Ungauged Stations Research Articles

Estimating the Ungauged Natural Flow Regimes for Environmental Flow Management

Regime-based approach recently becomes an important strategy while considering aquatic ecosystems in environmental flow management. The key element for supporting this strategy is long streamflow data which is usually not available for determining natural flow regimes. This study uses a back-propagation network to estimate ungauged natural flow regimes. A set of the upper reaches of Taiwan’s 42 flow stations with non-human control streamflow and at least 20 years daily flow data is used to quantify the natural flow regimes using 31 Indicators of Hydrologic Alteration (IHA). Watershed geomorphologic characteristic factors and rainfall parameters are used to classify homogeneous flow regime areas. The results show that there are three types of flow regimes from the flow stations, and each group of indicators in the IHA has different correlations with different geomorphologic characteristic factors and rainfall parameters. The results of using an artificial neural network model to estimate IHA show that the group average percent error fell from 21 % to 8 % and the average correlation coefficient was over 0.7, indicating that the model presented in this study is able to accurately estimate the natural flow regime in ungauged stations. Instead of predicting daily streamflow, this study estimates indicator values for ease of ecological water resources management.

On evaluating the robustness of spatial-proximity-based regionalization methods

Summary In absence of streamflow data to calibrate a hydrological model, its parameters are to be inferred by a regionalization method. In this technical note, we discuss a specific class of regionalization methods, those based on spatial proximity, which transfers hydrological information (typically calibrated parameter sets) from neighbor gauged stations to the target ungauged station. The efficiency of any spatial-proximity-based regionalization method will depend on the density of the available streamgauging network, and the purpose of this note is to discuss how to assess the robustness of the regionalization method (i.e., its resilience to an increasingly sparse hydrometric network). We compare two options: (i) the random hydrometrical reduction (HRand) method, which consists in sub-sampling the existing gauging network around the target ungauged station, and (ii) the hydrometrical desert method (HDes), which consists in ignoring the closest gauged stations. Our tests suggest that the HDes method should be preferred, because it provides a more realistic view on regionalization performance.

Simulation and Regionalization of Daily Global Solar Radiation: A Case Study in Quebec, Canada

Global solar radiation (GSR) is essential for agricultural and plant growth modelling, air and water heating analyses, and solar electric power systems. However, GSR gauging stations are scarce compared with stations for monitoring common meteorological variables such as air temperature and relative humidity. In this study, one power function, three linear regression, and three non-linear models based on an artificial neural network (ANN) are developed to extend short records of daily GSR for meteorological stations where predictors (i.e., temperature and/or relative humidity) are available. The seven models are then applied to 19 meteorological stations located across the province of Quebec (Canada). On average, the root-mean-square errors (RMSEs) for ANN-based models are 0.33–0.54 MJ m−2 d−1 smaller than those for the power function and linear regression models for the same input variables, indicating that the non-linear ANN-based models are more efficient in simulating daily GSR. Regionalization potential of the seven models is also evaluated for ungauged stations where predictors are available. The power function and the three linear regression models are tested by interpolating spatially correlated at-site coefficients using universal kriging or by applying a leave-one-out calibration procedure for spatially uncorrelated at-site coefficients. Regional ANN-based models are also developed by training the model based on the leave-one-out procedure. The RMSEs for regional ANN models are 0.08–0.46 MJ m−2 d−1 smaller than for other models using the same input conditions. However, the regional ANN-based models are more sensitive to new station input values compared with the other models. Maps of interpolated coefficients and regional equations of the power function and the linear regression models are provided for direct application to the study area.

Application of Parametric-Based Framework for Regionalisation of Flow Duration Curves

It is common knowledge that the end user of stream flow data may necessarily not have any prior knowledge of the quality control measures applied in their generation, therefore, conclusions drawn most often times may not be effective as desired. Thus, this study is an attempt at providing an independent quality construct to boost the confidence in the use of stream flow data by developing regional flow duration curves for selected ungauged stations of the upper Niger River Basin, Nigeria. Toward this end, stream flow data for seven gauging stations cover some sub basins in the Basin were obtained; precisely, monthly stream flow data covering a range of eleven to fifty-three years period. The flow duration curves from the gauging stations were fitted with three probability distribution models; i.e., logarithmic, power and exponential regression models. For the regionalisation, parameterisation was carried out in terms of the drainage area alone to allow for simplicity of models. Results obtained showed that the exponential regression model, in terms of Coefficient of Determination (R2) had the best fit. Though the regionalised model was simple, measurable agreement was obtained during the calibration and validation phases. However, considering the length of data used and probable variability in the stream flow regime, it is not possible to objectively generalise on the quality of the results. Against this backdrop, it suffices to take into cognisance the need to use an ensemble of catchment characteristics in the development of the flow duration curves and the overall regional models; this is important considering the implications of anthropogenic activities and hydro-climatic variations.

Estimating water availability across the Upper Salween and Mekong river basins

Abstract. According to Liu et al. (2014), borrowing, substituting and generating (BSG) are the main methods people used to acquire the discharge at ungauged stations. Two of the substitution (modelling and disaggregation) methods in combination with the borrowing idea are compared for simulating discharge for the Upper Salween and Mekong River Basin (USMRB). It is seen that with a simple borrowing/ disaggregating method, the Nash-Sutcliffe Efficiency (NSE) can reach 0.82. The similarity in the seasonal variation pattern is a more important requirement to identify if the two stations are to be considered as having hydrological similarity. From the experience obtained for the USMRB, an upstream station with shorter geographical distance may be more in hydrological similarity than a station in the far downstream. The NSE is quite low when borrowing occurs within the low altitude downstream region. The efficiency will be decreased when we borrow information from several stations which may be not in hydrological similarity.

Simulation of Sediment Yield Over Un-gauged Stations Using MUSLE and Fuzzy Model

Land and water are two most vital natural resources of the world and hence these resources must be conserved carefully to protect environment to maintain ecological balance. Estimation of runoff and sediment yield is one of the prerequisites for conservation and management of water resources and also for many hydrological applications. The present study has been taken up to predict runoff and sediment yield for a reservoir basin viz. Megadrigedda Reservoir situated in Visakhapatnam District, Andhra Pradesh, India which is having a drainage area of 363 Sq.km. Modified Universal Soil Loss Equation (MUSLE) has been used to estimate the sediment yield. The runoff factors of MUSLE were computed by the measured values of runoff and peak rate of runoff at outlet of the reservoir. Topographic factor (LS) and crop management factor(C) were determined using geographic information system (GIS) and field-based survey of land use/land cover. The conservation practice factor (P) is obtained from the literature. Sediment yield at the outlet of the study reservoir has been simulated for fifteen storm events spread over the period of 2010-2013 and is validated with that of measured values. The resulted coefficient of determination value has been obtained as 0.84 for the study area which indicates that MUSLE model is working satisfactory for the selected basin. Fuzzy logic based model has also been developed to estimate sediment yield. The resulted correlation obtained between Fuzzy logic model and MUSLE model is 0.97 and with that of measured value it is 0.937.

A simplified storm index method to extrapolate intensity–duration–frequency (IDF) curves for ungauged stations in central Chile

AbstractMost of meteorological stations in Chile register rainfall amounts once every 24 h. The creation of intensity–duration–frequency (IDF) curves requires continuous recorded data, and this insufficiency of proper instrumentation has resulted in a lack of IDF curves nationwide. The objective of this study is to further develop and evaluate the feasibility of a new method to estimate IDF curves in ungauged stations under Mediterranean climates of central Chile. A technique used to address this problem is the use of a storm index (SI), also known as the ‘K’ method, which allows the construction of IDF curves from stations with discontinuous data, by extrapolating data from stations with continuous records, as long as daily rainfall intensities for both stations differ by less than 2 mm h−1. To test the applicability of this method, SI values were calculated for 40 meteorological stations located throughout Central Chile (latitudes 30°S to 40°S). The extrapolated IDF curves were then compared with observed data, and the goodness of fit was determined. The results indicate that the storm index method can adequately estimate hourly IDF curve values for stations lacking of continuous rainfall data. Copyright © 2014 John Wiley & Sons, Ltd.

Study on Characteristics of Sediment and Sedimentation Rate at Sungai Lembing, Kuantan, Pahang

River is important in human life. River is very useful and has various functions in human life such as for domestics, economics, connection for one place to others place and many more. The main function of the river is to flow the water to the water storage or sea. River also brings the sediment from upstream or from erosion process. Sediments may affect the characteristics and the rate of the river. The study of sedimentation rate is quite important for development our country. It also can avoid the problem which related to our human society such as flood and water quality. As example, the depth of river become shallow if the sedimentation occurred. It also will make the quantity of aquatic life will reduced. This study was carried out to determine the sedimentation rate for five locations in the study area at Sungai Lembing, Kuantan, using Duboys and Schoklitsch equation. The highest sedimentation rate using Duboys is 2.06 lb-sec/ft was obtained at Station 3 and the lowest sedimentation rate is 0.073 lb-sec/ft also at Station 3 but in different day. Meanwhile, by using Schoklitsch equation, the highest rate is 1.12 lb-sec/ft at Station 1 and the lowest rate at Station 5 with 0.263 lb-sec/ft. The results for Duboys indicated that the rate is related to the mean size of sediment and the cross section of the river. By using Schoklitsch, the results depend on the flow rate of the river. If the flow rate higher, the sediment rate will also increase. The sediment sample sieving test results was classified using U. S. Army Corps of Engineer (USACE). The major size at Sungai Lembing for every station is in range between 2 mm-0.5 mm (Medium sand) and the minor size of sediment for the five ungauged station is 0.25 mm- 0.0625 mm (very fine sand).

Prediction of Flow Duration Curves for Ungauged Basins with Quasi-Newton Method

Prediction of flow-duration-curves (FDC) is an important task for water resources planning, management and hydraulic energy production. Classification of the basins as carstic and non-carstic may be used to estimate parameters of the FDC with predictive tools for catchments with/without observed stream flow. There is a need for obtaining FDC for ungauged stations for efficient water resource planning. Thus, study proposes a quite new approach, called the EREFDC model, for estimating the parameters of the FDC for which the parameters of the FDC are obtained with quasi-Newton method. Estimation are made for using the bv gauged stations at first than the FDC parameters are estimated for ungauged stations based on drainage area, annual mean precipitation, mean permeability, mean slope, latitude, longitude, and elevation from the mean sea level are used. The EREFDC model consists of various type of linear- and nonlinear mathematical equations, is able to predict a wide range of the FDC parameters for gauged and ungauged basins. The method is applied to 72 unimpaired catchments studied are about for 50 years average daily measured stream flow. Results showed that the EREFDC model may be used for estimating. FDC parameters for ungauged hydrological basins in order to find FDC for ungauged stations. Results also showed that the EREFDC model performs better in carstic regions than non-carstic regions. In addition, parameters of FDC for tributaries at the basins with insufficient flow data or without flow data may be determined by using basin characteristics.

미계측 관측 강수 자료 생성을 통한 제주도 지역의 수문총량 추정

본 연구에서는 미계측 강수자료를 생성하여 공간 해석함으로써 제주도의 정확한 수문총량을 산정하였다. 미계측 강수자료는 본 연구에서 제시된 수정된 다중회귀선형 모형으로 생성하였으며 공간강수량은 PRISM을 적용하여 구하였다. 수정된 다중선형회귀 모형에 의한 미계측 강수자료의 추정 값들은 기존의 강수 패턴과 유사한 양상을 나타내어 모형의 정확도가 우수한 것으로 나타났으며, 공간강수량의 해석결과는 Case 1(원자료)과 Case 2(미계측 강수자료를 보완한 자료)의 연평균 강수량이 약 1.5%의 미미한 차이를나타내었으나 고도별 연평균 강수량 차이는 최대 37.4%가 증가하는 것으로 산정되었다. 따라서 본 연구에서 제안한 미계측 관측 자료 생성방법은 현재 관측소의 밀도가 낮은 곳과 국지적으로 강수량의 변화가 큰 곳에서의 수문총량의 산정시 유용할 것으로 판단된다. In this study, the total precipitation amount in Jeju Island was estimated with the simulated precipitation for ungauged stations missing precipitation data using the spatial precipitation analysis. The missing data were generated through the modified multiple linear regression in this study, and the analysis of spatial precipitation was conducted with the PRISM(Parameter-elevation Regression on Independent Slope Model). The generated data with modified multiple linear regression model have similar pattern with original data. Thus, the model in this study shows good applicability to estimate the missing data. The difference of annual average precipitation between Case 1 (original data) and Case 2 (modified data) appears very small ratio which is about 1.5%. However, the difference of annual average precipitation according to elevation shows the large ratio up to 37.4%. As the results, the method of estimating missing data in this study would be useful to calculate the total precipitation amount at the low station density area and the places with the high spatial variation of precipitation.

Reverse flow routing in open channels: A Bayesian Geostatistical Approach

Summary Reverse flow routing in open channels is a procedure of practical interest: it allows to obtain hydrographs in upstream ungauged stations by means of information available at downstream monitored sites. In this paper a Bayesian Geostatistical Approach for reverse flow routing in open channels is presented. The capabilities of the methodology are shown by means of synthetic test cases. Input hydrographs of different shape were routed downstream using a numerical flow model that solves the one dimensional De Saint Venant equations; the resulting outflow hydrographs were, in almost all the cases, corrupted with random errors and then used for the inversion. Both prismatic and non-prismatic irregular channels, under subcritical flow conditions, were analyzed as well. The considered non-prismatic channel with irregular cross sections and variable friction coefficients represents a very practical situation that can be encountered in the field. The results show that the proposed methodology is able to properly reproduce the input inflows even in presence of errors affecting the downstream discharges up to 10%.

Regional flood frequency analysis using residual kriging in physiographical space

AbstractIn this article, an approach using residual kriging (RK) in physiographical space is proposed for regional flood frequency analysis. The physiographical space is constructed using physiographical/climatic characteristics of gauging basins by means of canonical correlation analysis (CCA). This approach is a modified version of the original method, based on ordinary kriging (OK). It is intended to handle effectively any possible spatial trends within the hydrological variables over the physiographical space. In this approach, the trend is first quantified and removed from the hydrological variable by a quadratic spatial regression. OK is therefore applied to the regression residual values. The final estimated value of a specific quantile at an ungauged station is the sum of the spatial regression estimate and the kriged residual. To evaluate the performance of the proposed method, a cross‐validation procedure is applied. Results of the proposed method indicate that RK in CCA physiographical space leads to more efficient estimates of regional flood quantiles when compared to the original approach and to a straightforward regression‐based estimator. Copyright © 2010 John Wiley & Sons, Ltd.

Feasibility study of a geostatistical modelling of monthly maximum stream temperatures in a multivariate space

Healthy river conditions through optimal thermal regime controls water quality as well as the availability and distribution of fish habitat. A multivariate and geostatistical approach was developed to estimate maximum stream temperatures at a large basin scale. The methodology relies on the construction of a physiographical space using characteristics of gauging stations by testing two multivariate methods: principal components analysis (PCA) and canonical correlation analysis (CCA). Within the physiographical space, a geostatistical technique called ordinary kriging was then used to interpolate stream temperatures. Data from 12 temperature monitoring stations during July 1996 and July 1997 were used to estimate monthly maximum temperature. Results from the proposed approach were evaluated by comparing kriging performance obtained using both multivariate methods. Cross-validation technique has been performed on both approaches and satisfactory results were obtained. Kriging in the CCA physiographical space leads to better results because this approach seems more adapted to link physiographical information with specific water temperature. In addition, CCA requires less physiographical information than PCA (i.e. 10 metrics for PCA vs 8 metrics for CCA) to provide more satisfactory results (up to 15% decrease in RMSEr). In physiographical space, the gauging stations were found to cluster, potentially providing information to improve the accuracy of interpolation in that space. An example is provided to illustrate how to estimate one of the stream temperature properties at ungauged stations using the PCA algorithm. The relevance of the results regarding the quality of fish habitats of the Moisie river is discussed.

Predicting river width, depth and velocity at ungauged sites in England and Wales using multilevel models

AbstractUsing a dataset of gauged river discharges taken from sites in England and Wales, linear multilevel models (also known as mixed effects models) were applied to quantify the variability in discharge and the discharge‐hydraulic geometry relationships across three nested spatial scales. A jackknifing procedure was used to test the ability of the multilevel models to predict hydraulic geometry, and therefore width, mean depth and mean velocity, at ungauged stations. These models provide a framework for making predictions of hydraulic geometry parameters, with associated levels of uncertainty, using different levels of data availability. Results indicate that as one travels downstream along a river there is greater variability in hydraulic geometry than is the case between rivers of similar sizes. This indicates that hydraulic geometry (and therefore hydrology) is driven by catchment area, to a greater extent than by natural geomorphological variations in the streamwise direction at the mesoscale, but these geomorphological variations can still have a major impact on channel structure. Copyright © 2008 John Wiley & Sons, Ltd.

Characteristic scales, temporal variability modes and simulation of monthly Elbe River flow time series at ungauged locations

Spatial and temporal patterns of the long-range extreme monthly Elbe River flows across Germany are investigated, using various statistical methods, among others, principal component and wavelet analysis. Characteristic time scales are derived for various time series statistics. The wavelet analysis of the raw river discharge data as well as of the major principal component reveal the main oscillatory components and their temporal behavior, namely low frequency oscillations at interannual (6.9 yr) and interdecadal (13.9 yr) scales. The EOFs at ungauged stations are estimated from the principal components of the observed time series sampled over a limited time span whose length equals the major temporal variability scale (≈7 yr). The EOFs (empirical orthogonal functions) obtained in this way are subsequently used to simulate long-range flows at these locations. A comparison of this method with linear interpolation and ordinary kriging of the EOF shows the superiority of the former in representing the distributional properties of the observed time series. The simulated time series preserve also short and long-memory.

On evaluating design storm for a hilly catchment with inadequate raingauge network

Procedural steps involved in the estimation of design storm rainfall for a hilly catchment with inadequate raingauge network has been discussed and applied for evaluation of Standard Project Storm and Maximum Probable Storm for the Barak basin (upto Silchar), located in south Assam. Attempt has been made to correlate normal monsoon seasonal rainfall on the windward and lee sides to the elevation of the hills surrounding the catchment. Utilising these relationships normal seasonal rainfall for the ungauged stations situated inside the basin has been more number 0£ estimated and the normal seasonal isohyetal pattern evolved for the basin. Isopercental technique has been used for ears are studied assessing isohyetal pattern for the major flood. Producing rainstorms and their weighted rainfall depths obtained for tended to obtained the basin and maximised for the moisture charge.