Benchmarking Optical/Thermal Satellite Imagery for Estimating Evapotranspiration and Soil Moisture in Decision Support Tools

Generally, one expects evapotranspiration (ET) maps derived from optical/thermal Landsat and MODIS satellite imagery to improve decision support tools and lead to superior decisions regarding water resources management. However, there is lack of supportive evidence to accept or reject this expectation. We “benchmark” three existing hydrologic decision support tools with the following benchmarks: annual ET for the ET Toolbox developed by the United States Bureau of Reclamation, predicted rainfall‐runoff hydrographs for the Gridded Surface/Subsurface Hydrologic Analysis model developed by the U.S. Army Corps of Engineers, and the average annual groundwater recharge for the Distributed Parameter Watershed Model used by Daniel B. Stephens & Associates. The conclusion of this benchmark study is that the use of NASA/USGS optical/thermal satellite imagery can considerably improve hydrologic decision support tools compared to their traditional implementations. The benefits of improved decision making, resulting from more accurate results of hydrologic support systems using optical/thermal satellite imagery, should substantially exceed the costs for acquiring such imagery and implementing the remote sensing algorithms. In fact, the value of reduced error in estimating average annual groundwater recharge in the San Gabriel Mountains, California alone, in terms of value of water, may be as large as $1 billion, more than sufficient to pay for one new Landsat satellite.     

南方丘陵地区河谷城市用地时空演变与驱动分析——以上饶市城区为例

以揭示中国南方丘陵地区河谷城市的空间演变过程和特征为目的,以上饶市城区为例,在遥感与GIS技术的支持下,对1988~2013年间上饶市城区城市用地的时空演变过程、特征及驱动影响因素进行了研究。结果表明,1988~2013年的25 a间,上饶市城区城市用地呈现出快速增长的态势,城市形态的演变具有明显的时空特征:时间序列上,不论扩展幅度还是扩展速度,2001~2013年间的值均高于1988~2001年间的值,前后两个时段的扩展特征呈现出明显的差异性;空间格局上,上饶市城区以老城区的中心广场为中心向四周扩展,先后经历了放射性扩展、组团式分散扩展两个阶段,同时呈现出明显的方向分异性,西南和西为其主要扩展方向,而其东南方向的扩展速度最为缓慢。自然环境中的地貌对上饶市城区城市用地的扩展起到很大的限制作用,经济社会的发展、政策规划等因素成为城市用地扩张与时空演化的外在驱动因素。     

多源信息融合技术在内陆湖库水华预警中的研究进展与展望

面对水体富营养化愈来愈严重,水华爆发越来越频繁的严峻形式;为减少水华发生频率及由此造成的损失,开展水华预警已成当务之急。水华爆发是水体中营养盐的累积、气候条件与水力条件等众多因素非线性共同作用的产物;为此,有必要在众多水华影响因素的动态监测信息的融合基础上,寻求水华爆发与这些影响因素间的影射关系,这就需要信息融合技术。通过归纳总结多源信息融合技术在内陆湖库水华预警中应用的研究进展,结合目前我国水华预警的具体需求,提出建立基于多源信息融合技术的水华预警决策支持系统的研究前景与初步设想。信息融合技术为水华预警提供了一个良好的平台,它将与水华相关的不同信息源（水文、气象、水环境质量与环境遥感）所提供的局部不完整的观测信息加以集成与互补,消除多源信息之间存在的冗余和矛盾,形成对水华爆发环境相对完整的感知与描述;从而提高水华预警与应急响应决策的效率,提高预警信息的时间与空间分辨率,扩展信息的时空监测范围。     

The role of remote sensing in hydrological modelling of the Okavango Delta, Botswana

A coupled surface water-groundwater model of the Okavango Delta has been built based on the United States Geological Survey software MODFLOW 2000 including the SFR2 package for stream-flow routing. It will provide a new tool for evaluating water management and climate change scenarios. The delta's size and limited accessibility make direct, on the ground data acquisition difficult. Remote sensing methods are the most promising source of acquiring spatially distributed data for both model input parameters and calibration. Topography, aquifer thickness, channel positions, evapotranspiration and precipitation data are all based on remote sensing. Simulated flooding patterns are compared to patterns derived from visible to thermal NOAA-AVHRR data and microwave radar ENVISAT-ASAR data.     

Predictive models of turbidity and water depth in the Doñana marshes using Landsat TM and ETM+ images

We have used Landsat-5 TM and Landsat-7 ETM+ images together with simultaneous ground-truth data at sample points in the Doñana marshes to predict water turbidity and depth from band reflectance using Generalized Additive Models. We have point samples for 12 different dates simultaneous with 7 Landsat-5 and 5 Landsat-7 overpasses. The best model for water turbidity in the marsh explained 38% of variance in ground-truth data and included as predictors band 3 (630–690 nm), band 5 (1550–1750 nm) and the ratio between bands 1 (450–520 nm) and 4 (760–900 nm). Water turbidity is easier to predict for water bodies like the Guadalquivir River and artificial ponds that are deep and not affected by bottom soil reflectance and aquatic vegetation. For the latter, a simple model using band 3 reflectance explains 78.6% of the variance. Water depth is easier to predict than turbidity. The best model for water depth in the marsh explains 78% of the variance and includes as predictors band 1, band 5, the ratio between band 2 (520–600 nm) and band 4, and bottom soil reflectance in band 4 in September, when the marsh is dry. The water turbidity and water depth models have been developed in order to reconstruct historical changes in Doñana wetlands during the last 30 years using the Landsat satellite images time series.     

利用中巴地球资源卫星数据反演武汉市湖泊营养状态指数

以武汉市主要湖泊为例,研究了利用中巴地球资源卫星（CBERS2）数据反演水体营养状态指数（TLI）。研究旨在评估利用中巴地球资源卫星数据来估算内陆水体富营养化程度的可能性。首先利用地面水质监测数据计算武汉市某些湖泊监测点的“真实的”营养状态指数（包括综合营养状态指数和修正的Carlson营养状态指数）,同时,在事先经过辐射校正和几何校正的CBERS2图像上,以9×9像元为采样窗口,提取各个对应地点的灰度值均值（从波段1至波段4）;然后,采用多元逐步回归分析,以各波段灰度值均值为自变量,建立营养状态指数经验遥感反演模型;最后,利用模型对整个湖泊水体的营养化状态指数进行反演,并绘制了其空间分布图。 结果显示,营养状态指数的自然对数值与CBERS2图像各波段灰度值之间存在较好相关关系,回归系数平方值(R²)为0.51。利用反演模型反演得到的湖区水质分布与实际情况基本相符。由于CBERS2图像数据可以从我国许多数据分发中心免费获取,这为低成本的水质遥感监测提供了一条途径。     

Urbanization and its impact on groundwater: a remote sensing and GIS-based assessment approach

The perils of unplanned urbanization and increasing pressure of human activities on hydro-geomorphologic system often result in modification of the existing recharge mechanism, which leads to many environmental consequences. In the present research, an attempt has been made to investigate the applicability of remote sensing and geographical information system (GIS) in dealing with spatial and temporal variability of dynamic phenomena, like urbanization and its impact on groundwater. This paper covers primarily, quantitative and qualitative impacts of urban growth on the behavior of aquifer in Ajmer city (India). Urban growth of the Ajmer city in last 17 years has been estimated from the satellite images. Database related to urbanization and groundwater has been created in GIS. Groundwater recharge has been computed using a water balance approach known as Water Level Fluctuation Methodology. Recharge estimation methodology has been implemented in GIS to introduce the spatial variability of hydro-geological characteristics. Further, temporal and spatial variations in groundwater quality and quantity have been correlated with urban growth using overlay analysis in GIS. The study reveals a general decline in water table and quality with urbanization. Further, remote sensing and GIS technologies have been found useful in assessment of spatial and temporal phenomena of urbanization and its impact on groundwater system.     

MODIS Biophysical States and NEXRAD Precipitation in a Statistical Evaluation of Antecedent Moisture Condition and Streamflow1

Abstract: The potential of remotely sensed time series of biophysical states of landscape to characterize soil moisture condition antecedent to radar estimates of precipitation is assessed in a statistical prediction model of streamflow in a 1,420 km² watershed in south‐central Texas, Moderate Resolution Imaging Spectroradiometer (MODIS) time series biophysical products offer significant opportunities to characterize and quantify hydrologic state variables such as land surface temperature (LST) and vegetation state and status. Together with Next Generation Weather Radar (NEXRAD) precipitation estimates for the period 2002 through 2005, 16 raw and deseasoned time series of LST (day and night), vegetation indices, infrared reflectances, and water stress indices were linearly regressed against observed watershed streamflow on an eight‐day aggregated time period. Time offsets of 0 (synchronous with streamflow event), 8, and 16 days (leading streamflow event) were assessed for each of the 16 parameters to evaluate antecedent effects. The model results indicated a reasonable correlation (r² = 0.67) when precipitation, daytime LST advanced 16 days, and a deseasoned moisture stress index were regressed against log‐transformed streamflow. The estimation model was applied to a validation period from January 2006 through March 2007, a period of 12 months of regional drought and base‐flow conditions followed by three months of above normal rainfall and a flood event. The model resulted in a Nash‐Sutcliffe estimation efficiency (E) of 0.45 for flow series (in log‐space) for the full 15‐month period, ?0.03 for the 2006 drought condition period, and 0.87 for the 2007 wet condition period. The overall model had a relative volume error of ?32%. The contribution of parameter uncertainties to model discrepancy was evaluated.     

Montane Meadows as Indicators of Environmental Change

We used a time series of satellite multispectral imagery for mapping and monitoring six classes of montane meadows arrayed along a moisture gradient (from hydric to mesic to xeric). We hypothesized that mesic meadows would support the highest species diversity of plants, birds, and butterflies because they are more moderate environments. We also hypothesized that mesic meadows would exhibit the greatest seasonal and interannual variability in spectral response across years. Field sampling in each of the meadow types was conducted for plants, birds, and butterflies in 1997 and 1998. Mesic meadows supported the highest plant species diversity, but there was no significant difference in bird or butterfly species diversity among meadow types. These data show that it may be easier to detect significant differences in more species rich taxa (e.g., plants) than taxa that are represented by fewer species (e.g., butterflies and birds). Mesic meadows also showed the greatest seasonal and interannual variability in spectral response. Given the rich biodiversity of mesic montane meadows and their sensitivity to variations in temperature and moisture, they may be important to monitor in the context of environmental change     

Monitoring urban growth and detecting land-cover changes on the Istanbul metropolitan area

Istanbul is the most populated city of Turkey with a population of around 10.58 M (2000) living on around 5,750 km². In 1980, the population was only 4.7 M and then it has been more than doubled in only two decades. The population has been increasing as a result of mass immigration. An urbanization process continues and it causes serious increases in urban areas while decreasing the amount of green areas. This rapid, uncontrolled, and illegal urbanization accompanied by insufficient infrastructure has caused degradation of forest and barren lands in the metropolitan area, especially through the last two decades. The watershed basins inside the metropolitan area and the transportation network have accelerated the land-cover changes, which have negative impacts on water quality of the basins. Monitoring urban growth and land cover change will enable better management of this complex urban area by the Greater Istanbul Metropolitan Municipality (GIMM). A temporal assessment of land-cover changes of Istanbul has been documented in this study. The study mainly focuses on the acquisition and analysis of Landsat TM and Landsat GeoCover LC satellite images reflecting the significant land-cover changes between the years of 1990 and 2005. Raster data were converted to vector data and used in Geographic Information Systems (GIS). A database was created for Istanbul metropolitan area to plan, manage, and utilize statistical attribute data covering population, water, forest, industry, and topographic position. Consequently an overlay analysis was carried out and land use/cover changes through years have been detected for the case study area. The capability of Landsat images in determining the alterations in the macro form of the city are also discussed.