for the Weir Bahrain Headrace Tunnel Madian Powerhouse Madain Town VOLUME IV HYDRO - METEOROLOGICAL DATA BASE Part 1 of 3 Weir Axis 7166P02 February 2009
Table of Contents VOLUME I: EXECUTIVE SUMMARY VOLUME II: MAIN REPORT VOLUME III: GEOLOGY AND GEOTECHNICAL FIELD INVESTIGATIONS VOLUME IV: HYDRO-METEOROLOGICAL DATA BASE VOLUME V: TOPOGRAPHIC SURVEY VOLUME VI 6a: VOLUME VI 6b: ENVIRONMENTAL IMPACT ASSESSMENT RESETTLEMENT ACTION PLAN VOLUME 7: DRAWING ALBUM 7166P02
Sarweystrasse 3 70191 Stuttgart Germany Phone: + 49 711 8995-0/311 Fax: + 49 711 8995-459 www.fichtner.de Please contact: Dr. Jörg Grossmann Extension: -732 E-mail: grossmannj@fichtner.de 7166P02
Table of Contents 1 Hydrology 1 1.1 Available Information 1 1.1.1 Meteorological Data 1 1.1.1 Hydrological Data 2 1.2 Precipitation and Temperature Regime 3 1.2.1 Precipitation Regime 3 1.2.2 Maximum Precipitation 5 1.2.3 Temperature Regime 7 1.3 Estimation of Flows 11 1.3.1 Description of Stations 11 1.3.2 Processing of Water Stage Records 12 1.3.3 Rating Curves 13 1.3.4 Calculation of Daily Flows 16 1.3.5 Extension of Flow Records 16 1.3.6 Calculation of Flows at Weir and Power House 18 1.3.7 Discussion of Results 21 1.3.8 Calculation of Flows of Kedam Nullah and Bara Dar 22 1.3.9 Determination of Ecological Flow 24 1.4 Estimation of Maximum Floods 25 1.4.1 Origin of Maximum Floods 25 1.4.2 Snowmelt Generated Floods 26 1.4.3 Rainfall Generated Floods 30 1.4.4 Model Development 30 1.4.5 Simulation of Rainfall Generated Floods 34 1.4.6 Design Floods 39 1.5 Sediment Transport 40 1.5.1 Suspended Sediment Transport 41 1.5.2 Grain Size Characteristics 43 1.5.3 Estimation of Bed Load and Total Sediment Transport 43 1.6 References 45 7166 P02 I
List of Annexes Climatological Data Temperature Daily Precipitation Hourly Precipitation Flow Data Daily Flows - Kalam - Raimet - Kedam Nallah - Kedam - Chakdara Part 1 of 3 Part 2 of 3 Flow Measurements - Kalam - Raimet - Kedam Nallah - Kedam Extended Flows - Weir - Power House Part 3 of 3 Floods Results of Simulation Suspended Sediment - Kalam - Ramet - Kedam Gauge Readings (CD) - Kalam - Ramet - Kedam Nallah - Kedam 7166 P02 II
1 Hydrology 1.1 Available Information 1.1.1 Meteorological Data Meteorological data of the Swat Catchment is limited to the station located at Kalam observed by Surface Water Hydrology. However, some stations installed at high altitude in the north of Pakistan provide valuable supplementary information of the meteorological conditions in the region, although not located in the Swat catchment. The location of the meteorological stations is shown on Figure 1.1. In Table 1.1 1 the relevant information of the meteorological stations used in this report is summarized. Figure 1.1 Location of Meteorological Stations 1 WAPDA, Meteorological Data Bank. Snow and Ice Hydrology Project, Lahore, July 2006
Table 1.1 Meteorological Stations Coordinates Elevation Record Nr Name Latitude Longitude (m asl) Organization Initial Final 1 Kalam 35 o 28' 10 72 o 35' 40 2026 SWHP 1963 2003 2 Shangla 34 o 52' 00 72 o 36' 00 2100 SIHP 1994 2005 3 Shandur 36 o 05' 00 72 o 32' 00 3560 SIHP 1994 2005 4 Ushkor 36 o 38' 00 73 o 04' 00 2977 SIHP 1994 2005 Only one of the meteorological stations indicated in Table 1.1 and Figure 1.1 is located in the Swat catchment area above Kalam. This is especially critical for the estimation of floods based on precipitation run-off models. Precipitation run-off models need a precipitation-area distribution model that for an area like the Swat catchment is preferably be based on various meteorological stations. 1.1.1 Hydrological Data Hydrologic information relevant for the hydropower project and available in the Swat valley includes Kalam and Chakdara on the Swat River. Both stations are operated by Surface Water Hydrology Project (SWHP). Two additional hydrological stations were installed by the Madian Hydropower Limited on the Swat River in 2006 at Kedam and Ramet on Swat River and one on the Kedam Nullah. The stations are located close to the weir site, and are currently being operated by the project. The relevant information about the hydrological stations is shown on Table 1.2 2. The location of the hydrological stations is depicted on Figure 1.2. The available records of the stations are summarized in Table 1.2. Table 1.2 Hydrological Stations Coordinates Catchment Elevation Record Code Station River Lat Long Area (km 2 ) (m asl) Start End 35724502 Kalam Swat 352810 723540 2,012 1921 1961 2007 35722503 Ramet Swat 351640 723550 2,365 1585 2006 2008 35722504 Kedam Nullah Kedam 351505 723508 55 1541 2006 2008 35722505 Kedam Swat 351455 723505 2,529 1500 2006 2008 35726002 Chakdara Swat 352915 723545 5,776 1951 1991 2005 2 WAPDA. Meteorological Data Bank. Surface Water Hydrology Project. Lahore, July 2006. 2
Figure 1.2 Location of Hydrological Stations 1.2 Precipitation and Temperature Regime 1.2.1 Precipitation Regime The precipitation regime in the Swat Valley is dominated by the occurrence of eastward moving extra tropical zones of low pressure, also known locally as Western Disturbances. The Western Disturbances bring humidity to the region of the Swat River from the Atlantic Ocean and the Mediterranean See. The Western Disturbances are more frequently and intense, during the Winter Season and they provoke the largest amount of precipitation over the Swat catchment 3. During the summer season the frequency and intensity of the Western Disturbances normally decrease, and the precipitation on the region also decreases. 3 Pakistan Meteorological Department, Report on Flood Activities 1992. Flood Forecasting and Warning Centre. Lahore, February 1993. 3
Figure 1.3 shows the distribution of the monthly precipitation observed at Kalam. The monthly precipitation is given in Table 1.3. 200 150 Precipitation (mm) 100 50 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure 1.3 Kalam, Monthly Precipitation Table 1.3 Kalam, Monthly Precipitation (1963-2006) Precipitation (mm) Period Jan 74.5 Feb 136.6 Mar 179.9 Apr 173.6 May 89.3 Jun 24.9 Jul 32.6 Aug 37.4 Sep 36.2 Oct 45.6 Nov 45.5 Dec 51.3 Annual 927.4 4
1.2.2 Maximum Precipitation Similar to the occurrence of mean precipitation, maximum precipitation in the Swat Valley is normally due to the occurrence of eastward moving extra tropical depressions also known as Western Disturbances. As precipitation in the winter season is in the form of snow, no large flood is observed after the occurrence of large precipitation. Large amount of precipitation in winter is important to determine the base flow during the summer months. A combination of large precipitation in winter followed by high temperatures in summer, produce floods and large base flows. However, in September 1992, when a large flood was observed in the northern areas of Pakistan, a large and deep low pressure moved from the Indian Ocean into the sub continent and reached the north of the country. At the same time, a Western Disturbance was moving to the east, across the Swat, Gilgit and Upper Indus catchments, where it provoked large floods in the region. The effect in the Swat valley was mixed. The flood inundated the lower Swat valley, while the upper Swat valley was only affected by severe rains. The flood observed at Kalam was of no special magnitude, but the run-off provoked by the rains is the largest observed during the period of record at Kalam. Figure 1.4 shows the monthly maximum observed 1-day precipitation and the mean maximum 1-day precipitation recorded at Kalam. The data is included in Table 1.4. Figure 1.4 shows that the maximum precipitation follows a similar pattern as the mean maximum, although it can deviate significantly from the mean. This is especially evident in the case of the maximum precipitation observed in September. The maximum precipitation in September was observed during the events of September 1992, and is out of the general trend. The magnitude of the observed rainfall is comparable to the maximum values observed in the winter months, suggesting that maximum precipitation can be observed at any time of the year. 5
140 120 Mean Maximum Maximum Precipitation (mm) 100 80 60 40 20 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure 1.4 Kalam: Maximum 1-Day Precipitation Table 1.4 Kalam: Maximum 1-Day Precipitation Maximum 1-Day Period Precipitation (mm) Mean Maximum Jan 27.9 71.3 Feb 36.8 68.2 Mar 48.1 123.6 Apr 45.6 102.4 May 28.8 117.2 Jun 10.3 42.2 Jul 12.3 30.4 Aug 12.8 32.9 Sep 14.4 101.8 Oct 19.3 80.0 Nov 20.3 61.0 Dec 19.8 49.2 Annual 24.7 123.6 6
1.2.3 Temperature Regime The temperature regime follows the temperature pattern in the northern hemisphere. Figure 1.5 shows the variation of the mean temperature during the year. The mean temperature and the mean maximum and minimum temperature values are given in Table 1.5. When the temperature is at its maximum in July, and the flows are mostly snowmelt generated, it can be expected that largest flows occur during this month. Therefore, for the estimation of maximum discharges the temperature is important. High temperatures in addition to high precipitation during the previous winter months result in high base flows. 30 25 Mean Mean Maximum Mean Minimum 20 Temperature ( o C) 15 10 5 0-5 -10 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure 1.5 Temperature Regime 7
Table 1.5 Kalam: Temperature Temperature ( o C) Period Mean Maximum Minimum Jan 0.7 7.5-6.1 Feb 1.7 8.4-5.1 Mar 5.3 11.5-1.0 Apr 10.7 17.1 4.4 May 15.1 22.0 8.1 Jun 19.0 26.3 11.6 Jul 20.2 25.8 14.7 Aug 19.4 24.6 14.3 Sep 16.0 22.5 9.5 Oct 11.8 19.4 4.3 Nov 7.1 14.5-0.4 Dec 3.2 9.9-3.4 Mean 10.8 17.4 4.2 Figure 1.6 shows the temperature regime observed at the stations Kalam, Shangla, Shandur and Ushkore. Figure 1.6 shows that the pattern of the mean monthly temperature in the region is very similar, with Shangla located the southernmost having its maximum temperature earlier in June, while the other stations located to the north, registered the maximum temperature in July. The data of Figure 1.6 is presented in Table 1.6. 25 20 15 Kalam Shangla Shandur Ushkore Temperature ( o C) 10 5 0-5 -10-15 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure 1.6 Mean Monthly Temperature Distribution 8
Table 1.6 Mean Monthly Temperature Elev Mean Temperature ( o C) Station (m asl) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Annual Kalam 2026 0.7 1.7 5.3 10.7 15.1 19.0 20.2 19.4 16.0 11.8 7.1 3.2 10.8 Shangla 2100 1.7 2.4 6.8 12.0 16.2 19.4 19.1 18.2 16.3 12.8 8.7 4.7 11.5 Shandur - 3560-8.4-3.3 10.6 2.2 7.1 11.9 14.6 14.3 10.2 3.4-4.3-8.0 2.4 Ushkore 2977-6.9-5.3-1.0 4.8 10.0 14.9 18.2 17.9 13.4 6.9 0.7-4.8 5.7 Figure 1.7 depicts the relationship between the mean annual temperature and the elevation of the points of observation. Figure 1.7 shows that in the region the mean temperature decreases at a rate of 5.9 o C per km in elevation, similarly as the maximum and minimum temperatures decrease. The relationship of temperature with elevation determines the status of water (solid or liquid) in the catchment and therefore, the possibility to develop runoff at a given elevations. For the month of September, when the 1992 flood occurred, the temperature-elevation relationship is presented on Figure 1.8. Figure 1.8 shows that the mean minimum temperature is cero, at about an elevation of 4,000 m asl. The snow line is assumed at this elevation. Similarly, Figure 1.9 shows the temperature-elevation relationship during July when the highest temperature is observed and the base flow is at its maximum. 4000 3500 t = - 0.0059h + 23.4 R 2 = 0.989 Shandur Mean Maximum Minimum Elevation (m) 3000 2500 t = - 0.0066h + 20.3 R 2 = 0.8468 Shokore y = - 0.0065h + 29.6 R 2 = 0.9669 Kalam Shangla 2000-5.0 0.0 5.0 10.0 15.0 20.0 Temperature (oc) Figure 1.7 Relation Temperature Elevation 9
4000 3500 t = -0.0038 * h + 24.1 R2 = 0.9713 Mean Maximum Minimum Elevation (m) 3000 2500 t = -0.0041 * h + 19.8 R2 = 0.7713 t = -0.0039 * h + 29.1 R2 = 0.8517 2000 1500 0 5 10 15 20 25 Temperature (oc) Figure 1.8 Temperature Elevation Relationship for September 4000 t = -0.0031 * h + 26.217 R2 = 0.8805 Mean Maximum Minimum 3500 Elevation (masl) 3000 t = -0.0025 * h + 29.65 R2 = 0.541 2500 t = -0.0037 * h + 22.952 R2 = 0.937 2000 5.0 10.0 15.0 20.0 25.0 30.0 Temperature (oc) Figure 1.9 Temperature Elevation Relationship for July 10
1.3 Estimation of Flows Available hydrological data relevant to the Madian HPP comprises the flows observed at the stations Kalam and Chakdara installed, maintained and processed by WAPDA s Surface Water Hydrology Project. Hydrological stations on the Swat River at Ramet and Kedam and on Kedam Nullah were installed by the Project Sponsor Madian Hydro Power Ltd. close to the weir site to improve the basis for estimation of the available flows. 1.3.1 Description of Stations Hydrological stations included in the hydrological investigations contained in this document, are described in the following paragraphs. The stations are mentioned in the downstream direction. 1.3.1.1 Swat River at Kalam The station was installed by Surface Water Hydrology Project (SWHP) in 1961. Stage records are available from 01/01/1961 to 31/10/2007. Daily flow records calculated by SWHP are available for the period from 1961 to 2006. Calculation of 2007 flows was undertaken from gauge readings and flow measurements taken by SWHP. 1.3.1.2 Swat River at Kedam The station was installed by the sponsor Madian Hydro Power Ltd. on 4. March 2006. Stage records are available from 4. March 2006 to 31. January 2008. A total of 131 flow measurements conducted at the site are available. The equipment installed at the site comprises staff gauge and a data logger with attached pressure sensor to record automatically water levels. The equipment was installed on the right bank of the river. A concrete bridge located some 450 m further downstream is used to take flow measurements at the site. 1.3.1.3 Kedam Nullah at Kedam The station was installed by the sponsor Madian Hydro Power Ltd. on 9/04/2006. Stage records are available from 9. April 2006 to 27. July 2006. At the site a total of 23 flow measurements are available. 11
The equipment installed at the site is similar to the one installed at the other automatic stations. The equipment was installed on the right bank of the river. Flow measurements at the site were taken by wadding. 1.3.1.4 Swat River at Ramet The station was installed by the Project Sponsor Madian Hydro Power Ltd. on 19/02/2006. Stage records are available from 19/02/2006 to 31/01/2008. At the site a total of 54 flow measurements are available. The equipment installed at the site is similar to the one installed at the other stations. The housing was installed on the right bank of the river. A concrete bridge on the river was used to take flow measurements at the site. 1.3.1.5 Swat River at Chakdara The station was installed by Surface Water Hydrology Project (SWHP) in 1961. At the site, the daily flow records estimated by SWHP are available for the period from 1961 to 2005. 1.3.2 Processing of Water Stage Records Water stages recorded in the automatic equipment include 24 hours continuous data, while gauge readings were taken on an 8-hours basis. Consequently, the automatic water stages record was used for calculation of flows. To avoid the use of non-calibrated water stages from the automatic record, comparison of the records with gauge readings was performed. The automatic records were adjusted when required. 24 hour continuous records of stages ensure the acquisition of maximum and minimum levels of the river. Maximum and minimum water levels may occur during night hours, and consequently may not be observed by the gauge observer. Particularly in the case of the Swat River, almost every day, a small flood occurs at midnight, due to snow melt when the temperature is at its highest. The small flood is not recorded at the gauge observer file, but it is present in the files of the automatic station. During the preparation of the present report, processing of water stage records was undertaken for the following stations: Swat River at Kedam, Kedam Nallah at Kedam and Swat River at Ramet. The processing of water stages was undertaken using DBHYDRO program developed for processing and storage of hydrological data. The corresponding processed water stage data are given in the soft copy attached to the present report. 12
1.3.3 Rating Curves Rating curves are mathematical functions relating water stages and discharge at the sites of the hydrological stations. Rating curves can be adequately be established when sufficient (in number and quality) flow measurements are available. In the case of the stations in the Swat River sufficient number of flow measurements is available to represent the relation between stage and discharge at the sites. Processing of flow measurements and development of rating curves was undertaken using program DBHYDRO. The following paragraphs describe the analysis performed to establish the rating curves for the stations on Swat River at Kalam, Swat River at Kedam, Kedam Nullah at Kedam and Swat River at Ramet. 1.3.3.1 Swat River at Kalam After a detailed analysis of the flow measurements taken at the station the years 2006 and 2007, no sensible change was found in the relation between gauge heights and discharge indicated by the measurements. Consequently, only one rating curve was used to calculate the mean daily flows. The rating curve of Swat River at Kalam is shown on Figure 1.9. 4.5 4.0 Flow Measurements Rating Curve 3.5 Gauge Reading (m) 3.0 2.5 2.0 Q = 1.019 * (H + 0.738) 3.732 1.5 1.0 0 50 100 150 200 250 300 350 400 Discharge (m 3 /s) Figure 1.9 Swat River at Kalam. Rating Curve 13
1.3.3.2 Swat River at Ramet After a detailed analysis of the flow measurements taken at the station Swat River at Ramet, it has been concluded that the flow measurements only cover a limited range of the gauge readings and consequently the extrapolation of the rating curve was undertaken. The extrapolation of the rating curve is made following the formula by Manning extrapolating the value of (S 1/2 /n) obtained from the flow measurements. The area and hydraulic radius is taken from the survey of the cross section at the bridge taken in April 2006. A single rating curve representing the values of the flow measurements and the extrapolated points was obtained and is shown on Figure 1.10. 3.5 3.0 Flow Measurements Rating Curve Extrapolated Gauge Reading (m) 2.5 2.0 1.5 Q = 9.843 * (H + 0.6227) 2.412 1.0 0.5 0 50 100 150 200 250 300 350 Discharge (m 3 /s) Figure 1.10 Swat River at Ramet, Rating Curve 1.3.3.3 Kedam Nallah at Kedam After the analysis of the measurements available of the station Kedam Nullah at Kedam, The rating curve depicted on Figure 1.11 was applied to calculate the daily flows. It has to point out that only few measurements are available at the site, however, the measurements cover a sufficient range of flows and stages to develop a rating curve. 14
0.8 0.7 Flow Measurement Rating Curve Gauige Height (m) 0.6 0.5 0.4 0.3 Q = 3.803 * (H + 0.33) 2.573 0.2 0.1 0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 Discharge (m 3 /s) Figure 1.11 Kedam Nullah at Kedam, Rating Curve 1.3.3.4 Swat River at Kedam After a detailed analysis of the flow measurements taken at the station Kedam at Swat River, no sensible change was found in the relation between gauge heights and discharge indicated by the measurements. Consequently, only one rating curve was used to calculate the means daily flows. The rating curve of Swat River at Kedam is shown on Figure 1.12. 3.5 3.0 Flow Measurements Rating Curve Gauge Reading (m) 2.5 2.0 1.5 1.0 Q = 26.23 * (H + 0.7398) 2.11 0.5 0.0 0 50 100 150 200 250 300 350 400 450 Discharge (m 3 /s) Figure 1.12 Swat River at Kedam, Rating Curve 15
1.3.4 Calculation of Daily Flows Calculation of daily flows was undertaken applying the rating curves to the gauge heights. The gauge height data were processed earlier as explained above. To calculate the daily flows, it was considered that the observed dispersion of the flow measurements is due to the erosion/deposition of sediments in the river bed as well as variation of riverbed roughness and efficient energy gradient. Consequently, to account for the river bed changes, the calculation of the daily flows was made applying the method of shifting of the rating curve. The method consists of shifting the rating curve to the position of every flow measurement, however following restrictions are observed while calculating the daily flows: a) Large shifting of the rating curve are generally avoided. b) If a number of flow measurements indicate a shift in one direction (positive or negative) of the rating curve during a large period, a new rating curve is required for the period. c) Flow measurements indicating large shifting or modifying the flow pattern, are eliminated from the calculation of daily flows. Results of the calculation of daily flows are included in Annex 2. 1.3.5 Extension of Flow Records Extension of the flow records was undertaken to improve the available estimations of flows. To extend the period of records, correlation between the series of flow records of the stations in the Swat River was undertaken. Generally, an excellent correlation is obtained for the flow records of the stations. The excellent correlation between the flow series indicates the good quality of the records. The extension of the flow records was undertaken as follows: First the flows of the stations Ramet and Kedam were correlated with the flows recorded at Kalam. To estimate the flows at the weir site, the regression equation obtained from the series of flows of Kalam and Ramet was used; the values were then adjusted to the site of the weir according to the difference in the area of the catchments. In particular for the extension of the flow records, the correlation between the long term station (Kalam), and the short term stations (Ramet and Kedam) was found to be excellent. The correlation between Kalam and Ramet, is shown on Figure 1.13, the results of the correlation analysis as well as the regression equation are included in the same figure. Using the regression equation of Figure 1.13, the flows of the stations at Ramet were extended and adjusted to the weir site. 16
1000 y = 7.5191x 0.6665 R 2 = 0.7126 Flows at Ramet (m 3 /s) 100 y = 1.3988x 1.0387 R 2 = 0.9668 10 10 100 1000 Flows at Kalam (m 3 /s) Figure 1.13 Correlation between Kalam and Ramet To estimate the flows at the power house, the relationship between Kalam and Kedam was utilized; the values were then adjusted to the site of the power house according to the difference in area of the catchments. The correlation between Kalam and Kedam was made up of two curves as shown on Figure 1.14. The results of the correlation analysis as well as the regression equation are given in the same figure. 1000 y = 1.8384x 0.9953 R 2 = 0.9748 Flows at Kedam (m 3 /s) 100 10 10 100 1000 Flows at Kalam (m 3 /s) Figure 1.14 Correlation between Kalam and Kedam 17
Using the regression equation of Figure 1.14, the flows of Kedam were extended and adjusted to the site of the power house. The results of the extension of flow records at the power house are included in Annex 2. To complete the analysis, the correlation 1000 Flows at Raimet (m 3 /s) 100 y = 1.2006x 0.9317 R 2 = 0.9807 10 10 100 1000 Flows at Kedam (m 3 /s) Figure 1.15 Correlation between Ramet and Kedam between Ramet and Kedam is depicted on Figure 1.15. The figure includes the regression equation and the correlation coefficient. 1.3.6 Calculation of Flows at Weir and Power House The weir site is located downstream of the gauging station Ramet. The catchment area to the weir site is 2,403 km 2, while at Ramet the catchment area is 2,365 km 2. The difference in catchment area between both sites is only 1.6%. Therefore, to calculate the flows at the weir site, the flows at Kalam were converted to flows at Ramet according to the formula on Figure 1.13. An additional 1.6% was added to the resulting value to account for the difference in catchment area. On the other hand, the site of the Power House is located downstream of the station Kedam. The catchment area to the power house site is 2,842 km 2, while at Kedam the catchment area is 2,529 km 2. The difference in catchment area between both sites is 12%. Therefore, to calculate the flows at Power House, the flows at Kalam were converted to flows at Kedam applying the formula on Figure 1.14 and an additional 12% was added to account for the difference in catchment between Kedam and the power House site. 18
Estimated monthly flows at weir site are included in Table 1.7. The monthly flows are shown in graphical form on Figure 1.16. Similarly, the flow duration curve at the site of the weir can be seen on Table 1.8. The flow duration curve is depicted on Figure 1.17. Table 1.7 Monthly Flows at Weir Site Period Flows (m 3 /s) Weir Power House Jan 23.566 28.524 Feb 21.611 26.259 Mar 27.173 32.399 Apr 78.716 88.347 May 191.704 234.138 Jun 298.382 431.686 Jul 302.924 440.336 Aug 227.325 291.515 Sep 128.836 143.362 Oct 57.446 65.067 Nov 36.401 42.559 Dec 27.807 33.212 Annual 118.491 154.784 500 450 Weir Power House 400 Mean Monthly Flow (m 3 /s) 350 300 250 200 150 100 50 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure 1.16 Weir Site and Power House, Mean Monthly Flows 19
Table 1.8 Weir Site and Power House Flow Duration Curves Flows (m 3 /s) % of Time Power House Weir 100 12.803 16.159 95 19.862 24.324 90 21.510 26.197 80 25.241 30.405 70 30.007 35.719 60 39.320 45.944 50 59.331 67.393 40 106.390 116.091 30 178.723 202.492 20 232.433 296.501 10 294.980 419.015 5 340.769 516.630 4 353.717 545.364 3 364.883 570.526 2 379.671 604.387 1 400.820 653.857 0 650.000 969.596 800 600 Discharge (m 3 /s) 400 200 0 0 20 40 60 80 100 % of Time Figure 1.17 Weir Site, Flow Duration Curves 20
1.3.7 Discussion of Results The results of the estimation of flows at the weir site give an increment of about 9% of the estimated flow compared to the prefeasibility study phase. The discharge at the weir site is slightly larger than the discharge at Kalam. Due to the quality of the data obtained from the stations at Ramet and Kedam, the increment is considered acceptable and can be explained as below. The flows at the weir are calculated on basis of 24 hours recorded water stages, while the flows at Kalam are calculated on basis of 8 hours gauge readings. This is especially important in summer when a daily flood is observed at night and the difference of both flows calculated from 24 hours recorded water stages exceed by about 5% the flows calculated with the 8 hours readings. In winter the difference is less, but it increases when a flood occurs. The specific discharge in the Swat River catchment in the reach of the project increases with the area, due to the fact that at higher elevations most of the water remains frozen. The catchment of Batal Khwar at Utror, located upstream of Kalam, shows a specific discharge larger than the one at Kalam, because its catchment has a lower mean elevation than the Swat catchment at Kalam. Additionally, at lower elevation the influence of rainfall increases, this is observed at Bahrain where the specific discharge is larger than the one at Kalam and at the weir site. Specific discharges observed at other stations in the surrounding area, especially in the Indus catchment, show specific discharges with similar and even larger values as the one obtained for the weir site. In Table 1.9 a series of mean annual flows and specific discharges of various stations at various rivers is given. The Table 1.9 shows that the specific discharge calculated at weir site is within the limits of observed values in the area. The hydrological model developed by GTZ, including other hydrological stations in the upper Swat catchment shows that the mean annual flow at Kalam is underestimated by about 4%, with respect to the results of the simulation. The reason may be the adjustment of the rating curves by SWHP to ensure lower flows at the upstream stations, when compared with downstream stations. 21
Table 1.9 Flows and Specific Discharges Catchment Area (km2) Mean Annual Flow (m3/s) Specific Discharge (lts/(s-km 2 ) Station River Jildat Ushu 782 33.10 42.33 Gulshanabad Gabral 704 30.32 43.07 Utror Batal 189 10.13 53.60 Swat Kalam 2012 87.56 43.52 Bahrein Daral Khwar 268 14.05 52.43 Weir Swat 2403 118.49 49.31 Karora Gorband 614 34.72 56.55 Duber Bela Duber Khwar 408 24.03 58.89 Gosak Summar Gah 147 5.19 35.31 Thautti Br Kandiah 1047 57.15 54.59 Kayal Khwar Shimshal 154 12.03 78.10 As a consequence of the above discussion, it was concluded that the estimation of flows at the weir site is consistent with the limits of observed values in other catchments with similar regime and within the limits that ensure that good practices are applied while taking the measurements. Consequently, the flows can be used with confidence for the estimation of the design flows of the hydropower project. 1.3.8 Calculation of Flows of Kedam Nullah and Bara Dar Calculation of mean daily flows of Kedam Nullah at Kedam was undertaken as described above. To estimate the flows of Kedam Nullah and Bara Dar, the calculated flows of Kedam Nallah at Kedam were compared with the flows of Daral Khwar at Bahrain. The mean monthly flows are included in Table 1.10 and shown on Figure 1.18. The specific discharges of both stations and the flow pattern are similar, with Bahrain being on the lower side during the low flow season. Bahrain has been operated since 1992 and, therefore, the series of flows of this station are more reliable. The specific discharges and flow pattern of Daral Khwar at Bahrain were adopted for the calculation of the flows of Kedam Nullah and Bara Dar. The flows of both rivers are used to calculate the ecological flow. 22
Table 1.10 Kedam Nullah and Daral Khwar Mean Monthly Flows Mean Monthly Flows (m3/s) Specific Discharge (lts/(s-km2) Period Kedam N Bahrain Kedam N Bahrain Jan 0.57 1.66 10.37 6.21 Feb 0.62 2.03 11.32 7.56 Mar 1.27 5.13 23.08 19.13 Apr 4.04 18.42 73.41 68.75 May 6.17 42.07 112.27 156.99 Jun 4.74 44.17 86.12 164.82 Jul 4.44 24.57 80.81 91.70 Aug 4.32 13.81 78.50 51.52 Sep 2.21 6.07 40.22 22.66 Oct 1.00 5.28 18.19 19.71 Nov 1.01 3.31 18.43 12.36 Dec 0.75 2.03 13.59 7.58 Annual 2.60 14.05 47.19 52.42 180 160 Kedam Bahrein 140 Specific Discharge (lts/(s-km 2 ) 120 100 80 60 40 20 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Figure 1.18 Kedam Nallah-Daral Khwar. Mean Monthly Flows 23
1.3.9 Determination of Ecological Flow For the determination of the mean monthly ecological flow, a formula representing a function of the available mean monthly discharges and the mean annual discharges was used and as presented below: MQ eco = {(0.0651 * MQ mo + 2)/100} * MQ an Were MQ eco = mean monthly ecological flow in m 3 /s MQ mo = mean monthly flow in m 3 /s MQ an = mean annual flow in m 3 /s The formula was also used for the feasibility study of the Gabral- Kalam Hydropower Project and was developed by CEMAGREF, agricultural and Environmental Engineering Research, situated in Antony France. CEMAGREF is a public research institute that targets results directly useable in land and water management. The formula is also recommended by the International Association of Small Hydropower. The formula was used to calculate the minimum ecological flow downstream of the weir. The monthly average values are given in the table below. Together with the contribution from the Kedam Nullah and Bara Dar, which join the Swat River just downstream of the dam, the required releases from the reservoir are computed. All monthly average values are given in the Table 1.11. Table 1.11 Ecological Discharge Downstream of the Madian Weir Swat River at Weir Required Ecological Discharge (m 3 /s) Contribution of Tributaries Required Release Period Flow Kedam Bara Dar Total Jan 23.57 4.19 0.31 0.47 0.78 3.41 Feb 21.61 4.04 0.38 0.57 0.95 3.09 Mar 27.17 4.47 0.96 1.45 2.41 2.06 Apr 78.72 8.44 3.44 5.19 8.63 Surplus Spill May 191.70 17.16 7.85 11.86 19.71 Surplus Spill Jun 298.38 25.39 8.24 12.45 20.69 Surplus Spill Jul 302.92 25.74 4.58 6.93 11.51 Surplus Spill Aug 227.33 19.91 2.58 3.89 6.47 Surplus Spill Sep 128.84 12.31 1.13 1.71 2.84 9.47 Oct 57.45 6.80 0.99 1.49 2.48 4.32 Nov 36.40 5.18 0.62 0.93 1.55 3.63 Dec 27.81 4.51 0.38 0.57 0.95 3.56 24
1.4 Estimation of Maximum Floods 1.4.1 Origin of Maximum Floods Maximum annual floods in the Upper Swat catchment have been recorded for the last 46 years at Kalam (1961-2006). The recorded maximum floods have a regular pattern and occur between May and July, when the temperature is nearly or at its maximum, and when no significant amount of precipitation occurs in the catchment. Therefore, it has been concluded that the maximum floods recorded at Kalam are originated by snowmelt. Taking into consideration that the flood series is relatively long and that the station is well maintained and observed, the flood series at Kalam adequately represent the normal floods in the catchment. On the other hand, floods at Chakdara show a different pattern, with several flood values significantly exceeding the normal trend. Because precipitation becomes more important to the south as a flood generating process, this deviation of the normal trend is most probably due to a mixed population of floods. In September 1992 a large and deep low pressure front moved from the Indian Ocean into the sub continent and reached the north of the country. At the same time, a Western Disturbance was moving to the east, across the Swat, Gilgit and Upper Indus catchments, where it provoked large floods in the region. In the Swat catchment, the rains provoked the inundation of the lower Swat Valley and in Kalam heavy rainfall was reported. The flood observed at Kalam was not the largest observed flood because at the time of the flood the base flow has receded, however, the run-off was the largest recorded at Kalam. The event of 1992 demonstrated that rainfall can produce a significantly larger amount of run-off than snowmelt in the Upper Swat catchment and consequently may affect the site of the hydropower project. As observed in other catchments in northern areas of Pakistan, maximum floods are normally from snowmelt origin, but for larger periods of return, rainfall can be the predominant process originating maximum floods. Therefore, for a complete analysis of maximum floods in the Swat catchment, both floods of snowmelt and rainfall origin were analyzed. 25
1.4.2 Snowmelt Generated Floods Snowmelt generated floods were analyzed applying a frequency analysis to the floods recorded at Kalam and Chakdara. The corresponding results are presented in Table 1.31. The two maximum recorded floods of Swat at Chakdara were eliminated from the analysis, because they follow a different trend and are classified as outliers. Both values represent a different statistical population, most probably rainfall generated floods. As discussed previously, rainfall generated floods are analyzed separately. Various frequency distributions (see Table 1.31) were applied to estimate the maximum floods. After examination of the results, the distribution by Gumbel was selected. The analysis of both series give good results for various distributions, however, the Gumbel distribution was selected because the results for both stations are comparable and consistent. The Gumbel distribution is world wide applied and its use has shown good simulation results in Pakistan. The available series of floods of both stations are given in Tables 1.12 and 1.13 and the results of the frequency analysis of both series of floods are included in Table 1.14 and in Figure 1.19. Table 1.12 Chakdara: Series of Maximum Floods Date Discharge (m³/s) Date Discharge (m³/s) 24-Jul-61 744.7 20-Jul-95 2773.0 22-Jul-62 943.0 10-Jul-97 1009.6 17-Jul-65 809.9 16-Jul-98 759.5 31-Jul-66 1002.4 7-Mar-99 843.4 24-Jul-67 900.5 30-Jul-00 451.7 30-Jul-68 926.0 23-Jul-01 1438.9 10-Aug-69 985.4 14-Aug-02 809.4 6-Oct-70 673.9 31-Oct-73 781.5 26
Table 1.13 Kalam: Series of Maximum Floods Date Discharge (m³/s) Date Discharge (m³/s) 16-Jul-61 311.5 17-Jun-84 413.4 22-Jul-62 404.9 12-Jul-85 308.7 12-Jul-63 472.9 8-Jul-86 518.2 4-Jul-64 521.0 25-Jul-87 379.4 26-Jul-65 464.4 15-Jul-88 390.8 19-Jun-66 424.8 30-Jul-89 333.8 25-Jul-67 421.9 25-Jun-90 534.0 9-Jul-68 438.9 13-Jul-91 549.8 456.0 22-Jul-92 468.8 1-Jul-70 371.0 7-Jul-93 403.1 12-Jun-71 351.1 3-Jul-94 489.3 27-Jun-72 472.9 25-Jul-95 487.8 3-Jul-73 387.9 13-Jun-96 533.7 19-Jul-74 337.0 10-Jul-97 344.7 16-May-75 464.4 12-Jul-98 494.7 393.0 9-Jun-99 373.6 24-Jun-77 342.6 12-May-00 236.9 6-Jul-78 597.5 24-Jul-01 196.5 470.0 24-Jun-02 347.5 25-Jun-80 393.6 27-Jun-03 393.1 30-Jun-81 407.8 17-Jun-04 327.7 24-Jul-82 233.0 27-Jun-05 505.6 2-Jun-83 368.1 13-Jul-06 270.4 Table 1.14 Frequency Analysis of Floods Maximum Floods (m 3 /s) Return Period Chakdara (A = 5,776 km 2 ) Kalam (A = 2,012 km 2 ) 2 806.7 394 5 940.1 472 10 1,028.4 524 20 1,113.1 589 50 1,222.7 638 100 1,304.9 686 1,000 1,576.4 844 10,000 1,847.4 1,002 Figure 1.19 shows the similar pattern of the flood frequency curves of Kalam and Chakdara. The figure shows that the two maximum recorded floods of the Chakdara series, follow a different pattern as compared to the general pattern defined by the rest of the floods and described by the frequency curve. 27
-2.79-0.79 1.21 3.21 5.21 7.21 9.21 Feasibility Study 10000 1.1 2 5 Return Period (years) 10 20 50 100 1,000 10,000 Kalam Chakdara Maximum Flood (m 3 /s) 1000 100 91 50 20 10 5 2 Probability (%) 1 0.1 0.01 Figure 1.19 Flood Frequency Curves The magnitude of the maximum floods of snowmelt origin at the sites of weir and power house was estimated by interpolating the area of the catchment in a curve connecting the specific discharges of both stations for each period of return. The specific discharges of the maximum floods are included in Table 1.15. Table 1.15 Specific Discharges of Maximum Floods Specific Discharge of Maximum Floods (Lts/(s-km 2 ) Return Period Chakdara (A = 5,776 km 2 ) Kalam (A = 2,012 km 2 ) 2 140 196 5 163 235 10 178 260 20 193 293 50 212 317 100 226 341 1,000 273 419 10,000 320 498 28
The distribution of floods along a catchment does not follow a simple catchment area relationship, due to the fact that smaller catchments tend to have higher specific discharges. It has been observed that a power equation better describes the distribution of flows in the same catchment or in catchments with similar pattern of floods. The power equation used to interpolate the values of the maximum floods at intake and power house is of the form: Where: q = specific discharge (lts/(s-km 2 )) C = coefficient A = catchment area n = coefficient q = C * A n The values of the coefficients obtained from the specific discharges of the floods for the given return periods are included in Table 1.16. Table 1.16 Coefficients Return Coefficient Period N C 2-0.32 2,242 5-0.35 3,277 10-0.36 4,047 20-0.40 5,974 50-0.38 5,849 100-0.39 6,638 1,000-0.41 9,316 10,000-0.42 12,144 The interpolated values of the floods of snowmelt origin at weir and power house are shown in Table 1.17. Table 1.17 Maximum Floods of Snowmelt Origin at Weir and Power House Maximum Floods (m 3 /s) Return Period Weir Site (A = 2403 km 2 ) Power House (A = 2878 km 2 ) 2 445 502 5 530 596 10 587 659 20 656 731 50 712 796 100 764 853 1,000 938 1,043 10,000 1,111 1,233 29
1.4.3 Rainfall Generated Floods To estimate the magnitude of the rainfall generated floods, a precipitation- run off model was applied. The computer program selected to simulate the floods in the Swat Catchment was HEC- HMS developed by the Hydrologic Engineering Centre of the US Corp of Engineers. The program utilizes four main components called model managers, the Basin Model Manager, the Meteorological Model Manager, the Control Specifications Manager and the Time-Series Data Manager. The basin model manager is intended to manage the models that describe the different conditions of the catchment. The model of the catchment includes catchment areas, river topology (catchments, channels and connections), definition of the methods to estimate water losses, transform rainfall excess into run-off and base flow, and the parameters to estimate excess, and transform the excess into a hydrograph. The meteorological model manager defines the rainfall gauges to be used to calculate the precipitation over the catchment. The control specifications manager defines the time limits of the simulation, i.e. the starting date and time, and the ending date and time of the simulation. In the time series data manager the data of the storm are given. The data of the storm include the amount of precipitation and time distribution of the rainfall, used to estimate the floods. 1.4.4 Model Development The geomorphologic parameters of the Swat River catchment, required to simulate the catchment, were obtained from the 1:50,000 topographic sheets. The catchment of the Swat River was divided into 4 sub-catchments, as follows: Gabral River, Ushu River, Swat River to Weir and Swat River from Weir to Power House. The model of the catchment is presented on Figure 1.20. The method selected to estimate the water losses was the Curve Number classification developed by the US Soil Conservation Soils (SCS). To estimate the parameters required by the program especially the water losses, an approximation to the land use was obtained from the 1:50,000 maps of the catchment. The areas of the catchments classified by land use are included in Table 1.18. The soils were classified according to the following criteria: Forest Land: thin stand, poor cover, no mulch. Hydrologic soil group B, soils with low organic content and usually high in clay. SCS No 66. 30
Figure 1.20 Swat River Catchment Model Table 1.18 Catchment Areas by Land Use Areas by Land Use (km 2 ) Total No Reach Forest Cultivated Bare Land Glaciers Without Glaciers Total 1 Gabral 388 21 575 194 984 1178 2 Ushu 313 13 304 141 629 770 3 Swat-1 2 28 361 65 391 456 4 Swat-2 56 25 372 21 453 474 Cultivated Land: without conservation treatment, Hydrologic soil group B, Shallow loess, sandy loam. SCS No 70. Bare Land: range land in poor condition. Hydrologic soil group C, soils that swell significantly when wet. SCS No 80. For catchments that consist of several soil types and land uses a composite CN is calculated as: CN = Σ A i CN i / Σ A i The Initial loss was calculated for each sub catchment according to the following formula: I a = 0.2 * S S = (100/CN) - 10 31
The values obtained for the catchments of the Swat River are included in Table 1.19. No Table 1.19 Calculation of Water Losses Weighted CN S Ia=0.2S Reach 1 Gabral U/S Conf Ushu 74 88.0 17.6 2 Ushu U/S Conf Gabral 73 94.7 18.9 3 Swat U/S Weir 79 66.6 13.3 4 Swat Weir-PH 78 72.8 14.6 To transform the precipitation into run-off the SCS unit hydrograph was selected. The SCS unit hydrograph is a dimensionless single peaked UH. The SCS suggests that the UH lag time (t lag ) of the hydrograph can be related to the time of concentration (t c ) as: t lag = 0.6 * t c The time of concentration can be estimated as: tc = 3 * L 1.15 /(154 * (h u h d ) 0.38 ) L = Length of flow in meters h u = Elevation at the highest point in meters h d = Elevation at lowest point in meters The values of the times of concentration and lags for the catchments and channels are given in Table 1.20. Table 1.20 Time of Concentration and Lags Time of Concentration (minutes) Lag Subcatchment (minutes) Catchment Channel Catchment Channel Gabral 1541 925 Ushu 846 507 Swat-1 553 452 332 271 Swat-2 530 240 318 144 Simulation of September 1992 Flood The 1992 flood recorded at the hydrologic station Kalam was simulated using the parameters described above. The input data to simulate the flood, comprises the precipitation recorded on September 9 th of 1992 at meteorological station Kalam. Other precipitation data of the storm is not available to improve the data basis of the storm. 32
Precipitation over larger areas decrease as the areas of the storm increase, then recorded precipitation represents point values. The precipitation was calibrated to meet the flood values recorded at Kalam. The reduction coefficient is within the limits of the study on storms on the Swat catchment in reference 4. In this regard, it has to be pointed out that the Swat catchment is not at the centre of the storm analyzed in the study and is not expected to be at the centre of the storm when a major storm occurs. The values of the precipitation recorded the 09/09/1992 and the reduced values are presented in Table 1.21. Table 1.21 Precipitation of 9/9/1992 Time Precipitation (mm) (Hours) Recorded Reduced 1:00 AM 2.5 1.4 2:00 AM 2.5 1.4 3:00 AM 2.5 1.4 4:00 AM 3.8 2.1 5:00 AM 1.3 0.7 6:00 AM 1.3 0.7 7:00 AM 0.0 0.0 8:00 AM 2.3 1.3 9:00 AM 1.3 0.7 10:00 AM 1.3 0.7 11:00 AM 2.5 1.4 12:00 PM 6.3 3.5 1:00 PM 5.1 2.8 2:00 PM 3.8 2.1 3:00 PM 7.6 4.2 4:00 PM 57.7 31.7 The results of the simulation of the September 1992 are shown in Figure 1.21. A summary of the observed and simulated peak values is included in Table 1.22. 33
Figure 1.21 Simulation of September 92 Flood Table 1.22 Comparison of Observed and Simulated Flood Peak Flood (m 3 /s) Flood Date Time Simulated 10-Sep-92 2:00 374.40 Observed 10-Sep-92 0:00 381.14 The time to peak of the simulated flood is two hours later than the observed flood and the volume of the simulated flow is slightly smaller that the volume of the observed flood. However, the results of the simulation are considered satisfactory. Consequently, it was concluded that the simulation of the September 1992 flood represents the conditions in the catchment during a major flood event, and the simulation of the 100, 1,000 and 10,000 flood was undertaken. 1.4.5 Simulation of Rainfall Generated Floods To establish the precipitation model to be used for simulation of the maximum floods generated by rainfall, frequency analysis of the annual maximum hourly and daily precipitation recorded at Kalam was performed. The series of maximum hourly and daily precipitation recorded at the meteorological station Kalam is given in Table 1.23. 34
Table 1.23 Kalam: Maximum Precipitation Maximum Precipitation (mm) Maximum Precipitation (mm) Year Hourly Daily Year Hourly Daily 1963 14.0 47.2 1985 13.7 24.4 1964 10.9 65.5 1986 26.7 62.0 1965 15.2 43.4 1987 15.7 48.8 1966 7.6 40.9 1988 10.2 51.8 1967 36.1 51.6 1989 61.0 88.9 1968 12.2 66.8 1990 30.5 59.2 1969 14.2 45.0 1991 41.9 80.0 1970 15.5 41.9 1992 57.7 94.0 1971 10.7 39.6 1993 22.9 38.4 1972 10.7 26.7 1994 21.6 62.6 1973 9.9 43.4 1995 19.3 108.0 1974 18.5 34.3 1996 14.5 52.1 1975 19.3 68.6 1997 12.7 83.8 1976 15.2 55.9 1998 20.8 82.6 1977 20.1 62.2 1999 31.2 99.1 1978 30.7 51.8 2000 20.3 64.8 1979 8.6 63.2 2001 15.2 33.3 1980 12.7 39.6 2002 16.5 60.2 1981 12.2 116.3 2003 11.4 68.6 1982 17.3 37.8 2004 9.1 80.0 1983 35.6 40.6 2005 17.8 62.7 1984 13.2 49.0 2006 15.2 69.9 Various frequency distributions were applied to estimate the maximum precipitation for the large period of return. Various distribution give good results, but the 3-parameter log normal distribution adjusted by the method of maximum likelihood gives the best fit for both hourly and daily maximum precipitation (see Table 1.31a and 1.31b). The results of the frequency analysis of maximum hourly and daily precipitation are shown on Table 1.24 an in Figure.1.22. Table 1.24 Kalam: Frequency Analysis of Maximum Precipitation Return Period Maximum Precipitation (mm) (Years) Hourly Daily 2 16.2 62.0 5 25.5 82.0 10 33.5 95.5 20 42.4 108.7 50 56.1 126.0 100 68.0 139.3 1000 118.7 185.5 10000 190.4 236.0 35
-1.40 0.60 2.60 4.60 6.60 8.60 Feasibility Study 1000 1.1 2 5 Return Period (years) 10 25 50 100 200 500 1,000 10,000 Hourly Daily Maximum Precipitation (mm) 100 10 1 50 20 10 5 2 1 Probability (%) 0.1 0.01 Figure 1.22 Frequency Analysis of Maximum Precipitation For simulation of the maximum floods various distributions of precipitation were applied to the maximum precipitation. The model was the run with the catchment conditions of the September event. The distribution of the precipitation of the September 1992 event was found to be the most critical, producing the highest flood. Therefore, the distribution of the September 1992 was adopted for estimation of the maximum floods. The hyetographs of the other storms are given in Table 1.25. 36
Table 1.25 Hyetographs of Storms Time Precip (mm) Time Precip (mm) Time Precip (mm) In Date 8/9/92 In Date 1/5/89 In Date 24/5/95 2400 2.5 100 1.8 2400 5.1 100 2.5 200 4.6 100 4.3 200 2.5 300 1.8 200 4.6 300 2.5 400 0 300 3.8 400 3.8 500 0 400 3.8 500 1.3 600 0 500 5.1 600 1.3 700 0 600 5.1 700 0 800 61 700 6.4 800 2.3 900 1.3 800 0 900 1.3 1000 1.3 900 6.4 1000 1.3 1100 6.3 1000 6.4 1100 2.5 1200 3.8 1100 6.4 1200 6.3 1300 2.5 1200 6.4 1300 5.1 1400 2.5 1300 6.4 1400 3.8 1500 6.3 1400 7.6 1500 7.6 1600 2.5 1500 5.1 1600 57.7 1700 5.8 1600 5.1 1800 5.6 1700 3.8 1900 1.5 1800 3.8 2000 2.3 1900 12.7 2100 5.3 2000 6.4 2200 0 2100 0 2300 0 2200 6.4 2400 1 2300 3.8 100 2 2400 3.8 200 5.6 128.7 300 10.2 400 7.6 500 2 600 0.5 700 2.5 800 10.2 900 1.3 1000 1.3 1100 0 1200 0.5 1300 0.5 The time distribution of the September 1992 rainfall is given in Table 1.26 along with the values and the data of the adopted 100-year, 1,000-year and 10,000-year maximum precipitation. 37
Table 1.26 Precipitation Data Time September 1992 Storm (mm) Maximum Reduced Storms (mm) (Hours) Observed Reduced 100-y 1,000y 10,000-y 1 2.5 1.4 2.0 2.5 3.2 2 2.5 1.4 2.0 2.5 3.2 3 2.5 1.4 2.0 2.5 3.2 4 3.8 2.1 3.0 3.8 4.8 5 1.3 0.7 1.1 1.3 1.7 6 1.3 0.7 1.1 1.3 1.7 7 0 0.0 0.0 0.0 0.0 8 2.3 1.3 1.8 2.3 2.9 9 1.3 0.7 1.1 1.3 1.7 10 1.3 0.7 1.1 1.3 1.7 11 2.5 1.4 2.0 2.5 3.2 12 6.3 3.5 5.0 6.3 8.0 13 5.1 2.8 4.0 5.1 6.5 14 3.8 2.1 3.0 3.8 4.8 15 7.6 4.2 6.1 7.6 9.7 16 57.7 31.7 33.3 57.8 73.6 When the distribution of the September 92 was applied to the 100- year maximum precipitation, the maximum 1-hour precipitation was exceeded. The precipitation data of the 100-year flood was adjusted to prevent the 1-hour maximum to exceed the maximum 1-hour precipitation with a return period of 100-year. Similarly, the reduction coefficient of the same return period was slightly reduced to meet more frequent conditions. The data presented in Table 1.26 constitutes the input data to the flood model to estimate the design floods. In the simulation of the design floods the following conditions were taken into consideration: a) The western disturbances can produce heavy precipitation during summer as well as in winter, and therefore they can produce maximum precipitation in June. b) The base flow at the beginning of the flood is considered to be high; the occurrence of a high flood resulting from snow melt is not considered to be a realistic at the same time as a flood from a rainfall scenario; rainfall is accompanied by a drop in the temperature and consequently, high snow melt floods cannot occur in the event of a rainfall generated flood; the base flow was estimated from the flow records of the gauging station at Kalam. c) As a consequence of the above, the base flow of the maximum floods is calculated for every sub-catchment from the specific discharge of the mean monthly flow at Kalam during June. The other conditions remain as in the simulation model of the 1992 flood. 38
d) The frequency analysis of maximum precipitation obtained applying the 3-parameter log normal distribution was adopted. The summary of the results of the simulation of the design floods is shown in Table 1.27, obtained from the simulation model. The hydrograph of the 10,000-year flood at the weir site, as shown by the HEC program, is depicted in Figure 1.23. The detailed hydrograph of the maximum rainfall generated floods are given in Annex 3. 1.4.6 Design Floods Figure 1.23 10,000-year Flood at Weir Table 1.27 Estimated Maximum Rainfall Generated Floods Maximum Flood (m 3 /s) Site 100-y 1,000-y 10,000-y Weir 860 1,450 2,002 Power House 1,095 1,785 2,450 From the results of the flood studies, it is concluded that the floods from snowmelt origin, estimated by frequency analysis are relevant for the short periods of return, while for the larger periods of return, the floods estimated with the precipitation run-off model are more critical. In the latter case, the design floods are composite of the large snowmelt and rainfall generated floods. The maximum values obtained from the flood analysis for the site of the weir and power house, are shown in Table 1.28. The values of the maximum floods are depicted in Figure 1.24. 39