Predictability of stream flow and rainfall based on ENSO for water resources management in Sri Lanka

Chandimala, Janaki; Zubair, Lareef

doi:10.1016/j.jhydrol.2006.11.024

Cited by 62 publications

(38 citation statements)

References 27 publications

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“…The rain gauges are managed by the Department of Meteorology, Sri Lanka. The Department personnel inspect these gauges, archive the data, and undertake quality control of it regularly [28]. We have undertaken further quality test for this data, like identification of outliers, cross checks for extreme values, checks for drifts in the data, and cross correlation analysis.…”

Section: Methodsmentioning

confidence: 99%

Monitoring Water Resources over the Kotmale Reservoir in Sri Lanka Using ENSO Phases

Chandrasekara

Venkatraman

Kwon

2017

Advances in Meteorology

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In this study, the El Nino Southern Oscillation (ENSO) phase index is used for water management over the Kotmale reservoir in Sri Lanka. Daily rainfall data of 9 stations over the Kotmale catchment during 1960-2005 June-September (JJAS) season is investigated over the Kotmale catchment. The ENSO phases are identified based on the 0.5 ∘ C sea surface temperature (SST) anomaly over Nino 3 region. The study has brought out few stations showing increasing and a few decreasing seasonal rainfall trends for JJAS season, while there is no change in the annual rainfall for the catchment. Monthly and seasonal rainfall of all the selected stations showed negative correlation with the sea surface temperature (SST) over the Nino-3 region index during JJAS season with varying magnitudes. During the warm phase of ENSO, below average rainfall is prominent for JJAS season over many stations. The rainfall especially during early September showed a significant below average rainfall during the warm ENSO phase. The seasonal rainfall during neutral and cold ENSO phases does not experience similar significant changes as seen during warm ENSO phase. Inflow of the Kotmale reservoir shows decreasing trend for the period of 1960-2005 in the observation from all stations collectively.

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Section: Methodsmentioning

confidence: 99%

Monitoring Water Resources over the Kotmale Reservoir in Sri Lanka Using ENSO Phases

Chandrasekara

Venkatraman

Kwon

2017

Advances in Meteorology

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“…Many studies have examined the teleconnection between ENSO and precipitation throughout the tropics and in broad swaths of the extratropical regions (Ropelewski and Halpert, 1986, 1987Chiew et al, 1998;Chandimala and Zubair, 2007). In this section, using historical monthly precipitation data (1956 to 2005) and ENSO indicator data (SOI, Niño1.2, Niño3, Niño4, and Niño3.4 from 1955 to 2005), the correlation between monthly precipitation of the HRYR and ENSO indicators were examined (Table 2).…”

Section: Enso-precipitation Relationshipsmentioning

confidence: 99%

“…There have been numerous studies examining the relationship between ENSO and rainfall Halpert, 1986, 1987;Chiew et al, 1998;Chandimala and Zubair, 2007). These studies showed that rainfall variability is significantly correlated with ENSO activity across different spatiotemporal scales.…”

Section: Introductionmentioning

confidence: 99%

“…The potential for forecasting was investigated by calculating the lagged correlation between streamflow and two indicators of ENSO in that study. At a regional scale, the ENSO-streamflow teleconnection has been studied in the United States (Redmond and Koch, 1991;Cayan et al, 1999;Piechota et al, 1997;Kahya and Dracup, 1993), Turkey (Kahya and Karabork, 2001), Australia (Simpson et al, 1993;Chiew et al, 1998), Sri Lanka (Zubair andChandimala, 2006;Chandimala and Zubair, 2007), and Nepal (Shrestha and Kostaschuk, 2005). At a local scale, a significant relationship between ENSO indicators and the streamflow have been observed for a number of rivers, such as the Mississippi (Twine et al, 2005), Colombia (Gutiérrez and Dracup, 2001;Barton and Ramírez, 2004;Hamlet and Lettenmaier, 1999), Arizona's Salt River Basin (Karamouz and Zahraie, 2004), and the Ganges Rivers (Whitaker et al, 2001;Jahan et al, 2006).…”

Section: Introductionmentioning

confidence: 99%

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El Niño-Southern Oscillation and water resources in the headwaters region of the Yellow River: links and potential for forecasting

Lü¹,

Jia

Zhu

et al. 2011

Hydrol. Earth Syst. Sci.

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Abstract. This research explores the rainfall-El Niño-Southern Oscillation (ENSO) and runoff-ENSO relationships and examines the potential for water resource forecasting using these relationships. The Southern Oscillation Index (SOI), Niño1.2, Niño3, Niño4, and Niño3.4 were selected as ENSO indicators for cross-correlation analyses of precipitation and runoff. There was a significant correlation (95% confidence level) between precipitation and ENSO indicators during three periods: January, March, and from September to November. In addition, monthly streamflow and monthly ENSO indictors were significantly correlated during three periods: from January to March, June, and from October to December (OND), with lag periods between one and twelve months. Because ENSO events can be accurately predicted one to two years in advance using physical modeling of the coupled ocean-atmosphere system, the lead time for forecasting runoff using ENSO indicators in the Headwaters Region of the Yellow River could extend from one to 36 months. Therefore, ENSO may have potential as a powerful forecasting tool for water resources in the headwater regions of Yellow River.

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“…We focus on Sri Lanka given the availability of finescale data. This work shall also benefit ongoing use of climate information for risk management in the health , agriculture (Zubair 2002;Peiris et al 2008), water resources (Chandimala and Zubair 2006), and disaster management sectors (Lyon et al 2009). …”

Section: Introductionmentioning

confidence: 99%

The Effect of Grid Spacing and Domain Size on the Quality of Ensemble Regional Climate Downscaling over South Asia during the Northeasterly Monsoon

Qian

Zubair

2010

Monthly Weather Review

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The performance of an ensemble-based dynamical regional climate downscaling system is evaluated over southern Asia in a northeasterly monsoon season for different choices in grid spacing and domain size. A seven-member ensemble of the ECHAM4.5 global climate model at a resolution of about 300-km grid size was used to drive the RegCM3 regional climate model with grid sizes of 100, 50, 25, and 20 km, respectively. The performance is reported in detail over Sri Lanka. Two sets of regional model runs were undertaken to assess the effect of grid spacing and model domain size on the downscaling performance. The RegCM3 simulation with 100-km grid size significantly underestimates the height of the central mountain range in Sri Lanka, in a manner that is too coarse to capture orographic influences on the rainfall. However, the RegCM3 simulations with grid sizes from 20 to 50 km capture mesoscale features that arise from uplift condensation on the windward side of the monsoon winds due to the topography. These simulations also capture the orographic influences on the month-to-month rainfall over Sri Lanka that were absent in the ECHAM4.5. While the ''small domain'' runs [where only the forcings for the region immediately around Sri Lanka (48-118N, 768-858E) are used] are computationally more efficient, the results are overly controlled by the lateral boundary driving of the ECHAM4.5 so they inherit large uncertainty from the seven ECHAM4.5 realizations used for the RegCM3 ensemble runs. The ''large domain'' simulation used a domain comprising both land and ocean (approximately 48S-228N, 658-968E). The large-domain group of simulations produced reasonable spatial distribution of precipitation over the region. Moreover, the ensemble spread was considerably reduced in the large-domain high-resolution runs. Therefore, fine enough grid resolution (25 km or less) and sufficiently large domain size are both needed to simulate the essential features of precipitation in this tropical and monsoonal region.

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Predictability of stream flow and rainfall based on ENSO for water resources management in Sri Lanka

Cited by 62 publications

References 27 publications

Monitoring Water Resources over the Kotmale Reservoir in Sri Lanka Using ENSO Phases

Monitoring Water Resources over the Kotmale Reservoir in Sri Lanka Using ENSO Phases

El Niño-Southern Oscillation and water resources in the headwaters region of the Yellow River: links and potential for forecasting

The Effect of Grid Spacing and Domain Size on the Quality of Ensemble Regional Climate Downscaling over South Asia during the Northeasterly Monsoon

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