三峡工程大江截流的水文技术

鉴于三峡工程大江截流水深大，流量大，工期紧，特别是截流过程中要考虑不断航因素，因此，在大江截流和二期围堰阶段的施工进程中，应充分考虑到各方面的因素，尽可能采取一切减少大江截流和二期围堰施工难度的手段和措施，其中水文测验，水文气象预报，河道观测，水文分析与计算和水力学计算等水文工作则是为顺利实施高质量大江截流的重要条件。     

基于GIS/RS的流域水文过程分布式模拟——Ⅰ模型的原理与结构

面向流域水资源管理,提出了一个基于GIS/RS的流域分布式水文模型,模型主要包括单元水文模型与河网汇流模型两大部分。单元水文模型涉及到冠层截留、融雪、蒸散发、坡面流、非饱和土壤水运动和地下水出流等水文物理过程。产流计算考虑到地形坡度的影响采用基于地形指数的计算方法。汇流演算基于河网结构采用分段马斯京根方法。模型的大部分参数与输入信息可以利用GIS和RS技术获取,能够对气候变化和人类活动对下垫面的改变,做出快速的模拟与响应。     

干旱区内陆河流域水文与水资源问题

阐述了我国水文水资源研究的发展阶段,面临的主要问题,以及当前研究中的热点问题。以新疆地区为例,对干旱区内陆河流域的水文水资源研究方向作了初步探讨。     

Impact of land-cover and climate changes on runoff of the source regions of the Yellow River

After dividing the source regions of the Yellow River into 38 sub-basins, the paper made use of the SWAT model to simulate streamflow with validation and calibration of the observed yearly and monthly runoff data from the Tangnag hydrological station, and simulation results are satisfactory. Five land-cover scenario models and 24 sets of temperature and precipitation combinations were established to simulate annual runoff and runoff depth under different scenarios. The simulation shows that with the increasing of vegetation coverage annual runoff increases and evapotranspiration decreases in the basin. When temperature decreases by 2oC and precipitation increases by 20%, catchment runoff will increase by 39.69%, which is the largest situation among all scenarios.     

“探宝号”船可变阵列震源的实现及应用

2001年，广州海洋地质调查局对“探宝号”船原有震源更新升级为阵列可变的BOLT震源系统。随着更新改造工程的成功，该船已成为具备承担高分辨率、常规、低频深水油气地震勘探的多功能地震调查船。本文介绍了地震勘探震源的基本工作原理以及三种阵列的分布、波形、频谱等特性。     

Modelling surface runoff to evaluate the effects of wildfires in multiple semi‐arid,shrubland‐dominated catchments

Wildfires change the infiltration properties of soil, reduce the amount of interception and result in increased runoff. A wildfire at Northeast Attica, Central Greece, in August 2009, destroyed approximately one third of a study area consisting of a mixture of shrublands, pastures and pines. The present study simultaneously models multiple semi‐arid, shrubland‐dominated Mediterranean catchments and assesses the hydrological response (mean annual and monthly runoff and runoff coefficients) during the first few years following wildfires. A physically based, hydrological model (MIKE SHE) was chosen. Calibration and validation results of mean monthly discharge presented very good agreement with the observed data for the pre‐wildfire and post‐wildfire period for two subcatchments (Nash–Sutcliffe Efficiency coefficient of 79.7%). The model was then used to assess the pre‐wildfire and post‐wildfire runoff responses for each of seven catchments in the study area. Mean annual surface runoff increased for the first year and after the second year following the wildfires increased by 112% and 166%, respectively. These values are within the range observed in similar cases of monitored sites. This modelling approach may provide a way of prioritizing catchment selection with respect to post‐fire remediation activities. Additionally, this modelling assessment methodology would be valuable to other semi‐arid areas because it provides an important means for comprehensively assessing post‐wildfire response over large regions and therefore attempts to address some of the scaled issues in the specific literature field of research. Copyright © 2015 John Wiley & Sons, Ltd.     

The role of climate change and human interventions in affecting watershed runoff responses

Identifying the role of the two main driving factors—climate change and human interventions—in influencing runoff processes is essential for sustainable water resources management. For this purpose, runoff regime change detection methods were used to divide the available hydroclimatic variables into a baseline and a disturbed period. We applied hydrological modelling and the climate elasticity of runoff method to determine the contribution of climate change and human interventions to changes in runoff. The hydrological model, SWAT, was calibrated during the baseline period and used to simulate the naturalized runoff pattern for the disturbed period. Significant changes in runoff in the study watershed were detected from 1982, suggesting that human interventions play a dominant role in influencing runoff. The combined effects of climate change and human interventions resulted in a 41.3 mm (23.9%) decrease in runoff during the disturbed period, contributing about 40% and 60% to the total runoff change, respectively. Furthermore, analysis of changes in land cover dynamics in the watershed over the past four decades supported these changes in runoff. Contrary to other decades, the discrepancy between naturalized and observed runoff was small in the 2010s, likely due to increased baseflow as a result of storage and/or release of excess water during the dry season. This study contributes to our understanding of how climate change and human interventions affect hydrological responses of watersheds, which is important for future sustainable water management and drought adaptation.     

Using raw regional climate model outputs for quantifying climate change impacts on hydrology

General circulation model outputs are rarely used directly for quantifying climate change impacts on hydrology, due to their coarse resolution and inherent bias. Bias correction methods are usually applied to correct the statistical deviations of climate model outputs from the observed data. However, the use of bias correction methods for impact studies is often disputable, due to the lack of physical basis and the bias nonstationarity of climate model outputs. With the improvement in model resolution and reliability, it is now possible to investigate the direct use of regional climate model (RCM) outputs for impact studies. This study proposes an approach to use RCM simulations directly for quantifying the hydrological impacts of climate change over North America. With this method, a hydrological model (HSAMI) is specifically calibrated using the RCM simulations at the recent past period. The change in hydrological regimes for a future period (2041–2065) over the reference (1971–1995), simulated using bias‐corrected and nonbias‐corrected simulations, is compared using mean flow, spring high flow, and summer–autumn low flow as indicators. Three RCMs driven by three different general circulation models are used to investigate the uncertainty of hydrological simulations associated with the choice of a bias‐corrected or nonbias‐corrected RCM simulation. The results indicate that the uncertainty envelope is generally watershed and indicator dependent. It is difficult to draw a firm conclusion about whether one method is better than the other. In other words, the bias correction method could bring further uncertainty to future hydrological simulations, in addition to uncertainty related to the choice of a bias correction method. This implies that the nonbias‐corrected results should be provided to end users along with the bias‐corrected ones, along with a detailed explanation of the bias correction procedure. This information would be especially helpful to assist end users in making the most informed decisions.     

Soil property variation mapping through data mining of soil category maps

Spatial information on soil properties is an important input to hydrological models. In current hydrological modelling practices, soil property information is often derived from soil category maps by the linking method in which a representative soil property value is linked to each soil polygon. Limited by the area‐class nature of soil category maps, the derived soil property variation is discontinuous and less detailed than high resolution digital terrain or remote sensing data. This research proposed dmSoil, a data‐mining‐based approach to derive continuous and spatially detailed soil property information from soil category maps. First, the soil–environment relationships are extracted through data mining of a soil map. The similarity of the soil at each location to different soil types in the soil map is then estimated using the mined relationships. Prediction of soil property values at each location is made by combining the similarities of the soil at that location to different soil types and the representative soil property values of these soil types. The new approach was applied in the Raffelson Watershed and Pleasant Valley in the Driftless Area of Wisconsin, United States to map soil A horizon texture (in both areas) and depth to soil C horizon (in Pleasant Valley). The property maps from the dmSoil approach capture the spatial gradation and details of soil properties better than those from the linking method. The new approach also shows consistent accuracy improvement at validation points. In addition to the improved performances, the inputs for the dmSoil approach are easy to prepare, and the approach itself is simple to deploy. It provides an effective way to derive better soil property information from soil category maps for hydrological modelling. Copyright © 2014 John Wiley & Sons, Ltd.