ࡱ> egdiVU@”bjbj *;Q,    ;;;8<TV< U<=(<=<=<=O>?u@HTTTTTTT$bVRX~Tu IK>O>IIT<=<=fULLLI$|<= <=TLITLLWMX WM<=< e;JWMN|U0UWM2YK2YWM( t J2Y WM@qCL_EF@@@TT 1;yL( ;Problems with Consistency of Hydrological Data Series Caused By Different Time Discretization Used in Their Primary Analysis Gordana, Buaeli, Josip Rubini Meteorological and Hydrological Service of Croatia Zagreb, CROATIA Abstract The present paper focuses on problems arising from changes in monitoring technology and methodology used for primary analyses of series of hydrological data of the same type primarily series of data on water levels and flow rates calculated from them. As consequence of such changes, inconsistencies are encountered in collected data series, which are particularly pronounced in data from hydrological stations on small torrential streams. The inconsistency of collected data is usually attributed to replacement of discrete water gauge reading of water levels with continuous water level recording. Another important change affecting consistency of collected data series is change in primary analyses of collected data that are stored in national hydrological databases. After the initial long-term period when the mean daily flow rates were determined directly from the data on mean daily water levels, the Croatian Meteorological and Hydrological Service (DHMZ) has been carrying out more precise hourly flow rate analyses since 2001. This paper uses several typical examples to analyse changes caused by the said modifications in monitoring and primary analyses method, and gives recommendations for use of available data series. Keywords: hydrological data, databases, primary analyses Introduction One of conditions for multi-annual series of hydrological data to be statistically analysed is that they are homogenous, which is often not the case. The non-homogeneity is generally attributed to man-induced changes in water regime, and too short time series available for analysis. However, it is often neglected that inconsistency of hydrological data series arises from differences in primary analyses of the observed data. Increased discretization of hydrological data results in growing precision in describing actual nature of the observed hydrological phenomena. Negative side effect is that consistency of earlier collected data series is disturbed. Large quantities of hydrological data are exchanged, often on large distances, and within greater regional areas. Thus, they often reach users (hydrological series analysts) which are not aware of changes in nature of primary analyses of the obtained hydrological data, and therefore do not respect them. Consequently, the available series are analysed and interpreted as a whole. The resulting quantitative changes are interpreted so that they are attributed to changes in water regime rather than to monitoring regime or primary data analyses. The present paper focuses on comparison of results obtained by different monitoring methods and primary hydrological data analyses, and on experience with and guidelines for work with the reference national hydrological database HIS2000 developed by the Croatian Meteorological and Hydrological Service. Examples of selected hydrological stations set up on torrential streams and on the streams with steady discharge regime were used for comparative analysis of flow rate results. Before level recording was introduced, mean daily flow rates were determined from regular daily one-time water level readings, which rarely reflected extraordinary daily readings outside the preset readout time (7.30 a.m.). After introduction of the level recorders, the Meteorological and Hydrological Service standard practice for quite a long period of time relied on determination of mean daily flow rates from the data on mean daily water levels. The than used database did not offer a possibility to store discrete data on characteristic daily values. Development of the new database HIS2000 (Bueli&Oskorua&Lovoaevi (2003); Buaeli, (2004)) enabled an extended entry and storing of hydrological data, including the hourly water levels, and hourly flow rates deduced from these values. This enabled more adequate quantification of observed hydrological events and reopened an issue of consistency of the series of collected data of the same type (water levels, flow rates, suspended load transportation). This does not resolve an issue of impact of input data time discretization. Changes in nature of monitoring technology enable registration of even more discrete time records of observed data, i.e. data within the time increment of one hour adopted in current practice. Currently, conventional water level recorders are being replaced with adequate electronic devices, which offer an option of registration within even shorter time intervals. The hydrological databases are generally characterised by series or tidily arranged data from individual hydrological stations. In their further hydrological analyses, it is often neglected that the described changes in monitoring methods and primary analyses happened during longer time periods. This paper presents several examples of data series on flow rates from different hydrological stations, with illustration of possible effect of changes on the hydrological analysis results. Although these are examples from the Croatian hydrological practice, we believe the neighbouring regions might find them interesting. The enhanced international exchange of hydrological data certainly resulted in analysis of the observed series of hydrological data by hydrologists from other countries which have no background information on the nature of the available hydrological data. Still, even the hydrologists who analyse their regional area frequently do not analyse the nature of the available series of hydrological data. This paper aims at highlighting the problem of consistency of the hydrological data series caused by different time discretization methods used in their primary analyses. Status of Monitoring and Resulting Primary Hydrological Data Analyses in Croatia On the Croatian territory, 440 hydrological stations are in operation of which 288 monitor flow rates. The stations most interesting for statistical analysis of hydrological data are those with long-term flow rate data series, usually series longer than 30 years. Croatia has 141 station with keep such data, of which 114 are in operation. Table 1 shows stations by catchment areas, as they are presented in the national hydrological database HIS2000. Table 1. Basic characteristics of hydrological monitoring in Croatia Catchment area No. of operating flow rate metering stations  Stations with flow rate data series > 30 years Databases on recording stations with series > 30 years ( year/station )  Total  Water gauging stations Water level recording stations Stations that started as water gauging, subsequently retrofitted with level recorders  Total  No. of years with flow rates analysed from water gauging results  No. of years with flow rates analysed from mean daily water levels No. of years with flow rates analysed from hourly water levelsDalmatia6925451699438052094Drava River2816201477231739263Istria, Primorje, G.Kotar region 37 23 2 12 9 873 136 666 71Kupa River493153231285429737119Lika region16114162869317617Sava River893546251582559908115Total288141212793579219143399479100%15%19%66%100%33%59%8% The above data illustrate that the stations which had been retrofitted from water gauging to level recording stations cover most of the Croatian territory (66%). Data on mean daily flow rates from the stations when they operated as water gauging stations account for about 33% of total collected flow rate data in the DHMZ database. The table indicates that dominant share of the stored data on mean daily flow rates is obtained from averaged daily water levels, and only 8% are the mean daily flow rates obtained from hourly flow rates. The results of analyses carried out below indicate that the problem of inconsistency of stored data series is present, and that the analysts should have this in mind when performing secondary hydrological analyses. Relation between Water Gauging and Level Recording Data Readings The more series of collected hydrological data go back into history, the higher the share of water gauging stations related to the level recording stations. The recording of the water levels at the Croatian territory started already in the mid-seventeenth century, but the first conventional water gauging hydrological station was established on the Sava River near Stara Gradiaka in 1817. Such a station on the Drava River near Vara~din was set up in 1821, and the one on the Sava near Zagreb in 1849. The longest continuous series of hydrological water level data stored in the HIS2000 database have been acquired from the Zagreb and Slavonski Brod stations, both on the Sava River (series since 1920). The longest series of continuous data on flow rates is the one from the Zagreb Station. Mean daily flow rates from this station stored in the recent database were analysed from the water gauging readouts for the period 1926-1955, from the level recording data on mean daily water levels analysis for the period 1956-2000, and from hourly water level data for the period 2001-2005. In this section, stored data on flow rates based on daily water gauging and mean daily water level recording are compared. The comparison was made for the same observation period (1954-2000) for two typical stations. The first is the BotovoDrava Station, taken to represent the stations on major rivers and the other is BuzetMirna Station, representing stations located on minor torrential streams characteristic for more pronounced daily flow rate changes. Since the differences in flow rate data are the most distinct for the high flow days, when changes are comparatively the fastest, comparison of results on flow rates obtained from the water gauging and level recording data are shown on an example of data series covering the highest recorded mean daily flows. For the period before the water level recording was introduced, only data on maximum mean daily flow rates from the daily water level readouts at standard morning time (7.30 a.m.), and sometimes averaged multiple readouts, were used. After the water level recorders were set up, the data have also been presented on maximum mean daily flow rates obtained from the morning water level readouts, and those obtained from the averaged hourly water levels for a particular date (Figure 1).  EMBED Excel.Chart.8 \s  Figure 1. Comparison of maximum mean daily flow rates at the Botovo-Drava and BuzetMirna stations (1960-2000). The above overview clearly points to the differences in calculated values of the mean daily flow rates obtained by the described methodologies used by different monitoring systems. These differences have a common characteristic, i.e. lack of precision in time discretization of the water level readouts makes the observed errors random errors. For the Botovo-Drava Station, this difference ranges from 0 to 20.1%, with an average value of 4.0 % and standard deviation of 3.6%. For The BuzetMirna Station, these differences are more pronounced. They are due to faster daily change in hydrological conditions which additionally underscores the effect of non-linear nature of consumption curves on calculated mean daily flow rates. For Buzet, the determined differences range from 0 to as much as 45.1%, with an average difference of 6.7% and standard deviation of these differences of 8.8%. Such differences, actually errors in assessment of mean daily flow rates based on the data collected from water gauges, as compared to the data obtained from the water level recorders, are of such magnitude that they could affect results of further secondary hydrological analyses of characteristic hydrological indicators. In our example, the said differences are shown using daily data on maximum recorded mean daily flow rates, and they relatively decrease with increase in period of time for which the characteristic averaged flow rates are determined, e.g. mean monthly or annual values. However, it should be noted that these differences also increase in relative terms when the catchments and flow rates are smaller and torrential characteristics of the stream higher. Relation of Analysed Data on Mean Daily and Hourly Water Levels The recent quality leap in primary analysis of hydrological data in Croatia was the made in 2001, since when the water level recording stations analyse mean daily discharges by averaging calculated hourly flow rates determined from the data on hourly water levels. Creation of the HIS2000 database enabled standardised entry and storing in the database of hourly water levels, and hourly flow rates derived from them by using consumption curves. Thus, the standard procedure used since for all the hydrological stations at the Croatian territory networked by the DHMZ is that the annual overview of mean daily flow rates is based on the hourly water levels. However, an alternative option is that the mean daily flow rates be derived from the data on mean daily water levels. Comparison of the mean daily flow rates resulting from use of these two methodologies indicates differences which, as a rule, point to deviation shown as increase in mean daily flow rates obtained from hourly flow rates (i.e. from direct functional relation of flow rates based on hourly water levels) as compared to the mean daily flow rates obtained from mean daily water levels. This is a systemic error caused by non-linear nature of relation between the water levels and flow rates, where the functions that describe that relation generally have more pronounced gradient with increase in water levels. Same as in the above case, the differences are more pronounced for small torrential streams with more intensive daily changes in water levels. This is shown in Table 2, with comparative presentation of calculated values of the highest mean daily flow rates for the BotovoDrava, the BuzetMirna and ButariButari stations (period 2001-2005). The latter station represents the stations set up on very small torrential streams (catchment area of only 5.5 km2). It was determined that during the analysed periods the difference between mean daily flow rates calculated from the data on the mean daily water levels and those calculated from the mean hourly flow rates was comparatively small, about 1%, both at the stations in very large catchments (BotovoDrava) and those in small catchments (BuzetMirna). However, the differences noticed at the Butari Station set up at the stream of the same name were very high and ranged between 11.3 and 50.7%, which was as much as 27.7% on average. Since the differences have the same sign, it is obviously a systemic error which causes that actual balance is underestimated when the flow rates are calculated from more frequently recorded (hourly) instead of the mean daily water levels. Table 2. Comparative presentation of differences in values of maximum mean daily flow rates calculated from mean daily and hourly water levels for the BotovoDrava, The BuzetMirna and ButariButari Stations (2001-2005) YearBotovo - DravaBuzet - MirnaButari ButariQ (m3/s) from mean daily Q (m3/s) from hourly Difference (%)Q (m3/s) from mean dailyQ (m3/s) from hourly Difference (%)Q (m3/s) from mean dailyQ (m3/s) from hourly Difference (%)2001107310800.622.222.40.90.9591.1919.42002142214230.138.538.60.32.043.3338.72003105410661.120.320.30.00.9591.1718.02004135113510.025250.01.721.9411.32005193819400.113.613.70.70.6891.4050.8average0.40.427.7 Differences noticed for Butari Station, namely for very small torrential streams it represents, are not evident only in individual daily events with more intensive flow rates (Table 2), but can also occur in mean monthly and even mean annual flow rates. Figure 2 illustrates the correlation between the mean monthly flow rates for the Butari Station calculated using both methodologies for the primary analysis of the water level records, i.e. mean daily and hourly water levels.  Figure 2. Comparative presentation of correlation between the mean daily flow rates for the ButariButari Station (2001-2005) calculated from hourly and mean daily water levels The correlation shown in Figure 3 is similar, only the corresponding calculated flow rates are shown in x-y chart. It is obvious that the flow rates derived from mean daily water levels have, as a rule, lower values compared to the flow rates derived from hourly water levels - they are placed below the straight line of value pairs of the same kind. The differences range from 0 to 100%, with average difference of 13.9 %, and standard deviation of 19.8%.  Figure 3. Correlation between mean daily flow rates at the ButariButari station (2001-2005) calculated from hourly and mean daily water levels Significant differences were also noted in analysed mean annual flow rate data for the Butari Station. The differences ranged between 11.8% (2005) and 24.0% (2002), with an average difference of 16.3 %. These values are several times higher than the allowed tolerance for the flow rate which is 5% (WMO, 1994). Therefore, it is obvious that in case the differences between the flow rates derived from hourly and those derived from mean daily water level data are significant, when switching to the new method of analysis (using hourly data) it is imperative to check historical data series analysed conventionally, on the basis of the daily water levels. Conclusion The paper relies on several characteristic examples to analyse issues related to creation on inconsistent flow rate data series due to changes in monitoring methods and primary analysis of the water level records during the station operation history. It has been determined that there are differences between characteristic hydrological data obtained from the water gauging and water level recording stations, and between the data from the water level recording stations calculated using hourly or mean daily water levels. These differences have to a certain degree character of a systemic error (in water level record analyses based on the mean daily water levels). Consequently, the errors accumulate and calculated values of the water balance decrease and even for the mean annual flow rates exceed 10-15%, while for shorter discretization intervals such errors may even be several times higher. To minimise such errors caused by insufficient time discretization of calculated flow rates, it is necessary to repeat primary analyses of the water level record data at least for the stations with more intensive daily water level fluctuation amplitudes, and to derive the mean daily flow rates from the mean hourly water levels. The hydrological database HIS2000 is designed so that, in addition to the stored data, it provides its users with additional information on nature of collected data and method of their analysis. The information is offered in textual and graphic form, and the users have access to sufficient information on the data themselves and their primary analyses. When such information is respected, it is possible to use the available stored flow rate data series adequately. When the users need it, it is possible to initiate additional analyses of historical data series by conducting flow rate analyses based on hourly water levels as input data. 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Such data can also be stored in the database provided the mean hourly flow rates are saved instead of hourly flow rates. However, the current priority is supplementing of the daily flow rate data series based on the hourly flow rates. References Buaeli, G., Oskorua, D., Lovoaevi, B., 2003: Development and Implementation of New Information System - HIS2000, 3rd Croatian Conference on Waters, Osijek, Croatia, 2003. Buaeli, G., 2004: HIS2000 Hydrological Informati"(,ďԏ֏ӽ|dQA4AhBB6CJOJQJaJhBBhBB6CJOJQJaJ%hBB6CJOJQJ^JaJmH sH .h* hBB56CJOJQJ^JaJmH sH "hN+2CJOJQJ^JaJmH sH "h*)h*)6CJH*OJQJaJh*)6CJOJQJaJh*)h*)6CJOJQJaJ+h*)h*)6CJOJQJ^JaJmH sH +h*)h;c6CJOJQJ^JaJmH sH +h*)hN+26CJOJQJ^JaJmH sH  "GHIUtyz{vpvevpaQEQh"0JCJOJQJjh"0JCJOJQJUh"h"0JmHnHu h"0Jjh"0JU+hBBhBB6CJOJQJ^JaJmH sH .h* hBB56CJOJQJ^JaJmH sH "hBBCJOJQJ^JaJmH sH %hBB6CJOJQJ^JaJmH sH h* 6CJOJQJaJUhBBhBB6CJOJQJaJhBB6CJOJQJaJon System, BALWOIS 2004 Conference, Ohrid, Republic of Macedonia, 2004. 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