•Four latest satellite–gauge QPEs and their hydrologic applications are evaluated.•Gauge adjustment procedures and the gauge density greatly affect the QPE quality.•The error characteristics of ...rainfall are propagated into hydrologic simulations.•CMORPH CMA can serve as an alternative high quality QPE in China.
Satellite–gauge quantitative precipitation estimate (QPE) products may reduce the errors in near real-time satellite precipitation estimates by combining rain gauge data, which provides great potential to hydrometeorological applications. This study aims to comprehensively evaluate four of the latest satellite–gauge QPEs, including NASA’s Tropical Rainfall Measuring Mission (TRMM) 3B42V7 product, NOAA’s Climate Prediction Center (CPC) MORPHing technique (CMORPH) bias-corrected product (CMORPH CRT), CMORPH satellite–gauge merged product (CMORPH BLD) and CMORPH satellite–gauge merged product developed at the National Meteorological Information Center (NMIC) of the China Meteorological Administration (CMA) (CMORPH CMA). These four satellite–gauge QPEs are statistically evaluated over the Huaihe River basin during 2003–2012 and applied into the distributed Variable Infiltration Capacity (VIC) model to assess hydrologic utilities.
Compared to the China Gauge-based Daily Precipitation Analysis (CGDPA) newly developed at CMA/NMIC, the four satellite–gauge QPEs generally depict the spatial distribution well, with the underestimation in the southern mountains and overestimation in the northern plain of the Huaihe River basin. Specifically, both TRMM and CMORPH CRT adopt simple gauge adjustment algorithms and exhibit relatively poor performance, with evidently deteriorated quality in winter. In contrast, the probability density function-optimal interpolation (PDF-OI) gauge adjustment procedure has been applied in CMORPH BLD and CMORPH CMA, resulting in higher quality and more stable performance. CMORPH CMA further benefits from a merged dense gauge observation network and outperforms the other QPEs with significant improvements in rainfall amount and spatial/temporal distributions. Due to the insufficient gauge observations in the merging process, CMORPH BLD features the similar error characteristics of CMORPH CRT with a positive bias of light precipitation and a negative bias of heavy precipitation, in contrast to the overall large overestimation by TRMM. The quality of QPEs directly impacts streamflow simulations, as the precipitation biases are propagated into simulated streamflow through interaction with hydrologic processes. The general streamflow pattern is well captured at multiple time scales by the simulations using the four satellite–gauge QPEs as the input forcing. CMORPH CRT shows the worst simulations in both long-term streamflow and extreme flood events, while CMORPH CMA forced streamflow simulations even outperform that forced by CGDPA. CMORPH CMA is able to reproduce the July 2003 flood event, while the other three QPEs fail to generate such extreme flood. Overall, CMORPH CMA shows great potential to improve the precipitation distribution and hydrometeorological simulations, and can serve as an alternative high quality QPE in China.
Parameter optimization is needed for reliable simulations and predictions of natural processes by environmental models. The surrogate modeling‐based approach is an efficient way to reduce the number ...of model evaluations needed for optimization. However, building a surrogate of a distributed environmental model with many output variables over a large spatial domain is computationally intensive as it involves a large number of expensive model simulations on many spatial grid cells. In this study, a novel calibration method called the multi‐objective adaptive surrogate modeling‐based optimization using grid sampling (MO‐ASMOGS) is introduced. This method constructs the response surface surrogate of the original model more efficiently by using both parameter and spatial grid sampling. The spatial grid sampling strategy utilizes the evolutionary elitism and adaptive sampling concepts, thus allowing the surrogate model to be built using a fraction of the total grid cells over a large region. We apply MO‐ASMOGS to calibrating the Noah‐MP model against two surface fluxes: the gross primary production (GPP) and the latent heat flux (LH), over two plant function types (PFTs) across the continental United States. The results demonstrate that the MO‐ASMOGS method can significantly improve the GPP and LH simulations. The new method needs only a small portion of the total grid cells sampled for a given PFT to achieve comparable optimization results obtained by MO‐ASMO using all grid cells. This method can be very valuable in improving model calibration of computationally intensive distributed environmental models.
Key Points
A surrogate modeling based multi‐objective optimization method using grid sampling is proposed for calibration of environmental models
Multi‐objective adaptive surrogate modeling‐based optimization using grid sampling (MO‐ASMOGS) uses only 10% or less of the total grid cells to obtain the same calibration results as MO‐ASMO using 100% of the grids
MO‐ASMOGS is suitable for computationally intensive distributed environmental models such as continental or global‐scale land surface models
•Three traditional methods to address heteroscedasticity are compared.•A combined approach to address the complicated heteroscedasticity is proposed.•The combined approach suits the basin and can ...effectively avoid the negative flows.
The heteroscedasticity treatment in residual error models directly impacts the model calibration and prediction uncertainty estimation. This study compares three methods to deal with the heteroscedasticity, including the explicit linear modeling (LM) method and nonlinear modeling (NL) method using hyperbolic tangent function, as well as the implicit Box-Cox transformation (BC). Then a combined approach (CA) combining the advantages of both LM and BC methods has been proposed. In conjunction with the first order autoregressive model and the skew exponential power (SEP) distribution, four residual error models are generated, namely LM-SEP, NL-SEP, BC-SEP and CA-SEP, and their corresponding likelihood functions are applied to the Variable Infiltration Capacity (VIC) hydrologic model over the Huaihe River basin, China. Results show that the LM-SEP yields the poorest streamflow predictions with the widest uncertainty band and unrealistic negative flows. The NL and BC methods can better deal with the heteroscedasticity and hence their corresponding predictive performances are improved, yet the negative flows cannot be avoided. The CA-SEP produces the most accurate predictions with the highest reliability and effectively avoids the negative flows, because the CA approach is capable of addressing the complicated heteroscedasticity over the study basin.
With the growing and aging population round the world, it becomes increasingly important to understand what factors impact the mental health and cognition of the older generations in order to design ...effective interventions. In this paper, we investigate the effect of a child’s gender on parental mental health and cognition in the context of one of the world’s largest developing countries and the unique one-child policy, using China Family Panel Studies (CFPS). We exploit the exogeneity of the first child’s gender and find that having a son has significant protective effects on parents’ mathematics performance and memory functions in one-child families, but such effects are absent in multi-child families. Moreover, we find that the protective effect is more pronounced among one-child families in rural areas than urban areas. Our results suggest the existence of gender inequality in China and reveal the hidden long-term social cost of the one-child policy.
•Provide new empirical evidence to better understand gender preference in the context of contemporary China.•Investigate the effect of a child’s gender on parents’ mental health by exploiting the exogeneity of the first child’s gender in China.•Focus on multidimensional mental health including depression symptoms, mathematics performance, and memory functions.•Examine the heterogeneity and mechanisms to show important policy implementations to address gender inequality in China.
The present problem aims to study the scattering behavior of SH-waves by a circular cavity near two symmetrically permeable interface cracks in the piezoelectric bi-material half-space. The ...steady-state response of the problem is obtained, with the aid of the Green’s function method and the complex function method. Above all, the essential expression of Green’s function is constructed by the mirror method. This expression satisfies the conditions of being stress-free and electric insulation on the horizontal boundary of the orthogonal space where the circular cavity is located, and the condition of bearing a harmonic out-plane line source force on the vertical boundary. Next, on the basis of dividing the bi-material medium into two parts along the vertical boundary, the first kind of Fredholm integral equation with uncertain anti-plane forces is established by using the conjunction method and the crack-division technology. Then, the solution is obtained by solving an algebraic equation with finite terms, which is an effective truncation of the integral equation. Finally, the dynamic stress concentration factor around the edge of the circular cavity and the dynamic stress intensity factor at the crack tip are calculated numerically. On this basis, the effects of incident wave frequency, crack length, crack location and circular cavity position on the dynamic stress concentration factor and dynamic stress intensity factor are discussed.
Aluminum nanoparticles (ANPs) are considered energetic, economical, and eco-friendly additives. In this investigation, advanced ReaxFF molecular dynamics (MD) simulation has been used to discover the ...mechanism of coating ether and ethanol molecules on ANPs. Those MD results generally reveal the dynamics process of ethanol and ether adsorption. It is found that the adsorption of ethanol and ether molecules is not a physical adsorption process only. Newly generated aluminum-oxygen bonds are formed between oxygen atoms and aluminum atoms. Those oxygen atoms come from both ethanol and ether molecules. Moreover, ethanol and ether molecules generate ethyl and new ethanol molecules during the adsorption process. The radial distribution function curves and adsorption curves are used to describe the adsorption process. The results show that the adsorption amount of ethanol molecule is significantly higher than that of the ether molecule. It is observed that the outermost aluminum atoms form an organic-provided alumina layer, the inside of ANPs is active aluminum atoms, and the outside is the organic coating layer. Heating could eliminate the hydrogen-bonding between solution molecules. High pressure and high temperature destroy the external structure of aluminum particles, which makes atoms migrate to the interior of aluminum particles. Finally, the oxidation resistance test shows that at 300 K, the organic coating layer can maintain good stability and oxidation resistance.
Considering the resistance and toxicity of traditional chemotherapeutic drugs, seeking potential candidate for treating breast cancer effectively is a clinical problem that should be solved urgently. ...Natural products have attracted extensive attention, owing to their multi-target advantages and low toxicity. In the current study, the effects of XK-81, a novel bromophenol compound extracted from
, on breast cancer, and its underlying mechanisms, were explored. Firstly, data from in vitro experiments indicated that 4T-1, one of common mouse breast cancer cell lines, was a XK-81-susceptible cell line, and ferroptosis was the major death manner in response to XK-81 treatment, which was evidenced by increasing intracellular Fe
and ROS level with condensed mitochondrial membrane densities, as well as decreasing the protein expressions of SLC7A11 and GPX4. In vivo, XK-81 suppressed the growth of 4T-1 breast-tumor in both BALB/C mice and zebrafish. Obviously, XK-81 decreased the protein expression of SLC7A11 and GPX4 in tumor tissues, hinting at the occurrence of ferroptosis. Moreover, XK-81 increased CD8+ T cells and NK cells numbers and regulated M1/M2 macrophage ratio in tumor tissues, indicating XK-81's immunotherapeutic effect. Additionally, the secretions of immune-related cytokines, including TNF-α, IL-1β, and IL-12, were elevated with XK-81 stimulation in RAW 264.7 cells. Intriguingly, compared with doxorubicin-induced heart damage, XK-81 demonstrated the therapeutic advantage of little cardiotoxicity on the heart. XK-81 demonstrated potential antitumor advantage by both directly inducing ferroptosis-mediated death of tumor cells and immunization.
Abstract
Studies on nitrocellulose (NC) mixtures with little solubilities were neglected in many cases previously. This investigation was performed to provide supplemental characterizations of NC and ...its soaked state with pure liquid ethanol or diethyl ether by simulations and practical methods. Above all, a short-chained NC model (polymerisation degree: 8) and a dried NC specimen were characterized for their substitution of nitrate and microstructure. It was confirmed that both the numerical model and practical specimen belonged to low-nitrated NC. The bonding information of a glycosyl unit and nitrate ester were summarized via first-principle calculations. Then, ReaxFF potential based Molecular Dynamic (MD) simulations and soaking tests on binary organic mixtures demonstrated that both ethanol and diethyl ether had limited solubility for our specified NC. However, potential energies and diffusion coefficients of both computational models showed that the interactions from ethanol molecules were relatively stronger than diethyl ether molecules. The viscosities of saturated NC solutions also proved this consequence, as the difference between pure ether and its filtered NC solution was only 0.02 mm
2
s
−1
. Finally, the strong volatility of diethyl ether itself could keep the wetness of NC upper surface shortly, because this was an upward volatilization effect. Due to this effect, the penetration of NC-diethyl ether mixture was higher in the early period of penetration tests.
Abstract Land surface hydrologic models adeptly capture crucial terrestrial processes with a high level of spatial detail. Typically, these models incorporate numerous uncertain, spatially varying ...parameters, the specification of which can profoundly impact the simulation capabilities. There is a longstanding tradition wherein parameter calibration has served as the conventional procedure to enhance model performance. However, calibrating distributed land surface hydrologic models presents a great challenge, often resulting in uneven spatial performance due to the compression of information inherent in model outputs and observations into a single‐value objective function. To address this problem, we propose a novel Generative Adversarial Network‐based Parameter Optimization (GAN‐PO) method. By leveraging a deep neural network to discern model spatial biases, we train a generative network to produce spatially coherent parameter fields, minimizing distinctions between simulations and observations. By leveraging neural network‐based surrogate models to make the physical model differentiable, we employ GAN‐PO to calibrate the Variable Infiltration Capacity (VIC) model against evapotranspiration (ET) over China's Huaihe basin. The results show that GAN‐PO can diminish errors in simulated ET derived from default parameters across nearly all grid cells within the study region, surpassing the conventional calibration approach based on the parameter regionalization technique. Ablation analysis indicates that relying solely on the traditional loss could lead to deteriorated model performance, underscoring the crucial role of the discriminator. Notably, due to the discriminator's explicit identification of model spatial biases, GAN‐PO excels in maintaining spatial consistency, outperforming the state‐of‐the‐art differentiable parameter learning (dPL) method in terms of model spatial performance.
Key Points A novel generative adversarial network‐based parameter estimation method is proposed to calibrate distributed land surface hydrologic models By employing a discriminator to identify model spatial biases, this method contributes to effective and spatially coherent parameter estimation This method can substantially reduce model simulated errors at grid scale and achieve consistent spatial performance
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