With remote sensing we can readily observe the Earth’s surface, but direct observation of the sub-surface remains a challenge. In hydrology, but also in related disciplines such as agricultural and atmospheric sciences, knowledge of the dynamics of soil moisture in the root zone of vegetation is essential, as this part of the vadose zone is the core component controlling the partitioning of water into evaporative fluxes, drainage, recharge, and runoff. In this paper, we compared the catchment-scale soil moisture content in the root zone of vegetation, computed by a lumped conceptual model, with the remotely sensed Normalized Difference Infrared Index (NDII) in the Upper Ping River basin (UPRB) in northern Thailand. The NDII is widely used to monitor the equivalent water thickness (EWT) of leaves and canopy. Satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to determine the NDII over an 8-day period, covering the study area from 2001 to 2013. The results show that NDII values decrease sharply at the end of the wet season in October and reach lowest values near the end of the dry season in March. The values then increase abruptly after rains have started, but vary in an insignificant manner from the middle to the late rainy season. This paper investigates if the NDII can be used as a proxy for moisture deficit and hence for the amount of moisture stored in the root zone of vegetation, which is a crucial component of hydrological models. During periods of moisture stress, the 8-day average NDII values were found to correlate well with the 8-day average soil moisture content (Su) simulated by the lumped conceptual hydrological rainfall–runoff model FLEX for eight sub-catchments in the Upper Ping basin. Even the deseasonalized Su and NDII (after subtracting the dominant seasonal signal) showed good correlation during periods of moisture stress. The results illustrate the potential of the NDII as a proxy for catchmentscale root zone moisture deficit and as a potentially valuable constraint for the internal dynamics of hydrological models. In dry periods, when plants are exposed to water stress, the EWT (reflecting leaf water deficit) decreases steadily, as moisture stress in the leaves is connected to moisture deficits in the root zone. Subsequently, when the soil moisture is replenished as a result of rainfall, the EWT increases without delay. Once leaf water is close to saturation – mostly during the heart of the wet season – leaf characteristics and NDII values are not well correlated. However, for both hydrological modelling and water management, the stress periods are most important, which is why this product has the potential of becoming a highly efficient model constraint, particularly in ungauged basins.