Your search found 5 records
1 Shah, Tushaar; Mehta, M.; Sankar, G.; Mondal, S.. 2012. Organizational reform in Gujarat’s electricity utility: lessons for revitalizing a bureaucratic service delivery agency. IWMI-Tata Water Policy Research Highlight, 6. 7p.
(Location: IWMI HQ Call no: e-copy only Record No: H045175)
(1.03MB)
2 Pani, Peejush; Alahacoon, Niranga; Amarnath, Giriraj; Bharani, Gurminder; Mondal, S.; Jeganathan, C. 2016. Comparison of SPI [Standardized Precipitation Index] and IDSI [Integrated Drought Severity Index] applicability for agriculture drought monitoring in Sri Lanka. Paper presented at the 37th Asian Conference on Remote Sensing (ACRS): Promoting Spatial Data Infrastructure for Sustainable Economic Development, Colombo, Sri Lanka, 17-21 October 2016. 8p.
Precipitation ; Drought ; Monitoring ; Agriculture ; Climate change ; Meteorology ; Remote sensing ; Vegetation ; Rain ; Temperature ; Soil moisture ; Spatial distribution ; Statistical analysis / Sri Lanka
(Location: IWMI HQ Call no: e-copy only Record No: H047942)
Increasing frequency of drought events coupled uncertainty imparted by climate change pose grave threat to agriculture and thereby overall food security. This is especially true in South Asian region where world’s largest concentration of people depends on agriculture for their livelihood. Indices derived from remote sensing datasets signifying different bio-physical aspects are increasingly used for operational drought monitoring. This study focuses on evaluating a newly created index for agricultural drought referred as Integrated Drought Severity Index (IDSI) in comparison with the traditional Standardized Precipitation Index (SPI) primarily representing precipitation condition to delineate drought using custom created ArcGIS toolbox for a period of fourteen years (2001-2014) in Sri Lanka. SPI created using remotely sensed PERSIANN precipitation dataset was compared with the IDSI created using hybrid datasets. IDSI is created based on seamless mosaic of remotely sensed multi-sensor data that takes vegetation (computed from MODIS data product MOD09A1), temperature (MOD11A2) and precipitation (TRMM & GPM) status into consideration. The comparative study was made to assess the efficiency of newly created index and ArcGIS toolbox techniques for near real-time monitoring of spatio-temporal extent of agricultural drought. The result showed significant correlation of 0.85 between the two indices signifying the potential of using IDSI that integrates the response of agriculture drought variables (vegetation, rainfall, temperature and soil moisture) in monitoring shortterm drought and application in risk reduction measures.
3 Mondal, S.; Jeganathan, C.; Amarnath, Giriraj; Pani, Peejush. 2017. Time-series cloud noise mapping and reduction algorithm for improved vegetation and drought monitoring. GIScience and Remote Sensing, 54(2):202-229. [doi: https://doi.org/10.1080/15481603.2017.1286726]
Climate change ; Drought ; Clouds ; Noise ; Monitoring ; Vegetation ; Satellite observation ; Satellite imagery ; Land cover mapping ; Remote sensing ; Spatial distribution ; Models ; Statistical methods ; Performance evaluation ; Homogenization ; Agriculture / Sri Lanka
(Location: IWMI HQ Call no: e-copy only Record No: H048010)
Moderate Resolution Imaging Spectro-radiometer (MODIS) time-series Normalized Differential Vegetation Index (NDVI) products are regularly used for vegetation monitoring missions and climate change analysis. However, satellite observation is affected by the atmospheric condition, cloud state and shadows introducing noise in the data. MODIS state flag helps in understanding pixel quality but overestimates the noise and hence its usability requires further scrutiny. This study has analyzed MODIS MOD09A1 annual data set over Sri Lanka. The study presents a simple and effective noise mapping method which integrates four state flag parameters (i.e. cloud state, cloud shadow, cirrus detected, and internal cloud algorithm flag) to estimate Cloud Possibility Index (CPI). Usability of CPI is analyzed along with NDVI for noise elimination. Then the gaps generated due to noise elimination are reconstructed and performance of the reconstruction model is assessed over simulated data with five different levels of random gaps (10–50%) and four different statistical measures (i.e. Root mean square error, mean absolute error, mean bias error, and mean absolute percentage error). The sample-based analysis over homogeneous and heterogeneous pixels have revealed that CPI-based noise elimination has increased the detection accuracy of number of growing cycle from 45–60% to 85–95% in vegetated regions. The study cautions that usage of time-series NDVI data without proper cloud correction mechanism would result in wrong estimation about spatial distribution and intensity of drought, and in our study 50% of area is wrongly reported to be under drought though there was no major drought in 2014.
4 Pal, P. K.; Ganguly, B.; Roy, D.; Guha, A.; Hanglem, A.; Mondal, S.. 2017. Social and biophysical impacts of watershed development programmes: experiences from a micro-watershed area in India. Water Policy, 19(4):773-785. [doi: https://doi.org/10.2166/wp.2017.189]
Watershed management ; Integrated management ; Development programmes ; Socioeconomic environment ; Biophysics ; Microirrigation ; Drainage ; Water conservation ; Technological changes ; Crop production ; Cropping patterns ; Agricultural productivity ; Dry farming ; Land use ; Farm area / India / West Bengal / Cooch Behar / Rangamati Micro-Watershed
(Location: IWMI HQ Call no: e-copy only Record No: H048228)
(0.37 MB)
Rainwater conservation and soil erosion prevention are vital for the economic and financial sustainability of dry land agriculture. An integrated watershed development programme is thus a means of achieving these goals. Presently, integrated watershed management is receiving worldwide recognition as an effective model for watershed planning. A watershed is considered the basic geographical unit for developing any plan by integrating various social, economic, and policy factors with modern science. Hence, it is an approach to develop the basic resources for sustainable life support. The present study was conducted to assess the impacts of the watershed development programme on the social and biophysical aspects in a micro-watershed area of Cooch Behar district, West Bengal, India. This study confirmed that the project had positive effects that strengthened the socio-personal and economic characteristics of the farmers and improved the biophysical environment of the farms. The soil and water conservation efforts have increased the total cultivable area as well as improved the irrigation and drainage facilities in the micro-watershed units, thereby increasing the acreage and productivity of crops.
5 Amarnath, Giriraj; Pani, Peejush; Alahacoon, Niranga; Chockalingam, J.; Mondal, S.; Matheswaran, K.; Sikka, Alok; Rao, K. V.; Smakhtin, Vladimir. 2019. Development of a system for drought monitoring and assessment in South Asia. In Mapedza, Everisto; Tsegai, D.; Bruntrup, M.; McLeman, R. (Eds.). Drought challenges: policy options for developing countries. Amsterdam, Netherlands: Elsevier. pp.133-163. (Current Directions in Water Scarcity Research Volume 2) [doi: https://doi.org/10.1016/B978-0-12-814820-4.00010-9]
Drought ; Monitoring ; Assessment ; Temperature ; Rain ; Precipitation ; Satellite observation ; Weather forecasting ; Land use ; Land cover ; Remote sensing ; Vegetation index ; Agriculture ; Crop yield / South Asia / India / Sri Lanka / Pakistan
(Location: IWMI HQ Call no: IWMI Record No: H049369)
(15.10 MB)
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