Your search found 12 records
1 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)
2 De Silva, R. P. (Ed.) 2004. Geo-informatics research and applications: proceedings of the First Symposium on Geo-informatics, Peradeniya, Sri Lanka, 30 July 2004. Peradeniya, Sri Lanka: Geo-Informatics Society of Sri Lanka (GISSL). 202p.
GIS ; Hydrology ; Technology ; Radar ; Models ; River basins ; Lakes ; Urbanization ; Climatology ; Temperature ; Rain ; Runoff ; Flooding ; Erosion ; Watersheds ; Catchment areas ; Groundwater development ; Groundwater assessment ; Water pollution ; Land use ; Land cover ; Case study ; Developing countries / Sri Lanka / Bangladesh / Kenya / Walawe River Basin / Lake Naivasha Basin / Kukule Watershed / Moneragala District / Hambantota / Deduru Oya Upper Watershed / Kndy Lake
(Location: IWMI HQ Call no: 621.3678 G000 DES Record No: H045953)
(0.30 MB)
3 Gangodagamage, C.; Biradar, C. M.; Islam, A.; Thenkabail, P. S. 2004. Shuttle Radar Topography Mission (SRTM) data for Sri Lanka: potential contributions in river basin research. In De Silva, R. P. (Ed.). Geo-informatics research and applications: proceedings of the First Symposium on Geo-informatics, Peradeniya, Sri Lanka, 30 July 2004. Peradeniya, Sri Lanka: Geo-Informatics Society of Sri Lanka (GISSL). pp.19-30.
River basins ; Catchment areas ; Radar ; Models ; Global Positioning Systems) ; Hydrology / Sri Lanka
(Location: IWMI HQ Call no: 621.3678 G000 DES Record No: H045954)
(1.11 MB)
4 Petropoulos, G. P. 2014. Remote sensing of energy fluxes and soil moisture content. Boca Raton, FL, USA: CRC Press. 506p.
Remote sensing ; Energy balance ; Soil moisture ; Soil properties ; Hydrology ; Models ; Climate change ; Heat ; Flooding ; Agroecosystems ; Spatial distribution ; Evapotranspiration ; Radar ; Satellite observation ; Environmental factors ; Land use ; Vegetation ; Measurement ; Case studies ; Solar radiation ; Water balance / Brazil
(Location: IWMI HQ Call no: 551.52530287 G000 PET Record No: H046471)
(0.44 MB)
5 Pandey, Rajesh; Amarnath, Giriraj. 2015. The potential of satellite radar altimetry in flood forecasting: concept and implementation for the Niger-Benue River Basin. Proceedings of the International Association of Hydrological Sciences, 370:223-227. [doi: https://doi.org/10.5194/piahs-370-223-2015]
Satellite observation ; Radar ; Weather forecasting ; Floods ; River basins ; Hydrology ; Models ; Water levels ; Flow discharge ; Case studies / Nigeria / Niger River / Benue River
(Location: IWMI HQ Call no: e-copy only Record No: H047061)
http://www.proc-iahs.net/370/223/2015/piahs-370-223-2015.pdf
https://vlibrary.iwmi.org/pdf/H047061.pdf
https://vlibrary.iwmi.org/pdf/H047061.pdf
(1.43 MB) (1.43 MB)
Flood forecasting in the downstream part of any hydrological basin is extremely difficult due to the lack of basin-wide hydrological information in near real-time and the absence of a data-sharing treaty among the transboundary nations. The accuracy of forecasts emerging from a hydrological model could be compromised without prior knowledge of the day-to-day flow regulation at different locations upstream of the Niger and Benue rivers. Only satellite altimeter monitoring allows us to identify the actual river levels upstream that reflect the human intervention at that location. This is critical for making accurate downstream forecasts. This present study aims to demonstrate the capability of altimeter-based flood forecasting along the Niger-Benue River in Nigeria. The study includes the comparison of decadal (at every 10 days from Jason-2) or monthly (at every 35 days from Envisat/AltiKa) observations from 2002 to 2014, with historical in situ measurements from 1990 to 2012. The water level obtained from these sources shows a good correlation (0.7–0.9). After validation of hydrological parameters obtained from two sources, a quantitative relation (rating curve) of upstream water level and downstream discharge is derived. This relation is then adopted for calculation of discharge at observation points, which is used to propagate the flow downstream at a desired location using a hydraulic river model. Results from this study from Jason-2 shows a promising correlation (R2 90% with a Nash-Sutcliffe coefficient of more than 0.70) with 5 days ahead of downstream flow prediction over the Benue stream.
6 Brocca, L.; Crow, W. T.; Ciabatta, L.; Massari, C.; de Rosnay, P.; Enenkel, M.; Hahn, S.; Amarnath, Giriraj; Camici, S.; Tarpanelli, A.; Wagner, W. 2017. A review of the applications of ASCAT [Advanced SCATterometer] soil moisture products. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 10(5):2285-2306. [doi: https://doi.org/10.1109/JSTARS.2017.2651140]
Soil moisture ; Hydrology ; Remote sensing ; Weather forecasting ; Radar ; Meteorological observations ; Satellite observation ; Hydrological cycle ; Climate change ; Rain ; Flooding ; Precipitation ; Evaporation ; Evapotranspiration ; Landslides
(Location: IWMI HQ Call no: e-copy only Record No: H048009)
Remote sensing of soil moisture has reached a level of good maturity and accuracy for which the retrieved products are ready to use in real-world applications. Due to the importance of soil moisture in the partitioning of the water and energy fluxes between the land surface and the atmosphere, a wide range of applications can benefit from the availability of satellite soil moisture products. Specifically, the Advanced SCATterometer (ASCAT) on board the series of Meteorological Operational (Metop) satellites is providing a near real time (and long-term, 9+ years starting from January 2007) soil moisture product, with a nearly daily (sub-daily after the launch of Metop-B) revisit time and a spatial sampling of 12.5 and 25 km. This study first performs a review of the climatic, meteorological, and hydrological studies that use satellite soil moisture products for a better understanding of the water and energy cycle. Specifically, applications that consider satellite soil moisture product for improving their predictions are analyzed and discussed. Moreover, four real examples are shown in which ASCAT soil moisture observations have been successfully applied toward: 1) numerical weather prediction, 2) rainfall estimation, 3) flood forecasting, and 4) drought monitoring and prediction. Finally, the strengths and limitations of ASCAT soil moisture products and the way forward for fully exploiting these data in real-world applications are discussed.
7 El-Agha, Doaa E.; Closas, Alvar; Molle, Francois. 2017. Below the radar: the boom of groundwater use in the central part of the Nile Delta in Egypt. Hydrogeology Journal, 25(6):1621-1631. [doi: https://doi.org/10.1007/s10040-017-1570-8]
Socioeconomic environment ; Legislation ; Groundwater extraction ; Groundwater irrigation ; Groundwater development ; Water use ; Domestic water ; Industrial uses ; Radar ; Deltas ; Water drilling ; Wells ; Irrigated land ; Farmers ; Surface water ; Aquifers ; Economic aspects ; Spatial distribution ; Salinity / Egypt / Nile Delta
(Location: IWMI HQ Call no: e-copy only Record No: H048137)
The Nile Delta of Egypt is known for its large irrigated area supplied with water diverted from the Nile River, with a limited use of groundwater, largely for domestic and industrial use. Official statistics for the whole delta indicate that there are a few thousand individual wells used for agriculture by a population of over 2 million farmers. This study, however, shows that a phenomenon of groundwater development for irrigation has been unfolding over the last few years, largely below the radar of managers and researchers. A survey was carried out in the central part of the delta with the objective of (1) uncovering the actual situation of groundwater use in this part of the delta and (2) speculating on its implications. The results of the survey pointed to a recent and booming tube-well drilling industry, with well densities in some parts reaching one well every 2 ha. The development of groundwater abstraction in the central delta is strongly linked to inadequate and/or untimely availability of surface water in the canals. A technical, economic, and management characterization of wells complements the study, showing a continuum between purely private/individual ownership of wells and collective investments and management. Lastly, the article explores the implications of unchecked abstraction at the farm, local and delta scales.
8 Ghosh, S.; Thakur, P. K.; Sharma, R.; Nandy, S.; Garg, V.; Amarnath, Giriraj; Bhattacharyya, S. 2017. The potential applications of satellite altimetry with SARAL [Satellite with ARGOS and ALTIKA]/AltiKa for Indian inland waters. Proceedings of the National Academy of Sciences India Section A-Physical Sciences, 19p. (Online first). [doi: https://doi.org/10.1007/s40010-017-0463-5]
Earth observation satellites ; Inland waters ; Surface water ; Monitoring ; Satellite observation ; Radar ; Water levels ; River basins ; Flow discharge ; Reservoirs ; Sedimentation ; Measurement ; Hydrology ; Models ; Calibration / India
(Location: IWMI HQ Call no: e-copy only Record No: H048445)
(1.39 MB)
The satellite radar altimetry datasets are now extensively used for continental water monitoring although it was primarily designed for oceanic surface and ice cap studies. Water level estimated from satellite altimetry can help to assess many hydrological parameters like river discharge and reservoir volume. These parameters can be employed for calibration and validation purposes of hydrological and hydrodynamic models, rating curve (stage-discharge relationship) generation, near real-time flood forecasting, reservoir operations and transboundary water related issues. Satellite with Argos and AltiKa (SARAL/AltiKa), a joint venture of Indian Space Research Organisation and Centre National d’Etudes Spatiales, is one of the pioneer missions in the history of satellite radar altimetry. It is first high-frequency (Ka-band, 35.75 GHz) mission with the highest sampling rate (40 Hz). The applications of radar altimetry to inland hydrology have been significantly increased in recent years in India. Major studies have been carried out in Ganga, Brahmaputra, Tapi and Godavari river basins with AltiKa data. AltiKa datasets have been successfully used for retrieving water level in reservoir and river, estimating river discharge and calculating reservoir sedimentation. Considering the stress on India’s fresh water resources and the importance of SARAL/AltiKa mission, this work was carried out. The present review paper may be helpful to understand the working principle of altimetry, altimetry waveform, waveform retracking methods, water stage, river discharge and changes in reservoir’s water storage calculation, and the status of altimetry applications to inland hydrology, specifically solicitation of SARAL/AltiKa in the Indian context.
9 Tarpanelli, A.; Amarnath, Giriraj; Brocca, L.; Massari, C.; Moramarco, T. 2017. Discharge estimation and forecasting by MODIS and altimetry data in Niger-Benue River. Remote Sensing of Environment, 195:96-106. [doi: https://doi.org/10.1016/j.rse.2017.04.015]
Weather forecasting ; Flooding ; Rivers ; Discharges ; Estimation ; Satellite imagery ; Moderate Resolution Imaging Spectroradiometer ; Models ; Radar ; Remote sensing ; Water levels ; Downstream / Nigeria / Niger River / Benue River / Lokoja / Makurdi
(Location: IWMI HQ Call no: e-copy only Record No: H048996)
(3.09 MB)
Flooding is one of the most devastating natural hazards in the world and its forecast is essential in flood risk reduction and disaster response decision. The lack of adequate monitoring networks, especially in developing countries prevents near real-time flood prediction that could help to reduce the loss of lives and economic damages. In the last few years, increasing availability of multi-satellite sensors induced to develop new techniques for retrieving river discharge and especially in supporting discharge nowcasting and forecasting activities. Recently, the potential of radar altimetry to estimate water levels and discharge in ungauged river sites with good accuracy has been demonstrated. However, the considerable benefit derived from this technique is attenuated by the low revisit time of the satellite (10 or 35 days, depending on the satellite mission) causing delays on the predicting operations. For this reason, sensors with a higher temporal resolution such as the MODerate resolution Imaging Spectroradiometer (MODIS), working in visible/Infra-Red bands, can support flood forecasting.
In this study, we performed the forecast of river discharge by using MODIS and we compared it with the radar altimetry and in-situ data along the Niger-Benue River in Nigeria to develop an operational flood forecasting scheme that could help in rapid emergency response and decision making processes. In the first step, four MODIS products (daily and, 8-day from the TERRA and AQUA satellites) at two gauged sites were used for discharge estimation. Secondly, the capability of remote sensing sensors to forecast discharge a few days (~4 days) in advance at a downstream section using MODIS is analyzed and also compared with the one obtained by the use of radar altimetry by ENVISAT and Jason-2.
The results confirmed the capability of the MODIS data to estimate river discharge with performance indices N0.97 and 0.95 in terms of coefficient of correlation and Nash Sutcliffe efficiency. In particular, RMSE does not exceed 1300 m3 /s and the fractional RMSE ranges between 0.15 and 0.23. For the forecasting exercise, both altimetry and MODIS provide satisfactory results with positive coefficient of persistence considering 4 days of lead time (N0.34). Although altimetry was found to be more accurate in the forecasting of river discharge (RMSE ~350 m3 /s), the much higher temporal resolution of MODIS guarantees a continuity that is more suitable to address operational activities.
In this study, we performed the forecast of river discharge by using MODIS and we compared it with the radar altimetry and in-situ data along the Niger-Benue River in Nigeria to develop an operational flood forecasting scheme that could help in rapid emergency response and decision making processes. In the first step, four MODIS products (daily and, 8-day from the TERRA and AQUA satellites) at two gauged sites were used for discharge estimation. Secondly, the capability of remote sensing sensors to forecast discharge a few days (~4 days) in advance at a downstream section using MODIS is analyzed and also compared with the one obtained by the use of radar altimetry by ENVISAT and Jason-2.
The results confirmed the capability of the MODIS data to estimate river discharge with performance indices N0.97 and 0.95 in terms of coefficient of correlation and Nash Sutcliffe efficiency. In particular, RMSE does not exceed 1300 m3 /s and the fractional RMSE ranges between 0.15 and 0.23. For the forecasting exercise, both altimetry and MODIS provide satisfactory results with positive coefficient of persistence considering 4 days of lead time (N0.34). Although altimetry was found to be more accurate in the forecasting of river discharge (RMSE ~350 m3 /s), the much higher temporal resolution of MODIS guarantees a continuity that is more suitable to address operational activities.
10 Tarpanelli, A.; Santi, E.; Tourian, M. J.; Filippucci, P.; Amarnath, Giriraj; Brocca, L. 2019. Daily river discharge estimates by merging satellite optical sensors and radar altimetry through artificial neural network. IEEE Transactions on Geoscience and Remote Sensing, 57(1):329-341. [doi: https://doi.org/10.1109/TGRS.2018.2854625]
Rivers ; Discharges ; Estimation ; Water levels ; Remote sensing ; Satellite imagery ; Landsat ; Moderate Resolution Imaging Spectroradiometer ; Neural networks ; Radar ; Performance indexes ; Time series analysis ; Case studies / Nigeria / Italy / Niger River / Benue River / Po River / Lokoja / Pontelagoscuro
(Location: IWMI HQ Call no: e-copy only Record No: H048997)
(2.81 MB)
Thanks to the large number of satellites, the multimission approach is becoming a viable method to integrate measurements and intensify the number of samples in space and time for monitoring the earth system. In this paper, we merged data from different satellite missions, optical sensors, and altimetry, for estimating daily river discharge through the application of the artificial neural network (ANN) technique. ANN was selected among other retrieval techniques because it offers an easy but effective way of combining input data from different sources into the same retrieval algorithm. The network is trained in a calibration period and validated in an independent period against in situ observations of river discharge for two gauging sites: Lokoja along the Niger River and Pontelagoscuro along the Po River. For optical sensors, we found that the temporal resolution is more important than the spatial resolution for obtaining accurate discharge estimates. Our results show that Landsat fails in the estimation of extreme events by missing most of the peak values due to its long revisit time (14–16 days). Better performances are obtained from Moderate Resolution Imaging Spectroradiometer (MODIS) and Medium Resolution Imaging Spectrometer. Radar altimetry provides results in between MODIS-TERRA and MODIS-AQUA at Lokoja, whereas it outperforms all single optical sensors at Pontelagoscuro. The multimission approach, involving optical sensors and altimetry, is found the most reliable tool to estimate river discharge with a relative root-mean-square error of 0.12% and 0.27% and Nash-Sutcliffe coefficient of 0.98 and 0.83 for the Niger and Po rivers, respectively.
11 Asfaw, W.; Haile, Alemseged Tamiru; Rientjes, T. 2020. Combining multisource satellite data to estimate storage variation of a lake in the Rift Valley Basin, Ethiopia. International Journal of Applied Earth Observation and Geoinformation, 89:102095. [doi: https://doi.org/10.1016/j.jag.2020.102095]
Water storage ; Estimation ; Lakes ; Surface area ; Satellite imagery ; Landsat ; Radar ; Remote sensing ; Water levels ; Water extraction ; Rivers / Ethiopia / Rift Valley Basin / Lake Ziway
(Location: IWMI HQ Call no: e-copy only Record No: H049749)
https://www.sciencedirect.com/science/article/pii/S0303243419311997/pdfft?md5=640ffced1d934faff7ef42e894ee9542&pid=1-s2.0-S0303243419311997-main.pdf
https://vlibrary.iwmi.org/pdf/H049749.pdf
https://vlibrary.iwmi.org/pdf/H049749.pdf
(2.11 MB) (2.11 MB)
Integration of remote sensing data sets from multiple satellites is tested to simulate water storage variation of Lake Ziway, Ethiopia for the period 2009-2018. Sixty Landsat ETM+/OLI images served to trace temporal variation of lake surface area using a water extraction index. Time series of lake levels were acquired from two altimetry databases that were validated by in-situ lake level measurements. Coinciding pairs of optical satellite based lake surface area and radar altimetry based lake levels were related through regression and served for simulating lake storage variation. Indices for extracting lake surface area from images showed 91–99 % overall accuracy. Lake water levels from the altimetry products well agreed to in-situ lake level measurements with R2 = 0.92 and root mean square error of 11.9 cm. Based on this study we conclude that integrating satellite imagery and radar altimetry is a viable approach for frequent and accurate monitoring of lake water volume variation and for long-term change detection. Findings indicate water level reduction (4 cm/annum), surface area shrinkage (0.08km2 /annum) and water storage loss (20.4Mm3 /annum) of Lake Ziway (2009–2018).
12 Kubitza, C.; Krishna, V. V.; Schulthess, U.; Jain, M. 2020. Estimating adoption and impacts of agricultural management practices in developing countries using satellite data. A scoping review. Agronomy for Sustainable Development, 40(3):16. [doi: https://doi.org/10.1007/s13593-020-0610-2]
Agricultural practices ; Developing countries ; Satellite imagery ; Landsat ; Radar ; Remote sensing ; Moderate resolution imaging spectroradiometer ; Intensive cropping ; Crop yield ; Tillage ; Technology ; Soil conservation ; Water conservation ; Smallholders ; Vegetation index ; Land cover ; Irrigation
(Location: IWMI HQ Call no: e-copy only Record No: H050034)
(0.86 MB)
Development and dissemination of sustainable practices are key to enhance agricultural productivity in developing countries and to curtail potential negative externalities. Rigorous adoption/impact evaluations provide valuable lessons to enhance the capacity of agricultural research-for-development (R4D) systems in this context. Conventional evaluation studies rely solely on farm-household surveys for data. Generation of survey data however requires considerable financial and human capital, and the process often misses several important explanatory variables, ignores the longer-term impacts, and suffers from measurement errors. Complementary data sources are explored to make the evaluations more robust and rigorous. Here we review 54 studies that used satellite data to estimate adoption and impact of agricultural practices in developing countries. Some evidence on successful application of satellite data in high-income countries is also provided. The main findings of the paper are threefold: (1) satellite data have been successfully used to detect agricultural practices, such as cropping intensity, tillage, crop residue cover, irrigation, and soil and water conservation; (2) only a few studies have estimated the yield impacts of agricultural practices, although the estimation of crop yields with satellite data is fairly developed; and (3) only a small number of studies have explored impact estimation beyond the biophysical sphere. Estimation of certain environmental impacts of agricultural practices is possible through satellite data, although only a few studies have carried it out. Not many have assessed the economic impacts of interventions. We conclude that satellite data analysis allows information access with little delay and over longer periods, provide a unique set of variables over wide geographies, and reduce measurement error in certain variables. However, more interdisciplinary research is necessary to speed up the uptake of this alternative data source in R4D evaluations.
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