Characterizing uncertainty in process-based hydraulic modeling, exemplified in a semiarid Inner Mongolia steppe

Assessing root sources of three uncertainties – parameterization of soil hydraulic characteristics, boundary conditions, and estimation of source/sink terms – is a significant challenge in soil water transport modeling. This study aims to evaluate the uncertainty of three each widely-used parameter estimation methods affecting plot-scale water dynamics. The study employs HYDRUS, a process-based hydrologic model, to incorporate these uncertainties and compare model predictions to measured values in a semiarid Inner Mongolia steppe, China. Soil hydraulic parameters are determined using two direct methods (laboratory-derived approach and evaporation method) and one indirect method (neural network). While each hydraulic parameter method generally simulates soil moisture dynamics, the evaporation method performed better, especially under dry conditions. This suggests that measuring the intensity properties, such as unsaturated hydraulic conductivity, with the evaporation method is crucial for reasonable soil moisture simulation. The study also demonstrates the impact of different applied boundary conditions on simulated soil moisture, specifically the partitioning of reference FAO evapotranspiration via one direct method (soil fraction cover) and two indirect methods (leaf area index and crop height). The partitioning via soil fraction cover reflected a better simulation. Additionally, the study compares the uncertainties of root water uptake function with root growth parameters and constant root depth referenced to grass and pasture, and finds no significant difference among them. Comparing three sources of uncertainty in predicting soil moisture, the study concludes that the input soil hydraulic parameter is more sensitive than evapotranspiration partitioning or representation of root water uptake function. Our study highlights that measuring soil intensity properties can better reflect the effects of land use change, such as compaction, on field water transports

Measurement of the vertical atmospheric density profile from the X-ray Earth occultation of the Crab Nebula with Insight-HXMT

In this paper, the X-ray Earth occultation (XEO) of the Crab Nebula is investigated by using the Hard X-ray Modulation Telescope (Insight-HXMT). The pointing observation data on the 30th September, 2018 recorded by the Low Energy X-ray telescope (LE) of Insight-HXMT are selected and analyzed. The extinction lightcurves and spectra during the X-ray Earth occultation process are extracted. A forward model for the XEO lightcurve is established and the theoretical observational signal for lightcurve is predicted. The atmospheric density model is built with a scale factor to the commonly used MSIS density profile within a certain altitude range. A Bayesian data analysis method is developed for the XEO lightcurve modeling and the atmospheric density retrieval. The posterior probability distribution of the model parameters is derived through the Markov Chain Monte Carlo (MCMC) algorithm with the NRLMSISE-00 model and the NRLMSIS 2.0 model as basis functions and the best-fit density profiles are retrieved respectively. It is found that in the altitude range of 105--200 km, the retrieved density profile is 88.8% of the density of NRLMSISE-00 and 109.7% of the density of NRLMSIS 2.0 by fitting the lightcurve in the energy range of 1.0--2.5 keV based on XEOS method. In the altitude range of 95--125 km, the retrieved density profile is 81.0% of the density of NRLMSISE-00 and 92.3% of the density of NRLMSIS 2.0 by fitting the lightcurve in the energy range of 2.5--6.0 keV based on XEOS method. In the altitude range of 85--110 km, the retrieved density profile is 87.7% of the density of NRLMSISE-00 and 101.4% of the density of NRLMSIS 2.0 by fitting the lightcurve in the energy range of 6.0--10.0 keV based on XEOS method. This study demonstrates that the XEOS from the X-ray astronomical satellite Insight-HXMT can provide an approach for the study of the upper atmosphere.Comment: 31 pages, 15 figures, 5 tables, accepted for publication in Atmospheric Measurement Technique

Insight-HXMT dedicated 33-day observation of SGR J1935+2154 I. Burst Catalog

Magnetars are neutron stars with extreme magnetic field and sometimes manifest as soft gamma-ray repeaters (SGRs). SGR J1935+2154 is one of the most prolific bursters and the first confirmed source of fast radio burst (i.e. FRB 200428). Encouraged by the discovery of the first X-ray counterpart of FRB, Insight-Hard X-ray Modulation Telescope (Insight-HXMT) implemented a dedicated 33-day long ToO observation of SGR J1935+2154 since April 28, 2020. With the HE, ME, and LE telescopes, Insight-HXMT provides a thorough monitoring of burst activity evolution of SGR J1935+2154, in a very broad energy range (1-250 keV) with high temporal resolution and high sensitivity, resulting in a unique valuable data set for detailed studies of SGR J1935+2154. In this work, we conduct a comprehensive analysis of this observation including detailed burst search, identification and temporal analyses. After carefully removing false triggers, we find a total of 75 bursts from SGR J1935+2154, out of which 70 are single-pulsed. The maximum burst rate is about 56 bursts/day. Both the burst duration and the waiting time between two successive bursts follow log-normal distributions, consistent with previous studies. We also find that bursts with longer duration (some are multi-pulsed) tend to occur during the period with relatively high burst rate. There is no correlation between the waiting time and the fluence or duration of either the former or latter burst. It also seems that there is no correlation between burst duration and hardness ratio, in contrast to some previous reports. In addition, we do not find any X-ray burst associated with any reported radio bursts except for FRB 200428.Comment: 31 pages, 10 figures, accepted for publication in ApJ

New method for Earth neutral atmospheric density retrieval based on energy spectrum fitting during occultation with LE/\emph{Insight}-HXMT

We propose a new method for retrieving the atmospheric number density profile in the lower thermosphere, based on the X-ray Earth occultation of the Crab Nebula with the Hard X-ray Modulation Telescope (\emph{Insight}-HXMT) Satellite. The absorption and scattering of X-rays by the atmosphere result in changes in the X-ray energy, and the Earth's neutral atmospheric number density can be directly retrieved by fitting the observed spectrum and spectrum model at different altitude ranges during the occultation process. The pointing observations from LE/\emph{Insight}-HXMT on 16 November 2017 are analyzed to obtain high-level data products such as lightcurve, energy spectrum and detector response matrix. The results show that the retrieved results based on the spectrum fitting in the altitude range of 90--200 km are significantly lower than the atmospheric density obtained by the NRLMSISE-00 model, especially in the altitude range of 110--120 km, where the retrieved results are 34.4\% lower than the model values. The atmospheric density retrieved by the new method is qualitatively consistent with previous independent X-ray occultation results (Determan et al., 2007; Katsuda et al., 2021), which are also lower than empirical model predictions. In addition, the accuracy of atmospheric density retrieved results decreases with the increase of altitude in the altitude range of 150--200 km, and the accurate quantitative description will be further analyzed after analyzing a large number of X-ray occultation data in the future.Comment: 9 pages, 6 figures, 2 tables, accepted for publication in Advances in Space Researc

Characterizing uncertainty in process-based hydraulic modeling, exemplified in a semiarid Inner Mongolia steppe

Assessing root sources of three uncertainties – parameterization of soil hydraulic characteristics, boundary conditions, and estimation of source/sink terms – is a significant challenge in soil water transport modeling. This study aims to evaluate the uncertainty of three each widely-used parameter estimation methods affecting plot-scale water dynamics. The study employs HYDRUS, a process-based hydrologic model, to incorporate these uncertainties and compare model predictions to measured values in a semiarid Inner Mongolia steppe, China. Soil hydraulic parameters are determined using two direct methods (laboratory-derived approach and evaporation method) and one indirect method (neural network). While each hydraulic parameter method generally simulates soil moisture dynamics, the evaporation method performed better, especially under dry conditions. This suggests that measuring the intensity properties, such as unsaturated hydraulic conductivity, with the evaporation method is crucial for reasonable soil moisture simulation. The study also demonstrates the impact of different applied boundary conditions on simulated soil moisture, specifically the partitioning of reference FAO evapotranspiration via one direct method (soil fraction cover) and two indirect methods (leaf area index and crop height). The partitioning via soil fraction cover reflected a better simulation. Additionally, the study compares the uncertainties of root water uptake function with root growth parameters and constant root depth referenced to grass and pasture, and finds no significant difference among them. Comparing three sources of uncertainty in predicting soil moisture, the study concludes that the input soil hydraulic parameter is more sensitive than evapotranspiration partitioning or representation of root water uptake function. Our study highlights that measuring soil intensity properties can better reflect the effects of land use change, such as compaction, on field water transports