基于区域特征相似度的微波土壤水分反演结果可信度评价

微波遥感反演土壤水分的精度评价,一般通过选取有限数量采样点的地表实测土壤水分数据与反演值进行比较,实际上只能反映局部采样区的反演精度。本文提出了微波反演土壤水分中一种可以评价整个研究区反演土壤水分可信程度的方法。首先选择采样区的实测土壤水分数据和地表粗糙度数据,通过多元回归统计拟合得到土壤水分反演经验方程,对整个研究区进行土壤水分反演;然后从TM和SAR数据中通过反演和提取,选择影响土壤水分的10个因子(土壤湿度、地表温度、NDVI、土壤质地指数、地形指数、雷达入射角以及Landsat TM的b3、b4、b5、b7共4个波段),采用主成分分析法(PCA)筛选提取主成分,将前3个主成分合成为RGB影像;再使用分水岭算法分割包含前3个主成分的RGB影像,得到一幅分割区域图;最后计算各分割区域的6维特征向量(土壤湿度、地表温度、NDVI、土壤质地指数、地形指数、雷达入射角)与反演时选择采样区的特征向量间的马氏距离,得到区域特征相似度数据集,基于该数据集计算反演结果可信度。以此为基础,利用2008年甘肃黑河地区的ENVISAT ASAR双极化数据(VV、VH)和实测土壤水分数据进行土壤水分反演并评价反演结果的可信度,同时使用反演区域中多个采样区土壤水分实测数据和确定系数(R2)评价反演精度,对比可信度和R2,表明提出的反演可信度可以有效反映土壤水分反演精度。     

基于分布式水文模拟的流域土壤水分时间稳定性分析

针对大范围地面土壤水监测会耗费大量人力物力等问题,为了获取密度较高同时又准确可靠的流域土壤水数据用于时间稳定性分析,寻找可以反映流域土壤水平均状况的代表性点,利用分布式水文土壤植被模型(DHSVM)模拟淮河黄泥庄水文站以上小流域293个采样网格上、中、下三层土壤含水量数据。结果显示:垂向方向上,黄泥庄流域土壤水分时间稳定性随深度递减;流域上层和中层具备时间稳定性特征的代表性点具有较高的一致性,易发生于流域主要土壤和植被类型覆盖区域,在此区域布设测点观测土壤水,可以更准确快速地捕获代表黄泥庄流域上层和中层平均土壤水分特征;采样点7、17和215可作为上、中层土壤的流域平均土壤水代表性点,利用它们预测流域土壤水平均值,可降低观测成本。研究成果可为流域土壤水监测方案设计提供参考。     

TM遥感影像监测裸露土壤含水率的方法研究

 土壤含水率是灌区干旱监测的重要指标。选择经济易得的遥感数据对灌区的土壤含水率进行定量监测,是非常具有实用价值的研究。采用地面光谱采样与土壤采样同步进行的方法,对漳河干渠最重要渠道——三干渠灌溉范围内的土壤水分状况进行了遥感定量分析,最终根据准同步遥感影像获得灌区表层土壤含水率分布图。     

考虑人类活动用水的土壤含水量神经网络反演

为在利用神经网络对地表土壤含水量的模拟中,实现对降水等天然要素和人类活动用水的综合考虑,以MPDI(modified perpendicular drought index)作为人类活动作用下的地表干湿状况指标,结合传统的天然要素构建土壤含水量神经网络模型,对河北省2018年地表土壤含水量进行了模拟.结果表明:考虑MP...     

地形指数与流域退水特征的关系分析

地形指数可反映流域土壤蓄水能力以及产流的空间分布,是表征流域水文相似性的一个重要指标。以新安江流域的8个子流域为研究对象,利用DEM提取了各子流域的地形指数,分析了地形指数与退水特征的关系。研究发现,地形指数均值及其标准差大的流域,其调蓄作用强,洪水退水指数较小,退水速率较慢,表明流域的地势起伏相对较小则含水层发育较好。通过研究,初步揭示了流域地形指数与退水特征之间存在的联系,成果可为新安江流域无资料区水文过程预测提供依据和参考。     

空间均化水文模型及其验证

本文基于空间均化方法构建了空间均化水文模型SAHM.该模型采用基于空间均化方法建立的宏观尺度水文控制方程描述了计算单元内入渗、壤中流和坡面汇流等基本水文过程,在方程中直接包含了土壤饱和导水率和微地形的空间非均匀性,使SAHM在保持传统"点"尺度方程机理性的同时从理论上避免了方程适用尺度和模型应用尺度的不匹配问题.模型在半干旱半湿润的沁河流域上游进行了验证,并对模型参数敏感性进行了分析,结果 表明,模型具有较高的计算精度和计算效率,可用于大中尺度流域水文模拟、水资源评价和洪水预报.     

基于子流域的TOPMODEL模拟研究

 TOPMODEL是根据水文相似性——地形指数相同的栅格划分为同一产流单元进行产流计算,但是其不能考虑降雨和地形指数统计分布曲线等流域地形地貌信息的空间不均匀性。通过对流域DEM处理,建立了基于水系子流域的TOPMODEL。该模型考虑了降雨、地形指数分布曲线等空间不均匀性。将基于子流域的TOPMODEL和TOPMODEL应用在九州流域,并进行模拟比较,发现基于子流域的TOPMODEL更能反映流域的实际情况,模拟的结果更加合理。可以预测不同子流域降雨组合下的流域出口的流量过程。     

Data Fusion Techniques for Improving Soil Moisture Deficit Using SMOS Satellite and WRF-NOAH Land Surface Model

Microwave remote sensing and mesoscale weather models have high potential to monitor global hydrological processes. The latest satellite soil moisture dedicated mission SMOS and WRF-NOAH Land Surface Model (WRF-NOAH LSM) provide a flow of coarse resolution soil moisture data, which may be useful data sources for hydrological applications. In this study, four data fusion techniques: Linear Weighted Algorithm (LWA), Multiple Linear Regression (MLR), Kalman Filter (KF) and Artificial Neural Network (ANN) are evaluated for Soil Moisture Deficit (SMD) estimation using the SMOS and WRF-NOAH LSM derived soil moisture. The first method (and most simplest) utilizes a series of simple combinations between SMOS and WRF-NOAH LSM soil moisture products, while the second uses a predictor equation generally formed by dependent variables (Probability Distributed Model based SMD) and independent predictors (SMOS and WRF-NOAH LSM). The third and fourth techniques are based on rigorous calibration and validation and need proper optimisation for the final outputs backboned by strong non-linear statistical analysis. The performances of all the techniques are validated against the probability distributed model based soil moisture deficit as benchmark; estimated using the ground based observed datasets. The observed high Nash Sutcliffe Efficiencies between the fused datasets with Probability Distribution Model clearly demonstrate an improved performance from the individual products. However, the overall analysis indicates a higher capability of ANN and KF for data fusion than the LWA or MLR approach. These techniques serve as one of the first demonstrations that there is hydrological relevant information in the coarse resolution SMOS satellite and WRF-NOAH LSM data, which could be used for hydrological applications.     

基于DEM的流域流水网对比分析

在广东西江中下游区间流域和长江三峡区间流域上 ,运用ARC/INFO和RiverTools ,由数字高程模型 (DEM )分别导出了不同空间比例尺下的流域流水网 .对比分析结果表明 :地形起伏大的流域上流水网的可靠性高 ;不同方法推导出的流水网存在一定的差异 ,尤其在地形起伏较小的流域上 ;由流水网计算的流域平均汇流路径长度和坡度等地形特征值随DEM网格的大小而变 ,故只能作为描述地形的相对指标 .上述指标可应用于流域水文模拟中 ,但应用时需考虑地形的起伏程度和DEM网格的大小 .     

Flood Modeling for Complex Terrain Using GIS and Remote Sensed Information

A spatially distributed hydrological model WetSpa (Water and Energy Transfer between Soil, Plants and Atmosphere) working on an hourly time scale is presented in this paper. The model combines elevation, soil and land use data, and predicts flood hydrograph and the spatial distribution of hydrological characteristics in a watershed. The model is tested on a small catchment in Belgium for which topography and soil data are available in GIS form, while the land use and soil cover is obtained from remote sensed images. The resulting calculated discharges compare favorably with the field measurements. Next a 102-year series of measured hourly precipitation data is processed with the model and the resulting hydrographs are analyzed statistically to determine the characteristics of extreme floods. Finally, the simulated extreme peak discharges are compared to the results calculated with design storms. Comparison of the two methods shows that the model is capable to predict both normal and extreme floods. Since the model accounts for spatially distributed hydrological and geophysical characteristics of the catchment, it is suitable for simulating hydrological processes in a complex terrain and for predicting the influence of changes in land use on the hydrological behavior of a river basin.     

数值地形图的生成及其水文地貌特征评价

数值地形图(DEM)是利用地理信息系统(GIS)进行流域水文模拟的基础, 其精度直接影响模拟结果在没有现成的数值地形图时, 应用人员往往利用传统的地形图来生成它. 本文分别采用Arc/Info地理信息系统软件提供的哈奇逊法和不规则三角网五次插值法, 对一个实验流域的高程取样点进行插值, 生成了4种不同的数值地形图, 从凹洼分布、流域界定、河网提取、地面坡度和地形指数、以及地面径流汇成等方面, 对它们的水文地貌精度进行了比较. 结果表明, 两种方法都能生成由高程点群所反映的地形, 然而由于哈奇逊法能够结合流域的河网结构及其具有物理基础的水文地貌加强法来处理凹洼问题, 因此大大地提高了其所生成的流域数值地形图水文地貌特征精度.     

Statistical Modelling of Vertical Soil Moisture Profile: Coupling of Memory and Forcing

Information of Soil Moisture Content (SMC) at different depths i.e. vertical Soil Moisture (SM) profile is important as it influences several hydrological processes. In the era of microwave remote sensing, spatial distribution of soil moisture information can be retrieved from satellite data for large basins. However, satellite data can provide only the surface (~0–10?cm) soil moisture information. In this study, a methodological framework is proposed to estimate the vertical SM profile knowing the information of SMC at surface layer. The approach is developed by coupling the memory component of SMC within a layer and the forcing component from soil layer lying above by an Auto-Regressive model with an exogenous input (ARX) where forcing component is the exogenous input. The study highlights the mutual reliance between SMC at different depths at a given location assuming the ground water table is much below the study domain. The methodology is demonstrated for three depths: 25, 50 and 80?cm using SMC values of 10?cm depth. Model performance is promising for all three depths. It is further observed that forcing is predominant than memory for near surface layers than deeper layers. With increase in depth, contribution of SM memory increases and forcing dissipates. Potential of the proposed methodology shows some promise to integrate satellite estimated surface soil moisture maps to prepare a fine resolution, 3-dimensional soil moisture profile for large areas, which is kept as future scope of this study.     

Evaluation of Multiple Satellite-Based Soil Moisture Products over Continental U.S. Based on In Situ Measurements

Measurements of soil water content are of great importance for climatic researches and hydrological applications. Satellite remote sensing techniques have provided convenient access to global soil moisture data at high temporal resolution. The evaluation of remotely sensed soil moisture products from multiple sensors are fundamental for understanding the quality and usefulness of the products and are helpful for the improvements of the retrieval algorithms. In this study, we evaluated four satellite-based soil moisture products against two in situ networks over continental U.S. These products are the Soil Moisture and Ocean Salinity (SMOS), the Advanced Microwave Scanning Radiometer for the Earth observing system (AMSR-E), the Fengyun-3B/Microwave Radiation Imager (FY-3B/MWRI), and the Essential Climate Variable (ECV) soil moisture products. The evaluation results show that the temporal characteristics of ECV and SMOS soil moisture products are consistent with those of in situ measurements. Larger errors and bias exist in AMSR-E and FY-3B/MWRI over the study region. In general, the ECV product performs the best comparing with other products. Therefore, the ECV product is recommended in regional hydrological applications and water resource management over the continental U.S. for its good performance in absolute values and soil moisture anomalies.     

影响黄土丘陵区次降水泥沙输移比的水文要素

以桥沟小流域为研究对象,利用该流域不同地貌部位的野外径流场及沟道水文站网观测资料,计算了不同场次降水的泥沙输移比,较为系统地研究了影响桥沟流域次降水泥沙输移比的水文要素。结果表明:土壤前期含水量、流域的降水过程特征、洪峰流量、径流量、水流含沙量是影响次降水泥沙输移比的主要水文要素;提出了表示降水、径流、泥沙对泥沙输移比影响的表征参数,即降水峰现系数、径流侵蚀力和泥沙相对容重。     

土壤水分空间变异的套合结构模型及区域信息估值

本文运用线性地质统计理论，确定研究区域的半变异函数二维平面结构为带状各向异性套合结构模型，给出土壤水分区域估值合理采样数，将Ｋｒｉｇｉｎｇ最优内插无偏估计法扩展为待估域的土壤水分含量外延估计，通过模糊聚类分析，绘制区域土壤水分含量的信息分布图，可为灌区水资源的计算机管理及灌区土壤水分监测预报提供依据。     

利用双抛物线型土壤蓄水容量曲线对新安江产流模型的改进

提出了双抛物线型土壤蓄水容量关系曲线，对新安江模型产流计算公式进行了改进。利用珠江三角洲不同土壤水分状态的多年水文资料，对改进前和改进后新安江模型产流计算公式进行了比较。结果表明，双抛物线型关系曲线能够代表流域中多种土壤水分状态并存的情况，包括湿润、干燥以及从湿润到干燥过渡阶段，而原单抛线型的模型则是双抛物线的一个特例，只能反映单一土壤水分状态的分布。对于那些发生在湿润季节的暴雨，两种曲线的模拟精度相当，但对于发生在旱季及旱湿过渡时期的暴雨，双抛物线明显优于单抛物线。     

蓄水容量曲线设定分布式霍顿模型土壤含水量初值

分布式水文模型对土壤含水量的空间描述能力对土壤墒情模拟、分布式输出等具有重要的意义。但分布式水文模型的土壤含水量空间分布计算,需耗费大量的计算资源。为了提高分布式模型的计算效率,从定性的理论分析和定量的数据比对2个方面,证明蓄水容量曲线和分布式模型中逐单元土壤含水量序列的相关关系,并建立了二者之间的转换公式,据此可以将面平均的土壤含水量转换为空间分布的土壤含水量。用离散蓄水容量曲线法设置分布式模型的土壤含水量初值,并与传统模型预热法进行比较,结果表明两种方法得到的土壤含水量空间分布总体趋势完全一致,次洪模拟效果相同,并且节省了大量的计算资源,极大地提高了分布式模型的计算效率。     

基于水文应用的多源数字高程模型精度分析

天空地监测技术的迅速发展使得可免费获取的地形数据越来越多,而不同地形数据的精度和现势性制约着水文科学的创新和发展。收集目前可免费获取的数字高程模型,基于分辨率、现势性、覆盖范围等属性筛选出SRTM、ASTER2 GDEM和ALOS World 3D三类数据源为研究对象,针对不同地形地貌区,计算分析与水文密切相关的DEM衍生特征的精度,进而提出不同数字高程模型在水文应用中的适用范围。经分析:各DEM在地势起伏大的区域,地形宏观描述基本一致;地势起伏小的区域,Aster2 DEM与其他三种DEM存在差异;在中小河流洪水预报的经验模型中,根据资料情况利用任何一种数字高程模型提取流域参数均可,不作为影响模型精度的重要指标。在地势起伏大的地区,除SRTM外各DEM对水系形态的描述精度较高;地势起伏小的地区,除ALOS world 3D能准确描述河口区域水系结构关系外,其余DEM均不能准确描述河口区域水系形态;分布式水文模型的产汇流分析、水文通视性分析等建议使用ALOS world 3D。     

Potential implications of pre-storm soil moisture on hydrological prediction

Numerous hydrological models with various complexities, strengths, and weaknesses are available. Despite technological development, the association of runoff accuracy with the underlying model's parameters in watersheds with limited data remains elusive. Evaluating the soil moisture impacts at the watershed scale is often a difficult task, but it can be vital to optimally managing water resources. Incorporating pre-storm soil moisture accounting (PSMA) procedures into hydrologic models affects the watershed response to generate runoff from storm rainfall. This study demonstrated the impact of pre-storm and post-storm soil moisture in order to circumvent major obstacles in accurate runoff estimation from watersheds employing the conventional curve number (CN) model. The proposed hydrological lumped model was tested on a data set (1,804 rainfall-runoff events) from 39 watersheds in South Korea. Its superior performance indicates that the reconciliation of pre- and post-storm conceptualization has the potential to be a solution for efficient hydrological predictions and to demonstrate the complex and dynamic nature of tractable hydrological processes. The statistically significant results reveal that the proposed model can more effectively predict runoff from watersheds in the study area than the conventional CN model and its previously proposed modifications.