Browsing by Subject "vedenkorkeus"

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  • Bhattacharjee, Joy; Rabbil, Mehedi; Fazel, Nasim; Darabi, Hamid; Choubin, Bahram; Khan, Md. Motiur Rahman; Marttila, Hannu; Haghighi, Ali Torabi (Elsevier, 2021)
    Science of the Total Environment 797 (2021), 149034
    Lake water level fluctuation is a function of hydro-meteorological components, namely input, and output to the system. The combination of these components from in-situ and remote sensing sources has been used in this study to define multiple scenarios, which are the major explanatory pathways to assess lake water levels. The goal is to analyze each scenario through the application of the water balance equation to simulate lake water levels. The largest lake in Iran, Lake Urmia, has been selected in this study as it needs a great deal of attention in terms of water management issues. We ran a monthly water balance simulation of nineteen scenarios for Lake Urmia from 2003 to 2007 by applying different combinations of data, including observed and remotely sensed water level, flow, evaporation, and rainfall. We used readily available water level data from Hydrosat, Hydroweb, and DAHITI platforms; evapotranspiration from MODIS and rainfall from TRMM. The analysis suggests that the consideration of field data in the algorithm as the initial water level can reproduce the fluctuation of Lake Urmia water level in the best way. The scenario that combines in-situ meteorological components is the closest match to the observed water level of Lake Urmia. Almost all scenarios showed good dynamics with the field water level, but we found that nine out of nineteen scenarios did not vary significantly in terms of dynamics. The results also reveal that, even without any field data, the proposed scenario, which consists entirely of remote sensing components, is capable of estimating water level fluctuation in a lake. The analysis also explains the necessity of using proper data sources to act on water regulations and managerial decisions to understand the temporal phenomenon not only for Lake Urmia but also for other lakes in semi-arid regions.
  • Silander, Jari; Vehviläinen, Bertel; Niemi, Jorma; Arosilta, Anna; Dubrovin, Tanja; Jormola, Jukka; Keskisarja, Ville; Keto, Antton; Lepistö, Ahti; Ollila, Markku; Pajula, Heikki; Pitkänen, Heikki; Sammalkorpi, Ilkka; Suomalainen Merja; Veijalainen, Noora (Finnish Environment Institute, 2006)
    Finnish Environment Institute Mimeographs 336 (Suomen ympäristökeskuksen moniste 336)
    The most important effect of climate change on hydrological regimes in Finland is the change in seasonal distribution of runoff. Winter runoff is expected to increase considerably due to an increase in snowmelt and rainfall, while spring floods are estimated to decrease in southern Finland. In northern Finland spring floods are expected to increase during the next few decades due to increased snowfall, but then to decline over the longer term with continuous warming. Yearly runoff is estimated to change from -5 % to 10 %. Decreases are predicted for catchments with a large lake surface which enhance lake evaporation; increases are through winter runoff. In winter excess water from snowmelt and rainfall can cause winter floods, especially large central lakes Saimaa, Päijänne and Näsijärvi will be more frequently flooded. Extreme runoff events are projected to be more frequent due to increased maximum precipitation. Impacts and adaptation to these effects in hydrological cycle are described in this publication.
  • Pellikka, Havu (2020)
    Finnish Meteorological Institute Contributions 167
    This thesis presents research on two topics related to sea level in the Baltic Sea: regional sea level rise and meteotsunamis, i.e. meteorologically generated tsunami waves. While these phenomena act on very different time scales, they are both relevant for estimates of coastal flooding risks. Main objectives of this work are i) to present projections of mean sea level change in Finland by 2100 as location-specific probability distributions that can be used as a basis for decision-making in coastal management, and ii) to study the occurrence of meteotsunamis on the Finnish coast and the weather conditions that create these waves. Global mean sea level is rising in the warming climate. This will affect coastal life worldwide, but sea level does not rise uniformly around the globe. Projections of future sea level rise have large uncertainties, especially because the response of the Antarctic ice sheet to climatic changes is poorly known. This makes the upper tail of the probability distribution of sea level rise hard to pin down. In this work, an ensemble of global sea level rise projections is adjusted regionally to form a probability distribution of regional sea level rise. The results suggest that sea level rise in the Baltic Sea will be about 80% of the global mean, without including the effect of land uplift. To obtain probability distributions of mean sea level change relative to land, the effects of postglacial land uplift and wind-induced changes in mean sea level are combined with the sea level rise distributions. According to the average scenario, the sea level in the Gulf of Finland is expected to rise ca. 30 cm in 2000–2100, while mean sea level decline will continue in the Gulf of Bothnia. However, the high-end scenario projects sea level rise everywhere on the Finnish coast, ranging from 21 cm in Vaasa to 90 cm in Hamina. Meteotsunamis occur in shallow sea areas worldwide and can reach a height of several metres in extreme cases. In the Baltic Sea, such high, inexplicable sea waves are historically known as Seebär on the German-speaking southern coast and sjösprång in Swedish-speaking regions. According to old literature and recent eyewitness reports, meteotsunamis can occur all around the Baltic Sea and cause mild damage. The highest reliably documented events have been 1–1.5 metres high. After decades of no reported occurrences, three meteotsunamis were observed in Finland in the summers of 2010 and 2011. This work gives a detailed description of these events and their meteorological origin. The waves were created by air pressure disturbances propagating over the sea. The speeds of the disturbances were close to the long wave speed in the sea, which amplifies the wave. Such resonance effects, in addition to local coastal bathymetry, are central in the formation of meteotsunamis. To study the frequency of meteotsunami occurrence on the Finnish coast, meteotsunamis were detected in the original tide gauge charts and high-resolution sea level data from the Gulf of Finland over the past century. In total, 121 potential events were identified in the summer months of 1922–2014, with typical wave heights of 10–30 cm at the tide gauges. A statistically significant increasing trend in the number of meteotsunamis was found in Hamina in the eastern part of the gulf, but not in Hanko in the west. A strong connection between lightning observations (1998–2014) and meteotsunami occurrence was found: lightning numbers were over ten times higher on days when a meteotsunami was recorded compared to other summer days. *** Tässä työssä käsitellään kahta Itämeren vedenkorkeuteen liittyvää aihetta: alueellista merenpinnan nousua ja säätsunameja eli meteorologisten ilmiöiden synnyttämiä tsunamiaaltoja. Vaikka ilmiöiden aikaskaalat ovat hyvin erilaiset, ovat ne molemmat olennaisia Itämeren meritulvariskien arvioinnin kannalta. Työn tärkeimpinä tavoitteina on i) laskea ennusteet keskimerenpinnan tason muutokselle Suomessa vuoteen 2100 saakka paikkakohtaisina todennäköisyysjakaumina, jotka sopivat käytettäväksi päätöksenteon tukena rannikkosuunnittelussa, sekä ii) tutkia säätsunamien esiintymistä Suomen rannikolla ja niihin liittyviä sääolosuhteita. Ilmaston lämpenemisen aiheuttama valtamerien pinnannousu vaikuttaa rannikkoseutujen elämään ympäri maailman, mutta merenpinta ei nouse tasaisesti kaikkialla. Merenpinnan nousuennusteissa on myös suuria epävarmuuksia erityisesti siksi, että Etelämantereen mannerjäätikön tulevaisuus muuttuvassa ilmastossa tunnetaan huonosti. Sen vuoksi merenpinnan nousun todennäköisyysjakauman yläpäätä on vaikea arvioida. Tässä työssä käytetään alueellisen merenpinnan nousun jakauman pohjana joukkoa globaaleja ennusteita, joihin sovelletaan alueellisia korjaustekijöitä. Tulosten perusteella merenpinnan nousu Itämerellä on noin 80 % globaalista keskiarvosta, jos ei huomioida maankohoamisen vaikutusta. Kun merenpinnan nousujakaumiin lisätään maankohoamisen ja tuulen aiheuttamien keskimerenpinnan muutosten vaikutus, saadaan todennäköisyysjakaumat keskimerenpinnan tason muutoksesta maan suhteen. Keskimääräisen skenaarion mukaan merenpinta nousee Suomenlahdella noin 30 cm vuosina 2000–2100, kun taas Pohjanlahdella merenpinta edelleen laskee. Korkeimpien ennusteiden toteutuminen johtaisi kuitenkin merenpinnan nousuun kaikkialla Suomen rannikolla nousun vaihdellessa Vaasan 21 cm:stä Haminan 90 cm:iin. Säätsunameja esiintyy matalilla merialueilla ympäri maailmaa ja ne voivat saavuttaa ääritapauksissa useiden metrien korkeuden. Itämeren piirissä tällaiset korkeat, selittämättömät aallot tunnetaan vanhastaan saksankielisellä nimellä Seebär ja ruotsinkielisellä nimellä sjösprång. Vanhojen kirjallisuuslähteiden ja uusien silminnäkijähavaintojen perusteella säätsunameja esiintyy kaikkialla Itämeren rannikolla ja ne voivat aiheuttaa lievää vahinkoa. Suurimmat luotettavasti dokumentoidut tapaukset ovat olleet 1–1,5 metrin korkuisia. Useiden vuosikymmenten mittaisen hiljaisen jakson jälkeen Suomessa havaittiin kolme säätsunamia kesällä 2010 ja 2011. Tässä työssä kuvataan nuo tapaukset ja niiden meteorologinen tausta yksityiskohtaisesti. Aallot syntyivät meren yllä liikkuvien ilmanpaineen häiriöiden seurauksena. Häiriöiden nopeus oli lähellä pitkien aaltojen nopeutta meressä, mikä kasvattaa aallon korkeutta. Tällaiset resonanssi-ilmiöt ovat rannikon paikallisen pohjatopografian lisäksi keskeisiä säätsunamien muodostumisessa. Ilmiön yleisyyden tutkimiseksi säätsunameja etsittiin Suomenlahden mareografien alkuperäisiltä piirturirullilta ja korkean resoluution vedenkorkeushavainnoista lähes vuosisadan ajalta. Aineistosta tunnistettiin kaikkiaan 121 potentiaalista säätsunamia kesäkuukausilta 1922–2014; aaltojen tyypillinen korkeus mareografeilla oli 10–30 cm. Säätsunamien lukumäärässä havaittiin tilastollisesti merkitsevä lisääntyvä trendi Haminassa, mutta ei Hangossa. Salamahavaintojen (1998–2014) ja säätsunamien esiintymisen välillä havaittiin selvä yhteys: salamamäärät olivat yli kymmenkertaisia säätsunamien esiintymispäivinä verrattuna muihin kesäpäiviin.
  • Martinmäki, Kati; Hellsten, Seppo; Visuri, Mika; Ulvi, Teemu; Aronsuu, Kimmo (Suomen ympäristökeskus, 2008)
    Suomen ympäristökeskuksen raportteja 11/2008
  • Shu, Song; Liu, Hongxing; Beck, Richard A.; Frappart, Frédéric; Korhonen, Johanna; Lan, Minxuan; Xu, Min; Yang, Bo; Huang, Yan (Copernicus Publications / European Geosciences Union, 2021)
    Hydrology and Earth System Sciences Discussions 25:3
    A total of 13 satellite missions have been launched since 1985, with different types of radar altimeters on board. This study intends to make a comprehensive evaluation of historic and currently operational satellite radar altimetry missions for lake water level retrieval over the same set of lakes and to develop a strategy for constructing consistent long-term water level records for inland lakes at global scale. The lake water level estimates produced by different retracking algorithms (retrackers) of the satellite missions were compared with the gauge measurements over 12 lakes in four countries. The performance of each retracker was assessed in terms of the data missing rate, the correlation coefficient r, the bias, and the root mean square error (RMSE) between the altimetry-derived lake water level estimates and the concurrent gauge measurements. The results show that the model-free retrackers (e.g., OCOG/Ice-1/Ice) outperform the model-based retrackers for most of the missions, particularly over small lakes. Among the satellite altimetry missions, Sentinel-3 gave the best results, followed by SARAL. ENVISAT has slightly better lake water level estimates than Jason-1 and Jason-2, but its data missing rate is higher. For small lakes, ERS-1 and ERS-2 missions provided more accurate lake water level estimates than the TOPEX/Poseidon mission. In contrast, for large lakes, TOPEX/Poseidon is a better option due to its lower data missing rate and shorter repeat cycle. GeoSat and GeoSat Follow-On (GFO) both have an extremely high data missing rate of lake water level estimates. Although several contemporary radar altimetry missions provide more accurate lake level estimates than GFO, GeoSat was the sole radar altimetry mission, between 1985 and 1990, that provided the lake water level estimates. With a full consideration of the performance and the operational duration, the best strategy for constructing long-term lake water level records should be a two-step bias correction and normalization procedure. In the first step, use Jason-2 as the initial reference to estimate the systematic biases with TOPEX/Poseidon, Jason-1, and Jason-3 and then normalize them to form a consistent TOPEX/Poseidon–Jason series. Then, use the TOPEX/Poseidon–Jason series as the reference to estimate and remove systematic biases with other radar altimetry missions to construct consistent long-term lake water level series for ungauged lakes.
  • Olsonen, Riitta (Merentutkimuslaitos, 2007)
    Meri 59
  • Henttonen, Juhani; Malin, Väinö; Verta, Matti (Vesihallitus. National Board of Waters, 1980)
    Vesientutkimuslaitoksen julkaisuja 39, 3-12
    Vesihallituksen vesientutkimuslaitoksen hydrologiset rekisterit
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1971)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1972)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1973)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1974)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1975)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1976)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1977)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1978)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1979)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1980)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1981)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1982)
  • Unknown author (Vesihallitus, vesientutkimuslaitos, hydrologian toimisto, 1983)