声相关海流剖面(ACCP)测量的流速估值方法

声相关海流剖面（ACCP）测量技术对水体回波信号进行空间相关处理来估计流速值，与声学多普勒海流剖面仪（ADCP）相比ACCP的工作频工，更适合深海测流应用，ACCP测量系统对回波信号进行时空相关处理，根据相关函数的位置来估计被测水团的流速值，ACCP从信号中提取流速值要运用参数估计技术，本文介绍了采用极大似然法和最小二乘法进行流速参数的处理方法，给出一些典型流速情形的数值计算结果。     

Study on visual control system of acoustic in situ measurement technology for survey of seafloor sediment

Abstract

A new kind of visual acoustic measurement system was developed to obtain the acoustic characteristics of seabed sediment and the working state of in situ measuring equipment in real time. The control unit of the system structure is mainly made up of the underwater control unit and the deck control unit. In comparison with similar traditional systems, the system can transmit the working video image, the measured acoustic data and the waveform synchronous from the underwater control equipment to the deck control unit through the connecting cable. Apart from self-contained in situ measurement, the working modes of it include visual online real-time control. In order to guarantee the stability and measurement precision of the video control system, the process control of in situ measurement was strictly tested in the experimental tank. In 2017, sea trials of the in situ measurement system was carried out in the South China Sea. In the process, data related to measurement, including the acoustic velocity and attenuation coefficient of the seabed sediment, were obtained as well. The results from sea trials show that the control process of the visual system is intuitive, reliable and accurate, and therefore it can be popularized and applied.     

Seismic hazard maps for Jordan and vicinity

Probabilistic methods are used to quantify the seismic hazard in Jordan and neighbouring regions. The hazard model incorporates the uncertainties associated with the seismicity parameters and the attenuation equation. Seven seismic sources are identified in the region and the seismicity parameters of these sources are estimated by making use of all the available information. Seismic hazard computations and the selection of peak ground acceleration and modified Mercalli intensity values at the nodes of a 25 × 25 km mesh covering the region under study are carried out by two different computer programs.The results of the study are presented through a set of seismic hazard maps displaying iso-acceleration and iso-intensity contours corresponding to specified return periods. The first set of maps is derived based on the seismicity data assessed in this study and display our best estimate of the seismic hazard for Jordan and the neighbouring areas. The second set of maps which shows the alternative estimate of seismic hazard is based solely on the seismicity parameters reported by other researchers. The third set of maps, called the Bayesian estimate of seismic hazard, reflects the influence of expert opinion involving more conservative assumptions regarding the Red Sea and Araba faults.     

Utility of high-resolution climate model simulations for water resources prediction over the Korean Peninsula: a sensitivity study / Utilité de simulations de modèle climatique à haute résolution pour la prévision des ressources en eau dans la Péninsule Coréenne: étude de sensibilité

Abstract

Abstract The utility of simulations of Global Climate Models (GCMs) for regional water resources prediction and management on the Korean Peninsula was assessed by a probabilistic measure. Global Climate Model simulations of an indicator variable (e.g. surface precipitation or temperature) were used for discriminating high vs low regional observations of a target variable (e.g. watershed precipitation or reservoir inflow). The formulation uses the significance probability of the Kolmogorov-Smirnov test for detecting differences between two distributions. High resolution Atmospheric Model Intercomparison Project-II (AMIP-II) type GCM simulations performed by the European Centre for Medium-Range Weather Forecasts (ECMWF) and AMIP-I type GCM simulations performed by the Korean Meteorological Research Institute (METRI) were used to obtain information for the indicator variables. Observed mean areal precipitation and temperature, and watershed-outlet discharge values for seven major river basins in Korea were used as the target variables. The results suggest that the use of the climate model nodal output from both climate models in the vicinity of the target basin with monthly resolution will be beneficial for water resources planning and management analysis that depends on watershed mean areal precipitation and temperature, and outlet discharge.     

Usages astronomiques du gnomon au cours des siècles

Gnomon is the oldest astronomic instrument, as its use is attested as early as the second millenium B.C. It allowed the ancients to ascertain the Earth's main basic parameters, such as its movement relatively to the Sun. The use of gnomon was generalized in numerous antique civilizations. It was constantly improved up to reaching a precision of a few seconds of degree for the inner meridians built in Europe during the 17th and 18th centuries. More remarkably, it was used during the 21st-century space missions.     

Quantification of uncertainty in the assessment of future streamflow under changing climate conditions

Climate change has a significant influence on streamflow variation. The aim of this study is to quantify different sources of uncertainties in future streamflow projections due to climate change. For this purpose, 4 global climate models, 3 greenhouse gas emission scenarios (representative concentration pathways), 6 downscaling models, and a hydrologic model (UBCWM) are used. The assessment work is conducted for 2 different future time periods (2036 to 2065 and 2066 to 2095). Generalized extreme value distribution is used for the analysis of the flow frequency. Strathcona dam in the Campbell River basin, British Columbia, Canada, is used as a case study. The results show that the downscaling models contribute the highest amount of uncertainty to future streamflow predictions when compared to the contributions by global climate models or representative concentration pathways. It is also observed that the summer flows into Strathcona dam will decrease, and winter flows will increase in both future time periods. In addition to these, the flow magnitude becomes more uncertain for higher return periods in the Campbell River system under climate change.     

Multiple adaptation types with mitigation: A framework for policy analysis

Effective climate policy will consist of mitigation and adaptation implemented simultaneously in a policy portfolio to reduce the risks of climate change. Previous studies of the tradeoffs between mitigation and adaptation have implicitly framed the problem deterministically, choosing the optimal paths for all time. Because climate change is a long-term problem with significant uncertainties and opportunities to learn and revise, critical tradeoffs between mitigation and adaptation in the near-term have not been considered. We propose a new framework for considering the portfolio of mitigation and adaptation that explicitly treats the problem as a multi-stage decision under uncertainty. In this context, there are additional benefits to near-term investments if they reduce uncertainty and lead to improved future decisions. Two particular features are fundamental to understanding the relevant tradeoffs between mitigation and adaptation: (1) strategy dynamics over time in reducing climate damages, and (2) strategy dynamics under uncertainty and potential for learning. Our framework strengthens the argument for disaggregating adaption as has been proposed by others. We present three stylized classes of adaptation investment types as a conceptual framework: short-lived “flow” spending, committed “stock” investment, and lower capacity “option” stock with the capability of future upgrading. In the context of sequential decision under uncertainty, these subtypes of adaptation have important tradeoffs among them and with mitigation. We argue that given the large policy uncertainty that we face currently, explicitly considering adaptation “option” investments is a valuable component of a near-term policy response that can balance between the flexible flow and committed stock approaches, as it allows for the delay of costly stock investments while at the same time allowing for lower-cost risk management of future damages.     

Simultaneous calibration of surface flow and baseflow simulations: a revisit of the SWAT model calibration framework

Accurate analysis of water flow pathways from rainfall to streams is critical for simulating water use, climate change impact, and contaminants transport. In this study, we developed a new scheme to simultaneously calibrate surface flow (SF) and baseflow (BF) simulations of soil and water assessment tool (SWAT) by combing evolutionary multi‐objective optimization (EMO) and BF separation techniques. The application of this scheme demonstrated pronounced trade‐off of SWAT's performance on SF and BF simulations. The simulated major water fluxes and storages variables (e.g. soil moisture, evapotranspiration, and groundwater) using the multiple parameters from EMO span wide ranges. Uncertainty analysis was conducted by Bayesian model averaging of the Pareto optimal solutions. The 90% confidence interval (CI) estimated using all streamflows substantially overestimate the uncertainty of low flows on BF days while underestimating the uncertainty of high flows on SF days. Despite using statistical criteria calculated based on streamflow for model selection, it is important to conduct diagnostic analysis of the agreement of SWAT behaviour and actual watershed dynamics. The new calibration technique can serve as a useful tool to explore the trade‐off between SF and BF simulations and provide candidates for further diagnostic assessment and model identification. Copyright © 2011 John Wiley & Sons, Ltd.     

Bayesian dynamic modelling for nonstationary hydroclimatic time series forecasting along with uncertainty quantification

Forecasting of hydrologic time series, with the quantification of uncertainty, is an important tool for adaptive water resources management. Nonstationarity, caused by climate forcing and other factors, such as change in physical properties of catchment (urbanization, vegetation change, etc.), makes the forecasting task too difficult to model by traditional Box–Jenkins approaches. In this paper, the potential of the Bayesian dynamic modelling approach is investigated through an application to forecast a nonstationary hydroclimatic time series using relevant climate index information. The target is the time series of the volume of Devil's Lake, located in North Dakota, USA, for which it was proved difficult to forecast and quantify the associated uncertainty by traditional methods. Two different Bayesian dynamic modelling approaches are discussed, namely, a constant model and a dynamic regression model (DRM). The constant model uses the information of past observed values of the same time series, whereas the DRM utilizes the information from a causal time series as an exogenous input. Noting that the North Atlantic Oscillation (NAO) index appears to co‐vary with the time series of Devil's Lake annual volume, its use as an exogenous predictor is explored in the case study. The results of both the Bayesian dynamic models are compared with those from the traditional Box–Jenkins time series modelling approach. Although, in this particular case study, it is observed that the DRM performs marginally better than traditional models, the major strength of Bayesian dynamic models lies in the quantification of prediction uncertainty, which is of great value in hydrology, particularly under the recent climate change scenario. Copyright © 2008 John Wiley & Sons, Ltd.     

Ecohydrological modelling in a deciduous boreal forest: Model evaluation for application in non-stationary climates

Soil moisture is an important driver of growth in boreal Alaska, but estimating soil hydraulic parameters can be challenging in this data-sparse region. Parameter estimation is further complicated in regions with rapidly warming climate, where there is a need to minimize model error dependence on interannual climate variations. To better identify soil hydraulic parameters and quantify energy and water balance and soil moisture dynamics, we applied the physically based, one-dimensional ecohydrological Simultaneous Heat and Water (SHAW) model, loosely coupled with the Geophysical Institute of Permafrost Laboratory (GIPL) model, to an upland deciduous forest stand in interior Alaska over a 13-year period. Using a Generalized Likelihood Uncertainty Estimation parameterisation, SHAW reproduced interannual and vertical spatial variability of soil moisture during a five-year validation period quite well, with root mean squared error (RMSE) of volumetric water content at 0.5 m as low as 0.020 cm³/cm³. Many parameter sets reproduced reasonable soil moisture dynamics, suggesting considerable equifinality. Model performance generally declined in the eight-year validation period, indicating some overfitting and demonstrating the importance of interannual variability in model evaluation. We compared the performance of parameter sets selected based on traditional performance measures such as the RMSE that minimize error in soil moisture simulation, with one that is designed to minimize the dependence of model error on interannual climate variability using a new diagnostic approach we call CSMP, which stands for Climate Sensitivity of Model Performance. Use of the CSMP approach moderately decreases traditional model performance but may be more suitable for climate change applications, for which it is important that model error is independent from climate variability. These findings illustrate (1) that the SHAW model, coupled with GIPL, can adequately simulate soil moisture dynamics in this boreal deciduous region, (2) the importance of interannual variability in model parameterisation, and (3) a novel objective function for parameter selection to improve applicability in non-stationary climates.