Evaluation of Surface Runoff Generation Processes Using a Rainfall Simulator: A Small Scale Laboratory ExperimentPublished: 21 December 2017 by IOP Publishing in IOP Conference Series: Earth and Environmental Science
Nowadays, rainfall simulators are being used by many researchers in field or laboratory experiments. The main objective of most of these experiments is to better understand the underlying runoff generation processes, and to use the results in the process of calibration and validation of hydrological models. Many research groups have assembled their own rainfall simulators, which comply with their understanding of rainfall processes, and the requirements of their experiments. Most often, the existing rainfall simulators differ mainly in the size of the irrigated area, and the way they generate rain drops. They can be characterized by the accuracy, with which they produce a rainfall of a given intensity, the size of the irrigated area, and the rain drop generating mechanism. Rainfall simulation experiments can provide valuable information about the genesis of surface runoff, infiltration of water into soil and rainfall erodibility. Apart from the impact of physical properties of soil, its moisture and compaction on the generation of surface runoff and the amount of eroded particles, some studies also investigate the impact of vegetation cover of the whole area of interest. In this study, the rainfall simulator was used to simulate the impact of the slope gradient of the irrigated area on the amount of generated runoff and sediment yield. In order to eliminate the impact of external factors and to improve the reproducibility of the initial conditions, the experiments were conducted in laboratory conditions. The laboratory experiments were carried out using a commercial rainfall simulator, which was connected to an external peristaltic pump. The pump maintained a constant and adjustable inflow of water, which enabled to overcome the maximum volume of simulated precipitation of 2.3 l, given by the construction of the rainfall simulator, while maintaining constant characteristics of the simulated precipitation. In this study a 12-minute rainfall with a constant intensity of 5 mm/min was used to irrigate a corrupted soil sample. The experiment was undertaken for several different slopes, under the condition of no vegetation cover. The results of the rainfall simulation experiment complied with the expectations of a strong relationship between the slope gradient, and the amount of surface runoff generated. The experiments with higher slope gradients were characterised by larger volumes of surface runoff generated, and by shorter times after which it occurred. The experiments with rainfall simulators in both laboratory and field conditions play an important role in better understanding of runoff generation processes. The results of such small scale experiments could be used to estimate some of the parameters of complex hydrological models, which are used to model rainfall-runoff and erosion processes at catchment scale.
When designing the water management systems and their components, there is a need of more detail research on hydrological conditions of the river basin, runoff of which creates the main source of water in the reservoir. Over the lifetime of the water management systems the hydrological time series are never repeated in the same form which served as the input for the design of the system components. The design assumes the observed time series to be representative at the time of the system use. However, it is rather unrealistic assumption, because the hydrological past will not be exactly repeated over the design lifetime. When designing the water management systems, the specialists may occasionally face the insufficient or oversized capacity design, possibly wrong specification of the management rules which may lead to their non-optimal use. It is therefore necessary to establish a comprehensive approach to simulate the fluctuations in the interannual runoff (taking into account the current dry and wet periods) in the form of stochastic modelling techniques in water management practice. The paper deals with the methodological procedure of modelling the mean monthly flows using the stochastic Thomas-Fiering model, while modification of this model by Wilson-Hilferty transformation of independent random number has been applied. This transformation usually applies in the event of significant asymmetry in the observed time series. The methodological procedure was applied on the data acquired at the gauging station of Horné Orešany in the Parná Stream. Observed mean monthly flows for the period of 1.11.1980 - 31.10.2012 served as the model input information. After extrapolation the model parameters and Wilson-Hilferty transformation parameters the synthetic time series of mean monthly flows were simulated. Those have been compared with the observed hydrological time series using basic statistical characteristics (e. g. mean, standard deviation and skewness) for testing the quality of the model simulation. The synthetic hydrological series of monthly flows were created having the same statistical properties as the time series observed in the past. The compiled model was able to take into account the diversity of extreme hydrological situations in a form of synthetic series of mean monthly flows, while the occurrence of a set of flows was confirmed, which could and may occur in the future. The results of stochastic modelling in the form of synthetic time series of mean monthly flows, which takes into account the seasonal fluctuations of runoff within the year, could be applicable in engineering hydrology (e. g. for optimum use of the existing water management system that is related to reassessment of economic risks of the system).
An Application of a Stochastic Semi-Continuous Simulation Method for Flood Frequency Analysis: A Case Study in SlovakiaPublished: 01 September 2017 by Walter de Gruyter GmbH in Slovak Journal of Civil Engineering
A reliable estimate of extreme flood characteristics has always been an active topic in hydrological research. Over the decades a large number of approaches and their modifications have been proposed and used, with various methods utilizing continuous simulation of catchment runoff, being the subject of the most intensive research in the last decade. In this paper a new and promising stochastic semi-continuous method is used to estimate extreme discharges in two mountainous Slovak catchments of the rivers Váh and Hron, in which snow-melt processes need to be taken into account. The SCHADEX method used, couples a precipitation probabilistic model with a rainfall-runoff model used to both continuously simulate catchment hydrological conditions and to transform generated synthetic rainfall events into corresponding discharges. The stochastic nature of the method means that a wide range of synthetic rainfall events were simulated on various historical catchment conditions, taking into account not only the saturation of soil, but also the amount of snow accumulated in the catchment. The results showed that the SCHADEX extreme discharge estimates with return periods of up to 100 years were comparable to those estimated by statistical approaches. In addition, two reconstructed historical floods with corresponding return periods of 100 and 1000 years were compared to the SCHADEX estimates. The results confirmed the usability of the method for estimating design discharges with a recurrence interval of more than 100 years and its applicability in Slovak conditions.
Process-based selection of copula types for flood peak-volume relationships in Northwest Austria: a case studyPublished: 01 December 2016 by Walter de Gruyter GmbH in Contributions to Geophysics and Geodesy
The case study aims at selecting optimal bivariate copula models of the relationships between flood peaks and flood volumes from a regional perspective with a particular focus on flood generation processes. Besides the traditional approach that deals with the annual maxima of flood events, the current analysis also includes all independent flood events. The target region is located in the northwest of Austria; it consists of 69 small and mid-sized catchments. On the basis of the hourly runoff data from the period 1976- 2007, independent flood events were identified and assigned to one of the following three types of flood categories: synoptic floods, flash floods and snowmelt floods. Flood events in the given catchment are considered independent when they originate from different synoptic situations. Nine commonly-used copula types were fitted to the flood peak - flood volume pairs at each site. In this step, two databases were used: i) a process-based selection of all the independent flood events (three data samples at each catchment) and ii) the annual maxima of the flood peaks and the respective flood volumes regardless of the flood processes (one data sample per catchment). The goodness-of-fit of the nine copula types was examined on a regional basis throughout all the catchments. It was concluded that (1) the copula models for the flood processes are discernible locally; (2) the Clayton copula provides an unacceptable performance for all three processes as well as in the case of the annual maxima; (3) the rejection of the other copula types depends on the flood type and the sample size; (4) there are differences in the copulas with the best fits: for synoptic and flash floods, the best performance is associated with the extreme value copulas; for snowmelt floods, the Frank copula fits the best; while in the case of the annual maxima, no firm conclusion could be made due to the number of copulas with similarly acceptable overall performances. The general conclusion from this case study is that treating flood processes separately is beneficial; however, the usually available sample size in such real life studies is not sufficient to give generally valid recommendations for engineering design tasks.
The aim of this paper was to evaluate the possible impact of climate change on the runoff regime of the Hron River basin up to the Banská Bystrica profile until the year 2100. The daily rainfall-runoff model Hron which was developed at the Department of Land and Water Resources Management, SUT Bratislava, was used. The model was calibrated on a period between 1981-1995 and validated on 1996-2010 For the simulation of the possible impact of climate change, the KNMI and MPI climate change scenarios, which illustrate changes in daily precipitation, daily air temperature and the average air humidity in the river basin for future periods, were used. In conclusion the average monthly flows for the future time horizons of 2011-2040, 2041-2070 and 2071-2100 with a reference period (1981-2010) were compared. Based on the results of the two hydrological models and the two different climate change scenarios, we can expect an increase in long-term mean monthly discharges for the winter and spring periods and a decrease for the summer period.
In order to estimate possible changes in the flood regime in the mountainous regions of Slovakia, a simple physically-based concept for climate change-induced changes in extreme 5-day precipitation totals is proposed in the paper. It utilizes regionally downscaled scenarios of the long-term monthly means of the air temperature, specific air humidity and precipitation projected for Central Slovakia by two regional (RCM) and two global circulation models (GCM). A simplified physically-based model for the calculation of short-term precipitation totals over the course of changing air temperatures, which is used to drive a conceptual rainfall-runoff model, was proposed. In the paper a case study of this approach in the upper Hron river basin in Central Slovakia is presented. From the 1981–2010 period, 20 events of the basin’s most extreme average of 5-day precipitation totals were selected. Only events with continual precipitation during 5 days were considered. These 5-day precipitation totals were modified according to the RCM and GCM-based scenarios for the future time horizons of 2025, 2050 and 2075. For modelling runoff under changed 5-day precipitation totals, a conceptual rainfall-runoff model developed at the Slovak University of Technology was used. Changes in extreme mean daily discharges due to climate change were compared with the original flood events and discussed.
One of the tools which are currently being used in flood frequency analysis (FFA) is rainfall-runoff (RR) modelling. Its use in FFA often confronts the problem of how to correctly calibrate RR models to extreme flows. Since FFA only deals with extreme flows, traditional calibration techniques using simple objective functions such as the Nash-Sutcliffe model’s efficiency criterion are not sufficient. In this paper we have focused on proposing alternative approaches for calibration techniques of RR models in order to enhance the description of extreme flows. We have selected the HBV type conceptual, lumped model HRON as an RR model. We have suggested two alternative calibration approaches: 1) the use of a new optimization function that compares only values higher than the 95th percentile of observed flows and 2) using two sets of parameters to separately simulate low and high flows. Each of these improvements has enhanced the simulation of extreme flows, which has been demonstrated in the empirical cumulative distribution function calculated for the simulated and observed annual maximum series of flows. The results of this paper show that improvement can be obtained by both approaches, which give good agreement between observed and simulated extreme flows, while preserving a good simulation of low and medium flows
Assessment of The Uncertainties of a Conceptual Hydrologic Model By Using Artificially Generated FlowsPublished: 01 December 2012 by Walter de Gruyter GmbH in Slovak Journal of Civil Engineering
Most of the studies that assess the performance of various calibration techniques have to deal with a certain amount of uncertainty in the calibration data. In this study we tested HBV model calibration procedures in hypothetically ideal conditions under the assumption of no errors in the measured data. This was achieved by creating an artificial time series of the flows created by the HBV model using the parameters obtained from calibrating the measured flows. The artificial flows were then used to replace the original flows in the calibration data, which was then used for testing how calibration procedures can reproduce known model parameters. The results showed that in performing one hundred independent calibration runs of the HBV model, we did not manage to obtain parameters that were almost identical to those used to create the artificial flow data without a certain degree of uncertainty. Although the calibration procedure of the model works properly from a practical point of view, it can be regarded as a demonstration of the equifinality principle, since several parameter sets were obtained which led to equally acceptable or behavioural representations of the observed flows. The study demonstrated that this concept for assessing how uncertain hydrological predictions can be applied in the further development of a model or the choice of calibration method using artificially generated data.
Analysis of Nitrate Concentrations Using Nonlinear Time Series ModelsThis study examines two long-term time series of nitrate-nitrogen concentrations from the River Ouse and Stour situated in the Eastern England. The time series of monthly averages were decomposed into trend, seasonal and cyclical components and residuals to create a simple additive model. Residuals were then modelled by linear time series models represented by models of the ARMA (autoregressive moving average) class and nonlinear time series models with multiple regimes represented by SETAR (self-exciting threshold autoregressive) and MSW (Markov switching) models. The analysis showed that, based on the minimal value of residual sum of squares (RSS) of one-step ahead forecast in both datasets, SETAR and MSW models described the time series better than models ARMA. However, the relative improvement of SETAR models against ARMA models was low ranging between 1% and 4% with the exception of the three-regime model for the River Stour where the improvement was 48.9%. In comparison, the relative improvement of MSW models was between 44.6% and 52.5 for two-regime and from 60.4% to 75% for three-regime models. However, the visual assessment of models plotted against original datasets showed that despite a high value of RSS, some ARMA models could describe the analyzed time series better than AR (autoregressive), MA (moving average) and SETAR models with lower values of RSS. In both datasets MSW models provided a very good visual fit describing most of the extreme values. The results of this work could be used as a base for construction of other time series models used to describe or predict nitrate-nitrogen concentrations. Analýza Koncentrácií Dusičnanov Pomocou Nelineárnych Modelov Časových Radov.Štúdia sa zaoberá analýzou dlhých časových radov koncentrácií dusičnanového dusíka v rieke Ouse a Stour vo Východnom Anglicku. Časové rady priemerných mesačných koncentrácií dusičnanov boli rozložené na trendovú, sezónnu a cyklickú zložku a reziduá pripočítané k sebe a tvoriace jednoduchý aditívny model. Reziduá boli ďalej modelované zložitejŠími lineárnymi modelmi reprezentovanými modelmi triedy ARMA a nelineárnymi viacrežimovými modelmi SETAR a MSW. Výsledky analýzy ukázali, že na základe minimálnej hodnoty sumy Štvorcov reziduí (SSR) jednokrokovej predpovede, v oboch prípadoch SETAR aj MSW modely opísali časové rady lepŠie ako modely triedy ARMA. Vo väčŠine prípadov relatívne zlepŠenie modelov SETAR oproti jednoduchým AR(1) modelom bolo malé v rozmedzí od 1 do 4 % s výnimkou trojrežimového modelu pre rieku Stour, kde to bolo až 48,9 %. Naopak, relatívne zlepŠenie modelov MSW oproti AR(1) modelom bolo v rozmedzí 44,6 až 52,5 % pre dvojrežimové a 60,4 až 75 % pre trojrežimové modely. Vizuálne posúdenie jednotlivých modelov vŠak ukázalo, že napriek vysokým hodnotám SSR, niektoré ARMA modely dokázali lepŠie opísať dané časové rady ako modely AR, MA a SETAR s nižŠími hodnotami SSR. V oboch prípadoch MSW modely dokázali dostatočne dobre opísať aj extrémne hodnoty oboch časových radov. Výsledky práce môžu byť použité pri tvorbe iných opisných alebo predpovedných modelov koncentrácie dusičnanového dusíka vo vodách.