Extent Of Water Bodies Research Articles

Evaluation of seasonal water body extents in Central Asia over the past 27 years derived from medium-resolution remote sensing data

In this study medium resolution remote sensing data of the AVHRR and MODIS sensors were used for derivation of inland water bodies extents over a period from 1986 till 2012 for the region of Central Asia. Daily near-infrared (NIR) spectra from the AVHRR sensor with 1.1km spatial resolution and 8-day NIR composites from the MODIS sensor with 250m spatial resolution for the months April, July and September were used as input data. The methodological approach uses temporal dynamic thresholds for individual data sets, which allows detection of water pixel independent from differing conditions or sensor differences. The individual results are summed up and combined to monthly composites of areal extent of water bodies. The presented water masks for the months April, July, and September were chosen to detect seasonal patterns as well as inter-annual dynamics and show diverse behaviour of static, decreasing, or dynamic water bodies in the study region. The size of the Southern Aral Sea, as the most popular example for an ecologic catastrophe, is decreasing significantly throughout all seasons (R2 0.96 for April; 0.97 for July; 0.96 for September). Same is true for shallow natural lakes in the northern Kazakhstan, exemplary the Tengiz-Korgalzhyn lake system, which have been shrinking in the last two decades due to drier conditions (R2 0.91 for July; 0.90 for September). On the contrary, water reservoirs show high seasonality and are very dynamic within one year in their areal extent with maximum before growing season and minimum after growing season. Furthermore, there are water bodies such as Alakol-Sasykol lake system and natural mountainous lakes which have been stable in their areal extent throughout the entire time period. Validation was performed based on several Landsat images with 30m resolution and reveals an overall accuracy of 83% for AVHRR and 91% for MODIS monthly water masks. The results should assist for climatological and ecological studies, land and water management, and as input data for different modelling applications.

Spatiotemporal dynamic of surface water bodies using Landsat time-series data from 1999 to 2011

Detailed information on the spatiotemporal dynamic in surface water bodies is important for quantifying the effects of a drying climate, increased water abstraction and rapid urbanization on wetlands. The Swan Coastal Plain (SCP) with over 1500 wetlands is a global biodiversity hotspot located in the southwest of Western Australia, where more than 70% of the wetlands have been lost since European settlement. SCP is located in an area affected by recent climate change that also experiences rapid urban development and ground water abstraction. Landsat TM and ETM+ imagery from 1999 to 2011 has been used to automatically derive a spatially and temporally explicit time-series of surface water body extent on the SCP. A mapping method based on the Landsat data and a decision tree classification algorithm is described. Two generic classifiers were derived for the Landsat 5 and Landsat 7 data. Several landscape metrics were computed to summarize the intra and interannual patterns of surface water dynamic. Top of the atmosphere (TOA) reflectance of band 5 followed by TOA reflectance of bands 4 and 3 were the explanatory variables most important for mapping surface water bodies. Accuracy assessment yielded an overall classification accuracy of 96%, with 89% producer’s accuracy and 93% user’s accuracy of surface water bodies. The number, mean size, and total area of water bodies showed high seasonal variability with highest numbers in winter and lowest numbers in summer. The number of water bodies in winter increased until 2005 after which a decline can be noted. The lowest numbers occurred in 2010 which coincided with one of the years with the lowest rainfall in the area. Understanding the spatiotemporal dynamic of surface water bodies on the SCP constitutes the basis for understanding the effect of rainfall, water abstraction and urban development on water bodies in a spatially explicit way.

Automated mapping of water bodies using Landsat multispectral data

The assessment of the role of lakes and impoundments at regional and global scales, e.g., in biogeochemical cycles, requires good estimates of the areal extent and shape of water bodies. Upscaling to large regions, except in limited areas where precise maps are available, so far depends on statistical estimates of the number and size of lakes, which explains why estimates are poor. We present an automated procedure that allows mapping of the actual number, size, and distribution of lakes at large scale. Landsat 7 Enhanced Thematic Mapper Plus (ETM +) mosaics from the GeoCover Circa 2000 dataset covering the Earth land surfaces with 14.25 m spatial resolution were used as input data. We developed an approach called GWEM (GeoCover™ Water bodies Extraction Method) that combines remote sensing and GIS to extract water bodies and study their abundance and morphometry. All water bodies greater than 0.0002 km2 were taken into account as lakes. The accuracy of the method was tested on Sweden, where detailed maps of lakes, based on in situ data and orthophotos, exist for the whole country. The proposed method produced accurate results. The largest sources of errors are shadows of mountains and clouds, since the GeoCover mosaics are not absolutely cloud free.

Space-based passive microwave soil moisture retrievals and the correction for a dynamic open water fraction

Abstract. The large observation footprint of low-frequency satellite microwave emissions complicates the interpretation of near-surface soil moisture retrievals. While the effect of sub-footprint lateral heterogeneity is relatively limited under unsaturated conditions, open water bodies (if not accounted for) cause a strong positive bias in the satellite-derived soil moisture retrieval. This bias is generally assumed static and associated with large, continental lakes and coastal areas. Temporal changes in the extent of smaller water bodies as small as a few percent of the sensor footprint size, however, can cause significant and dynamic biases. We analysed the influence of such small open water bodies on near-surface soil moisture products derived from actual (non-synthetic) data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E) for three areas in Oklahoma, USA. Differences between on-ground observations, model estimates and AMSR-E retrievals were related to dynamic estimates of open water fraction, one retrieved from a global daily record based on higher frequency AMSR-E data, a second derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and a third through inversion of the radiative transfer model, used to retrieve soil moisture. The comparison demonstrates the presence of relatively small areas (<0.05) of open water in or near the sensor footprint, possibly in combination with increased, below-critical vegetation density conditions (optical density <0.8), which contribute to seasonally varying biases in excess of 0.2 (m3 m−3) soil water content. These errors need to be addressed, either through elimination or accurate characterisation, if the soil moisture retrievals are to be used effectively in a data assimilation scheme.

Land Use and Land Cover Change (LULC) in the Lake Malawi Drainage Basin, 1982-2005

Changes in land use and land cover (LULC) in the drainage basin of Lake Malawi over the period 1982-2005 were estimated from satellite imagery, and possible relationships were evaluated among the four major land-cover classes: cropland, forest, water, and savanna/shrub/woodland. AVHRR and MODIS sensors gave different values of areal extent of the four classes, limiting the feasibility of establishing consistent temporal trends over the entire period of the study, but forest land showed the least change among three land cover types, and extent of water bodies remained virtually unaltered over the period. AVHRR results show that cropland was mainly derived from savanna/shrub/woodland, which declined by almost 90% over the period 1982-1995.

How well do we know northern land cover? Comparison of four global vegetation and wetland products with a new ground‐truth database for West Siberia

An unprecedented collection of 2161 geolocated, irregularly spaced field observations of land cover spanning ∼106 km2 throughout West Siberia suggests that currently available land cover classification products are remarkably poor indicators of vegetation type and water body extent in this northern wetland environment. The ground‐truth data are compared with (1) the Global Land Cover Characteristics database derived from Advanced Very High Resolution Radiometer data (GLCC.AVHRR), (2) the Global Land Cover Classification derived from Moderate Resolution Imaging Spectroradiometer data (GLCC.MODIS), (3) the Global Lakes and Wetlands Database (GLWD), and (4) the West Siberian Lowland Peatland Database (WSLPD) using: (1) all land cover categories and (2) permanent wetland and water body categories only. Overall agreement with ground observations of land cover is only 21% for the GLCC.AVHRR database and 11% for the GLCC.MODIS database. However, at a much broader scale (one degree of latitude) there is improved qualitative agreement between vegetation classes, with some notable exceptions: (1) at low latitudes (∼54°N–58°N), both the GLCC.AVHRR and GLCC.MODIS databases underestimate woody savannas in favor of croplands; (2) at midlatitudes (∼58°N–64°N), the GLCC.AVHRR database underestimates evergreen needleleaf forest in favor of mixed forest; and (3) at high latitudes (∼64°N–68°N), both the GLCC.AVHRR and GLCC.MODIS databases underestimate deciduous needleleaf forest in favor of woody savannas or open shrublands, respectively. It is clear that all four data databases significantly underestimate permanent wetlands and water bodies, although those specifically developed for this purpose (GLWD and WSPLD) perform better than the more widely used, multiclass land cover products. For permanent wetlands, agreement with our ground data is only 2% for GLCC.MODIS, 23% for GLCC.AVHRR, 45% for GLWD and 56% for WSLPD. Agreement with open water bodies is even poorer (0–5%). These results raise into question the efficacy of incorporating currently available land cover products into terrestrial ecosystem models in northern wetland environments.

Water quality indices across Europe—a comparison of the good ecological status of five river basins

The European Water Framework Directive (WFD) requires the definition of near-natural reference conditions to determine the extent of water bodies' deviation from "good ecological status" caused by stress gradients. However, the classification of ecological quality depends on the assessment method applied and the stressor concerned. While assessment methods that are generally applicable would be favourable, many European countries employ the locally developed water quality metrics that assess the impact of organic pollution (including eutrophication) and the associated decrease in dissolved oxygen. These indices do not specifically address stress from organic toxicants, such as pesticides. The aim of this study was to examine the performance of presently used assessment methods to identify reference conditions of non-contaminated streams in five selected European river basins, covering the geographical region from Spain to Finland, as a crucial prerequisite to indicate toxic gradients. The analysis comprised the Belgium biotic index (BBI), the biological monitoring working party (BMWP) scoring system and the revised German saprobic index. For comparison, we included an adaptation of the recently developed SPEAR index. In two previous field studies, this metric highly correlated with measured pesticide gradients. In this study, SPEAR was the only indicator that was generally applicable to all monitoring data and capable of determining "high ecological status" of reference conditions in all basins. Thus, based upon previous and own results, the authors suggest the species at risk (SPEAR) index to be potentially useful as a European-wide index to address deviations from "good ecological status" due to organic toxicants and recommend it for consideration in integrated water-resource evaluations under the WFD.

Reproductive performance and nest-site selection of White-naped Cranes Grus vipio in the Ulz river valley, north-eastern Mongolia

North-eastern Mongolia is an important breeding area for the globally threatened White-naped Crane Grus vipio. We studied reproductive performance and the influence of factors related to livestock grazing on reproduction and nest-site selection of the White-naped Crane population in the Ulz river valley, north-eastern Mongolia in 2000 and 2001. In 2001, 42 territorial pairs were found in 270 km of river basin. Recruitment was 18–22% resulting in 0.5–0.6 juveniles per territorial pair. The years 2000 and 2001 were within a dry period and recruitment might have been below the long-term average. White-naped Crane nests were significantly associated with river basin sections containing shallow water-bodies. The number and extent of shallow water-bodies are likely to be a limiting factor for breeding population size. Nest-sites in water-bodies were selected for high nest concealment, but nests were initiated even when concealing vegetation was not available. Only 26% of nests were >90% concealed suggesting that appropriate cover was often not available. Nest-sites were also selected for low grazing intensity. No correlation was found between hatching or fledging success and nest concealment or grazing intensity. Brood-size of successful pairs was higher if the home range was ungrazed, but further investigations are needed to clarify whether this was caused by absence of livestock grazing or other factors. Both because of internationally important numbers and because of a potentially high reproductive output, the study area is of high importance for the species.

Land use indicators of a watershed in arid region, western Rajasthan using Remote Sensing and GIS

The vegetation dynamics and land use/land cover types of Birantiya Kalan watershed located in the arid tracts of western Rajasthan have been characterized and evaluated using Remote Sensing and Geographical Information System (GIS). The watershed under study falls in the transitional plain of Luni Basin and is characterized by Aravali ranges in the eastern half and vast alluvial plains in the west. The land use/land cover types, as identified are cropland, fallow, forest, land with scrub, land without scrub, sandy area and the water body. Land with scrub occupied maximum area (39% area of the watershed) in 1996 in place of crop land which was dominant (43% of total area) in the year 1988. During eight years period, seasonal fallow land increased significantly and the areal extent of water body decreased to almost half. Vegetation vigour types have been classified into very poor, poor. moderate, good and very good categories. Moderate vigour type reduced from 62 to 27% and poor type increased from 34 to 68% during the period 1988 to 1996. Other vegetation vigour types have not shown any significant changes. To quantify the changes over the years in both vegetation and land use/land cover, weightages have been given to each type and composite values of both vegetation vigour and land use types for 1996 and 1988 have been calculated. It has been observed that the ratio for vegetation vigour has been found to be 0.85 showing that the overall vegetation have not improved after the treatment. The ratio for land use is found to be 1.01, which indicates negligible change in land use.

The contribution of spaceborne SAR and optical data in monitoring flood events: examples in northern and southern France

This paper demonstrates the utility of satellite remote sensing data in water management, and particularly, for flood monitoring and impact analysis. Satellite-derived data can provide timely geographical data from which water body extent in normal and flood regimes can be ascertained. Combined with exogenous and historical data, within a GIS, these can provide information useful for flood prevention decision making. The recent French Alsation, Camargue and Vaison la Romaine floods are taken to illustrate the utility of satellite remote sensing.