meteorological baseline report assessment of rainfall intensity

Meteorological Baseline Report

Assessment of Rainfall Intensity, Frequency and Runoff for the Rosia Montana Project

Prepared for:

S.C. ROŞIA MONTANĂ GOLD CORPORATION S.A.

Prepared by:

RADU DROBOT

Environmental Impact Study: Meteorological Baseline Report

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Table of Contents 1 Executive Summary.................................................................................................... 5 2 Introduction ................................................................................................................ 7 3 Methodology............................................................................................................. 15

3.1 Maximum Precipitation ...................................................................................... 15 3.2 Snowmelt .......................................................................................................... 17 3.3 Probable Maximum Precipitation (Pmp).......................................................... 19 3.4 Runoff Coefficients ............................................................................................ 23

4 Analyses................................................................................................................... 26 4.1 Maximum Precipitation ...................................................................................... 26 4.2 Snowmelt .......................................................................................................... 28 4.3 Probable Maximum Precipitation (Pmp).......................................................... 29 4.4 Runoff Coefficients ............................................................................................ 29

5 Findings and Conclusions ........................................................................................ 31 6 References............................................................................................................... 32 Table of Figures Figure 2.1 Zone of maximum hourly precipitation in Romania (Diaconu and al, 1995) .......... 8 Figure 2.2 Maximum precipitation worldwide (Maidment, 1993) ............................................ 8 Figure 2.3 Outstanding rainstorm recorded in Romania (Stanescu and Drobot, 2002)........ 10 Figure 2.4 Regionalization of Romania (Diaconu and Serban, 1994) .................................. 12 Figure 2.5 Rationalization of S1% (Diaconu and all, 1995) .................................................. 13

Figure 2.6 Regionalization of the index n (Diaconu and all, 1995)....................................... 14

Figure 3.1 The degree-day factor M to be used with maxT ................................................... 17

Figure 3.2 The degree-day factor M’ to be used with medT .................................................. 18

Figure 3.3 Identification of the critical month based on the envelope curves ....................... 19 Figure 3.4 Variation of K as a function of the mean extreme precipitation and rainfall duration (after Hershfield; taken from WMO, 1973). ............................................................ 21

Figure 3.5 Adjustment 1f of mean value (after Hershfield; from WMO, 1973).................... 22

Figure 3.6 Adjustment 2f of standard deviation (WMO, 1973)............................................ 22

Figure 3.7 Adjustment 3f of mean and standard deviation for length of record................... 22

Figure 3.8 Effective Rainfall ................................................................................................ 23 Figure 3.9 Runoff coefficient range ..................................................................................... 25 Figure 4.1 Area subject to detailed analysis ........................................................................ 26 Figure 4.2 Distribution of the summer extreme 24 h precipitation........................................ 27 Figure 4.3 Distribution of the winter-spring extreme 24 h precipitation................................. 28 Figure 6.1 Runoff coefficient - Light texture soil................................................................... 40 Figure 6.2 Runoff coefficient Average texture...................................................................... 41 Figure 6.3 Runoff coefficient Heavy texture......................................................................... 42


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Table of Tables Table 1-1 Comparison of extreme precipitation ..................................................................... 6 Table 2-1 Maximum depth for 24 hour rainfall events............................................................ 7 Table 2-2 Maximum depths for 24 hour precipitation and snowmelt events........................... 7 Table 2-3 Extreme 24 hours precipitation registered in Romania between 1886-1997 .......... 9 Table 2-4 Extreme precipitation in Romania........................................................................ 11 Table 2-5 Regionalization of Romania (Diaconu and Serban, 1994) ................................... 12 Table 3-1 Relevant Meteorological station in the area......................................................... 15 Table 3-2 Station period of record....................................................................................... 15 Table 3-3 Storm duration conversion coefficients................................................................ 16 Table 3-4 Runoff Coefficients.............................................................................................. 24 Table 4-1 Frequency analysis ............................................................................................. 27 Table 4-2 Estimated maximum temperature........................................................................ 28 Table 4-3 Estimated PMP ................................................................................................... 29 Table 6-1 Winter storm + snowmelt (15-min to 3-day duration) ........................................... 34 Table 6-2 Summer storm (15-min to 3-day duration)........................................................... 36 Appendixes APPENDIX 1 Precipitation, Snowmelt, Runoff Tables......................................................... 33 APPENDIX 2 Runoff Coefficients........................................................................................ 39 APPENDIX 3 Monthly Precipitation Data from Abrud, RMGC-Roşia Montană, Rotunda- Roşia Montană Stations...................................................................................................... 43


Section 1: Executive Summary

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1 Executive Summary A number of hydrological studies were performed in the past to evaluate 24-hours extreme rainfall and snowmelt events for the Rosia Montana project: Knight Piésold (2001), INMH (2002) and INMH (2003). The values reported in previous studies were compared to recorded 24-hour precipitation values in Romania over the last 100 years. The comparison suggested that the previously reported Probable Maximum Precipitation (PMP) were likely significantly underestimated. Furthermore, comparison with usually accepted 100-yr precipitation in Romania indicated that other design precipitation values proposed by Knight Piesold (2001) and INMH (2003) might have also been underestimated. Given the importance and scale of the proposed project, MWH/RMGC have commissioned in 2004 another independent hydro-meteorological study to resolve these important design parameters The study included spatial distribution assessment of extreme historical precipitation over Romania and data collection and statistical analysis of the record from 21 meteorological stations located in a 60-km radius around the Rosia Montana site The most significant historical event is the recorded 262 mm 24-hr precipitation in Deva (July 1936), only 50 km south from the Rosia Montana site. This recorded event is comparable to the PMP reported in previous studies. Based on statistical analyses of the 21 regional stations over a 16-year common period of record, 10 stations were selected as representative for the Rosia Montana site and a full station record was obtained and analyzed for those stations. The analysis was carried out for two distinct periods: summer from May to November, and winter from December to April. The winter precipitation values were then combined with the maximum snowmelt value, calculated using day-degree method. By analysis of the snow cover at the Rosia Montana site, snow density and recorded temperatures, it was found that March and February are critical snowmelt periods. The derived 24-hr precipitation and snowmelt values for the two seasons were then converted to different duration events (15 minutes to 3 days) using accepted regional conversion coefficients. Main finding of the study are shown in Table 1-1, comparing the results of the study with previous studies for the Rosia Montana site. The results indicate the following:

The PMP was underestimated in previous studies. The new values are almost 2 times higher compared to previous estimates;

Summer extreme precipitation is higher than winter one. Summer PMP is similar to the winter PMP combined with extreme snowmelt. Critical snowmelt months are March and February;

Other design precipitations are somewhat lower compared to the values proposed by SNC Lavalin report (2002), but they are higher then the values proposed by Knight Piesold (2201) and INMH (2003).


Section 1: Executive Summary

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Table 1-1 Comparison of extreme precipitation

Knight Piesold (2001)

SNC (2002) INMH (2003) Drobot/MWH (2004)

ARI

Probability of exceedence in

17 years Rainfall Summer

Rainfall

Winter Rainfall+ Snowmelt

Rainfall Summer Rainfall

Winter Rainfall + Snowmelt

100 15.7% 78 132 137 88 112 122 500 3.3% 102 155 163 146 147

1,000 1.7% 115 166 176 112 161 158 10,000 0.2% 169 209 227 138 211 191

100,000 0.0% 263 293 PMP 249 450 440

The study also briefly assessed runoff coefficients during design storm events. Runoff coefficients for small basins vary generally from 35% to 80% and they are a function of the basin slope, forest cover, soil texture and Anterior Precipitation Index (API). The latter represents a measure of the soil humidity resulting from previous precipitation. The winter PMP runoff could theoretically occur immediately after or concurrently with significant snowmelt, in which case a high API coefficient, and consequently a high runoff coefficient could be expected. For that reason, the winter PMP runoff coefficient of 90% was proposed. A higher winter runoff coefficient could be expected in situations of frozen ground and frozen snow cover, but it would not be justified to combine this PMP scenario with the with the maximum snowmelt. As for the summer PMP, a maximum runoff coefficient of 80% is considered reasonable. In both cases, a 100% runoff coefficient should be used for water surface and over impervious areas. Maximum runoff coefficients for other design events were also assessed in the study and they range from 30% to 45% for 10-year return period, 35% to 60% for 100-yr and 50% to 70% for 1,000-yr or higher return period. The limits of the ranges correspond to the shortest and the longest rainfall duration, respectively.


Section 2: Introduction

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2 Introduction A number of hydrological studies were previously carried out to evaluate 24-hours extreme rainfall events for the Rosia Montana project: Knight Piésold (2001), INMH/SNC-Lavalin (2002) and INMH (2003). The maximum depth for 24 hour rainfall events derived by these studies are presented in Table 2-2. Some of the values were extrapolated by SLE&C, as marked in the table. Table 2-1 Maximum depth for 24 hour rainfall events

Hourly rainfall INMH (2002)

hourly rainfall Knight Piésold (2001)

hourly rainfall INMH (2003)

Return period (years)

Depth (mm)

Remarks Depth (mm)

Remarks Depth (mm)

2 - - 38 Reported 44.6 25 - - 65 Reported 72 50 - - 71 Reported 80.6 100 132 SLE&C 78 Reported 87.8 500 155 SLE&C 102 SLE&C

1,000 166 Reported 115 SLE&C 112.3 10,000 209 Reported 169 SLE&C 138.2 100,000 263 SLE&C - - -

PMP - - 249 Reported 249 Maximum depths for 24 hour precipitation and snowmelt events are presented in Table 2-3. Table 2-2 Maximum depths for 24 hour precipitation and snowmelt events

Depth for 24 hours event Return period (years) Precipitation (mm) Snowmelt (mm) Total

(mm)

Remarks

100 - - 137 SLE&C 500 - - 163 SLE&C

1,000 126 50 176 INMH (2002) 10,000 162 65 227 INMH (2002)

100,000 - - 293 SLE&C These values were compared with the commonly used values for hourly and 24- hour precipitation for the 100-year return period in Romania. In the usual practice of INMH, one considers the hourly precipitation for the 100- year return period to be in the range 100-130 mm (Figure 1). Based on accepted duration conversion factors, this corresponds to a 24-hour precipitation of in the range of 120-160 mm.



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Figure 2.1 Zone of maximum hourly precipitation in Romania (Diaconu and al, 1995)

The maximum intensity in Romania was registered at Curtea de Arges: more than 200 mm in about 20 minutes. This is the highest intensity 20-min precipitation recorded anywhere in the world, as shown in Figure 2.2. Figure 2.2 Maximum precipitation worldwide (Maidment, 1993)



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Furthermore, historical data show that significant storm events occurred over Romania, as shown in the Table 2-4. The table 2-4 lists 90 maximum 24-hour precipitations recorded in the country in the period 1896-1997. Table 2-3 Extreme 24 hours precipitation registered in Romania between 1886-1997

This is supplemented by data on outstanding rainstorm recorded in Romania (Stanescu and Drobot, 2002), shown in Figure 2.3 and Table 2-5.



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Figure 2.3 Outstanding rainstorm recorded in Romania (Stanescu and Drobot, 2002)



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Table 2-4 Extreme precipitation in Romania

Date

Location Depth of rainstorm

(mm)

Duration

29/30.08.1924 Casimcea Bestepe 650 24h 26.06.1925 Ciuperceni- Dolj 348.9 24h 19.06.1924 Fundata-Brasov 306 24h 16.06.1938 Cârlibaba-Suceava 280.4 24h 10.06.1901 Surdila-Gaiseanca 266 24h 09.07.1934 Deva 262 24h 05.09.1912 Vatra Dornei 260 24h 07.07.1889 Curtea de Argeº 226.3 24h

29/30. 08.1924 Sulina 239.5 17h 29/30.08.1924 Letea-Tulcea 691 16h

30.08.1924 Caraomer_Constanta 320 4h 30.08.1924 Sarichioi-Tulcea 243 3-5h

29/30. 08.1924 Sulina 239.5 3-4h 17.08.1900 Caraomer-Constanta 300 4h 13min. 14.06.1889 Radeni-Botosani 122 4h 30min. 10.06.1901 Surdila-Gaiseanca 200 4h 25min. 21.o6.1979 Lucieni-Dambovita 260 2h

28/28. 07.1991 Livezi-Bacau 149 2h 30min. 12.07.1999 Lunca Tomeasa 136 2h 27.05.1897 Piria-Mehedinti 145.2 2h 30min. 02.06.1897 Piria-Mehedinti 98 2h

28/29.07.1991 Lucacesti-Bacau 95.5 2h 21.06.1979 Tatarani 256 2-3h 07.07.1889 Curtea de Arges 204.6 20min. 02.06.1897 Piria-Mehedinti 180.5 35min 09.06.1999 Laslea-Mures 52 30min. 29.07.1991 Solont-Bacau 56.1 20min. 24.06.1889 Cuzganu-Constanta 80 30min. 02.08.1997 Paltinu-Prahova 35 15min 28.06.1889 R.Sarat 35 6min

Quite recently, in 1999 at Raul Mare – Retezat, a storm of 190 mm over 2 hours was estimated based on the increase in the reservoir level (Solacolu, 2000). Diaconu and Serban (1994) based on spatio-temporal probabilities of exceedance and regionalization studies (Figure 2.4) provided among other values, the extreme precipitation for 24 hours for small basins below 10 km2 (Table 2-6).



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Figure 2.4 Regionalization of Romania (Diaconu and Serban, 1994)

Table 2-5 Regionalization of Romania (Diaconu and Serban, 1994)

According to the above reference, Rosia Montana is located in the zone 2A. For example, for 1% probability of exceedance the daily extreme precipitation in the area is evaluated at 201 mm. This value has to be considered with some reserve due to the scale of investigation,



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which did not allow detailed assessment of local aspects like the orographic influence, the variation of heavy precipitation with altitude or foehn effects. Diaconu and others (1995), using a different methodology, provided isoline maps, based on evaluation of concentration times and the point maximum instantaneous precipitation. The reference suggests computation of the average intensity of 1% probability precipitation using the following relation:

( )nctS

i1

%1%1

+= (mm/min)

where: S1% is the instantaneous intensity for 1% rain (Figure 5) n - reduction index of the rain intensity (Figure 6). ct - concentration time. Figure 2.5 Rationalization of S1% (Diaconu and all, 1995)



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Figure 2.6 Regionalization of the index n (Diaconu and all, 1995)

For small basins under 10 km2, like Corna, considering the concentration time of about 1 hour, for n = 0.5 and S1% = 12, the computed 1% rain intensity is %1i = 1.5 mm/min, i.e. 90 mm/hour, having an equivalent of 112-115 mm/24 hours. The above considerations suggest that proposed 24-hour extreme precipitation for 100-year return period of below 100 mm are likely underestimated, as it is the case with values provided by Knight Piésold (2001) and INMH (2003) reports. Furthermore, different values provided by different previous studies and the scale of the project warranted a more detailed look into the extreme precipitation events at the Rosia Montana site.


Section 3: Methodology

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3 Methodology 3.1 Maximum Precipitation

20 meteorological stations, located from 6 to 57 km from the Rosia Montana site, were identified for the study, as shown in Table 3-1. Table 3-1 Relevant Meteorological station in the area

Station Distance (km)

Station Distance (km)

Abrud 6 Intregalde 22 Alba Iulia 43 Mogos 12 Albac 21 Scarisoara 27 Arieseni 35 Stana de Vale 57 Avram Iancu 26 Stei 57 Baia de Aries 14 Tebea 35 Baisoara 29 Turda 57 Bistra 8 Vidra 20 Cheia 29 Vladeasa 57 Deva 51 Zlatna 22

These stations have record for different time intervals, starting from 1895; sometimes, the record is discontinued with a number of gaps in the time series. Rosia Montana station, located above the proposed project site, has a precipitation record since 1983. A common period of record for all 21 stations (including Rosia Montana station) is from 1983 to1998. Analyses comprised the following steps:

a. First, spatial distribution of the average and standard deviation values of the annual maximum 24-hr precipitation was carried out for the 21 stations. This step resulted in selection of 8 stations with similar average and standard deviation values to the Rosia Montana station: Abrud, Albac, Avram Iancu, Baia de Aries, Bistra-Campeni, Mogos, Tebea, Zlatna. The corresponding period of record for the selected stations is presented in Table 3-2.

Table 3-2 Station period of record

Abrud Albac Avram Iancu

Baia de Aries Bistra Mogos Tebea Zlatna

1895-1915 1950-1960 1949-1978 1890-1904 1963-1971 1950-1956 1963-1982 1890-1918

1923-1941 1979-1982 1980-1982 1908-1910 1972-1982 1961-1975 1999-2003 1922

1946-1960 1983-1998 1999-2000 1935-1938 1999-2003 1977-1982 1983-1998 1927-1932

1974-1975 1983-1998 1940-1964 1983-1998 1983-1998 1934-19371978-1982 1974-1975 1939-19641983-1998 1977-1982 1973-1975 1983-1998 1977-1982 1983-1998

Additionally, maximum daily precipitation for the stations Alba-Iulia (1881-1900; 1923-1998) and Deva (1921-1998) were used for the detailed analyses.



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b. Detailed statistical analyses using Gumbel and Person III distributions were performed for the selected stations, considered to belong to the statistically homogeneous group. Distinct statistical analyses were made for the winter season (November-March) and the summer season (April-October).

Annual maximum 24-hr precipitation for different probabilities of exceedance (0.01%, 0.1%, 0.2%, 0.5%, 1%, 2%, 4%, 5%, 10%, 20% and 50%) were obtained using the following approach:

a) Each station was analyzed individually; for every probability of exceedance the design value of the precipitation was obtained as:

• the maximum 24-hr precipitation value for all stations, resulting in an envelope

of the highest values; • inverse or inverse square distance weighted value.

b) For each year, the maximum recorded 24-hr precipitation at all stations was retained

for statistical analyzes; this approach is justified by the fact that the stations are situated in a very compact area, so every station could have been hit by the maximum annual event. Due to the fact that the envelope of the computed values for different probabilities of exceedance and the inverse distance weighted lead to inconsistent results, only the results obtained through the b2) method were presented in this report. After obtaining the values of the 24-hr precipitation corresponding to the mentioned probabilities of exceedance, precipitation for different other duration (15’, 30’, 1h, 2h, 3h, 6h, 12h, 1 day, 2 days and 3 days) were obtained using conversion coefficients given in Table 3-3 (C. Diaconu and P. Serban, Sinteze si Regionalizari Hidrologice, Ed. Tehnica, 1994, page 251). Given the location of the Rosia Montana site (see Figure 2.4), average values of the zones A and B was used.

Table 3-3 Storm duration conversion coefficients



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3.2 Snowmelt

• Degree-day method was used for the snowmelt estimate . Two methods are

commonly accepted: Based on maxT - the maximum daily temperature (P. Serban, V. Al. Stanescu, P.Roman - Hidrologie Dinamica, Ed. Tehnica, 1989 – pages 73-74): ( ) maxmax TMTTMh emelted ⋅≈−= where : eT is the equilibrium temperature (which can be considered equal to zero); maxT - the maximum daily temperature; M - the degree-day factor or the melting factor to be used with maxT (mm/0C day), represented in Figure 3.1. Figure 3.1 The degree-day factor M to be used with maxT

Based on medT - the medium daily temperature (R. Drobot, P. Serban – Aplicatii de hidrologie si gospodarirea apelor, Ed. HGA, 1999 – pages 8-9):

( ) medemedmelted TMTTMh ⋅≈−⋅= ''

where : eT is the equilibrium temperature (considered equal to zero); medT - the average daily temperature; M’ - the degree-day factor to be used with medT (mm/0C day), represented in Figure 3.2.



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Figure 3.2 The degree-day factor M’ to be used with medT

The two methods generally produce similar results. Due to the availability of maximum daily record at the Rosia Montana station, the first method was used.

• For each month of the winter period for which positive temperature can occur, the maximum value was selected; a frequency analyses lead to the maximum daily positive temperature for different return periods.

The water content of the melted snow is obtained with the relation:

maxTMhmelted ⋅= It has to be mentioned that meltedh represents the potential value of the melted snow (expressed in form of the water content); the effective value depends of the snow availability. Thus, even if April is the critical month concerning the positive temperature and the value of the degree-day coefficient, due to the small reserve of the snow in the basin in fact the critical months are March and February, when both significant snow cover and positive temperatures can be expected Figure 3.3).



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Figure 3.3 Identification of the critical month based on the envelope curves

The historical snow depth was 740 mm in March 1999, while the maximum water content for the same month was 163 mm in 1984. In April, the corresponding values are: 42 cm of snow in 1966, respectively 86 mm water content in the same year. On the other hand, historical snow depth presents 950 mm snow cover in February 1999, and a maximum water content of 189 mm in February 1987, but the positive temperature values are lower compared to March. Thus, for 2 and 3 days evaluation of the snowmelt equivalent water content , the analyses was based on March.

• For 2 days period the water released by the snowmelt is obtained with the relation: ( )2max1max2max1max2 TTMTMTMh dayssnowmelt +⋅=⋅+⋅=

• For 3 days period a similar relation was used: ( )3max2max1max3 TTTMh dayssnowmelt ++⋅= A frequency analyses for March indicate that the available water content in the snow is always higher than the potential value of the melted water computed with the degree-day method even for 3 days duration. If this were not the case, the effective released water would be the minimum of the potential melted water and the available water in the snow depth. For durations lower than 1 day (15’, 30’, 1h, 2h, 3h, 6h) it was considered that the melting generally occurs during daytime (8h-16h). A fractional value of the water released daily by snowmelt was assigned for each of the time intervals.

3.3 Probable Maximum Precipitation (Pmp)

Statistical procedures for estimating PMP may be used wherever sufficient precipitation data are available or where other meteorological data, such as storm radar data, dew point or wind records, are unavailable.



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Taking into account the precipitation record from the surrounding stations, extreme 24 h precipitation record is available for over 100 years. However, storm pattern, dew point and the wind records were not available. Despite some issues that the statistical PMP estimate may arise, it was the only available approach for the data available. From the different statistical methodologies, Hershfield’s procedure received the widest acceptance (WMO, 1973, 1986). An important number of recent studies (mentioned by Koutsoyiannis, 1999) use different statistical approaches for the PMP estimate. PMP is defined as “theoretically the greatest depth of precipitation for a given duration that is physically possible over a given size storm area at a particular geographical location at a certain time of the year” (WMM, 1986). In a first attempt to derive the project PMP, the Hershfield’s procedure was performed for each of the 20 stations. This approach was still not considered consistent with the international practice; thus, in Australia and United States the PMP occurrence is associated with large areas having dozens or even hundreds of thousands square kilometers. In such conditions, an average value of the PMP obtained for 5 representative stations (Abrud, Arieseni, Avram Iancu, Deva and Stana de Vale) was considered. As representative stations were considered those having registrations for a large period (like Abrud, Avram Iancu, Deva) or having recorded important extreme precipitation or high values of average and standard deviation for 24 hours extreme precipitation (Deva, but also Arieseni and Stana de Vale). The computation was made distinctly for summer and winter periods. Hershfield’s procedure (WMO, 1973) is based on the well-known relation of the frequency analyses (Ven Te Chow, 1961):

nnT SKXX ⋅+= where: TX is the rainfall for the return period T;

nX - mean of the series of n annual maxima ; nS - standard deviation of the same series ; K - a frequency variable, which depends on the statistical distribution fitting extreme values hydrologic data. To derive PMP, records from 2 600 stations were used for the determination of an enveloping value of K. These values, depending on the storm duration, are presented in figure 3.4. A maximum value of 20 can be considered for K.



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Figure 3.4 Variation of K as a function of the mean extreme precipitation and rainfall duration (after Hershfield; taken from WMO, 1973).

Unreasonable values of PMP can be obtained due to the occurrence by pure chance of an extreme value having a very low probability of exceedance (like 0.1% in a series of 100 years). To diminish the influence of such an outlier on the mean and the standard deviation, adjustments were proposed by Hershfield to be made to nX and nS . In figures 3.5 and 3.6,

mnX − and mnS − refer respectively to the mean and standard deviation of the annual series after excluding the maximum registered value. Another adjustment of nX and nS is made to take into account the sample size (Figure 3.7). By applying these corrections, the parameters nX and nS from Ven Te Chow relation will

be replaced by cornX and cor

nS given by:

( ) ( )nfXXfXX nmnncorn 31 / ⋅⋅= −

( ) ( )nfSSfSS nmnncorn 32 / ⋅⋅= −



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Figure 3.5 Adjustment 1f of mean value (after Hershfield; from WMO, 1973).

Figure 3.6 Adjustment 2f of standard deviation (WMO, 1973).

Figure 3.7 Adjustment 3f of mean and standard deviation for length of record



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3.4 Runoff Coefficients

In the most general manner (Figure 3.8) the runoff coefficient α is defined as the ratio between the depth of runoff (effective or net rainfall noted nh ) and the rainfall depth (global rainfall noted bh ). Thus:

b

nhh

=α

Figure 3.8 Effective Rainfall

The runoff coefficients for small basins vary generally in the range 0.35 – 0.80 (Table 3-4, Figure 3.9 and Appendix 2), being function of the basin slope ( Ib %), forestation degree ( Cp %), soil texture (light, average and heavy) and Anterior Precipitation Index (API) as a measure of the influence of precipitation produced during previous days.

Rai

nfal

lIn

filtra

tion

inte

nsity

Duration [min]

Effective rainfall

Infiltrated rainfall

Infiltration capacity



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Table 3-4 Runoff Coefficients

• Light texture

Cp %

Ib %

0 - 20

20 - 40

40 - 60

60 - 80

80 – 100

5 - 10 0,44 0,42 0,40 0,38 0,36 10 - 20 0,46 0,44 0,42 0,40 0,38 20 - 30 0,48 0,46 0,44 0,42 0,40 30 - 40 0,50 0,48 0,46 0,44 0,42 40 - 50 0,52 0,50 0,48 0,46 0,44

• Average texture

Cp %

Ib %

0 - 20

20 - 40

40 - 60

60 - 80

80 – 100

5 - 10 0,55 0,53 0,51 0,49 0,47 10 - 20 0,57 0,55 0,53 0,51 0,49 20 - 30 0,59 0,57 0,55 0,53 0,51 30 - -40 0,62 0,60 0,58 0,55 0,53 40 - 50 0,64 0,62 0,60 0,57 0,55

• Heavy texture

Cp %

Ib %

0 - 20

20 - 40

40 - 60

60 - 80

80 – 100

5 - 10 0,66 0,63 0,61 0,58 0,56 10 - 20 0,69 0,66 0,63 0,60 0,57 20 - 30 0,73 0,69 0,66 0,63 0,60 30 - 40 0,75 0,72 0,69 0,65 0,63 40 - 50 0,78 0,75 0,72 0,68 0,65

Higher values of the runoff coefficient than 0.8 are possible for very steep terrains and higher values of API, i.e. after considerable previous precipitation preceding the rainstorm led to saturation of the upper soil layers.



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Figure 3.9 Runoff coefficient range

L ig h t te x t u r e - F o r e st 1 0 0 % - A P I = 0 m m

0 . 0 00 . 0 50 . 1 00 . 1 50 . 2 00 . 2 50 . 3 00 . 3 50 . 4 00 . 4 50 . 5 00 . 5 50 . 6 00 . 6 50 . 7 00 . 7 5

5 0 6 0 7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0

R a i n fa l l ( m m )

Run

off c

oef

ficie

nt

Ib = 5 - 1 0 %Ib = 1 0 -2 0 %

Ib = 2 0 -3 0 %

Ib = 3 0 -4 0 %Ib = 4 0 -5 0 %

H e a v y t e x tu re -F o re s t= 0 % - A P I= 4 0 m m

0 .0 0 0 .0 5 0 .1 0 0 .1 5 0 .2 0 0 .2 5 0 .3 0 0 .3 5 0 .4 0 0 .4 5 0 .5 0 0 .5 5 0 .6 0 0 .6 5 0 .7 0 0 .7 5

5 0 6 0 7 0 8 0 9 0 1 0 0 1 1 0 1 2 0 1 3 0

R a in fa l l ( m m )

R un of f c oe f f ic ien t

Ib = 5 -1 0 % Ib = 1 0 -2 0 % Ib = 2 0 -3 0 % Ib = 3 0 -4 0 % Ib = 4 0 -5 0 %


Section 4: Analyses

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4 Analyses 4.1 Maximum Precipitation

Based on the average and standard deviation values of the extreme 24 hours precipitation for the period 1983-1998 at 21 stations in the upper Aries river basin (including Rosia Montana station) a homogeneous area around Rosia Montana was identified. A number of 10 stations (Abrud, Albac, Avram Iancu, Baia de Aries, Bistra-Campeni, Mogos, Tebea, Zlatna, Alba-Iulia and Deva) having average values for annual maximum 24-hr precipitation in the range of 30-45 mm and standard deviation of 10-15 mm were chosen for detailed analyses (Figure 4.1). Figure 4.1 Area subject to detailed analysis

This analysis was undertaken considering the maximum annual 24 hours extreme value in the area; separate analyses were performed for the summer (May-November) and winter-spring (December-April) season. The obtained results for these two periods using Pearson III distribution are presented in Table 4-1 and in Figures 4.2 and 4.3.


Section 4: Analyses

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Table 4-1 Frequency analysis

Exceedance probabilities Summer period Winter-spring

ppxpk

5020

10

5

4

2

1

0.5

0.2

0.1

0.01

%

=

PP3pk

37.34752.717

65.73679.35883.83397.938

112.284126.809146.22

161.027

210.757

=

PP3pk

26.38838.167

47.21156.31159.24968.39577.56486.74998.912

108.125

138.781

=

Figure 4.2 Distribution of the summer extreme 24 h precipitation

0.01 0.1 1 10 1000

50

100

150

200

250

Empiric - WeibullGumbelPearson III

Exceedance probabilities

P [%]

Prec

ipat

ion

[mm

]

250

0

PA s jk⎛⎝

⎞⎠ i 2,

P

P

1000.01 P empiric i

%

PA Gumbel P jk,( )

%,

PA Pearson3 P jk,( )

%,


Section 4: Analyses

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Figure 4.3 Distribution of the winter-spring extreme 24 h precipitation

4.2 Snowmelt

Using Gumbel distribution, the following positive values were obtained for time intervals of 1, 2 respectively 3 days (Table 4-2). Table 4-2 Estimated maximum temperature TEMPERATURE

Return Period 1 day temp 2 days temp 3 days temp

[years] [degrees] [degrees] [degrees] 2 13 23 33 5 16 30 37 10 18 34 39 25 21 38 43 50 21,5 40 44

100 22 41 45 500 24 44 47

1.000 25 45 48 10.000 26 47 50

PMT 30 50 60

0.01 0.1 1 10 1000

50

100

150

200

250

Empiric - WeibullGumbelPearson III

Exceedance probabilities

P [%]

Prec

ipat

ion

[mm

]

250

0

PA s jk⎛⎝

⎞⎠ i 2,

P

P

99.9990.01 P empiric i

%

PA Gumbel P jk,( )

%,

PA Pearson3 P jk,( )

%,


Section 4: Analyses

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Snowmelt water equivalent depth was obtained by multiplying these values with the degree-day coefficient for March (2 mm/oC day). For shorter durations, i.e. 15’, 30’, 1h, 2h, 3h, 6h, considering that the snowmelt occurs during daytime (8h-16h), a fractional value of the snowmelt water was calculated for each of these intervals.

4.3 Probable Maximum Precipitation (Pmp)

PMP for 24 h was determined both for annual precipitation and for winter-spring season. Due to the uncertainties related to the PMP evaluation, particularly a relatively short period of record for 2 stations (Arieseni and Stana de Vale), different hypotheses were made for the annual precipitation, resulting in a range of PMP value at each station (Table 4-3). The summer PMP of 450 mm was selected for the Rosia Montana project, while the winter PMP of 380 mm was adopted. These values are within the range of recently reported PMP values for Central Europe:

800 mm in 24 h (Tetzlaff and all, 2003);

350 mm in 24 h (Becker and Grunewald, 2003). It can be noticed that the reported range is very wide. The PMP value for Europe is being revised after recent heavy flooding, which caused heavy damage in Central and Southern Europe. Table 4-3 Estimated PMP

Station PMP (mm) PMP (mm) Annual Winter

Abrud 263-298 272 Arieseni 492-568 565

Avram Iancu 346-490 351 Deva 359-528 118

Stana de Vale 486-560 582

PMP Rosia Montana 390-490 (450 adopted) 380

PMP for 2 and 3-day duration was computed using the conversion coefficients. The same approach was adopted for shorter durations of 15’, 30’, 1h, 2h, 3h, 6h and 12 h.

4.4 Runoff Coefficients

Most of the project basin area has a natural slope below 40%. The forested areas in the Rosia and Corna basins are estimated at 20% and 30% respectively and comprise medium texture soils. Based on the above and the runoff coefficients discussed in Section 3.4 of the report and shown on the Appendix 2, a 30% to maximum 80 % runoff coefficient could be expected. It is estimated that during summer, maximum runoff coefficients could range from 0.3 - 0.45 for 10-yr events, 0.35-0.60 for 100-yr events and 0.5-0.7 for T=1.000 or greater. The limits of the ranges correspond to the smallest and the highest rainfall duration, respectively. In winter-spring period, all corresponding coefficients were increased by 0.1 to account for possible higher API. Due to the exceptional character of the PMP and conservative assumptions needed for a safe design, a higher than usual runoff coefficients were recommended and adopted for hydrological analyses.


Section 4: Analyses

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The winter PMP runoff could theoretically occur after and parallel with significant snowmelt, where soil would be saturated. For that reason, the winter PMP runoff coefficient of 90% was adopted over land and 100% over water surface and impervious areas. As for the summer PMP, an 80% runoff coefficient was adopted over land and 100% runoff coefficient over water surface and impervious area.


Section 5: Findings and Conclusions

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5 Findings and Conclusions Based on the presented results, the extreme precipitations for different time intervals for the two seasons were obtained. The 24-hr events are summarized in Table 13, while the precipitation, snowmelt and estimated runoff coefficients for other durations are shown in Appendix A. ional The obtained values for 24 hours are slightly lower than the corresponding values provided by INMH in 2002. This can be explained by the fact that more detailed regional analysis carried as part of this study. On the other hand, the project PMP value, which is driving the design of the most important project structure, has been significantly increased compared to the PMP values proposed by previous studies. Rosia Montana will be the first project in Romania to be designed based on the PMP and PMF criteria.


Section 6: References

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6 References

1. C. Diaconu, P. Serban, Sinteze si Regionalizari Hidrologice, Ed. Tehnica, 1994; 2. C. Diaconu, P. Mita, E. Nita – Instructiuni pentru calculul scurgerii maxime in bazine

mici. INMH, 1995. 3. V. T. Chow – A general formula for hydrologic frequency analyses. Transactions

American Geophysical union, Vol. 32, pp 231-237 4. Manual for estimation of Probable Maximum Precipitation. Geneva, WMO, 1973. 5. D. Koutsoyiannis – A probabilistic view of Hershfield’s method for estimating probable

maximum precipitation. Water Resources Research, vol. 35, no. 4, pages 1313-1322, April 1999.

6. R. Drobot, P. Serban, Aplicatii de Hidrologie si Gospodarirea Apelor. Ed. HGA, Bucuresti, 1999

7. V. Al. Stanescu, R. Drobot – Masuri nestructurale de gestiune a inundatiilor. Ed. HGA, Bucuresti, 2002.

8. A. Becker, U. Grunewald , Flood Risk in Central Europe. Science, vol. 300, May 2003, page 1099.

9. G. Tetzlaff, M. Borngen, M. Mudelsee, Comparison of maximum precipitation estimates with runoff depths for the 1342 and 2002 Central European flood events. Water Resources systems - Proceedings of Symposium HS02b – IUGG2003, Sapporo, July 2003, pages 59-64.


Appendix 1: Precipitation, Snowmelt, Runoff Tables

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APPENDIX 1 Precipitation, Snowmelt, Runoff Tables



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Table 6-1 Winter storm + snowmelt (15-min to 3-day duration)

15 min (1/4 hour) 30 min (1/2 hour)

Return Period Rainfall Snowmelt

March Total Runoff coefficient Rainfall Snowmel

t March Total Runoff coefficient

[years] [mm] [mm] [mm] [mm] [mm] [mm] 2 10 1 11 0.38 13 2 15 0.40 5 14 1 15 0.38 18 2 21 0.40 10 17 1 18 0.39 22 3 25 0.40 25 21 2 23 0.40 27 3 31 0.42 50 25 2 26 0.41 32 3 35 0.43

100 28 2 30 0.42 36 3 40 0.44 500 36 2 37 0.45 46 4 50 0.48

1,000 39 2 41 0.51 50 4 54 0.53 10,000 50 2 52 0.58 65 4 69 0.60

PMP 137 2 139 0.90 177 5 181 0.90

60 min (1 hour) 120 min (2 hours)


March Total Runoff

coefficient

Rainfall Snowmelt March Total Runoff

coefficient

[years] [mm] [mm] [mm] [mm] [mm] [mm] [ 2 15 4 19 0.41 17 8 25 0.43 5 22 5 26 0.41 25 10 34 0.43

10 26 5 31 0.41 30 11 41 0.43 25 33 6 39 0.43 37 13 50 0.45 50 38 6 45 0.45 44 13 57 0.47 100 43 7 50 0.47 50 13 63 0.50 500 55 7 62 0.52 63 14 77 0.55

1,000 60 8 67 0.55 69 15 84 0.57 10,000 77 8 85 0.62 88 16 104 0.64

PMP 211 9 220 0.90 241 18 259 0.80



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180 min (3 hours) 360 min (6 hours)


March Total Runoff

coefficient

Rainfall Snowmelt March Total Runoff

coefficient

[years] [mm] [mm] [mm] [ - ] [mm] [mm] [mm] [ - ] 2 18 12 30 0.44 20 22 42 0.46 5 26 14 41 0.44 29 27 57 0.46

10 32 16 48 0.44 35 31 66 0.46 25 40 19 59 0.46 45 36 80 0.48 50 47 19 66 0.49 52 37 89 0.50 100 53 20 72 0.51 59 37 96 0.54 500 67 22 88 0.57 75 41 116 0.59

1,000 73 23 95 0.59 82 43 124 0.61 10,000 94 23 117 0.65 105 44 149 0.67

PMP 257 27 284 0.90 287 51 338 0.90

720 min (12 hours) 1,440 min (1 day)


March Total Runoff coefficient Rainfall Snowmelt

March Total winter

Runoff coefficient

[years] [mm] [mm] [mm] [ - ] [mm] [mm] [mm] [ - ] 2 23 25 48 0.48 27 26 53 0.50 5 34 30 64 0.48 39 32 71 0.50

10 41 34 75 0.48 47 36 83 0.50 25 51 40 91 0.51 59 42 101 0.53 50 60 41 101 0.55 69 43 112 0.56 100 67 42 109 0.58 78 44 122 0.59 500 86 46 131 0.62 99 48 147 0.64

1,000 93 48 141 0.64 108 50 158 0.66 10,000 120 49 170 0.70 139 52 191 0.72

PMP 329 57 386 0.90 380 60 440 0.90



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2,880 min (2 days) 4,320 Minutes (3 days)


March Total winter

Runoff coefficient Rainfall Snowmelt

March Total

winter Runoff

coefficient

[years] [mm] [mm] [mm] [ - ] [mm] [mm] [ - ] 2 31 46 77 0.53 33 66 99 0.55 5 44 60 104 0.53 48 74 122 0.55

10 54 68 122 0.53 58 78 136 0.55 25 67 76 143 0.57 73 86 159 0.60 50 79 80 159 0.62 86 88 174 0.65 100 89 82 171 0.66 97 90 187 0.70 500 113 88 201 0.69 123 94 217 0.73

1,000 123 90 213 0.71 134 96 230 0.75 10,000 158 94 252 0.76 172 100 272 0.80

PMP 433 100 533 0.90 471 120 591 0.90

Table 6-2 Summer storm (15-min to 3-day duration)

15 min (1/4 hour) 30 min (1/2 hour)

Return Period Rainfall Snowmelt Total Runoff

coefficient Rainfall Snowmelt Total Runoff coefficient

[years] [mm] [mm] [mm] [ - ] [mm] [mm] [mm] [ - ] 2 15 15 0.28 19 19 0.30 5 20 20 0.28 26 26 0.30

10 24 24 0.29 31 31 0.30 25 30 30 0.30 39 39 0.32 50 35 35 0.31 46 46 0.33 100 40 40 0.32 52 52 0.34 500 53 53 0.35 68 68 0.38

1,000 58 58 0.41 75 75 0.43 10,000 76 76 0.48 98 98 0.50

PMP 162 162 0.80 209 209 0.80



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60 min (1 hour) 120 min (2 hours)


coefficient Rainfall Snowmelt Total Runoff coefficient

[years] [mm] [mm] [mm] [ - ] [mm] [mm] [mm] [ - ] 2 23 23 0.31 26 26 0.33 5 31 31 0.31 36 36 0.33

10 37 37 0.31 43 43 0.33 25 46 46 0.33 53 53 0.35 50 54 54 0.35 62 62 0.37 100 62 62 0.37 71 71 0.40 500 81 81 0.42 93 93 0.45

1,000 89 89 0.45 102 102 0.47 10,000 117 117 0.52 134 134 0.54

PMP 250 250 0.80 286 286 0.80

180 min (3 hours) 360 min (6 hours)


coefficient Rainfall Snowmelt Total Runoff

coefficient

[years] [mm] [mm] [mm] [ - ] [mm] [mm] [mm] [ - ] 2 28 28 0.34 31 31 0.36 5 38 38 0.34 42 42 0.36 10 45 45 0.34 51 51 0.36 25 56 56 0.36 63 63 0.38 50 66 66 0.39 74 74 0.40

100 76 76 0.41 85 85 0.44 500 99 99 0.47 110 110 0.49

1,000 109 109 0.49 122 122 0.51 10,000 142 142 0.55 159 159 0.57

PMP 304 304 0.80 340 340 0.80



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720 min (12 hours) 1,440 min (1 day)


coefficient Rainfall Snowmelt

Total winter

Runoff coefficient

[years] [mm] [mm] [mm] [ - ] [mm] [mm] [mm] [ - ] 2 35 35 0.38 41 41 0.40 5 48 48 0.38 56 56 0.40 10 58 58 0.38 67 67 0.40 25 72 72 0.41 83 83 0.43 50 85 85 0.45 98 98 0.46

100 97 97 0.48 112 112 0.49 500 126 126 0.52 146 146 0.54

1,000 139 139 0.54 161 161 0.56 10,000 183 183 0.60 211 211 0.62

PMP 389 389 0.80 450 450 0.80

2,880 min (2 days) 4,320 Minutes (3 days)

Return Period Rainfall Snowmelt Total

winterRunoff

coefficient Rainfall Snowmelt

Total winter

Runoff coefficient

[years] [mm] [mm] [mm] [ - ] [mm] [mm] [ - ] 2 47 47 0.43 51 51 0.45 5 64 64 0.43 69 69 0.45 10 76 76 0.43 83 83 0.45 25 95 95 0.47 103 103 0.50 50 112 112 0.52 122 122 0.55

100 128 128 0.56 139 139 0.60 500 166 166 0.59 181 181 0.63

1,000 184 184 0.61 200 200 0.65 10,000 241 241 0.66 262 262 0.70

PMP 513 513 0.80 558 558 0.80


Appendix 2: Runoff Coefficients

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APPENDIX 2 Runoff Coefficients



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Figure 6.1 Runoff coefficient - Light texture soil

Light texture - Forest=0% - API = 0mm

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall (mm)

Runo

ff co

effic

ient

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%

Light texture - Forest100% - API = 0 mm

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall (mm)

Run

off c

oeffi

cien

t

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%

Light texture-Forest=0% - API=40mm

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall (mm)

Run

off c

oeffi

cien

t

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%

Light texture - Forest=100% - API=40mm

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall(mm)

Run

off c

oeffi

cien

t

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%



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Figure 6.2 Runoff coefficient Average texture

Average texture-Forest=0%-API=0mm

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall(mm)

Run

off c

oeffi

cien

t

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%

Average texture-Forest 100%-API=0mm

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall(mm)

Run

off c

oeffi

cien

t

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%


0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall(mm)

Run

off c

oeffi

cien

t

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%


0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall(mm)

Run

off c

oeffi

cien

t

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%



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Figure 6.3 Runoff coefficient Heavy texture

Heavy texture-Forest=0%- API=0mm

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall (mm)

Run

off c

oeffi

cien

t

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%

Heavy texture-Forest=100%-API=0mm

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall (mm)

Run

off c

oeffi

cien

t

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%

Heavy texture-Forest=0%-API=40mm

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall(mm)

Run

off c

oeffi

cien

t

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%

Heavy texture-Forest 100%-API=40mm

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

50 60 70 80 90 100 110 120 130Rainfall (mm)

Run

off c

oeffi

cien

t

Ib=5-10%Ib=10-20%Ib=20-30%Ib=30-40%Ib=40-50%



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APPENDIX 3 Monthly Precipitation Data from Abrud, RMGC-Roşia Montană, Rotunda- Roşia Montană Stations

meteorological baseline report assessment of rainfall intensity

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