基于水文模型的蒸散发数据同化研究进展

本文系统综述了基于水文模型的蒸散发数据同化研究,阐述了蒸散发作为非状态变量构建数据同化演算关系的难点和瓶颈,并系统分析了利用当前各种通用水文模型进行蒸散发同化的可行性.基于此,尝试提出了一种易于操作且具有水循环物理机制的蒸散发同化新方案,该方案利用具有蒸散发—土壤湿度非线性时间响应关系的分布式时变增益模型(DTVGM),并进一步完善DTVGM蒸散发机理,构建基于DTVGM水文模型的蒸散发数据同化系统.该新方案将为区域蒸散发精确模拟提供新的思路和借鉴.     

水文循环模拟中蒸散发估算方法综述

为选取基于水文循环估算蒸散发方法提供依据, 首先对常用水文模型中蒸散发估算方法进行回顾, 根据其物理机理的强弱性, 将水文模型中蒸散估算方法分为整体折算法和分类汇总法。当前水文模型中整体折算法占较大比重, 它们之间的差异有两点:一是潜在蒸散发估算方法不同;二是土壤干燥度折算函数不同;研究表明:由于水文模型存在不确定性及Penman-Monteith 方法具有较高资料要求, 致使模拟中使用该方法与使用其它简化经验公式相似或更差的水文循环模拟效果。所以对于不同水文模型, 如何选取与之复杂程度相兼容的潜在蒸散发估算方程和土壤干燥度折算函数来降低模型的不确定性需进一步讨论。在此基础上, 预估基于水文循环估算蒸散发方法朝着复杂机理化和简单实用化两个方向发展。     

基于遥感数据的叶尔羌河流域水文过程模拟与分析

在西北荒漠-绿洲生态系统中,山区水循环对下游水资源管理具有重要作用。为了准确地理解高寒山区水文过程,以降水、温度和潜在蒸散发的遥感数据为模型输入,建立叶尔羌河流域的MIKE SHE模型。根据模型输出,从径流、积雪和蒸散发三方面探讨了流域的水文过程。结果表明：经校正后的遥感产品在叶尔羌河流域的水文模拟中取得了良好的应用效果,出山口卡群站日径流的效率系数达0.71,相关系数达0.85。河道的年平均径流深为146.66 mm,其中稳定的基流补给占21.3%。流域的年平均降雪231 mm,占总降水的74%左右;73.9%的融雪发生在7-9月,积雪主要分布于5000 m以上区域。蒸散发以7-9月中低山区植被覆盖良好的针叶林和草地为主。选用合适的方法对遥感数据进行验证和率定,有助于提高对资料缺失的高寒山区流域水文过程的认识。对不同水文要素进行分析验证,可更准确地理解水资源的转化、储存方式及其时空分布,以便为下游水资源管理提供依据。     

分布式水文模型的并行计算研究进展

大流域、高分辨率、多过程耦合的分布式水文模拟计算量巨大,传统串行计算技术不能满足其对计算能力的需求,因此需要借助于并行计算的支持。本文首先从空间、时间和子过程三个角度对分布式水文模型的可并行性进行了分析,指出空间分解的方式是分布式水文模型并行计算的首选方式,并从空间分解的角度对水文子过程计算方法和分布式水文模型进行了分类。然后对分布式水文模型的并行计算研究现状进行了总结。其中,在空间分解方式的并行计算方面,现有研究大多以子流域作为并行计算的基本调度单元;在时间角度的并行计算方面,有学者对时空域双重离散的并行计算方法进行了初步研究。最后,从并行算法设计、流域系统综合模拟的并行计算框架和支持并行计算的高性能数据读写方法3个方面讨论了当前存在的关键问题和未来的发展方向。     

水文循环模拟中蒸散发估算方法综述(英文)

Actual evapotranspiration is a key process of hydrological cycle and a sole term that links land surface water balance and land surface energy balance.Evapotranspiration plays a key role in simulating hydrological effect of climate change,and a review of evapotranspiration estimation methods in hydrological models is of vital importance.This paper firstly summarizes the evapotranspiration estimation methods applied in hydrological models and then classifies them into the integrated converting methods and the classification gathering methods by their mechanism.Integrated converting methods are usually used in hydrological models and two differences exist among them:one is in the potential evaporation estimation methods,while the other in the function for defining relationship between potential evaporation and actual evapotranspiration.Due to the higher information requirements of the Penman-Monteith method and the existing data uncertainty,simplified empirical methods for calculating potential and actual evapotranspiration are widely used in hydrological models.Different evapotranspiration calculation methods are used depending on the complexity of the hydrological model,and importance and difficulty in the selection of the most suitable evapotranspiration methods is discussed.Finally,this paper points out the prospective development trends of the evapotranspiration estimating methods in hydrological modeling.     

基于ETM+与MODIS数据融合的伊洛河流域地表蒸散估算

MODIS数据时间分辨率较高,在对地能量和水分变化监测应用中具有不可比拟的优势。但其空间分辨率较低,混合象元效应显著,尤其在地表土地利用类型复杂和空间异质性较大时,会带来较大的误差。而ETM+数据具备较高的空间分辨率,但其单一的热红外波段导致反演的地表温度精度不高,且时间分辨率低,因而限制了在地表蒸散监测中的应用。本文探讨了将TM/ETM+与MODIS数据相融合估算区域地表蒸散的一种多尺度遥感方法,利用TM/ETM+计算得到的植被指数,基于空间增强方法将MODIS反演的地表温度尺度提高到30 m,并结合SEBS模型对伊洛河流域的地表蒸散进行了估算。验证与分析的结果表明,估算精度得到提高,研究区当日蒸散量在0～5.32 mm/d之间,空间分布具有明显的地域性差异,区域分布不均衡。     

基于SWH模型的青藏高原高寒草甸蒸散发及其组分变化分析

基于Shuttleworth-Wallace Hu（SWH）双源蒸散模型对青藏高原那曲、纳木错、藏东南站蒸散发进行估算,在结果验证良好基础上,对青藏高原蒸散发变化特征及各站主要影响因素进行了分析。结果表明：SWH模型在青藏高原3个草甸站适用性良好;年蒸散发介于388~732 mm之间,年内分布呈先增大后减小特征;3站蒸散发组分差异较大,那曲站和纳木错站土壤蒸发对蒸散总量的贡献分别为53%和56%,藏东南站蒸散发则几乎全部由植被蒸腾贡献,占比高达95%;植被叶面积指数为3站蒸散发最主要的影响因素,饱和水汽压差对藏东南站蒸散发影响也较大。研究结果可对青藏高原蒸散发及其组分时空格局与水循环过程研究提供科学依据。     

基于Hargreaves-Samani回归修正的作物参考蒸散发计算适用性研究

为提高Hargreaves-Samani（H-S）模型计算参考蒸散发的精度,利用西北黄河流域与长江中下游平原共128个气象站点1961—2010年的逐日气象资料对H-S模型进行回归修正,以Penman-Monteith（P-M）模型为标准,评价了H-S改进模型H-S_CORR模型的计算精度,并且以第六次国际耦合模式比较计划（CMIP6）气候模式来对H-S_CORR模型进行了未来适应性评价。结果表明：修正后,在验证期内,长江中下游平原4个分区的平均绝对误差（MAE）和均方根误差（RMSE）的平均值分别下降了6.21 mm·月^-1和6.38 mm·月^-1;西北黄河流域4个分区的MAE和RMSE的平均值分别下降了9.26 mm·月^-1和9.23 mm·月^-1,2个研究区域修正后的决定系数（R²）比修正前最少提高1%。在CMIP6气候模式的未来气候情景下R²均达到0.98以上,具有良好的适应性。该研究修正的模型方法可为仅有气温数据的地区提供较高精度的参考蒸散发估算方法,为高频灌溉提供较为准确的数据基础。     

Cryosphere evapotranspiration in the Tibetan Plateau: A review

Land surface actual evapotranspiration is an important process that influences the Earth's energy and water cycles and determines the water and heat transfer in the soil-vegetation-atmosphere system. Meanwhile, the cryosphere's hydrological process is receiving extensive attention, and its water problem needs to be understood from multiple perspectives. As the main part of the Chinese cryosphere, the Tibetan Plateau faces significant climate and environmental change. There are active interaction and pronounced feedback between the environment and ET_a in the cryosphere. This article mainly focuses on the research progress of ET_a in the Tibetan Plateau. It first reviews the ET_a process, characteristics, and impact factors of typical underlying surfaces in the Tibetan Plateau (alpine meadows, alpine steppes, alpine wetlands, alpine forests, lakes). Then it compares the temporal and spatial variations of ET_a at different scales. In addition, considering the current greening of cryosphere vegetation due to climate change, it discusses the relationship between vegetation greening and transpiration to help clarify how vegetation activities are related to the regional water cycle and surface energy budget.     

水文模型参数敏感性分析—优化—区域化方法研究进展

水文模型是认识水文科学规律、分析水文过程及研究水文循环机理的重要科学工具。水文模型模拟结果的不确定分析是提高模型可靠性、进行有效水情预报的一个重要研究内容。参数不确定性是影响水文模型模拟结果不确定性的关键因素之一,开展模型参数不确定性及其影响因素分析对水文预报具有重要现实意义。目前的参数不确定性分析方法大致可分为3类：参数敏感性分析、参数优化以及考虑无资料流域参数值估计的参数区域化方法。论文归纳总结了近年来国内外水文模型参数不确定性分析工作的主要研究进展,分析了不同方法的优点与不足,提出了未来水文模型不确定性分析方法研究的潜在发展方向。借助多学科理论和技术方法,加强水文模型不确定性分析系统性方法的研究,是水文学科当前的迫切需求及发展趋势。     

Implications of diurnal variations in land surface temperature to data assimilation using MODIS LST data

Based on the Beijing Climate Center's land surface model BCC_AVIM(Beijing Climate Center Atmosphere-Vegetation Interaction Model), the ensemble Kalman filter(En KF) algorithm has been used to perform an assimilation experiment on the Moderate Resolution Imaging Spectroradiometer(MODIS) land surface temperature(LST) product to study the influence of satellite LST data frequencies on surface temperature data assimilations. The assimilation results have been independently tested and evaluated by Global Land Data Assimilation System(GLDAS) LST products. The results show that the assimilation scheme can effectively reduce the BCC_AVIM model simulation bias and the assimilation results reflect more reasonable spatial and temporal distributions. Diurnal variation information in the observation data has a significant effect on the assimilation results. Assimilating LST data that contain diurnal variation information can further improve the accuracy of the assimilation analysis. Overall, when assimilation is performed using observation data at 6-hour intervals, a relatively good assimilation result can be obtained, indicated by smaller bias(2.2 K) and root-mean-square-error(RMSE)(3.7 K) and correlation coefficients larger than 0.60. Conversely, the assimilation using 24-hour data generally showed larger bias(2.2 K) and RMSE(4 K). Further analysis showed that the sensitivity of assimilation effect to diurnal variations in LST varies with time and space. The assimilation using observations with a time interval of 3 hours has the smallest bias in Oceania and Africa(both1 K); the use of 24-hour interval observation data for assimilation produces the smallest bias(2.2 K) in March, April and July.     

Evaluating the suitability of TRMM satellite rainfall data for hydrological simulation using a distributed hydrological model in the Weihe River catchment in China

The objective of this study is to quantitatively evaluate Tropical Rainfall Measuring Mission (TRMM) data with rain gauge data and further to use this TRMM data to drive a Distributed Time-Variant Gain Model (DTVGM) to perform hydrological simulations in the semi-humid Weihe River catchment in China. Before the simulations, a comparison with a 10-year (2001-2010) daily rain gauge data set reveals that, at daily time step, TRMM rainfall data are better at capturing rain occurrence and mean values than rainfall extremes. On a monthly time scale, good linear relationships between TRMM and rain gauge rainfall data are found, with determination coefficients R² varying between 0.78 and 0.89 for the individual stations. Subsequent simulation results of seven years (2001-2007) of data on daily hydrological processes confirm that the DTVGM when calibrated by rain gauge data performs better than when calibrated by TRMM data, but the performance of the simulation driven by TRMM data is better than that driven by gauge data on a monthly time scale. The results thus suggest that TRMM rainfall data are more suitable for monthly streamflow simulation in the study area, and that, when the effects of recalibration and the results for water balance components are also taken into account, the TRMM 3B42-V7 product has the potential to perform well in similar basins.     

基于台站和MOD16数据的山东省蒸散及潜在蒸散时空变化

蒸散发的时空格局分析对理解气候变化与水资源之间的相互影响具有重要的作用。本文基于Penman-Monteith公式,利用MODIS全球蒸散发产品(MOD16)及气象站点的蒸发皿观测数据,先对数据精度进行评价,再从空间和时间两个尺度上对数据进行统计分析,系统阐释了2000-2014年山东省地表蒸散(ET)及潜在蒸散(PET)的时空分布特征及其与气象因子的相关性。主要结论为：①山东省不同区域蒸散分布差异明显,地表植被对ET的月际变化趋势有重要影响;②山东省ET及PET年际波动不大,全省ET均值为1529 mm,PET均值为2178 mm,年均ET与PET相对较大的差值说明该省整体相对缺水。③ET及PET的时空变化与诸多气象因子相关,其中与降水及温度的关系最为密切。     

基于DEM的清水河分布式水文模型

对于以冰雪融水和雨水混合补给为主的西北山区流域,需要结合山区特点建立分布式水文模型。通过取塔里木河流域中的清水河水系为研究区域,采用300 m×300 m DEM数据进行流域河网水系提取,同时用DEM数据对参数进行分布式异化,建立冰雪融水与降雨相结合的分布式水文模型。分析模拟结果表明:夏季模拟径流主峰值与实测径流值较为接近,而冬春季节两者之间的差别较大,反映了西北山区流域冰雪融水和雨水混合补给为主的特点;进而开拓塔里木河区域应用该类模型的可行性。     

基于MOD16的山西省地表蒸散发时空变化特征分析

基于MOD16全球蒸散发产品和气象站点实测数据,运用变异系数法、Sen趋势法等研究了山西省2000—2014年地表蒸散发ET、潜在蒸散发PET的空间分布特征、变化趋势及影响因素。结果表明：① MOD16蒸散产品与气象站点实测蒸散发之间具有良好的时空相关性(R ²=0.90),其产品精度可以满足山西省蒸散发时空分布研究的要求;②山西省多年平均ET、PET分别为816.77、1608.46 mm,年内变化表现为先增高后下降的“单峰”型分布,二者差值在5月、6月最大,此时山西省最为干旱;③ 全省年平均ET呈现西北低、东南高的分布特征,PET呈西南高、东北低的分布特征,二者差值整体上较大,表现为全省地表水分比较缺乏,其中忻州、吕梁西部最为严重;④ 全省近15 a来ET和PET的年际变化都比较小,整体上全省PET在增加,ET在相对减少,意味着近15 a来干旱情况在加剧;⑤ ET、PET的时空变化与诸多气象因子相关,在空间尺度上与降水、相对湿度密切相关,在时间尺度上与气温、降水关系最为密切。     

基于MODIS数据的无定河流域蒸散模拟

利用黄土高原无定河流域水文气象资料、MODIS数据及GIS背景信息,应用分布式生态水文模型（VIP模型）,按250m空间分辨率模拟了该流域水量平衡各分量的时空分布。结果表明:2000²003年无定河流域年蒸散量分别为300 mm、397 mm、460 mm和443 mm;流域蒸散有明显的由南向北,由东到西的梯度递减特征,降水量和地表植被覆盖度的差异是其空间变异的主要因素;蒸腾与蒸发空间分异显著,但两者的变化相互补偿,降低了蒸散的空间变异性。整个流域平均而言,不同植被类型间的年蒸散总量差异不明显。白家川等9个子流域年蒸散量的模拟结果与水量平衡法估计结果具有较好的一致性。     

集成遥感数据的陆地净初级生产力估算模型研究综述

净初级生产力(NPP)是衡量碳循环、指导土地利用、评估生态安全、指示环境变化、反映粮食安全等的重要参量,其估算受模型构建机理和生态系统关键地表参数输入的影响。近年来,随着遥感数据的不断丰富和遥感处理技术的快速发展,集成遥感数据的NPP估算模型相较于仅采用气候、土壤等传统观测数据的非遥感模型,在分析时空异质性等方面的优势日益凸显。本文基于Web of Science和CNKI两大数据库,采用文献统计分析方法,系统回顾NPP研究概况及国内外集成遥感数据的NPP估算模型的近期进展;并将集成遥感数据进行NPP估算的模型分为统计模型、光能利用率模型、过程模型及耦合模型四类;重点阐述了各类遥感估算模型的机理、差异性、适宜性及局限性;最后,在分析NPP遥感估算面临困境和科学挑战的基础上,从机理与影响因素、数据基础、参数反演、时空尺度拓展、软硬件支撑等方面对未来研究进行了展望。     

基于遥感的黄河三角洲蒸散的动态分析

Evapotranspiration (ET) is an important parameter for water resource management. Compared to the traditional ET computation and measurement methods, the ET computation method based on remote sensing has the advantages of quickness, precision, raster mapping and regional scale. SEBAL, an ET computation model using remote sensing method is based on the surface energy balance equation which is a function of net radiance flux, soil heat flux, sensible heat flux and latent heat flux. The former three fluxes can be computed through the parameters retrieved from remote sensing image, then the latent heat flux can be obtained to provide energy for ET. Finally we can obtain the daily ET. In this study SEBAL was applied to compute ET in the Yellow River Delta of China where water resource faces a rigorous situation. Three Landsat TM images and meteorology data of 1999 were used for ET computation, and spatial and temporal change patterns of ET in the Yellow River Delta were analysed.     

Dynamic analysis of evapotranspiration based on remote sensing in Yellow River Delta

Evapotranspiration (ET) is an important parameter for water resource management. Compared to the traditional ET computation and measurement methods, the ET computation method based on remote sensing has the advantages of quickness, precision, raster mapping and regional scale. SEBAL, an ET computation model using remote sensing method is based on the surface energy balance equation which is a function of net radiance flux, soil heat flux, sensible heat flux and latent heat flux. The former three fluxes can be computed through the parameters retrieved from remote sensing image, then the latent heat flux can be obtained to provide energy for ET. Finally we can obtain the daily ET. In this study SEBAL was applied to compute ET in the Yellow River Delta of China where water resource faces a rigorous situation. Three Landsat TM images and meteorology data of 1999 were used for ET computation, and spatial and temporal change patterns of ET in the Yellow River Delta were analysed.