多源遥感驱动的SRM模型在缺资料地区的研究及应用

以MODIS雪盖、风云静止卫星降水、GLDAS气温等多源数据,作为传统SRM模型的输入参数,构建多源遥感驱动的SRM融雪径流模型,并在缺资料地区——青藏高原的年楚河流域进行融雪过程的径流模拟。研究表明融雪后期的瞬时降雪很大程度上影响了插值后积雪覆盖率的精度,在插值的时候考虑降水和气温,排除瞬时积雪干扰,改进线性插值获得每天的积雪覆盖率,可以提高模型模拟精度;遥感驱动的SRM模型在缺资料地区年楚河适用性较好,Nash-Sutcliffe系数(NSE)达到0.681,体积差(Dv)为-0.17%,均方根误差(RMSE)为9.678,模型模拟的精度较高。研究结果可为高寒地区生态水文模型研究提供重要参考,同时可为SRM模型在其他流域尤其是缺资料地区融雪径流计算中的应用提供有效支撑。     

A fast mobile early warning system for water quality emergency risk in ungauged river basins

Environmental decision support system (EDSS) has become an important research topic in the fields of water environment protection and emergency early warning. Most existing systems require plenty of measured data, which are typically unavailable in ungauged basins. In order to develop an early warning system that can work with few measured data, a mobile environment decision support system (MEWSUB) for early warning and emergency assessment in ungauged river basins was developed. A one-dimensional water quality model was built for the system and the terrain module and pollutant module were developed for terrain digitization and pollutant release process data generation. MEWSUB can quickly create water quality model input files, simulate the temporal release of pollutants, and display the results in a dynamically rendered map and trend line diagram via HTML5. The system has been used successfully to support early warning efforts during accidents on several ungauged rivers in China.     

MGB-IPH model for hydrological and hydraulic simulation of large floodplain river systems coupled with open source GIS

Large-scale hydrological models are useful tools for water resources studies, however, river network flow routing is generally represented using simplified methods, which may lead to simulation errors in flat regions. We present recent improvements to the large-scale hydrological model MGB-IPH to improve its capability of simulating large river basins with extensive floodplains. We also describe the coupling of MGB-IPH to an open source GIS and a large set of developed pre-processing tools with a user-friendly interface for remote sensing data preparation and output visualization. The new features implemented are demonstrated applying the model to the whole Araguaia river basin (380,000 km²). Results are compared to the previous MGB-IPH routing method, observed flow and water level data and remote sensing imagery, showing improvement in the representation of floodplain inundation dynamics. The test case also shows that the proposed model software framework amplifies possibilities of large-scale simulation of ungauged basins.     

流域系统森林作用水文动态过程的仿真分析

该文对森林状态所引起的流域系统水文动态过程特征的变化作了计算机仿真分析。流域系统的森林状态随时间变化,包含森林的自然生长、采伐、造林等。而自然地质环境,如地形地貌等流域特征相对保持稳定。所以不同时期的流域水文动态过程特性变化主要由森林状态的变化所引起。选择长江流域湖南省境内三个集水面积在500-950KM^2的流域系统,收集连续30年的水文气象数据,以连续和5年数据作为一组,分成多个对比样本系列,辨别不同时期的水文动态过程模型。应用的模型有ARX和模糊神经网络。对模型作脉冲输入的响应仿真,得到不同时期的水文动态过程特性。比较各个时期的流域水文动态过程特性和相应时期的森林状态,得出了森林作用于水文动态过程的一些结论。     

基于遥感与地埋信息系统的额敏河流域积雪变化分析

2005年3月新疆北部部分地区发生融雪洪水灾害,给当地人民的生活和国民生产都带来了严重的影响。分析积雪的分布及其变化可为防洪抗灾提供决策依据,同时精确的流域积雪制图和雪盖消融曲线可为融雪径流的模拟提供参数。本文介绍了MODIS数据积雪监测的方法及流域雪盖的分带提取,利用MODIS影像,结合地理信息系统技术分析了额敏河流域3月4日—3月12日每天、每个海拔高度带的积雪变化情况,并利用逐步回归法对积雪变化与气象因子作了回归分析,结果表明400~900m海拔高度带积雪变化与气温降水相关性很好,相关系数R=0.9。     

基于GEE云平台的黄河源区河流径流量遥感反演研究

河流径流量是陆地上最重要的水文要素之一,准确获取径流信息对于区域的水资源评价和生态修复方面都具有重要作用.研究基于Google Earth Engine(GEE)云平台提供的Sentinel-1、Sentinel-2影像数据,结合数字高程模型(DEM)对河长、河宽、糙率、比降、河深和流速等水力学参数进行遥感估算,进而采...     

An automated multi-step calibration procedure for a river system model

Predicted climate change impact on future water availability in the Murray–Darling Basin (MDB) has highlighted the need for a whole of basin model that incorporates various physical and management characteristics for planning and operational purposes. Modelling platforms such as eWater Source Integrated Modelling System (Source) offer a useful framework in this regard, but at present lack automated calibration techniques to parameterise river system models.This paper presents an automated river system calibration procedure which is robust, repeatable, transparent and systematic. The procedure allows for river network calibration (as opposed to isolated reach by reach calibration), since this has more utility for basin planning and prediction. The calibration procedure routs upstream flow, estimates ungauged inputs via rainfall–runoff (RR) models, and estimates flow based split (distributary) functions and loss functions in complex river systems.This procedure was tested in the Northern Murray–Darling Basin (MDB) and results from the Border Rivers catchment are presented. The results from the Border Rivers case study demonstrate the applicability of the procedure with median calibration and evaluation NSE values of 0.88 and 0.79, respectively. The use of this procedure in the Border Rivers region has highlighted the likelihood of changing stream channel connections at higher flows in the lower reaches of the river network.     

HydroTrend v.3.0: A climate-driven hydrological transport model that simulates discharge and sediment load leaving a river system

HydroTrend v.3.0 is a climate-driven hydrological water balance and transport model that simulates water discharge and sediment load at a river outlet, by incorporating drainage basin properties (river networks, hypsometry, relief, reservoirs) together with biophysical parameters (temperature, precipitation, evapo-transpiration, and glacier characteristics). HydroTrend generates daily discharge values through: snow accumulation and melt, glacier growth and ablation, surface runoff, and groundwater evaporation, retention and recharge. The long-term sediment load is predicted either by the ART-QRT module based on drainage area, discharge, relief, and temperature, or the BQART module that also incorporates basin-average lithology and anthropogenic influences on soil erosion. Sediment trapping efficiency of reservoirs is based on reservoir location in the river network and its volume that determines the residence time of water within the reservoir. Glacial influence is based on the extent of ice cover, equilibrium altitude, and freezing line mobility. HydroTrend v.3.0 captures the inter- and intra-annual variability of sediment flux by using either high-resolution climate observations or a stochastic climate generator for simulations over longer geological intervals. A distributary channel module simulates the flow conditions and transport capacity across a multiple deltaic channel system. Simulations of the Metauro and the Po rivers, in Italy, are used as case studies to demonstrate the applicability of the new model.     

遥感和地理信息系统在半干旱地区降雨-径流关系模拟中的应用

为解决黄土高原半干旱地区农业和生活缺水问题 ,许多地方实施了集水工程以收集雨水。为分析集水潜力 ,以黄土高原半干旱地区的 6个自然集水区为研究对象 ,利用遥感和地理信息系统获得研究区地形、植被、流域特征等参数。通过统计分析的办法得出该区域多年平均年径流量与降雨量、地形、植被等因素的关系模型。该模型将影响降雨 -径流关系的几个主要因素定量表示出来 ,可以快速、准确地计算一个集水区的径流量 ,克服采用径流等值线计算径流带来的误差     

遥感和地理信息系统在半干旱地区降雨-径流关系模拟中的应用

为解决黄土高原半干旱地区农业和生活缺水问题,许多地方实施了集水工程以收集雨水。为分析集水潜力,以黄土高原半干旱地区的6个自然集水区为研究对象,利用遥感和地理信息系统获得研究区地形、植被、流域特征等参数。通过统计分析的办法得出该区域多年平均年径流量与降雨量、地形、植被等因素的关系模型。该模型将影响降雨-径流关系的几个主要因素定量表示出来,可以快速、准确地计算一个集水区的径流量,克服采用径流等值线计算径流带来的误差。     

基于CNN深度学习的径流预判方法及应用

为快速预判流量等级,将复杂洪水预报过程简化为径流预判任务,借鉴卷积神经网络（CNN）在图像识别领域的应用思路,研究 CNN 径流预判模型搭建过程,深入分析样本处理、网络搭建、参数率定、性能测试、精度检验、知识训练等关键环节,提出基于 CNN 深度学习的径流预判方法。根据某水库 2008—2017 年的历史运行资料,构建其入库径流等级预测 CNN 模型实例,采用 61 362 个样本进行参数训练,17 532 个样本进行模型测试,8 766 个样本进行成果检验,预测准确率为 92.94%。研究结果表明,CNN 径流预判方法可作为防汛形势分析及会商决策的重要依据。     

Maximum speedup ratio curve (MSC) in parallel computing of the binary-tree-based drainage network

Restricted computational capacity has become a key factor in limiting the development of a majority of distributed basin models. Parallel computing is one of the most effective methods for solving this problem. Although many parallel-computing methods have been employed in basin models, few studies have carried out theoretical research on parallel characteristics of river basins. In this paper, the drainage network of river basins is treated as a binary-tree structure. Using the binary-tree theory, we find that there exists a maximum speedup curve (MSC) for an arbitrary drainage network. The x-coordinate of the MSC represents the number of processors used during the computing, while the y-coordinate corresponds to the maximum speedup ratio (MSR) that can be obtained. Under several essential assumptions, the theoretical function of MSC is established. The function indicates that the MSC consists of an ascending section and a horizontal section. A parallel algorithm capable of acquiring the MSC is proposed as well. Using this algorithm, the MSC is tested at two different-resolution drainage networks of the Lhasa River Basin. A 2-year rainfall-runoff process is simulated. The results prove the existence of MSC. However, primarily influenced by the load imbalance of subbasins, the simulation values of MSR are usually smaller than the theoretical ones.     

Errors in river lengths derived from raster digital elevation models

Length of river reaches is one of the most important characteristics of stream networks when applying hydrological or environmental simulation models. A common method of obtaining estimates of river lengths is based on deriving flow directions, accumulated area and drainage lines from raster digital elevation models (DEM). This method leads to length estimates with variable accuracy, which depends on DEM horizontal resolution, flatness of terrain, DEM vertical accuracy, the algorithm used to obtain flow directions and the way by which distances are calculated over raster structures. We applied an automatic river length extraction method for eight river reaches in the River Uruguay Basin (206 000 km²), in Southern Brazil, and compared its results to the lengths obtained from drainage vector lines digitalized over satellite images. Our results show that relative errors can be higher than 30% in flat regions with relatively low DEM resolution. Preprocessing of DEM by the method known as stream burning greatly improves results, reducing errors to the range 1.9–7.4%. Further improved estimates were obtained by applying optimized values for the length of orthogonal and diagonal steps called distance transforms, reducing the errors to the range ?2.0–3.3%.     

Using MODIS snow cover maps in modeling snowmelt runoff process in the eastern part of Turkey

Water perhaps is the most valuable natural asset in the Middle East as it was a historical key for settlement and survival in Mesopotamia, “the land between two rivers”. At present, the Euphrates and Tigris are the two largest trans-boundary rivers in Western Asia where Turkey, Syria, Iran, Iraq and Saudi Arabia are the riparian countries. The Euphrates and Tigris basins are largely fed from snow precipitation whereby nearly two-thirds occur in winter and may remain in the form of snow for half of the year. The concentration of discharge mainly from snowmelt during spring and early summer months causes not only extensive flooding, inundating large areas, but also the loss of much needed water required for irrigation and power generation purposes during the summer season. Accordingly, modeling of snow-covered area in the mountainous regions of Eastern Turkey, as being one of the major headwaters of Euphrates-Tigris basin, has significant importance in order to forecast snowmelt discharge especially for energy production, flood control, irrigation and reservoir operation optimization.A pilot basin, located on the upper Euphrates River, is selected where five automated meteorological and snow stations are installed for real time operations. The daily snow cover maps obtained from Moderate Resolution Imaging Spectroradiometer MODIS at 500 m resolution are compared with ground information for the winter of 2002-2003 both during accumulation and ablation and at accumulation stage for the winter of 2003-2004. The snow presence on the ground is determined from the snow courses performed. Such measurements were made at 19 points in and around the upper Euphrates River in Turkey and at 20 points in the upper portion of the pilot basin for the winters of 2002-2003 and 2003-2004, respectively. Comparison of MODIS snow maps with in situ measurements over the snow season show good agreement with overall accuracies ranging between 62% and 82% considering the shift in the days of comparison. The main reasons to have disagreement between MODIS and in situ data are the high cloud cover frequency in the area and the current version of the MODIS cloud-mask that appears to frequently map edges of snow-covered areas and land surfaces. The effect of elevation and land cover types on validation of MODIS snow cover maps is also analyzed. In order to minimize the cloud cover and maximize the snow cover, MODIS-8 daily snow cover products are used in deriving the snow depletion curve, which is one of the input parameters of the snowmelt runoff model (SRM). The initial results of modeling process show that MODIS snow-covered area product can be used for simulation and also for forecasting of snowmelt runoff in basins of Turkey.     

Determination of land surface temperature and its lapse rate in the Satluj River basin using NOAA data

Temperature lapse rate (TLR), an essential parameter for snowmelt runoff analysis, was determined for the Satluj River basin in the Western Himalayas. National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR) data sets were used to determine the land surface temperature (LST) of the region using the split‐window algorithm proposed by Coll and Caselles (Journal of Geophysical Research, 1997, 102, pp. 16697–16713). The LST was correlated with the elevation values obtained from a US Geological Survey digital elevation model (USGS‐DEM) of the same area and the trend showed an inverse relationship between LST and elevation. The TLRs for the study area on 2 February, 1 March, 26 March, 16 October, 1 November and 20 November 2004 were in the range 0.6–0.74°C/100 m. The results obtained were compared with lapse rates determined using Moderate Resolution Imaging Spectroradiometer (MODIS) LST maps. TLR determination in the past was based on air temperature data available from meteorological stations that are sparsely located in rugged terrain such as the Himalayas. As these measurements were point data and had been measured manually, they may have led to erroneous results. Satellite data, however, provide continuous and potentially unbiased recording provided an accurate radiometric calibration and atmospheric correction can be achieved. A previous TLR calculation using air temperature from meteorological stations for the western Himalayan region was found to be 0.65°C/100 m. Air temperature and LST from NOAA‐AVHRR and MODIS‐Terra data were found to be in good agreement. This type of study will be useful for snowmelt runoff modelling studies for the Himalayan region.     

A common parallel computing framework for modeling hydrological processes of river basins

Restricted computing power has become one of the primary factors obstructing advancement in basin simulations for majority of hydrological models. Parallel computing is one of the most available approaches to solve this problem. Using binary-tree theory, we present in this study a common parallel computing framework based on the message passing interface (MPI) protocol for modeling hydrological processes of river basins. A practical and dynamic spatial domain decomposition method, based on the binary-tree structure of the drainage network, is proposed. This framework is computationally efficient, and is independent of the type of physical models chosen. The framework is tested in the Chabagou river basin of China, where two years of runoff processes of the entire basin were simulated. Results demonstrate that the system may provide efficient computing performance. However, primarily because of the constraint of the binary-tree structure for drainage network, this study finds that unlimited enhancement of computing efficiency is impossible to realize.     

MODIS vegetation metrics as indicators of hydrological response in watersheds of California Mediterranean-type climate zones

Vegetation characteristics of a watershed can be important in estimating hydrological response variables (HRVs) such as streamflow (Q), evapotranspiration (ET), and river yield (Q/P). Quantifying the relationship between satellite-derived vegetation metrics and hydrological response to precipitation (P) has the potential to facilitate prediction of HRVs for ungauged watersheds, and/or aid in the assessment of watershed similarity as an initial phase of hydrological regionalization. The utility of Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data to estimate HRVs of watersheds at the regional scale (southern and central California) is tested in this study. An exhaustive statistical regression analysis was conducted to quantify the relationships between MODIS vegetation metrics and HRVs using both ordinary least squares and spatially varying parameter models. Additionally a confirmatory analysis was conducted to test the effect precipitation and potential evaporation have on the exploratory regression results. Results from both the exploratory and confirmatory analyses suggest that (1) while there are limitations in the water balance approach to estimating ET (errors associated with changes in storage and meteorological data are unknown), moderate statistical relationships exist between MODIS vegetation metrics and HRVs; (2) these relationships are heavily influenced by vegetation-precipitation relationships and general precipitation magnitudes; (3) relationships between MODIS metrics and precipitation/HRVs are strongest when drought conditions prevail; and (4) LAI has the strongest relationship with precipitation and HRVs compared to other MODIS vegetation metrics.     

An open-book watershed model for prototyping space-borne flood monitoring systems in International River Basins

A new era involving both simple and complex hydrologic modeling of un-gauged river basins may now emerge with the anticipated global availability of high resolution satellite rainfall data from the proposed Global Precipitation Measurement (GPM) mission. This era of application pertains to rapid prototyping of GPM-based flood monitoring systems for downstream nations in International River Basins (IRBs) where basin-wide in-situ rainfall data is unavailable due to lack of either an infrastructure or a treaty for real-time data sharing with upstream riparian nations. In this paper, we develop, verify and apply an open-book watershed model for demonstrating the value of a parsimonious modeling scheme in quick prototyping of satellite rainfall-based flood monitoring systems for lowermost nations in flood-prone IRBs. The open-book watershed modeling concept was first formulated by Yen and Chow [1969. A laboratory study of surface runoff due to moving rainstorms. Water Resources Research 5(5), 989–1006] more than 30 years ago as a convenient and pragmatic framework to understand the underlying physics behind surface hydrologic phenomena. Our developed model is based on first principles of conservation of mass and momentum that parsimoniously represents the static geophysical features of a basin with minimum calibration. Such a generic and parsimonious representation has the added potential to supplement complex hydrologic models for stakeholder involvement and conflict management in transboundary river basins, among many additional applications. We first demonstrate the physical consistency of our model through sensitivity analysis of some geophysical basin parameters pertinent to the rainfall-runoff transformation. Next, we simulate the stream-flow hydrograph for a 4-month long period using basin-wide radar (WSR-88D) rainfall data over Oklahoma assuming an open-book river basin configuration. Finally, using the radar-simulated hydrograph as the benchmark, and assuming a two-nation hypothetical IRB over Oklahoma, we explored the impact of assimilating NASA's real-time satellite rainfall data (IR-3B41RT) over the upstream nation on the flow monitoring accuracy for the downstream nation. We developed a relationship defining the improvement in flow monitoring that can be expected from assimilating IR-3B41RT over transboundary regions as a function of the relative area occupied by the downstream nation for a semi-arid region. The relative improvement in flow monitoring accuracy for the downstream nation was found to be clearly high (over 35% reduction in root mean squared error) when more than 90% of the basin is transboundary. However, flow monitoring accuracy reduces considerably and even becomes negative when 60% or less of the basin area is transboundary to the downstream nation. Our findings, although hypothetical and very regime-specific, illustrate very clearly the feasibility of utilizing anticipated GPM data to alleviate the current flood monitoring limitations experienced by many nations in IRBs through the application of a generic and parsimonious model.     

Mapping the potential annual total nitrogen load in the river basins of Japan with remotely sensed imagery

The increase of nutrient loads such as nitrogen and phosphorus to a river due to land cover changes in surrounding areas has been one of the major sources of water pollution or eutrophication. Monitoring the influent nutrient load from river basins to rivers is now crucial in the management of river basin environments. The monitoring is not easy, however, because it requires spatial and temporal measurement tools for land cover changes in the river basin and water qualities, and also it requires models relating them.In this study, we first analyzed the relation between the land cover types estimated from monthly maximum Normalized Difference Vegetation Index (NDVI) imagery calculated from NOAA Advanced Very High Resolution Radiometer (AVHRR) imagery and the annual total nitrogen load discharged from river basins. We found that the runoff load factor from urban areas is higher than those of forested areas. We also found that the impacts of land cover such as plantation and field weed communities on the total nitrogen load of each river are higher than the impacts of other land cover types such as Beech and Camellia japonica community type.Finally, we produced two advanced maps of the potential annual total nitrogen load (PTNL) index and the potential annual total nitrogen load for each river basin area (PTNL/area) index by considering the relationship between the land cover types and the annual total nitrogen load discharged from river basins in Japan. The PTNL map will be useful for the risk assessment of total nitrogen load impact on lakes and the sea through rivers from each basin. The PTNL/area index, which considers the effects of river basin areas, will allow evaluation of the state of river basins.