Your search found 13 records
1 Loeve, Ronald; Somaratne, Pallewatte G.; Ariyaratne, Badugodahewa Ranjith; Anputhas, Markandu; Jinapala, Kiribandage. 2004. Institutional changes to reduce land preparation delay in the North Central Province of Sri Lanka. Colombo, Sri Lanka: International Water Management Institute (IWMI) x, 68p. (IWMI Working Paper 069) [doi: https://doi.org/10.3910/2009.196]
Institutional development ; Irrigation systems ; Tillage ; Crop yield ; Rice ; Land tenure / Sri Lanka / North Central Province / Rajangana / Nuwarawewa / Huruluwewa / Minneriya
(Location: IWMI-HQ Call no: IWMI 631.7.2 G744 LOE Record No: H035302)
(772 KB)
Although many irrigation systems in the dry zone of Sri Lanka have water shortage problems, water consumption is very high during land preparation. This paper analyzes the impact of institutional interventions on efficient water management, especially during the land preparation period. It provides a comprehensive understanding of the factors behind prolonged periods of land preparation so that system managers and farmers communities can develop appropriate interventions to reduce water consumption
2 Amarasinghe, Upali A; Anputhas, Markandu. 2003. Intervention analysis for impact assessment of irrigation systems. Sri Lankan Journal of Applied Statistics, 4:59-81.
Irrigation systems ; Rehabilitation ; Modernization ; Irrigation canals ; Rehabilitation ; Modernization ; Irrigation programs ; Performance indexes ; Assessment ; Models / Sri Lanka / Gal Oya Irrigation Scheme
(Location: IWMI-HQ Call no: IWMI 631.7.1 G744 AMA Record No: H035775)
3 Samita, S.; Anputhas, Markandu; De Z. Abeysiriwardena, S. 2005. Accounting multi traits in recommending paddy varieties for diverse environments. Experimental Agriculture, 41(2):213-225.
(Location: IWMI-HQ Call no: IWMI 633.18 G744 SAM Record No: H035776)
4 Anputhas, Markandu; Samita, S.; De Z. Abeysiriwardena, S. 2004. Regression based on multivariate index as a tool for varietal recommendation. In Proceedings of the International Sri Lankan Statistical Conference, 28-30 December 2004. 9p.
(Location: IWMI-HQ Call no: IWMI 519.5 G000 ANP Record No: H035844)
5 Anputhas, Markandu. 2004. Multivariate approach in recommendation of crop varieties. Thesis accepted by the Postgraduate Institute of Agriculture, University of Peradeniya, Sri Lanka in partial fulfillment of the degree of Master of Philosophy. vii, 214p. + annexes.
(Location: IWMI-HQ Call no: D 310 G744 ANP Record No: H035983)
6 Anputhas, Markandu; Ariyaratne, B. Ranjith; Gamage, Nilantha; Jayakody, Priyantha; Jinapala, Kiribandage; Somaratne, Pallewatte G.; Weligamage, Parakrama; Weragala, Neelanga; Wijerathna, Deeptha. 2005. Bringing Hambantota back to normal: a post-tsunami livelihoods needs assessment of Hambantota District in southern Sri Lanka. Colombo, Sri Lanka: International Water Management Institute (IWMI). ix, 59p.
Natural disasters ; Research methods ; Mapping ; Villages ; Income generation ; Statistics ; Irrigated farming ; Livestock ; Fisheries ; Economic aspects ; Rehabilitation / Sri Lanka / Hambantota
(Location: IWMI-HQ Call no: IWMI 363.348068 G744 ANP Record No: H036747)
(2.74 MB)
7 Amarasinghe, Upali; Samad, Madar; Anputhas, Markandu. 2005. Locating the poor: spatially disaggregated poverty maps for Sri Lanka. Colombo, Sri Lanka: International Water Management Institute (IWMI). v, 33p. (IWMI Research Report 096) [doi: https://doi.org/10.3910/2009.096]
(Location: IWMI-HQ Call no: IWMI 339.46 G744 AMA Record No: H037905)
(1.56MB)
This report presents the results of subnational poverty estimation using aggregate poverty statistics and how they can help policy interventions. In particular, they estimate the poverty map across the DS division level in Sri Lanka. The poverty map depicts the proportion of households below the poverty line, which is based on household expenditure for food for obtaining the minimum calorie requirement.
8 Amarasinghe, Upali; Samad, Madar; Anputhas, Markandu. 2005. Spatial clustering of rural poverty and food insecurity in Sri Lanka. Food Policy, 30: 493-509.
(Location: IWMI-HQ Call no: IWMI 339.46 G744 AME Record No: H037889)
9 Amarasinghe, Upali; Anputhas, Markandu; Samad, Madar; Abayawardana, Sarath. 2006. Spatial clustering of the poor: Links with availability and access to land. In Melis, D. M.; Abeysuriya, M.; de Silva, N. (Eds.). Putting land first?: Exploring the links between land and poverty. Colombo, Sri Lanka: Centre for Poverty Analysis (CEPA) pp.331-363.
Poverty ; Land ownership ; Water availability ; Agricultural society ; Villages ; Regression analysis / Sri Lanka
(Location: IWMI-HQ Call no: 333.31 G744 MEL Record No: H039608)
10 Smakhtin, Vladimir; Anputhas, Markandu. 2006. An assessment of environmental flow requirements of Indian river basins. Colombo, Sri Lanka: International Water Management Institute (IWMI). 36p. (IWMI Research Report 107) [doi: https://doi.org/10.3910/2009.106]
River basins ; Environmental flows ; Assessment ; Hydrology ; Ecology ; Ecosystems ; Water allocation ; Water requirements ; Time series / India
(Location: IWMI-HQ Call no: IWMI 551.483 G635 SMA Record No: H039610)
(488KB)
The primary purpose of this report is to stimulate the debate about environmental water allocations in India, where this concept is only beginning to receive attention and recognition. It is a component of a larger research project which aims to assess multiple aspects of India's National River Linking Project and water future in general.
11 Biradar, Chandrashekhar; Thenkabail, Prasad; Islam, Aminul; Anputhas, Markandu; Tharme, Rebecca; Vithanage, Jagath; Alankara, Ranjith; Gunasinghe, Sarath. 2007. Establishing the best spectral bands and timing of imagery for land use-land cover (LULC) class separability using Landsat ETM+ and Terra MODIS data. Canadian Journal of Remote Sensing, 33(5):431-444.
Remote sensing ; Land use ; Land cover mapping ; Irrigated farming ; Irrigation programs / Sri Lanka / Uda Walawe River Basin
(Location: IWMI HQ Call no: IWMI 333.918 G744 BIR Record No: H040453)
12 Smakhtin, Vladimir; Anputhas, Markandu. 2009. An assessment of environmental flow requirements of Indian river basins. In Amarasinghe, Upali A.; Shah, Tushaar; Malik, R. P. S. (Eds.). Strategic Analyses of the National River Linking Project (NRLP) of India, Series 1: India’s water future: scenarios and issues. Colombo, Sri Lanka: International Water Management Institute (IWMI) pp.293-328.
(Location: IWMI HQ Call no: IWMI 333.9162 G635 AMA Record No: H042045)
(686.88 KB)
13 Cai, Xueliang; Thenkabail, P. S.; Biradar, C. M.; Platonov, Alexander; Gumma, Murali Krishna; Dheeravath, V.; Cohen, Y.; Goldlshleger, F.; Ben-Dor, E.; Alchanatis, V.; Vithanage, Jagath; Anputhas, Markandu. 2009. Water productivity mapping using remote sensing data of various resolutions to support more crop per drop. Journal of Applied Remote Sensing, 3(033557). 23p. [doi: https://doi.org/10.1117/1.3257643]
Water productivity ; Crops ; Water use ; Evapotranspiration ; Mapping ; Remote sensing ; Models / Central Asia / Kyrgyzstan / Tajikistan / Uzbekistan / Kazakhstan / Syr Darya River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H042408)
(4.07 MB)
The overarching goal of this research was to map crop water productivity using satellite sensor data at various spectral, spatial, radiometric, and temporal resolutions involving: (a) Moderate Resolution Imaging Spectroradiometer (MODIS) 500m, (b) MODIS 250m, (c) Landsat enhanced thematic mapper plus (ETM+) 60m thermal, (d) Indian Remote Sensing Satellite (IRS) 23.5 m, and (e) Quickbird 2.44 m data. The spectro-biophysical models were developed using IRS and Quickbird satellite data for wet biomass, dry biomass, leaf area index, and grain yield for 5 crops: (a) cotton, (b) maize, (c) winter wheat, (d) rice, and (e) alfalfa in the Sry Darya basin, Central Asia. Crop-specific productivity maps were developed by applying the best spectro-biophysical models for the respective delineated crop types. Water use maps were produced using simplified surface energy balance (SSEB) model by multiplying evaporative fraction derived from Landsat ETM+ thermal data by potential ET. The water productivity (WP) maps were then derived by dividing the crop productivity maps by water use maps. The results of cotton crop, an overwhelmingly predominant crop in Central Asian Study area, showed that about 55% area had low WP of < 0.3 kg/m3, 34% had moderate WP of 0.3-0.4 kg/m3, and only 11% area had high WP > 0.4 kg/m3. The trends were similar for other crops. These results indicated that there is highly significant scope to increase WP (to grow "more crop per drop") through better water and cropland management practices in the low WP areas, which will substantially enhance food security of the ballooning populations without having to increase: (a) cropland areas, and\or (b) irrigation water allocations.
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