Spatio-temporal variability and interaction between soil moisture and temperature in the Critical Zone Observatory in the Central Ganga Basin, North India

Both soil moisture (SM) and soil temperature (ST) facilitate the interaction between the atmosphere and the surface of the earth thereby influencing the global hydrological cycle. Additionally, they are the primary determinants of agricultural development and growth. In addition to being crucial in understanding how moisture and temperature interact, the spatiotemporal variability of soil temperature and moisture also provides scientific insights for agricultural productivity. The link between soil moisture content and temperature is still poorly known since it is challenging to quantify both variables accurately. This work has investigated the variability and relationship between soil moisture and temperature under different vegetation covers in a highly managed agro-rural critical zone observatory (CZO) in the central Ganga Basin. The catchment of the CZO is a 21 km2 watershed that has elevation ranging between 126 and 143 meters above MSL. The study area has a sub-humid climate, with high temperatures of 42⁰C and lows of 8.6⁰C. The average annual rainfall is 821.9 mm, and most of it falls from June to September. The measurements of the soil parameters were performed by two sets of dense networks of moisture-temperature sensors, installed in agricultural plots at a depth ranging from 0-80 cm with a measurement frequency of 10 minutes. These date sets were complemented by precipitation and air temperature measurements at two automatic weather station (AWS) located at the extreme ends of the watershed. The crop types together with irrigation patterns and estimated vegetation cover status from Sentinel-2 multispectral data were also used to synthesize the results. Spatial variability between surface and deeper SM at both study locations demonstrate the influence of soil texture and surface runoff, while in-situ precipitation, vegetation cover, and field water management are important factors of temporal SM variation. Correlations between observed time series of SM and ST demonstrate a strong association with sparse or missing vegetation cover but controlled agricultural and irrigation techniques weaken this relationship in daily time delay. The study indicated significant hydrometeorological variability within a closely monitored CZO, influenced by natural and anthropogenic factors.