In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements (∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76 % of the experimental sites with agricultural land use as the dominant type (∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it.

In West Sumatra, Indonesia, a high-yield perennial rice cropping method called SALIBU was recently reported, in which the most unique feature is double cutting (DC) at harvest and after harvest. The objective of this study was to verify the ratooning rice yield under the SALIBU system in Myanmar. Two cultivation trials consisting of two cutting and three moisture treatments were conducted in 2019 and 2020. We concluded that double cutting had no positive effect on grain yield and regeneration rate compared with single cutting (SC). For the cutting regime, significant results were detected in the ratoon crops on yield components, but all of these were negative effects of DC, and were statistically lower than those of SC. On the other hand, a significant positive effect of moisture regime on grain yield in all ratoons was observed. The grain yield of the dry regime was significantly increased by 69% compared with that of the saturated regime. Soil oxidation conditions during the initial growth period of ratoons could contribute to the improved yield performance of the ratoons.

Actual crop evapotranspiration (ET) and crop coefficient (Kc) of ratoon rice crop, which are necessary for irrigation planning, have been hardly reported. ET can be directly measured by lysimeter and eddy covariance but it is expensive, so it remains difficult to determine ET, especially in developing countries. The focus of this study was to evaluate the ET and Kc of ratoon cropping in a tropical region of Myanmar using a simplified method. Our method combined the manual observation of water depth in concrete paddy tanks and the ET model estimation using Bayesian parameter inference. The ET and Kc could be determined using this method with an incomplete observation dataset. The total ET of ratoon was 60–70% less than that of the main crop, but this difference was mainly attributed to climate conditions in each cultivation. The Kc regression curve between transplanted rice and ratoon crops was different because of the tillering traits. The results suggest that irrigation scheduling of ratoon cropping in the initial growth stage should take high crop water requirements into account. In addition, the productivity of ratoon crop is equivalent to transplanted rice, which was determined for cultivation in experiment conditions of small concrete tanks. Therefore, further study on ratoon in Myanmar is necessary for clarifying the viability of ratoon cropping.

The two-layer Shuttleworth–Wallace (SW) evapotranspiration (ET) model has been widely used for predicting ET with good results. Since the SW model has a large number of specific parameters, these parameters have been estimated using a simple non-hierarchical Bayesian (SB) approach. To further improve the performance of the SW model, we aimed to assess parameter estimation using a two-level hierarchical Bayesian (HB) approach that takes into account the variation in observed conditions through the comparison with a traditional one-layer Penman–Monteith (PM) model. The difference between the SB and HB approaches were evaluated using a field-based ET dataset collected from five agricultural fields over three seasons in Myanmar. For a calibration period with large variation in environmental factors, the models with parameters calibrated by the HB approach showed better fitting to observed ET than that with parameters estimated using the SB approach, indicating the potential importance of accounting for seasonal fluctuations and variation in crop growth stages. The validation of parameter estimation showed that the ET estimation of the SW model with calibrated parameters was superior to that of the PM model, and the SW model provided acceptable estimations of ET, with little difference between the SB and HB approaches.