This paper analyses the bivariate relationship between flood peaks and corresponding flood event volumes modelled by empirical and theoretical copulas in a regional context, with a focus on flood generation processes in general, the regional differentiation of these and the effect of the sample size on reliable discrimination among models. A total of 72 catchments in North-West of Austria are analysed for the period 1976-2007. From the hourly runoff data set, 25 697 flood events were isolated and assigned to one of three flood process types: synoptic floods (including long- and short-rain floods), flash floods or snowmelt floods (both rain-on-snow and snowmelt floods). The first step of the analysis examines whether the empirical peak-volume copulas of different flood process types are regionally statistically distinguishable, separately for each catchment and the role of the sample size on the strength of the statements. The results indicate that the empirical copulas of flash floods tend to be different from those of the synoptic and snowmelt floods. The second step examines how similar are the empirical flood peak-volume copulas between catchments for a given flood type across the region. Empirical copulas of synoptic floods are the least similar between the catchments, however with the decrease of the sample size the difference between the performances of the process types becomes small. The third step examines the goodness-of-fit of different commonly used copula types to the data samples that represent the annual maxima of flood peaks and the respective volumes both regardless of flood generating processes (the traditional engineering approach) and also considering the three process-based classes. Extreme value copulas (Galambos, Gumbel and Hüsler-Reiss) show the best performance both for synoptic and flash floods, while the Frank copula shows the best performance for snowmelt floods. It is concluded that there is merit in treating flood types separately when analysing and estimating flood peak-volume dependence copulas; however, even the enlarged dataset gained by the process-based analysis in this study does not give sufficient information for a reliable model choice for multivariate statistical analysis of flood peaks and volumes.
Since the beginning of hydrological research hydrologists have developed models that reflect their perception about how the catchments work and make use of the available information in the most efficient way. In this paper we develop hydrologic models based on field-mapped runoff generation mechanisms as identified by a geologist. For four different catchments in Austria, we identify four different lumped model structures and constrain their parameters based on the field-mapped information. In order to understand the usefulness of geologic information, we test their capability to predict river discharge in different cases: (i) without calibration and (ii) using the standard split-sample calibration/ validation procedure. All models are compared against each other. Results show that, when no calibration is involved, using the right model structure for the catchment of interest is valuable. A-priori information on model parameters does not always improve the results but allows for more realistic model parameters. When all parameters are calibrated to the discharge data, the different model structures do not matter, i.e., the differences can largely be compensated by the choice of parameters. When parameters are constrained based on field-mapped runoff generation mechanisms, the results are not better but more consistent between different calibration periods. Models selected by runoff generation mechanisms are expected to be more robust and more suitable for extrapolation to conditions outside the calibration range than models that are purely based on parameter calibration to runoff data.
The event runoff coefficient (Rc) and the recession coefficient (tc) are of theoretical importance for understanding catchment response and of practical importance in hydrological design. We analyse 57 event periods in the period 2013 to 2015 in the 66 ha Austrian Hydrological Open Air Laboratory (HOAL), where the seven subcatchments are stratified by runoff generation types into wetlands, tile drainage and natural drainage. Three machine learning algorithms (Random forest (RF), Gradient Boost Decision Tree (GBDT) and Support vector machine (SVM)) are used to estimate Rc and tc from 22 event based explanatory variables representing precipitation, soil moisture, groundwater level and season. The model performance of the SVM algorithm in estimating Rc and tc is generally higher than that of the other two methods, measured by the coefficient of determination R2, and the performance for Rc is higher than that for tc. The relative importance of the explanatory variables for the predictions, assessed by a heatmap, suggests that Rc of the tile drainage systems is more strongly controlled by the weather conditions than by the catchment state, while the opposite is true for natural drainage systems. Overall, model performance strongly depends on the runoff generation type.
In many Austrian catchments in recent decades an increase in the mean annual air temperature and precipitation has been observed, but only a small change in the mean annual runoff. The main objective of this paper is (1) to analyze alterations in the performance of a conceptual hydrological model when applied in changing climate conditions and (2) to assess the factors and model parameters that control these changes. A conceptual rainfall-runoff model (the TUW model) was calibrated and validated in 213 Austrian basins from 1981–2010. The changes in the runoff model’s efficiency have been compared with changes in the mean annual precipitation and air temperature and stratified for basins with dominant snowmelt and soil moisture processes. The results indicate that while the model’s efficiency in the calibration period has not changed over the decades, the values of the model’s parameters and hence the model’s performance (i.e., the volume error and the runoff model’s efficiency) in the validation period have changed. The changes in the model’s performance are greater in basins with a dominant soil moisture regime. For these basins, the average volume error which was not used in calibration has increased from 0% (in the calibration periods 1981–1990 or 2001–2010) to 9% (validation period 2001–2010) or –8% (validation period 1981–1990), respectively. In the snow-dominated basins, the model tends to slightly underestimate runoff volumes during its calibration (average volume error = –4%), but the changes in the validation periods are very small (i.e., the changes in the volume error are typically less than 1–2%). The model calibrated in a colder decade (e.g., 1981–1990) tends to overestimate the runoff in a warmer and wetter decade (e.g., 2001–2010), particularly in flatland basins. The opposite case (i.e., the use of parameters calibrated in a warmer decade for a colder, drier decade) indicates a tendency to underestimate runoff. A multidimensional analysis by regression trees showed that the change in the simulated runoff volume is clearly related to the change in precipitation, but the relationship is not linear in flatland basins. The main controlling factor of changes in simulated runoff volumes is the magnitude of the change in precipitation for both groups of basins. For basins with a dominant snowmelt runoff regime, the controlling factors are also the wetness of the basins and the mean annual precipitation. For basins with a soil moisture regime, landcover (forest) plays an important role.
Recently hydrological mapping have gained renewed interest in connection with climate-change impact studies, determination of water budgets at different temporal and spatial scales and the validation of atmospheric simulation models and hydrological models. Grids maps are often chosen for the representation of the spatial distribution of diverse physiographic and hydrologic information. This study focuses on the spatial estimation of the long-term mean annual actual (ET) and potential (EP) evapotranspiration in mountainous basins in Central Slovakia. Three methods used for EP and ET estimations are compared in a mapping framework: the modified empirical Turc model, the energy based SOLEI model and continuous water balance simulation using WASIM model. The spatial variability and consistency of EP and ET estimated by the different methods is evaluated and the performance of resulting ET grid maps is compared with the observed long-term water balance in three Hron river basins: river Hron to Bystra, Hron to Brezno and Hron to Banska Bystrica profiles. and Mapovanie prvkov hydrologickej bilancie má čoraz väčšie uplatnenie pri modelovaní priestorových zmien jednotlivých hydrologických prvkov, na určenie komponentov hydrologickej bilancie vybraných území, pri overovaní platnosti údajov pre rôzne atmosférické a hydrologické modely, ale aj pri štúdiách spojených s posudzovaním dôsledkov možnej zmeny klímy na hydrologický cyklus. Táto práca je venovaná možnostiam mapovania dlhodobého priemerného ročného aktuálneho (ET) a potenciálneho výparu (EP) s využitím rastrovej (štvorcovej) formy vyjadrenia ich priestorovej variability. Na konštrukciu máp EP a ET boli použité tri rôzne metódy: empirický model Turca, energeticky založený model SOLEI a model hydrologickej bilancie WaSiM. Výsledkom práce bolo zhodnotenie priestorovej variability a vzájomnej konzistencie rôznych metód aplikovaných na mapovanie EP a ET a porovnanie ich presnosti voči meraným dlhodobým prvkom hydrologickej bilancie v troch povodiach - povodí Bystrej, povodí Hrona po profil Brezno a po profil Banská Bystrica.
We computed annual precipitation totals for six catchments in the West and High Tatra Mountains (Roháčska, Jalovecká, Žiarska, Račkova, Tichá and Kôprová dolina) for hydrological years 1989-1998 using different interpolation and extrapolation methods. Precipitation estimates for the entire period as well as for particular hydrological years were used to compute evapotranspiration from the hydrological balance equation. The results have shown that although we used all existing precipitation data from the region along with the sophisticated methods to estimate catchment precipitation, yet, the water balance of the mountain catchments was not explained satisfactorily. and V práci sú vypočítané ročné zrážkové úhrny v šiestich povodiach Západných a Vysokých Tatier (Roháčska, Jalovecká, Žiarska, Račkova, Tichá a Kôprová dolina) pomocou rôznych interpolačných a extrapolačných metód pre hydrologické roky 1989 až1998, aj pre priemerné ročné úhrny za celé obdobie. Pre zrážkové úhrny určené rôznymi metódami bol z rovnice hydrologickej bilancie vypočítaný výpar a výsledky boli vyhodnotené opäť pre celé obdobie, aj pre jednotlové hydrologické roky. Získané výsledky ukazujú, že ani pri použití všetkých existujúcich údajov a moderných výpočtových metód existujúca meracia sieť nedáva uspokojivú odpoveď na pochybnosti, ktoré vznikajú pri určení základných prvkov hydrologickej bilancie v jednotlivých horských povodiach.
Editors of several journals in the field of hydrology met during the General Assembly of the European Geosciences Union–EGU in Vienna in April 2017. This event was a follow-up of similar meetings held in 2013 and 2015. These meetings enable the group of editors to review the current status of the journals and the publication process, and to share thoughts on future strategies. Journals were represented at the 2017 meeting by their editors, as shown in the list of authors. The main points on invigorating hydrological research through journal publications are communicated in this joint editorial published in the above journals.
The objective of this paper is to compare the results of two distributed snow models based on different approach to snow accumulation and melt. Model WaSiM is based on the degree-day approach, while model UEB-EHZ is an energy-based model. Simulations in the mountain catchment of Jalovecký creek in winters 1989-2001 showed that both approaches can produce similar results. Model parametrization is more important than basic approach to snow accumulation and melt. Therefore, model UEB-EHZ which took into acccount influence of forest on radiation reduction and snow drift, performed better for the forest sites. The paper presents also brief overview of snow accumulation and melt modelling including calibration and verification of distributed models. Finally, it shows some outupts which can be provided by distributed snow models. and Príspevok je venovaný porovnaniu dvoch distribuovaných matematických modelov akumulácie a topenia snehu s rôznym prístupom k modelovaniu snehu. V horskom povodí Jaloveckého potoka boli hodnotené výsledky energeticky založeného modelu UEB-EHZ a modelu WaSiM, vychádzajúceho z metódy teplotného indexu pre zimy 1988/89 - 2000/2001. Porovnanie výsledkov oboch modelov ukázalo, že pokiaľ ide o základný prístup k modelovaniu topenia snehu (energetická bilancia alebo teplotný index), nemohli sme v danom povodí určiť, ktorý z nich viedol k lepším výsledkom. Väčší vplyv na simuláciu vodnej hodnoty snehu ako výber základného prístupu k modelovaniu akumulácie a topenia snehu, má parametrizácia konkrétneho modelu. V modeli UEB-EHZ bol napríklad čiastočne zahrnutý vplyv lesa na globálne žiarenie a podmienky ukladania snehu (drift). Preto bolo topenie snehovej pokrývky v lese týmto modelom simulované reálnejšie ako modelom WaSiM. Okrem porovnania výsledkov dvoch základných prístupov k modelovaniu akumulácie a topenia snehu v horskom povodí príspevok ukazuje aj niektoré výstupy, ktoré možno získať pomocou distribuovaného snehového modelu a stručne sa zaoberá diskusiou o kalibrácii a validácii takéhoto modelu.
This study evaluates MODIS snow cover characteristics for large number of snowmelt runoff events in 145 catchments from 9 countries in Europe. The analysis is based on open discharge daily time series from the Global Runoff Data Center database and daily MODIS snow cover data. Runoff events are identified by a base flow separation approach. The MODIS snow cover characteristics are derived from Terra 500 m observations (MOD10A1 dataset, V005) in the period 2000–2015 and include snow cover area, cloud coverage, regional snowline elevation (RSLE) and its changes during the snowmelt runoff events. The snowmelt events are identified by using estimated RSLE changes during a runoff event. The results indicate that in the majority of catchments there are between 3 and 6 snowmelt runoff events per year. The mean duration between the start and peak of snowmelt runoff events is about 3 days and the proportion of snowmelt events in all runoff events tends to increase with the maximum elevation of catchments. Clouds limit the estimation of snow cover area and RSLE, particularly for dates of runoff peaks. In most of the catchments, the median of cloud coverage during runoff peaks is larger than 80%. The mean minimum RSLE, which represents the conditions at the beginning of snowmelt events, is situated approximately at the mean catchment elevation. It means that snowmelt events do not start only during maximum snow cover conditions, but also after this maximum. The mean RSLE during snowmelt peaks is on average 170 m lower than at the start of the snowmelt events, but there is a large regional variability.
In this paper a comparison of methods for estimating rainfall-runoff model parameters in ungauged basins based on geographical location are presented. As a pilot basin the Hron River basin in Slovakia with an available daily flow, precipitation and air temperature time series needed for calibration to obtain model parameter values in subcatchments was selected. The rainfall-runoff model was calibrated using a daily time step at 23 subcatchments. The Nearest Neighbour, Lumped Basin and Best Similarity Index methods were used to transfer the model parameters from the gauged to ''ungauged'' subcatchments. Finally, the effectiveness of the estimation method for ungauged basins was tested by comparing the model simulations to observed hydrographs and computing the Nash-Sutcliffe optimization criterion. The results were finally compared, and the best method was recommended for practical application by estimating of the rainfallrunoff model parameters in an ungauged catchment in this region. and V štúdii sú prezentované výsledky nepriamych metód odhadu parametrov zrážkovo-odtokového modelu na povodiach bez priamych hydrologických pozorovaní, ktoré sú založené na geografickej polohe povodí. Povodie Hrona bolo vybrané ako pilotný región s 23 čiastkovými povodiami, ktoré mali dostupné časové rady pozorovaní priemerných denných prietokov, zrážok a teploty vzduchu, potrebné na kalibráciu modelu. Zrážkovo-odtokový model bol v týchto podpovodiach nakalibrovaný na údajoch s denným časovým krokom. Následne boli použité na regionalizáciu parametrov modelu metódy Nearest Neighbour (Metóda najbližšieho suseda), Lumped Basin (Metóda sústredeného povodia) a Best Similarity Index methods (Metóda najlepšej podobnosti). Kvalita regionalizačných metód sa overovala pomocou optimalizačného kritéria Nash-Sutcliffe. Najlepšie výsledky boli dosiahnuté Metódou najlepšej podobnosti, ktorá môže byť v praxi odporúčaná na odhad parametrov zrážkovo-odtokového modelu na testovanom povodí.