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Τεχνική Υδρολογία (Engineering Hydrology)

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Abstract

Το βιβλίο αποτελείται από έξι κεφάλαια. Στο πρώτο δίνονται οι γενικές έννοιες και οι ορισμοί (υδρολογία, νερό και ιδιότητές του, υδρολογικός κύκλος), και ένα συνοπτικό ιστορικό της υδρολογίας από την αρχαιότητα μέχρι σήμερα. Εντάσσεται η υδρολογική επιστήμη στο γενικότερο επιστημονικό και τεχνολογικό πλαίσιο και οριοθετούνται οι σχέσεις της με τα υδραυλικά έργα και τη διαχείριση υδροσυστημάτων. Τέλος, αναλύονται οι χωρικές και χρονικές κλίμακες της υδρολογίας και οι μέθοδοι που ακολουθούνται, και σκιαγραφείται η υδρολογική πληροφορία. Το δεύτερο κεφάλαιο αναφέρεται στα ατμοσφαιρικά κατακρημνίσματα, το φυσικό και μετεωρολογικό τους πλαίσιο, τις μετρικές ιδιότητες και τη μέτρησή τους, την επεξεργασία της βροχομετρικής πληροφορίας, και την ανάλυση των ισχυρών βροχοπτώσεων. Το τρίτο κεφάλαιο μελετά την εξάτμιση και τη διαπνοή, το φυσικό και μετεωρολογικό τους πλαίσιο τις μεθόδους εκτίμησής τους με φυσικά θεμελιωμένες αλλά και εμπειρικές μεθόδους, και ποσοτικοποιεί την έννοια του υδατικού ισοζυγίου. Το τέταρτο κεφάλαιο αναφέρεται στην κατακράτηση και τη διήθηση και τον τρόπο εκτίμησής τους. Στο πέμπτο κεφάλαιο εξετάζεται η επιφανειακή απορροή και ειδικότερα οι μηχανισμοί και η προέλευσή της, το υδρογράφημα και οι συνιστώσες του, τα χαρακτηριστικά των λεκανών απορροής, οι μέθοδοι μέτρησης της απορροής και η επεξεργασία των υδρομετρικών δεδομένων. Τέλος το έκτο κεφάλαιο δίνει μια εισαγωγή στην υπόγεια υδρολογία εξετάζοντας ειδικότερα τα πορώδη μέσα και τους υδροφορείς, τις βασικές αρχές της υπόγειας ροής, τα μαθηματικά μοντέλα υπόγειων ροών, τη συμμετοχή των υπόγειων νερών στο υδατικό ισοζύγιο και την εκμετάλλευση των υπόγειων νερών.
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... The parameterized formulation proposed by Koutsoyiannis and Xanthopoulos (1999) with A and D indicating the area (expressed in km 2 ) and the duration (expressed in hours), respectively. ...
... (10.12) in relation to the Korean Peninsula, for which the Ministry of Land, Transport and Maritime Affairs (MLMT, 2011) proposed the following parameterization applicable to the major river basins: where M, a, and b are parameters depending on the return period and rainfall duration. Mineo et al. (2018) evaluated ARFs in the Lazio region (Central Italy) through an original empirical approach and compared the obtained values with four widespread empirical methodologies: NERC (1975), as parameterized by Koutsoyiannis and Xanthopoulos (1999), Moisello and Papiri (1986), US Weather Bureau (1957-1958 in the parameterization of Eagleson (1972), andChow (1964). In the proposed methodology, a single value of ARF is calculated through the relation: To protect the rights of the author(s) and publisher we inform you that this PDF is an uncorrected proof for internal business use only by the author(s), editor(s), reviewer(s), Elsevier and typesetter Aptara. ...
... The ARFs curves derived by the aforedescribed approach were compared with the following traditional methodologies: (NERC, 1975) as parameterized by Koutsoyiannis and Xanthopoulos (1999), Moisello and Papiri (1986), US Weather Bureau (19857, 1958) in the parameterization of Eagleson (1972), and the one proposed by Mineo et al. (2018). The results for a duration of 1 h are shown in Fig. 10.6. ...
Chapter
The areal reduction factor (ARF) is of paramount importance in the hydraulic structures design against hydrological hazards. In fact, the knowledge of areal-average rainfall over a basin is essential in rainfall–runoff models commonly adopted in the hydrological practice. Nevertheless, rainfall data are generally available at a point scale; ARF allows to transform such kind of data to an areal-average information. In this chapter, after an introduction providing a general overview over the topic, the main factors influencing ARFs are described. Then, the main empirical and analytical approaches to estimate ARFs available in the scientific literature are presented and critically discussed. The crucial issue of the transposition and applicability of ARFs values developed for a certain area to other regions is also deepened by presenting the results of several studies. Finally, a new empirical formulation for the ARFs estimate recently developed in the Umbria region (Central Italy) is proposed. On the basis of the specific case study and available data quality, indications to the reader in order to select the most suitable method to be applied for ARF estimation are provided.
... 51 2. History of the notion of climate 52 Although the historian Herodotus (Ἡρόδοτος; c. 484 -c. 425 BC) is perhaps the first 53 who described different climates of some areas on Earth in a geographical context (see 54 Appendix A), it is Aristotle (Figure 1) he who, a century later, put the notion of climate in 55 a scientific context. In his famous book Meteorologica he describes the climates on Earth in 56 connection with latitude but he uses a different term, crasis (κρᾶσις), literally meaning 57 mixing, blending of things which form a compound, temperament. ...
... Abundance. The water in the oceans amounts to 1.34 × 10 9 Gt [54] while additional 468 quantities are stored in the soil, ground and glaciers (which generally are not in tur-469 bulent motion, see below) and much smaller quantities of liquid water are on land. 470 For comparison the mass of air in the atmosphere is 5.14 × 10 6 Gt (of which 12 500 Gt 471 is water vapour) [55], i.e., 260 times smaller than the mass of water in turbulent mo-472 tion. ...
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Preprint
We revisit the notion of climate, along with its historical evolution, tracing the origin of the modern concerns about climate. The notion (and the scientific term) of climate has been established during the Greek antiquity in a geographical context and it acquired its statistical content (average weather) in modern times, after meteorological measurements had become common. Yet the modern definitions of climate are seriously affected by the wrong perception of the previous two centuries that climate should regularly be constant, unless an external agent acted. Therefore, we attempt to give a more rigorous definition of climate, consistent with the modern body of stochastics. We illustrate the definition by real-world data, which also exemplify the large climatic variability. Given this variability, the term “climate change” turns out to be scientifically unjustified. Specifically, it is a pleonasm as climate, like weather, has been ever-changing. Indeed, a historical investigation reveals that the aim in using that term is not scientific but political. Within the political aims, water issues have been greatly promoted by projecting future catastrophes while reversing the true roles and causality directions. For this reason, we provide arguments that water is the main element that drives climate and not the opposite.
... We illustrate the definition by real-world data, which also exemplify the large 37 variability of climate. Given this variability, the term climate change turns out to be scien- 38 tifically unjustified. Specifically, it is a pleonasm as the climate, like weather, has been 39 ever changing. ...
... The climate is generated by the everlasting turbulent motion of two flu-406 ids, water and air. The water in the oceans amounts to 1.34 × 10 9 Gt [38], not consid-407 ering the additional quantities stored in the soil, ground and glaciers, which gener-408 ally are not in turbulent motion, and neglecting the much smaller quantities of liquid 409 water on land. For comparison the mass of air in the atmosphere is 5.14 × 10 6 Gt (of 410 which 12 500 Gt is water vapour) [39], i.e., 260 times smaller than the mass of water 411 in motion. ...
Full-text available
Preprint
We revisit the notion of climate, along with its historical evolution, tracing the origin of the modern concerns about climate. The notion (and the scientific term) of climate has been established during the Greek antiquity in a geographical context and it acquired its statistical content (average weather) in modern times, after meteorological measurements had become common. Yet the modern definitions of climate are seriously affected by the wrong perception of the previous two centuries that climate should regularly be constant, unless an external agent acted. Therefore, we attempt to give a more rigorous definition of climate, consistent with the modern body of stochastics. We illustrate the definition by real-world data, which also exemplify the large climatic variability. Given this variability, the term “climate change” turns out to be scientifically unjustified. Specifi-cally, it is a pleonasm as climate, like weather, has been ever changing. Indeed, a historical inves-tigation reveals that the aim in using that term is not scientific but political. Within the political aims, water issues have been greatly promoted by projecting future catastrophes while reversing the true roles and causality directions. For this reason, we provide arguments that water is the main element that drives climate and not the opposite. (https://www.preprints.org/manuscript/202102.0180)
... Abundance. The water in the oceans amounts to 1.34 × 10 9 Gt [61] while additional quantities are stored in the soil, ground and glaciers (which generally are not in turbulent motion, see below) and much smaller quantities of liquid water are on land. ...
Full-text available
Article
We revisit the notion of climate, along with its historical evolution, tracing the origin of the modern concerns about climate. The notion (and the scientific term) of climate was established during the Greek antiquity in a geographical context and it acquired its statistical content (average weather) in modern times after meteorological measurements had become common. Yet the modern definitions of climate are seriously affected by the wrong perception of the previous two centuries that climate should regularly be constant, unless an external agent acts upon it. Therefore, we attempt to give a more rigorous definition of climate, consistent with the modern body of stochastics. We illustrate the definition by real-world data, which also exemplify the large climatic variability. Given this variability, the term “climate change” turns out to be scientifically unjustified. Specifically, it is a pleonasm as climate, like weather, has been ever-changing. Indeed, a historical investigation reveals that the aim in using that term is not scientific but political. Within the political aims, water issues have been greatly promoted by projecting future catastrophes while reversing true roles and causality directions. For this reason, we provide arguments that water is the main element that drives climate, and not the opposite.
... 610-c. 547 BC) and Anaximenes (585-525 BC) of Miletus, who studied the formation of clouds, rain and hail (Koutsoyiannis and Xanthopoulos, 1999; Koutsoyiannis et al., 2006). However, still the state of affairs regarding understanding and description of these phenomena and their behaviours may be not satisfactory. ...
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Chapter
Probabilistic modelling of extreme rainfall has a crucial role in flood risk estimation and consequently in the design and management of flood protection works. This is particularly the case for urban floods, where the plethora of flow control cites and the scarcity of flow measurements make the use of rainfall data indispensable. For half a century, the Gumbel distribution has been the prevailing model of extreme rainfall. Several arguments including theoretical reasons and empirical evidence are supposed to support the appropriateness of the Gumbel distribution, which corresponds to an exponential parent distribution tail. Recently, the applicability of this distribution has been criticized both on theoretical and empirical grounds. Thus, new theoretical arguments based on comparisons of actual and asymptotic extreme value distributions as well as on the principle of maximum entropy indicate that the Extreme Value Type 2 distribution should replace the Gumbel distribution. In addition, several empirical analyses using long rainfall records agree with the new theoretical findings. Further- more, the empirical analyses show that the Gumbel distribution may significantly underestimate the largest extreme rainfall amounts (albeit its predictions for small return periods of 5-10 years are satisfactory), whereas this distribution would seem as an appropriate model if fewer years of measurements were available (i.e., parts of the long records were used).
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Chapter
The study of rainfall extremes is important for design purposes of flood protection works, in the development of flood risk management plans and in assessing the severity of occurring storm and flood events. Such study unavoidably relies on observational data, which, given the enormous variability of the precipitation process in space and in time, should be local, of the area of interest. While general statistical laws or patterns apply over the globe, the parameters of those laws vary substantially and need local data to be estimated. Because of their global coverage, satellite data can be insightful to show the behavior of precipitation over the globe. However, only ground data (observations from raingages) are reliable enough for rainfall extremes and also have adequate length of archive that allows reliable statistical fitting. The study of the record rainfalls throughout the globe provides some useful information on the behavior of rainfall worldwide. While most of these record events have been registered at tropical areas (with a tendency for grouping in time with highest occurrence frequency in the period 1960-1980), there are record events that have occurred in extratropical areas and exceed, for certain time scales, those that occurred in tropical areas. The record values for different time scales allow the fitting of a curve which indicates that the record rainfall depth increases approximately proportionally to the square root of the time scale. Clearly, however, these record values do not suggest an upper limit of rainfall and are destined to be exceeded, as past record values have already been exceeded. In addition, the very concept of the probable maximum precipitation, which assumes a physical upper limit to precipitation at a site, is demonstrated to be fallacious. The only scientific approach to quantify extreme rainfall is provided by the probability theory. Theoretical arguments and general empirical evidence from many rainfall records worldwide suggest power-law distribution tail of extreme rainfall and favor the Extreme Value type II (EV2) distribution of maxima. The shape parameter of the EV2 distribution appears to vary in a narrow range worldwide. This facilitates fitting of the EV2 distribution and allows its easy implementation in typical engineering tasks such as estimation and prediction of design parameters, including the construction of theoretically consistent ombrian (also known as IDF) curves, which constitute a very important tool for hydrological design and flood severity assessment.
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