Evaluation of Using Remote Sensing Evapotranspiration Data in SWAT

This study applied a time series evapotranspiration (ET) data derived from the remote sensing to evaluate Soil and Water Assessment Tool (SWAT) model calibration, which is a unique method. The SWAT hydrologic model utilized monthly stream flow data from two US Geological Survey (USGS) stations within the Big Sunflower River Watershed (BSRW) in Northwestern, Mississippi. Surface energy balance algorithm for land (SEBAL), which utilized MODerate Resolution Imaging Spectro-radiometer (MODIS) to generate monthly ET time series data images were evaluated with the SWAT model. The SWAT hydrological model was calibrated and validated using monthly stream flow data with the default, flow only, ET only, and flow-ET modeling scenarios. The flow only and ET only modeling scenarios showed equally good model performances with the coefficient of determination (R²) and Nash Sutcliffe Efficiency (NSE) from 0.71 to 0.86 followed by flow-ET only scenario with the R² and NSE from 0.66 to 0.83, and default scenario with R² and NSE from 0.39 to 0.78 during model calibration and validation at Merigold and Sunflower gage stations within the watershed. The SWAT model over-predicted ET when compared with the Modis-based ET. The ET-based ET had the closest ET prediction (~8% over-prediction) as followed by flow-ET-based ET (~16%), default-based ET (~27%) and flow-based ET (~47%). The ET-based modeling scenario demonstrated consistently good model performance on streamflow and ET simulation in this study. The results of this study demonstrated use of Modis-based remote sensing data to evaluate the SWAT model streamflow and ET calibration and validation, which can be applied in watersheds with the lack of meteorological data.     

Evaluating Flood Hazard for Land-Use Planning in Greater Dhaka of Bangladesh Using Remote Sensing and GIS Techniques

Floods are a common feature in rapidly urbanizing Dhaka and its adjoining areas. Though Greater Dhaka experiences flood almost in every year, flood management policies are mostly based on structural options including flood walls, dykes, embankments etc. Many shortcomings of the existing flood management systems are reported in numerous literatures. The objective of this paper is to assess flood hazard in Greater Dhaka for the historical flood event of 1998 using Synthetic Aperture Radar (SAR) data with GIS data. Flood-affected frequency and flood depth calculated from the multi-date SAR imageries were used as hydrologic parameters. Elevation heights, land cover classification, geomorphic division and drainage network data generated from optical remote sensing and analogue maps were used through GIS approach. Using a ranking matrix in three dimensional multiplication mode, flood hazard was assessed. All possible combination of flood hazard maps was prepared using land-cover, geomorphology and elevation heights for flood-affected frequency and floodwater depth. Using two hazard maps which produced the highest congruence for flood frequency and flood depth, a new flood hazard map was developed by considering the interactive effect of flood-affected frequency and floodwater depth, simultaneously. This new hazard map can provide more safety for flood countermeasures because pixels belonging to higher hazard degrees were increased due to the consideration of higher degrees of ranks. The estimation of flood hazard areas revealed that a major portion of Greater Dhaka comprised moderate to very high hazard zone. Only a little portion (8.04%) was found to be the least vulnerable to potential flood hazard. Conversely, 28.70% of Greater Dhaka was found within very high hazard zone. Based on this study, comprehensive flood hazard management strategies for land use planning decision were proposed for the efficient management of future flood disasters.     

基于高光谱数据的汉江中下游典型河段水体悬浮物遥感反演

选择汉江中下游典型河段作为研究区域,利用2012—2013年实测水质数据及高光谱数据,基于有效信息变量筛选和神经网络算法构建研究区水体悬浮物浓度高光谱反演模型,分析评价了模型性能与估测效果,讨论了研究区水体悬浮物浓度分布特征。研究结果表明:基于变量投影重要性指数和神经网络优势构建的高光谱反演模型在反演精度、稳定性和适应性方面表现出优异的性能;而对于基于简单相关性分析构建的单波段模型和比值模型而言,建模样本选择对模型精度有较大影响,导致模型反演精度、稳定性和适用性较差;汉江中下游典型河段水体总悬浮物浓度整体上在18.8~187.0 mg/L之间变化,季节性差异明显,即春、夏两季悬浮物浓度低于秋季。     

基于GIS和遥感数据的洪水风险分析

随着城市化进程的不断深化,洪涝灾害已经成为威胁人类生存的一种主要自然灾害。人们逐步认识到,仅仅使用工程措施来防御洪水是远远不够的,非工程措施近年来已进入到防洪领域。管理洪水、分析洪水灾害是非工程措施的一个重要方面。应用GIS工具研究ASAR数据和DEM数据获取研究区域的水深信息。以东洞庭湖区域为研究对象,运用3种常用的插值方法（IDW、Kriging和Topo to Raster）进行水面插值．但这些方法的插值效果不是很好。一种新的插值方法（ADDM,基于平均距离插值方法）被用来进行水面插值。相互比较的结果表明,ADDM方法在水深精度和水面连续性方面都优于其他3种方法。最后,根据ADDM方法获取的水深信息和洪水频率图制作东洞庭湖区洪水风险图。     

多源卫星遥感数据和水色遥感技术在鹤地水库采砂监察中的应用

近年来,鹤地水库的采砂活动频繁,相关管理部分迫切希望了解采砂活动在水库库区的时空分布,以指导库区的管护和执法活动。该基于多源卫星遥感数据和水色遥感技术对鹤地水库悬浮泥沙浓度进行了分析,结合现场调研,发现悬浮物浓度高值区存在采砂行为。认为基于多源卫星遥感数据和水色遥感技术可对水库的采砂行为时空变化进行监察,辅助库区管理人员执法。     

水利遥感数据共享平台的高性能运行机制研究

随着遥感技术在水利应用上的逐步推进,海量多源遥感数据的低处理效率和共享程度成为该技术应用瓶颈。借鉴国内外现有技术经验,结合水利信息聚合应用特点,分析了解决该问题的空间数据密集和并行计算、快速检索与传输等几个关键支撑技术。通过对现有系统集成和应用模式的剖析,在理论上提出该运行框架的初步设计,为水利遥感数据中心的建设提供参考和建议。     

RUSLE2 Model Application for Soil Erosion Assessment Using Remote Sensing and GIS

The study is focused on the estimation of rate of soil erosion, using Revised Universal Soil Loss Eq. 2 (RUSLE2), in the Veppanapalli subwatershed of Krishnagiri catchment located in Tamil Nadu, India. The soil erosion is estimated for each of the hillslope units in the study area. The factors considered are intensity of rainfall, type of soil, land use classification and the existing soil conservation practices. Detailed analysis of soil samples were done to assess the texture, structure, permeability and organic matter content of the soil samples of each hillslope unit. The required data for the other parameters were estimated by carrying out intense field investigations and by the analysis of the satellite imagery of 5.6 m resolution. A data base was created with all the subfactor values for the hillslope units. Incorporation of remote sensing technique and Geographic Information System (GIS) made the spatial analysis of the study more reliable and accurate. The annual average soil erosion rate is estimated as 25 t/ha/year, which is on a higher range. This indicates the immediate need for the adoption of proper conservation strategies in this area to control the eutrophication in the Krishnagiri reservoir and to prevent further watershed degradation.     

Coastal Urban Flood Simulation Using FEM,GIS and Remote Sensing

In this paper, a rainfall runoff model for coastal urban watershed considering the effects of tidal variations using Finite Element Method (FEM) is presented. Overland flow is modeled using the mass balance equation considering the impervious character of the urban watershed. Storm water flow through the channel is modeled using the diffusion wave form of the Saint Venant’s equations and considering the tidal variations. Galerkin’s FEM is used in the approximation of the governing equations. One dimensional linear line elements are used in the channel discretization. Further the mass balance based overland flow model and diffusion wave based channel flow model have been integrated for prediction of flood. Slope values for the overland flow are determined using the Geographical Information System (GIS) from the Digital Elevation Model (DEM) of the area. The landuse is determined using the remote sensing data. Remote sensing data is analyzed using the ERDAS Imagine and ArcGIS and the Manning’s roughness is calculated for each subdivision of subcatchment. The developed models have been verified with the models available in literature and are found to be satisfactory. Further, the integrated model has been applied to the runoff simulation of a coastal urban watershed in Navi Mumbai, in Maharashtra state of India to analyze the flooding in monsoon season along with the tidal influences. The model could satisfactorily predict the runoff due to monsoon rains coupled with the tidal variations. The developed model will be useful in the urban coastal flood analysis due to heavy rainfall and tidal effects.     

多源水利遥感数据的一体化管理机制研究

随着水利遥感数据及产品在水利业务中的普遍应用,存储和管理问题日益成为限制数据应用的瓶颈.针对水利遥感数据及产品的存储管理问题进行研究,以空间数据库引擎技术为基础,提出面向数据库的多源水利遥感数据一体化管理机制.开发并实现基于 C/S 模式的多源水利遥感数据管理系统,利用空间数据库引擎屏蔽数据的复杂性和异构性,通过统一的接口实现水利遥感数据的数据库存取.经过系统测试,证明该系统具有良好的数据存取性能,能够为上层的水利应用提供可靠的数据保障     

Remote Sensing for Wetland Mapping and Inventory

ABSTRACT

This paper describes the state-of-the-art of the management of river sedimentation in China. Attention will be focused on the following problems: (1) the sediment load carried by main rivers in China; (2) the related sediment problems encountered in developing water resources; and (3) the methods in dealing with those problems.     

Satellite SAR Remote Sensing of Great Lakes Ice Cover,Part 2. Ice Classification and Mapping

During the 1997 winter season, shipborne polarimetric backscatter measurements of Great Lakes (freshwater) ice types using the Jet Propulsion Laboratory C-band scatterometer, together with surface-based ice physical characterization measurements and environmental parameters, were acquired concurrently with Earth Resource Satellite 2 (ERS-2) and RADARSAT Synthetic Aperture Radar (SAR) data. This polarimetric data set, composed of over 20 variations of different ice types measured at incident angles from 0° to 60° for all polarizations, was processed to radar cross-section to establish a library of signatures (look-up table) for different ice types. The library is used in the computer classification of calibrated satellite SAR data. Computer analysis of ERS-2 and RADARSAT ScanSAR images of Great Lakes ice cover using a supervised classification technique indicates that different ice types in the ice cover can be identified and mapped, and that wind speed and direction can have an influence on the classification of water as ice based on single frequency, single polarization data. Once satellite SAR data are classified into ice types, the ice map provides important and necessary input for environmental protection and management, ice control and ice breaking operations, and ice forecasting and modeling efforts.     

Improvement to the Thornthwaite Method to Study the Runoff at a Basin Scale Using Temporal Remote Sensing Data

Most of the popular hydrological models are intensive data driven hence, it has become a constraint in computing runoff of river basins where the meteorological data availability is scant. Studying environmental impact assessment on runoff has also become complex in many basins due to non-availability of sufficient historic meteorological data. Directly or indirectly, major components of hydrological cycle such as evapotranspiration and soil moisture are dependent on land use pattern at basin scale. Keeping in view of this, in this paper, an attempt was made to propose modification to simple monthly water balance model by integrating potential evapotranspiration with land use coefficients that were derived from the temporal satellite remote sensing data to compute runoff at basin scale. Godavari Basin, India was selected as study basin to demonstrate the approach. Monthly land use coefficients of all land use classes were computed during the calibration process of the model by matching the computed runoff with field runoff. Runoff during the last 18 years (1990–91 to 2007–08) was computed using the developed methodology. Four years datasets were used for model calibration and the rest of the data for model validation. Spatial annual groundwater flux, reservoir flux and domestic water consumption grids were computed using the field data and integrated with the model in computing runoff. From the Nash-Sutcliffe efficiency coefficient, it is found that computed runoff is very well matching the field runoff. The demonstrated approach is found to be more accurate and simple in computing runoff at basin scale in absence of high intensity meteorological data.     

Implication of Remote Sensing Data under GIS Environment for Appraisal of Irrigation System Performance

Water Resources Management - Poor irrigation management is a common issue of irrigated agriculture. Assessment of irrigation system performance is essential to improve the irrigation system, which...     

Assessing the Accuracy of Soil and Water Quality Characterization Using Remote Sensing

Assessing the risks of agricultural management practices on agro-ecosystem sustainability has special relevance in Ohio, USA due to the states prominence in agricultural production. However, identifying detrimental management practices remains controversial, a situation that may explain the inability to halt the recurring harmful algal blooms in inland waters, or the build-up of nutrients in the agricultural soils. Thus, detailed and accurate information is required to identify soils and water susceptible to degradation, and to support counteractive remedial measures. In this study soil and water spectral reflectance data were acquired with an Analytical Spectral Device, and modeled with laboratory measured physical and chemical properties using the Analysis of Variance (ANOVA) and decision trees. Results reveal no site differences in pH for the water, but the differences in electrical conductivity (EC) were significant. Similarly, the pH for soils did not vary significantly with depth increments. However, the no till (NT) managed soils had significantly higher pH. EC varied with depth of the water, whereas the soil carbon: nitrogen (C/N) ratio varied with management in 4 out of 5 sites. Finally, this study shows that remotely sensed data can be utilized to effectively characterize agricultural management practices based on inherent soil and water properties, thus providing information critical for assessing the efficacy of Water Quality Trading initiatives.     

基于遥感和GIS的流域社会经济数据空间化方法研究

人口和社会经济数据及其空间分布,在资源、环境及自然灾害评估中的重要性已被广泛认知。把遥感和GIS技术相结合,是探讨解决社会经济统计数据空间化的重要思路。以东江流域为例,以多期人口、GDP、土地利用数据为基础,建立东江流域人口与土地利用、GDP和土地利用的多元线性回归模型;以土地利用数据和100 m×100 m网格数据为基础,构建东江流域人口和GDP空间分布约束力指标图层;然后结合统计模型和面积内插,实现了东江流域2009年人口、GDP统计数据的空间化。在县域空间尺度上对模拟结果进行了验证,与同尺度研究工作进行了对比,结果显示模拟得到的人口和GDP空间分布数据,与同尺度的研究工作处于同一精度或者略高的精度水平,表明该方法是一种进行流域社会经济数据空间化处理的有效方法。     

利用遥感技术监测江苏海岸线变迁与滩涂围垦

掌握江苏沿海滩涂的现状与变化情况对于江苏沿海大开发具有重要的意义。利用1975年、1984年、1992年、2002年和2009年5个时相的多源遥感影像对江苏盐城—南通段海岸线变迁与滩涂围垦情况进行动态监测,获取每个时期发生变化的岸段、滩涂围垦面积等信息,并结合GIS的空间分析工具进行了定量分析。结果表明:利用遥感影像能够满足准确、快速监测海岸线变迁的要求;1975—1984年,江苏省海岸线快速向海域推进,滩涂围垦面积为46 045 hm2;1984—1992年间岸线推进速度有所放缓,新增陆地面积为9 955 hm2;1992—2002年与2002—2009年两个时间段内,海岸线全面加速向海域推进,围垦面积分别为53 055 hm2和36 360 hm2。总体而言,1975—2009年间江苏海岸线变化呈现快—慢—全面加速推进的特点。     

Assessment of Snowmelt Runoff Using Remote Sensing and Effect of Climate Change on Runoff

Runoff regimes in Himalayan basins are controlled mainly by melting of snow and ice cover. The air temperature is the principal variable to estimate the importance of the melting of the snow cover when using snowmelt runoff model. Changes in temperature will ultimately affect stream flow and snow/ice melt runoff in particular. Global atmospheric general circulation models (GCMs) have been developed to simulate the present climate and used to predict future climatic changes and its effect. These GCMs have certain disadvantages, therefore another simple approach of hypothetical scenarios have been developed and successfully demonstrated in this study to investigate the effect of changes in temperature. Adopted plausible climate scenarios included three temperature scenarios (T + 1, T + 2, T + 3°C). The effect of these changes has been studied on the stream flow which has contribution from snowmelt, rainfall and base flow in the Satluj basin. It was observed that with the increase in temperature there is not much change in total stream flow, but the distribution of stream flow have changed. More snowmelt runoff occurred earlier due to increased snow melting however, reduced in the monsoon months.     

Understanding Seasonal Water Clarity Dynamics of Lake Dahuchi from In Situ and Remote Sensing Data

Obtaining, analyzing and understanding the seasonal dynamics of water clarity is of importance for understanding and managing lakes and sustaining their ecosystem services. This study aimed to explore the seasonal dynamics of water clarity and to analyze how water level, wind velocity and total precipitation influence this dynamics in Lake Dahuchi, China. The Secchi disk depths recorded in the field and derived from Moderate Resolution Imaging Spectroradiometer (MODIS) images together demonstrated a seasonal pattern of water clarity, which was lower in winter and spring, increased in April or May to reach the highest values in summer, upon which it gradually declined from September onward. Piecewise linear regression analysis between water clarity and water level showed that water level could explain 70% of the variation of the logarithm of Secchi disk depth. The water clarity of Lake Dahuchi was primarily controlled by suspended sediment, while the seasonal variation of water level induced different sediment resuspension, thus we concluded that the water clarity seasonal dynamics of Lake Dahuchi was mainly regulated by seasonal variation of water level.     

Satellite Remote Sensing for Estimating Productivities of Land and Water

Satellite remote sensing offers the capability of objectively measuring spatiotemporalland surface parametersthat can provide information critical to irrigation performance studies. This study demonstrates the use of satellite remote sensing to identify the spatially distributed patterns of wheat yield and crop evapotranspirationfor the Bhakra command area (1.2 million ha), in the Haryana State of north-west India. For the first time, satellite remote sensing has been used to obtain estimates of productivity per unit of water consumed by crop evapotranspiration,a key indicator of the performance of irrigated agriculture. It is shown that areas with the highest grain yield correspond to the areas having the highest evapotranspiration.Consequently, the spatial variations in crop production per unit evapotranspiration are less (cv = 0.10) than spatial variations in productivity of land (cv = 0.17). Whereas head- and tail-end differences in three major branch canals were found for productivity of land, this trend was not detected for the productivity of water consumed. Causal factors for the spatial patterns of productivity need to be more thoroughly investigated. While calculation approaches are suggested to estimate productivity of land and water using satellite remote sensing, further research is required to refine these techniques. Better estimations of the productivity of land and water will allow for more detailed and objective performance studies at a range of scales from individual farm fields to entire irrigation schemes. It will help scientists understand productivity issues better, and enable water managers and policy makers to support improvements in the utilization of land and water resources.     

Flood Hazards Mitigation Analysis Using Remote Sensing and GIS: Correspondence with Town Planning Scheme

Flood is an overflow of water that submerges land and the inflow of tide onto land. Floods usually cause large-scale loss of human life and wide spread damage to properties. In this study, integration of the satellite and GIS datasets are carried out to prepare the flood zonation mapping of Surat district, Gujarat, India. High resolution remote sensing images from Google-earth, IRS-1D, 1:50000 topographical maps are combined with hydraulic analysis and digital elevation model (DEM) to identify the flood susceptible area of the various zones divided as North, South, East, West, Central, South-East and South-West validated with the field surveys. The work is extended up to the Town Planning Scheme (TPS), to detect the most vulnerable areas in terms of submergence. Overall analysis indicates that more than 90–95 % of the area would be submerged if the flood of the same frequency happened over this flood plain in the near future. To mitigate the floods hazards, various remedial measures are suggested to lower the degree of danger owing to future flood events.