Journal of Hydrology

This data article is a presentation of data related to the research article entitled “Ground Observation-based Analysis of Soil Moisture Spatiotemporal Variability Across A Humid to Semi-Humid Transitional Zone in China”. The original soil moisture data are from the observations of the soil moisture-observing network in Anhui Province. The relative dielectric constant of the soil is measured by the DZN2 (GStar-I) automatic soil moisture sensors and then is converted to volumetric soil water content. The Kriging interpolation method is used to interpolate the site data into gridded data. Analysis of soil moisture spatiotemporal variability are used to understand the dataset.

The data of pore pressures, acceleration and water level in every scenario (total 24 scenarios), collected by the pore pressure, acceleration and water level sensors. They will be used to analyze the variation of pore pressures, acceleration and water level in different shaking conditions. Data Set S1-S24. The data of pore pressures in Scenario 1-24, collected by the pore pressure sensors in settings. It includes 9 pore pressure points, P1-P9 in order(see the position in figure 1). The first and second column is DATE and TIME, from the third to eleventh columns are the PORE PRESSURE data. Note that the collection frequency is 256Hz, so there are 256 numbers in 1 second. Data Set S25-48. The data of acceleration in Scenario 1-24, collected by the acceleration sensors in settings. It includes 5 acceleration points, A1-A5 in order(see the position in figure 1). The first and second column is DATE and TIME, from the third to seventh columns are the ACCELERATION data. Note that the collection frequency is 256Hz, so there are 256 numbers in 1 second. Data Set S49-72. The data of water level in Scenario 1-24, collected by the three water level sensors in settings. It has 3 columns of water level, No.1-No.3 in order(see the position in figure 1). The first and second column is DATE and TIME, from the third to fifth columns are the WATER LEVEL data. Note that the collection frequency is 1Hz, so there is 1number in 1 second undercollection.

Dataset including radium isotopes and nutrients for the estimation of SGD in the Sydney Harbour, Australia

The basic data and process data, including the flow data, reservoir characteristic curve, flood disaster of Guilin city, accumulater areal rainfall of each flood, and so on.

Discharge and concentration data along the Arc and Isère river system for the six studied dam flushing events

Geochemistry and isotope data for IES Spring Mountain Springs. Rock leaching data for Spring Mountains rocks.

Ethiopia precipitation water isotope data.

Water Quality datsa of the MApocho Upper Basin (Chile)

Geochemical data including major ions, stable isotopes, 14C and 3H from groundwater and surface water samples from floodplains on the River Murray, South Australia

Noble gas data and calculations