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This paper presents the effect of spatially-distributed rainfall on both rainfall-sediment-runoff and erosion or deposition in the experimental Cheoncheon catchment: upstream of Yongdam dam basin. The rainfall fields were generated by three rainfall interpolation techniques (Thiessen polygon: TP, Inverse Distance Weighting: IDW, Kriging) based only on ground gauges and two radar rainfall synthetic techniques (Gauge-Radar ratio: GR, Conditional Merging: CM). Each rainfall field was then assessed in terms of spatial feature and quantity and also used for rainfall-sediment-runoff and erosion-deposition simulation due to the spatial difference of rainfall fields. The results showed that all the interpolation methods based on ground gauges provided very similar hydrologic responses in spite of different spatial pattern of erosion and deposition while raw radar and GR rainfall fields led to underestimated and overestimated simulation results, respectively. The CM technique was acceptable to improve the accuracy of raw radar rainfall for hydrologic simulation even though it is more time consuming to generate spatially-distributed rainfall.

This study aims to simulate a flood inundation propagation due to Janghyeon and Dongmak dam breaches by the typhoon `Rusa`, 2002 in the Kangwon-do using the 2-D flood inundation model and also estimate flood damages of the study site using the MD-FDA method. Flood inundated areas increased gradually from simulation time of 0.5 h to 9 h since the reservoir water surface elevation exceeded the design flood elevation. The maximum inundation depths of downstream area were simulated at 4.73 m of the Janghyen and 4.3 m of Dongmak, respectively. The simulated inundated area showed a very good agreement with the field-surveyed inundated area. The estimated results using the MD-FDA with spatially-distributed inundation depth information showed that the damages of the MD-FDA were overestimated at 7.3 billion won than the reported damages of 45 billion won. However, the flood damage estimation result using the MD-FDA was recalculated at 46.4 billion won under no considerations to the dead and wounded because of early evacuation and it was then acceptable.

This study presents a new method to estimate the Nash model parameters on the basis of the concept of geomorphologic dispersion stemming from spatial heterogeneity of flow paths within a catchment. The proposed method is formulated by including physically meaningful characteristic velocities for channel and hillslope and also takes account of the effect of complex interactions between channel and hillslope hydrological behaviors on catchment responses. We applied the proposed formulas to the Bocheong watershed, an experimental area established under the International Hydrological Programme (IHP) in Korea, with several storm events to assess the individual effect of channel and hillslope on hydrological responses in the study site. The characteristic velocities were estimated by topographic data based on a 20×20 m digital elevation model (DEM) from a 1∶25000-scaled topographic map and statistical features of the historical events. We then calculated the Nash model parameters by substituting the estimated ...

This study aims to demonstrate the relationship between various factors and soil erosion or deposition, simulated from distributed rainfall-sediment-runoff model applications. We selected area, overland flow length, local slope as catchment representative characteristics among many important geographic factors and also used the grid-based accumulated rainfall as a representative hydro-climatic factor to assess the effect of these two different types of factors on erosion and deposition. The study catchment was divided based on the Strahler`s stream order method for analysis of the relationship between area and erosion or deposition. Both erosion and deposition increased linearly as the catchment area became larger. Erosion occurred widely throughout the catchment, whereas deposition was observed at the grid-cells near the channel network with short overland flow lengths and mild slopes. In addition, the relationship results between grid-based accumulated rainfall and soil erosion or deposition showed that erosion increased gradually as rainfall amount increased, whereas deposition responded irregularly to variations in rainfall. Within the context of these results, it can be concluded that deposition is closely related with the geographic factors used in this study while erosion is significantly affected by rainfall.

Development of basin-scale rainfall-runoff modeling systems is essential for integrated water resources management in terms of both assessing management alternatives and real-time resource management. This study developed a distributed rainfall-runoff modeling system based on the Object-oriented Hydrologic Modeling System (OHyMoS) for a large river basin (the Daechung Dam basin, South Korea; 3,994 km2) that is highly regulated by multipurpose dams. We applied three hydrologic element modules to simulate hillslope runoff, channel runoff, and dam reservoir outflow and then linked these modules together under OHyMoS to simultaneously predict discharges at eight specific outlets. This newly developed rainfall-runoff modeling system generally provided acceptable hydrographs during the typical Korean rainy period from 1 June to 30 September, although the simulated hydrographs for extreme flood events during typhoons and local heavy rainfall were underestimated compared to measured hydrographs. The developed modeling system can be used for water resources planning and management in the Daechung Dam basin and also readily extended to other large basins, such as the whole Geum River basin (9,835 km2) that includes the Daechung Dam basin, by incorporating sub-basin models into the system.

This study aims to propose a method for effectively recognising and evaluating model structural uncertainty. It began with a comparative assessment of various model structures that have differing features regarding the rainfall-runoff mechanism and DEM spatial resolution. The assessment applied a multi-objective optimisation method (MOSCEM-UA) with two objective functions (simple least-squares and the heteroscedastic maximum likelihood estimator), and focused on five historical flood events. The study was based on the assumptions that a structurally sound model assures improved prediction results (either minimized or maximized model performance measure), allows constant model performance with regard to objective functions (a small Pareto solution set), and yields good applicability of a calibrated parameter set to various events (good parameter stability). The results indicated that KWMSS, a distributed model, was superior to SFM, a simple lumped model, when estimating a Pareto solution set and assessing parameter stability for the applied events. In addition, three different spatial resolutions (250 m, 500 m, and 1 km) were compared to assess the structural uncertainty due to changes in the topographical representation in distributed rainfall-runoff modelling. The results indicated that the 250 and 500 m models were Pareto-equivalent, containing similar Pareto fronts, and both produced Pareto results superior to the 1 km model. Both models also yielded parameter stability values that were much more superior to the model based on a 1 km DEM. As the topographic representation became more detailed, the model showed a tendency to have less structural uncertainty in terms of guarantying better performance, better parameter stability, and a smaller Pareto solution set. On the other hand, the output of a spatially detailed model was likely to be insensitive to the variation of model parameters (i.e. equifinality). Copyright © 2011 John Wiley & Sons, Ltd.

Identifying the optimal drainage network based on digital elevation models (DEMs) is a fundamental task in rainfall-runoff modeling. Rapidly improving geographic information system technology enables hydrologists to use a variety of DEM-based hydrologic models that yield spatially concrete outputs. However, reliable drainage networks are still difficult to represent due to insufficient information about the dynamic behavior of water movement on catchment hillslopes. This study proposes an efficient method for drainage network identification through a comparative analysis of geomorphologic characteristics, such as drainage density, length of hillslope flow path, source area, etc., using area threshold and slope-area threshold criteria that incorporate scaling properties between the local slope and the contributing area. The results demonstrate that both criteria yield different drainage networks from “blue lines” based on topographic map from the Korean National Geographic Information Institute. Although t...

The purpose of this research is to understand the change of runoff characteristics by estimated spatial rainfall. Therefore, this paper largely composed of two parts. First, we compared the simulated result according to estimation method, ID(Inverse Distance Method, ID2(Inverse Square Distance Method), and Kr(General Covariance Kriging Method), after letting miss rainfall data to the observed data. Second, we reviewed the runoff characteristics of the distributed runoff model according to the estimated spatial rainfall. On the basis of Yuseong water level station, we select the target basin as Gabchun watershed. We assumed 1 point or 2 point of the 6 rainfall gauge stations in watershed were missed. We applied the spatial rainfall distributed by Kr to Hy-GIS GRM, distributed runoff model. When 1 point rainfall data is missed, Kr is superior to others in point rainfall estimation and runoff estimation of Hy-GIS GRM. However, in case rainfall data of 2 points is missed, all of three methods did not give suitable result for them. In conclusion, Kr showed better applicability than other estimated methods if rainfall’s data less than 2 points is missed.Key Words :General covariance Kriging, HyGIS-GRM, Missing rainfall data

In hydrologic modeling, prediction uncertainty generally stems from various uncertainty sources associated with model structure, data, and parameters, etc. This study aims to assess the parameter uncertainty effect on hydrologic prediction results. For this objective, a distributed rainfall-sediment yield-runoff model, which consists of rainfall-runoff module for simulation of surface and subsurface flows and sediment yield module based on unit stream power theory, was applied to the mesoscale mountainous area (Cheoncheon catchment; 289.9 ). For parameter uncertainty evaluation, the model was calibrated by a multi-objective optimization algorithm (MOSCEM) with two different objective functions (RMSE and HMLE) and Pareto optimal solutions of each case were then estimated. In Case I, the rainfall-runoff module was calibrated to investigate the effect of parameter uncertainty on hydrograph reproduction whereas in Case II, sediment yield module was calibrated to show the propagation of parameter uncertainty into sedigraph estimation. Additionally, in Case III, all parameters of both modules were simultaneously calibrated in order to take account of prediction uncertainty in rainfall-sediment yield-runoff modeling. The results showed that hydrograph prediction uncertainty of Case I was observed over the low-flow periods while the sedigraph of high-flow periods was sensitive to uncertainty of the sediment yield module parameters in Case II. In Case III, prediction uncertainty ranges of both hydrograph and sedigraph were larger than the other cases. Furthermore, prediction uncertainty in terms of spatial distribution of erosion and deposition drastically varied with the applied model parameters for all cases.

Accelerated soil erosion due to extreme climate change, such as increased rainfall intensity, and human-induced environmental changes, is a widely recognized problem. Existing soil erosion models are generally based on the gross erosion concept to compute annual upland soil loss in tons per acre per year. However, such models are not suitable for event-based simulations of erosion and deposition in time and space. Recent advances in computer geographic information system (GIS) technologies have allowed hydrologists to develop physically based models, and the trend in erosion prediction is towards process-based models, instead of conceptually lumped models. This study aims to propose an effective and robust distributed rainfall-sediment yield-runoff model consisting of basic element modules: a rainfall-runoff module based on the kinematic wave method for subsurface and surface flow, and a runoff-sediment yield-runoff model based on the unit stream power method. The model was tested on the Cheoncheon catchment, upstream of the Yongdam dam using hydrological data for three extreme flood events due to typhoons. The model provided acceptable simulation results with respect to both discharge and sediment discharge even though the simulated sedigraphs were underestimated, compared to observations. The spatial distribution of erosion and deposition demonstrated that eroded sediment loads were deposited in the cells along the channel network, which have a short overland flow length and a gentle local slope while the erosion rate increased as rainfall became larger. Additionally, spatially heterogeneous rainfall intensity, dependant on Thiessen polygons, led to spatially-distinct erosion and deposition patterns.

Selecting an appropriate digital elevation model (DEM) resolution is an essential part of distributed rainfall-runoff modeling since the resolution affects parameter values and, in turn, leads to predictive uncertainty. Moreover, the DEM resolution directly determines the computational workload required for model simulation. This study conducted several experiments to clarify the interaction between topographic and process parameters due to the spatial resolution of DEMs in distributed rainfall-runoff modeling. First, five different spatial resolutions (from 50 m to 1 km) were used to analyze the effects of DEM resolution on the topographic and process parameters of a distributed rainfall-runoff model [kinematic wave method for subsurface and surface runoff (KWMSS)]. Second, parameter compatibility was tested with regard to the sensitivity of model performance to optimal parameter values for each DEM, by applying the best-performing parameter combinations for each resolution to the models based on differi...

A natural rainfall-runoff process is conceptualized by means of mathematical form reflecting a physical law and hydrologist’s perception and it is typically calibrated and verified based on streamflow data, the commonly used catchment response. The streamflow data is obviously required, but is not sufficient to identify a conceptual parameter of a hydrologic model since numerous parameter combinations can often result in quite similar numerical values in terms of objective function and even indistinguishable simulated hydrographs. One of the efficient techniques to resolve this impasse is a combination of the model with streamflow data augmented by other kinds of hydrological information relevant to the prediction. In this study, internal dynamic response of catchment, spatiotemporally separated components of hydrograph, to the various mimic parameter sets is presented. It is concluded that all of simulations based on plausible parameter combinations sampled by using deterministic and stochastic automatic optimization algorithms, are performed equally well in terms of both model performance measure and visual comparison between observed and simulated hydrograph while internal behaviors of catchment show totally different aspects. The spatiotemporal information presented here can be utilized as one of the complementary constraints capable of filtering out non-physical parameter set(s).

No matter how sophisticated and accurate hydrologic models may be, prediction uncertainty is unavoidable problem in rainfall-runoff modeling and it stems from various components. Therefore, it is essential to identify and reduce sources of uncertainty for more precise agreement between model prediction and observations in the real system. In the context of uncertainty issues, the problem of model structural uncertainty or stability is an issue of increasing interest in recent research. This paper examines a nature of model structural inadequacy using a single-objective global optimization method in hydrological modeling and proposes a framework to assess model structural stability through a comparison of two hydrologic models.