strategy relying on a global optimization approach known as particle swarm optimization. With this approach we generate an ensemble of acceptable velocity models, i.e., models explaining our data equally well. We test and evaluate our approach using synthetic seismic travel times and field data collected across a creeping hillslope in the Austrian Alps. Our synthetic study mimics a layered near‐surface environment, including a sharp velocity increase with depth and complex refractor topography. Analysing the generated ensemble of acceptable solutions using different statistical measures demonstrates that our inversion strategy is able to reconstruct the input velocity model, including reasonable, quantitative estimates of uncertainty. Our field data set is inverted, employing the same strategy, and we further compare our results with the velocity model obtained by a standard local optimization approach and the information from a nearby borehole. This comparison shows that both inversion strategies result in geologically reasonable models (in agreement with the borehole information). However, analysing the model variability of the ensemble generated using our global approach indicates that the result of the local optimization approach is part of this model ensemble. Our results show the benefit of employing a global inversion strategy to generate near‐surface velocity models from refraction seismic data sets, especially in cases where no detailed a priori information regarding subsurface structures and velocity variations is available.     

Convergence of deterministic and stochastic approaches in optimal remediation design of a contaminated aquifer

The comparison between two series of optimal remediation designs using deterministic and stochastic approaches showed a number of converging features. Limited sampling measurements in a supposed contaminated aquifer formed the hydraulic conductivity field and the initial concentration distribution used in the optimization process. The deterministic and stochastic approaches employed a single simulation–optimization method and a multiple realization approach, respectively. For both approaches, the optimization model made use of a genetic algorithm. In the deterministic approach, the total cost, extraction rate, and the number of wells used increase when the design must satisfy the intensified concentration constraint. Growing the stack size in the stochastic approach also brings about same effects. In particular, the change in the selection frequency of the used extraction wells, with increasing stack size, for the stochastic approach can indicate the locations of required additional wells in the deterministic approach due to the intensified constraints. These converging features between the two approaches reveal that a deterministic optimization approach with controlled constraints is achievable enough to design reliable remediation strategies, and the results of a stochastic optimization approach are readily available to real contaminated sites.     

Watershed delineation using hydrographic features and a DEM in plain river network region

Watershed delineation is a required step when conducting any spatially distributed hydrological modelling. Automated approaches are often proposed to delineate a watershed based on a river network extracted from the digital elevation model (DEM) using the deterministic eight‐neighbour (D8) method. However, a realistic river network cannot be derived from conventional DEM processing methods for a large flat area with a complex network of rivers, lakes, reservoirs, and polders, referred to as a plain river network region (PRNR). In this study, a new approach, which uses both hydrographic features and DEM, has been developed to address the problems of watershed delineation in PRNR. It extracts the river nodes and determines the flow directions of the river network based on a vector‐based hydrographic feature data model. The river network, lakes, reservoirs, and polders are then used to modify the flow directions of grid cells determined by D8 approach. The watershed is eventually delineated into four types of catchments including lakes, reservoirs, polders, and overland catchments based on the flow direction matrix and the location of river nodes. Multiple flow directions of grid cells are represented using a multi‐direction encoding method, and multiple outflows of catchments are also reflected in the topology of catchments. The proposed approach is applied to the western Taihu watershed in China. Comparisons between the results obtained from the D8 approach, the ‘stream burning’ approach, and those from the proposed approach clearly demonstrate an improvement of the new approach over the conventional approaches. This approach will benefit the development of distributed hydrological models in PRNR for the consideration of different types and multiple inlets and outlets of catchments. Copyright © 2015 John Wiley & Sons, Ltd.     

A fuzzy approach to reliability based design of storm water drain network

This paper proposes an approach to estimate reliability of a storm water drain (SWD) network in fuzzy framework. It involves: (i) use of proposed fuzzy Monte-Carlo simulation (FMCS) methodology to estimate fuzzy reliability of conduits in the network, (ii) construction of a reliability block diagram (RBD) for the network (system) using suggested guidelines, and (iii) use of the RBD and reliability estimates of the conduits in the network to compute system reliability based on a proposed procedure. In addition, a system reliability based methodology is proposed for design/retrofitting of SWD network by optimization of its conduit dimensions. Conventionally used reliability analysis approaches assume that the cumulative distribution function (CDF) of performance function (marginal safety) of conduits follows Gaussian distribution, which cannot be ensured in the real world scenario. The proposed approach alleviates the need for making such assumptions and can account for linguistic ambiguity in variables defining the performance function. Effectiveness of the proposed approach is demonstrated on a hypothetical SWD network and a real network in Bangalore, India. Comparison of the results obtained from the proposed approach with those from conventional Monte-Carlo simulation (MCS) reliability assessment approach indicated that the estimate of system reliability and conduit reliability are higher with FMCS approach. Consequently, conduit dimensions required to attain required system (network) reliability could be expected to be lower when FMCS approach is used for designing or retrofitting a system.     

An improved neural network approach to the determination of aquifer parameters

In this paper, an artificial neural network (ANN) approach to the determination of aquifer parameters is developed. The approach is based on the combination of an ANN and the Theis solution. The proposed ANN approach has advantages over the existing ANN approach. It avoids inappropriate setting of a trained range. It also determines the aquifer parameters more accurately and needs less required training time. Testing the existing and the proposed ANN approaches by 1000 sets of synthetic data also demonstrates these advantages. As to the comparison between the proposed ANN approach and the type-curve graphical method, an application to actual time-drawdown data shows that the proposed ANN approach determines the aquifer parameters more precisely. The proposed ANN approach is recommended as an alternative to the type-curve graphical method and the existing ANN approach.