This paper presents a novel framework to use artificial neural network (ANN) for accurate forecasting of river flows at higher lead times. The proposed model, termed as sequential ANN (SANN), is based on the heuristic that a mechanism that provides an accurate representation of physical condition of the basin at the time of forecast, in terms of input information to ANNs at higher lead time, helps improve the forecast accuracy. In SANN, a series of ANNs are connected sequentially to extend the lead time of forecast, each of them taking a forecast value from an immediate preceding network as input. The output of each network is modified by adding an expected value of error so that the residual variance of the forecast series is minimized. The applicability of SANN in hydrological forecasting is illustrated through three case examples: a hypothetical time series, daily river flow forecasting of Kentucky River, USA and hourly river flow forecasting of Kolar River, India. The results demonstrate that SANN is capable of providing accurate forecasts up to 8 steps ahead. A very close fit (>94% efficiency) was obtained between computed and observed flows up to 1 hour in advance for all the cases, and the deterioration in fit was not significant as the forecast lead time increased (92% at 8 steps ahead). The results show that SANN performs much better than traditional ANN models in extending the forecast lead time, suggesting that it can be effectively employed in developing flood management measures.
Soil moisture content was measured by TDR sensors Aqua-Tel-TDR (Automata, Inc., today McCrometer CONNECT) in a loamy Chernozem on carbonate-rich loess substrate. The sensors, wrapped in slurry made of local soil and water, were installed horizontally into pre-made holes. The bias caused by imperfectly filled gaps between the wall of the hole and the sensor surface was reduced by field calibration. The same gaps made it possible to detect the preferential flow in soil macropores, due to which the reflectometric readings were perceivably higher than analogous readings before percolation events and sometimes higher than the native soil porosity. One typical event is presented. It is envisaged that sensors of this type can be used for semi-quantitative estimation of the preferential flux density, e.g. with the help of dual or multiple porous medium models or the momentum dissipation theory. and Vlhkost hlinité černozemní půdy na karbonátovém sprašovém substrátu byla měřena metodou TDR čidly Aqua-Tel-TDR (Automata, Inc., dnes McCrometer CONNECT). Čidla, obalená před osazením pastou z místní zeminy a vody, byla instalována vodorovně do předvrtaných otvorů. Systematická chyba způsobená nedokonale zaplněnými mezerami mezi čidlem a stěnou otvoru byla zmenšena terénní kalibrací. Tytéž mezery umožnily indikovat preferenční proudění v půdních makropórech, díky němuž byla reflektometrická měření citelně vyšší než analogické hodnoty před průsakovou epizodou a někdy i vyšší než pórovitost původní půdy. Je demonstrována jedna typická epizoda. Lze předpokládat, že čidla tohoto typu mohou být použita k semikvantitativnímu odhadu hustoty preferenčního toku, např. za pomoci modelů dvojného nebo vícenásobného pórovitého prostředí nebo teorie rozptylu hybnosti.
The main objective of this study is to develop a model procedure for predicting low flows for a large set of gauged basins located in the Rhine-Meuse area. The methodology is primarily based on the analysis of recession curves, river discharges being essentially provided by groundwater flow during drought period. Our objective is to use recession coefficients in order to calibrate base flow predictions coming out from a groundwater reservoir. Problems related to the temporal variability of recession coefficients are discussed. We come to the conclusion that lows flows prediction can be improved by implementing a new groundwater reservoir into the RR model based on our knowledge of low flow processes. and Cieľom tejto štúdie je návrh procedúry pre predpoveď minimálnych prietokov pre početnú skupinu malých povodí lokalizovaných v oblasti riek Rýn - Meuse. Metóda je založená predovšetkým na analýze výtokových kriviek počas suchého obdobia, keď sú prietoky dotované hlavne podzemnými vodami. Naším cieľom je použitie výtokových koeficientov na kalibráciu predpovede základného prietoku z podzemných zdrojov. Sú tu diskutované problémy súvisiace s časovou zmenou výtokových koeficientov. Prišli sme k záveru, že prognóza nízkych prietokov môže byť zlepšená implementáciou nového rezervoáru podzemných vôd do zrážkoodtokového modelu, založeného na našich poznatkoch o procesoch tvorby nízkych prietokov.
An investigation has been carried out using the FLUENT Computational Fluid Dynamics (CFD) software, which uses the finite-volume method to determine whether it is feasible to improve the capacity and quality of the clarifier at the Al-Wathba Water Treatment Works (Iraq) by some relatively inexpensive means. Simulations were carried out with two dimensional, radially symmetric models, representing the existing configuration as well as a number of proposed modifications involving baffles and additional clarified water off-takes. A convection-diffusion equation, which is extended to incorporate the sedimentation of sludge flocs in the field of gravity, governs the mass transfer in the clarifier. The standard k-ε turbulence model is used to compute the turbulent motion, and our CFD model accounts for buoyancy flow. The sludge settling velocity was measured as a function of the concentration, and we have used the double-exponential settling velocity function to describe its dependence on the concentration. The CFD model is validated using measured concentration profiles. The results were evaluated on the basis of the simulated profiles of vertical up-flow velocity in the body of the clarifier. and Pri výskume bol použitý softvér FLUENT CFD, ktorý využíva metódu konečných objemov na určovanie toho, či možno zlepšiť kapacitu a kvalitu číričov v úpravni vody Al-Wathba (Irak) niektorým z relatívne nenákladných spôsobov. Simulácie sa uskutočnili s využitím 2D radiálne symetrických modelov, ktoré predstavovali skutočnú konfiguráciu ako aj počet navrhnutých modifikácií s usmerňovačmi a dodatočnými odtokmi upravenej vody. Konvekčno-difúzna rovnica, ktorá je rozšírená o sedimentáciu kalových vločiek v gravitačnom poli, určuje prenos hmoty v číriči. Na výpočet turbulentného pohybu sme použili štandardný model turbulencie k-ε a na vztlakové prúdenie CFD model. Rýchlosť usadzovania kalu bola meraná ako funkcia koncentrácie, pričom my sme použili dvojexponenciálnu funkciu rýchlosti usadzovania na opis závislosti od koncentrácie. CFD model je overený pomocou meraných profilov koncentrácií. Výsledky boli vyhodnotené na základe simulovaných profilov vertikálnej rýchlosti prúdenia v číriči smerom nahor.
Drainage networks allow the extraction of topographic parameters that are useful for basins characterization and necessary for hydrologic modelling. One way to obtain drainage networks is by their extraction from Digital Elevation Models (DEMs). However, it is common that no freely available DEMs at regional or national level exist. One way to overcome this situation is to use the available free Global Digital Elevation Models (GDEMs). However, these datasets have relatively low spatial resolutions, 30 and 90 meters for ASTER and SRTM, respectively, and it has been shown that their accuracy is relatively low in several regions (e.g., Kääb, 2005; Mukul et al., 2017). In this study a methodology is presented to improve the positional accuracy of the drainage networks extracted from the GDEMs using crowdsourced data available in the collaborative project OpenStreetMap (OSM). In this approach only free and global datasets are used, enabling its application to any location of the world. The methodology uses elevation points derived from the GDEMs and the water lines extracted from the collaborative project OSM to generate new DEMs, from which new water lines are obtained. The methodology is applied to two study areas and the positional accuracy of the used data and the obtained results are assessed using reference data.
In this paper, we defend the main claims of our earlier paper “Mental Fictionalism as an Undermotivated Theory” (in The Monist) from Gábor Bács’s criticism, which appeared in his “Mental fictionalism and epiphenomenal qualia” (in Dialectica). In our earlier paper, we tried to show that mental fictionalism is an undermotivated theory, so there is no good reason to give up the realist approach to the folk psychological discourse. The core of Bács’s criticism consists in that our argumentation rests on an equivocation concerning the folk psychological concepts of conscious experiences. In our present argumentation, at first, we shortly recapitulate our earlier argumentation and Bács’s main objection to it. After that, we argue against the case of equivocation, claiming that it rests on a highly implausible and unsupported verificationist approach. Lastly, in answering another remark of Bács’s, we discuss the possibility of a realist mental fictionalism and conclude that it is an incoherent standpoint.