• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.5
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• pp.110-116
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• 2003

A catchment modelling system is the summation of the numerous hydrologic, hydraulic and other process models necessary to simulate the response of a catchment to a storm event. Differences between the recorded catchment response and that predicted by a catchment modelling system can arise from structural errors within the catchment modelling system, evaluation errors in the control parameters, or measurement errors in the recorded data being used to assess the reliability of the evaluation of the control parameters. Presented herein is an investigation of the potential measurement errors within the recorded information, which was considered to occur from instrument error in the ultra sonic flow monitor. This investigation was undertaken using three available rating curves at the Musgrave Avenue Stormwater System in Centennial Park, Sydney, developed by Abustan (1997), Water Board (1994), and using Manning's equation.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.5
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• pp.117-125
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• 2003

Since the recorded information used for operation of a catchment modelling system contain errors that influence the calibration of catchment modelling system control parameter values, the accurate estimation of these parameters is difficult. Despite these influences, existing traditional calibration approaches focus only on achieving the best "curve fitting" between simulated and recorded data, and not on generic evaluation of control parameter values. This paper introduces an Early Stopping Technique which is aimed at avoiding the procedure of curve-fitting through monitoring improvements in the objective function used for assessing the optimal parameter set. Application of this approach to the calibration of SWMM (Storm Water Management Model) on the Centennial Park catchment in Sydney, Australia is outlined. outlined.

• Journal of Korea Water Resources Association
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• v.36 no.4
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• pp.587-596
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• 2003

Application of a catchment modelling system requires recorded information to ascertain the reliability and robustness of the predicted flow conditions. Where this recorded information is not available, the necessary information for reliable and robust predictions must be obtained from other available information sources. The alternative approach presented in this paper used inference models for getting this necessary information that is required to calibrate and validate the catchment modelling system for both an ungauged and a gauged catchments. In this study, inference models were developed for determination of control parameters of the Storm Water Management Model (SWMM), mainly based on landuse component of the catchment, which is a major factor to impact on quantity and quality of catchment runoff. Results from the study show that the new approach for determination of the spatially variable control parameters produced more accurate estimates than a traditional approach. Also, the number of control parameters estimated can be reduced significantly as the proposed method only requires determination of control parameters associated with each land use of the catchment while a traditional approach needs to assign a number of control parameters for a number of subcatchment.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.4
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• pp.89-97
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• 2003

Using inference models developed for estimation of the parameters necessary to implement the Runoff Block of the Stormwater Management Model (SWMM), a number of alternative inference scenarios were developed to assess the influence of inference model complexity and structure on the calibration of the catchment modelling system. These inference models varied from the assumption of a spatially invariant value (catchment average) to spatially variable with each subcatchment having its own unique values. Fur-thermore, the influence of different measures of deviation between the recorded information and simulation predictions were considered. The results of these investigations indicate that the model performance is more influenced by model structure than complexity, and control parameter values are very much dependent on objective function selected as this factor was the most influential for both the initial estimates and the final results.

• Journal of the Korean Association of Geographic Information Studies
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• v.6 no.3
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• pp.129-138
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• 2003

A new methodology for selecting spatially variable model control parameter values through consideration of inference models within a Hydroinformatic system has been developed to overcome problems associated with determination of spatially variable control parameter values for both ungauged and gauged catchment. The adopted Hydroinformatic tools for determination of control parameter values were a GIS(Arc/Info) to handle spatial and non-spatial attribute information, the SWMM(stormwater management model) to simulate catchment response to hydrologic events, and lastly, L_BFGS_B(a limited memory quasi-Newton algorithm) to assist in the calibration process. As a result, high accuracy of control parameter estimation was obtained by considering the spatial variations of the control parameters based on landuse characteristics. Also, considerable time and effort necessary for estimating a large number of control parameters were reduced from the new calibration approach.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.14 no.4
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• pp.875-886
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• 1994

This study is to develop an advanced storm runoff analysis program which takes geomorphological characteristics of watershed into consideration in determining model parameters. Basic concept of storm runoff modelling is based upon the kinematic wave theory. And numerical solution is obtained by the characteristic curve method. The storm runoff analysis program developed by this study is composed of multiple equivalent roughness sub-basins, each of which has two equivalent catchments on both side of a stream. Because it is based upon the stream-order of the Strahler system, the equivalent catchment-stream network reflects the stochastic geomorphological characteristics in the model parameter. Applicability and reliability of the storm runoff analysis program is evidenced by model calibration and verification process utilizing geographical and hydrological data of the Bocheong-river area which is a representative watershed of IHP projects in Korea. This study will hopefully contribute to hydrological calculation essentially required to understand water quality effect caused by regional development.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.40-48
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• 2008

The Waimea Basin is located on the northern tip of the South Island of New Zealand. It is a highly productive area with intense water use with multi-stakeholder interest in water. Irrigation from the underground aquifers here makes up the largest portion of used water; however the same aquifers are also the key urban and industrial sources of water. The Waimea/Wairoa Rivers are the main sources of recharge to the underlying aquifers and also feed the costal springs that highly valued by the community and iwi. Due to the location of the main rivers and springs close to the urban centre the water resource system here has high community and aesthetic values. Recent enhanced hydrological modelling work has shown the water resources in this area to be over allocated by 22% for a 1:10 year drought security for maintaining a minimalistic flow of 250 l/s in the lower Waimea River. The current irrigated land area is about 3700 hectares with an additional potential for irrigation of 1500 hectares. Further pressures are also coming on-line with significant population growth in the region. Recent droughts have resulted in significant water use cutbacks and the threat of seawater intrusion in the coastal margins. The Waimea Water Augmentation Committee (WWAC) initiated a three year stage 1 feasibility study in 2004/2005 into the viability of water storage in the upper parts of the catchment for enhancing water availability and its security of supply for consumptive, environmental, community and aesthetic benefits downstream. The project also sought to future proof water supply needs for the Waimea Plains and the surrounding areas for a 50 - 100 year planning horizon. The broad range stage 1 investigation programme has identified the Upper Lee Catchment as being suitable for a storage structure to provide the needs identified and also a possibility for some small scale hydro electricity generation as well. The stage 2 detailed feasibility investigations that are underway now (2007/2008), and to be completed in two years is to provide all details for progressing with the next stage of obtaining necessary permits for construction and commissioning a suitable dam.

• Journal of Korea Water Resources Association
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• v.32 no.6
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• pp.711-720
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• 1999

In this study, a various rainfall-runoff modelling approaches have been applied to the runoff response of flood hydrograph in three experimental watershed of the western part of korea. Mathematical models of runoff response also have been studied including linear system theory based on modeling techniques. Eight models were operated at the five water level gauging stations and the parameters of each model were computed by the Rosenbrock's hill climbing method to minimize the objective function. For the parameter verification of the models, a different complex rainfall-runoff event was selected in the same of the three river basins and derived IUH of the each model could be calibrated. Furthermore multiple regressions of the logarithmic transformation method between model parameters and catchment characteristics were studied in the selected five station.

• Journal of the Korean Association of Geographic Information Studies
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• v.9 no.4
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• pp.34-44
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• 2006

Simulation models allow researchers to model large hydrological catchment for comprehensive management of the water resources and explication of the diffuse pollution processes, such as land-use changes by development plan of the region. Recently, there have been reported many researches that examine water body quality using Geographic Information System (GIS) and dynamic watershed models such as AGNPS, HSPF, SWAT that necessitate handling large amounts of data. The aim of this study is to develop a watershed based water quality estimation system for the impact assessment on stream water quality. KBASIN-HSPF, proposed in this study, provides easy data compiling for HSPF by facilitating the setup and simulation process. It also assists the spatial interpretation of point and non-point pollutant information and thiessen rainfall creation and pre and post processing for large environmental data An integration methodology of GIS and water quality model for the preprocessing geo-morphologic data was designed by coupling the data model KBASIN-HSPF interface comprises four modules: registration and modification of basic environmental information, watershed delineation generator, watershed geo-morphologic index calculator and model input file processor. KBASIN-HSPF was applied to simulate the water quality impact by variation of subbasin pollution discharge structure.