High-Frequency Water Isotopic Analysis Using an Automatic Water Sampling System in Rice-Based Cropping Systems

Abstract

High-resolution data on a field scale is very important for improving our understanding of hydrological processes. This is particularly the case for water-demanding agricultural production systems such as rice paddies, for which water-saving strategies need to be developed. Here we report on the application of an in situ, automatic sampling system for high-resolution data on stable isotopes of water (18O and 2H). We investigate multiple rice-based cropping systems consisting of wet rice, dry rice and maize, with a single, but distributed analytical system on a sub-hourly basis. Results show that under dry conditions, there is a clear and distinguishable crop effect on isotopic composition in groundwater. The least evaporative affected groundwater source is that of maize, followed by both rice varieties. Groundwater is primarily a mixture of irrigation and rainwater, where the main driver is irrigation water during the dry season and rainwater during the wet season. Stable isotopes of groundwater under dry season maize react rapidly on irrigation, indicating preferential flow processes via cracks and deep roots. The groundwater during the dry season under wet and dry rice fields is dominated at the beginning of the growing season mainly by the input of rainwater; later, the groundwater is more and more replenished by irrigation water. Overall, based on our data, we estimate significantly higher evaporation (63â 77%) during the dry season as compared to the wet season (27â 36%). We also find, for the first time, significant sub-daily isotopic variation in groundwater and surface ponded water, with an isotopic enrichment during the daytime. High correlations with relative humidity and temperature, explain part of this variability. Furthermore, the day-night isotopic difference in surface water is driven by the temperature and relative humidity; however, in groundwater, it is neither driven by these factors.