The Normalized Difference Infrared Index (NDII) as a proxy for soil moisture storage in hydrological modelling
Abstract. With remote sensing we can readily observe the Earth's surface, but looking under the surface into the root zone of vegetation is still a major challenge. Yet knowledge on the dynamics of soil moisture in the root zone is essential for agriculture, land–atmosphere interaction and hydrological modelling, alike. In this paper we develop a novel approach to monitor the soil moisture storage deficit in the root zone of vegetation, by using the remotely sensed Normalised Difference Infrared Index (NDII) in the Upper Ping River Basin (UPRB) in northern Thailand. Satellite data from the Moderate Resolution Imaging Spectro-radiometer (MODIS) was used to evaluate 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. The NDII proves to be a very strong proxy for moisture storage deficit in the root zone, which is a crucial component of hydrological models. In addition, the NDII appears to be a reliable indicator for the temporal and spatial distribution of drought conditions in the UPRB. The 8 day average NDII values were found to correlate very well with the 8 day average soil moisture content (SU) simulated by FLEXL (rainfall–runoff model) at 8 runoff stations during the dry season – giving an average R2 value 0.87 on an exponential relationship, while for the wet season it reduced to be around 0.61. Apparently, the NDII is an effective index for the moisture storage in the root zone during the time of moisture deficit, and a powerful indicator to assess droughts. In the dry season, when plants are exposed to water stress, the leaf-water deficit increases steadily. Once leaf-water is close to saturation – mostly at the end of the wet season – leaf characteristics and NDII values do not vary significantly, causing lower correlation between NDII and Su in the wet season. However, the correlations between NDII and Su still remain high for both seasons and therefore the product can be used to define drought situations throughout the year and be of use to water management.