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We present a preliminary study on using the Surface Water and Ocean Topography (SWOT) mission to extend water surface elevation (WSE) measurements from a sparsely distributed in situ gauge network along a one-dimensional (1D) study reach within the Mahanadi River basin in India. We use the Centre National d’Etudes Spatiales (CNES) simulator to simulate 3 years of synthetic measurements of SWOT WSE, which are assimilated into a 1D stochastic model based on six independent configurations. For each configuration, the model is derived using historical measurements of in situ WSE to simulate daily WSE estimates every 200 m along the study reach. Assimilated outputs showed high Nash-Sutcliffe efficiency (0.697–0.811), high correlation (0.838–0.901) and low root mean square error (0.242–0.513 m) with respect to in situ validation data. Results indicate consistent performance of the SWOT-assimilated model framework and are relevant considering the declining availability of in situ monitoring stations. [ABSTRACT FROM AUTHOR]

The Surface Water and Ocean Topographic (SWOT) mission is aimed to improve flood mapping by providing high-resolution data of water surface elevation, slope and water extent for rivers wider than 100 m and water bodies as small as 62500 m². Although, SWOT's data latency and huge data size of rawest point cloud data make it impracticable for real or near-real-time flood forecasting but the SWOT data will provide new insight in the first-hand information of flood mapping. In this study, we explore the potential of SWOT mission for flood mapping over India. It is observed that the spatio-temporal resolution of SWOT allows the observation of 0.67%, 15.79%, 29.24%, 45.54%, and 8.06% of Indian districts with one, two, three, four and more than four observations per cycle of SWOT respectively. It is observed that SWOT would have observed 49.6% of flood events at least once if the mission were launched earlier. The SWOT could also observe 30.6% of small flood events with flood duration <4 at least once. Using the information, this study proposes a flood severity map by combining geomorphological and physical flood parameters for a reach of Brahmaputra river. From the map different flood severity zones can be observed. [ABSTRACT FROM AUTHOR]

Data assimilation (DA) offers immense potential for uncertainty identification, improving the initial estimates for hydrological and atmospheric modelling. This paper reviews the studies in hydrological DA using Kalman filters. Recent applications of Kalman filters in hydrological and atmospheric DA are summarized. Existing challenges for DA studies are briefly described. In addition, three case study examples are presented highlighting the effects of: (a) soil moisture DA in the Noah land surface model; (b) variational assimilation for improving precipitation forecasts in the WRF (Weather Research Forecast) model; and (c) simulating AMSR-2 (Advanced Microwave Scanning Radiometer-2) radiances towards DA. Although there are many unresolved issues in DA that warrant further research, it has immense potential for predicting variables at a better lead time for hydrometeorology. [ABSTRACT FROM AUTHOR]

L-band microwave radiometry is one of the globally accepted techniques to estimate surface soil moisture by measuring upwelling brightness temperature (TB) from the surface. L-band radiometers have been historically used for ground truth validation of space-borne missions. Existing devices are distinguished by using huge and bulky antennas to conduct precise multi-angular measurements at the cost of portability. The current work demonstrates that a portable ground-based L-band microwave radiometer can be used to measure high-resolution TB, soil temperature and emissivity in a case study area in India as an alternative to a traditional huge ground-based radiometer. To show the influence of surface soil moisture (SM) on TB, a controlled experiment was conducted to investigate the temporal variation of TB over a bare soil surface. Spatial analysis of the measured data shows that the compact radiometer can efficiently capture the linear relationship between emissivity and TB, while temporal analysis of TB over a small area shows the variation in TB dynamics with SM. [ABSTRACT FROM AUTHOR]

Groundwater (GW) storage plays a critical role in the sustainable development of the water-energy-food nexus of a country. Intensive exploitation of GW for irrigation has led to severe water deficit in many parts of India. Severe droughts (meteorological drought) further increases the rate of GW depletion. In the last decade, India witnessed severe droughts during 2002, 2009, and 2012. However, the critical change in the rate of GW depletion in India after frequent severe droughts remains unidentified. Here, we have devised a methodology to detect the point of maximum fluctuation in Gravity Recovery and Climate Experiment (GRACE) based GW time series using change point analysis. The occurrence of 2009 severe drought has significantly affected the GW balance over the majority of India. Our study indicates the transition in the GW trend observed in South India from positive to negative post-2009 drought. In the southern states, Karnataka indicates a maximum GW depletion rate of 0.25 cm per month for a time period from 2009 to 2016. [ABSTRACT FROM AUTHOR]

A regionalized rain/no-rain classification (RNC) based on scattering index methodology is developed for detecting rainfall signatures over the land regions of the Mahanadi basin (India), using data products from the passive and active sensors onboard the Tropical Rainfall Measuring Mission (TRMM), namely the TRMM Microwave Imager (TMI) and Precipitation Radar (PR). The proposed model, developed using data for two years from the orbital database, was validated using PR andin-situdata for selected case study events in 2011 and 2012. Performance evaluation of the model is discussed using 10 metrics derived from the contingency table. Overall, the results show superior performance, with an average probability of detection of 0.83, bias of 1.10 and odds ratio skill score greater than 0.93. Accurate rainfall detection is obtained for 95% of case study events. The relative performance of the proposed model is dependent on rainfall type, but it should be useful in rainfall retrieval algorithms for current missions such as the Global Precipitation Measurement Mission.Editor M.C. Acreman; Associate editor Y. Gyasi-Agyei [ABSTRACT FROM PUBLISHER]