We used remote sensing data, field observations and numerical groundwater modelling to investigate long-term storage losses in the regional aquifer of Ganga Basin India. This comprised trend analysis for level from 2851 monitoring bores, anomaly estimation using GRACE Global Land Data Assimilation System (GLDAS) data sets changes underpinned by over 50,000 uncertainty analysis. Three analyses based on different methods consistently informed that is declining at a significant rate....

Error characterization is vital for the advancement of precipitation algorithms, evaluation numerical model outputs, and their integration in various hydro-meteorological applications. The Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) has been a benchmark successive Global Measurement (GPM) based products. This given way to evolution many multi-satellite study evaluates performance newly released Multi-Source Weighted-Ensemble (MSWEP) product, whose...

Groundwater level (GWL) monitoring datasets are essential for effective groundwater resource management and understanding the potential impacts of climate change. However, these frequently contain gaps irregular measurement intervals, posing challenges time series analyses that depend on consistent sampling. As a result, GWL with substantial excluded from further analysis, leading to loss temporal spatial coverage, regional representativity, potentially valuable insights. Addressing this...

In the present study, soil moisture assimilation is conducted over Indian subcontinent, using Noah Land Surface Model (LSM) and Soil Moisture Operational Products System (SMOPS) observations by utilizing Ensemble Kalman Filter. The study in two stages involving of simulation brightness temperature (Tb) radiative transfer scheme. results data form simulated (SSM) maps are evaluated for summer monsoonal months June, July, August, September (JJAS) Parameter Retrieval (LPRM) AMSR-E as reference....

The transfer of water and energy fluxes between the ground atmosphere is influenced by soil moisture (SM), which an important factor in land surface dynamics. Accurate representation SM over permafrost-affected regions remains challenging. Leveraging blended from microwave satellites, this study examines potential for satellite assimilation to enhance LSM (Land Surface Model) seasonal Ensemble Kalman Filter (EnKF) used integrate data across Iya River Basin, Russia. Considering permafrost,...

Abstract The alarming decline in groundwater (GW) storage threatens the sustainable development of water‐energy‐food linkages a country. India has experienced severe dry spells during years 2002, 2004, 2009, and 2012. However, relative contribution factors affecting GW depletion (such as variability precipitation rate extraction) still remains unknown. Here, we first evaluate current condition by implementing reliability, resilience, vulnerability analysis on 5,988 monitoring well...

Data assimilation (DA) offers immense potential for uncertainty identification, improving the initial estimates hydrological and atmospheric modelling. This paper reviews studies in DA using Kalman filters. Recent applications of filters are summarized. Existing challenges briefly described. In addition, three case study examples presented highlighting effects of: (a) soil moisture Noah land surface model; (b) variational precipitation forecasts WRF (Weather Research Forecast) (c) simulating...

Groundwater (GW) storage plays a critical role in the sustainable development of water-energy-food nexus country. Intensive exploitation GW for irrigation has led to severe water deficit many parts India. Severe droughts (meteorological drought) further increases rate depletion. In last decade, India witnessed during 2002, 2009, and 2012. However, change depletion after frequent remains unidentified. Here, we have devised methodology detect point maximum fluctuation Gravity Recovery Climate...

Abstract. This study emphasises the importance of soil moisture (SM) in subseasonal-to-seasonal (S2S) predictions at midlatitudes. To address this we introduce Norwegian Climate Prediction Model Land (NorCPM-Land), a land reanalysis framework tailored for integration with (NorCPM). NorCPM-Land assimilates blended SM data from European Space Agency’s Change Initiative into 30-member offline simulation Community fluxes coupled model. The assimilation reduces error by 10.5 % when validated...

Lakes are an essential component of biogeochemical processes, and variations in lake level regarded as indicators climate change. For more than a decade, satellite altimetry has successfully monitored variation water levels over inland seas, lakes, rivers, wetlands. Through altimetry, the surface measured at varying temporal scales depending on orbit cycle satellite. The futuristic mission Surface Water Ocean Topography (SWOT) scheduled to be launched year 2022 shall offer spatial coverage...

Abstract This study shows the importance of soil moisture (SM) in subseasonal-to-seasonal (S2S) predictions at mid-latitudes. We do this through introducing Norwegian Climate Prediction Model Land (NorCPM-Land), a land reanalysis framework tailored for integration with (NorCPM). NorCPM-Land assimilates blended SM data from European Space Agency’s Change Initiative into 30-member offline simulation Community fluxes coupled model. The assimilation reduces error by 10.5 % when validated against...

This letter presents a new approach to incorporate topographic relief effect in land data assimilation system over mountainous terrain. The conventional radiative transfer model (RTM) used for of microwave brightness temperature (Tb) is subjected systematic bias owing its flat earth assumption. theoretically important direct Tb since difference between simulated and observed may disarray the system. Here, we consider three crucial effects, namely: 1) change local incidence angle; 2) rotation...

Satellite radar altimetry has immense potential for monitoring fresh surface water resources and predicting the intra-seasonal, seasonal, inter-annual variability of inundated over large river basins. As part Preparation Surface Water Ocean Topography mission scheduled launch in mid-2022, present study aimed to evaluate performance inland bodies India. The Joint Altimetry Oceanography Network (Jason) with ARgos ALtiKa (SARAL/AltiKa) data were used derive levels 18 major reservoirs India by...

Abstract. Groundwater is utilized intensively as a source of fresh water for irrigation and human needs. Hence, it necessary to monitor groundwater storage security the region in future. The present study aims evaluate resource over Krishna basin South India. comprises 210 major medium projects, which makes important balance sustainable draft. This evaluates trend anomaly derived from GRACE mascon product. Results indicate that subjected strong decline at rate 0.34 cm per year. Further,...

Brightness temperature (Tb) is sensitive to soil moisture (SM) estimates and has the advantage of increasing spatial coverage SM measurements. This letter focuses on simulation Tb from land surface variables generated by Noah with multiparameterized (Noah-MP) a forward observation operator, community microwave emission model (CMEM) over Indian subcontinent resolution 0.25 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">°</sup> ×0.25 ....

L-band microwave radiometers (1.4 GHz) are relied in the field of remote sensing to retrieve and analyze land surface characteristics. However, existing ground based not portable requires heavy maintenance. This paper focuses on introducing a new terrestrial hand held radiometer measure passive data over bare surface. Soil temperature, brightness temperature (TB), emissivity soil moisture is measured relationships between values evaluated for present study.