Was the 2002/03 Maha's Bumper Paddy Harvest due to El Nino?

Zubair, Lareef; Perera, R. N. N.; Yahiya, Zeenas

doi:10.4038/engineer.v38i4.7229

Cited by 4 publications

(5 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Rice and coconut are the crops that affect food security the most. Analysis of the ENSO impact on rice (Zubair et al, 2005) and on coconut (Peiris, 2004) are used in policy-making and seasonal planning. Currently seasonal rainfall predictions are monitored by the Sri Lanka government agencies in providing guidance on the choice of crops and extent of land to be cultivated at the start of each agricultural season.…”

Section: Resultsmentioning

confidence: 99%

Predictability of Sri Lankan rainfall based on ENSO

Zubair¹,

Siriwardhana

Chandimala

et al. 2007

Intl Journal of Climatology

Self Cite

View full text Add to dashboard Cite

Investigating the year-round rainfall of Sri Lanka provides understanding into the South Asian monsoon system as it compliments studies on the Indian summer monsoon. The El Niño-Southern Oscillation (ENSO) is a primary mode of climate variability of this area. Here, the predictability of Sri Lanka rainfall based on ENSO is quantified based on composite analysis, correlations and contingency tables. The rainfall is modestly predictable based on ENSO

show abstract

Section: Resultsmentioning

confidence: 99%

Predictability of Sri Lankan rainfall based on ENSO

Zubair¹,

Siriwardhana

Chandimala

et al. 2007

Intl Journal of Climatology

Self Cite

View full text Add to dashboard Cite

show abstract

“…Zubair et al () showed that variations in the Niño 3.4 dataset explained some of the variability in seasonal agricultural production. The relationship between the scores and monthly anomalies of Niño 3.4 (Rayner et al , ) was assessed using crosswavelet transforms (XWTs) and wavelet coherences (WTCs).…”

Section: Methodsmentioning

confidence: 99%

“…Thus far, studies in Sri Lanka have predominantly focused on characterizing specific years of anomalous rainfall (Jayamaha, ); spatiotemporal patterns of rainfall (Suppiah and Yoshino, , ); and relationships among rainfall, rice production, and Southern Oscillation Index and other El Niño indices (Suppiah, , , Kane, , Zubair, , Malmgren et al , , Zubair et al , , Wickramagamage, ). Chithranayana () developed a monthly Moisture Availability Index to identify regions of Sri Lanka that are vulnerable to drought.…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal Patterns of Agricultural Drought in Sri Lanka: 1881–2010

Gunda

Hornberger

Gilligan

2015

Intl Journal of Climatology

View full text Add to dashboard Cite

A spatiotemporal analysis of two well-known agricultural drought indices, the Palmer Drought Severity Index (PDSI) and the Standardized Precipitation Index at a 9-month scale (SPI-9), is presented for Sri Lanka. The analysis was conducted based on monthly precipitation and temperature data from January 1881 to December 2010 using 13 stations distributed across the three climatic zones of the country. Principal component analysis shows that the first two principal components of PDSI and SPI-9 are spatially comparable and could physically represent the two main monsoons. A wavelet analysis of these principal components' scores for both indices indicates a stronger association between the Northeastern monsoon and El-Niño in recent decades. Correlation analysis with agricultural metrics suggests that different indices might be appropriate for each of the climatic zones in Sri Lanka. PDSI correlated best with the intermediate zone districts; SPI-9 correlated best with the dry zone districts; but neither index correlated well with the wet zone districts.

show abstract

“…There is a vast amount of literature in the transportation field regarding accessibility disruptions to critical facilities (Horner and Widener, 2011;Islam and Aktar, 2011;Kocatepe et al, 2018;Boakye et al, 2022). Generally, these accessibility studies either aim to quantify how well a network performs or identify critical points and "hot spots" such as areas with the highest economic impact (Yamano et al, 2007), vulnerability (Elalem and Pal, 2015), or risk (Zubair et al, 2006;Thacker et al, 2017). Determining hot spot areas that are likely to flood can aid in identifying where network performances are likely to degrade (Jalayer et al, 2014;Pedrozo-Acuña et al, 2017;Wang et al, 2019).…”

Section: Defining Network Accessibility and Resiliencymentioning

confidence: 99%

A network-based analysis of critical resource accessibility during floods

Preisser,

Passalacqua,

Bixler

et al. 2023

Front. Water

View full text Add to dashboard Cite

Numerous government and non-governmental agencies are increasing their efforts to better quantify the disproportionate effects of climate risk on vulnerable populations with the goal of creating more resilient communities. Sociodemographic based indices have been the primary source of vulnerability information the past few decades. However, using these indices fails to capture other facets of vulnerability, such as the ability to access critical resources (e.g., grocery stores, hospitals, pharmacies, etc.). Furthermore, methods to estimate resource accessibility as storms occur (i.e., in near-real time) are not readily available to local stakeholders. We address this gap by creating a model built on strictly open-source data to solve the user equilibrium traffic assignment problem to calculate how an individual's access to critical resources changes during and immediately after a flood event. Redundancy, reliability, and recoverability metrics at the household and network scales reveal the inequitable distribution of the flood's impact. In our case-study for Austin, Texas we found that the most vulnerable households are the least resilient to the impacts of floods and experience the most volatile shifts in metric values. Concurrently, the least vulnerable quarter of the population often carries the smallest burdens. We show that small and moderate inequalities become large inequities when accounting for more vulnerable communities' lower ability to cope with the loss of accessibility, with the most vulnerable quarter of the population carrying four times as much of the burden as the least vulnerable quarter. The near-real time and open-source model we developed can benefit emergency planning stakeholders by helping identify households that require specific resources during and immediately after hazard events.

show abstract

Was the 2002/03 Maha's Bumper Paddy Harvest due to El Nino?

Cited by 4 publications

References 3 publications

Predictability of Sri Lankan rainfall based on ENSO

Predictability of Sri Lankan rainfall based on ENSO

Spatiotemporal Patterns of Agricultural Drought in Sri Lanka: 1881–2010

A network-based analysis of critical resource accessibility during floods

Contact Info

Product

Resources

About