Your search found 30 records
1 Turral, H.. 1994. Strategic water resources management and decentralised local water management organisations: institutional implications and issues. In IIMI; Wuhan University of Hydraulic and Electrical Engineering. International Conference on Irrigation Management Transfer, Wuhan, China, 20-24 September 1994. Draft conference papers. Vol.3. Colombo, Sri Lanka: International Irrigation Management Institute (IIMI); Wuhan, China: Wuhan University of Hydraulic and Electrical Engineering. pp.333-339.
(Location: IWMI-HQ Call no: IIMI 631.7.3 G000 IIM Record No: H015583)
2 Turral, H.. 1995. Devolution of management in public irrigation systems: Cost shedding, empowerment and performance: A review. London, UK: ODI. 96p. (ODI working paper 80)
(Location: IWMI-HQ Call no: 631.7.3 G000 TUR Record No: H017379)
3 Turral, H.. 1995. Recent trends in irrigation management - Changing directions for the public sector. ODI Natural Resource Perspectives, 5:1-4.
(Location: IWMI-HQ Call no: P 4090 Record No: H017644)
4 Turral, H.. 1998. Hydro logic?: Reform in water resources management in developed countries with major agricultural water use - Lessons for developing nations. London, UK: ODI. xi, 174p. (ODI research study)
(Location: IWMI-HQ Call no: 333.91 G000 TUR Record No: H022646)
5 Malano, H. M.; Chien, N. V.; Turral, H.. 1999. An asset management approach to the rehabilitation and modernisation of irrigation and drainage infrastructure - Case study: La Khe Irrigation Scheme, Vietnam. In ICID, 17th Congress on Irrigation and Drainage, Granada, Spain, 1999: Water for Agriculture in the Next Millennium - Transactions, Vol.1E, Q.49: Rehabilitation and Modernization of Irrigation and Drainage Systems: 49.1: Criteria for the initiation of rehabilitation and/or modernization programs; Q.49.2: The involvement of private initiative; Q.49.3: Institutional framework. New Delhi, India: ICID. pp.197-211.
(Location: IWMI-HQ Call no: ICID 631.7 G000 ICI Record No: H025201)
6 Turral, H.; Malano, H.; Chien, N. V. 2002. Development and specification of a service agreement and operational rules for La Khe Irrigation System, Ha Dong, Vietnam. Irrigation and Drainage, 51(2):129-140.
(Location: IWMI-HQ Call no: PER, IWMI 631.7.1 G784 TUR Record No: H029961)
7 Molden, D.; Turral, H.; Amerasinghe, F.; Sharma, B. R.; Hatibu, N.; Drechsel, P.; van Koppen, B.; Wester, F.; Tharme, R.; Raschid-Sally, L.; Samad, M.; Murray-Rust, H.; Shah, T.; Acreman, M.; Smakhtin, V.; Peden, D.; Burton, M.; Albergel, J.; Meinzen-Dick, R.; Dunkhorst, B.; Merrey, D.; Mustafa, M.; Brown, D.; Dalton, J.; Flugel, W.; Gichuki, F.; Harrington, L.; Moustafa, M.; Samarasinghe, S. A. P.; Wallender, W.; Mohammed, A. 2002. Integrating research in water, food and environment. Challenge Program on Water and Food background paper 4. In CGIAR Challenge Program on Water and Food. Challenge Program on Water and Food: background papers to the full proposal. Colombo, Sri Lanka: CGIAR Challenge Program on Water and Food. pp.115-160.
(Location: IWMI HQ Call no: 333.91 G000 CGI Record No: H031290)
(2.41 MB)
(Location: IWMI-HQ Call no: PER Record No: H032265)
9 Turral, H.; Malano, H. 2002. Water policy in practice: A case study from Vietnam. In Brennan, D. (Ed.), Water policy reform: Lessons from Asia and Australia – Proceedings of an International Workshop held in Bangkok, Thailand, 8-9 June 2001. Canberra, Australia: ACIAR. pp.189-205.
(Location: IWMI-HQ Call no: 631.7.3 G570 BRE Record No: H034520)
(Location: IWMI-HQ Call no: PER Record No: H033592)
(Location: IWMI HQ Call no: e-copy only Record No: H041669)
The goal of this paper was to develop methods and protocols for water productivity mapping (WPM) using remote sensing data at multiple resolutions and scales in conjunction with field-plot data. The methods and protocols involved three broad categories: (a) Crop Productivity Mapping (CPM) (kg/m2); (b) Water Use (evapotranspiration) Mapping (WUM)(m3/m2); and (c) Water Productivity Mapping (WPM) (kg/m3). First, the CPMs were determined using remote sensing by: (i) Mapping crop types; (ii) modeling crop yield; and (iii) extrapolating models to larger areas. Second, WUM were derived using the Simplified Surface Energy Balance (SSEB) model. Finally, WPMs were produced by dividing CPMs and WUMs. The paper used data from Quickbird 2.44m, Indian Remote Sensing (IRS) Resoursesat-1 23.5m, Landsat-7 30m, and Moderate Resolution Imaging Spectroradiometer (MODIS) 250m and 500m, to demonstrate the methods for mapping water productivity (WP). In terms of physical water productivity (kilogram of yield produced per unit of water delivered), wheat crop had highest water productivity of 0.60 kg/m3 (WP), followed by rice with 0.5 kg/m3, and cotton with 0.42 kg/m3. In terms of economic value (dollar per unit of water delivered), cotton ranked highest at $ 0.5/m3 followed by wheat with $ 0.33/m3 and rice at $ 0.10/m3. The study successfully delineated the areas of low and high WP. An overwhelming proportion (50+%) of the irrigated areas were under low WP for all crops with nly about 10% area in high WP.
Call no: e-copy only Record No: H041815)
13 Thenkabail, P. S.; Biradar, C. M.; Noojipady, P.; Dheeravath, V.; Li, Yuan Jie; Velpuri, N. M.; Gumma, Murali Krishna; Gangalakunta, O. R. P.; Turral, H.; Cai, Xueliang; Vithanage, Jagath; Schull, M. A.; Dutta, R. 2009. Global irrigated area map (GIAM), derived from remote sensing, for the end of the last millennium. International Journal of Remote Sensing, 30(14):3679-3733. [doi: https://doi.org/10.1080/01431160802698919]
(Location: IWMI HQ Call no: e-copy only Record No: H042409)
(18.23 MB)
A Global Irrigated Area Map (GIAM) has been produced for the end of the last millennium using multiple satellite sensor, secondary, Google Earth and groundtruth data. The data included: (a) Advanced Very High Resolution Radiometer (AVHRR) 3-band and Normalized Difference Vegetation Index (NDVI) 10 km monthly time-series for 1997–1999, (b) Syste`me pour l’Observation de la Terre Vegetation (SPOT VGT) NDVI 1 km monthly time series for 1999, (c) East Anglia University Climate Research Unit (CRU) rainfall 50km monthly time series for 1961–2000, (d) Global 30 Arc-Second Elevation Data Set (GTOPO30) 1 km digital elevation data of the World, (e) Japanese Earth Resources Satellite-1 Synthetic Aperture Radar (JERS-1 SAR) data for the rain forests during two seasons in 1996 and (f) University of Maryland Global Tree Cover 1 km data for 1992–1993. A single mega-file data-cube (MFDC) of the World with 159 layers, akin to hyperspectral data, was composed by re-sampling different data types into a common 1 km resolution. The MFDC was segmented based on elevation, temperature and precipitation zones. Classification was performed on the segments. Quantitative spectral matching techniques (SMTs) used in hyperspectral data analysis were adopted to group class spectra derived from unsupervised classification and match them with ideal or target spectra. A rigorous class identification and labelling process involved the use of: (a) space–time spiral curve (ST-SC) plots, (b) brightness–greenness–wetness (BGW) plots, (c) time series NDVI plots, (d) Google Earth very-high-resolution imagery (VHRI) ‘zoom-in views’ in over 11 000 locations, (e) groundtruth data broadly sourced from the degree confluence project (3 864 sample locations) and from the GIAM project (1 790 sample locations), (f) high-resolution Landsat-ETM+ Geocover 150m mosaic of the World and (g) secondary data (e.g. national and global land use and land cover data). Mixed classes were resolved based on decision tree algorithms and spatial modelling, and when that did not work, the problem class was used to mask and re-classify the MDFC, and the class identification and labelling protocol repeated. The sub-pixel area (SPA) calculations were performed by multiplying full-pixel areas (FPAs) with irrigated area fractions (IAFs) for every class. A 28 class GIAMwas produced and the area statistics reported as: (a) annualized irrigated areas (AIAs), which consider intensity of irrigation (i.e. sum of irrigated areas from different seasons in a year plus continuous year-round irrigation or gross irrigated areas), and (b) total area available for irrigation (TAAI), which does not consider intensity of irrigation (i.e. irrigated areas at any given point of time plus the areas left fallow but ‘equipped for irrigation’ at the same point of time or net irrigated areas). The AIA of the World at the end of the last millennium was 467million hectares (Mha), which is sum of the non-overlapping areas of: (a) 252Mha from season one, (b) 174Mha from season two and (c) 41Mha from continuous yearround crops. The TAAI at the end of the last millennium was 399 Mha. The distribution of irrigated areas is highly skewed amongst continents and countries. Asia accounts for 79% (370 Mha) of all AIAs, followed by Europe (7%) and North America (7%). Three continents, South America (4%), Africa (2%) and Australia (1%), have a very low proportion of the global irrigation. The GIAM had an accuracy of 79–91%, with errors of omission not exceeding 21%, and the errors of commission not exceeding 23%. The GIAM statistics were also compared with: (a) the United Nations Food and Agricultural Organization (FAO) and University of Frankfurt (UF) derived irrigated areas and (b) national census data for India. The relationships and causes of differences are discussed in detail. The GIAM products are made available through a web portal (http://www.iwmigiam.org).
(Location: IWMI HQ Call no: 631.7.1 G000 THE Record No: H042416)
(2.65 MB)
Provides a comprehensive knowledge base in the use of satellite sensor-based maps and statisics for irrigated and rainfed croplands and available water that will ensure food security.
15 Turral, H.; Thenkabail, P. S.; Lyon, J. G.; Biradar, C. M. 2009. Context, needed: the need and scope for mapping global irrigated and rain-fed areas. In Thenkabail, P. S.; Lyon, J. G.; Turral, H.; Biradar, C. M. (Eds.). Remote sensing of global croplands for food security. Boca Raton, FL, USA: CRC Press. pp.3-11. (Taylor & Francis Series in Remote Sensing Applications)
(Location: IWMI HQ Call no: 631.7.1 G000 THE Record No: H042417)
16 Ahmad, Mobin-ud-Din; Turral, H.; Nazeer, Aamir; Hussain, Asghar. 2009. Satellite-based assessment of agricultural water consumption, irrigation performance, and water productivity in a large irrigation system in Pakistan. In Thenkabail, P. S.; Lyon, J. G.; Turral, H.; Biradar, C. M. (Eds.). Remote sensing of global croplands for food security. Boca Raton, FL, USA: CRC Press. pp.331-354. (Taylor & Francis Series in Remote Sensing Applications)
(Location: IWMI HQ Call no: 631.7.1 G000 THE Record No: H042429)
(1.08 MB)
17 Biradar, C. M.; Thenkabail, P. S.; Noojipady, P.; Dheeravath, V.; Velpuri, M.; Turral, H.; Cai, Xueliang; Gumma, Murali Krishna; Gangalakunta, O. R. P.; Schull, M. A.; Alankara, Ranjith; Gunasinghe, Sarath; Xiao, X. 2009. Global map of rainfed cropland areas (GMRCA) and statistics using remote sensing. In Thenkabail, P. S.; Lyon, J. G.; Turral, H.; Biradar, C. M. (Eds.). Remote sensing of global croplands for food security. Boca Raton, FL, USA: CRC Press. pp.357-389. (Taylor & Francis Series in Remote Sensing Applications)
(Location: IWMI HQ Call no: 631.7.1 G000 THE Record No: H042430)
(1.40 MB)
18 Gamage, Nilantha; Ahmad, Mobin ud Din; Turral, H.. 2009. Mapping irrigated crops from Landsat ETM + imagery for heterogeneous cropping systems in Pakistan. In Thenkabail, P. S.; Lyon, J. G.; Turral, H.; Biradar, C. M. (Eds.). Remote sensing of global croplands for food security. Boca Raton, FL, USA: CRC Press. pp.421-437. (Taylor & Francis Series in Remote Sensing Applications)
(Location: IWMI HQ Call no: 631.7.1 G000 THE Record No: H042433)
(0.64 MB)
19 Turral, H.; Connell, D.; McKay, J. 2009. Much ado about the Murray: the drama of restraining water use. In Molle, Francois.; Wester, P. (Eds.). River basin trajectories: societies, environments and development. Wallingford, UK: CABI; Colombo, Sri Lanka: International Water Management Institute (IWMI). pp.263-291. (Comprehensive Assessment of Water Management in Agriculture Series 8)
(Location: IWMI HQ Call no: IWMI 333.9162 G000 MOL Record No: H042455)
(Location: IWMI HQ Call no: 631.7.1 G000 THE c2 Record No: H042543)
Provides a comprehensive knowledge base in the use of satellite sensor-based maps and statisics for irrigated and rainfed croplands and available water that will ensure food security.
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