Your search found 11 records
1 Islam, Aminul. 2004. DSP global: global and regional databases in IWMI-DSP. Print out of powerpoint presentation made at the Observing river basins from space: why is it important for IWMI - A Remote Sensing and GIS (RS/GIS) Workshop held at the International Water Management Institute, Colombo, Sri Lanka, 28 June 2004. RS/GIS training materials. 19p.
(Location: IWMI-HQ Call no: IWMI 574.526323 G000 IWM Record No: H036223)
2 Thenkabail, Prasad Srinivas; Biradar, Chandrashekhar; Gangodagamage, Chandana; Islam, Aminul; Schull, Mitchell; Gamage, Nilantha; Turral, Hugh; Zomer, Robert; Biggs, Trent; Scott, Christopher; Ahmad, Mobin-ud Din; De Fraiture, Charlotte. 2004. RS/GIS training materials for awareness: version 1.0. Print out of powerpoint presentation made at the Observing river basins from space: why is it important for IWMI - A Remote Sensing and GIS (RS/GIS) Workshop held at the International Water Management Institute, Colombo, Sri Lanka, 28 June 2004. RS/GIS training materials. 6p.
(Location: IWMI-HQ Call no: IWMI 574.526323 G000 IWM Record No: H036216)
3 Thenkabail, Prasad; Biradar, Chandrashekhar; Noojipady, Praveen; Islam, Aminul; Vithanage, Jagath; Velpuri, Manohar; Dheeravath, Venkateswarlu; Kulawardhana, Wasantha; Jie, Li Yuan; Gunasinghe, Sarath; Alankara, Ranjith. 2006. International Water Management Institute’s Data Storehouse Pathway (IWMIDSP): A unique data and knowledge gateway of spatial data with emphasis on river basins. In Li, D.; Xia, L. (Eds.). Geoinformatics 2006: GNSS and Integrated Geospatial applications. Proceedings of SPIE Vol.6418, Wuhan, China, 28-29 October 2006. Bellingham, Washington, USA: SPIE – The International Society for Optical Engineering. 6418(64181R):1-6.
(Location: IWMI-HQ Call no: IWMI 621.3678 G000 THE Record No: H039738)
4 Thenkabail, Prasad; Biradar, Chandrashekhar; Noojipady, Praveen; Islam, Aminul; Velpuri, Manohar; Vithanage, Jagath; Kulawardhana, Wasantha; Jie, Li Yuan; Venkateswarlu, Dheeravath; Gunasinghe, Sarath; Alankara, Ranjith. 2006. The spatial data and knowledge gateways at the International Water Management Institute (IWMI) In Li, D.; Xia, L. (Eds.). Geoinformatics 2006: GNSS and Integrated Geospatial applications. Proceedings of SPIE Vol.6421, Wuhan, China, 28-29 October 2006. Bellingham, Washington, USA: SPIE – The International Society for Optical Engineering. 64211Z. 10p.
(Location: IWMI-HQ Call no: IWMI 621.3678 G000 THE Record No: H039739)
5 Kulawardhana, Wasantha; Thenkabail, Prasad; Vithanage, Jagath; Biradar, Chandrashekhar; Islam, Aminul; Gunasinghe, Sarath; Alankara, Ranjith. 2007. Evaluation of the wetland mapping methods using Landsat ETM+ and SRTM data. Journal of Spatial Hydrology, 2. 47p.
Wetlands ; Remote sensing ; Mapping ; River basins / Botswana / Zimbabwe / South Africa / Mozambique / Limpopo River Basin
(Location: IWMI HQ Call no: IWMI 333.918 G178 KUL Record No: H040222)
6 Islam, Aminul; Thenkabail, Prasad S.; Kulawardhana, Wasantha; Alankara, Ranjith; Gunasinghe, Sarath; Edussuriya, C.; Gunawardana, A. 2008. Semi-automated methods for mapping wetlands using Landsat ETM+ and SRTM data. International Journal of Remote Sensing, 29:(24):7077-7106.
(Location: IWMI HQ Call no: IWMI 333.918 G744 ISL Record No: H040452)
The overarching goal of this study was to develop a comprehensive methodology for mapping natural and human-made wetlands using fine resolution Landsat enhanced thematic mapper plus (ETM+), space shuttle radar topographic mission digital elevation model (SRTM DEM) data and secondary data. First, automated methods were investigated in order to rapidly delineate wetlands; this involved using: (a) algorithms on SRTM DEM data, (b) thresholds of SRTM-derived slopes, (c) thresholds of ETM+ spectral indices and wavebands and (d) automated classification techniques using ETM+ data. These algorithms and thresholds using SRTM DEM data either over-estimated or under-estimated stream densities (S d) and stream frequencies (S f), often generating spurious (non-existent) streams and/or, at many times, providing glaring inconsistencies in the precise physical location of the streams. The best of the ETM+-derived indices and wavebands either had low overall mapping accuracies and/or high levels of errors of omissions and/or errors of commissions. Second, given the failure of automated approaches, semi-automated approaches were investigated; this involved the: (a) enhancement of images through ratios to highlight wetlands from non-wetlands, (b) display of enhanced images in red, green, blue (RGB) false colour composites (FCCs) to highlight wetland boundaries, (c) digitizing the enhanced and displayed images to delineate wetlands from non-wetlands and (d) classification of the delineated wetland areas into various wetland classes. The best FCC RGB displays of ETM+ bands for separating wetlands from other land units were: (a) ETM+4/ETM+7, ETM+4/ETM+3, ETM+4/ETM+2, (b) ETM+4, ETM+3, ETM+5 and (c) ETM+3, ETM+2, ETM+1. In addition, the SRTM slope threshold of less than 1% was very useful in delineating higher-order wetland boundaries. The wetlands were delineated using the semi-automated methods with an accuracy of 96% as determined using field-plot data. The methodology was evaluated for the Ruhuna river basin in Sri Lanka, which has a diverse landscape ranging from sea shore to hilly areas, low to very steep slopes (0° to 50°), arid to semi-arid zones and rain fed to irrigated lands. Twenty-four per cent (145 733 ha) of the total basin area was wetlands as a result of a high proportion of human-made irrigated areas, mainly under rice cropping. The wetland classes consisted of irrigated areas, lagoons, mangroves, natural vegetation, permanent marshes, salt pans, lagoons, seasonal wetlands and water bodies. The overall accuracies of wetland classes varied between 87% and 94% (K hat = 0.83 to 0.92) with errors of omission less than 13% and errors of commission less than 1%.
7 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)
8 Ahmad, Mobin-ud-Din; Islam, Aminul; Masih, Ilyas; Muthuwatta, Lal; Karimi, Poolad; Turral, Hugh. 2008. Mapping basin level water productivity using remote sensing and secondary data in the Karkheh River Basin, Iran. Paper presented at the 13th IWRA World Water Congress on Global Changes and Water Resources, "Confronting the expanding and diversifying pressures", Montpellier, France, 1-4 September 2008. 13p.
Water productivity ; Evapotranspiration ; Mapping ; River basins ; Farming systems / Iran / Karkheh River Basin
(Location: IWMI HQ Call no: IWMI 333.9162 G690 AHM Record No: H041537)
Water productivity (WP) mapping is essential to evaluate the performance of current water use at the river basin scale. WP mapping is also essential to identify opportunities to improve the net gain from water by either increasing the productivity for a given consumption of water or reducing consumption without decreasing production. This requires the computation of all benefits and overall water use at a similar spatial domain. Generally the secondary data related to agricultural, livestock and poultry production are managed at administrative district level, whereas hydrological data are collected at sub-watershed scale. This scale difference, hinders estimation at hydrological scales such as sub-catchment to river basin. Due to these limitations, estimates of WP beyond field and farm scale usually do not exist, as is the case of the Karkheh River basin of Iran. To address these issues, in this paper we demonstrate an approach to estimate WP at different scales using a range of datasets. To understand the productivity gaps within and between sub-basins of the Karkheh Basin, we assessed land and water productivity for major crops using a questionnaire survey of 298 farmers. The farm-level land and water productivity in irrigated areas was considerably higher than in rainfed areas. The yield of irrigated wheat and its WP, in terms of yield per unit of gross inflow, averaged 3320±1510 kg/ha and 0.55±0.20 kg/m3, whereas the corresponding values for rainfed wheat were 1460±580 kg/ha and 0.46±0.22 kg/m.For analysis from sub-catchment to basin scale, we assessed economic WP, in terms of gross value of production per unit of actual evapotranspiration, for all agricultural enterprises including rainfed and irrigated agriculture, livestock production and overall vegetation production using remote sensing data and routine secondary data/agricultural statistics. The sub-catchment estimates show that the water productivity variability is quite high: 0.027-0.071 $/m3 and 0.120-0.524 $/m3 for rainfed and irrigated systems respectively. Inclusion of livestock changes both the magnitude and patterns of overall water productivity and in doing so highlights the importance of fully accounting for all components in agricultural production systems. The WP mapping exercise presented in this paper identified both bright- and hot-spots for helping policy makers and managers to target better resource (re)allocation and measures to enhance productivity in the Karkheh Basin. The approach is applicable to other river basins.
9 Masih, Ilyas; Uhelnbrook, S.; Maskey, S.; Ahmad, Mobin-ud-Din; Islam, Aminul. 2008. Estimating ungauged stream flows based on model regionalization: examples from the mountainous, semi-arid Karkheh River Basin, Iran. In Brhuthans J.; Kovar, K.; Hrkal, Z. (Eds.). HydroPredict 2008 Conference on Predictions for Hydrology, Ecology, and Water Resources Management: Using Data and Models to Benefit Society, Prague, Czech Republic, 15-18 September 2008. pp 7-10.
River basins ; Stream flow ; Time series analysis ; Simulation models ; Calibration ; Runoff ; Catchment areas ; Water resource management / Iran / Karkheh River Basin
(Location: IWMI HQ Call no: IWMI 551.483 G690 MAS Record No: H041587)
The study examines the possibility of simulating time series of stream flows for ungauged catchments based on hydrological similarity. As an example the mountainous, semiarid Karkheh river basin (50,764 km2) of Iran is presented. The frequently applied HBV model was applied to simulate daily stream flow with parameters transferred from gauged catchment counterparts. Hydrological similarity is defined based on three similarity measures: geographical area, spatial proximity and shape of the flow duration curve (FDC). FDCs for the ungauged catchments were predicted using logarithmic relationship derived from physiographic characteristics of eleven gauged catchments. The study shows that transferring HBV model parameters based on the FDC similarity criterion produces better runoff simulation compared to the similarity criteria based on catchment area and geographical proximity. The validation of the catchment similarity analysis using the FDC on monthly and daily flow simulation resulted in mean Nash-Sutcliffe model efficiency, Reff, of 0.70 and 0.57, respectively. The study concludes that the methods of utilizing FDCs could be applied for estimating ungauged stream flows in the mountainous parts of the Karkheh river basin and source area of other major rivers in that region (e.g. Dez, Karun and Zayandeh Rud).
10 Ahmad, Mobin-ud-Din; Islam, Aminul; Masih, Ilyas; Muthuwatta, Lal P.; Karimi, Poolad; Turral, Hugh. 2008. Water productivity mapping to identify opportunities to improve agricultural water management in the Karkheh River Basin, Iran. In Humphreys, E.; Bayot, R. S.; van Brakel, M.; Gichuki, F.; Svendsen, M.; Wester, P.; Huber-Lee, A.; Cook, S. Douthwaite, B.; Hoanh, Chu Thai; Johnson, N.; Nguyen-Khoa, Sophie; Vidal, A.; MacIntyre, I.; MacIntyre, R. (Eds.). Fighting poverty through sustainable water use: proceedings of the CGIAR Challenge Program on Water and Food, 2nd International Forum on Water and Food, Addis Ababa, Ethiopia, 10-14 November 2008. Vol.1. Keynotes; Cross-cutting topics. Colombo, Sri Lanka: CGIAR Challenge Program on Water and Food. pp.119-122.
River basin management ; Water productivity ; Mapping ; Rainfed farming ; Irrigated farming ; Evapotranspiration / Iran / Karkheh River Basin
(Location: IWMI HQ Call no: IWMI 333.91 G000 HUM Record No: H041785)
http://ifwf2.org/addons/download_presentation.php?fid=1042
https://vlibrary.iwmi.org/pdf/H041785.pdf
https://vlibrary.iwmi.org/pdf/H041785.pdf
11 Ahmad, Mobin-ud-Din; Islam, Aminul; Masih, Ilyas; Muthuwatta, Lal P.; Karimi, Poolad; Turral, Hugh. 2009. Mapping basin-level water productivity using remote sensing and secondary data in the Karkheh River Basin, Iran. Water International, 34(1):119-133. [doi: https://doi.org/10.1080/02508060802663903]
River basins ; Water productivity ; Mapping ; Remote sensing ; Livestock ; Crop production ; Plant water relations ; Water allocation ; Climate ; Catchment areas ; Water use ; Evapotranspiration ; Rainfed farming ; Irrigated farming / Iran / Karkheh River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H042128)
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