THE ANDES BETWEEN PARALLELS 30° 50´ AND 39° 40´ OF SOUTH LATITUDE
3 AREA OF STUDY
This study focused in the area between parallels 34°50’S and 39°40’S. This is one of the main basins of the central-southern zone of Chile (Figure 2).
Figure 2. Area of study.
3.1 Mataquito River Basin
Mataquito River basin (Figure 3), extends from latitude 34°50’S by the North to 35°30’ by the South, creating part of the VII Maule Region and covering an area of 6,190 km2 (MOP, 2004).
3.2 Maule River Basin
Maule River basin (Figure 4), extends from 35°05’S by the North to 36°30’S by the South, covering an area of 20,295 km2, being the fourth largest one of the country. It is part of the VII Maule Region (MOP, 2004).
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3.3 Itata River Basin
Itata River basin (Figure 5) is located between 36°00’ and 37°20’ of South latitude. Is part of the VIII Biobío Region, and covers an area of 11,294 km2 (MOP, 2004).
3.4 Biobío River Basin
Biobío River basin (Figure 6) is located between parallels 36°42’S and 38°49’S. It is one of the largest basins, covering a total of 24,264 km2. It is mainly in the VIII Biobío Region, but it also occupies part of the Malleco province and Cautín province, which belong to the IX Region (MOP, 2004).
3.5 Imperial River Basin
Imperial River basin (Figure 7) extends from 37°40’S to 38°50’S. It is part of the IX Araucanía Region and it has an extension of 12,763 km2. It takes place mainly west of the Biobío River high basin (MOP, 2004).
3.6 Toltén River Basin
Toltén River basin (Figure 8) extends from 38º40’ by the North to the latitude 39º40’ by the South. It is part of the IX Araucanía Region and it has an extension of 8,398 km2, being relatively small (MOP, 2004).
Figure 3. Mataquito River basin. Figure 4. Maule River basin.
Figure 5. Itata River basin. Figure 6. Biobío River basin.
Figure 7. Imperial River basin. Figure 8. Toltén River basin.
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4 METHODOLOGY
Firstly, once the area of study was determined, the existent information was reviewed. In the case of floods, data respecting height and instant flow was used and in the case of maximum precipitations, the data was formed by a series of rain gauge stations that had daily registers of the last 30 years.
After that, the stations used in this study were selected. In order to do that, a series of criteria that had to be met were defined. In the case of floods there was:
a) Stream gauging stations with limnological data.
b) Data of 30 years.
c) The most important floods was to be correctly registered, especially the flood of July 2006.
d) They must belong to rain gauge basins from the same hydro-meteorological event.
e) The maximum flood events should not be controlled by lakes, dams, etc.
Once the stations were chosen, the annual maximum series, the annual excess series and the partial duration series with up to 4 times the amount of data per year registered were created.
Firstly, with the series of annual maximum, a graphical analysis was carried out. The behaviour of moving averages with a window of 15 years was studied and a trend line was added to observe the gradient.
Then, in order to make a statistic analysis, the non-parametric Mann-Kendall test was run to the annual maximum series. The null hypothesis is that there is no trend in the series, and the alternative hypothesis is that there is, this for a trusted interval of 95%.
Finally, three-dimensional graphics were created, where the stations were arranged by latitude and 95%
of maximum floods were represented using the partial duration series. The magnitude of each flood is shown in the diameter of the point in the graphic. In order to make a better analysis, the flow values were normalized by the maximum value of each station. These graphics were developed for station with 30 years’ worth of data, and for stations with 40 years.
In the case of stations with precipitation measurements, the following criteria was to be followed: (a) have 30 years of daily continuous register of data, (b) each station has to have the most amount of data per year, a minimum of 11 registered months.
After choosing the stations, a consistency analysis was made through double mass curve analysis with the purpose of detecting possible mistakes in the translation of data collected in site, situation that affects the representation of the register; this with the aim of correcting the statistic if necessary.
Afterwards, a statistic gap filling was made on the days that didn’t present precipitation measurement through rain gauge modules in order to have data 365 days of the year.
Once the register was completed, to find the daily maximum precipitation with T=10 days the following steps were applied to each rain gauge station: The 365 days of each year of the 30 years of data were observed and their daily precipitation value was examined, registering only the highest. This way for each year of the 30 years of data a daily maximum precipitation value (DMP) was obtained, therefore, for each station there are 30 different DMP values. Then, the 30 values were entered into the software “Easyfit”, which adjusted different “probability functions” (Gamma, Lognormal 3p, Pearson, Gumbel max, etc.) to the 30 values of each station.
Later on, the Kolmogorov-Smirnov goodness-of-fit test was run to each probability function and based on the test results the probability function that best adjusted the data was selected. That way, using said function, the precipitation value that exceeds only 10% of the time was found, that means the value associated to a return period of 10 years.
With these precipitation values a map of isohyets was made throughout the area of study with the SIG Arcgis.
Finally, these daily maximum precipitation values associated to T=10 years were compared with the daily maximum precipitation values of an official study carried out by the Dirección General de Aguas (DGA) in 1991 called Precipitaciones máximas en 1,2 y 3 días with the aim of knowing the variations in the last years of this variable.
5 RESULTS
In relation to the basins, regarding the aforementioned criteria, a total of 26 stations were selected, which are detailed in Table 1. In each basin, a number of stations was used: 3 in Mataquito Basin (34°50´-35°30´S), 7 in Maule Basin (35°05´-36°30´S), 4 in Itata Basin (36°00´-37°20´S), 7 in Biobío Basin (36°42´-38°49´S), 4 in Imperial Basin (37°40´-38°50´S) and 2 in Toltén Basin (38°40´-39°40´).
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Table 1. Selected Station for the study. (*) Year in which limnological data starts.
Rain gauge station number
Basin Station Latitude
(S)
Longitude (W)
Height (m a.s.l.)
Starting year (*)
Duration (years) Mataquito Teno después de junta con Claro 34°59´46´´ 70°49´14´´ 647 1961 53 Mataquito Palos en Junta con Colorado 35°16´28´´ 71°00´56´´ 600 1967 47 Mataquito Colorado en junta con Palos 35°16´42´´ 71°00´10´´ 600 1967 47 Maule Claro en Camarico 35°10´42´´ 71°23´05´´ 220 1969 45 Maule Lircay en Puente Las Rastras 35°29´08´´ 71°17´36´´ 240 1977 37 Maule Loncomilla en Las Brisas 35°37´01´´ 71°46´04´´ 68 1984 30 Maule Ancoa en el Morro 35°54´31´´ 71°17´53´´ 402 1960 54 Maule Longavi en la Quiriquina 36°13´49´´ 71°27´25´´ 449 1952 62 Maule Perquilauquen en San Manuel 36°22´33´´ 71°37´24´´ 266 1953 61 Itata Ñuble en La Punilla 36°39´30´´ 71°19´15´´ 635 1965 49 Itata Diguillin en Longitudinal 36°52´00´´ 72°20´00´´ 80 1981 33 Itata Diguillin San Lorenzo 36°55´28´´ 71°04´32´´ 727 1959 55 Itata Itata en Cholguan 37°09´00´´ 72°04´00´´ 220 1962 52 Biobío Biobio en Desembocadura 36°50´19´´ 73°03´43´´ 16 1963 51 Biobío Duqueco en Villucura 37°33´00´´ 72°02´00´´ 228 1963 51 Biobío Biobio en Rucalhue 37°42´38´´ 71°54´06´´ 261 1971 43 Biobío Lirquen en Cerro el Padre 37°46´32´´ 71°51´46´´ 340 1963 51 Biobío Mininco en Longitudinal 37°51´49´´ 72°23´39´´ 125 1963 51 Biobío Malleco en Collipulli 37°57´53´´ 72°26´10´´ 153 1977 37 Biobío Lonquimay antes de junta con Biobio 38°26´00´´ 71°14´00´´ 901 1985 29 Imperial Lumaco en Lumaco 38°09´00´´ 72°54´00´´ 70 1975 39 Imperial Cautin en Rari Ruca 38°25´49´´ 72°00´38´´ 425 1979 35 Imperial Cholchol en Cholchoñ 38°26´29´´ 72°50´52´´ 20 1964 50 Imperial Quepe en Quepe 38°51´00´´ 72°37´00´´ 80 1975 39 Tolten Liucura en Liucura 39°15´22´´ 71°49´28´´ 402 1977 37 Tolten Trancura antes de río Llafenco 39°20´00´´ 70°46´00´´ 386 1987 27
When the annual maximum series (Fig. 9, 10, 11, 12), their moving averages with a window of 15 years and trend lines were analysed, the result was that of the 26 stations, 13 present a positive trend (Fig. 9, 10), 5 don’t present a noticeable trend (Fig. 11), and 8 have a negative trend (Fig. 12). For each basin, the results are detailed in Table 2.
Figure 9. Annual Maximum Graph, with their moving averages (15) and trend line for the Colorado en junta con Palos station. Positive
trend.
Figure 10. Annual Maximum Graph, with their moving averages (15) and trend line for Perquilauquén en San Manuel station. Positive
trend.
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Figure 11. Annual Maximum Graph, with their moving average (15) and trend line for Lirquén en Cerro El Padre station. A significant trend is not seen.
Figure 12. Annual Maximum Graph, with their moving averages (15) and trend line for Quepe en Quepe station. A negative trend is seen.
The graphic results of trends are summarised in Table 2.
Table 2. Graphic analysis of trends by basins.
Basin Positive
Trend No Trend Negative Trend
Mataquito 3 0 0
Maule 3 2 1
Itata 4 0 0
Biobío 1 3 3
Imperial 0 0 4
Toltén 2 0 0
Total 13 5 8
In the case of maximum precipitations, a total of 72 stations were selected following the criteria previously defined. The geographic distribution of the stations can be seen in Figure 13.
The daily maximum precipitation of the area is represented in Figure 14, where the isohlines in red represent the isohlines calculated with data of the last 30 years, and the isohyets in green correspond to the study carried out by the DGA in 1991.
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Figure 13. Geographic distribution of rain gauge stations.
Figure 14. Isohyets of daily maximum precipitation.
When analysing the changes in maximum precipitations, all localities that have a rain gauge station were taken into account. It is important to point out that many of the main localities of the area didn’t have a precipitation measuring station; therefore, it was impossible to use them in the analysis. That way, the number of examined stations decreased significantly and comparatively it was much lower than the total of stations that were used in the study.