Space-time dynamics of soil moisture and groundwater in an agriculture-dominated critical zone observatory (CZO) in the Ganga basin, India.

Space-time variability of soil moisture (SM) and ground water plays a fundamental role in shaping hydrology of terrestrial ecosystem, best represented as the Critical Zone (CZ), which extends from top of vegetation canopy to the bottom of groundwater table. In several parts of the world, a network of instrumented sites, known as Critical Zone Observatories (CZOs), have been set up to understand the hydrodynamics of soil-water system in particular reference to natural and anthropogenic forcings. Here, we employed the empirical orthogonal function (EOF), random combination, and temporal stability approach to understand the in-situ space-time dynamics of SM and depth to groundwater table (DTGT) over an agriculture-dominated CZO in the Ganga basin. Our results showed that both the components exhibit a constant temporal coefficient of variation, suggesting a consistent seasonal changing pattern. Around 91 % of the observed DTGT spatial variation are explained by first two spatial EOFs while the first five EOFs explain only 67 % of the total SM variability. On an annual basis, the spatial patterns of SM and DTGT are driven by topography and soil texture (% clay) while monsoon rainfall and post-monsoon crop cycle appear to be the leading factors for temporal variability of both components. Furthermore, we have demonstrated that randomly selected four sampling locations and three monitoring wells within the CZO could capture the mean spatial variability of SM (RMSE = 3 % vol/vol) and DTGT (RMSE = 0.7 mgbl) respectively. In addition, temporal stability analysis indicates that four representative sites and a single monitoring well can provide robust catchment mean with an absolute error of ±2 % vol/vol and 0.36 mgbl respectively. Overall, this study provides an insight to the hydrodynamics and controls of SM and groundwater in an agricultural landscape with significant implications for upscaling and efficient water resource management in such regions.