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1
EN
The aim of the study was to compare two grouping methods for regionalisation of watersheds, which are similar in respect of low flow and chosen catchments parameters (physiographic and meteorological). In the study, a residual pattern approach and cluster analysis, i.e. Ward’s method, were used. The analysis was conducted for specific low flow discharge q95 (dm3∙s-1∙km-2). In the analysis, 50 catchments, located in the area of the upper and central Vistula River basin, were taken. Daily flows used in the study were monitored from 1976 to 2016. Based on the residual pattern approach (RPA) method, the analysed catchments were classified into two groups, while using the cluster analysis method (Ward’s method) - into five. The predictive performance of the complete regional regression model checked by cross-validation R2cv was 47% and RMSEcv= 0.69 dm3∙s-1∙km-2. The cross validation procedure for the cluster analysis gives a predictive performance equal to 33% and RMSEcv= 0.81 dm3∙s-1∙km-2. Comparing both methods, based on the cross-validated coefficient of determination (R2cv), it was found that the residual pattern approach had a better fit between predicted and observed values. The analysis also showed, that in case of both methods, an overestimation of specific low flow discharge q95 was observed. For the cross-validation method and the RPA method, the PBIAS was -10%. A slightly higher value was obtained for the cross-validation method and models obtained using cluster analysis for which the PBIAS was -13.8%.
EN
Bank filtration (BF) is a nature-based solution that can provide safe drinking water at a low cost, in being a green technology that benefits from natural ecosystem services and saves energy as well. The objective of the present paper is to evaluate the potentiality of a new site for bank filtration along a surface water source that experiences periods of both high and low flow. This site is located along the Ismailia Canal in the eastern Nile Delta fringe of Egypt. The present evaluation is based on exploratory drilling, installation of monitoring infrastructure and monitoring of both water level and water quality parameters for one year. The site has favourable hydrogeological conditions; the mean hydraulic conductivity of aquifer materials (sand and gravel) is 18.98 m/day. Moreover, there is a hydraulic connection between canal and aquifer; under steady conditions, the canal feeds the aquifer. Using different tracers, such as Cl, EC, Sr and SO4, the average bank filtration share is in excess of 95%. BF has reduced the particulates (turbidity) by 96%, total coliform by 99 % and total organic carbon (TOC) expressed as ultra-violet absorbance at 254 wavelengths (UVA254) by 44%. In addition, BF reduces concentrations of disinfection by-products due to its ability to remove organic matter. The potential degradation of TOC in the canal bed sediments may cause the release of iron (Fe) and manganese (Mn) to the bank filtrate water; this process is exaggerated during low-flow periods. Compared to conventional water treatment, BF is a cost-effective green technology, because no chemicals are used and no waste products are generated.
EN
Despite many studies on the hydrological responses to forest cover changes in micro and mesoscale watersheds, the hydrological responses to forest cover alterations and associated mechanisms through the large spatial scale of the river watershed have not been comprehensively perceived. This paper thus reviews a wide range of available scientific evidence concerning the impacts exerted by the forest removal on precipitation, water yield, stream flow, and flow regimes. It is concluded that there is no statistical correlation between forest cover and precipitation and water yield at the micro and mesoscale. In contrast, there is a relative correlation coefficient (r = 0.77, p < 0.05) between forest cover and water yield at large scales (>1000 km2). These findings help our understanding of the hydrological response to forest disturbance at large and regional scale and provide a scientific perception to future watershed management in the context of human activities and natural hazards.
PL
Dynamika przepływów niskich w Stróży na Rabie była analizowana na podstawie serii przepływów dobowych z wielolecia hydrologicznego 1960–2019, udostępnionych przez IMGW-PIB. W pracy wykorzystano również ciąg dobowych opadów ze stacji IMGW-BIP w Stróży oraz wskaźnik standaryzowanego klimatycznego bilansu wodnego SPEI w skalach 1- i 12-miesięcznej z lat 1960–2018 na badanym obszarze. Zbadano wieloletnią i sezonową zmienność czasu trwania i objętości niżówki na tle opadów oraz SPEI. Nie zaobserwowano istotnych statystycznie zmian badanych charakterystyk niżówek w przebiegu wieloletnim.
EN
The dynamics of low flows in Stróża on the Raba river was analyzed on the basis of a series of daily flows from the hydrological multi-year period 1960–2019, provided by the IMGW-BIP. The study also used the sequence of daily precipitation from the IMGW-BIP station in Stróża and the standardized precipitation evapotranspiration index SPEI on the 1- and 12-month scales from 1960–2018 in the study area. The long-term and seasonal variabilities of the duration and volume of the streamflow drought was examined against the background of precipitation and SPEI. No statistically significant changes were observed in the characteristics of the low flows.
EN
This article explores the suitability of a long short-term memory recurrent neural network (LSTM-RNN) and artificial intelligence (AI) method for low-flow time series forecasting. The long short-term memory works on the sequential framework which considers all of the predecessor data. This forecasting method used daily discharged data collected from the Basantapur gauging station located on the Mahanadi River basin, India. Diferent metrics [root-mean-square error (RMSE), Nash–Sutclife efciency (ENS), correlation coefcient (R) and mean absolute error] were selected to assess the performance of the model. Additionally, recurrent neural network (RNN) model is also used to compare the adaptability of LSTM-RNN over RNN and naïve method. The results conclude that the LSTM-RNN model (R=0.943, ENS=0.878, RMSE=0.487) outperformed RNN model (R=0.935, ENS=0.843, RMSE=0.516) and naïve method (R=0.866, ENS=0.704, RMSE=0.793). The fnding of this research concludes that LSTM-RNN can be used as new reliable AI technique for low-flow forecasting.
6
Content available remote Trend detection in river flow indices in Poland
EN
The issue of trend detection in long time series of river flow records is of vast theoretical interest and considerable practical relevance. Water management is based on the assumption of stationarity; hence, it is crucial to check whether taking this assumption is justified. The objective of this study is to analyse long-term trends in selected river flow indices in small- and medium-sized catchments with relatively unmodified flow regime (semi-natural catchments) in Poland. The examined indices describe annual and seasonal average conditions as well as annual extreme conditions—low and high flows. The special focus is on the spatial analysis of trends, carried out on a comprehensive, representative data set of flow gauges. The present paper is timely, as no spatially comprehensive studies (i.e. covering the entire Poland or its large parts) on trend detection in time series of river flow have been done in the recent 15 years or so. The results suggest that there is a strong random component in the river flow process, the changes are weak and the spatial pattern is complex. Yet, the results of trend detection in different indices of river flow in Poland show that there exists a spatial divide that seems to hold quite generally for various indices (annual, seasonal, as well as low and high flow). Decreases of river flow dominate in the northern part of the country and increases usually in the southern part. Stations in the central part show mostly ‘no trend’ results. However, the spatial gradient is apparent only for the data for the period 1981–2016 rather than for 1956–2016. It seems also that the magnitude of increases of river flow is generally lower than that of decreases.
PL
Celem niniejszej pracy jest ocena częstości występowania niżówek w rzekach położonych w otoczeniu środowiska przyrodniczego o różnym charakterze – w rzece górskiej, tj. Wisłoce i jej dopływach, i w rzece wyżynnej, tj. górnym Wieprzu wraz z dopływami. Analizę dynamiki pojawiania się przepływów niżówkowych wykonano na podstawie zmienności podstawowych charakterystyk niżówek (tj. czasu trwania i objętości niżówki) w wieloleciu 1983–2013. W rozpatrywanym okresie zaobserwowano więcej niżówek w rzekach górskich niż wyżynnych, lecz były one krótsze. W rzekach wyżynnych stwierdzono więcej lat „bezniżówkowych”. Badanie stacjonarności rocznych szeregów charakterystyk niżówek wykonano z użyciem testu Shapiro–Wilka, Ljunga–Boxa i Manna–Kendalla z poprawką na autokorelację. Około połowy analizowanych szeregów nie spełniało warunku normalności. Do badania trendu wykorzystano test Manna–Kendalla. Test ten wykazał trend malejący badanych ciągów w prawie wszystkich przekrojach w rzekach wyżynnych i tylko w jednym – w rzekach górskich. W około połowie ciągów stwierdzono istotną, potwierdzoną testem Ljunga–Boxa, autokorelację rzędu pierwszego – zarówno w szeregach czasów trwania, jak i objętości niżówek. Stwierdzono, że w badanych ciągach występują dwa typy funkcji autokorelacji. Pierwszy typ funkcji, występujący głównie w rzekach wyżynnych, cechuje się dłuższą pamięcią, okresy podobne trwają około 10–11 lat. W pozostałych przypadkach ACF wskazują na pamięć krótszą i odnoszą się do rzek o większej dynamice przepływów.
EN
The main goal of this study is to assess the long-term dynamics of low flows occurrence in catchments located in different environment conditions: mountain river: Wisłoka and its tributaries and upland river: Upper Wieprz with tributaries. Analysis of low flows occurrence was based on variability of basic low flow characteristics (duration time and volume of low flow episode) in period 1983–2013. In studied period, more low flows occurred in mountain rivers, however the time of duration was shorter than in upland area. On uplands, more years without low flow episodes were observed. For stationary of annual series analysis Shapiro–Wilk, Ljung–Box and Mann–Kendall tests with autocorrelation correction were used. About half of studied series does not complete the terms of normal distribution. For this reason, trend studies were performed by using nonparametric tests. Mann–Kendal test showed descending trends in almost all gauging sections located in upland region and only in one located in mountain rivers. In half of series there was a significant, confirmed by Ljung–Box test, first rank autocorrelation – in both duration time and volume series. It was found that in tested series, there were two types of autocorrelation function. First type of function, that occurred mainly in upland area, was characterized by long-term memory, where similar periods last for about 10–11 years. In other cases, ACF indicated a short memory of episodes and occurred in catchments with higher flow dynamics.
EN
In the paper the possibility of using statistical method for data agglomeration, i.e. nonhierarchical cluster analysis for low flow grouping was made. The study material included daily flows from the multi-year period of 1963–1983 collected for 19 catchments, located in the upper Vistula basin. Regions with the same flow were determined with the use of nonhierarchical cluster analysis (K-means). Groups were characterized by low flow and selected physiographic and meteorological features of the catchments. The procedure of catchments assigning to the clusters was started from two clusters and finished at five. The next moving and assigning of catchments into clusters resulted in a cluster in which there was only one catchment (for five clusters). Another objects’ delineation did not give an objective effects, based on which it was difficult to determine a clear criterion of assigning each catchments into the clusters. The last step involved development of the models reflecting correlation and regression relationships. The identified clusters comprised catchments similar in terms of unit runoff, watercourse length, mean precipitation, median altitude, mean catchment slope, watercourse staff gauge zero, area covered by coniferous forests, arable lands, and soils.
PL
Celem niniejszej pracy jest charakterystyka sezonowości niżówek występujących w rzekach mających zlewnie o różnych warunkach obiegu wody oraz wskazanie okresów o najwyższym stopniu zagrożenia wystąpieniem niżówki. W pracy wykorzystano wartości dobowe przepływów z okresu 01.11.1983–31.10.2013, udostępnione przez IMGW dla 7 przekrojów wodowskazowych umieszczonych na rzekach o charakterze górskim – Wisłoka i jej dopływy oraz 6 przekrojów położonych na rzekach o charakterze wyżynnym w zlewni górnego Wieprza. Do identyfikacji okresów niżówkowych wykorzystano metodę PUT (ang. Peak Under Threshold) z przepływem granicznym wynoszącym Q70%. W celu przedstawienia dynamiki sezonowej zastosowano miary sezonowości Markhama oraz analizę współczynników autokorelacji ACF z przesunięciem od 1 do 24 miesięcy. Na podstawie analizy stwierdzono przewagę niżówek w sezonie letnim. Rozkład zjawiska w ciągu roku był zorientowany sezonowo w rzekach górskich, gdzie niżówki kumulowały się głównie w drugiej połowie sezonu letniego. W rzekach wyżynnych rozkład objętości niżówek w ciągu roku był nieco bardziej wyrównany. Zarówno w przypadku rzek górskich, jak i wyżynnych zaobserwowano występowanie dwóch okresów z mniejszą liczbą niżówek (okres wiosenny – przełom marca i kwietnia oraz jesienny – październik–listopad). Zaobserwowano również większą liczbę niżówek w sezonie zimowym na obszarze wyżynnym w rzekach mających zlewnie o większej lesistości, jak też w rzekach górskich mających zlewnie o mniejszej lesistości. Analiza autokorelacji świadczy o występowaniu wyraźnych cyklów półrocznych i rocznych w kształtowania się niżówek.
EN
The main goal of this study was to characterize seasonal occurrence of low flows during a year period, in catchments of different character and indication of periods with the highest risk of low flows occurrence. The study was based on the daily flows data series from period 01.11.1983– 31.10.2013, provided by IMGW for 7 gauging sections located on rivers with mountain character – in catchment of Wisłoka River and 6 sections located in upper Wieprz catchment on Lublin Upland. To identify periods of low flows PUT (Peak Under Threshold) method was used with threshold at Q70%. To present seasonal dynamics Markham seasonality index and analysis of autocorrelation coefficient ACF (with displacement from 1 to 24 months) were used. The analysis showed superiority of low flows that are occurring in summer season in both areas. More season-focused distribution of phenomenon were observed in mountain catchments, where low flows were accumulating mainly in the second part of summer season. In the upland catchments distribution of low flows volumes was more balanced over the year. In both areas two periods with reduced prevalence of low flows were observed: first at spring (March/April) and second at autumn (October/November). There was also an increase in the share winter season low flows in upland catchments with greater forest cover and in mountain catchment with the lowest afforestation. Autocorrelation analysis showed a distinct semiannual and annual cycles in low flows occurrence.
PL
Celem niniejszej pracy było porównanie charakterystyk niżówek występujących w zlewni górskiej Wisłoki oraz wyżynnej górnego Wieprza. Analizę przeprowadzono na podstawie przepływów dobowych za lata 1983-2013. Niżówki określono metodą PUT, dla dwóch wartości przepływu granicznego: Q70% i Q90%, przy założeniu minimalnego czasu trwania 7 dni, oraz 3 dniowym kryterium łączenia w zdarzenia zależne. W górskiej zlewni Wisłoki zaobserwowano większą liczbę niżówek, o krótszym czasie trwania i większych objętościach. Pomimo tego korelacje czasów trwania i objętości niżówek były zbliżone w obu obszarach i wynosiły około 0,9. Związek ten malał w zlewniach południowych o najwyższych rzędnych terenu, gdzie obserwowano również wydłużenie czasów trwania i objętości epizodów.
EN
The main goal of this research was to compare characteristics of low flows that occur in mountain catchment of Wisłoka river and upland catchment of upper Wieprz river. The analysis was conducted on daily flow data for hydrological years 1983-2013. Low flows were determined by PUT method, with two threshold levels: Q70% and Q90%, with 7 day minimal duration time criterion and 3 day pooling method. In mountain Wisłoka river greater number of episodes, with shorter duration time and higher volume of deficits was observed. Correlations between duration time and deficit volume were similar in both areas: around 0,9. This relation was decreasing in the southern catchments, with highest elevations, where also prolongation of low flows duration and higher deficits were observed.
EN
The present study is aimed to: (a) project future low flow conditions in the five largest river basins in Germany, and (b) to account for the projections uncertainties. The eco-hydrological model SWIM was driven by different regional climate models (REMO, CCLM, and Wettreg) to simulate daily river discharg es in each study basin. The 50-year low flow was estimated for the period 1961 to 2000, and its return period was assessed for two scenario periods, 2021-2060 and 2061-2100, using the generalized extreme value distribu tion. The 50-year low flow is likely to occur more frequently in western, southern, and parts of central Ger- many after 2061, as suggested by more than or equal to 80 per cent of the model runs. The current low flow period (from August to September) may be extended until late autumn at the end of this century. The return period of 50-year deficit volume shows a similar temporal and spatial pattern of change as for the low flow, indicating slightly less severe con- ditions with lower confidence. When compared with flood projections for the same area using the same models, the severer low flows projected in this study appear more pronounced, consistent, and have lower uncertainty.
12
Content available remote Classification of low flow and hydrological drought for a river basin
EN
The occurrence of drought is one of the characteristic features of Polish climate. Drought usually lasts for many weeks and covers consid- erable area causing economic and social losses. Due to the influence which drought has on environment, economy and society, more and more research and implementation works are devoted to issues concerning its occurrence, risk assessment, monitoring, and forecasting. Literature indicates that hydrological droughts are most often associated with low flow periods on rivers. The paper presents analyses of hydrological drought periods on the basis of hydrological drought index (HDI) for selected Nysa Kłodzka study basin (SW part of Poland). Analyses were carried out in relation to the Maximum Credible Hydrological Drought (MCHD). In addition, attempts were taken to assess the hydrological drought based on atmospheric drought focused on application in ungauged basins in terms of hydrological monitoring.
PL
Określenie modeli zależności regresyjnych dla przepływu niskiego o czasie trwania wynoszącym 95% czasu w całym okresie badawczym. Zależności regresyjne i korelacyjne określono dla regionów homogenicznych wyznaczonych na podstawie statystycznej metody grupowania - analizy skupień.
EN
Determination of dependency regression models for low flow with a duration of 95% of the time throughout the study period. Regression and correlation dependencies defined for the homogeneous regions identified on the basis of statistical methods- cluster analysis grouping.
14
Content available remote Zasoby wodne województwa dolnośląskiego w okresach suszy
PL
Województwo dolnośląskie jest jednym z najuboższych w wodę obszarów kraju. Pierwszoplanową rolę w kształtowaniu stosunków hydrologicznych odgrywają tutaj opady atmosferyczne oraz ich rozkład w czasie i na obszarze dorzecza Odry. Naturalną przyczyną niżówek jest deficyt zasilania rzeki, który może być spowodowany brakiem opadów, dużym parowaniem oraz długotrwałymi mrozami. Brak opadów powoduje, że rzeki zasilane są jedynie przez wody podziemne. Na wielkość zasilania ma wpływ długość okresu bezopadowego. Im on jest dłuższy, tym bardziej wyczerpują się zasoby wód podziemnych i zasilanie rzek maleje. W okresie letnim, gdy wysokie temperatury powietrza ułatwiają szybkie parowanie wody oraz występują niewielkie opady, zasilanie rzek maleje. Współdziałanie tych czynników może doprowadzać do powstawania niżówek letnich. Zasoby wodne w takich okresach ulegają stopniowemu sczerpywaniu, co doprowadzić może do wystąpienia deficytów w zaspokajaniu potrzeb wszystkich użytkowników. W artykule oceniono zasoby wodne na podstawie wybranych okresów niżówkowych w rzekach obszaru województwa dolnośląskiego, określono ich objętość deficytu oraz czas trwania.
EN
The Dolnoslaskie Province is the one of the poorest region in water supply in the whole territory of Poland. The crucial role for hydrological conditions plays precipitations and also their temporal and spatial distribution in Odra basin. The natural reason of low flow in rivers is river supply scarcity which is caused by precipitations lack and increasing of evaporation. The lack precipitation caused that rivers are supply by only groundwater. In summer season when high temperatures help to evaporation increasing water supply are decreased. Water resources in such periods are gradually bailing. It can lead to appearance breaks in water demand for all users. In this paper water resources were assessed on the basis of low flow periods in rivers Dolnoslaskie Province territory and described their deficit volume and duration.
15
Content available remote Rozkłady prawdopodobieństwa niżówek maksymalnych
EN
The complete method, based on Zelenbasic and Salvai model, for estimating unknown distributions of low flow indices (drought amount and duration) is presented. Good fiting is shown on data taken from two different catchments: upper Nysa Kłodzka and Odra rivers.
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