PM10 data assimilation over south Korea to Asian dust forecasting model with the optimal interpolation method

A data assimilation (DA) system using ground PM₁₀ observation for Asian Dust Aerosol Model version 2 (ADAM2), which is the operational dust forecasting model of Korea Meteorological Administration (KMA), has been developed with the optimal interpolation (OI) method. The observations are provided by the PM₁₀ network operated by KMA. Three DA experiments are performed to simulate a dust event observed in Korea from 1 March to 31 May 2009 with different assimilation cycles of 24 (DA24), 12 (DA12), and 06 hours (DA06). 48-hour forecasts from the adjusted Initial Condition (IC) of dust concentration are compared with control simulation (CTL) and observation from independent stations. It is found that CTL simulates spatial patterns of dust emitted and transported associated with a developing low pressure system over the dust source regions quite well, compared with satellite measurement. However, it appears that there is considerable uncertainty in estimating the concentration of dust. With IC adjustment, the model simulates improved dust concentration, showing considerably reduced RMSE, particularly for the prediction within 12 hours of forecast. At the same time, it is shown that the time interval of DA affects the predictability of ADAM2, so that DA06 appears to have better predictability within a 12-hour simulation, reducing RMSE by 50% compared with CTL. This suggests that assimilating PM₁₀ to the dust prediction model using OI has the potential to predict air quality in Korea when the cycle of assimilation is sufficiently short.     

Future change of Asian-Australian monsoon under RCP 4.5 anthropogenic warming scenario

We investigate the future changes of Asian-Australian monsoon (AAM) system projected by 20 climate models that participated in the phase five of the Coupled Model Intercomparison Project (CMIP5). A metrics for evaluation of the model’s performance on AAM precipitation climatology and variability is used to select a subset of seven best models. The CMIP5 models are more skillful than the CMIP3 models in terms of the AAM metrics. The future projections made by the selected multi-model mean suggest the following changes by the end of the 21st century. (1) The total AAM precipitation (as well as the land and oceanic components) will increase significantly (by 4.5 %/°C) mainly due to the increases in Indian summer monsoon (5.0 %/°C) and East Asian summer monsoon (6.4 %/°C) rainfall; the Australian summer monsoon rainfall will increase moderately by 2.6 %/°C. The “warm land-cool ocean” favors the entire AAM precipitation increase by generation of an east-west asymmetry in the sea level pressure field. On the other hand, the warm Northern Hemisphere-cool Southern Hemisphere induced hemispheric SLP difference favors the ASM but reduces the Australian summer monsoon rainfall. The combined effects explain the differences between the Asian and Australian monsoon changes. (2) The low-level tropical AAM circulation will weaken significantly (by 2.3 %/°C) due to atmospheric stabilization that overrides the effect of increasing moisture convergence. Different from the CMIP3 analysis, the EA subtropical summer monsoon circulation will increase by 4.4 %/°C. (3) The Asian monsoon domain over the land area will expand by about 10 %. (4) The spatial structures of the leading mode of interannual variation of AAM precipitation will not change appreciably but the ENSO-AAM relationship will be significantly enhanced.     

Locally weighted learning based hybrid intelligence models for groundwater potential mapping and modeling: A case study at Gia Lai province,Vietnam

The groundwater potential map is an important tool for a sustainable water management and land use planning,particularly for agricultural countries like Vietnam. In this article, we proposed new machine learning ensemble techniques namely Ada Boost ensemble(ABLWL), Bagging ensemble(BLWL), Multi Boost ensemble(MBLWL),Rotation Forest ensemble(RFLWL) with Locally Weighted Learning(LWL) algorithm as a base classifier to build the groundwater potential map of Gia Lai province in Vietnam. For this study, eleven conditioning factors(aspect, altitude, curvature, slope, Stream Transport Index(STI), Topographic Wetness Index(TWI), soil, geology,river density, rainfall, land-use) and 134 wells yield data was used to create training(70%) and testing(30%)datasets for the development and validation of the models. Several statistical indices were used namely Positive Predictive Value(PPV), Negative Predictive Value(NPV), Sensitivity(SST), Specificity(SPF), Accuracy(ACC),Kappa, and Receiver Operating Characteristics(ROC) curve to validate and compare performance of models. Results show that performance of all the models is good to very good(AUC: 0.75 to 0.829) but the ABLWL model with AUC = 0.89 is the best. All the models applied in this study can support decision-makers to streamline the management of the groundwater and to develop economy not only of specific territories but also in other regions across the world with minor changes of the input parameters.     

局部空间自相关及其在勘探地球化学中的空间聚集研究

运用局部空间自相关 Moran的 Ii 和G*i 指数,研究8130 km2区域内采集的1∶20万水系沉积物1482个组合样点的空间聚集情况,与基于稳健统计学的地球化学异常下限确定方法所圈定的异常范围对空间聚集范围进行对比。结果表明,局部Ii 指数能够很好地探测出程度较弱和范围较小的空间聚集,局部G*i 指数适合于程度较强和范围大的高高聚集探测,所探测出的空间聚集范围较大。使用该方法所发现的地球化学空间聚集范围和程度符合客观实际,与已知矿床(点)吻合很好。     

A multiphase approach for evaluating the horizontal and rocking impedances of pile group foundations

This paper advocates the use of a multiphase model, already developed for static or quasi‐static geotechnical engineering problems, for simulating the behaviour of piled raft foundations subject to horizontal as well as rocking dynamic solicitations. It is shown that such a model, implemented in a FEM code, yields appropriate predictions for the foundation impedance characteristics, provided that shear and bending effects in the piles are taken into account, thus corroborating the findings of the asymptotic homogenization theory. Besides, it is notably pointed out that such a multiphase‐based computational tool makes it possible to assess the dynamic behaviour of pile groups in a much quicker way than when using direct numerical simulations, which may face oversized problems when large pile groups are concerned. Copyright © 2016 John Wiley & Sons, Ltd.     

Quantitative estimation of submarine groundwater discharge using airborne thermal infrared data acquired at two different tidal heights

Submarine groundwater discharge (SGD) plays an important role in coastal biogeochemical processes and hydrological cycles, particularly off volcanic islands in oligotrophic oceans. However, the spatial and temporal variations of SGD are still poorly understood owing to difficulty in taking rapid SGD measurements over a large scale. In this study, we used four airborne thermal infrared surveys (twice each during high and low tides) to quantify the spatiotemporal variations of SGD over the entire coast of Jeju Island, Korea. On the basis of an analytical model, we found a linear positive correlation between the thermal anomaly and squares of the groundwater discharge velocity and a negative exponential correlation between the anomaly and water depth (including tide height and bathymetry). We then derived a new equation for quantitatively estimating the SGD flow rates from thermal anomalies acquired at two different tide heights. The proposed method was validated with the measured SGD flow rates using a current meter at Gongcheonpo Beach. We believe that the method can be effectively applied for rapid estimation of SGD over coastal areas, where fresh groundwater discharge is significant, using airborne thermal infrared surveys.     

Submarine groundwater discharge revealed by aerial thermal infrared imagery: a case study on Jeju Island,Korea

Submarine groundwater discharge (SGD) is a global phenomenon that carries large volumes of groundwater and dissolved chemical species such as nutrient, metals, and organic compounds to coastal zones. We report the influence of SGD on the coastal waters of Jeju Island, Korea, using high‐resolution aerial thermal infrared (TIR) mapping techniques and field investigations. An aircraft‐based system was implemented using a cost‐effective TIR camera for aerial TIR mapping. Ground‐based calibrations and system integration with GPS/IMU (global positioning system/inertial measurement unit) were performed for the aerial systems. The aerial surveys showed distinct low‐temperature signatures of SGD along the coasts of Jeju Island, revealing large groundwater inputs from the coastal aquifers to the ocean. Multiple aerial surveys over a range of seasons and tidal stages revealed that SGD rates dynamically affect the sea surface temperature (SST) of the coastal zone. The in‐situ measurements supported that SGD has a substantial influence on the coastal water chemistry as well as SST. Our observations highlight the extent to which aerial‐based TIR mapping can serve as a powerful tool for studying SGD and other coastal processes. Copyright © 2016 John Wiley & Sons, Ltd.     

The data‐driven approach as an operational real‐time flood forecasting model

Accurate water level forecasts are essential for flood warning. This study adopts a data‐driven approach based on the adaptive network–based fuzzy inference system (ANFIS) to forecast the daily water levels of the Lower Mekong River at Pakse, Lao People's Democratic Republic. ANFIS is a hybrid system combining fuzzy inference system and artificial neural networks. Five ANFIS models were developed to provide water level forecasts from 1 to 5 days ahead, respectively. The results show that although ANFIS forecasts of water levels up to three lead days satisfied the benchmark, four‐ and five‐lead‐day forecasts were only slightly better in performance compared with the currently adopted operational model. This limitation is imposed by the auto‐ and cross‐correlations of the water level time series. Output updating procedures based on the autoregressive (AR) and recursive AR (RAR) models were used to enhance ANFIS model outputs. The RAR model performed better than the AR model. In addition, a partial recursive procedure that reduced the number of recursive steps when applying the AR or the RAR model for multi‐step‐ahead error prediction was superior to the fully recursive procedure. The RAR‐based partial recursive updating procedure significantly improved three‐, four‐ and five‐lead‐day forecasts. Our study further shows that for long lead times, ANFIS model errors are dominated by lag time errors. Although the ANFIS model with the RAR‐based partial recursive updating procedure provided the best results, this method was able to reduce the lag time errors significantly for the falling limbs only. Improvements for the rising limbs were modest. Copyright © 2011 John Wiley & Sons, Ltd.     

Influence of anthropogenic pressure and seasonal upwelling on coral reefs in Nha Trang Bay (Central Vietnam)

The growing coastal development, dredging and dumping activities, overfishing and expansion of marine cage culture in Nha Trang Bay (NTB) of Central Vietnam since the beginning of the 2000s have resulted in a dramatic decrease of live coral cover. Surveys conducted in April–May 2013 and the same period in 2014 revealed that with an increase in distance from the outer part of the bay towards the mainland, the rivers’ influxes and dredged areas, coral cover decreased from 75% to 0.6% and species richness from 63 to 5, while the abundance of macroalgae increased from 0% to 56%. These changes correlate with differences in the concentration of suspended sediments on the same gradient. The abundance of the crown‐of‐thorns starfish Acanthaster planci and of the echinoid Diadema setosum significantly increased between the first estimation in 1998 and the survey in 2014, from 0 to 1.7 individuals (ind.) per 100 m^?2 and from 50.8 to 94.5 ind. per 100 m^?2, respectively, contributing to coral loss and intensive bioerosion of the reef framework in the bay. The large sizes of adult colonies of tabulate Acropora on the remote stations with negligible sedimentation and eutrophication loads were inconsistent with the assumptions that temperature‐induced coral bleaching or cyclones could be the major impacts in Nha Trang Bay. Analysis of the 16‐year thermal history of the bay did not reveal any instances in which the coral thermal bleaching threshold had been exceeded up to the present study. Seasonal upwelling, which occurs annually in the vicinity of Central Vietnam, may contribute to mitigation of thermal anomalies within NTB and to the maintenance of healthy coral communities on the remote reefs with relatively low anthropogenic impact.