Your search found 6 records
1 Gumma, M. K.; Thenkabail, P. S.; Muralikrishna. I. V.; Velpuri, M. N.; Gangadhara Rao, Parthasaradhi; Dheeravath, V.; Biradar, C. M.; Acharya, N. Sreedhar; Gaur, A. 2011. Changes in agricultural cropland areas between a water-surplus year and a water-deficit year impacting food security, determined using MODIS 250 m time-series data and spectral matching techniques, in the Krishna River basin (India). International Journal of Remote Sensing, 32(12):3495-3520. [doi: https://doi.org/10.1080/01431161003749485]
(Location: IWMI HQ Call no: e-copy only Record No: H043968)
(1.46 MB)
The objective of this study was to investigate the changes in cropland areas as a result of water availability using Moderate Resolution Imaging Spectroradiometer (MODIS) 250 m time-series data and spectral matching techniques (SMTs). The study was conducted in the Krishna River basin in India, a very large river basin with an area of 265 752 km2 (26 575 200 ha), comparing a water-surplus year (2000–2001) and a water-deficit year (2002–2003). The MODIS 250 m time-series data and SMTs were found ideal for agricultural cropland change detection over large areas and provided fuzzy classification accuracies of 61–100% for various land-use classes and 61–81% for the rain-fed and irrigated classes. The most mixing change occurred between rain-fed cropland areas and informally irrigated (e.g. groundwater and small reservoir) areas. Hence separation of these two classes was the most difficult. The MODIS 250 m-derived irrigated cropland areas for the districts were highly correlated with the Indian Bureau of Statistics data, with R2-values between 0.82 and 0.86. The change in the net area irrigated was modest, with an irrigated area of 8 669 881 ha during the water-surplus year, as compared with 7 718 900 ha during the water-deficit year. However, this is quite misleading as most of the major changes occurred in cropping intensity, such as changing from higher intensity to lower intensity (e.g. from double crop to single crop). The changes in cropping intensity of the agricultural cropland areas that took place in the water-deficit year (2002–2003) when compared with the water-surplus year (2000–2001) in the Krishna basin were: (a) 1 078 564 ha changed from double crop to single crop, (b) 1 461 177 ha changed from continuous crop to single crop, (c) 704 172 ha changed from irrigated single crop to fallow and (d) 1 314 522 ha changed from minor irrigation (e.g. tanks, small reservoirs) to rain-fed. These are highly significant changes that will have strong impact on food security. Such changes may be expected all over the world in a changing climate.
2 Adams, J. B.; Gillespie, A. R. 2006. Remote sensing of landscapes with spectral images: a physical modeling approach. New York, NY, USA: Cambridge University Press. 362p.
(Location: IWMI HQ Call no: 551.48 G000 ADA Record No: H046138)
(0.73 MB)
(Location: IWMI HQ Call no: 519.55 G000 SHU Record No: H046803)
(0.36 MB)
(Location: IWMI HQ Call no: e-copy only Record No: H047509)
(6.45 MB)
Interannual variation in rainfall throughout Tamil Nadu has been causing frequent and noticeable land use changes despite the rapid development in groundwater irrigation. Identifying periodically water-stressed areas is the first and crucial step to minimizing negative effects on crop production. Such analysis must be conducted at the basin level as it is an independent water accounting unit. This paper investigates the temporal variation in irrigated area between 2000–2001 and 2010–2011 due to rainfall variation at the state and sub-basin level by mapping and classifying Moderate Resolution Imaging Spectroradiometer (MODIS) 8-day composite satellite imagery using spectral matching techniques. A land use/land cover map was drawn with an overall classification accuracy of 87.2 %. Area estimates between the MODISderived net irrigated area and district-level statistics (2000–2001 to 2007–2008) were in 95 % agreement. A significant decrease in irrigated area (30–40 %) was observed during the water-stressed years of 2002–2003, 2003–2004, and 2009–2010. Major land use changes occurred three times during 2000 to 2010. This study demonstrates how remote sensing can identify areas that are prone to repeated land use changes and pin-point key target areas for the promotion of drought-tolerant varieties, alternativewater management practices, and new cropping patterns to ensure sustainable agriculture for food security and livelihoods.
(Location: IWMI HQ Call no: e-copy only Record No: H049963)
(1.91 MB)
Water managers and stakeholders usually face uncertainty in water availability due to the challenge of incorporating the dynamic nature of precipitation into the water management system. Surface water rights are commonly related to the baseflow component, which is part of the precipitation incident on a watershed. This study proposes an empirical linear model to predict baseflow in perennial streams based on a moving average of antecedent rainfall data and the basin time response. The short-term responses of three nested basins were estimated using cross Fourier spectral analysis, and the proposed model was applied to two nested basin scales (1,867 and 3,519 km2), located in southeastern Brazil. Results indicate that the aquifer stores the rainfall water with regulation times of approximately 60 days for the fast-subsurface flow and approximately 2–3 years for the slow groundwater flow in both basins. Differences between our model results and monthly 95% exceedance discharge (Q95) were as high as 10 m3 s-1 between September and November in the largest basin, revealing how conservative Q95 can be as a criterion for water allocation purposes. Despite the simplicity, our empirical rainfall-based model is structurally consistent and robust in representing the hydrological processes involving precipitation, groundwater storage and baseflow interactions at multiple scales by using few inputs and calibration parameters. Because it considers a range of rainfall periods, from past to present, our model contributes to a dynamic, predictive, and integrated water rights management.
6 Wei, J.; Wang, M.; Mikelsons, K.; Jiang, L.; Kratzer, S.; Lee, Z.; Moore, T.; Sosik, H. M.; Van der Zande, D. 2022. Global satellite water classification data products over oceanic, coastal, and inland waters. Remote Sensing of Environment, 282:113233. [doi: https://doi.org/10.1016/j.rse.2022.113233]
(Location: IWMI HQ Call no: e-copy only Record No: H051470)
(8.68 MB) (8.68 MB)
Satellites have generated extensive data of remote sensing reflectance spectra (Rrs( )) covering diverse water classes or types across global waters. Spectral classification of satellite Rrs( ) data allows for the distinguishing and grouping of waters with characteristic bio-optical/biogeochemical features that may influence the productivity of a given water body. This study reports new satellite water class products (Level-2 and Level-3) from the Visible Infrared Imaging Radiometer Suite (VIIRS). We developed and implemented a hyperspectral scheme that accounts for the Rrs( ) spectral shapes and globally resolves oceanic, coastal, and inland waters into 23 water classes. We characterized the light absorption and scattering coefficients, chlorophyll-a concentration, diffuse attenuation coefficient, and suspended particulate matter for individual water classes. It is shown that the water classes are separable by their distinct bio-optical and biogeochemical properties. Furthermore, validation result suggests that the VIIRS water class products are accurate globally. Finally, we examined the spatial and temporal variability of the water classes in case studies for a demonstration of applications. The water class data in open oceans reveal that the subtropical ocean gyres have experienced dramatic expansion over the last decade. In addition, the water class data appear to be a valuable (and qualitative) indicator for water quality in coastal and inland waters with compelling evidence. We stress that this new satellite product is an excellent addition to the aquatic science database, despite the need for continuous improvement toward perfection.
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