Enhancing the Stability of Hydrological Modelling through Multivariable Calibration Schemes Using the Satellite-Based Soil Moisture and Evapotranspiration

Water Resources Management, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 1, 2025

Language: Английский

Water Balance Analysis in the Majalaya Watershed: Two-Step Calibration and Application of the SWAT+ Model for Low-Flow Conditions

Water, Journal Year: 2024, Volume and Issue: 16(23), P. 3498 - 3498

Published: Dec. 5, 2024

Understanding hydrological processes is crucial for effective watershed management, with SWAT+ being one of the widely adopted models analyzing water balance at scales. While components are often assessed through sensitivity analysis, calibration, and validation, parameter during dry periods (low-flow conditions) when baseflow predominant remains a relevant focus, especially watersheds like Majalaya, Indonesia, which experience distinct low-flow periods. This study analyzes in Majalaya watershed, using across 2014–2022 period, focusing on conditions. employs two-step calibration approach various datasets, including ground rainfall (2014–2022), NASA POWER meteorological data, MODIS land cover, DEMNAS terrain, DSMW soil types, streamflow data model calibration. The first step optimized overall performance (R2 = 0.41, NSE PBIAS −7.33), second improved simulation 0.40, 0.35, 12.45). A Sobol analysis identified six primary parameters, i.e., CN3_SWF, CN2, LATQ_CO, PERCO, SURLAG, CANMX, as most influential CN3_SWF CN2 critical. demonstrates SWAT+’s effectiveness management resource optimization, particularly

Language: Английский

Prediction of Soil Temperature in Wheat Field Using Machine Learning Models

Communications in Soil Science and Plant Analysis, Journal Year: 2024, Volume and Issue: unknown, P. 1 - 25

Published: Sept. 16, 2024

Language: Английский