Application of wavelet‐based multi‐model Kalman filters to real‐time flood forecasting

This paper presents the application of a multimodel method using a wavelet‐based Kalman filter (WKF) bank to simultaneously estimate decomposed state variables and unknown parameters for real‐time flood forecasting. Applying the Haar wavelet transform alters the state vector and input vector of the state space. In this way, an overall detail plus approximation describes each new state vector and input vector, which allows the WKF to simultaneously estimate and decompose state variables. The wavelet‐based multimodel Kalman filter (WMKF) is a multimodel Kalman filter (MKF), in which the Kalman filter has been substituted for a WKF. The WMKF then obtains M estimated state vectors. Next, the M state‐estimates, each of which is weighted by its possibility that is also determined on‐line, are combined to form an optimal estimate. Validations conducted for the Wu‐Tu watershed, a small watershed in Taiwan, have demonstrated that the method is effective because of the decomposition of wavelet transform, the adaptation of the time‐varying Kalman filter and the characteristics of the multimodel method. Validation results also reveal that the resulting method enhances the accuracy of the runoff prediction of the rainfall–runoff process in the Wu‐Tu watershed. Copyright © 2004 John Wiley & Sons, Ltd.     

Modelling the hydrologic effects of dynamic land‐use change using a distributed hydrologic model and a spatial land‐use allocation model

This study develops a novel approach for modelling and examining the impacts of time–space land‐use changes on hydrological components. The approach uses an empirical land‐use change allocation model (CLUE‐s) and a distributed hydrological model (DHSVM) to examine various land‐use change scenarios in the Wu‐Tu watershed in northern Taiwan. The study also uses a generalized likelihood uncertainty estimation approach to quantify the parameter uncertainty of the distributed hydrological model. The results indicate that various land‐use policies—such as no change, dynamic change and simultaneous change—have different levels of impact on simulating the spatial distributions of hydrological components in the watershed study. Peak flow rates under simultaneous and dynamic land‐use changes are 5·71% and 2·77%, respectively, greater than the rate under the no land‐use change scenario. Using dynamic land‐use changes to assess the effect of land‐use changes on hydrological components is more practical and feasible than using simultaneous land‐use change and no land‐use change scenarios. Furthermore, land‐use change is a spatial dynamic process that can lead to significant changes in the distributions of ground water and soil moisture. The spatial distributions of land‐use changes influence hydrological processes, such as the ground water level of whole areas, particularly in the downstream watershed. Copyright © 2010 John Wiley & Sons, Ltd.     

Two‐dimensional continuous simulation of spatiotemporally varied hydrological processes using the time‐area method

Distributed, continuous hydrologic models promote better understanding of hydrology and enable integrated hydrologic analyses by providing a more detailed picture of water transport processes across the varying landscape. However, such models are not widely used in routine modelling practices, due in part to the extensive data input requirements, computational demands, and complexity of routing algorithms. We developed a two‐dimensional continuous hydrologic model, HYSTAR, using a time‐area method within a grid‐based spatial data model with the goal of providing an alternative way to simulate spatiotemporally varied watershed‐scale hydrologic processes. The model calculates the direct runoff hydrograph by coupling a time‐area routing scheme with a dynamic rainfall excess sub‐model implemented here using a modified curve number method with an hourly time step, explicitly considering downstream ‘reinfiltration’ of routed surface runoff. Soil moisture content is determined at each time interval based on a water balance equation, and overland and channel runoff is routed on time‐area maps, representing spatial variation in hydraulic characteristics for each time interval in a storm event. Simulating runoff hydrographs does not depend on unit hydrograph theory or on solution of the Saint Venant equation, yet retains the simplicity of a unit hydrograph approach and the capability of explicitly simulating two‐dimensional flow routing. The model provided acceptable performance in predicting daily and monthly runoff for a 6‐year period for a watershed in Virginia (USA) using readily available geographic information about the watershed landscape. Spatial and temporal variability in simulated effective runoff depth and time area maps dynamically show the areas of the watershed contributing to the direct runoff hydrograph at the outlet over time, consistent with the variable source area overland flow generation mechanism. The model offers a way to simulate watershed processes and runoff hydrographs using the time‐area method, providing a simple, efficient, and sound framework that explicitly represents mechanisms of spatially and temporally varied hydrologic processes. Copyright © 2015 John Wiley & Sons, Ltd.     

Performance of a conceptual and physically based model in simulating the response of a semi‐urbanized watershed in San Antonio,Texas

The need for accurate hydrologic analysis and rainfall–runoff modelling tools has been rapidly increasing because of the growing complexity of operational hydrologic and hydraulic problems associated with population growth, rapid urbanization and expansion of agricultural activities. Given the recent advances in remote sensing of physiographic features and the availability of near real‐time precipitation products, rainfall–runoff models are expected to predict runoff more accurately. In this study, we compare the performance and implementation requirements of two rainfall–runoff models for a semi‐urbanized watershed. One is a semi‐distributed conceptual model, the Hydrologic Engineering Center‐Hydrologic Modelling System (HEC‐HMS). The other is a physically based, distributed‐parameter hydrologic model, the Gridded Surface Subsurface Hydrologic Analysis (GSSHA). Four flood events that took place on the Leon Creek watershed, a sub‐watershed of the San Antonio River basin in Texas, were used in this study. The two models were driven by the Multisensor Precipitation Estimator radar products. One event (in 2007) was used for HEC‐HMS and GSSHA calibrations. Two events (in 2004 and 2007) were used for further calibration of HEC‐HMS. Three events (in 2002, 2004 and 2010) were used for model validation. In general, the physically based, distributed‐parameter model performed better than the conceptual model and required less calibration. The two models were prepared with the same minimum required input data, and the effort required to build the two models did not differ substantially. Copyright © 2012 John Wiley & Sons, Ltd.     

A comparison of snowmelt‐derived streamflow from temperature‐index and modified‐temperature‐index snow models

Reliable estimation of the volume and timing of snowmelt runoff is vital for water supply and flood forecasting in snow‐dominated regions. Snowmelt is often simulated using temperature‐index (TI) models due to their applicability in data‐sparse environments. Previous research has shown that a modified‐TI model, which uses a radiation‐derived proxy temperature instead of air temperature as its surrogate for available energy, can produce more accurate snow‐covered area (SCA) maps than a traditional TI model. However, it is unclear whether the improved SCA maps are associated with improved snow water equivalent (SWE) estimation across the watershed or improved snowmelt‐derived streamflow simulation. This paper evaluates whether a modified‐TI model produces better streamflow estimates than a TI model when they are used within a fully distributed hydrologic model. It further evaluates the performance of the two models when they are calibrated using either point SWE measurements or SCA maps. The Senator Beck Basin in Colorado is used as the study site because its surface is largely bedrock, which reduces the role of infiltration and emphasizes the role of the SWE pattern on streamflow generation. Streamflow is simulated using both models for 6 years. The modified‐TI model produces more accurate streamflow estimates (including flow volume and peak flow rate) than the TI model, likely because the modified‐TI model better reproduces the SWE pattern across the watershed. Both models also produce better performance when calibrated with SCA maps instead of point SWE data, likely because the SCA maps better constrain the space‐time pattern of SWE.     

On the use of multi‐algorithm,genetically adaptive multi‐objective method for multi‐site calibration of the SWAT model

With the availability of spatially distributed data, distributed hydrologic models are increasingly used for simulation of spatially varied hydrologic processes to understand and manage natural and human activities that affect watershed systems. Multi‐objective optimization methods have been applied to calibrate distributed hydrologic models using observed data from multiple sites. As the time consumed by running these complex models is increasing substantially, selecting efficient and effective multi‐objective optimization algorithms is becoming a nontrivial issue. In this study, we evaluated a multi‐algorithm, genetically adaptive multi‐objective method (AMALGAM) for multi‐site calibration of a distributed hydrologic model—Soil and Water Assessment Tool (SWAT), and compared its performance with two widely used evolutionary multi‐objective optimization (EMO) algorithms (i.e. Strength Pareto Evolutionary Algorithm 2 (SPEA2) and Non‐dominated Sorted Genetic Algorithm II (NSGA‐II)). In order to provide insights into each method's overall performance, these three methods were tested in four watersheds with various characteristics. The test results indicate that the AMALGAM can consistently provide competitive or superior results compared with the other two methods. The multi‐method search framework of AMALGAM, which can flexibly and adaptively utilize multiple optimization algorithms, makes it a promising tool for multi‐site calibration of the distributed SWAT. For practical use of AMALGAM, it is suggested to implement this method in multiple trials with relatively small number of model runs rather than run it once with long iterations. In addition, incorporating different multi‐objective optimization algorithms and multi‐mode search operators into AMALGAM deserves further research. Copyright © 2009 John Wiley & Sons, Ltd.     

Local‐scale and watershed‐scale determinants of summertime urban stream temperatures

The influence of urbanization on the temperature of small streams is widely recognized, but these effects are confounded by the great natural variety of their contributing watersheds. To evaluate the relative importance of local‐scale and watershed‐scale factors on summer temperatures in urban streams, hundreds of near‐instantaneous temperature measurements throughout the central Puget Lowland, western Washington State, were collected during a single 2‐h period in August in each of the years 1998–2001. Stream temperatures ranged from 8.9 to 27.5 °C, averaging 15.4 °C. Pairwise correlation coefficients between stream temperature and four watershed variables (total watershed area and the watershed percentages of urban development, upstream lakes, and permeable glacial outwash soils as an indicator of groundwater exchange) were uniformly very low. Akaike's information criterion was applied to determine the best‐supported sets of watershed‐scale predictor variables for explaining the variability of stream temperatures. For the full four‐year dataset, the only well‐supported model was the global model (using all watershed variables); for the most voluminous single‐year (1999) data, Akaike's information criterion showed greatest support for per cent outwash (Akaike weight of 0.44), followed closely by per cent urban development + per cent outwash, per cent lake area only, and the global model. Upstream lakes resulted in downstream warming of up to 3 °C; variability in riparian shading imposed a similar temperature range. Watershed urbanization itself is not the most important determining factor for summer temperatures in this region; even the long‐recognized effects of riparian shading can be no more influential than those imposed by other local‐scale and watershed‐scale factors. Copyright © 2013 John Wiley & Sons, Ltd.     

One‐ and two‐dimensional modelling of overland flow in semiarid shrubland,Jornada basin,New Mexico

Two distributed parameter models, a one‐dimensional (1D) model and a two‐dimensional (2D) model, are developed to simulate overland flow in two small semiarid shrubland watersheds in the Jornada basin, southern New Mexico. The models are event‐based and represent each watershed by an array of 1‐m² cells, in which the cell size is approximately equal to the average area of the shrubs. Each model uses only six parameters, for which values are obtained from field surveys and rainfall simulation experiments. In the 1D model, flow volumes through a fixed network are computed by a simple finite‐difference solution to the 1D kinematic wave equation. In the 2D model, flow directions and volumes are computed by a second‐order predictor–corrector finite‐difference solution to the 2D kinematic wave equation, in which flow routing is implicit and may vary in response to flow conditions. The models are compared in terms of the runoff hydrograph and the spatial distribution of runoff. The simulation results suggest that both the 1D and the 2D models have much to offer as tools for the large‐scale study of overland flow. Because it is based on a fixed flow network, the 1D model is better suited to the study of runoff due to individual rainfall events, whereas the 2D model may, with further development, be used to study both runoff and erosion during multiple rainfall events in which the dynamic nature of the terrain becomes an important consideration. Copyright © 2006 John Wiley & Sons, Ltd.     

Using a topographic index to distribute variable source area runoff predicted with the SCS curve‐number equation

Because the traditional Soil Conservation Service curve‐number (SCS‐CN) approach continues to be used ubiquitously in water quality models, new application methods are needed that are consistent with variable source area (VSA) hydrological processes in the landscape. We developed and tested a distributed approach for applying the traditional SCS‐CN equation to watersheds where VSA hydrology is a dominant process. Predicting the location of source areas is important for watershed planning because restricting potentially polluting activities from runoff source areas is fundamental to controlling non‐point‐source pollution. The method presented here used the traditional SCS‐CN approach to predict runoff volume and spatial extent of saturated areas and a topographic index, like that used in TOPMODEL, to distribute runoff source areas through watersheds. The resulting distributed CN–VSA method was applied to two subwatersheds of the Delaware basin in the Catskill Mountains region of New York State and one watershed in south‐eastern Australia to produce runoff‐probability maps. Observed saturated area locations in the watersheds agreed with the distributed CN–VSA method. Results showed good agreement with those obtained from the previously validated soil moisture routing (SMR) model. When compared with the traditional SCS‐CN method, the distributed CN–VSA method predicted a similar total volume of runoff, but vastly different locations of runoff generation. Thus, the distributed CN–VSA approach provides a physically based method that is simple enough to be incorporated into water quality models, and other tools that currently use the traditional SCS–CN method, while still adhering to the principles of VSA hydrology. Copyright © 2004 John Wiley & Sons, Ltd.     

Comparison of AnnAGNPS and SWAT model simulation results in USDA‐CEAP agricultural watersheds in south‐central Kansas

This study was conducted under the USDA‐Conservation Effects Assessment Project (CEAP) in the Cheney Lake watershed in south‐central Kansas. The Cheney Lake watershed has been identified as ‘impaired waters’ under Section 303(d) of the Federal Clean Water Act for sediments and total phosphorus. The USDA‐CEAP seeks to quantify environmental benefits of conservation programmes on water quality by monitoring and modelling. Two of the most widely used USDA watershed‐scale models are Annualized AGricultural Non‐Point Source (AnnAGNPS) and Soil and Water Assessment Tool (SWAT). The objectives of this study were to compare hydrology, sediment, and total phosphorus simulation results from AnnAGNPS and SWAT in separate calibration and validation watersheds. Models were calibrated in Red Rock Creek watershed and validated in Goose Creek watershed, both sub‐watersheds of the Cheney Lake watershed. Forty‐five months (January 1997 to September 2000) of monthly measured flow and water quality data were used to evaluate the two models. Both models generally provided from fair to very good correlation and model efficiency for simulating surface runoff and sediment yield during calibration and validation (correlation coefficient; R², from 0·50 to 0·89, Nash Sutcliffe efficiency index, E, from 0·47 to 0·73, root mean square error, RMSE, from 0·25 to 0·45 m³ s^?1 for flow, from 158 to 312 Mg for sediment yield). Total phosphorus predictions from calibration and validation of SWAT indicated good correlation and model efficiency (R² from 0·60 to 0·70, E from 0·63 to 0·68) while total phosphorus predictions from validation of AnnAGNPS were from unsatisfactory to very good (R² from 0·60 to 0·77, E from ? 2·38 to 0·32). The root mean square error–observations standard deviation ratio (RSR) was estimated as excellent (from 0·08 to 0·25) for the all model simulated parameters during the calibration and validation study. The percentage bias (PBIAS) of the model simulated parameters varied from unsatisfactory to excellent (from 128 to 3). This study determined SWAT to be the most appropriate model for this watershed based on calibration and validation results. Copyright © 2008 John Wiley & Sons, Ltd.     

Including spatial distribution in a data‐driven rainfall‐runoff model to improve reservoir inflow forecasting in Taiwan

Multi‐step ahead inflow forecasting has a critical role to play in reservoir operation and management in Taiwan during typhoons as statutory legislation requires a minimum of 3‐h warning to be issued before any reservoir releases are made. However, the complex spatial and temporal heterogeneity of typhoon rainfall, coupled with a remote and mountainous physiographic context, makes the development of real‐time rainfall‐runoff models that can accurately predict reservoir inflow several hours ahead of time challenging. Consequently, there is an urgent, operational requirement for models that can enhance reservoir inflow prediction at forecast horizons of more than 3 h. In this paper, we develop a novel semi‐distributed, data‐driven, rainfall‐runoff model for the Shihmen catchment, north Taiwan. A suite of Adaptive Network‐based Fuzzy Inference System solutions is created using various combinations of autoregressive, spatially lumped radar and point‐based rain gauge predictors. Different levels of spatially aggregated radar‐derived rainfall data are used to generate 4, 8 and 12 sub‐catchment input drivers. In general, the semi‐distributed radar rainfall models outperform their less complex counterparts in predictions of reservoir inflow at lead times greater than 3 h. Performance is found to be optimal when spatial aggregation is restricted to four sub‐catchments, with up to 30% improvements in the performance over lumped and point‐based models being evident at 5‐h lead times. The potential benefits of applying semi‐distributed, data‐driven models in reservoir inflow modelling specifically, and hydrological modelling more generally, are thus demonstrated. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluation of evapotranspiration models over semi‐arid and semi‐humid areas of China

Evapotranspiration (ET) is a critical component in the hydrological cycle. However, its actual values appear to be difficult to obtain, especially in areas in which precipitation has high inter‐annual variability. Here, we evaluated eight commonly used ET models in semi‐arid and semi‐humid areas of China. The order of overall performance from best to worst is as follows: the revised Priestley–Taylor model (PT‐JPL, 0.71, 1.65 [18.37%], 4.72 [49.19%]) a a Statistics (model abbreviation, coefficient of determination, bias [relative value], standard deviation [relative value]).
, the modified PT‐JPL model (M1‐PT‐JPL, 0.67, ?0.68 [7.56%], 3.87 [40.31%]), the Community Land Model (CLM, 0.68, ?2.52 [28.01%], 5.10 [53.17%]), the modified PT‐JPL model (M2‐PT‐JPL, 0.63, 0.57 [6.27%], 5.04 [52.52%]), the revised Penman–Monteith model (RS‐PM, 0.62, 3.56 [37.40%], 6.11 [63.68%]), an empirical model (Wang, 0.59, ?1.04 [11.57%], 5.61 [58.43%]), the advection‐aridity model (AA, 0.55, 5.56 [61.78%], 7.45 [77.60%]), and the energy balance model (SEBS, 0.35, 5.11 [56.72%], 9.43 [98.18%]). The performance of all of the models is comparably poor in winter and summer, except for the PT‐JPL model, and relatively good in spring and autumn. Because of the vegetation control on ET, the Wang, RS‐PM, PT‐JPL, M1‐PT‐JPL, and M2‐PT‐JPL models perform better for cropland, whereas the AA model, SEBS model and CLM perform better for grassland. The CLM, PT‐JPL, and Wang models perform better in semi‐arid region than in semi‐humid region, whereas the opposite is true for SEBS and RS‐PM. The AA, M1‐PT‐JPL, and M2‐PT‐JPL models perform similarly in semi‐arid and semi‐humid regions. When considering the inter‐annual variability in precipitation, the Wang model has relatively good performance under only some annual precipitation conditions; the performance of the PT‐JPL and AA models is reduced under conditions of high precipitation; the two modified PT‐JPL models inherited the steady performance of the PT‐JPL model and improved the performance under conditions of high annual precipitation by the modification of the soil moisture constraint. RS‐PM is more appropriate for humid conditions. CLM and PT‐JPL models could be effectively applied to all precipitation conditions because of their good performance across a wide annual precipitation range. Copyright © 2016 John Wiley & Sons, Ltd.     

Geospatially based distributed rainfall‐runoff modelling for simulation of internal and outlet responses in a semi‐forested lower Himalayan watershed

This study presents a Geographic Information System (GIS)‐based distributed rainfall‐runoff model for simulating surface flows in small to large watersheds during isolated storm events. The model takes into account the amount of interception storage to be filled using a modified Merriam ( 1960 ) approach before estimating infiltration by the Smith and Parlange ( 1978 ) method. The mechanics of overland and channel flow are modelled by the kinematic wave approximation of the Saint Venant equations which are then numerically solved by the weighted four‐point implicit finite difference method. In this modelling the watershed was discretized into overland planes and channels using the algorithms proposed by Garbrecht and Martz ( 1999 ). The model code was first validated by comparing the model output with an analytical solution for a hypothetical plane. Then the model was tested in a medium‐sized semi‐forested watershed of Pathri Rao located in the Shivalik ranges of the Garhwal Himalayas, India. Initially, a local sensitivity analysis was performed to identify the parameters to which the model outputs like runoff volume, peak flow and time to peak flow are sensitive. Before going for model validation, calibration was performed using the Ordered‐Physics‐based Parameter Adjustment (OPPA) method. The proposed Physically Based Distributed (PBD) model was then evaluated both at the watershed outlet as well as at the internal gauging station, making this study a first of its kind in Indian watersheds. The results of performance evaluation indicate that the model has simulated the runoff hydrographs reasonably well within the watershed as well as at the watershed outlet with the same set of calibrated parameters. The model also simulates, realistically, the temporal variation of the spatial distribution of runoff over the watershed and the same has been illustrated graphically. Copyright © 2011 John Wiley & Sons, Ltd.     

A kinematic‐wave‐based distributed watershed model using FEM,GIS and remotely sensed data

For the appropriate management of water resources in a watershed, it is essential to calculate the time distribution of runoff for the given rainfall event. In this paper, a kinematic‐wave‐based distributed watershed model using finite element method (FEM), geographical information systems (GIS) and remote‐sensing‐based approach is presented for the runoff simulation of small watersheds. The kinematic wave equations are solved using FEM for overland and channel flow to generate runoff at the outlet of the watershed concerned. The interception loss is calculated by an empirical model based on leaf area index (LAI). The Green‐Ampt Mein Larson (GAML) model is used for the estimation of infiltration. Remotely sensed data has been used to extract land use (LU)/land cover (LC). GIS have been used to prepare finite element grid and input files such as Manning's roughness and slope. The developed overland flow model has been checked with an analytical solution for a hypothetical watershed. The model has been applied to a gauged watershed and an ungauged watershed. From the results, it is seen that the model is able to simulate the hydrographs reasonably well. A sensitivity analysis of the model is carried out with the calibrated infiltration parameters, overland flow Manning's roughness, channel flow Manning's roughness, time step and grid size. The present model is useful in predicting the hydrograph in small, ungauged watersheds. Copyright © 2007 John Wiley & Sons, Ltd.     

Gabor‐frame‐based Gaussian packet migration

We present a Gaussian packet migration method based on Gabor frame decomposition and asymptotic propagation of Gaussian packets. A Gaussian packet has both Gaussian‐shaped time–frequency localization and space–direction localization. Its evolution can be obtained by ray tracing and dynamic ray tracing. In this paper, we first briefly review the concept of Gaussian packets. After discussing how initial parameters affect the shape of a Gaussian packet, we then propose two Gabor‐frame‐based Gaussian packet decomposition methods that can sparsely and accurately represent seismic data. One method is the dreamlet–Gaussian packet method. Dreamlets are physical wavelets defined on an observation plane and can represent seismic data efficiently in the local time–frequency space–wavenumber domain. After decomposition, dreamlet coefficients can be easily converted to the corresponding Gaussian packet coefficients. The other method is the Gabor‐frame Gaussian beam method. In this method, a local slant stack, which is widely used in Gaussian beam migration, is combined with the Gabor frame decomposition to obtain uniform sampled horizontal slowness for each local frequency. Based on these decomposition methods, we derive a poststack depth migration method through the summation of the backpropagated Gaussian packets and the application of the imaging condition. To demonstrate the Gaussian packet evolution and migration/imaging in complex models, we show several numerical examples. We first use the evolution of a single Gaussian packet in media with different complexities to show the accuracy of Gaussian packet propagation. Then we test the point source responses in smoothed varying velocity models to show the accuracy of Gaussian packet summation. Finally, using poststack synthetic data sets of a four‐layer model and the two‐dimensional SEG/EAGE model, we demonstrate the validity and accuracy of the migration method. Compared with the more accurate but more time‐consuming one‐way wave‐equation‐based migration, such as beamlet migration, the Gaussian packet method proposed in this paper can correctly image the major structures of the complex model, especially in subsalt areas, with much higher efficiency. This shows the application potential of Gaussian packet migration in complicated areas.     

A simple concept for calibrating runoff thresholds in quasi‐distributed variable source area watershed models

Most semi‐distributed watershed water quality models divide the watershed into hydrologic response units (HRU) with no flow among them. This is problematic when watersheds are delineated to include variable source areas (VSAs) because it is the lateral flows from upslope areas to downslope areas that generate VSAs. Although hydrologic modellers have often successfully calibrated these types of models, there can still be considerable uncertainty in model results. In this paper, a topographic‐index‐based method is described and tested to distribute effective soil water holding capacity among HRUs, which can be subsequently adjusted using the watershed baseflow coefficient. The method is tested using a version of the Soil and Water Assessment Tool (SWAT) model that simulates VSA runoff and is applied to two watersheds: a New York State (NYS) watershed, and one in the head waters of the Blue Nile Basin (BNB) in Ethiopia. Daily streamflow predicted using effective soil water storage capacities based only on the topographic index were reassuringly accurate in both the NYS watershed (daily Nash Sutcliffe (E) = 0·73) and in the BNB (E = 0·70). Using the baseflow coefficient to adjust the effective soil water storage capacity only slightly improved streamflow predictions in NYS (E = 0·75) but substantially improved the BNB predictions (E = 0·80). By comparison, the standard SWAT model, which uses the traditional look‐up tables to determine a runoff curve number, performed considerably less accurately in un‐calibrated form (E = 0·51 for NYS and E = 0·45 for BNB), but improved substantially when explicitly calibrated to streamflow measurements (E = 0·76 for NYS and E = 0·67 for the BNB). The calibration method presented here provides a parsimonious, systematic approach to using established models in VSA watersheds that reduces the ambiguity inherent in model calibration. Copyright © 2011 John Wiley & Sons, Ltd.     

Performance evaluation of three DEM‐based fluvial terrace mapping methods

The availability of high‐resolution digital elevation models (DEMs) derived from airborne light detection and ranging (LiDAR) surveys has spurred the development of several methods to identify and map fluvial terraces. The post‐glacial landscape of the Sheepscot River watershed, Maine, where land‐use change has produced fill terraces upstream of historic dam sites, was selected to implement a comparison between terrace mapping methodologies. At four study sites within the watershed, terraces were manually mapped on LiDAR‐DEM‐derived hillshade images to facilitate the comparison among fully and semi‐automated DEM‐based procedures, including: (1) spatial relationships between interpreted terraces and surrounding natural topography, (2) feature classification algorithms, and (3) the TerEx terrace mapping toolbox. Each method was evaluated based on its accuracy and ease of implementation. The four study sites have varying longitudinal slope (0.0008–0.006 m/m), channel width (< 5–30 m), surrounding landscape relief (20–80 m), type and density of surrounding land use, and mapped surficial geologic units. All methods generally overestimate terrace areas (average predicted area 210% of manually defined area) with the most accurate results achieved within confined river valleys surrounded by the steep hillslopes. Accuracy generally decreases for study sites surrounded by low‐relief landscapes (predicted areas ranged 4–953% of manual delineations). We conclude with the advantages and drawbacks of each method tested and make recommendations for the scenarios where the use of each method is most appropriate. Copyright © 2016 John Wiley & Sons, Ltd.     

Investigating the impact of the Chi‐Chi earthquake on the occurrence of debris flows using artificial neural networks

Debris flows have caused enormous losses of property and human life in Taiwan during the last two decades. An efficient and reliable method for predicting the occurrence of debris flows is required. The major goal of this study is to explore the impact of the Chi‐Chi earthquake on the occurrence of debris flows by applying the artificial neural network (ANN) that takes both hydrological and geomorphologic influences into account. The Chen‐Yu‐Lan River watershed, which is located in central Taiwan, is chosen for evaluating the critical rainfall triggering debris flows. A total of 1151 data sets were collected for calibrating model parameters with two training strategies. Significant differences before and after the earthquake have been found: (1) The size of landslide area is proportioned to the occurrence of debris flows; (2) the amount of critical rainfall required for triggering debris flows has reduced significantly, about half of the original critical rainfall in the study case; and (3) the frequency of the occurrence of debris flows is largely increased. The overall accuracy of model prediction in testing phase has reached 96·5%; moreover, the accuracy of occurrence prediction is largely increased from 24 to 80% as the network trained with data from before the Chi‐Chi earthquake sets and with data from the lumped before and after the earthquake sets. The results demonstrated that the ANN is capable of learning the complex mechanism of debris flows and producing satisfactory predictions. Copyright © 2009 John Wiley & Sons, Ltd.     

Comparative analysis of a geomorphology‐based instantaneous unit hydrograph in small mountainous watersheds

A conceptual insytnataneous unit hydrograph (IUH) based on geomorphologival association of linear reservoirs (GR) previously developed by the authors has been compared with other IUH models: a distributed GR variation (GR(v)), the Nash IUH, the Chutha and Dooge IUH, and the Troutman and Karlinger IUH for the analysis of direct runoff hydrographs recorded in three experimental watershed of the north of Spain. The comparison was made through a calibration‐validation process in which a leave‐one‐out cross‐validation method was applied. The results indicate the satisfactory performance of all the models, with the advantage for the GR model of the dependence on only one parameter, which can be identified from the watershed and event characteristics. This property makes its use easier than that of other models. Copyright © 2011 John Wiley & Sons, Ltd.     

Quantifying rainfall controls on catchment‐scale landslide erosion in Taiwan

Landslide erosion is a dominant hillslope process and the main source of stream sediment in tropical, tectonically active mountain belts. In this study, we quantified landslide erosion triggered by 24 rainfall events from 2001 to 2009 in three mountainous watersheds in Taiwan and investigated relationships between landslide erosion and rainfall variables. The results show positive power‐law relations between landslide erosion and rainfall intensity and cumulative rainfall, with scaling exponents ranging from 2·94 to 5·03. Additionally, landslide erosion caused by Typhoon Morakot is of comparable magnitude to landslide erosion caused by the Chi‐Chi Earthquake (M_W = 7·6) or 22–24 years of basin‐averaged erosion. Comparison of the three watersheds indicates that deeper landslides that mobilize soil and bedrock are triggered by long‐duration rainfall, whereas shallow landslides are triggered by short‐duration rainfall. These results suggest that rainfall intensity and watershed characteristics are important controls on rainfall‐triggered landslide erosion and that severe typhoons, like high‐magnitude earthquakes, can generate high rates of landslide erosion in Taiwan. Copyright © 2012 John Wiley & Sons, Ltd.