Suitability of MUSLT for storm sediment yield prediction in Chehelgazi watershed,Iran

Abstract

The Chehelgazi watershed of Gheshlagh Dam in western Iran was selected to check the capability of the MUSLT (Theoretical Modified Universal Soil Loss Equation) model for estimating sediment yield during storms. The efficiency of MUSLT for sediment yield prediction was assessed using observed sediment data recorded for 11 storm events between October 2006 and April 2007. The results showed that MUSLT overestimated sediment yield with a high coefficient of determination (R² = 0.636 and p < 0.05), and it was then calibrated by examining regression models. The developed calibrated model (C-MUSLT) performed well, with a coefficient of determination of 0.739 (p < 0.05) and relative estimation and verification errors of 49.36 and 25.18%, respectively. The results of comparison between observed and estimated values, obtained by applying the calibrated model, confirmed that the difference was significant with a t value of 1.453 (p?=?0.05).

Citation Sadeghi, S.H.R., Gholami, L., and Khaledi Darvishan, A.V., 2013. Suitability of MUSLT for storm sediment yield prediction in Chehelgazi watershed, Iran. Hydrological Sciences Journal, 58 (4), 892–897.     

A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows

Abstract

A wavelet-neural network (WNN) hybrid modelling approach for monthly river flow estimation and prediction is developed. This approach integrates discrete wavelet multi-resolution decomposition and a back-propagation (BP) feed-forward multilayer perceptron (FFML) artificial neural network (ANN). The Levenberg-Marquardt (LM) algorithm and the Bayesian regularization (BR) algorithm were employed to perform the network modelling. Monthly flow data from three gauges in the Weihe River in China were used for network training and testing for 48-month-ahead prediction. The comparison of results of the WNN hybrid model with those of the single ANN model show that the former is able to significantly increase the prediction accuracy.

Editor D. Koutsoyiannis; Associate editor H. Aksoy

Citation Wei, S., Yang, H., Song, J.X., Abbaspour, K., and Xu, Z.X., 2013. A wavelet-neural network hybrid modelling approach for estimating and predicting river monthly flows. Hydrological Sciences Journal, 58 (2), 374–389.     

Identifying hydrograph parameters and their relationships to urbanization variables

Abstract

This study examines relationships between model parameters and urbanization variables for evaluating urbanization effects in a watershed. Rainfall–runoff simulation using the Nash model is the main basis of the study. Mean rainfall and excesses resulting from time-variant losses were completed using the kriging and nonlinear programming methods, respectively. Calibrated parameters of 47 events were related to urbanized variables, change of shape parameter responds more sensitively than that of scale parameter based on comparisons between annual average and optimal interval methods. Regression equations were used to obtain four continuous correlations for linking shape parameter with urbanization variables. Verification of 10 events demonstrates that shape parameter responds more strongly to imperviousness than to population, and a power relationship is suitable. Therefore, an imperviousness variable is a major reference for analysing urbanization changes to a watershed. This study found that time to peak of IUH was reduced from 11.76 to 3.97 h, whereas peak discharge increased from 44.79 to 74.92 m³/s.

Editor D. Koutsoyiannis; Associate editor S. Grimaldi

Citation Huang, S.-Y., Cheng, S.-J., Wen, J.-C. and Lee, J.-H., 2012. Identifying hydrograph parameters and their relationships to urbanization variables. Hydrological Sciences Journal, 57 (1), 144–161.     

Analysis of stream water quality and estimation of nutrient load with the aid of Quick Bird remote sensing imagery

Abstract

Human activities have created high nutrient surpluses in agricultural lands due to the increasing rate of chemical fertilizer application and the increase in livestock production. To analyse the nutrient characteristics and estimate the nutrient load in streams, we conducted extensive field survey and water quality experiments from 2007 to 2008 in Koise River, a major river of the Lake Kasumigaura watershed, Japan. Water quality indicators of total nitrogen (TN), total phosphorus (TP) and total organic carbon (TOC) were investigated. The nutrient loads of TN, TP and TOC, as well as dissolved total nitrogen, dissolved inorganic nitrogen, dissolved organic nitrogen, particle organic nitrogen, dissolved total phosphorus, dissolved organic carbon and particle organic carbon were also estimated for the Koise River. Seasonal variation of the nutrient concentration from 2007 to 2008 was analysed considering the river discharge variation and agricultural activities. The results showed that the irrigation water from Lake Kasumigaura has the potential ability to decrease the TN concentration and increase the TOC concentration in the Koise River. Significant correlation coefficients between nutrient load and river discharge were found. The monthly pollution loads from different sources were then evaluated based on land cover classification generated from high-resolution Quick Bird remote sensing imagery. This study presents a useful interpretation of water quality data sets with a view to obtaining better information about water quality for more effective management of water resources in river basins.

Editor Z.W. Kundzewicz

Citation He, B., Oki, K., Wang, Y., Oki, T., Yamashiki, Y., Takara, K., Miura, S., Imai, A., Komatsu, K. and Kawasaki, N., 2012. Analysis of stream water quality and estimation of nutrient load with the aid of Quick Bird remote sensing imagery. Hydrological Sciences Journal, 57 (5), 850–860.     

Prediction of hydrological drought durations based on Markov chains: case of the Canadian prairies

Abstract

Hydrological drought durations (lengths) in the Canadian prairies were modelled using the standardized hydrological index (SHI) sequences derived from the streamflow series at annual, monthly and weekly time scales. The rivers chosen for the study present high levels of persistence (as indicated by values exceeding 0.95 for lag-1 autocorrelation in weekly SHI sequences), because they encompass large catchment areas (2210–119 000 km²) and traverse, or originate in, lakes. For such rivers, Markov chain models were found to be simple and efficient tools for predicting the drought duration (year, month, or week) based on annual, monthly and weekly SHI sequences. The prediction of drought durations was accomplished at threshold levels corresponding to median flow (Q50) (drought probability, q?=?0.5) to Q95 (drought probability, q?=?0.05) exceedence levels in the SHI sequences. The first-order Markov chain or the random model was found to be acceptable for the prediction of annual drought lengths, based on the Hazen plotting position formula for exceedence probability, because of the small sample size of annual streamflows. On monthly and weekly time scales, the second-order Markov chain model was found to be satisfactory using the Weibull plotting position formula for exceedence probability. The crucial element in modelling drought lengths is the reliable estimation of parameters (conditional probabilities) of the first- and second-order persistence, which were estimated using the notions implicit in the discrete autoregressive moving average class of models. The variance of drought durations is of particular significance, because it plays a crucial role in the accurate estimation of persistence parameters. Although, the counting method of the estimation of persistence parameters was found to be unsatisfactory, it proved useful in setting the initial values and also in subsequent adjustment of the variance-based estimates of persistence parameters. At low threshold levels corresponding to q < 0.20, even the first-order Markov chain can be construed as a satisfactory model for predicting drought durations based on monthly and weekly SHI sequences.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Sharma, T.C. and Panu, U.S., 2012. Prediction of hydrological drought durations based on Markov chains in the Canadian prairies. Hydrological Sciences Journal, 57 (4), 705–722.     

Input data measurement-induced uncertainty in watershed modelling

Abstract

This study presents a new methodology for estimation of input data measurement-induced uncertainty in simulated dissolved oxygen (DO) and nitrate-nitrogen (NO₃-N) concentrations using the Hydrological Simulation Program–FORTRAN (HSPF) model and data from the Amite River, USA. Simulation results show that: (1) a multiplying factor of 1.3 can be used to describe the maximum error in temperature measurements; similarly, a multiplying factor of 1.9 was estimated to accommodate the maximum of ±5% error in rainfall measurements; (2) the uncertainty in simulated DO concentration due to positive temperature measurement errors can be described with a normal distribution, N(0.062, 0.567); (3) the uncertainty in simulated NO₃-N concentration due to rainfall measurement errors follows a generalized extreme value distribution; and (4) the probability density functions can be utilized to determine the measurement-induced uncertainty in simulated DO and NO₃-N concentrations according to the risk level acceptable in water quality management.

Editor D. Koutsoyiannis

Citation Patil, A. and Deng, Z.-Q., 2012. Input data measurement-induced uncertainty in watershed modelling. Hydrological Sciences Journal, 57 (1), 118–133.     

Effects of urbanization variables on model parameters for watershed divisions

Abstract

A semi-distributed model with a parallel connection was applied to examine the effects of urbanization variables. Data were obtained from watershed divisions that were characterized by various degrees of urbanization. The mean rainfall was calculated using the kriging method. The model inputs were obtained by subtracting mean rainfall from Ф-index values, based on the spatially uniform loss assumption. Regression analysis was applied to determine the relationship between the parameters of 64 calibrations and urbanization variables among the divisions. The results showed that overland parameters produced more consistent change in response to imperviousness than to population. Conversely, the channel parameter was unaffected by changes in urbanization. The verification results of 46 cases showed that power linkage was a potential option for linking division parameters with the corresponding imperviousness based on four evaluation criteria. The changes in imperviousness on overland parameters show the hydrological effects of division urbanizations.

Editor D. Koutsoyiannis; Associate editor T. Wagener

Citation Chen, R., Chuang, W.-N., and Cheng, S., 2014. Effects of urbanization variables on model parameters for watershed divisions. Hydrological Sciences Journal, 59 (6), 1167–1183. http://dx.doi.org/10.1080/02626667.2014.910305     

Assessing the performance and uncertainty analysis of the SWAT and RBNN models for simulation of sediment yield in the Nagwa watershed,India

Abstract

The process-based Soil and Water Assessment Tool (SWAT) model and the data-driven radial basis neural network (RBNN) model were evaluated for simulating sediment load for the Nagwa watershed in Jharkhand, India, where soil erosion is a severe problem. The SWAT model calibration and uncertainty analysis were performed with the Sequential Uncertainty Fitting algorithm version 2 and the bootstrap technique was applied on the RBNN model to analyse uncertainty in model output. The percentage of data bracketed by the 95% prediction uncertainty (95PPU) and the r factor were the two measures used to assess the goodness of calibration. Comparison of the results of the two models shows that the value of r factor (r = 0.41) in the RBNN model is less than that of SWAT model (r = 0.79), which means there is a wider prediction interval for the SWAT model results. More values of observed sediment yield were bracketed by the 95PPU in the RBNN model. Thus, the RBNN model estimates the sediment yield values more accurately and with less uncertainty.

Editor D. Koutsoyiannis; Associate editor H. Aksoy

Citation Singh, A., Imtiyaz, M., Isaac, R.K., and Denis, D.M., 2014. Assessing the performance and uncertainty analysis of the SWAT and RBNN models for simulation of sediment yield in the Nagwa watershed, India. Hydrological Sciences Journal, 59 (2), 351–364.     

Improving kriging of groundwater level data using nonlinear normalizing transformations—a field application

Abstract

The present research study investigates the application of nonlinear normalizing data transformations in conjunction with ordinary kriging (OK) for the accurate prediction of groundwater level spatial variability in a sparsely-gauged basin. We investigate three established normalizing methods, Gaussian anamorphosis, trans-Gaussian kriging and the Box-Cox method to improve the estimation accuracy. The first two are applied for the first time to groundwater level data. All three methods improve the mean absolute prediction error compared to the application of OK to the non-transformed data. In addition, a modified Box-Cox transformation is proposed and applied to normalize the hydraulic heads. The modified Box-Cox transformation in conjunction with OK is found to be the optimal spatial model based on leave-one-out cross-validation. The recently established Spartan semivariogram family provides the optimal model fit to the transformed data. Finally, we present maps of the groundwater level and the kriging variance based on the optimal spatial model.

Editor D. Koutsoyiannis; Associate editor A. Montanari

Citation Varouchakis, E.A., Hristopoulos, D.T., and Karatzas, G.P., 2012. Improving kriging of groundwater level data using nonlinear normalizing transformations—a field application. Hydrological Sciences Journal, 57 (7), 1404–1419.     

Atmospheric,weathering and biological contributions in the chemical signature of stream water: the upper Iskar Reka watershed,Bulgaria

Abstract

The chemical signature of stream water is influenced by several factors: atmospheric input, weathering of bedrock and soils, biological uptake, soil storage, and decomposition of organic matter. The importance of weathering and biological activity, according to season, can be assessed by subtracting atmospheric input. In the upper Iskar Reka watershed, Bulgaria, results show that Na and Ca are mainly exported out of the basin (weathering is dominant), while nitrate and sulphate are consumed/stored. The behaviour of K suggests that biological activity is dominated by vegetation uptake in spring and by bacterial activity in autumn. In summer, the weathering load of Mg is compensated by reactions with clays. The low nutrient input from weathering due to low reserves in the soil may lead to a biomass production closely linked to a rapid internal cycle and also to a relative sensitivity of the ecosystem to any change in vegetation cover and atmospheric input.

Editor Z.W. Kundzewicz

Citation Gassama, N. and Violette, S., 2012. Atmospheric, weathering and biological contributions in the chemical signature of stream water: the Upper Iskar Reka watershed, Bulgaria. Hydrological Sciences Journal, 57 (3), 535–546.     

Rainfall–runoff simulation using a normalized antecedent precipitation index

Abstract

The normalized antecedent precipitation index (NAPI) model by Heggen for the prediction of runoff yield is analytically derived from the water balance equation. Heggen's model has been simplified further to a rational form and its performance verified with the Soil Conservation Service Curve Number (SCS-CN) model. The simplified model has three coefficients specific to a watershed, and requires two inputs: rainfall and the derived parameter, NAPI. The characteristic behaviour of the NAPI has resonance with the curve number (CN) of the SCS model. The proposed NAPI model was applied to three watersheds in the semi-arid region of India to simulate runoff yield. The model showed improved correlation between the observed and predicted runoff data compared to the SCS-CN model. The F test and paired t test also confirmed the reliability of the model with significance levels of 0.01 and 0.001%, respectively. The proposed model could be used successfully for rainfall–runoff modelling in a watershed.

Citation Ali, S., Ghosh, N. C. & Singh, R. (2010) Rainfall–runoff simulation using a normalized antecedent precipitation index. Hydrol. Sci. J. 55(2), 266–274.     

Estimation of the generalized logistic distribution of extreme events using partial L-moments

Abstract

Statistical analysis of extreme events is often carried out to predict large return period events. In this paper, the use of partial L-moments (PL-moments) for estimating hydrological extremes from censored data is compared to that of simple L-moments. Expressions of parameter estimation are derived to fit the generalized logistic (GLO) distribution based on the PL-moments approach. Monte Carlo analysis is used to examine the sampling properties of PL-moments in fitting the GLO distribution to both GLO and non-GLO samples. Finally, both PL-moments and L-moments are used to fit the GLO distribution to 37 annual maximum rainfall series of raingauge station Kampung Lui (3118102) in Selangor, Malaysia, and it is found that analysis of censored rainfall samples of PL-moments would improve the estimation of large return period events.

Editor D. Koutsoyiannis; Associate editor K. Hamed

Citation Zakaria, Z.A., Shabri, A. and Ahmad, U.N., 2012. Estimation of the generalized logistic distribution of extreme events using partial L-moments. Hydrological Sciences Journal, 57 (3), 424–432.     

Has urbanization changed ecological streamflow characteristics in Maine (USA)?

Abstract

This paper examines the potential effects of urbanization on streamflow in Maine, USA, from 1950 to 2000. The study contrasts nine watersheds in southern Maine, which has seen steady urban growth over the study period, with nine rural watersheds from northern Maine. Historical population data and current land cover data are used to develop an urbanization score for each watershed. Trends in watershed urbanization over the study period are compared to trends in ecologically relevant streamflow characteristics. The results indicate that trends in northern, rural watersheds are much more consistent than the trends in the southern watersheds. Additionally, trends in the southern watersheds are inconsistent with the hydrological characteristics observed in urban watersheds elsewhere, likely due to the comparatively low level of current urban development in Maine's urban watersheds. Our study suggests that urban areas in Maine have not yet reached an urbanization threshold where streamflow impacts become consistently detectable.

Editor Z.W. Kundzewicz

Citation Martin, E.H., Kelleher, C., and Wagener, T., 2012. Has urbanization changed ecological streamflow characteristics in Maine (USA)? Hydrological Sciences Journal, 57 (7), 1337–1354.     

Improvement of a drainage system for flood management with assessment of the potential effects of climate change

Abstract

Runoff discharge in the Tuku lowlands, Taiwan, has increased with land development. Frequent floods caused by extreme weather conditions have resulted in considerable economic and social losses in recent years. Currently, numerous infrastructures have been built in the lowland areas that are prone to inundation; the measures and solutions for flood mitigation focus mainly on engineering aspects. Public participation in the development of principles for future flood management has helped both stakeholders and engineers. An integrated drainage–inundation model, combining a drainage flow model with a two-dimensional overland-flow inundation model is used to evaluate the flood management approaches with damage loss estimation. The proposed approaches include increasing drainage capacity, using fishponds as retention ponds, constructing pumping stations, and building flood diversion culverts. To assess the effects on the drainage system of projected increase of rainfall due to climate change, for each approach simulations were performed to obtain potential inundation extent and depth in terms of damage losses. The results demonstrate the importance of assessing the impacts of climate change for implementing appropriate flood management approaches.

Editor Z.W. Kundzewicz

Citation Chang, H.-K., Tan, Y.-C., Lai, J.-S., Pan, T.-Y., Liu, T.-M., and Tung, C.-P., 2013. Improvement of a drainage system for flood management with assessment of the potential effects of climate change. Hydrological Sciences Journal, 58 (8), 1581–1597.     

The nature of rainfall in the main drainage sub-basins of Uganda

Abstract

A study of rainfall trends and temporal variations within seven sub-basins of Uganda spanning from 1940 to 2009 has been made. Rainfall climatologies are constructed from observational data, using 36 station records which reflect hydroclimatic conditions. Long-term changes in rainfall characteristics were determined by non-parametric tests (Mann-Kendall and Sen’s T tests), coefficient of variation (CV), precipitation concentration index and drought severity index. Magnitude of change was estimated by applying Sen’s estimator of slope. Decadal variability of rainfall with marked seasonal cycles is evident. Temporal variability of drought patterns is detected. Variations in annual rainfall are low with no significant trends observed in the main drainage sub-basins. Significant trends occur in October, November, December and January. A noticeable decrease in the annual total rainfall was observed mostly in northwestern and southwestern sub-basins. Rainfall trend in the second normal of June–July–August (JJA) was decreasing in all the main drainage sub-basins.

Editor Z.W. Kundzewicz; Associate editor S. Yue

Citation Nsubuga, F.W.N., Botai, O.J., Olwoch, J.M., Rautenbach, C.J.deW., Bevis, Y., and Adetunji, A.O., 2014. The nature of rainfall in the main drainage sub-basins of Uganda. Hydrological Sciences Journal, 59 (2), 278–299.     

Critical analysis of thermal inertia approaches for surface soil water content retrieval

Abstract

The “thermal inertia” method to retrieve surface soil water content maps on bare or sparsely-vegetated soils is analysed. The study area is a small experimental watershed, where optical and thermal images (in day and night time) and in situ data were simultaneously acquired. The sensitivity of thermal inertia to the phase difference between incoming radiation and soil temperature is demonstrated. Thus, to obtain an accurate value of the phase difference, the temporal distance between thermographs using a three-temperature approach is evaluated. We highlight when a cosine correction of the temperature needs to be applied, depending on whether the thermal inertia formulation includes two generic acquisition times, or not. Finally, the deviation in soil water content retrieval is quantifies for given values of each parameter by performing a sensitivity analysis on the basic parameters of the thermal inertia method that are usually affected by calibration errors.

Citation Maltese, A., Bates, P.D., Capodici, F., Cannarozzo, M., Ciraolo, G., and La Loggia, G., 2013. Critical analysis of thermal inertia approaches for surface soil water content retrieval. Hydrological Sciences Journal, 58 (5), 1144–1161.

Editor D. Koutsoyiannis; Associate editor D. Hughes     

Comparison between the peaks-over-threshold method and the annual maximum method for flood frequency analysis

Abstract

Flood frequency analysis can be made by using two types of flood peak series, i.e. the annual maximum (AM) and peaks-over-threshold (POT) series. This study presents a comparison of the results of both methods for data from the Litija 1 gauging station on the Sava River in Slovenia. Six commonly used distribution functions and three different parameter estimation techniques were considered in the AM analyses. The results showed a better performance for the method of L-moments (ML) when compared with the conventional moments and maximum likelihood estimation. The combination of the ML and the log-Pearson type 3 distribution gave the best results of all the considered AM cases. The POT method gave better results than the AM method. The binomial distribution did not offer any noticeable improvement over the Poisson distribution for modelling the annual number of exceedences above the threshold.

Editor D. Koutsoyiannis

Citation Bezak, N., Brilly, M., and ?raj, M., 2014. Comparison between the peaks-over-threshold method and the annual maximum method for flood frequency analysis. Hydrological Sciences Journal, 59 (5), 959–977.     

Modelling streamflow trends for a watershed with limited data: case of the Litani basin,Lebanon

Abstract

Streamflow variability in the Upper and Lower Litani basin, Lebanon was modelled as there is a lack of long-term measured runoff data. To simulate runoff and streamflow, daily rainfall was derived using a stochastic rainfall generation model and monthly rainfall data. Two distinct synthetic rainfall models were developed based on a two-part probabilistic distribution approach. The rainfall occurrence was described by a Markov chain process, while the rainfall distribution on wet days was represented by two different distributions (i.e. gamma and mixed exponential distributions). Both distributions yielded similar results. The rainfall data were then processed using water balance and routing models to generate daily and monthly streamflow. Compared with measured data, the model results were generally reasonable (mean errors ranging from 0.1 to 0.8?m³/s at select locations). Finally, the simulated monthly streamflow data were used to investigate discharge trends in the Litani basin during the 20th century using the Mann-Kendall and Sen slope nonparametric trend detection methods. A significant drying trend of the basin was detected, reaching a streamflow reduction of 0.8 and 0.7 m³/s per decade in January for the Upper and Lower basin, respectively.

Editor D. Koutsoyiannis; Associate editor Sheng Yue

Citation Ramadan, H.H., Beighley, R.E., and Ramamurthy, A.S., 2012. Modelling streamflow trends for a watershed with limited data: case of the Litani basin, Lebanon. Hydrological Sciences Journal, 57 (8), 1516–1529.     

Regional models of flow-duration curves of perennial and intermittent streams and their use for calibrating the parameters of a rainfall–runoff model

Abstract

One of the main challenges faced by hydrologists and water engineers is the estimation of variables needed for water resources planning and management in ungauged river basins. To this end, techniques for transposing information, such as hydrological regional analyses, are widely employed. A method is presented for regionalizing flow-duration curves (FDCs) in perennial, intermittent and ephemeral rivers, based on the extended Burr XII probability distribution. This distribution shows great flexibility to fit data, with accurate reproduction of flow extremes. The performance analysis showed that, in general, the regional models are able to synthesize FDCs in ungauged basins, with a few possible drawbacks in the application of the method to intermittent and ephemeral rivers. In addition to the regional models, we summarize the experience of using synthetic FDCs for the indirect calibration of the Rio Grande rainfall–runoff model parameters in ungauged basins.

Editor D. Koutsoyiannis

Citation Costa, V., Fernandes, W., and Naghettini, M., 2013. Regional models of flow-duration curves of perennial and intermittent streams and their use for calibrating the parameters of a rainfall–runoff model. Hydrological Sciences Journal, 59 (2), 262–277.     

Standardized uncertainty analysis for hydrometry: a review of relevant approaches and implementation examples

Abstract

The water-centric community has continuously made efforts to identify, assess and implement rigorous uncertainty analyses for routine hydrological measurements. This paper reviews some of the most relevant efforts and subsequently demonstrates that the Guide to the expression of uncertainty in measurement (GUM) is a good candidate for estimation of uncertainty intervals for hydrometry. The demonstration is made by implementing the GUM to typical hydrometric applications and comparing the analysis results with those obtained using the Monte Carlo method. The results show that hydrological measurements would benefit from the adoption of the GUM as the working standard, because of its soundness, the availability of software for practical implementation and potential for extending the GUM to hydrological/hydraulic numerical simulations.

Editor D. Koutsoyiannis

Citation Muste, M., Lee, K. and Bertrand-Krajewski, J.-L., 2012. Standardized uncertainty analysis for hydrometry: a review of relevant approaches and implementation examples. Hydrological Sciences Journal, 57 (4), 643–667.