Predicting floods in a large karst river basin by coupling PERSIANN-CCS QPEs with a physically based distributed hydrological model

In general, there are no long-term meteorological or hydrological data available for karst river basins. The lack of rainfall data is a great challenge that hinders the development of hydrological models. Quantitative precipitation estimates (QPEs) based on weather satellites offer a potential method by which rainfall data in karst areas could be obtained. Furthermore, coupling QPEs with a distributed hydrological model has the potential to improve the precision of flood predictions in large karst watersheds. Estimating precipitation from remotely sensed information using an artificial neural network-cloud classification system (PERSIANN-CCS) is a type of QPE technology based on satellites that has achieved broad research results worldwide. However, only a few studies on PERSIANN-CCS QPEs have occurred in large karst basins, and the accuracy is generally poor in terms of practical applications. This paper studied the feasibility of coupling a fully physically based distributed hydrological model, i.e., the Liuxihe model, with PERSIANN-CCS QPEs for predicting floods in a large river basin, i.e., the Liujiang karst river basin, which has a watershed area of 58 270 km-2, in southern China. The model structure and function require further refinement to suit the karst basins. For instance, the sub-basins in this paper are divided into many karst hydrology response units (KHRUs) to ensure that the model structure is adequately refined for karst areas. In addition, the convergence of the underground runoff calculation method within the original Liuxihe model is changed to suit the karst water-bearing media, and the Muskingum routing method is used in the model to calculate the underground runoff in this study. Additionally, the epikarst zone, as a distinctive structure of the KHRU, is carefully considered in the model. The result of the QPEs shows that compared with the observed precipitation measured by a rain gauge, the distribution of precipitation predicted by the PERSIANN-CCS QPEs was very similar. However, the quantity of precipitation predicted by the PERSIANN-CCS QPEs was smaller. A post-processing method is proposed to revise the products of the PERSIANN-CCS QPEs. The karst flood simulation results show that coupling the post-processed PERSIANN-CCS QPEs with the Liuxihe model has a better performance relative to the result based on the initial PERSIANN-CCS QPEs. Moreover, the performance of the coupled model largely improves with parameter re-optimization via the post-processed PERSIANN-CCS QPEs. The average values of the six evaluation indices change as follows: the Nash-Sutcliffe coefficient increases by 14 %, the correlation coefficient increases by 15 %, the process relative error decreases by 8 %, the peak flow relative error decreases by 18 %, the water balance coefficient increases by 8 %, and the peak flow time error displays a 5 h decrease. Among these parameters, the peak flow relative error shows the greatest improvement; thus, these parameters are of page1506 the greatest concern for flood prediction. The rational flood simulation results from the coupled model provide a great practical application prospect for flood prediction in large karst river basins

Sub-threshold J/ψ and ϒ production in γA collisions

We study sub-threshold heavy quarkonium (J/ψ and ϒ) photo-productions in γA collisions as an independent test of the universality of the nucleon-nucleon short range correlation (SRC) in nuclear scattering processes. Just below the γp threshold, the cross section is dominated by the mean field contribution of nucleons inside the nucleus. The SRC contributions start to dominate at lower photon energies, depending on the fraction of the SRC pairs in the target nucleus. We give an estimate of the cross sections in the sub-threshold region both for J/ψ and ϒ. This may be helpful for future measurements at JLab as well as at the Electron-Ion Collider in the U.S., and especially in China

An Ultra-fast DOA Estimator with Circular Array Interferometer Using Lookup Table Method

The time-consuming phase ambiguity resolution makes the uniform circular array (UCA) interferometer not suitable for real-time direction-of-arrival (DOA) estimation. This paper introduces the lookup table (LUT) method to solve this problem. The key of the method is that we look up the ambiguity numbers instead of the eventual DOA from the table, and then the DOA is obtained by relatively small amount of calculation. This makes it possible that we are able to shrink the table size while maintain the DOA estimation accuracy. The table addresses cover all possible measured phase differences (PDs), which enables the method to be free of spatial scanning. Moreover, without adding frequency index to the lookup table, the estimator can realize wideband application. As an example, a field-programmable gate array (FPGA) based DOA estimator with the estimation time of 180 ns is presented, accompanied by the measured results. This method possesses the advantages of ultra-high speed, high accuracy and low memory usage

Probing Electroweak Symmetry Breaking Mechanism at the LHC: A Guideline from Power Counting Analysis

We formulate the equivalence theorem as a theoretical criterion for sensitively probing the electroweak symmetry breaking mechanism, and develop a precise power counting method for the chiral Lagrangian formulated electroweak theories. Armed with these, we perform a systematic analysis on the sensitivities of the scattering processes $W^\pm W^\pm \rightarrow W^\pm W^\pm$ and $q\bar{q}'\rightarrow W^\pm Z$ for testing all possible effective bosonic operators in the chiral Lagrangian formulated electroweak theories at the CERN Large Hadron Collider (LHC). The analysis shows that these two kinds of processes are "complementary" in probing the electroweak symmetry breaking sector.Comment: Extended version, 11-page-Latex-file and 3 separate PS-Figs. To be Published in Mod.Phys.Lett.