AN ALGORITHM FOR ESTIMATING SURFACE SUSPENDED SEDIMENT CONCENTRATIONS WITH LANDSAT MSS DIGITAL DATA1

ABSTRACT: Algorithms for Landsat MSS digital data are needed to reduce the necessity of calibrating each Landsat scene if these data are to be useful in monitoring programs for surface suspended sediments. In this study digital data were extracted from 16 Landsat Multispectral Scanner (MSS) scenes collected between March 1987 and August 1988 over Enid Reservoir in North Central Mississippi. These data were converted to radiance and reflectance data for comparison with field measurements of surface suspended sediment concentrations. Concentrations ranged from 2 to 168 mg/1 during the study with only four greater than 100 mg/l. Linear and polynomial regression analyses were used to relate the surface suspended sediment concentrations with radiance and reflectance. Reflectance in MSS band 2 (0.6 to 0.7 μm) and MSS band 3 (0.7 to 0.8 μm) were best related to the surface suspended sediment concentrations with coefficients of determination accounting for 71 percent and 68 percent of the variation in the data, respectively. Regressions with radiance data accounted for 36 percent (band 2) or less of the variation. Logarithmic transformations of either reflectance or sediment concentrations increase the coefficients of determination for MSS band 2 reflectance data to 81 percent. Regressions between the ratio of MSS band 1 to MSS band 2 reflectances and concentrations also accounted for 80 percent of the variation. An equation Log_e SS (mg/l) = 9.21R½+ 2.71R½2 + 8.45, where S is surface suspended sediment concentrations and R¹/₂ is the ratio of MSS band 1 to MSS band 2 reflectances, provided the best fit to the data with a coefficient of determination of 0.82. This equation is essentially the same as an algorithm proposed by Topliss et at. (1990), for estimating surface suspended sediment concentrations in Canadian coastal waters. These equations for Enid Reservoir and Canadian waters suggest that it may be possible to develop an algorithm for widespread use for estimating surface suspended sediments.     

SPATIAL DISTRIBUTION OF POINT SOIL MOISTURE ESTIMATES USING LANDSAT TM DATA AND FUZZY-C CLASSIFICATION1

ABSTRACT: Many hydrologic models have input data requirements that are difficult to satisfy for all but a few well-instrumented, experimental watersheds. In this study, point soil moisture in a mountain watershed with various types of vegetative cover was modeled using a generalized regression model. Information on sur-ficial characteristics of the watershed was obtained by applying fuzzy set theory to a database consisting of only satellite and a digital elevation model (DEM). The fuzzy-c algorithm separated the watershed into distinguishable classes and provided regression coefficients for each ground pixel. The regression model used the coefficients to estimate distributed soil moisture over the entire watershed. A soil moisture accounting model was used to resolve temporal differences between measurements at prototypical measurement sites and validation sites. The results were reasonably accurate for all classes in the watershed. The spatial distribution of soil moisture estimates corresponded accurately with soil moisture measurements at validation sites on the watershed. It was concluded that use of the regression model to distribute soil moisture from a specified number of points can be combined with satellite and DEM information to provide a reasonable estimation of the spatial distribution of soil moisture for a watershed.     

RESERVOIR TROPHIC STATE EVALUATION USING LANISAT TM IMAGES1

ABSTRACT: Reservoir water quality is traditionally monitored and evaluated based on field data. Collecting and analyzing field water quality data are costly and time consuming tasks, and whether a limited number of field data truly characterize the spatial variation of the trophic state within a vast water body is often disputed. In this study we utilize Landsat TM data to estimate the water quality and trophic state of the Te‐Chi reservoir in Central Taiwan. A modified multi‐parameter model of Carlson's trophic state index (TSI) was developed for the Te‐chi reservoir. Water quality parameters (concentration of chlorophyll‐a, total phosphorous measurement, and secchi disk depth) required by the model are found to have high correlations with combinations of TM bands. Therefore, TM data are used to map the trophic state of the reservoir. TM‐derived TSI maps of the reservoir reveal that, in summer, the trophic state in the reservoir generally improves from upstream to downstream and that zones of distinct trophic state exist. A trophic state index based on secchi disk depth may give erroneous values in the upstream section of the reservoir pool due to high sediment concentration in the reservoir inflow. We conclude that the Te‐Chi reservoir is eutrophic or worse in summer and meso‐eutrophic in winter. Implementation of best management practices to reduce nonpoint source pollution in the upstream watershed is highly recommended. This study demonstrates the capability of mapping the trophic state in impounded water bodies using the Landsat TM data.     

SOURCES OF VARIABILITY IN PHOSPHORUS AND CHLOROPHYLL AND THEIR EFFECTS ON USE OF LAKE SURVEY DATA1

Summer lake survey measurements of total phosphorus (TP) and chlorophyll a (CHLa) from 188 reserviors and natural lakes in the midwest were analyzed to determine the magnitude of major sources of variability. Median variance among replicate samples collected at the same location and time was about 7-8 percent of the mean for both TP and CHLa. Median observed temporal variability within summers was 27 percent of the mean for TP and 45 percent of the mean for CHLa. Median values of year-to-year variance in average TP and CHLa were 22 percent and 31 percent of the mean, respectively. A range of approximately two orders of magnitude was observed among individual estimates of variance in each of these categories. The magnitude of observed temporal variability was affected only slightly by variance among replicate samples on individual days and was weakly correlated with the length of time during which samples were collected from individual lakes. Observed temporal variation was similar between reservoirs and natural lakes when variances were calculated with logtransformed data. The magnitude of temporal and year-to-year variance can severely limit the power of statistical comparisons of TP and CHLa means, but has less effect on establishing relative rankings of lake means, Sources and relative magnitude of variability are important in the use of TP and CHLa data in regression models and in the planning of lake surveys and subsequent data analysis.     

THE USE OF LANDSAT IMAGERY IN GROUND WATER EXPLORATION1

ABSTRACT: Water supplies in Arizona are becoming increasingly limited because municipal, industrial, and agricultural consumption depletes ground water reserves by three million acre-feet annually. Additional demands are being created by electric power generation, particularly in northeastern Arizona where ground water pumpage is expected to escalate by sixfold during the next 10 years. The results of a study to determine the ease and feasibility of using satellite imagery as a tool in exploring for new sources of ground water are reported. Lineaments detected on Landsat images of two sites were mapped and correlated with well data in the two study areas by means of well centered grid model. The correlations developed between lineament density and water well data in the two study sites support the hypothesis that a relationship exists between regional geologic structure and the presence of ground water.     

LAKE EVAPORATION STUDIES USING SATELLITE THERMAL INFRARED DATA1

Thermal infrared radiation data were acquired by the Heat Capacity Mapping Mission (HCMM) satellite over the surface area (385 km²) of Utah Lake during periodic overpasses in 1978 and 1979. The thermal infrared data were converted to lake surface temperatures which were subsequently used in correlations with lake evaporation. Correlations between HCMM surface temperature and pan-derived evaporation exceeded r = 0.90 when HCMM night and day/night average temperatures and two-day average evaporation values were tested. Similar regression studies were done using monthly data from a conceptual evaporation model and the evaporation pan versus monthly HCMM temperature data. In this test both the HCMM day and night monthly temperature versus the monthly model or pan evaporation had correlations exceeding r = 0.95. Empirical estimates of both short and long term lake evaporation using satellite thermal infrared data seem feasible. Attempts to use the HCMM thermal information as direct input to a theoretical approach to calculating evaporation were inconclusive; however, a definite potential seems to exist.     

SIMPLE TROPHIC STATE CLASSIFICATION OF THE CANADIAN NEARSHORE WATERS OF THE GREAT LAKES1

ABSTRACT: Trophic classification of the Canadian nearshore waters of the Great Lakes is attempted using summer, surface water quality data for the early 1970's. A generalized Composite Trophic Index is developed using paired linear relationships for total phosphorus, chlorophyll a, and Secchi depth data for 66 defined nearshore regions. The chlorophyll a and total phosphorus relationship indicates that the nearshore waters contain a low chlorophyll a concentration for a given total phosphorus concentration than observed for the open waters of the Great Lakes or for smaller Canadian lakes. The most eutrophic nearshore regions occur in areas of relatively restricted circulation and/or high nutrient loadings. These include the Bay of Quinte, Toronto and Hamilton harbours, and portions of Lake We's Western Basin. Lakes Huron and Superior are generally oligotrophic, except for some embayments. Although nearshore water quality is highly variable, this apprach represents a reasonable compromise with respect to analytical complexity. The Composite Trophic Index removes biases introduced through the use of a single trophic state indicator and uniquely describes the nearshore water quality in terms generally comparable to other water bodies.     

EFFECTIVE USE OF LANDSAT DATA IN HYDROLOGIC MODELS1

ABSTRACT: In a cooperative demonstration project, NASA and the U.S. Army Corps of Engineers (Corps) compared conventional and Landsat-derived land-use data for use in hydrologic models, and the resulting discharge frequency curves were analyzed. When a grid-based data-management system was used on a cell-by-cell basis (size about 1.1 acres or 0.45 hectare), Landsat classification accuracy was only 64 percent, but, when the grid cells were aggregated into watersheds, the classification accuracy increased to about 95 percent. When both conventional and Landsat land-use data were input to the HEC-1 model for generating discharge frequency curves, the differences in calculated discharge were judged insignificant for subbasins as small as 1.0mi² (2.59 km²). For basins larger than 10mi² (25.9km²), use of the Landsat approach is more cost-effective than use of conventional methods. Digital Landsat data can also be used effectively by local and regional agencies for hydrologic analysis by incorporating the data into grid-based data-management systems. The transfer of this new technology is well under way through inclusion in some Corps training courses and through use by both county government personnel and private consultants.     

THE USE OF A SIMPLE MODEL AND UNCERTAINTY ANALYSIS IN LAKE MANAGEMENT1

ABSTRACT: A simple, black-box lake model was developed for phosphorus, using nonlinear regression analysis on a data base of north temperate lakes. The uncertainty associated with the model was then combined with the parameter uncertainty and the independent variable uncertainty to provide an estimate of the confidence limits associated with a predicted value. The prediction uncertainty is often neglected, yet it is an important measure of the usefulness of a model. Prediction uncertainty reflects the modeler's confidence in the model, and it should be used by a decision maker as a weight indicating the value of the model prediction. A procedure is outlined that combined lake modeling and uncertainty analysis for use in lake quality assessment and lake management. An example is provided illustrating the use of this procedure in nutrient budget sampling design, data analysis, and the evaluation of lake management strategies for a 208 program in New Hampshire.     

SCS URBAN CURVE NUMBERS FROM A LANDSAT DATA BASE1

Estimating the Curve Numbers used in the Soil Conservation Service hydrologic models is a tedious and costly task. Recent advances in remote sensing and data processing have led to the development of readily available land cover data bases for many areas of the United States. This study evaluated the potential of using a Landsat data base to make the Curve Number estimation process more cost-effective and less tedious. Ten watersheds in the Washington, D.C., area were evaluated using a Landsat land cover data base developed by the U.S. Geological Survey. Results showed that these data can be useful. Predictions can be improved if ancillary data on residential lot size are included. It was concluded that this type of data base must be examined carefully before implementation.     

LANDSAT MID-INFRARED DATA AND GIS IN REGIONAL SURFACE SOIL-MOISTURE ASSESSMENT1

ABSTRACT: Landsat satellite Thematic Mapper (TM) data were used to assess regional soil moisture conditions. The mid-infrared (MIR) data of TM band 7 were overlain onto four principal land-use categories (Agricultural/Irrigated, Urban/Clearings, Forest/ Wetlands, Water) using a geographic information system (GIS). M data were used to assess four qualitative surface soil-moisture conditions (water/very wet, wet, moist, and dry) within each land-use category of a 208,354 ha southwestern Florida study area. The MIR response was inversely related to the qualitative surface soil-moisture content. Integration of Landsat TM MIR data with land use through GIS appears to be a useful technique for high-resolution regional soil moisture assessment, and further research to reline this technique is recommended.     

ASSESSMENT OF NUTRIENT EFFECTS AND NUTRIENT LIMITATION IN LAKE OKEECHOBEE1

ABSTRACT: Lake Okeechobee, the third largest lake in the United States, is a shallow, mixing basin with annual total phosphorus concentrations ranging from 50–100 μg P/L. Data, mainly from unpublished agency reports, are analyzed to determine if nutrients limit phytoplankton, to describe spatial and temporal variability in trophic state parameters, and to evaluate conclusions obtained from empirical trophic state models. Algal bioassay experiments that have been used to assess nutrient limitation have produced equivocal results. However, seasonal minima in orthophosphorus and inorganic nitrogen indicate that both nutrients may be limiting seasonally. Strong, but reverse north-south gradients and large seasonal changes in phosphorus and nitrogen concentrations, show that empirical models based on annual phosphorus loadings or concentrations are not adequate to predict chlorophyll concentrations or other trophic state variables. Spatially-segmented, multi-class phytoplankton-nutrient models of seasonal phytoplankton responses that are coupled with hydrodynamic models may provide predictability in assessing effects of changing nutrient loads on phytoplankton composition and standing crop. Successful modeling efforts of responses to nutrients also must deal with resuspended and benthic algae, periphyton, and emergent and submergent aquatic plants that must play important trophic roles in some of the lake basin.     

EMPIRICAL MODELS FOR TROPHIC STATE IN SOUTHEASTERN U.S. LAKES AND RESERVOIRS1

ABSTRACT: A cross-sectional data set of 80 lakes and reservoirs in nine southeastern states was examined to specify and parameterize trophic state relationships. The relationships fitted are based on measurements of several limnological variables taken over the course of a growing season or year in each of the lakes. The trophic state models relate phosphorus and nitrogen loading to inlake phosphorus and nitrogen concentrations, which in turn are related to maximum chlorophyll level, Secchi disk depth, dominant algal species, and hypolimnetic dissolved oxygen status. Due to the empirical nature of the study, causal conclusions are limited; rather, the models are most useful for prediction of average growing season conditions related to trophic state.     

A CARLSON-TYPE TROPHIC STATE INDEX FOR NITROGEN IN FLORIDA LAKES1

: A data base consisting of predominantly nitrogen limited Florida lakes from the National Eutrophication Survey (NES) was used to develop a trophic state index based on total nitrogen concentration. This index was compared with Carlson's (1977) index based on total phosphorus concentration, and the lesser of the two values for each lake was averaged with indices based on Secchi disk transparency and chlorophyll a concentration to assess the trophic state of the 40 Florida NES lakes.     

CHANGE IN LAKE TROPHIC STATE AND INTERNAL PHOSPHORUS RELEASE AFTER ALUMINUM SULFATE APPLICATION1

ABSTRACT: Recovery of eutrophic lakes after nutrient diversion may be delayed if the lake experiences significant internal phosphorus (p) loading to the water column. A maximum dose of aluminum sulfate, defined herein, was applied to the anaerobic sediments of the hypolimnia of two dimictic Ohio lakes following septic tank diversion, with the objective of attaining long term control of the release of phosphorus to the water column from these sediments. The results were compared to a similar, downstream, untreated lake. Total phosphorus concentration declined sharply after treatment and has remained so through 1980 for both lakes, a period of 5 and 6 years of control, respectively. Internal P loading from anaerobic, hypolimnetic sediments was partially controlled by the treatment but there are other important sources, perhaps in the littoral zone, in these lakes. Algal biomass is Smaller and water transparency has increased. Both lakes became mesotrophic after treatment, as described by the Carlson (1977) trophic state index, and remain in that improved condition to date. No deleterious side effects were observed, although one lake experienced a significant decrease in diversity of planktonic microcrustacea and a lakeward extension of the macrophyte community. This method appears to be an effective and lasting means of accelerating the recovery of a eutrophic lake following nutrient diversion.     

INTEGRATING DEMOGRAPHIC AND LANDSAT (TM) DATA AT A WATERSHED SCALE1

ABSTRACT: Recurrent calls for integrated resource management urge that an understanding of human activities and populations be incorporated into natural resource research, management, and protection efforts. In this paper, we hypothesize that watersheds can be a valuable geography for organizing an inquiry into the relationship between humans and the environment, and we present a framework for conducting such efforts. The framework is grounded in the emerging field of landscape ecology and incorporates demographic theory and data. Demography has been advanced by technological capabilities associated with the 1990 Census. Employing Geographic Information System (GIS) tools, we couple Landsat Thematic Mapper (TM) land cover data with census‐derived housing density data to demonstrate the operation of our framework and its utility for better understanding human‐landscape interactions. In our investigation of the Kickapoo Watershed and two sub‐ watersheds, located in southwestern Wisconsin, we identify relationships between landscape composition and the distribution and social structure of human populations. Our findings offer insight into the interplay between people and biophysical systems.     

LAKE WATER QUALITY ASSESSMENT FROM LANDSAT THEMATIC MAPPER DATA USING NEURAL NETWORK: AN APPROACH TO OPTIMAL BAND COMBINATION SELECTION1

Abstract: The concern about water quality in inland water bodies such as lakes and reservoirs has been increasing. Owing to the complexity associated with field collection of water quality samples and subsequent laboratory analyses, scientists and researchers have employed remote sensing techniques for water quality information retrieval. Due to the limitations of linear regression methods, many researchers have employed the artificial neural network (ANN) technique to decorrelate satellite data in order to assess water quality. In this paper, we propose a method that establishes the output sensitivity toward changes in the individual input reflectance channels while modeling water quality from remote sensing data collected by Landsat thematic mapper (TM). From the sensitivity, a hypothesis about the importance of each band can be made and used as a guideline to select appropriate input variables (band combination) for ANN models based on the principle of parsimony for water quality retrieval. The approach is illustrated through a case study of Beaver Reservoir in Arkansas, USA. The results of the case study are highly promising and validate the input selection procedure outlined in this paper. The results indicate that this approach could significantly reduce the effort and computational time required to develop an ANN water quality model.     

USING LANDSAT DATA TO CLASSIFY LAND USE FOR ASSESSING THE BASINWIDE RUNOFF INDEX1

Remote sensing data in the form of Landsat computer compatible tapes (CCT) was used to determine land use and land cover as an aid in hydrologic studies that were used to estimated a basinwide runoff index. With the use of the General Electric Image 100 multispectral image processing system in conjunction with the Earth Resources Laboratory Application Software (ELAS), CCT's on February 9, 1976, were analyzed by spectral differences to determine unique land use conditions within the Econlockhatchee (Econ) River Basin, Florida. The result showed that the Landsat data can be successfully used to monitor the USGS land use Level 1. An advantage of using the Landsat data for land use classification is that new data are periodically available for updating the land use information. The Soil Conservation Service curve number was used to establish a basinwide runoff index which includes a prime variable of land use changes with the time. The basinwide runoff index in 1972 (with USGS 1972 Land Use maps) was similar to the one in 1976 (with Landsat data dated February 9, 1976). This implies that the runoff from the entire Econ Basin was not noticeably changed during the period of 1972 and 1976.     

SELECTING RECONNAISSANCE STRATEGIES FOR FLOODPLAIN SURVEYS1

ABSTRACT: Multispectral aircraft and satellite data over the West Branch of the Susquehanna River were analyzed to evaluate potential contributions of remote sensing to floodplain surveys. Multispectral digital classifications of land cover features indicative of floodplain areas were used by interpreters to locate various floodprone area boundaries. The boundaries thus obtained were found to be more striking and continuous in the Landsat data than in the low altitude aircraft data. The digital approach permitted satellite results to be displayed at 1:24,000 scale and aircraft results at even larger scales. Results indicate that remote sensing techniques can delineate floodprone areas more easily in agricultural and limited development areas than in areas covered by a heavy forest canopy. At this time it appears that the remote sensing data would be best used as a form of preliminary planning information or as an internal check on previous or ongoing floodplain studies. In addition, the remote sensing techniques can assist in effectively monitoring floodplain activities after a community enters into the National Flood Insurance Program.     

NUTRIENT CONCENTRATION CRITERIA AND CHARACTERIZATION OF PATTERNS IN TROPHIC STATE FOR RIVERS IN HETEROGENEOUS LANDSCAPES1

ABSTRACT: A method is demonstrated for the development of nutrient concentration criteria and large scale assessment of trophic state in environmentally heterogeneous landscapes. The method uses the River Environment Classification (REC) as a spatial framework to partition rivers according to differences in processes that control the accrual and loss of algae biomass. The method is then applied to gravel bed rivers with natural flow regimes that drain hilly watersheds in New Zealand's South Island. An existing model is used to characterize trophic state (in terms of chlorophyll a as a measure of maximum biomass) using nutrient concentration, which controls the rate of biomass accrual, and flood frequency, which controls biomass loss. Variation in flood frequency was partitioned into three classes, and flow data measured at 68 sites was used to show that the classes differ with respect to flood frequency. Variation in nutrient concentration was partitioned at smaller spatial scales by subdivision of higher level classes into seven classes. The median of flood frequency in each of the three higher level classes was used as a control variable in the model to provide spatially explicit nutrient concentration criteria by setting maximum chlorophyll a to reflect a desired trophic state. The median of mean monthly soluble reactive phosphorus and soluble inorganic nitrogen measured at 68 water quality monitoring sites were then used to characterize the trophic state of each of the seven lower level classes. The method models biomass and therefore allows variation in this response variable to provide options for trophic state and the associated nutrient concentrations to achieve these. Thus it is less deterministic than using reference site water quality. The choice from among these options is a sociopolitical decision, which reflects the management objectives rather than purely technical considerations.