• 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.33 no.4
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• pp.1413-1424
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• 2013

Recently, the frequency of severe storms increases in Korea. Severe storms occurring in a short time cause huge losses of both life and property. A considerable research has been performed for the flood control system development based on an accurate stream discharge prediction. A physical model is mainly used for flood forecasting and warning. Physical rainfall-runoff models used for the conventional flood forecasting process require extensive information and data, and include uncertainties which can possibly accumulate errors during modelling processes. ANFIS, a data driven model combining neural network and fuzzy technique, can decrease the amount of physical data required for the construction of a conventional physical models and easily construct and evaluate a flood forecasting model by utilizing only rainfall and water level data. A data driven model, however, has a disadvantage that it does not provide the mathematical and physical correlations between input and output data of the model. The characteristics of a data driven model according to functional options and input data such as the change of clustering radius and training data length used in the ANFIS model were analyzed in this study. In addition, the applicability of ANFIS was evaluated through comparison with the results of HEC-HMS which is widely used for rainfall-runoff model in Korea. The neuro-fuzzy technique was applied to a Cheongmicheon Basin in the South Han River using the observed precipitation and stream level data from 2007 to 2011.

• Journal of Korea Water Resources Association
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• v.39 no.10 s.171
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• pp.823-832
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• 2006

Precipitation is the most important component to the study of water and energy cycle in hydrology. In this study we investigate rainfall retrieval uncertainty from different sources of remotely sensed precipitation field and then probable error propagation in the simulation of hydrologic variables especially, runoff on different vegetation cover. Two remotely sensed rainfall retrievals (space-borne IR-only and ground radar rainfall) are explored and compared visually and statistically. Then, an offline Community Land Model (CLM) is forced with in situ meteorological data to simulate the amount of runoff and determine their impact on model predictions. A fundamental assumption made in this study is that CLM can adequately represent the physical land surface processes. Results show there are big differences between different sources of precipitation fields in terms of the magnitude and temporal variability. The study provides some intuitions on the uncertainty of hydrologic prediction via the interaction between the land surface and near atmosphere fluxes in the modelling approach. Eventually it will contribute to the understanding of water resources redistribution to the climate change in Korean Peninsula.

• Journal of the Korean Association of Geographic Information Studies
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• v.15 no.3
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• pp.103-118
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• 2012

A distributed model can easily obtain discharge at any grids spatially distributed in a watershed. But if there are subwatersheds which have various characteristics in a watershed, it is needed to apply a model calibrated at each subwatershed to obtain reliable simulation results for each subwatershed. In this study, a multi-site calibration module that can calibrate a distributed model at each subwatershed using observed flow data was developed. Methods to select multi-site calibration parameters, to apply subwatershed parameters, and to set subwatershed network information are suggested. Classes to implement multi-site calibration technique are designed and a GUI was developed, and procedures for runoff modelling using subwatershed parameters were established. Multi-site calibration module was applied to Sunsan watershed($977km^2$) of Nakdong river basin. Application results showed that the multi-site calibration technique could be applied effectively to model the calibration for each subwatershed, and the simulation results of subwatershed were improved by the application of multi-site calibration.

• Journal of Korea Water Resources Association
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• v.51 no.4
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• pp.347-354
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• 2018

In urban areas, runoff flow is drained through sewer networks as well as surface areas. Therefore, it is very important to consider sewer networks as a component of hydrological drainage processes when conducting urban inundation modelling. However, most researchers who have implemented urban inundation/flood modelling, instinctively simplified the sewer networks without the appropriate criteria. In this research, a 1D-2D fully coupled urban inundation model is applied to estimate the influence of sewer network simplification on urban inundation modelling based on the dendritic network classification. The one-dimensional (1D) sewerage system analysis model, which was introduced by Lee et al. (2017), is used to simulate inlet and overflow phenomena by interacting with surface flow. Two-dimensional (2D) unstructured meshes are also applied to simulate surface flow and are combined with the 1D sewerage analysis model. Sewer network pipes are simplified based on the dendritic network classification method, namely the second and third order, and all cases of pipes are conducted as a control group. Each classified network case, including a control group, is evaluated through their application to the 27 July 2011 extreme rainfall event, which caused severe inundation damages in the Sadang area in Seoul, South Korea. All cases are compared together regarding inundation area, inflow discharge and overflow discharge. Finally, relevant criterion for the simplification method is recommended.

• Journal of Wetlands Research
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• v.22 no.3
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• pp.187-193
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• 2020

The increase in the area of impervious water due to the recent abnormal weather conditions and rapid urbanization led to a decrease in the amount of low current, resulting in an increase in the amount of surface runoff. Increased surface runoff is causing erosion, destruction of underwater ecosystems, human and property damage in urban areas due to flooding of urban river. The damage has been increasing in Korea recently due to localized heavy rains, typhoons and floods. As a countermeasure, the Busan Metropolitan Government will proceed with the creation of the Eco-Delta City waterfront zone in Busan with the aim of creating a future-oriented waterfront city from 2012 to 2023. Therefore, the current urban river conditions and precipitation data were collected by utilizing SWMM developed by the Environment Protection Agency, and the target basin was selected to simulate flood damage. Measures to reduce flood damage in various cases were proposed using simulated data. It is a method to establish a disaster prevention plan for each case by establishing scenario for measures to reduce flood damage. Considering structural and non-structural measures by performing an analysis of the drainage door with a 30-year frequency of 80 minutes duration, the expansion effect of the drainage pump station is considered to be greater than that of the expansion of the drainage door, and 8 scenarios and corresponding alternatives were planned in combination with the pre-excluding method, which is a non-structural disaster prevention measure. As a result of the evaluation of each alternative, it was determined that 100㎥/s of the pump station expansion and the pre-excluding EL.(-)1.5m were the best alternatives.

• Journal of Korea Water Resources Association
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• v.45 no.1
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• pp.39-52
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• 2012

Surface-subsurface interactions are an intrinsic component of the hydrologic response within a watershed. In general, these interactions are considered to be one of the most difficult areas of the discipline, particularly for the modeler who intends simulate the dynamic relations between these two major domains of the hydrological cycle. In essence, one major complexity is the spatial and temporal variations in the dynamically interacting system behavior. The proper simulation of these variations requires the need for providing an appropriate coupling mechanism between the surface and subsurface components of the system. In this study, an approach for modelling surface-subsurface flow and transport in a fully intergrated way is presented. The model uses the 2-dimensional diffusion wave equation for sheet surface water flow, and the Boussinesq equation with the Darcy's law and Dupuit-Forchheimer's assumption for variably saturated subsurface water flow. The coupled system of equations governing surface and subsurface flows is discretized using the finite volume method with central differencing in space and the Crank-Nicolson method in time. The interactions between surface and subsurface flows are considered mass balance based on the continuity conditions of pressure head and exchange flux. The major module consists of four sub-module (SUBFA, SFA, IA and NS module) is developed.