Your search found 5 records
1 Alahacoon, Niranga; Edirisinghe, M.. 2021. Spatial variability of rainfall trends in Sri Lanka from 1989 to 2019 as an indication of climate change. ISPRS International Journal of Geo-Information, 10(2):84. [doi: https://doi.org/10.3390/ijgi10020084]
Rainfall patterns ; Trends ; Climate change ; Spatial variation ; Weather hazards ; Climatic zones ; Natural disasters ; Precipitation ; Flooding ; Monsoons ; Drought ; Arid zones ; Semiarid zones ; Geographical information systems / Sri Lanka
(Location: IWMI HQ Call no: e-copy only Record No: H050312)
(3.82 MB) (3.82 MB)
Analysis of long-term rainfall trends provides a wealth of information on effective crop planning and water resource management, and a better understanding of climate variability over time. This study reveals the spatial variability of rainfall trends in Sri Lanka from 1989 to 2019 as an indication of climate change. The exclusivity of the study is the use of rainfall data that provide spatial variability instead of the traditional location-based approach. Henceforth, daily rainfall data available at Climate Hazards Group InfraRed Precipitation corrected with stations (CHIRPS) data were used for this study. The geographic information system (GIS) is used to perform spatial data analysis on both vector and raster data. Sen’s slope estimator and the Mann–Kendall (M–K) test are used to investigate the trends in annual and seasonal rainfall throughout all districts and climatic zones of Sri Lanka. The most important thing reflected in this study is that there has been a significant increase in annual rainfall from 1989 to 2019 in all climatic zones (wet, dry, intermediate, and Semi-arid) of Sri Lanka. The maximum increase is recorded in the wet zone and the minimum increase is in the semi-arid zone. There could be an increased risk of floods in the southern and western provinces in the future, whereas areas in the eastern and southeastern districts may face severe droughts during the northeastern monsoon. It is advisable to introduce effective drought and flood management and preparedness measures to reduce the respective hazard risk levels.
2 Alahacoon, Niranga; Edirisinghe, M.; Simwanda, M.; Perera, E. N. C.; Nyirenda , V. R.; Ranagalage, M. 2022. Rainfall variability and trends over the African continent using TAMSAT data (1983-2020): towards climate change resilience and adaptation. Remote Sensing, 14(1):96. [doi: https://doi.org/10.3390/rs14010096]
Rainfall patterns ; Trends ; Climate change adaptation ; Resilience ; Weather hazards ; Climatic zones ; River basins ; Spatial distribution ; Monsoon climate ; Datasets / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H050897)
(13.40 MB) (13.4 MB)
This study reveals rainfall variability and trends in the African continent using TAMSAT data from 1983 to 2020. In the study, a Mann–Kendall (MK) test and Sen’s slope estimator were used to analyze rainfall trends and their magnitude, respectively, under monthly, seasonal, and annual timeframes as an indication of climate change using different natural and geographical contexts (i.e., sub-regions, climate zones, major river basins, and countries). The study finds that the highest annual rainfall trends were recorded in Rwanda (11.97 mm/year), the Gulf of Guinea (river basin 8.71 mm/year), the tropical rainforest climate zone (8.21 mm/year), and the Central African region (6.84 mm/year), while Mozambique (-0.437 mm/year), the subtropical northern desert (0.80 mm/year), the west coast river basin of South Africa (-0.360 mm/year), and the Northern Africa region (1.07 mm/year) show the lowest annual rainfall trends. There is a statistically significant increase in the rainfall in the countries of Africa’s northern and central regions, while there is no statistically significant change in the countries of the southern and eastern regions. In terms of climate zones, in the tropical northern desert climates, tropical northern peninsulas, and tropical grasslands, there is a significant increase in rainfall over the entire timeframe of the month, season, and year. This implies that increased rainfall will have a positive effect on the food security of the countries in those climatic zones. Since a large percentage of Africa’s agriculture is based only on rainfall (i.e., rain-fed agriculture), increasing trends in rainfall can assist climate resilience and adaptation, while declining rainfall trends can badly affect it. This information can be crucial for decision-makers concerned with effective crop planning and water resource management. The rainfall variability and trend analysis of this study provide important information to decision-makers that need to effectively mitigate drought and flood risk.
3 Alahacoon, Niranga; Edirisinghe, M.; Ranagalage, M. 2021. Satellite-based meteorological and agricultural drought monitoring for agricultural sustainability in Sri Lanka. Sustainability, 13(6):3427. [doi: https://doi.org/10.3390/su13063427]
Drought ; Monitoring ; Sustainable agriculture ; Weather hazards ; Precipitation ; Rain ; Temperature ; Monsoons ; Spatial analysis ; Remote sensing ; Satellite observation ; Vegetation index ; Moderate resolution imaging spectroradiometer / Sri Lanka
(Location: IWMI HQ Call no: e-copy only Record No: H050898)
(5.57 MB) (5.57 MB)
For Sri Lanka, as an agricultural country, a methodical drought monitoring mechanism, including spatial and temporal variations, may significantly contribute to its agricultural sustainability. Investigating long-term meteorological and agricultural drought occurrences in Sri Lanka and assessing drought hazard at the district level are the main objectives of the study. Standardized Precipitation Index (SPI), Rainfall Anomaly Index (RAI), and Vegetation Health Index (VHI) were used as drought indicators to investigate the spatial and temporal distribution of agriculture and meteorological droughts. Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) data from 1989 to 2019 was used to calculate SPI and RAI. MOD13A1 and MOD11A2 data from Moderate Resolution Imaging Spectroradiometer (MODIS) from 2001 to 2019, were used to generate the Vegetation Condition Index (VCI) and Temperature Condition Index (TCI). Agricultural drought monitoring was done using VHI and generated using the spatial integration of VCI and TCI. Thus, various spatial data analysis techniques were extensively employed for vector and raster data integration and analysis. A methodology has been developed for the drought declaration of the country using the VHI-derived drought area percentage. Accordingly, for a particular year, if the country-wide annual extreme and severe drought area percentage based on VHI drought classes is =30%, it can be declared as a drought year. Moreover, administrative districts of Sri Lanka were classified into four hazard classes, No drought, Low drought, Moderate drought, and High drought, using the natural-beak classification scheme for both agricultural and meteorological droughts. The findings of this study can be used effectively by the relevant decision-makers for drought risk management (DRM), resilience, sustainable agriculture, and policymaking.
4 Alahacoon, Niranga; Edirisinghe, M.. 2022. A comprehensive assessment of remote sensing and traditional based drought monitoring indices at global and regional scale. Geomatics, Natural Hazards and Risk, 13(1):762-799. [doi: https://doi.org/10.1080/19475705.2022.2044394]
Drought ; Assessment ; Remote sensing ; Monitoring ; Forecasting ; Evapotranspiration ; Precipitation ; Temperature ; Soil moisture ; Satellite imagery ; Socioeconomic aspects ; Indicators ; Models
(Location: IWMI HQ Call no: e-copy only Record No: H051084)
https://www.tandfonline.com/doi/pdf/10.1080/19475705.2022.2044394
https://vlibrary.iwmi.org/pdf/H051084.pdf
https://vlibrary.iwmi.org/pdf/H051084.pdf
(4.12 MB) (4.12 MB)
This study reports a comprehensive review on drought indices used in monitoring meteorological, agricultural, hydrological, and socio-economic drought. Drought indices have been introduced as an important approach to quantitative and qualitative calculations of drought’s severity and impact. There were 111 drought indices reviewed in this study, which fall into two categories: traditional (location-specific/model) and remote sensing (RS). Out of 111 indices, 44 belong to the traditional indices and 67 belong to the RS section. This study shows that meteorological drought monitoring has the highest number (22) of traditional indices, about 20% overall, while the lowest (7) agricultural drought monitoring is 6.3%. The specialty is that when considering remote sensing-based drought indices, 90% are used for agricultural drought monitoring and 10% for hydrological and meteorological drought monitoring. However, the study found that advances in satellite technology have accelerated the design of new drought indices and that replacing traditional location-specific data with satellite observation makes it easier to calculate more spatial distribution and resolution.
5 Maduranga, U. G. D.; Edirisinghe, M.; Alahacoon, Niranga; Ranagalage, M. 2022. Spatiotemporal variability of lightning activity over the railway network in Sri Lanka with special attention to the proposed suburban railway electrification network. Infrastructures, 7(7):92. [doi: https://doi.org/10.3390/infrastructures7070092]
Lightning ; Railways ; Spatial variation ; Transportation ; Safety ; Protection ; Electrification ; Weather hazards ; Vulnerability ; Population density / Sri Lanka
(Location: IWMI HQ Call no: e-copy only Record No: H051311)
https://www.mdpi.com/2412-3811/7/7/92/pdf?version=1657704167
https://vlibrary.iwmi.org/pdf/H051311.pdf
https://vlibrary.iwmi.org/pdf/H051311.pdf
(3.25 MB) (3.25 MB)
This study is oriented towards the investigation of the spatiotemporal variability of the lightning activity over the railway network in Sri Lanka using -lightning data from 1998 to 2014 that were downloaded from the database of Lightning Imaging Sensor (LIS) onboard NASA’s Tropical Rainfall Measuring Mission (TRMM). The study has also been extended to study the lightning activity over the proposed suburban railway electrification network. GIS was used to conduct an annual and seasonal analysis of the railway network, which consists of nine major railway lines, to identify vulnerable stations and segments. The average annual lightning flash density over a 1447 km-long railway network of Sri Lanka varies between 5.08–16.58 flashes/(km2 year). The railway lines run across the western and southern regions of the country have been identified as being in areas with higher lightning activity. In comparison to other railway lines, the Kelani Valley line in the Colombo district and Colombo-Maradana to Polgahawela segment of the Mainline are particularly vulnerable to lightning activity. These areas have also been recognized as regions with higher population density. The proposed 102 km long railway electrification network in Sri Lanka is also within higher population density segments, with higher lightning flash density values between 10.55–16.53 flashes/(km2 ·year). As a result, to improve the operational efficiency of the proposed electrification network, a fully coordinated lightning protection system in accordance with the findings of this study is strongly suggested.
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