水文循环模拟中下垫面参数化方法综述

针对水文循环模拟中地形、土地利用覆被等流域下垫面参数化方法众多,且模拟效果相差较大的现状。本文首先根据水文循环模拟中产汇流原理,对常用水文循环模拟中产汇流模拟方法进行汇总和分类;在此基础上,对产流模拟中的降水径流相关系数法、蓄满产流和超渗产流等及汇流模拟中的等流时线、单位线、圣维南方程、马斯京根法等主要模拟方法中地形、土地利用覆被和土壤类型参数化方法进行分析和讨论;根据其中流域地形、土地利用覆被和土壤类型参数化方法对机理过程的描述程度,将其分为无明确表示类、率定型参数类、确定型参数类、物理过程表达类;进而阐明不同参数化方法中流域地形、土地利用覆被和土壤类型对水文循环模拟结果的响应和贡献。最后回归模型本质,阐述水文循环模拟中流域下垫面参数化方法中存在经验关系对复杂机理简单表述的合理性和物理机理过程描述的欠缺性问题,并预估未来水文循环模拟中下垫面参数化方法朝着简洁实用化和复杂机理化两个方向发展。     

Thermal Remote Sensing of Near Surface Environmental Variables: Application Over the Oklahoma Mesonet

Many recent studies have applied satellite remote sensing data to large‐scale hydrologic and biospheric modeling. It is widely accepted that the thermal infrared observations from the Advanced Very High Resolution Radiometer (AVHRR) have the potential to estimate land surface conditions, such as surface temperature, near surface air temperature, and near surface water vapor. In this study, algorithms to estimate all three variables are presented and applied to an area covering the state of Oklahoma for a six day period in August, 1994. The results were validated using ground observations from the 111 station Oklahoma Mesonet. Validation of the remote sensing algorithms with Mesonet observations produced comparable results to previous validation studies. In addition, the validation process revealed inadequacies in thermal modeling that had not been detected in previous validation studies leading to the development of a new approach to estimate atmospheric water vapor.     

小波分析方法在水文学研究中的应用现状及展望

本文首先介绍了小波分析的基本方法,主要包括小波函数、小波变换和小波消噪等。然后从6个方面,即基于连续小波变换的水文序列多时间尺度变化特性分析、基于离散小波变换的水文序列分解和重构、水文过程复杂性定量描述、水文序列小波消噪、水文序列小波互相关分析和基于小波方法的水文序列模拟预报技术,综述了小波分析方法在水文学各领域的研究应用现状和主要不足,以及存在的关键和难点问题。最后,对小波分析方法在今后的水文学研究中的应用进行了展望,并就小波函数选择、小波阈值消噪、小波分解、小波互相关分析、水文序列小波预报等具体问题提出了建议。     

The reliability of an 'off-the-shelf' conceptual rainfall runoff model for use in climate impact assessment: uncertainty quantification using Latin hypercube sampling

Much uncertainty is derived from the application of conceptual rainfall runoff models. In this paper, HYSIM, an 'off-the-shelf' conceptual rainfall runoff model, is applied to a suite of catchments throughout Ireland in preparation for use in climate impact assessment. Parameter uncertainty is assessed using the GLUE methodology. Given the lack of source code available for the model, parameter sampling is carried out using Latin hypercube sampling. Uncertainty bounds are constructed for model output. These bounds will be used to quantify uncertainty in future simulations as they include error derived from data measurement, model structure and parameterization.     

A total water management analysis of the Las Vegas Wash watershed,Nevada

Climate change, land-use change, and population growth are fundamental factors affecting future hydrologic conditions in streams, especially in arid regions with scarce water resources. Located in the arid southwest within the Las Vegas Wash watershed, Las Vegas is one of the fastest growing metropolitan areas of the country. In the past 30?years, because of climate and land-use changes, it has experienced a decrease in clean water supply but an increase in water demand. To alleviate some of these problems, large amounts of water have been pumped into the city from different sources, such as Lake Mead, and the urban wastewater is treated and returned back to the reservoir for water augmentation. However, in the face of continual global climate change and urbanization in the watershed, long-term planning for sustainable water management is critical. This research was designed to provide a comprehensive analysis incorporating hydrologic modeling, population projection, land-use change modeling, and water management policies to examine the total water balance and management options in this arid and rapidly urbanizing watershed under various scenarios of climate regime, population growth, land-use change, and total water management programs for the year 2050.     

Predicting landscape sensitivity to present and future floods in the Pacific Northwest,USA

Floods are the most frequent natural disaster, causing more loss of life and property than any other in the USA. Floods also strongly influence the structure and function of watersheds, stream channels, and aquatic ecosystems. The Pacific Northwest is particularly vulnerable to climatically driven changes in flood frequency and magnitude, because snowpacks that strongly influence flood generation are near the freezing point and thus sensitive to small changes in temperature. To improve predictions of future flooding potential and inform strategies to adapt to these changes, we mapped the sensitivity of landscapes to changes in peak flows due to climate warming across Oregon and Washington. We first developed principal component‐based models for predicting peak flows across a range of recurrence intervals (2‐, 10‐, 25‐, 50‐, and 100‐years) based on historical instantaneous peak flow data from 1000 gauged watersheds in Oregon and Washington. Key predictors of peak flows included drainage area and principal component scores for climate, land cover, soil, and topographic metrics. We then used these regression models to predict future peak flows by perturbing the climate variables based on future climate projections (2020s, 2040s, and 2080s) for the A1B emission scenario. For each recurrence interval, peak flow sensitivities were computed as the ratio of future to current peak flow magnitudes. Our analysis suggests that temperature‐induced changes in snowpack dynamics will result in large (>30–40%) increases in peak flow magnitude in some areas, principally the Cascades, Olympics, and Blue Mountains and parts of the western edge of the Rocky Mountains. Flood generation processes in lower elevation areas are less likely to be affected, but some of these areas may be impacted by floodwaters from upstream. These results can assist land, water, and infrastructure managers in identifying watersheds and resources that are particularly vulnerable to increased peak flows and developing plans to increase their resilience. Copyright © 2015 John Wiley & Sons, Ltd.     

岷江上游森林水文效应研究

本文提出了用一般性流域水文模型研究森林水文效应的途径。得出在岷江上游地区随着覆盖率的下降年径流量减少、径流成份改变、年风分配更趋不均匀和洪峰流量增大的结论。在此基础上，预测了岷江上游地区水源涵养林建设的水文效益与前景。     

西北内陆平原水资源开发引起的区域水文效应及其对环境的影响

内陆平原水资源主要的赋存形式是河流-含水层系统。无论是开发利用河水,还是开采地下水,都将引起区域性的水文效应——地下水位大幅度波动、泉水衰竭和水质恶化。在水资源开发条件下,人工绿洲与天然绿洲之间的水源分配是彼长此消的,防止生态环境退化的要义在于:从宏观上合理配置水源,并可靠地预测其可能引起的区域水文效应,防患于未然。     

考虑抽样不确定性的水文设计值估计

水文频率分析计算过程中,水文极值样本系列容量一般都较小、代表性不高,使得水文设计值估计具有不确定性。利用Bootstrap方法,研究样本抽样不确定性对水文设计值的影响。与传统水文频率分析方法相比,基于Bootstrap方法不仅可提供设计值的点估计和区间估计,同时能够对设计值的不确定性进行定量评价。此外,基于Bootstrap技术,结合矩法、权函数法及线性矩法,设置3套方案,分析了该方法在不同参数估计方法间的有效性。以南通市1970-2011年共42年的年降雨量数据资料为例,对所提方法进行实例应用分析,结果表明,从期望设计值、90%置信区间及最终设计值角度而言,基于所提方法的设计成果受参数估计方法的选取影响不大,且可回避规范中B值诺莫图通用性较差及误差显著问题。