Stream Gauging Stations Research Articles

Evaluation of the capability of the Lombard test in detecting abrupt changes in variance

Summary Hydrologic time series are often characterized by temporal changes that give rise to non-stationarity. When the distribution describing the data changes over time, it is important to detect these changes so that correct inferences can be drawn from the data. The Lombard test, a non-parametric rank-based test to detect change points in the moments of a time series, has been recently used in the hydrologic literature to detect change points in the mean and variance. Little is known, however, about the performance of this test in detecting changes in variance, despite the potentially large impacts that these changes (shifts) could have when dealing with extremes. Here we address this issue in a Monte Carlo simulation framework. We consider a number of different situations that can manifest themselves in hydrologic time series, including the dependence of the results on the magnitude of the shift, significance level, sample size and location of the change point within the series. Analyses are performed considering abrupt changes in variance occurring with and without shifts in the mean. The results show that the power of the test in detecting change points in variance is small when the changes are small. It is large when the change point occurs close to the middle of the time series, and it increases nonlinearly with increasing sample size. Moreover, the power of the test is greatly reduced by the presence of change points in mean. We propose removing the change in the mean before testing for change points in variance. Simulation results demonstrate that this strategy effectively increases the power of the test. Finally, the Lombard test is applied to annual peak discharge records from 3686 U.S. Geological Survey stream-gaging stations across the conterminous United States, and the results are discussed in light of the insights from the simulations’ results.

Variability and Trends in Streamflow in Northeast United States

There is general consensus that climate is undergoing change but whether climate change is occurring or not is still being debated in certain scientific, political, and religious quarters. Hydrologic variability influences the design of civil works and assessment of long-term climate change would help improve design criteria. To this end, long-term variability of streamflow was estimated using Shannon entropy. Three statistical tests were applied to determine trends in annual and seasonal daily streamflow with 5% two-sided confidence limit. Daily streamflow data spanning 70 years (from 1943 to 2012) from 669 stream gauge stations located in 23 states in the northeastern part of United States of America, covering six different water regions were employed. The time variability of annual and seasonal daily streamflow was assessed using the Mean Decadal Apportionment Disorder Index (MDADI). Analysis showed that in all cases minimum and maximum streamflows had higher variability than average and median streamflows. A significant number of stations exhibited trends. Considering annual minimum, average and median daily streamflows, approximately 50% of the stations followed trends and for almost all these stations trends were increasing. Only for annual maximum daily streamflow, 15% of the stations showed increasing trend and 10% decreasing trend. In terms of geographical distribution, the stations with increasing trend were essentially located along the Atlantic coast and near Great Lakes and in the Upper Mississippi Water Region. Similar considerations apply for seasonal time series as well.

Determining the Adequacy of CFSR Data for Rainfall-Runoff Modeling Using SWAT

Stream discharge data are the essential information required to plan and design any watershed related project. In most of the cases, these data may not be available/ collected as there is no prior information regarding the commencement of a new project at the particular site. For a concerned watershed, number of stream gauge stations may be limited. But, due to the availability of large number of rain gauge stations, it is better to have rainfall – runoff model. However, land – based rain gauge stations do not always adequately represent the weather status of a watershed because they are point measurements, can be far from the characteristics of watershed of interest and can have gaps in their data series. Hence in the present study, the adequacy of CFSR (Climate Forecast System Reanalysis) data is determined to solve the problems of data deficiency in watersheds. Karuvannur watershed in Thrissur district is taken as the study area and is modeled using SWAT (Soil And Water Assessment Tool). Initially, the model was run for the available number of rain gauge stations. Then the model was executed by using CFSR data to find the accuracy of CFSR data in rainfall runoff modeling.

Low-Cost Pneumatic Sensor for Water Level Detection in Gauging Stations

Permanent stream gauge stations are a vital feature of river monitoring and water management worldwide, and their use is rapidly increasing. Water level sensors in gauging stations are subjected to a harsh physical environment and are generally the most troublesome component and may easily introduce corrosion, electrical interference and other potentially damaging influences to the other components. One technology currently available to address the shortcomings of traditional submersible sensors is pneumatic detection of stage. The primary advantage of this type of sensor is that it provides physical separation of electrical components from the water. They are also highly advantageous in systems with high silt or debris loads. The cost of pneumatic sensors has fallen in recent years and is comparable with submersible pressure sensors of similar range and resolution. The issue with pneumatic sensors is that there is a large gap in the literature addressing the development, use and accuracy of this sensor type. This paper presents a case study detailing the development and use of a low-cost pneumatic sensor and examines its suitability for use in streams and irrigation canals. The performance of the sensor is also evaluated against two types of traditional low-cost submersible pressure sensors. Copyright © 2015 John Wiley & Sons, Ltd.

On the seasonality of flooding across the continental United States

This study examines the seasonality of flooding across the continental United States using circular statistics. Analyses are based on 7506 USGS stream gage stations with a record of least 30 years of annual maximum instantaneous peak discharge. Overall, there is a very strong seasonality in flooding across the United States, reflecting differences in flood generating mechanisms. Most of the flood events along the western and eastern United States tend to occur during the October–March period and are associated with extratropical cyclones. The average seasonality of flood events shifts to April–May in regions where snowmelt is the dominant flood agent, and later in the spring–summer across the central United States. The strength of the seasonal cycle also varies considerably, with the weakest seasonality in the Appalachian Mountains and the strongest in the northern Great Plains. The seasonal distribution of flooding is described in terms of circular uniform, reflective symmetric and asymmetric distributions. There are marked differences in the shape of the distribution across the continental United States, with the majority of the stations exhibiting a reflective symmetric distribution.Finally, nonstationarities in the seasonality of flooding are examined. Analyses are performed to detect changes over time, and to examine changes that are due to urbanization and regulation. Overall, there is not a strong signal of temporal changes. The strongest impact of urbanization and regulation is on the strength of the seasonal cycle, with indications that the signal weakens (i.e., the seasonal distribution becomes wider) under the effects of regulation.

The Flashiest Watersheds in the Contiguous United States

Abstract The authors identify the flashiest watersheds in the contiguous United States based on frequency of discharge peaks exceeding 1 m3 s−1 km−2. The entire digitized record of USGS instantaneous discharge data is used for all stream gauging stations with over 10 years of data. Using the 1 m3 s−1 km−2 threshold, the flashiest basins in the contiguous United States are located in urban areas along a swath of states from the south-central United States to the mid-Atlantic and in mountainous areas of the West Coast, especially the Pacific Northwest. The authors focus on small watersheds to identify the flashiest cities and states across the country and find Tulsa, Oklahoma; Baltimore, Maryland; and St. Louis, Missouri, to be the flashiest cities in the contiguous United States. Thunderstorms are major agents for peak-over-threshold flood events east of the Rocky Mountains, and tropical cyclones play a secondary role, especially in the Southeast. West Coast flood events are associated with winter storms. Flooding west of and within the Rockies is linked to steeply sloped terrain and compact watersheds. East of the Rockies, urban areas dominate flashy watersheds. The authors find that watersheds northeast (downwind) of city centers are flashier than other urban watersheds, consistent with the downwind maximum in rainfall found in many urban regions. They examine anomalous flood response in the Illinois–Missouri region; St. Louis is among the flashiest cities in the United States, while Chicago is among the least flashy. Their flashiness map is compared with other measures of flooding, including flood damage and National Weather Service flash flood reports.

A simple iterative method for estimating evapotranspiration with integrated surface/subsurface flow models

Summary This work presents an iterative, water balance based approach to estimate actual evapotranspiration (ET) with integrated surface/subsurface flow models. Traditionally, groundwater level fluctuation methods have been widely accepted and used for estimating ET and net groundwater recharge; however, in watersheds where interactions between surface and subsurface flow regimes are highly dynamic, the traditional method may be overly simplistic. Here, an innovative methodology is derived and demonstrated for using the water balance equation in conjunction with a fully-integrated surface and subsurface hydrologic model (HydroGeoSphere) in order to estimate ET at watershed and sub-watershed scales. The method invokes a simple and robust iterative numerical solution. For the proof of concept demonstrations, the method is used to estimate ET for a simple synthetic watershed and then for a real, highly-characterized 7000 km2 watershed in Southern Ontario, Canada (Grand River Watershed). The results for the Grand River Watershed show that with three to five iterations, the solution converges to a result where there is less than 1% relative error in stream flow calibration at 16 stream gauging stations. The spatially-averaged ET estimated using the iterative method shows a high level of agreement (R2 = 0.99) with that from a benchmark case simulated with an ET model embedded directly in HydroGeoSphere. The new approach presented here is applicable to any watershed that is suited for integrated surface water/groundwater flow modelling and where spatially-averaged ET estimates are useful for calibrating modelled stream discharge.

Modeling stream temperature in the Anthropocene: An earth system modeling approach

AbstractA new large‐scale stream temperature model has been developed within the Community Earth System Model (CESM) framework. The model is coupled with the Model for Scale Adaptive River Transport (MOSART) that represents river routing and a water management model (WM) that represents the effects of reservoir operations and water withdrawals on flow regulation. The coupled models allow the impacts of reservoir operations and withdrawals on stream temperature to be explicitly represented in a physically based and consistent way. The models have been applied to the Contiguous United States driven by observed meteorological forcing. Including water management in the models improves the agreement between the simulated and observed streamflow at a large number of stream gauge stations. It is then shown that the model is capable of reproducing stream temperature spatiotemporal variation satisfactorily by comparing against the observed data from over 320 USGS stations. Both climate and water management are found to have important influence on the spatiotemporal patterns of stream temperature. Furthermore, it is quantitatively estimated that reservoir operation could cool down stream temperature in the summer low‐flow season (August–October) by as much as 1∼2°C due to enhanced low‐flow conditions, which have important implications to aquatic ecosystems. Sensitivity of the simulated stream temperature to input data and reservoir operation rules used in the WM model motivates future directions to address some limitations in the current modeling framework.

Application of Artificial Neural Networks and regression analysis to L-moments based regional frequency analysis in the Eastern Black Sea Basin, Turkey

This study presents the use of L-moments based regression analysis and Artificial Neural Networks (ANN) for forecasting maximum annual flows of Eastern Black Sea Basin, Turkey. Homogeneity of the region is determined by discordancy (Di) and heterogeneity (Hi) measures based on L-moments. Several distributions are fitted to the data of the 33 stream gauging stations. Return periods (T) corresponding to each flow rates are calculated using the probability density functions of best fit distribution of the region. Using these T values and also drainage area, main stream slope, elevation, stream density, and mean annual rainfall values as independent variables, regression and ANN models are adopted to the data. Mean relative error, mean absolute error and root mean square error are applied for evaluating the performance of the models. Error values indicate that ANN method yields better results for estimation of maximum flows.

Classical and generalized Horton laws for peak flows in rainfall-runoff events

The discovery of the Horton laws for hydrologic variables has greatly lagged behind geomorphology, which began with Robert Horton in 1945. We define the classical and the generalized Horton laws for peak flows in rainfall-runoff events, which link self-similarity in network geomorphology with river basin hydrology. Both the Horton laws are tested in the Iowa River basin in eastern Iowa that drains an area of approximately 32 400 km(2) before it joins the Mississippi River. The US Geological Survey continuously monitors the basin through 34 stream gauging stations. We select 51 rainfall-runoff events for carrying out the tests. Our findings support the existence of the classical and the generalized Horton laws for peak flows, which may be considered as a new hydrologic discovery. Three different methods are illustrated for estimating the Horton peak-flow ratio due to small sample size issues in peak flow data. We illustrate an application of the Horton laws for diagnosing parameterizations in a physical rainfall-runoff model. The ideas and developments presented here offer exciting new directions for hydrologic research and education.

Wet-dry runoff correlation in Western Route of South-to-North Water Diversion Project, China

The Western Route of the South-to-North Water Diversion Project is an important trans-basin diversion project to transfer water from the upstream Yangtze River and its tributaries (water-exporting area), to the upstream of the Yellow River (water-importing area). The long-term hydrological data from 14 stream gauging stations in the Western Route area and techniques including the pre-whitening approach, non-parametric test, Bayes, law, variance analysis extrapolation, and Wavelet Analysis are applied to identify the streamflow characteristics and trends, streamflow time series cross-correlations, wetness-dryness encountering probability, and periodicities that occurred over the last 50 years. The results show that the water-exporting area, water-importing area, and the stretch downstream of the water-exporting have synchronization in high–low flow relationship, whereas they display non-synchronization in long-term evolution. This corresponds to the complicated and variable climate of the plateau region. There is no obvious increasing or decreasing trend in runoff at any gauging station. The best hydrological compensation probability for rivers where water is diverted is about 25% to 10%, and those rivers influenced significantly by diversion are the Jinsha and Yalong rivers. Proper planning and design of compensation reservoirs for the water-exporting area and stretch downstream of the water-exporting area can increase the hydrological compensation possibility from water-exporting area to the water-importing area, and reduce the impact on the stretch of river downstream of the water-exporting area.

HEC-HMS model for runoff simulation in a tropical catchment with intra-basin diversions – case study of the Deduru Oya river basin, Sri Lanka

Hydrological modeling is a commonly used tool by water resource planners to simulate the hydrological response in a basin due to precipitation for the purpose of management of basin water. With the increasing demand for limited water resources in every basin, careful management of water resources becomes more important. The Deduru Oya river in Sri Lanka supplies water to number of new and ancient irrigation systems and the management of water resources in the Deduru Oya river basin, which has an area of 2620 km2, is important for optimum utilization of water for these irrigation systems. This paper describes a case study of continuous rainfall-runoff modeling in part of the Deduru Oya basin with intra-basin diversions and storage irrigation systems using the Hydrologic Engineering Center – Hydrologic Modeling System (HEC–HMS) version 3.0.1 to estimate runoff in the Deduru Oya river. Long term daily rainfall data at several rain gauging stations, evaporation, land use and soil data in the river basin, daily river runoff at a stream gauging station, intra-basin diversions from the river into a storage reservoir, irrigation releases from the reservoir and drainage flow returned to the river from irrigation systems were used to set up the HEC-HMS model. Five-layer soil moisture accounting loss method, Clark unit hydrograph transformation method, and recession base flow method of the HEC-HMS model were used. Temporally varying irrigation water uses, storages and losses in the basin were taken into account in the analysis. The results depict the capability of HEC–HMS to reproduce stream flows in the basin to a high accuracy with averaged computed Nash Sutcliffe efficiencies of 0.80. The study demonstrates potential HEC–HMS application in flow estimation from tropical catchments with intra-basin diversions and irrigation storages. The model developed is a tool for water management in the Deduru Oya river basin. ENGINEER, Vol. 48, No.01, pp. 1-9, 2015

Testing different cross-section spacing in 1D hydraulic modelling: a case study on Johor River, Malaysia

Cross-section data are essential to describe the topography of rivers and floodplain areas and support flood propagation and inundation modelling. To date, there are only a few guidelines available to assist hydraulic modellers in determining the required quantity and location of cross-sections. The aim of this paper is to investigate the impact of cross-section spacing on the results of hydraulic models. To this end, four hydraulic models were built using the HEC-RAS model code and four different numbers of cross-sections. The geometric data were extracted from a high-resolution digital elevation model (LiDAR DEM) of a 30-km reach of the Johor River in Malaysia. These hydraulic models were then compared using flood water levels recorded at two stream gauging stations during two recent flood events. The independent calibration and validation of the models allowed the evaluation of a set of equations proposed in the literature for determining the distance between cross-sections for hydraulic modelling.Editor D. Koutsoyiannis; Associate editor I. Nalbantis

Trends in Mean Annual Streamflows in Serra da Mantiqueira Environmental Protection Area

The aim of this study was to detect trends in the mean annual streamflow in watersheds of Serra da Mantiqueira Environmental Protection Area, an important Brazilian conservation area located between Minas Gerais, São Paulo and Rio de Janeiro States. Historical series of four selected streamgage stations were analyzed for the periods of 1980-1998 and 1980-2009, using the Mann-Kendall and Regional Mann-Kendall tests. The results showed that the mean annual streamflows of Serra da Mantiqueira Environmental Protection Area watersheds did not change during the complete period of 1980-2009. The tests detected statistically significant trends of reduction of mean annual streamflow during the 1980-1998 period. The confrontation of this result with the inexistence of rainfall trends during the same period suggested that the streamflow changes detected were consequences of changes in the watersheds physical characteristics, and/or increases in water abstraction for multiple uses.

Effect of land use change on water discharge in Srepok watershed, Central Highland, Viet Nam

Srepok watershed plays an important role in Central Highland in Viet Nam. It impacts to developing social-economic conditions. Therefore, it is necessary to research elements which impact to natural resources in this watershed. The Soil and Water Assessment Tool (SWAT) model and Geography Information System (GIS) were used to simulate water discharge in the Srepok watershed. The objectives of the research were to apply GIS and SWAT model for simulation water discharge and then, we assessed land use change which impacted on water discharge in the watershed. The observed stream flow data from Ban Don Stream gauge station was used to calibrate for the period from 1981 to 2000 and then validate for the period from 2001 to 2009. After using SWAT-CUP software to calibration, NSI reached 0.63 and R square value achieved 0.64 from 2004 to 2008 in calibration and NSI gained good level at 0.74 and R square got 0.75 from 2009 to 2012 in validation step at Ban Don Station. After that, land cover in 2010 was processed like land cover in 2000 and set up SWAT model again. The simulated water discharge in scenario 1 (land use 2000) was compared with scenario 2 (land use 2010), the simulation result was not significant difference between two scenarios because the change of area of land use was not much enough to affect the fluctuation of water discharge. However, the effect of land cover on water resource could be seen clearly via total water yield. The percentage of surface flow in 2000 was twice times more than in 2010; retard and base flow in 2000 was slightly more than in 2010. Therefore, decreased surface flow, increased infiltration capacity of water and enriched base flow resulted in the growth of land cover.

다목적 최적화 기법을 이용한 수위관측망 평가

본 연구에서는 남강댐 유역을 대상으로 수위관측소의 수문정보량과 설치목적별 중요도를 고려하여 수위관측망을 평가하였다. 엔트로피 이론을 적용하여 산정된 수문정보량과 설치목적별 중요도를 동시에 고려하기 위해 유클리디언 거리를 이용하여 2개의 목적함수를 통합하였으며, 이를 다목적 최적화 기법을 이용하여 최적관측망을 선정하였다. 최적 수위관측망을 구축하기 위해 대표단위도를 실제 강우-유출 해석을 결과를 바탕으로 유도한 후 확률밀도함수로의 전이를 통해 엔트로피 이론에 적용하였다. 아울러 설치목적별 중요도는 MLIT(2010)에서 조사한 수위관측소별 설치목적을 참조하여 등급을 정량화 하였다. 이를 남강댐에 유역에 적용한 결과 다목적 최적화 기법을 이용하여 수위관측망을 평가한 경우가 엔트로피 이론만을 적용했을 때보다 관측소의 설치목적을 보다 잘 만족함을 확인하였다. 이는 수위관측소의 설치목적별 중요도와 자료의 특성이 동시에 반영된 결과이다. 아울러 대상유역인 남강댐 유역에서는 총 12개의 수위관측소 중 8개의 수위관측소가 필요한 것으로 판단된다. This study has evaluated the stream gauge network which is considered the total hydrological information and the importance class of stream gauge stations, and is applied to Namgang Dam basin. The total hydrological information and the importance class of stream gauge stations are two different physical parameters. We adopt the Euclidean distance method to consider them simultaneously. An equation obtained by the Euclidean distance method is used as the objective function in multiobjective optimization method to determine the optimal combination of the stream gauge stations for satisfying the both criteria: the maximum total amount of the hydrological information and the importance class of stream gauge stations. To evaluate the optimal stream gauge network, the representative unit hydrograph which is derived by real rainfall-runoff analysis is transferred into probability density function for the application of entropy theory concept. The importance class of stream gauge stations is determined by referring the result of MLIT (2010). As result of applying to Namgang Dam basin, The optimal stream gauge network obtained by the suggested method shows more satisfied the importance of stream gauge station purpose than the optimal stream gauge network obtain by the entropy theory only. This result implies that the optimal steam gauge network by the suggested method can consider both the total hydrological information and the importance class of stream gauge station. It is found that Namgang Dam basin needs at least 8 steam gauge stations among 12 steam gauge stations.

Climate change sensitivity index for Pacific salmon habitat in southeast Alaska.

Global climate change may become one of the most pressing challenges to Pacific Salmon conservation and management for southeast Alaska in the 21st Century. Predicted hydrologic change associated with climate change will likely challenge the ability of specific stocks to adapt to new flow regimes and resulting shifts in spawning and rearing habitats. Current research suggests egg-to-fry survival may be one of the most important freshwater limiting factors in Pacific Salmon's northern range due to more frequent flooding events predicted to scour eggs from mobile spawning substrates. A watershed-scale hydroclimatic sensitivity index was developed to map this hypothesis with an historical stream gauge station dataset and monthly multiple regression-based discharge models. The relative change from present to future watershed conditions predicted for the spawning and incubation period (September to March) was quantified using an ensemble global climate model average (ECHAM5, HadCM3, and CGCM3.1) and three global greenhouse gas emission scenarios (B1, A1B, and A2) projected to the year 2080. The models showed the region's diverse physiography and climatology resulted in a relatively predictable pattern of change: northern mainland and steeper, snow-fed mountainous watersheds exhibited the greatest increases in discharge, an earlier spring melt, and a transition into rain-fed hydrologic patterns. Predicted streamflow increases for all watersheds ranged from approximately 1-fold to 3-fold for the spawning and incubation period, with increased peak flows in the spring and fall. The hydroclimatic sensitivity index was then combined with an index of currently mapped salmon habitat and species diversity to develop a research and conservation priority matrix, highlighting potentially vulnerable to resilient high-value watersheds. The resulting matrix and observed trends are put forth as a framework to prioritize long-term monitoring plans, mitigation experiments, and finer-scale climate impact and adaptation studies.

Exploring the Potential of SRTM Topography and Radar Altimetry to Support Flood Propagation Modeling: Danube Case Study

Flood inundation modeling is one of the essential steps in flood hazard mapping. However, the desirable input and calibration data for model building and evaluation are not sufficient or unavailable in many rivers and floodplains of the world. A potential opportunity to fill this gap is offered nowadays by global earth observation data, which can be obtained freely (or at low cost), such as the shuttle radar topography mission (SRTM) and radar altimetry. However, the actual usefulness of these data is still poorly investigated. This study attempts to assess the value of SRTM topography and radar altimetry in supporting flood-level predictions in data-poor areas. To this end, a hydraulic model of a 150-km reach of the Danube River was built by using SRTM topography as input data and radar altimetry of the 2006 flood event as calibration data. The model was then used to simulate the 2007 flood event and evaluated against water levels measured in four stream gauge stations. Model evaluation allows the investigation of the usefulness and limitations of SRTM topography and radar altimetry in supporting hydraulic modeling of floods.

Climate change impacts on snowmelt runoff for mountainous transboundary basins in eastern Turkey

ABSTRACTThis study investigates whether snowmelt runoff for the selected 15 streamflow stations located in the Euphrates, Tigris, Aras, and Çoruh basins in eastern Anatolia, Turkey, has shown a consistent hydrologic response to global climatic changes over the past several decades. It also investigates the future runoff changes in these basins. The analysis utilizes streamflow and meteorological data from 1970 to 2010 available within the study area to identify spatial and temporal patterns of trends in the seasonality of streamflow, temperature, and precipitation. Results indicate significant temperature increases (average 1.3 °C across the stations) over the time period. They also indicate increases in annual precipitation (average 7.5% across the stations) but the increases are not significant, in general. The streamflow timings in the mountainous basins are found to have already shifted to earlier days in the year (9 days on average), and this is a clear indication of earlier spring melting of snowpack due to increasing temperatures in recent years. Eight among fifteen stream gauging stations in the basins show significant time shifts in snowmelt runoff according to statistical trend tests (based on 90% confidence level). A regional climate change simulation based on a high emissions scenario suggests 10–30% declines in the annual surface runoffs of Aras, Euphrates, and Tigris basins and a slight increase (about 4%) in the annual surface runoff of Coruh basin by the end of the present century. It further indicates that the timing of the peak flows will continue to shift earlier (by about 4 weeks over the century) in response to further warming, increasing the fraction of winter runoff while decreasing the fraction of spring runoff in the year in all these basins.

재해위험지구의 홍수위험도 저감을 위한 최적 수위관측망 구성 방안

상 하류로 연결되어 있는 수위관측소의 자료는 수문학적으로 유사하다. 또한 이는 재해관리를 위하여 상당히 중요한 수문자료이다. 본 연구에서는 재해위험지구의 홍수위험도 저감을 위하여 기존 수위관측망에 더하여 수위관측소를 추가로 설치할 경우 이를 위한 최적 수위관측망을 구성하고자 하였으며 금강상류 유역을 대상으로 평가하였다. Clark 방법에 의한 수위관측소별 대표 단위도를 산정하고 대수정규분포를 기반으로 엔트로피 이론에 의한 정보전달량을 추정하였다. 그리고 관측망에 대한 3개의 시나리오에 대하여 유역내 최대 정보전달량을 나타내는 최적의 수위관측망을 도출하였다. 또한 상호정보이론에 의한 수여 정보량을 산정하여 각 재해위험지구 및 대상유역에서 재해관리를 위하여 가장 중요하게 고려될 수 있는 수위관측소를 선정하였다. The data of stream gauging stations connected to the upper and lower stream have similar hydrological characteristics. It is also very important data for disaster management. In this study, we suggest a methodology which is used to build an optimal stream gauge network for mitigating the flood risk of a disaster risk area by adding new stream gauges at disaster risk areas to the existing stream gauge network. The upper stream basin of Geum river was selected as a study area. Representative unit hydrograph was estimated by Clark method in each station. And the information transmission by entropy analysis were evaluated based on the log-normal distribution. The optimized stream gauging networks about three scenarios of the gauging stations were determined using the entropy theory. Finally the most important gauging station was selected using the received information transmission in each disaster risk area and the whole basin.