Hydrology & Meteorology

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Browsing Hydrology & Meteorology by Author "Bagale, Damodar"

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    Drought Detecting and Monitoring over Terai and Mountain Region of Nepal
    (Institute of Science & Technology, 2023-07) Bagale, Damodar
    This study was conducted using 42 years rainfall data since 1977 to 2018 of 107 meteorological stations to examine monthly to decadal rainfall variability of 107 stations over the country were used. The western region has observed low rainfall in pre-monsoons, monsoon, and post-monsoon seasons but observed heavy rainfall in winter season in comparison with the central and eastern regions. The contribution of winter rainfall to annually varied from 0.68% in the year 2006 to 7.04 % in the year 1989. Similarly, the contribution of monsoon rainfall annually varied from 76 % in the year 1992 to 86 % in 1984.The decadal wise rainfall was decreased both in monsoon and winter seasons in the recent couple of decades. There was a strong correlation between the rainfall and Southern Oscillation Index (SOI) in the monsoon season and weak in winter. Generally, large negative/positive magnitudes of SOI on the Indian and Pacific Ocean influence weakening/strengthening monsoon rainfall in Nepal. During El Niño year’s average deficit rainfall was approximately 9 % below the average monsoon rainfall. However, the negative trends of annual rainfall dominated over the country. This study identified winter, summer and annual drought events using the Standard Precipitation Index (SPI). Monthly rainfall was used as an input variable to generate the SPI of 107 stations from 1977 to 2018. The SPI threshold was used to identify, categorize and monitor droughts over Nepal. For this, we investigated the frequency, duration, and severity of drought events. The SPI3, SPI4 and SPI12 month time scales were interpolated to illustrate the spatial patterns of major drought episodes and their severity. In winter large percentage of stations over the country showed a significant decreasing trend for SPI3 in comparison with the monsoon (SPI4) and annual (SPI12).The drought events in El Niño years and non-El Niño years were more strongly related between SPI and SOI than the average years. The relationship between SPI and the climate indices such as the SOI and ONI anomaly over the Niño 3.4 has suggested that one of the causes for summer droughts is El Niño. This study indicated that summer droughts occurred in both El Niño and non-El Niño years. Out of eight drought years, only four drought years were associated with El Niño episodes (1982,1992, 2009, and 2015), and the remaining four drought years (1977,1979, 2005, and 2006) were recorded in non-El Niño years. Similarly, winter and annual droughts evolved in El Niño and non-El Niño years. There is a strong correlation (0.53) between SPI4 and SOI in the monsoon season and a weak in SPI3 and SOI is - 0.31 in the winter at 95 percent confidence level. The regional analysis identified that there is strong correlation between rainfall and SOI for the western region than the central and eastern regions in the monsoon season. Similarly, the correlation coefficient between rainfall and SOI in winter is strong in the western region than in the central eastern regions. Generally, during drought years; SPI and SOI have a strong phase relation compared to average years. Droughts have been recorded more frequently in Nepal since 2000.The areas of Nepal affected by extreme, severe and moderate drought in winter were 4, 21 and 37 percent. Likewise, the areas of Nepal affected by average extreme, severe and moderate drought both in summer and annual events are 7, 9, and 18 percentages and 7, 11, and 17 percentages respectively. The drought-hazardous zones are highest in the western and northwest parts in comparison with the central and eastern regions on both SPI4 and SPI12 time scales. About 47 and 30 percent of areas of Nepal were found to be under high and very high drought hazardous zones of the total area based on SPI4 and SPI12 time scales. यो शोधकार्य नेपालका एक सय सात वटा मौसमी केन्द्रहरूको मासिक तथा वार्षीक वर्षाको परिवर्तनशीलता तथा परिणात्मक अनुसन्धान अन्वेषण गर्नका लागि गत ४२ वर्ष (सन् १९७७–२०१८) को तथ्यङ्क प्रयोग गरी गरीएको हो । पश्चिम क्षेत्रमा प्रि–मनसुन, मनसुन र मनसुन पश्चातको मौसममा कमवर्षा हुने गरेको छ । तर मध्य र पूर्वी क्षेत्रको तुलनामा त्याँहा हिउँदमा भारी वर्षा हुने गरेको पाइयो । हिउँदे वर्षा सन् २००६ मा ०.६८ प्रतिशत र सन् १९८९ मा ७.०४ प्रतिशतसम्म परेको देखियो । त्यसैगरी मनसुन वर्षाको योगदान १९९२ मा ७६ प्रतिशत र सन् १९८४ मा ८६ प्रतिशत सम्म वार्षिक भिन्नता पाइयो । पछिल्ला चार दशकहरुमा वर्षे मनसुन र जाडो मौसममा हिउदे वर्षा घटेको अनुसन्धान बाट देखिएको छ । मनसुनी वर्षा र साउदन ओसिलेसन इन्डेक्स (SOI) विचको सम्बन्ध वर्षा याममा बलियो र जाडोमा कमजोर पाइयो । सामान्यतया हिन्द र प्रशान्त महासागरमा SOI को नकारात्मक र सकारात्मक परिणामले नेपालमा मनसुन वर्षालाई कमजोर र सशक्त बनाउन प्रभाव पार्दछ । एलनिनो वर्षको समयावधीमा (कम बर्षाको अवधिमा) औसत मनसुन वर्षा भन्दा लगभग ९ प्रतिशत कम वर्षा परेको अनुसन्धानले देखायो । यद्यपि वर्षाको घढ्दो क्रम देशमा बढिरहेको छ । यस अध्ययनले जाडो, गर्मी तथा वार्षिक खडेरी घटनाहरू मानक वर्षा सूचकांक (SPI) प्रयोग गरी पहिचान गरेको छ । सन् १९७७ देखि २०१८ सम्म एक सय सात वटा मौसमी केन्द्रहरुको SPI निकाल्नको लागि मासिक वर्षालाई उपायोग गरिएको थियो । SPI थ्रेसहोल्डलाई नेपालमा खडेरी पहिचान गर्न, वर्गीकरण गर्न र निरन्तर निगरानी गर्न प्रयोग गरिएको थियो । यसका लागि खडेरीका घटनाहरुको आवृति, अवधि र गम्भीरताको अनुसन्धान गरियो । हिउँदमा (SPI3), वर्षामा (SPI4) र वार्षिक रूपमा परिमाण (SPI12), विभिन्न अवधिहरुमा, प्रमुख खडेरी एपिसोडहरु र तिनीहरुको वार्षीक मनसुनी प्रभाव को तुलनामा हिउदमा उल्लेखनीयरुपमा घट्ने प्रवृत्ति देखायो । एलनिनो वर्ष र गैर एलनिनो वर्षहरुमा खडेरीका घटनाहरु SPI र वर्षा बिचमा बढी जोडदार रूपमा सम्बन्धित बडेको पाइयो । औसत वर्ष भन्दा SPI, निनो (३.४) क्षेत्रमा SOI र ONI जस्ता जलवायु सुचकाङ्कहरु बिचको सम्बन्धले ग्रीष्म कालीन खडेरीको समयको कारण एलनिनो हो भनी कीटान गरिएको छ । यस अध्ययनले ग्रीष्मकालीन खडेरी एलनिनो (१९८२, १९९२, २००९ र २०१५) वर्षहरुमा र आठ खडेरी वर्षहरु मध्ये केवल चार खडेरी वर्षहरु एलनिनो एपिसोडहरुसंग सम्बन्धित थिए र बाकि खडेरी वर्षहरु (१९७७, १९७९, २००५ र २००६) समेत पाइएको थियो । त्यस्तै खडेरीका घटनाहरु हिउद, ग्रीष्म कालीन र वार्षिक खडेरी एलनिनो र गैर–एलनिनो वर्षहरुमा विकसित भयको पाइयो । मनसुन याममा SPI र SOI बिच बलियो सम्बन्ध र हिउँदमा केही कमजोर सम्बन्ध रहेको (९५ प्रतिशत) सार्थक स्तरमा देखियो । क्षेत्रीय विश्लेषणगर्दा मनसुन समयमा मध्य र पूर्वी क्षेत्रको तुलनामा पश्चिमी क्षेत्रको वर्षा र SOI बिच कमजोर सम्बन्ध रहेको पाइयो । त्यसैगरी, हिउँदे वर्षा र SOI बिचको सम्बन्ध गणांक मध्य पूर्वी क्षेत्रहरु भन्दा पश्चिमी क्षेत्रमा बलियो देखियो । सामान्यतया खडेरी वर्षहरुमाः SPI र SOI बिच औसत वर्षको तुलनामा बलियो चरण सम्बन्ध अध्यनले पुष्टी गरेको छ । नेपालमा सन् २००० यता खडेरी धेरै पटक रेकर्ड गरिएको छ । नेपालको हिउँदमा चरम, गम्भीर र मध्यम खडेरीबाट प्रभावित क्षेत्रहरु क्रमश ४, २१ र ३७ प्रतिशत पाइयो । त्यसैगरी ग्रीष्म र वार्षीक समयावधीमा औसत चरम, गम्भीर र मध्यम खडेरीबाट प्रभाभित क्षेत्रहरु क्रमश ७, ९ र १८ प्रतिशत र ७, ११ र १७ प्रतिशत छन् । त्यसैगरि मध्य र पूर्वी क्षेत्रहरुको तुलनामा पश्चिम र उत्तर–पश्चिमी भागहरुमा खडेरीको आँकडा उच्च र अति उच्च भएको पाइयो । दुवै क्षेत्रहरुमा वर्षाका परीमाणहरु भने सबैभन्दा बढी भएको अध्यनले देखायो । नेपालका करिब ४७ र ३० प्रतिशत क्षेत्रहरु SPI4 र SPI12 टाइम स्केलमा उच्च र अति उच्च खडेरीको जोखिमयुक्त क्षेत्रहरु अन्तर्गत रहेको पाइयो ।
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    Estimation And Analysis of Low, High and Mean Monthly Flow For Ungauged Manohara River
    (Department of Hydrology and Meteorology, 2007) Bagale, Damodar
    Manohara River, an important tributary, of Bagmati River has a catchment area of66.34sq.km. with length andperimeter as 24 km and 47.25 km respectively. The formfactor is 0.115, elongation ratio as 0.38, the circulatory ratio as 0.37 and compactnesscoefficient is 1.5. These statistics relating to the shape of the catchment indicate that thecatchment is not symmetrical in shape. It has narrow width at the lower reach and has afan shape at the upper reach with relatively short river length and high relief of 1038meters. There is a possibility of flash flood with high intensity of monsoon rain which isfrequently experienced. The Manohara River is ungauged and this catchment has fertileagriculture fields supplying vegetables to Kathmandu city in all seasons. The settlement in this catchment is rapidly growing due to overcrowding of the nearbyKathmandu city. In the near future the agriculture-fields will require irrigation, thegrowing settlement will require more water supply and more link-roads have to beconstructed with many culverts and bridges. Since, no discharge data for Manohara riverwere available, low flows and high flows have been estimated using transposition datawith the help of Cudworth equation, as referred by WECS/DHM method. The dischargedata of Bagmati River at Khokana, Chovar and Sundarijal have been transposed for theManohara River forthe estimation of high flows and mean monthly flows. The low flowshave been estimated with WECS/DHM method using the catchment area with associatedparameters. The monthly minimum low flow for the return period of 2 year has beenfound to be 1m 3 /s. Similarly the monthly minimum flows have been calculated as 72 m /sand .56m 3 /s for the return periods of 10 and 20 years respectively. The one day minimumlow flow value for the return period of 2 years, 10 years and 20 years have beencalculated as 1m 3 /s, 0.65m 3 /s and 0.5m 3 /s. These values are very important for irrigationand domestic water supply projects that are likely to be implemented in the near future forthis ungauged river. The flow duration curve has also been constructed for this river withthe WECS/DHM method. The flow duration curve indicates that exceedence probabilityof 100% flow is only 0.14m 3 /s. Similarly exceedence probability of 20% and 60% are10m 3 /s and 2m 3 /s respectively. These values are also very important for irrigation projectsand drinking water projects in near future. Regarding high flood analysis for ManoharaRiver, discharge data were transposed to the Manohara River from Chovar and Khokanaand Sundarijal sites. Estimated floods for 5 years, 20 years, 50 years and 100 years have i 3 been calculated as about 201m 3 /s, 303 m 3 /s, 372 m ii 3 /s and 422 m 3 /s respectively. Thedischarge data of Bagmati River at Chovar and Khokana with transposed datamethodology for Manohara River gives reasonable estimated floods agreeing with thevalues estimated by WECS/DHM method. This is because the bridge site near Pepsi ColaFactory, Chovar site, and Khokana site all are situated in the flood plains of Kathmanduvalley, butSundarijal gauging site is located on the higher elevation near the origin ofBagmati River. The bridge site of Manohara near the Pepsi cola factory, Chovar site andKhokana site have same type of physiographic characteristics but Sundarijal site hascompletely different physiographic characteristics. Therefore, data from Sundarijal site isnot suitable for estimation of high flood for Manohara by data transposition method. The estimated high floods by transposition method will be useful for designing the bridgenear the Pepsi Cola Factory and many link roads with culverts in near future.The resultsfrom the discharge data transposition method for ungauged Manohara River which will beuseful for water resources project in the near future. Such techniques will also be usefuland can be applied for many ungauged catchments in various partsof the country.