Your search found 121 records
1 Joshi, P. K.; Priyanka, N.; Amarnath, Giriraj. 2011. Geospatial tools to assess forest ecosystems under climate change trajectories. In Joshi, P. K.; Singh, T. P. (Eds.). Geoinformatics for climate change studies. New Delhi, India: The Energy and Resources Institute (TERI) pp.129-176.
Remote sensing ; GIS ; Climate change ; Forests ; Ecosystems ; Phenology ; Ecology ; Greenhouse gases ; Models ; Vegetation ; Mountains ; Wildfires ; Invasive species ; Global warming ; Environmental temperature ; Land use ; Land cover / Nepal / Eastern Himalayas
(Location: IWMI HQ Call no: 621.3678 G000 JOS Record No: H044291)
(4.65 MB)
2 Amarnath, Giriraj; Murthy, M. S. R.; Shrestha, B. 2011. Evaluating biodiversity and spatial simulation of land-cover change in the tropical region of Western Ghats, India. In Pavlinov, I. Y. (Ed.). Research in biodiversity - models and applications. Rijeka, Croatia: InTech. pp.115-144.
Biodiversity ; Simulation models ; Land cover change ; Land use ; Satellite surveys ; Forests ; Vegetation ; Species ; Landscape ; Analytical methods / India / Western Ghats
(Location: IWMI HQ Call no: e-copy only Record No: H044390)
http://www.intechopen.com/source/pdfs/21532/InTech-Evaluating_biodiversity_and_spatial_simulation_of_land_cover_change_in_the_tropical_region_of_western_ghats_india.pdf
https://vlibrary.iwmi.org/pdf/H044390.pdf
https://vlibrary.iwmi.org/pdf/H044390.pdf
(3.10 MB) (439.47KB)
3 Gurung, D. R.; Kulkarni, A. V.; Amarnath, Giriraj; Aung, K. S.; Shrestha, B. 2011. Monitoring of seasonal snow cover in Bhutan using remote sensing technique. Current Science, 101(10):1364-1370.
Climate change ; Remote sensing ; Snow cover ; Monitoring ; Water availability ; Indicators / Bhutan
(Location: IWMI HQ Call no: e-copy only Record No: H044438)
(6.47 MB) (6.46MB)
All major rivers in Bhutan depend on snowmelt for discharge. Therefore, changes in snow cover due to climate change can influence distribution and availability of water. However, information about distribution of seasonal snow cover in Bhutan is not available. The MODIS snow product was used to investigate snow cover status and trends in Bhutan. Average snow cover area (SCA) of Bhutan estimated for the period 2002 to 2010 was 9030 sq. km, about 25.5% of the total land area. SCA trend of Bhutan for the period 2002–10 was found to decrease (–3.27 ± 1.28%). The average SCA for winter was 14,485 sq. km (37.7%), for spring 7411 sq. km (19.3%), for summer 4326 sq. km (11.2%), and for autumn 7788 sq. km (20.2%), mostly distributed in the elevation range 2500–6000 m amsl. Interannual and seasonal SCA trend both showed a decline, although it was not statistically significant for all sub-basins. Pho Chu sub-basin with 19.5% of the total average SCA had the highest average SCA. The rate of increase of SCA for every 100 m elevation was the highest (2.5%) in the Pa Chu sub-basin. The coefficient of variance of 1.27 indicates high variability of SCA in winter.
4 Babar, S.; Amarnath, Giriraj; Reddy, C. S.; Jurasinski, G.; Jentsch, A. 2011. Spatial patterns of phytodiversity - assessing vegetation using (Dis) similarity measures. In Grillo, O.; Venora, G. (Eds.). The dynamical processes of biodiversity - case studies of evolution and spatial distribution. Rijeka, Croatia: InTech. pp.147-186.
Vegetation ; Species ; Biodiversity ; Ecosystems ; Spatial information ; Statistical methods ; Plant ecology ; Forests / India / Andhra Pradesh / Eastern Ghats
(Location: IWMI HQ Call no: e-copy only Record No: H044596)
http://www.intechopen.com/source/pdfs/24414/InTech-Spatial_patterns_of_phytodiversity_assessing_vegetation_using_dis_similarity_measures.pdf
https://vlibrary.iwmi.org/pdf/H044596.pdf
https://vlibrary.iwmi.org/pdf/H044596.pdf
(0.71 MB) (630.62KB)
5 Babar, S.; Amarnath, Giriraj; Reddy, C. S.; Jentsch, A.; Sudhakar, S. 2012. Species distribution models: ecological explanation and prediction of an endemic and endangered plant species (Pterocarpus santalinus L.f.). Current Science, 102(8):1157-1165.
Ecology ; Species ; Pterocarpus santalinus ; Indigenous organisms ; Endangered species ; Models ; Geographical distribution ; Biodiversity / India / Andhra Pradesh / Eastern Ghats
(Location: IWMI HQ Call no: e-copy only Record No: H044856)
(0.87 MB) (893KB)
Pterocarpus santalinus L.f. (Red Sanders) is an endemic and endangered species largely confined to the southern portion of the Eastern Ghats, Andhra Pradesh, India. To understand its ecological and geographic distribution, we used ecological niche modelling (ENM) based on field sample-based istributional information, in relation to climatic and topographic datasets. Before modelling, hierarchical partitioning was used to optimize the choice of variables for better prediction and reliability. We used three ENM approaches, namely GARP, Maxent and BIOCLIM for predicting potential areas of occurrence. The ENM successfully reconstructed key features of the species geographic distribution, mainly in the forest tracts of Chittoor and Kadapa districts. GARP appeared to be more robust in prediction capabilities compared to BIOCLIM. The potential distributional area identified by these models falls mainly in regions not protected and experiencing high anthropogenic pressure owing to economic and medicinal use. The success of this model indicates that ENM-based approaches provide a promising tool for exploring various scenarios useful in the study of ecology, biogeography and conservation.
6 Amarnath, Giriraj; Bajracharya, B.; Shrestha, B. 2012. Geoinformatics for landscape ecology and biodiversity research. Asian Journal of Geoinformatics, 12(1):10p.
Remote sensing ; GIS ; Biodiversity ; Landscape ecology ; Monitoring ; Forests ; Satellite surveys ; Land use ; Land cover
(Location: IWMI HQ Call no: e-copy only Record No: H044859)
http://geoportal.icimod.org/downloads/2012/GeoinformaticsforLandscapeEcologyandBiodiversity%20Research.pdf
https://vlibrary.iwmi.org/pdf/H044859.pdf
https://vlibrary.iwmi.org/pdf/H044859.pdf
(6.86 MB)
This review paper evaluates the potential of remote sensing for assessing landscape and species diversity in mountainous terrain. Understanding the complex mechanism of biodiversity necessitate its spatial and temporal dynamics and synergetic adoption of measurement approaches with long-term plot inventories. In view of this, importance of geoinformatics - which can be seen as a combination of integrating tools such as Geographic Information System (GIS), satellite remote sensing, Global Positioning System (GPS), and information and communication technologies, are realized as complimentary systems to ground-based studies. This paper addresses how wide range of geospatial tools can be used in monitoring and assessment of biodiversity. Further discussions are made on the wide variety of landscape ecological application tools, and the required data from broad spatial extents that cannot be collected through field-based methods. Remote sensing data and techniques address these needs, which include identifying and detailing the biophysical characteristics of species’ habitats, predicting the distribution of species and spatial variability in species richness, and detecting natural and human-caused changes at scales ranging from individual landscapes to the entire world.
7 Amarnath, Giriraj. 2012. Large-scale flood event: global and regional assessment. In Centre for Space Science and Technology Education in Asia and the Pacific (CSSTEAP). International Training Course: Application of Space Technology for Disaster Risk Reduction. Lecture notes. Dehradun, India: Centre for Space Science and Technology Education in Asia and the Pacific (CSSTEAP). pp.187-202.
Natural disasters ; Flooding ; Assessment ; Remote sensing ; Satellite surveys ; Risk reduction ; Forecasting ; Mapping / India / Indo-Gangetic Plains
(Location: IWMI HQ Call no: IWMI Record No: H044891)
(1.04 MB)
8 Tang, B.-H.; Shrestha, B.; Li, Z.-L.; Liu, G.; Ouyang, H.; Gurung, D. R.; Amarnath, Giriraj; Aung, K. S. 2013. Determination of snow cover from MODIS data for the Tibetan Plateau Region. International Journal of Applied Earth Observation and Geoinformation, 21:356-365. [doi: https://doi.org/10.1016/j.jag.2012.07.014]
Snow cover ; Cloud cover ; Satellite surveys ; Data ; Mapping ; Indicators ; Algorithms / Central Asia / China / Tibet / Tibetan Plateau
(Location: IWMI HQ Call no: e-copy only Record No: H045039)
(1.65 MB)
This paper addresses a snow-mapping algorithm for the Tibetan Plateau region using Moderate Resolution Imaging Spectroradiometer (MODIS) data. Accounting for the effects of the atmosphere and terrain on the satellite observations at the top of the atmosphere (TOA), particularly in the rugged Tibetan Plateau region, the surface reflectance is retrieved from the TOA reflectance after atmospheric and topographic corrections. To reduce the effect of the misclassification of snow and cloud cover, a normalized difference cloud index (NDCI) model is proposed to discriminate snow/cloud pixels, separate from the MODIS cloud mask product MOD35. The MODIS land surface temperature (LST) product MOD11 L2 is also used to ensure better accuracy of the snow cover classification. Comparisons of the resulting snow cover with those estimated from high spatial-resolution Landsat ETM+ data and obtained from MODIS snow cover product MOD10 L2 for the Mount Everest region for different seasons in 2002, show that the MODIS snow cover product MOD10 L2 overestimates the snow cover with relative error ranging from 20.1% to 55.7%, whereas the proposed algorithm estimates the snow cover more accurately with relative error varying from 0.3% to 9.8%. Comparisons of the snow cover estimated with the proposed algorithm and those obtained from MOD10 L2 product with in situ measurements over the Hindu Kush-Himalayan (HKH) region for December 2003 and January 2004 (the snowy seasons) indicate that the proposed algorithm can map the snow cover more accurately with greater than 90% agreement.
9 Amarnath, Giriraj; Ameer, Mohamed; Aggarwal, Pramod; Smakhtin, Vladimir. 2012. Detecting spatio-temporal changes in the extent of seasonal and annual flooding in South Asia using multi-resolution satellite data. In Civco, D. L.; Ehlers, M.; Habib, S.; Maltese, A.; Messinger, D.; Michel, U.; Nikolakopoulos, K. G.; Schulz, K. (Eds.). Earth resources and environmental remote sensing/GIS applications III: proceedings of the International Society for Optics and Photonics (SPIE), Vol.8538, Amsterdam, Netherland, 1-6 July 2012. Bellingham, WA, USA: International Society for Optics and Photonics (SPIE). 11p. [doi: https://doi.org/10.1117/12.974653]
GIS ; Remote sensing ; Flooding ; Mapping ; Satellite surveys ; Indicators ; Statistical methods ; Time series analysis / South Asia
(Location: IWMI HQ Call no: e-copy only Record No: H045437)
(1.73 MB)
This paper presents algorithm for flood inundation mapping to understand seasonal and annual changes in the flood extent and in the context of emergency response. Time-series profiles of Land Surface Water Index (LSWI), Enhanced Vegetation Index (EVI), Normalized Difference Vegetation Index (NDVI) and Normalized Difference Snow Index (NDSI) are obtained from MOD09 8-day composite time-series data (resolution 500m; time period: 2000-2011). The proposed algorithm was applied for MODIS data to produce time-series inundation maps for the ten annual flood season over the period from 2000 to 2011. The flood product has three classes as flood, mixed and long-term water bodies. The MODIS flood products were validated via comparison with ALOS AVINIR / PALSAR and Landsat TM using the flood fraction comparison method. Compared with the ALOS satellite data sets at a grid size of 10km the obtained RMSE range from 5.5 to 15 km2 and the determination coefficients range from 0.72 to 0.97. The spatial characteristics of the estimated early, peak and late and duration of inundation cycle were also determined for the period from 2000 to 2011. There are clear contracts in the distribution of the estimated flood duration of inundation cycles between large-scale floods (2008-2010) and medium and small-scale floods (2002 and 2004). Examples on the analysis of spatial extent and temporal pattern of flood-inundated areas are of prime importance for the mitigation of floods. The generic approach can be used to quantify the damage caused by floods, since floods have been increasing each year resulting in the loss of lives, property and agricultural production.
10 Amarnath, Giriraj; Ameer, Mohamed; Aggarwal, Pramod; Smakhtin, Vladimir. 2012. An algorithm for rapid flood inundation mapping from optical data using reflectance differencing technique [Abstract only]. In de Silva, R. P.; Kumar, N.; Mehmood, H. (Eds.). GIT4NDM - reduce exposure to reduce risk: proceedings of the 4th International Conference on Geo-information Technology for Natural Disaster Management (GIT4NDM), Colombo, Sri Lanka, 7-8 November 2012. Pathumthani, Thailand: Geoinformatics Intenational. pp.19.
(Location: IWMI HQ Call no: e-copy only Record No: H045697)
(0.13 MB)
11 Uddin, K.; Gurung, D. R.; Amarnath, Giriraj; Shrestha, B. 2013. Application of remote sensing and GIS for flood hazard management: a case study from Sindh Province, Pakistan. American Journal of Geographic Information System, 2(1):1-5. [doi: https://doi.org/10.5923/j.ajgis.20130201.01]
Remote sensing ; GIS ; Vegetation ; Natural disasters ; Flood control ; Case studies ; Image analysis ; Models ; Mapping / Pakistan / Nepal / Sindh Province
(Location: IWMI HQ Call no: e-copy only Record No: H045720)
http://www.sapub.org/global/showpaperpdf.aspx?doi=10.5923/j.ajgis.20130201.01
https://vlibrary.iwmi.org/pdf/H045720.pdf
https://vlibrary.iwmi.org/pdf/H045720.pdf
(0.64 MB) (669.10KB)
Floods are one of the most common hazards in the world, affecting people’s lives and livelihoods. Flood hazard mapping and flood shelters suitability analysis are vital elements in appropriate land use planning for flood-prone areas. This paper describes application of Remote Sensing (RS) and Geographical Information Systems (GIS) in identifying flood hazard zones and flood shelters and are therefore important tools for planners and decision makers. The purpose of this article is to describe a simple and efficient methodology to accurately delineate flood inundated areas, flood-hazard areas, and suitable areas for flood shelter to minimize flood impacts. Possible extent of flooding and suitable location flood shelter sites were modeled and mapped for Sindh Province in Pakistan, using the software ArcGIS model builder. The output was validated using inundation maps based on flood events that took place in 2010 in Pakistan. These were mapped using object-based image analysis (OBIA) implemented in eCognition software. The catastrophic flood of 2010 inundated a total area of 7579 km2, while the modeled result indicated the hazard area to be 6216 km2 out of 46138 km2. Discrepancies in modeled and mapped results are insignificant and acceptable considering the manual flood management interventions which are beyond the capability of models to represent. Thus, this method is robust enough to develop flood hazard zoning maps and map shelter sites for flood management.
12 Amarnath, Giriraj; Sharma, Bharat. 2013. Manual of the Training on Application of Remote Sensing and GIS in Flood Inundation Mapping for Spate Irrigation Assessment in Sudan, jointly organized by IWMI, the Hydraulic Research Institute (HRS), Sudan, and the International Fund for Agricultural Development (IFAD), held at Wad Medani, Sudan, 15-17 January 2013. Colombo, Sri Lanka: International Water Management Institute (IWMI). 96p.
Training materials ; Remote sensing ; Image processing ; Radar ; GIS ; History ; Flooding ; Mapping ; Spate irrigation ; Assessment ; Institutions ; Data storage ; Data analysis ; Satellite observation
(Location: IWMI HQ Call no: e-copy only Record No: H045698)
(3.34 MB)
13 Amarnath, Giriraj; Pavelic, Paul; Smakhtin, Vladimir. 2013. Analysis of trends in extreme flood events and mitigation strategies in South East Asia. [Abstract only]. In German Aerospace Center (DLR); Germany. Federal Ministry of Education and Research (BMBF). Mekong Environmental Symposium, Ho Chi Minh City, Vietnam, 5-7 March 2013. Abstract volume, Topic 06 - Hazards and disaster risk reduction in the Mekong Basin. Wessling, Germany: German Aerospace Center (DLR); Bonn, Germany: Federal Ministry of Education and Research (BMBF). pp.46.
Natural disasters ; Flooding ; Monitoring ; Models ; Investment / South East Asia / Thailand / Cambodia / Vietnam
(Location: IWMI HQ Call no: e-copy only Record No: H045752)
http://www.mekong-environmental-symposium-2013.org/frontend/file.php?id=3020&dl=1
https://vlibrary.iwmi.org/pdf/H045752.pdf
https://vlibrary.iwmi.org/pdf/H045752.pdf
(0.08 MB) (2.09MB)
Floods are one of the most frequent and widespread natural hazards in the world. A recent example is the 2011 floods in three of the four Lower Mekong Basin Countries (Thailand, Cambodia and Vietnam) that caused severe impacts in terms of loss of life and damage to infrastructure. Several studies have highlighted the increasing importance of developing spatio-temporal flood hazard databases to understand flood dynamics more systematically at a range of spatial scales within South East Asia (SEA). This study is proceeding on two distinct fronts: the first focusses on ranking and prioritization of impacts across SEA, whilst the other examines an approach to flood monitoring that evaluates the feasibility of implementing possible mitigation strategies that still provide for the degree of flow variability needed to maintain ecosystems. Firstly, long-term time-series data from multiple sources (e.g. EM-DAT, DFO, Sentinel Asia) was used in identifying flood hotspots including their frequency, intensity/severity and societal impacts. This will also help in evaluating and improving hydrological modeling predictions and provide better information for more effective flood hazard, flood risk and preparedness studies. Flood hotspots were further investigated taking into account of agricultural extent loss, populations at risk and economic loss. The results from the hotspot analysis suggest more climate risk investments are needed to minimize risk and are likely to have the biggest payoff in terms of reduced losses. The nature of those investments and the associated cost-benefits are being revealed. Secondly, a new approach is being developed for flood monitoring from time-series MODIS data acquired from 2000 to 2012. This approach will help in identifying basin to regional-scale temporal changes in inundated area; duration of inundation cycles between large-medium-small scale floods. Thus satellite-based mapping of flood risks areas will help in identifying prospective areas for floodwater harvesting in the upstream areas to reduce negative impacts downstream.
14 Amarnath, Giriraj. 2014. An algorithm for rapid flood inundation mapping from optical data using a reflectance differencing technique. Journal of Flood Risk Management, 7(3):239-250. [doi: https://doi.org/10.1111/jfr3.12045]
Remote sensing ; Algorithms ; Flooding ; Mapping ; Satellite imagery ; Satellite surveys ; Surface water ; Indicators ; Vegetation
(Location: IWMI HQ Call no: e-copy only Record No: H045768)
(1.46 MB)
This paper presents an algorithm for flood inundation mapping in the context of emergency response. Rapid satellite-based flood inundation mapping and delivery of flood inundation maps during a flood event can provide crucial information for decision-makers to put relief measures in place.With the development of remote sensing techniques, flood mapping for large areas can be done easily. The algorithm discussed here involves the use of shortwave infrared, near-infrared and green spectral bands to develop a suitable band rationing technique for detecting surface water changes. This technique is referred to as Normalized Difference Surface Water Index (NDSWI). The NDSWI-based approach produces the best results for mapping of flood-inundated areas when verified with actual satellite data. Analysis of results reveals that NDSWI has the potential to detect floodwater turbidity, which was verified using principal component analysis. The application of the technique is informative about flood damages, which are illustrated using the floods in Pakistan in 2010 as an example.
15 Amarnath, Giriraj; Rajah, Ameer. 2013. Manual of the Training on Flood Inundation Mapping and Modeling: Case Study of Bangladesh, held at the Bangladesh Space Research and Remote Sensing Organization, Dhaka, Bangladesh, 12 - 16 May 2013. Colombo, Sri Lanka: International Water Management Institute (IWMI). 119p.
Training materials ; Remote sensing ; Flooding ; Mapping ; Vegetation index ; Models ; Case studies ; Satellite surveys ; Calibration ; Data analysis ; Surface water ; Land use ; Computer software / Bangladesh
(Location: IWMI HQ Call no: e-copy only Record No: H045843)
(5.14 MB)
16 Sharma, Bharat; Rebelo, Lisa-Maria; Amarnath, Giriraj; Miltenburg, I. 2013. Launching next generation ICT for weather and water information and advice to smallholders in Africa [Abstract only]. Paper presented at the Mobile Services that Empower Vulnerable Communities, Catholic Relief Services (CRS) 5th Conference on Information and Communications Technologies for Development (ICT4D), Accra, Ghana, 19-21 March 2013. 1p.
Information and communication technologies (ICTs) ; Weather ; Smallholders ; Water resources / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H045902)
(0.11 MB)
We implemented an IFAD-supported project to promote ICT-based technologies for weather, water and crop –related information and advice to smallholders in Africa. A detailed user need assessment was carried out at four project sites in Ethiopia, Egypt, Sudan and Mali. About 60 farmers at each of the site receive customised information allowing them to plan at the individual field scale not just what to plant and irrigate, but when the weather conditions will be just right for maximum success. Additionally, the farmers in Sudan shall receive forecast on the potential floods. This has hugely empowered the small farmers of the vulnerable communities.
17 Amarnath, Giriraj; Alahacoon, Niranga; Sharma, Bharat; Smakhtin, Vladimir. 2013. Manual of the Training on Development of Flood Forecasting System for Gash Basin using Hydrological Model System, held at the Hydraulic Research Station (HRS), Kassala, Sudan, 27-29 August 2013. Colombo, Sri Lanka: International Water Management Institute (IWMI). 83p.
Training materials ; Remote sensing ; GIS ; Flooding ; Forecasting ; River basins ; Models ; Spate irrigation ; Watersheds ; Rain ; Flow discharge ; Computer applications ; Data / Sudan / Gash Basin
(Location: IWMI HQ Call no: e-copy only Record No: H046101)
(17.26 MB)
18 Amarnath, Giriraj; Simons, G.; Sharma, Bharat; Mohammed, Y.; Gismalla, Y.; Smakhtin, Vladimir. 2013. Smart-ICT for weather and water information and advice to smallholders in Africa. In UNESCO-IHE Institute for Water Education. Conference on New Nile Perspectives Scientific Advances in the eastern Nile Basin, Khartoum, Sudan 6-8 May 2013. Advance copy of extended abstracts. Delft, Netherlands: UNESCO-IHE Institute for Water Education. pp.117-125.
Information and communication technologies (ICTs) ; Weather ; Smallholders ; Farmers ; Water resources ; Spate irrigation ; Flooding ; Mapping ; Rivers ; Catchment areas ; Satellite surveys ; Satellite imagery ; Evapotranspiration ; Crops ; Biomass / Africa / Sudan / Gash River
(Location: IWMI HQ Call no: e-copy only Record No: H046103)
(1.84 MB)
Climate change, water scarcity and food security are becoming increasingly important topics for the growing population of Africa. Due to a general lack of water resources in semi-arid and arid zones, water is an increasingly scarce input in agriculture. The impact of climate change exacerbates this situation further. Even in areas with abundant water resources, optimal use is hampered by insufficient infrastructure to capture these resources and knowledge on appropriate use. With the increased demand and competition for limited water resources the challenge is to increase agricultural production while reducing water consumption (“more crop per drop”). Solutions must be found to enable rural people to overcome poverty, and a start can be made by assisting in food production and water management to combat food insecurity. Local solutions must be adopted in which rural people’s access to new technologies increases. Therefore, smart and affordable technologies need to be adapted to customize farm management for this group of African farmers. Poor farmers need to access real-time information, be able to exchange and apply it: smart ICT (e.g. cell-phones backed up by the web) can play a fundamental role in the communication process.
19 Amarnath, Giriraj. 2013. Cascading Ganges: floods and their impact in the eastern Gangetic Plains. In Sharma, Bharat R.; Prathapar, Sanmugam A. Moving from water problems to water solutions: research needs assessment for the eastern Gangetic Plains. Proceedings of the International Workshop held at the National Agricultural Science Complex (NASC), Indian Council of Agricultural Research (ICAR), New Delhi, India, 7-8 May 2013. Colombo, Sri Lanka: International Water Management Institute (IWMI). CGIAR Research Program on Water, Land and Ecosystems (WLE). pp.55-64.
Flooding ; River basins ; International waters ; Models ; Remote sensing ; Vegetation ; Indicators ; Satellite surveys / Nepal / Bangladesh / Eastern India / Eastern Gangetic Plains
(Location: IWMI HQ Call no: e-copy only Record No: H046111)
(6.60 MB)
20 Amarnath, Giriraj; Sharma, Bharat; Smakhtin, Vladimir. 2014. Managing water resources in agriculture: opportunities from earth observation. [Abstract only]. In India Geospatial Media and Communications. India Geospatial Forum 2014 on Converging Geospatial Trade and Practices, Hyderabad, India, 5-7 February 2014. Programme guide. Noida, Uttar Pradesh, India: India Geospatial Media and Communications. pp.53.
Earth observation satellites ; Remote sensing ; Water management ; Water resources ; Agriculture ; Food production ; Climate change ; River basin / Asia / Africa
(Location: IWMI HQ Call no: e-copy only Record No: H046368)
(0.09 MB)
Food security and economic livelihood of millions of people in Asia and Africa shall continue to depend upon the flows in the major rivers. Variability of water and other resources in time and space is the major natural impediment for sustainable agriculture, food production and development at large. The extremes of variability - floods and droughts - are the primary "agents" of destruction, severe crop damage and loss of human life. According to EM-DAT (2012), about 3 billion people in more than 110 countries are affected by catastrophic flooding. In 2011 alone they killed tens of thousands of people, primarily in developing countries, and caused over $150 billion in damage globally. Our present capacity to understand and make a reasonable forecast of the occurrence and thus management of such anomalies is rather inadequate. Earth observation (EO) satellites play a major role in the provision of information for the study and monitoring of the water resources and can support better understanding in Agricultural Water Resource Management. Their global nature also helps to address the problems of data continuity in trans-national basins where complete, consolidated, and consistent information may be difficult to obtain. In the years to come, EO technology will enter into a new era, where the increasing number of more sophisticated missions will provide scientists with an unprecedented capacity to observe and monitor the different components of climate variability on water resources from the local to the global scales. Already today, global observations of several key parameters governing the global water dynamics (e.g. precipitation, soil moisture, evaporation, transpiration, water levels, mass balance, gravity-derived groundwater measurements, etc.) are feasible. In addition, significant progress has been made in the area of data assimilation enhancing the capabilities to integrate EO-based product into suitable land surface and hydrological models; hence opening new opportunities for science and application. The presentation will illustrate examples of such information and solutions globally and from large river basins in Asia and Africa including flood risks and drought monitoring; Smart-lCT system for climate and weather information, irrigated area mapping etc.
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