Effect of urbanization on runoff characteristics of the On-Cheon Stream watershed in Pusan,Korea     

In Shik Kang  Jun Il Park  Vijay P. Singh 《水文研究》1998,12(2):351-363

This study investigated the effect of urbanization on runoff from the On-Cheon Stream watershed in Pusan, Korea. This watershed has been experiencing considerable urbanization since the 1960s. There are two gauging stations in the watershed. For one of the stations there are recent flow data and for the other flow data were observed in the past. A linear reservoir model was chosen and runoff was analysed for several flood events. The linear reservoir model has been found to generate flood hydrographs accurately for both gauging stations, and its applicability to the study area has also been established. Using two methods of computing effective rainfall or rainfall excess (ϕ-index and constant percentage method), the results of runoff analyses were investigated. The ϕ-index method yielded better results than the constant percentage method. A comparison of hydrographs observed in the past with the simulation results at the Ie-Sup bridge site revealed that the peak discharge increased and the mean lag time of the study area decreased owing to urbanization over the past two decades. It is also possible to evaluate the effect of urbanization quantitatively. © 1998 John Wiley & Sons, Ltd.  相似文献   

Comparison of artificial neural network models for hydrologic predictions at multiple gauging stations in an agricultural watershed   总被引：1，自引：0，他引：1  

E. Mutlu  I. Chaubey  H. Hexmoor  S. G. Bajwa 《水文研究》2008,22(26):5097-5106

This paper reports on an evaluation of the use of artificial neural network (ANN) models to forecast daily flows at multiple gauging stations in Eucha Watershed, an agricultural watershed located in north‐west Arkansas and north‐east Oklahoma. Two different neural network models, the multilayer perceptron (MLP) and the radial basis neural network (RBFNN), were developed and their abilities to predict stream flow at four gauging stations were compared. Different scenarios using various combinations of data sets such as rainfall and stream flow at various lags were developed and compared for their ability to make flow predictions at four gauging stations. The input vector selection for both models involved quantification of the statistical properties such as cross‐, auto‐ and partial autocorrelation of the data series that best represented the hydrologic response of the watershed. Measured data with 739 patterns of input–output vector were divided into two sets: 492 patterns for training, and the remaining 247 patterns for testing. The best performance based on the RMSE, R² and CE was achieved by the MLP model with current and antecedent precipitation and antecedent flow as model inputs. The MLP model testing resulted in R² values of 0·86, 0·86, 0·81, and 0·79 at the four gauging stations. Similarly, the testing R² values for the RBFNN model were 0·60, 0·57, 0·58, and 0·56 for the four gauging stations. Both models performed satisfactorily for flow predictions at multiple gauging stations, however, the MLP model outperformed the RBFNN model. The training time was in the range 1–2 min for MLP, and 5–10 s for RBFNN on a Pentium IV processor running at 2·8 GHz with 1 MB of RAM. The difference in model training time occurred because of the clustering methods used in the RBFNN model. The RBFNN uses a fuzzy min‐max network to perform the clustering to construct the neural network which takes considerably less time than the MLP model. Results show that ANN models are useful tools for forecasting the hydrologic response at multiple points of interest in agricultural watersheds. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

LAND-USE IMPACT ON WATERSHED RESPONSE: THE INTEGRATION OF TWO-DIMENSIONAL HYDROLOGICAL MODELLING AND GEOGRAPHICAL INFORMATION SYSTEMS     

WILLIAM W. DOE III  BAHRAM SAGHAFIAN  PIERRE Y. JULIEN 《水文研究》1996,10(11):1503-1511

The integration of a two-dimensional, raster-based rainfall–runoff model, CASC2D, with a raster geographical information system (GIS), GRASS, offers enhanced capabilities for analysing the hydrological impact under a variety of land management scenarios. The spatially varied components of the watershed, such as slope, soil texture, surface roughness and land-use disturbance, were characterized in GRASS at a user-specified grid cell resolution for input into the CASC2D model. CASC2D is a raster-based, single-event rainfall–runoff model that divides the watershed into grid cell elements and simulates the hydrological processes of infiltration, overland flow and channel flow in response to distributed rainfall precipitation. The five-step integration of CASC2D and GRASS demonstrates the potential for analysing spatially and temporally varied hydrological processes within a 50 square mile semi-arid watershed. By defining possible land-use disturbance scenarios for the watershed, a variety of rainfall–runoff events were simulated to determine the changes in watershed response under varying disturbance and rainfall conditions. Additionally, spatially distributed infiltration outputs derived from the simulations were analysed in GRASS to determine the variability of hydrological change within the watershed. Grid cell computational capabilities in GRASS allow the user to combine the scenario simulation outputs with other distributed watershed parameters to develop complex maps depicting potential areas of hydrological sensitivity. This GIS–hydrological model integration provides valuable spatial information to researchers and managers concerned with the study and effects of land-use on hydrological response.  相似文献   

Stochastic multi-site generation of daily rainfall occurrence in south Florida     

Tae-woong Kim  Hosung Ahn  Gunhui Chung  Chulsang Yoo 《Stochastic Environmental Research and Risk Assessment (SERRA)》2008,22(6):705-717

This paper presents a stochastic model to generate daily rainfall occurrences at multiple gauging stations in south Florida. The model developed in this study is a space–time model that takes into account the spatial as well as temporal dependences of daily rainfall occurrence based on a chain-dependent process. In the model, a Markovian method was used to represent the temporal dependence of daily rainfall occurrence and a direct acyclic graph (DAG) method was introduced to encode the spatial dependence of daily rainfall occurrences among gauging stations. The DAG method provides an optimal sequence of generation by maximizing the spatial dependence index of daily rainfall occurrences over the region. The proposed space–time model shows more promising performance in generating rainfall occurrences in time and space than the conventional Markov type model. The space–time model well represents the temporal as well as the spatial dependence of daily rainfall occurrences, which can reduce the complexity in the generation of daily rainfall amounts.  相似文献   

Using the Climate Forecast System Reanalysis as weather input data for watershed models   总被引：4，自引：0，他引：4       下载免费PDF全文

Daniel R. Fuka  M. Todd Walter  Charlotte MacAlister  Arthur T. Degaetano  Tammo S. Steenhuis  Zachary M. Easton 《水文研究》2014,28(22):5613-5623

Obtaining representative meteorological data for watershed‐scale hydrological modelling can be difficult and time consuming. Land‐based weather stations do not always adequately represent the weather occurring over a watershed, because they can be far from the watershed of interest and can have gaps in their data series, or recent data are not available. This study presents a method for using the Climate Forecast System Reanalysis (CFSR) global meteorological dataset to obtain historical weather data and demonstrates the application to modelling five watersheds representing different hydroclimate regimes. CFSR data are available globally for each hour since 1979 at a 38‐km resolution. Results show that utilizing the CFSR precipitation and temperature data to force a watershed model provides stream discharge simulations that are as good as or better than models forced using traditional weather gauging stations, especially when stations are more than 10 km from the watershed. These results further demonstrate that adding CFSR data to the suite of watershed modelling tools provides new opportunities for meeting the challenges of modelling un‐gauged watersheds and advancing real‐time hydrological modelling. Copyright © 2013 John Wiley & Sons, Ltd.  相似文献   

Estimation and spatial interpolation of rainfall intensity distribution from the effective rate of precipitation   总被引：1，自引：0，他引：1  

Ming Li  Quanxi Shao  Luigi Renzullo 《Stochastic Environmental Research and Risk Assessment (SERRA)》2010,24(1):117-130

Great emphasis is being placed on the use of rainfall intensity data at short time intervals to accurately model the dynamics of modern cropping systems, runoff, erosion and pollutant transport. However, rainfall data are often readily available at more aggregated level of time scale and measurements of rainfall intensity at higher resolution are available only at limited stations. A distribution approach is a good compromise between fine-scale (e.g. sub-daily) models and coarse-scale (e.g. daily) rainfall data, because the use of rainfall intensity distribution could substantially improve hydrological models. In the distribution approach, the cumulative distribution function of rainfall intensity is employed to represent the effect of the within-day temporal variability of rainfall and a disaggregation model (i.e. a model disaggregates time series into sets of higher solution) is used to estimate distribution parameters from the daily average effective precipitation. Scaling problems in hydrologic applications often occur at both space and time dimensions and temporal scaling effects on hydrologic responses may exhibit great spatial variability. Transferring disaggregation model parameter values from one station to an arbitrary position is prone to error, thus a satisfactory alternative is to employ spatial interpolation between stations. This study investigates the spatial interpolation of the probability-based disaggregation model. Rainfall intensity observations are represented as a two-parameter lognormal distribution and methods are developed to estimate distribution parameters from either high-resolution rainfall data or coarse-scale precipitation information such as effective intensity rates. Model parameters are spatially interpolated by kriging to obtain the rainfall intensity distribution when only daily totals are available. The method was applied to 56 pluviometer stations in Western Australia. Two goodness-of-fit statistics were used to evaluate the skill—daily and quantile coefficient of efficiency between simulations and observations. Simulations based on cross-validation show that kriging performed better than other two spatial interpolation approaches (B-splines and thin-plate splines).  相似文献   

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

RAAJ Ramsankaran  U. C. Kothyari  S. K. Ghosh  A. Malcherek  K. Murugesan 《水文研究》2012,26(9):1405-1426

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.  相似文献   

Multi-method groundwater recharge estimation at Eshito micro-watershed,Rift Valley Basin in Ethiopia     

Mintamer Ferede  Alemseged Tamiru Haile  David Walker  John Gowing  Geoff Parkin 《水文科学杂志》2020,65(9):1596-1605

ABSTRACT

Understanding recharge processes is fundamental to improve sustainable groundwater resource management. Shallow groundwater (SGW) is being developed for multiple purposes in Ethiopia without consideration of monitoring. We established a citizen science-based hydro-meteorological monitoring network, with a focus on SGW recharge estimation, in Eshito micro-watershed, Ethiopia. Citizen scientists collected rainfall, groundwater-level and stream water-level data. We characterized the shallow aquifer using pumping tests. The data were used to estimate SGW recharge using three methods: chloride mass balance, water-level fluctuation (WLF) and baseflow separation. Approximately 20% and 35% of annual rainfall amount contributes to recharge based on the chloride mass balance and WLF results, respectively. Baseflow separation showed recharge values for the watershed vary from 38% to 28% of annual rainfall at the upstream and downstream gauging stations, respectively. This study shows that the recharge in previously unmonitored micro-watersheds can be studied if citizens are involved in data generation.  相似文献   

Uranium-series isotopes in river materials: Insights into the timescales of erosion and sediment transport     

Anthony Dosseto  Bernard Bourdon  Simon P. Turner 《Earth and Planetary Science Letters》2008,265(1-2):1-17

The uranium-series isotope signatures of the suspended and dissolved load of rivers have emerged as an important tool for understanding the processes of erosion and chemical weathering at the scale of a watershed. These signatures are a function of both time and weathering-induced fractionation between the different nuclides. Provided appropriate models can be developed, they can be used to constrain the residence time of river sediment. This chronometer is triggered as the bedrock starts weathering and the inferred timescale encompasses the residence time in the weathering profile, storage in temporary sediment deposits (e.g. floodplain) and transport in the river. This approach has been applied to various catchments over the past five years showing that river sediments can reside in a watershed for timescales ranging from a few hundreds of years (Iceland) to several hundreds of thousands of years (lowlands of the Amazon). Various factors control how long sediment resides in the watershed: the longest residence times are observed on stable cratons unaffected by glacial cycles (or more generally, climate variability) and human disturbance. Shorter residence times are observed in active orogens (Andes) or fast-eroding, recently glaciated catchments (Iceland). In several cases, the residence time of suspended sediments also corresponds to the time since the last major climate change. The U-series isotope composition of rivers can also be used to predict the river sediment yield assuming steady-state erosion is reached. By comparing this estimate with the modern sediment yield obtained by multi-year sediment gauging, it is clear that steady-state is seldom reached. This can be explained by climate variability and/or human disturbance. Steady-state is reached in those catchments where sediment transport is rapid (Iceland) or where the region has been unaffected by climate change and/or human disturbance. U-series are thus becoming an important tool to study the dynamics of erosion.  相似文献   

Simultaneous hydrological prediction at multiple gauging stations using the NARX network for Kemaman catchment,Terengganu, Malaysia     

Wei-Koon Lee  Tuan Asmaa Tuan Resdi 《水文科学杂志》2013,58(16):2930-2945

ABSTRACT

This paper presents a neural network model capable of catchment-wide simultaneous prediction of river stages at multiple gauging stations. Thirteen meteorological parameters are considered in the input, which includes rainfall, temperature, mean relative humidity and evaporation. The NARX model is trained with a representative set of hourly data, with optimal time delay for both the input and output. The network trained using 120-day data is able to produce simulations that are in excellent agreement with field observations. We show that for application with one-step-ahead predictions, the loss in network performance is marginal. Inclusion of additional tidal observations does not improve predictions, suggesting that the river stage stations under consideration are not sensitive to tidal backwater effects despite the claim commonly made.