Volume 14 Issue 4
Dec.  2021
Turn off MathJax
Article Contents
Kaushlendra Verma, Akhilesh S. Nair, Indu Jayaluxmi, Subhankar Karmakar, Stephane Calmant. 2021: Satellite altimetry for Indian reservoirs. Water Science and Engineering, 14(4): 277-285. doi: 10.1016/j.wse.2021.09.001
Citation: Kaushlendra Verma, Akhilesh S. Nair, Indu Jayaluxmi, Subhankar Karmakar, Stephane Calmant. 2021: Satellite altimetry for Indian reservoirs. Water Science and Engineering, 14(4): 277-285. doi: 10.1016/j.wse.2021.09.001

Satellite altimetry for Indian reservoirs

doi: 10.1016/j.wse.2021.09.001
Funds:

This work was supported by the DST CNRS Project (Grant No. DST CNRS-2015-1) and the project funded by DST Centre of Excellence in Climate Studies, Indian Institute of Technology, Bombay (Grant No. DST/ CCP/CoE/140/2018(G)).

  • Received Date: 2020-12-21
  • Accepted Date: 2021-07-31
  • Available Online: 2021-12-15
  • Satellite radar altimetry has immense potential for monitoring fresh surface water resources and predicting the intra-seasonal, seasonal, and inter-annual variability of inundated surface water over large river basins. As part of the Preparation for the Surface Water and Ocean Topography mission scheduled for launch in mid-2022, the present study aimed to evaluate the performance of radar altimetry over the inland water bodies of India. The Joint Altimetry Satellite Oceanography Network (Jason) and Satellite with ARgos and ALtiKa (SARAL/AltiKa) data were used to derive the water levels of 18 major reservoirs in India by incorporating the geophysical and propagation corrections into the radar range. In situ gauge data were used to evaluate the performance of the altimetry-derived water level time series from 2008 to 2019. The results showed a strong correlation between Jason-2 and in situ data with the determination coefficient (R2) and root mean squared error (RMSE) ranging from 0.96 to 0.99 and from 0.28 m to 1.62 m, respectively. The Jason-3 data had the highest correlation with the in situ observation (R2 = 0.99) and the lowest correlation (R2 = 0.82), with RMSE values ranging from 0.11 m to 1.18 m. With an R2 range of 0.93-0.99 and an RMSE range of 0.20-1.05 m, the SARAL/AltiKa mission presented greater accuracy than the Jason altimetry mission. The estimated water levels can be utilized in remote, inaccessible, or ungauged areas and in international transboundary rivers for water storage and river discharge estimations. However, the accuracy of remotely sensed data depends on such factors as along-track distance, water body area, and geographical and terrain conditions near water bodies.

     

  • loading
  • Alsdorf, D.E., Rodriguez, E., Lettenmaier, D.P., 2007. Measuring surface water from space. Rev. Geophys. 45(2), 1-24. https://doi.org/10.1029/2006RG000197.
    Becker, M., Santos da Silva, J., Calmant, S., Robinet, V., Linguet, L., Seyler, F., 2014. Water level fluctuations in the Congo Basin derived from ENVISAT satellite altimetry. Rem. Sens. 6(10), 9340-9358. https://doi.org/10.3390/rs6109340.
    Biancamaria, S., Andreadis, K.M., Durand, M., Clark, E.A., Rodrguez, E., Mognard, N.M., Alsdorf, D.E., Lettenmaier, D.P., Oudin, Y., 2010. Preliminary characterization of SWOT hydrology error budget and global capabilities. IEEE J. Selected Topics in App. Earth Obs. Remote Sens. 3(1), 6-19. https://doi.org/10.1109/JSTARS.2009.2034614.
    Biancamaria, S., Lettenmaier, D.P., Pavelsky, T.M., 2016. The SWOT mission and its capabilities for land hydrology. Surv. Geophys. 37(2), 307-337. https://doi.org/10.1007/s10712-015-9346-y.
    Birkett, C.M., 1995. The contribution of TOPEX/POSEIDON to the global monitoring of climatically sensitive lakes. J. Geophys. Res. 100(12), 25179-25204. https://doi.org/10.1029/95JC02125.
    Birkinshaw, S.J., O'Donnell, G.M., Moore, P., Kilsby, C.G., Fowler, H.J., Berry, P., 2010. Using satellite altimetry data to augment flow estimation techniques on the Mekong River. Hydrol. Process. 24(26), 3811-3825. https://doi.org/10.1002/hyp.7811.
    Bjerklie, D.M., Moller, D., Smith, L., Dingman, L., 2005. Estimating discharge in rivers using remotely sensed hydraulic information. J. Hydrol. 309(1-4), 191-209. https://doi.org/10.1016/j.jhydrol.2004.11.022.
    Blewitt, G., Kreemer, C., Hammond, W.C., Gazeaux, J., 2016. MIDAS robust trend estimator for accurate GPS station velocities without step detection. J. Geophysical Research Solid Earth 121(3), 2054-2068. https://doi.org/10.1002/2015JB012552.
    Brakenridge, G.R., Nghiem, S.V., Anderson, E., Chien, S., 2005. Space-based measurement of river runoff. EOS Transaction American Geophysical Union 86(19), 185-188. https://doi.org/10.1029/2005EO190001.
    Calmant, S., Seyler, F., 2006. Continental surface waters from satellite altimetry. Compt. Rendus Geosci. 338(14-15), 1113-1122. https://doi.org/10.1016/j.crte.2006.05.012.
    Calmant, S., Seyler, F., Cretaux, J.F., 2008. Monitoring continental surface waters by satellite altimetry. Surv. Geophys. 29(4), 247-269. https://doi.org/10.1007/s10712-008-9051-1.
    Chow, V.T., Maidment, D.R., Mays, L.W., 1998. Applied Hydrology. McGraw-Hill, New York.
    Cr etaux, J.F., Biancamaria, S., Arsen, A., Berg e-Nguyen, M., Becker, M., 2015. Global surveys of reservoirs and lakes from satellites and regional application to the Syrdarya river basin. Environ. Res. Lett. 10(1), 015002. https://doi.org/10.1088/1748-9326/10/1/015002.
    Cr etaux, J.F., Abarca-del-Río, R., Berge-Nguyen, M., Arsen, A., Drolon, V., Clos, G., Maisongrande, P., 2016. Lake volume monitoring from space. Surv. Geophys. 37(2), 269-305. https://doi.org/10.1007/s10712-016-9362-6.
    Domeneghetti, A., Tarpanelli, A., Brocca, L., Barbetta, S., Moramarco, T., Castellarin, A., Brath, A., 2014. The use of remote sensing-derived water surface data for hydraulic model calibration. Rem. Sens. Environ. 149, 130-141. https://doi.org/10.1016/j.rse.2014.04.007.
    Domeneghetti, A., Castellarin, A., Tarpanelli, A., Moramarco, T., 2015. Investigating the uncertainty of satellite altimetry products for hydrodynamic modelling. Hydrol. Process. 29(23), 4908-4918. https://doi.org/10.1002/hyp.10507.
    Dubey, A.K., Gupta, P., Dutta, S., Singh, R.P., 2015. Water level retrieval using SARAL/AltiKa observations in the braided Brahmaputra river, Eastern India. Mar. Geodes. 38(1), 549-567. https://doi.org/10.1080/01490419.2015.1008156.
    Durand, M., Fu, L.L., Lettenmaier, D.P., Alsdorf, D.E., Rodriguez, E., EstebanFernandez, D., 2010. The surface water and ocean topography mission:Observing terrestrial surface water and oceanic submesoscale eddies. Proc. IEEE 98(5), 766-779. https://doi.org/10.1109/JPROC.2010.2043031.
    Frappart, F., Papa, F., da Silva, J.S., Ramillien, G., Prigent, C., Seyler, F., Calmant, S., 2012. Surface freshwater storage and dynamics in the Amazon basin during the 2005 exceptional drought. Environ. Res. Lett. 7(4), 044010. https://doi.org/10.1088/1748-9326/7/4/044010.
    Frappart, F., Papa, F., Malbeteau, Y., Leon, J.G., Ramillien, G., Prigent, C., Seoane, L., Seyler, F., Calmant, C., 2015a. Surface freshwater storage variations in the Orinoco floodplains using multi-satellite observations. Rem. Sens. 7(1), 89-110. https://doi.org/10.3390/rs70100089.
    Frappart, F., Papa, F., Marieu, V., Malbeteau, Y., Jordy, F., Calmant, S., Durand, F., Bala, S., 2015b. Preliminary assessment of SARAL/AltiKa observations over the ganges-brahmaputra and irrawaddy rivers. Mar. Geodes. 38(1), 568-580. https://doi.org/10.1080/01490419.2014.990591.
    Fu, L.L., Alsdorf, D., Rodrıguez, R.M.E., Mognard, N., 2012. SWOT:the Surface Water and Ocean Topography Mission:Wide-Swath Altimetric Measurements of Water Elevation on Earth. Jet Propulsion Laboratory, Pasadena.
    Getirana, A.C.V., 2010. Integrating spatial altimetry data into the automatic calibration of hydrological models. J. Hydrol. 387(3-4), 244-255. https://doi.org/10.1016/j.jhydrol.2010.04.013.
    Gleason, C.J., Hamdan, A.N., 2017. Crossing the (watershed) divide:Satellite data and the changing politics of international river basins. Geogr. J. 183(1), 2-15. https://doi.org/10.1111/geoj.12155.
    Hossain, F., Siddique-E-Akbor, A.H., Mazumder, L.C., ShahNewaz, S.M., Biancamaria, S., Lee, H., Shum, C.K., 2014. Proof of concept of an altimeter-based river forecasting system for transboundary flow inside Bangladesh. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 7(2), 587-601. https://doi.org/10.1109/JSTARS.2013.2283402.
    Jiang, L., Nielsen, K., Andersen, O.B., Bauer-Gottwein, P., 2017. Monitoring recent lake level variations on the Tibetan Plateau using CryoSat-2 SARIn mode data. J. Hydrol. 544, 109-124. https://doi.org/10.1016/j.jhydrol.2016.11.024.
    Jiang, L., Nielsen, K., Dinardo, S., Andersen, O.B., Bauer-Gottwein, P., 2020. Evaluation of Sentinel-3 SRAL SAR altimetry over Chinese rivers. Rem. Sens. Environ. 237, 111546. https://doi.org/10.1016/j.rse.2019.111546.
    Kleinherenbrink, M., Lindenbergh, R.C., Ditmar, P.G., 2015. Monitoring of lake level changes on the Tibetan Plateau and Tian Shan by retracking Cryosat SARIn waveforms. J. Hydrol. 521, 119-131. https://doi.org/10.1016/j.jhydrol.2014.11.063.
    Kouraev, A.V., Zakharova, E.A., Samain, O., Mognard, N.M., Cazenave, A., 2004. Ob'river discharge from TOPEX/Poseidon satellite altimetry(1992-2002). Rem. Sens. Environ. 93(1-2), 238-245. https://doi.org/10.1016/j.rse.2004.07.007.
    LeFavour, G., Alsdorf, D., 2005. Water slope and discharge in the Amazon River estimated using the shuttle radar topography mission digital elevation model. Geophys. Res. Lett. 32(17), 1-5. https://doi.org/10.1029/2005GL023836.
    Leys, C., Ley, C., Klein, O., Bernard, P., Licata, L., 2013. Detecting outliers:Do not use standard deviation around the mean, use absolute deviation around the median. J. Exp. Soc. Psychol. 49(4), 764-766. https://doi.org/10.1016/j.jesp.2013.03.013.
    Maswood, M., Hossain, F., 2016. Advancing river modelling in ungauged basins using satellite remote sensing:The case of the GangeseBrahmaputraeMeghna basin. Int. J. River Basin Manag. 14(1), 103-117. https://doi.org/10.1080/15715124.2015.1089250.
    Michailovsky, C.I., Milzow, C., Bauer-Gottwein, P., 2013. Assimilation of radar altimetry to a routing model of the Brahmaputra River. Water Resour. Res. 49(8), 4807-4816. https://doi.org/10.1002/wrcr.20345.
    Nielsen, K., Stenseng, L., Andersen, O.B., Villadsen, H., Knudsen, P., 2015. Validation of CryoSat-2 SAR mode based lake levels. Rem. Sens. Environ. 171, 162-170. https://doi.org/10.1016/j.rse.2015.10.023.
    Pandey, R.K., Cr etaux, J.F., Berg e-Nguyen, M., Tiwari, M.V., Drolon, V., Papa, F., Calmant, S., 2014. Water level estimation by remote sensing for 2008 Flooding of the Kosi River. Int. J. Rem. Sens. 35(2), 424-440. https://doi.org/10.1080/01431161.2013.870678.
    Papa, F., Prigent, C., Durand, F., Rossow, W.B., 2006. Wetland dynamics using a suite of satellite observations:A case study of application and evaluation for the Indian subcontinent. Geophys. Res. Lett. 33(8), L08401. https://doi.org/10.1029/2006GL025767.
    Papa, F., Prigent, C., Aires, F., Jimenez, C., Rossow, W.B., Matthews, E., 2010. Interannual variability of surface water extent at the global scale, 1993-2004. Journal of Geophysical Research Atmospheres 115, D12111. https://doi.org/10.1029/2009JD012674.
    Paris, A., Dias de Paiva, R., Santos da Silva, J., Medeiros, M.D., Calmant, S., Garambois, P.A., Collischonn, W., Bonnet, M.P., Seyler, F., 2016. Stagedischarge rating curves based on satellite altimetry and modeled discharge in the Amazon basin. Water Resour. Res. 52(5), 3787-3814. https://doi.org/10.1002/2014WR016618.
    Rodriguez, E., Callahan, P.S., 2016. Surface Water and Ocean Topography Mission (SWOT) Project:Science Requirements Document. SWOT NASA/JPL Lab, Pasadena.
    Roohi, S., Sneeuw, N., Benveniste, J., Dinardo, S., Issawy, E.A., Zhang, G., 2019. Evaluation of CryoSat-2 water level derived from different retracking scenarios over selected inland water bodies. Adv. Space Res. 68(2), 947-962. https://doi.org/10.1016/j.asr.2019.06.024.
    Schwatke, C., Dettmering, D., Bosch, W., Seitz, F., 2015. DAHITI:An innovative approach for estimating water level time series over inland waters using multi-mission satellite altimetry. Hydrol. Earth Syst. Sci. 19(10), 4345-4364. https://doi.org/10.5194/hess-19-4345-2015.
    Seyler, F., Calmant, S., Santos da Silva, J., Filizola, N., Roux, E., Cochonneau, G., Vauchel, P., Bonnet, M.P., 2008. Monitoring water level in large trans-boundary ungauged basins with altimetry:The example of ENVISAT over the Amazon basin. J. Appl. Remote Sens. 7150, 715017. https://doi.org/10.1117/12.813258.
    Shamsudduha, M., Chandler, R.E., Taylor, R.G., Ahmed, K.M., 2009. Recent trends in groundwater levels in a highly seasonal hydrological system:The Ganges-Brahmaputra-Meghna Delta. Hydrol. Earth Syst. Sci. 13(12), 2373-2385. https://doi.org/10.5194/hess-13-2373-2009.
    Shu, S., Liu, H., Beck, R.A., Frappart, F., Korhonen, J., Xu, M., Yang, B., Hinkel, K.M., Huang, Y., Yu, B., 2020. Analysis of Sentinel-3 SAR altimetry waveform retracking algorithms for deriving temporally consistent water levels over ice-covered lakes. Rem. Sens. Environ. 239, 111643. https://doi.org/10.1016/j.rse.2020.111643.
    Silva, J., Calmant, S., Rotuono, O.C.F., Seyler, F., Cochonneau, G., Roux, E., Mansour, J.W., 2010. Water levels in the Amazon basin derived from the ERS-2 and ENVISAT radar altimetry missions. Rem. Sens. Environ. 114(10), 2160-2181. https://doi.org/10.1016/j.rse.2010.04.020.
    Silva, J., Seyler, F., Calmant, S., Rotunno, O.C.F., Cochonneau, G., Mansur, J.W., 2012. Water level dynamics of Amazon wetlands at the watershed scale by satellite altimetry. Int. J. Rem. Sens. 33(11), 3323-3353. https://doi.org/10.1080/01431161.2010.531914.
    Tarpanelli, A., Barbetta, S., Brocca, L., Moramarco, T., 2013. River discharge estimation by using altimetry data and simplified flood routing modeling. Rem. Sens. 5(9), 4145-4162. https://doi.org/10.3390/rs5094145.
    Tarpanelli, A., Camici, S., Nielsen, K., Brocca, L., Moramarco, T., Benveniste, J., 2019. Potentials and limitations of Sentinel-3 for river discharge assessment. Adv. Space Res. 68(2), 593-606. https://doi.org/10.1016/j.asr.2019.08.005.
    UNESCO, 2019. The United Nations World Water Development Report 2019:Leaving No One behind. United Nations Educational, Scientific and Cultural Organization, Paris.
    Verron, J., Bonnefond, P., Aouf, L., Birol, F., Bhowmick, S.A., Calmant, S., Conchy, T., Crétaux, J.F., Dibarboure, G., Dubey, A.K., et al., 2018. The benefits of the Ka-band as evidenced from the SARAL/AltiKa altimetric mission:Scientific applications. Rem. Sens. 10(2), 163. https://doi.org/10.3390/rs10020163.
    Wallemacq, P., Guha-Sapir, D., McClean, D., 2015. The Human Cost of Weather-Related Disasters, 1995-2015. The United Nations Office for Disaster Risk Reduction (UNISDR). https://doi.org/10.13140/RG.2.2.17677.33769.
    Zhang, M., Li, M., Wang, W., Liu, C., Gao, H., 2013. Temporal and spatial variability of soil moisture based on WSN. Math. Comput. Model. 58(3-4), 826-833. https://doi.org/10.1016/j.mcm.2012.12.019.
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Figures(1)

    Article Metrics

    Article views (216) PDF downloads(0) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return