On the Application of Probabilistic Hydrometeorological Simulation of Soil Moisture across Different Stations in India

Abstract

An application of a proposed hydrometeorological approach for probabilistic simulation of soil moisture is carried out. The time series of in-situ soil moisture and meteorological variables at monthly scale from a few monitoring stations having different soil-hydrologic properties across India are utilized. Preliminary investigation with both precipitation and near-surface air-temperature as meteorological variables to establish that the strength of association between soil moisture and precipitation is more significant as compared to that between soil moisture and temperature. Precipitation-based probabilistic estimation of soil moisture using the proposed hydrometeorological approach is tested with in-situ observed soil moisture, CPC model output and with soil moisture data of the Climate Change Initiative (CCI) project. The parameter of the developed model is linked to the soil-hydrologic characteristics through Hydrologic Soil Group (HSG) classification. Higher values of model parameter (dependence parameter (θ) for the selected copula) correspond to HSG A and B having higher soil porosity, whereas, lower values correspond to HSG B and C having lower soil porosity.

Spatial and temporal variability of soil moisture in non-flooded landscape units in Namibian Zambezi region

“…Soil moisture distribution on a landscape varies by spatial differences due to evapotranspiration and rainfall as influenced by topography, soil type, soil texture, vegetation type, condition of the land and management (Gaur and Mohanty, 2013;Das and Maity, 2014). As a matter of fact, small-scale spatial variations are readily influenced by soil texture; while larger scales are influenced by precipitation and evaporation.…”