Hydrological models often require input data on soil-water retention (SWR), but obtaining such data is laborious
and costly so that SWR in many places remains unknown. To fill the gap, a prediction of SWR using a pedotransfer
function (PTF) is one of the alternatives. This study aims to select the most suitable existing PTFs in order to predict
SWR for the case of the upper Bengawan Solo (UBS) catchment on Java, Indonesia. Ten point PTFs and two continuous
PTFs, which were developed from tropical soils elsewhere, have been applied directly and recalibrated based on a small
soil sample set in UBS. Scatter plots and statistical indices of mean error (ME), root mean square error (RMSE), model
efficiency (EF) and Pearson’s correlation (r) showed that recalibration using the Shuffled Complex Evolution-University
of Arizona (SCE-UA) algorithm can help to improve the prediction of PTFs significantly compared to direct application
of PTFs. This study is the first showing that improving SWR-PTFs by recalibration for a new catchment based on around
50 soil samples provides an effective parsimonious alternative to developing a SWR-PTF from specifically collected soil
datasets, which typically needs around 100 soil samples or more.
This study shows a comprehensive simulation of water and sediment fluxes from the catchment to the reach scale. We describe the application of a modelling cascade in a well researched study catchment through connecting stateof-the-art public domain models in ArcGIS. Three models are used consecutively: (1) the hydrological model SWAT to evaluate water balances, sediment input from fields and tile drains as a function of catchment characteristics; (2) the onedimensional hydraulic model HEC-RAS to depict channel erosion and sedimentation along a 9 km channel onedimensionally; and (3) the two-dimensional hydraulic model AdH for simulating detailed substrate changes in a 230 m long reach section over the course of one year. Model performance for the water fluxes is very good, sediment fluxes and substrate changes are simulated with good agreement to observed data. Improvement of tile drain sediment load, simulation of different substrate deposition events and carrying out data sensitivity tests are suggested as future work. Main advantages that can be deduced from this study are separate representation of field, drain and bank erosion processes; shown adaptability to lowland catchments and transferability to other catchments; usability of the model’s output for habitat assessments.
The scenario forecasting technique for assessing changes of water balance components of the northern river basins due to possible climate change was developed. Three IPCC global emission scenarios corresponding to different possible scenarios for economic, technological, political and demographic development of the human civilization in the 21st century were chosen for generating climate change projections by an ensemble of 16 General Circulation Models with a high spatial resolution. The projections representing increments of monthly values of meteorological characteristics were used for creating 3-hour meteorological time series up to 2063 for the Northern Dvina River basin, which belongs to the pan-Arctic basin and locates at the north of the European part of Russia. The obtained time series were applied as forcing data to drive the land surface model SWAP to simulate possible changes in the water balance components due to different scenarios of climate change for the Northern Dvina River basin.
Assessment of soil water repellency (SWR) was conducted in the decomposed organic floor layer (duff) and
in the mineral soil layer of two Mediterranean pine forests, one in Italy and the other in Spain, by the widely-used water
drop penetration time (WDPT) test and alternative indices derived from infiltration experiments carried out by the
minidisk infiltrometer (MDI). In particular, the repellency index (RI) was calculated as the adjusted ratio between
ethanol and water soil sorptivities whereas the water repellency cessation time (WRCT) and the specifically proposed
modified repellency index (RIm) were derived from the hydrophobic and wettable stages of a single water infiltration
experiment. Time evolution of SWR and vegetation cover influence was also investigated at the Italian site. All indices
unanimously detected severe SWR conditions in the duff of the pine forests. The mineral subsoils in the two forests
showed different wettability and the clay-loam subsoil at Ciavolo forest was hydrophobic even if characterized by organic
matter (OM) content similar to the wettable soil of an adjacent glade. It was therefore assumed that the composition
rather than the total amount of OM influenced SWR. The hydraulic conductivity of the duff differed by a factor of 3.8–
5.8 between the two forested sites thus influencing the vertical extent of SWR. Indeed, the mineral subsoil of Javea
showed wettable or weak hydrophobic conditions probably because leaching of hydrophobic compounds was slowed or
prevented at all. Estimations of SWR according to the different indices were in general agreement even if some discrepancies
were observed. In particular, at low hydrophobicity levels the SWR indices gathered from the MDI tests were able
to signal sub-critical SWR conditions that were not detected by the traditional WDPT index. The WRCT and modified
repellency index RIm yielded SWR estimates in reasonable agreement with those obtained with the more cumbersome RI
test and, therefore, can be proposed as alternative procedures for SWR assessment.
In this paper a new black box approach for rainfall-runoff modelling at a daily scale is presented. The considered black box model is non-linear regression based on Parzen probability density function. When using only measured rainfall as an input to any black box model there is a serious problem with building in the necessary memory. A standard approach to tackle this issue is to force a black box with a large number of rainfall and runoff variables of the past. In practice however, any regression technique, will have difficulties handling so large (possibly dependent) input set. For that reason, a more hydrological approach is proposed. Two linear reservoirs are used to model the memory. The reservoir constants are found by simple piecewise linear regression. An application to the Beerze catchment in the Netherlands is shown. A good correspondence between measured and estimated runoff is achieved. and Príspevok prezentuje nový prístup k zrážkovo-odtokovému modelovaniu, ktorý vychádza z metódy čiernej skrinky. V prípade, ak sa pri predpovedi prietokov použijú v modeli tohto typu ako vstupy len zrážkomerné pozorovania, môžu nastať ťažkosti s dostatočným zohľadnením pamäte procesu. Štandardný prístup ako riešiť tento problém, je zahrnúť dostatočné množstvo zrážkových a odtokových premenných zohľadňujúcich minulosť procesu odtoku. V praxi však môžu vzniknúť problémy pri aplikácii regresných metód na takýto súbor vstupných údajov (pravdepodobne vzájomne závislých). Preto je v príspevku navrhnutý hydrologicky vhodnejší prístup, pričom boli navrhnuté dve lineárne nádrže na modelovanie pamäte procesu odtoku. Konštanty nádrží boli určené metódou lineárnej regresie. Bol navrhnutý nelineárny regresný model založený na aplikácii Parzenovej funkcie hustoty rozdelenia pravdepodobnosti. V príspevku je uvedená aplikácia tohto prístupu na povodí Beerze v Holandsku. Dosiahla sa dobrá zhoda medzi meranými a modelovanými hodnotami odtoku.
In this paper we describe the use of modified passive capillary samplers (PCSs) to investigate the water isotope variability of snowmelt at selected sites in Slovenia during winter 2011/2012 and during winter 2012/2013. First, PCS with 3 fibreglass wicks covering approximately 1 m2 were tested to determine sample variability. We observed high variability in the amount of snowmelt water collected by individual wick (185 to 345 g) and in the isotope composition of oxygen (δ18O −10.43‰ to −9.02‰) and hydrogen (δ2H −70.5‰ to −63.6‰) of the collected water. Following the initial tests, a more detailed investigation was performed in winter 2012/2013 and the variability of snowmelt on the local scale among the different levels (i.e. within group, between the close and more distant groups of wicks) was investigated by applying 30 fibreglass wicks making use of Analysis Of Variance (ANOVA) and a balanced hierarchical sampling design. The amount of snowmelt water collected by an individual wick during the whole experiment was between 116 and 1705 g, while the isotope composition varied from −16.32‰ to −12.86‰ for δ18O and from −120.2‰ to −82.5‰ for δ2H. The main source of variance (80%) stems from the variability within the group of wicks (e.g. within group) while other sources contribute less than 20% of the variability. Amount weighted samples for the 2012–2013 season show no significant differences among groups, but significant differences for particular sampling events were observed. These investigations show that due to the variability within the group of wicks, a large number of wicks (> 5) are needed to sample snowmelt.
In this study, the FRIER rainfall-runoff model with distributed parameters was developed to assess changes in runoff and water balance due to changes in land use and climate. The water balance was calculated at 3 levels: on the surface and in unsaturated and saturated zones. Six basins from the central and eastern parts of Slovakia were selected on the basis of their similar size, but different topography, land use, soil texture and climate: the upper Hornád, the upper Hron, the Poprad, the Rimava, the Slaná and the Torysa River basins. Model parameters were estimated using data from the period from June 1998 to May 2000 in daily time steps. The differences and similarities of the hydrologic processes in individual basins were investigated during the calibration period. Several scenarios of changes in land use and two simple scenarios of changes in climate were developed to estimate the impact of these changes on water balance and runoff. The changes in the hydrological regime were compared and discussed. and V posledných rokoch sa veľmi často hodnotia a diskutujú vplyvy zmien využitia krajiny a klímy na procesy hydrologickej bilancie, aj keď miera ich vplyvu na hydrologický režim sa najmä pre komplexnosť týchto procesov veľmi ťažko kvantifikuje. Na odhad vplyvu zmien využitia krajiny a klímy na odtok a zložky hydrologickej bilancie bol vyvinutý zrážkovo-odtokový model FRIER s rozčlenenými parametrami. Na základe podobnej veľkosti, ale rôznej topografie, využitia krajiny a pôdnej štruktúry bolo vybraných šesť pilotných povodí: povodie horného Hornádu, horného Hrona, Popradu, Rimavy, Slanej a Torysy. Parametre modelu boli kalibrované pre obdobie jún 1998 - máj 2000 v dennom časovom kroku. Na základe simulácií hydrologickej bilancie pre súčasný stav sa hodnotili rozdiely a podobnosti procesov tvorby odtoku v jednotlivých povodiach. Odtok a zložky hydrologickej bilancie boli následne simulované pre sedem scenárov zmien využitia krajiny a dva jednoduché scenáre zmeny zrážok a teploty vzduchu. Zmeny odtoku a hydrologickej bilancie boli porovnané a diskutované.
Authors propose a beneficial methodology for hydrological planning in their study. Prospective evaluations of the basins' net capacity can be done using the technique presented. The HEC-HMS (Hydrologic Modelling System) software can be used to estimate in a basin, the sediment emitted. For a certain precipitation, this methodology allows estimating, within a certain range, the gradual blockage of a reservoir, and even a projected date for total blockage. This has some applications to adopt corrective measures that prevent or delay the planned blockage deadlines. The model is of the semi-distributed type, estimating the generation and emission of sediments by sub-basins. The integration of different return periods in HEC-HMS with a semi-distributed model by sub-basins and the application of a mathematical model are the differentiating element of this research. The novelty of this work is to allow prognosing the reservoir sedimentation rate of basins in a local and regional scale with a medium and large temporary framework. The developed methodology allows public institutions to take decisions concerning hydrological planning. It has been applied to the case of "Charco Redondo" reservoir, in Cádiz, Andalusia, in southern Spain. Applying the methodology to this case, an average soil degradation of the reservoir basin has been estimated. Therefore, it is verified that in 50 years the reservoir is expected to lose 8.4% of its capacity.
Knowledge of hydrological processes and water balance elements are important for climate adaptive water management as well as for introducing mitigation measures aiming to improve surface water quality. Mathematical models have the potential to estimate changes in hydrological processes under changing climatic or land use conditions. These models, indeed, need careful calibration and testing before being applied in decision making. The aim of this study was to compare the capability of five different hydrological models to predict the runoff and the soil water balance elements of a small catchment in Norway. The models were harmonised and calibrated against the same data set. In overall, a good agreement between the measured and simulated runoff was obtained for the different models when integrating the results over a week or longer periods. Model simulations indicate that forest appears to be very important for the water balance in the catchment, and that there is a lack of information on land use specific water balance elements. We concluded that joint application of hydrological models serves as a good background for ensemble modelling of water transport processes within a catchment and can highlight the uncertainty of models forecast.
Multi-agent system is a system of autonomous, intelligent but resource-bounded agents. Particular agents have to be able to make decisions on their own, based on the activities of other agents and events within the system as well as in its environment. To this end agents make use of their own internal knowledge base which serves them as a memory. In this paper we focus on the design and management of such a knowledge base. After a brief description of some classical fundamental approaches to the knowledge base management, we propose an improvement based on the application of statistical methods. We focus in particular on the optimization of the process., Multi-agent systém je systém autonomních, inteligentních, ale zdrojově omezených agentů. Konkrétní agenti musí být schopni sami rozhodovat na základě činností jiných agentů a událostí v systému i v jeho prostředí. K tomuto účelu agenti využívají vlastní interní znalostní základnu, která jim slouží jako paměť. V tomto příspěvku se zaměřujeme na návrh a správu takové znalostní báze. Po stručném popisu některých klasických základních přístupů k řízení znalostní báze navrhujeme zlepšení založené na aplikaci statistických metod. Zaměřujeme se především na optimalizaci procesu., and Michal Košinár ; Ondřej Kohut