Water Resources Modeling of the Ganges‐Brahmaputra‐Meghna River Basins Using Satellite Remote Sensing Data1

Nishat, Bushra and S.M. Mahbubur Rahman, 2009. Water Resources Modeling of the Ganges‐Brahmaputra‐Meghna River Basins Using Satellite Remote Sensing Data. Journal of the American Water Resources Association (JAWRA) 45(6):1313‐1327. Abstract: Large‐scale water resources modeling can provide useful insights on future water availability scenarios for downstream nations in anticipation of proposed upstream water resources projects in large international river basins (IRBs). However, model set up can be challenging due to the large amounts of data requirement on both static states (soils, vegetation, topography, drainage network, etc.) and dynamic variables (rainfall, streamflow, soil moisture, evapotranspiration, etc.) over the basin from multiple nations and data collection agencies. Under such circumstances, satellite remote sensing provides a more pragmatic and convenient alternative because of the vantage of space and easy availability from a single data platform. In this paper, we demonstrate a modeling effort to set up a water resources management model, MIKE BASIN, over the Ganges, Brahmaputra, and Meghna (GBM) river basins. The model is set up with the objective of providing Bangladesh, the lowermost riparian nation in the GBM basins, a framework for assessing proposed water diversion scenarios in the upstream transboundary regions of India and deriving quantitative impacts on water availability. Using an array of satellite remote sensing data on topography, vegetation, and rainfall from the transboundary regions, we demonstrate that it is possible to calibrate MIKE BASIN to a satisfactory level and predict streamflow in the Ganges and Brahmaputra rivers at the entry points of Bangladesh at relevant scales of water resources management. Simulated runoff for the Ganges and Brahmaputra rivers follow the trends in the rated discharge for the calibration period. However, monthly flow volume differs from the actual rated flow by (?) 8% to (+) 20% in the Ganges basin, by (?) 15 to (+) 12% in the Brahmaputra basin, and by (?) 15 to (+) 19% in the Meghna basin. Our large‐scale modeling initiative is generic enough for other downstream nations in IRBs to adopt for their own modeling needs.     

陕北红碱淖湖泊变化和生态需水初步研究

红碱淖位于陕北风沙区,是我国沙漠中最大的淡水湖,对当地生态环境保护具有重要作用。论文通过对陕北红碱淖湖泊的考察和调研,调查分析了湖泊近年来的变化趋势和流域的生态环境现状。在流域水资源开发利用分析和耗水计算基础上,初步定量评价了湖泊变化的主要影响因素。计算结果表明,红碱淖近年的萎缩主要是由于当地气候持续干旱的影响,目前该湖泊仍处于负均衡状态。根据湖泊对于当地生态环境的重要性,确定了湖泊保护的最小目标和适宜目标,根据水量平衡计算,确定了最小和适宜的生态需水量。通过对流域社会经济用水和生态建设用水研究,提出了湖泊保护的对策建议。     

我国中东部水生态环境评价与对策研究

利用遥感(RS)和地面野外调查手段,对我国中东部地区水生态环境进行了现状调查与评估.结果表明:我国中东部地区农业用水比重大,水资源利用效率低,资源浪费严重;地表水资源干流水质总体稳定,部分流域水质有所改善,主要污染由工业污染向生活污染、农村面源污染转化;湖泊污染严重,湖泊富营养化现象普遍,赤潮濒发,损失较大;地下水主要以点状和面状污染为主,南方城市污染程度普遍高于北方城市;不合理水利工程干扰了自然水生态过程,加剧河流泥沙淤积,湖泊调蓄洪水生态功能随之下降;水资源利用强度超过了30%～40%的国际警界线,加剧了江河断流;水资源需求增大,地下水超采严重,出现地下水位下降、地面沉降、海水倒灌、泉水干枯等现象.      

三峡库区乐天溪流域生态修复效果的遥感监测研究

论文利用多时相LandsatTM E/TM影像、文献和野外调查资料,从土地利用类型与结构、植被覆盖度、土壤侵蚀等方面对三峡库区乐天溪流域生态修复效果进行了定量研究。结果表明:通过5年的生态修复,乐天溪流域林草覆盖率由1997年的80.6%增加到2002年的83.23%,不仅林草覆盖率增长,而且林地质量有较大提高,覆盖度较高的林地和灌丛面积增幅达18.1%和9.1%,相反,疏林面积减少37.9%。流域土地利用结构明显有好转,结构基本合理,相对合理指数由0.76上升到0.81。土地利用结构的改善使得流域土壤侵蚀强度大为降低,微度、中度和强度土壤侵蚀面积分别减少11.49、26.43和4.61km₂,流域平均侵蚀模数由1999年的1562.5tk/m₂降为2002年的870.7t/km₂。生态修复效果显著,但在实际工作中生态修复也需要人工的合理干预。     

饮用水源地生态环境现场监察技术研究

准确快速地确定生态监察目标,以信息化的手段辅助现场执法以提高现场环境执法效能,是饮用水源地生态环境监察的关键.基于高空间分辨率卫星数据,在构建饮用水源地生态环境监察分类体系的基础上,实现了利用卫星数据提取水源保护区的风险源信息,并对水源地所有风险源实现空间定位和准确统计.基于卫星数据和平板电脑,结合遥感技术、地理信息技术和定位技术,开发了水源地保护区现场执法系统,实现了现场数据的快速采集和“图属”一体化的业务集成,该系统可为水源地生态环境现场监察提供有利的技术手段.     

Predicting the Planform Configuration of the Braided Toklat River,Alaska, With a Suite of Rule‐Based Models1

Abstract: An ensemble of rule‐based models was constructed to assess possible future braided river planform configurations for the Toklat River in Denali National Park and Preserve, Alaska. This approach combined an analysis of large‐scale influences on stability with several reduced‐complexity models to produce the predictions at a practical level for managers concerned about the persistence of bank erosion while acknowledging the great uncertainty in any landscape prediction. First, a model of confluence angles reproduced observed angles of a major confluence, but showed limited susceptibility to a major rearrangement of the channel planform downstream. Second, a probabilistic map of channel locations was created with a two‐parameter channel avulsion model. The predicted channel belt location was concentrated in the same area as the current channel belt. Finally, a suite of valley‐scale channel and braid plain characteristics were extracted from a light detection and ranging (LiDAR)‐derived surface. The characteristics demonstrated large‐scale stabilizing topographic influences on channel planform. The combination of independent analyses increased confidence in the conclusion that the Toklat River braided planform is a dynamically stable system due to large and persistent valley‐scale influences, and that a range of avulsive perturbations are likely to result in a relatively unchanged planform configuration in the short term.     

Application of Remote Sensing Detection and GIS in Analysis of Vegetation Pattern Dynamics in the Yellow River Delta

Abstract

Regional vegetation pattern dynamics has a great impact on ecosystem and climate change. Remote sensing data and geographical information system (GIS) analysis were widely used in the detection of vegetation pattern dynamics. In this study, the Yellow River Delta was selected as the study area. By using 1986, 1993, 1996, 1999 and 2005 remote sensing data as basic information resource, with the support of GIS, a wetland vegetation spatial information dataset was built up. Through selecting the land-scape metrics such as class area (CA), class percent of landscape (PL), number of patch (NP), largest patch index (LPI) and mean patch size (MPS) etc., the dynamics of vegetation pattern was analyzed. The result showed that the change of vegetation pattern is significant from 1986 to 2005. From 1986–1999, the area of the vegetation, the percent of vegetation, LPI and MPS decreased, the NP increased, the vegetation pattern tends to be fragmental. The decrease in vegetation area may well be explained by the fact of the nature environment evolution (Climate change and decrease in Yellow River runoff) and the increase in the population in the Yellow River Delta. However, from 1999–2005, the area of the vegetation, the percent of vegetation, LPI and MPS increased, while the NP decreased. This trend of restoration may be due to the implementation of water resources regulation for the Yellow River Delta since 1999.     

基于FY2C卫星数据的藏北高原降水估算研究

如何确切的掌握降水的时空分布,对区域气候、水文和生态应用等至关重要。以藏北高原典型区为研究区,在大量地面实况降水观测数据与对长时间序列FY 2C 影像光谱特征和云图特征分析的基础上,获取卫星降水模拟参数特征集以刻画云降水的发生与发展过程,选用最值归一化方法对不同量纲云图特征参数进行归一化处理。构建基于三层前向型反向传播神经网络的卫星降水估算模型,用于该地域降水估算,并采用多指标体系分析模型的降水模拟精度。结果表明：静止气象卫星红外波段能较精确地揭示云的降水机理,较高时间分辨率遥感图像可以监测云图的变化细节,并获取能够反映云图降水特征的降水模拟参数;人工神经网络能较好地刻画该地域卫星降水特征的非线性规律;三层前向型反向传播神经网络卫星降水估算模型的估算结果与雨量计实测值间的相关性可以达到0.57。模型估算结果系统性的低估偏小,预示着对该地域弱降水强度将有较好的指示性     

Estimating Annual Groundwater Evapotranspiration from Phreatophytes in the Great Basin Using Landsat and Flux Tower Measurements

Escalating concerns about water supplies in the Great Basin have prompted numerous water budget studies focused on groundwater recharge and discharge. For many hydrographic areas (HAs) in the Great Basin, most of the recharge is discharged by bare soil evaporation and evapotranspiration (ET) from phreatophyte vegetation. Estimating recharge from precipitation in a given HA is difficult and often has significant uncertainty, therefore it is often quantified by estimating the natural discharge. As such, remote sensing applications for spatially distributing flux tower estimates of ET and groundwater ET (ET_g) across phreatophyte areas are becoming more common. We build on previous studies and develop a transferable empirical relationship with uncertainty bounds between flux tower estimates of ET and a remotely sensed vegetation index, Enhanced Vegetation Index (EVI). Energy balance‐corrected ET measured from 40 flux tower site‐year combinations in the Great Basin was statistically correlated with EVI derived from Landsat imagery (r² = 0.97). Application of the relationship to estimate mean‐annual ET_g from four HAs in western and eastern Nevada is highlighted and results are compared with previous estimates. Uncertainty bounds about the estimated mean ET_g allow investigators to evaluate if independent groundwater discharge estimates are “believable” and will ultimately assist local, state, and federal agencies to evaluate expert witness reports of ET_g, along with providing new first‐order estimates of ET_g.     

Sound and Fury Signifying Nothing: Using Geoinformatics to Inform Resource Policy in the Gulf of California,Mexico

In this issue of Environmental Management, Glenn and others posit that a previous study had analytical and interpretive errors in analysis of shrimp fishing in the Upper Gulf of California, Mexico. Unfortunately, much of their evidence is too indirect and of insufficient scale to address the central question of salinity in the Upper Gulf. Also, many of their suppositions did not include direct interviews with local officials or a robust understanding of remote sensing literature. This response to their rebuttal presents a set of figures and analysis demonstrating that the Colorado River flows into a closed evaporative basin known as the Laguna Salada and thus cannot flow into the Gulf of California. Readers are asked to examine the images and interpret their meaning for themselves.