Capturing LiDAR‐Derived Hydrologic Spatial Parameters to Evaluate Playa Wetlands

The digital elevation model data from traditional stereo photogrammetric methods are inadequate in providing accurate vertical parameters to feed hydrologic models for low‐lying, extremely flat areas. High‐resolution light detection and ranging (LiDAR) data provide the robust capability of capturing small variations in low‐relief playa wetlands. The Rainwater Basin in south‐central Nebraska includes a complex of seasonally shallow playa wetlands that attract millions of migratory waterfowl every spring and fall. This research focuses on the development of a procedure with applicable protocols to produce LiDAR‐derived three‐dimensional wetland maps and to extract the critical surface parameters (i.e., watershed boundaries, flow direction, flow accumulation, and drainage lines) for playa wetlands. The topo‐hydrologic conditions of playa wetlands were evaluated at the watershed level. The results show that in the Rainwater Basin, 70.7% of the historic hydric soil footprints identified in the Soil Survey Geographic (SSURGO) database were not functioning as topographically depressional wetlands. This finding was confirmed by a recent five‐year Annual Habit Survey showing that 69.8% of the historic hydric soil footprints did not function during the spring migratory bird seasons between 2004 and 2009. The majority of playa wetlands' topographic conditions have been substantially changed and the SSURGO data cannot fully reflect current topographic reality in the Rainwater Basin.     

Measuring Suspended‐Sediment Concentration and Turbidity in the Middle Mississippi and Lower Missouri Rivers Using Landsat Data

The Middle Mississippi River (MMR) and lower Missouri River (MOR) provide critical navigation waterways, ecological habitat, and flood conveyance. They are also directly linked to processes affecting geomorphic and ecological conditions in the lower MR and Delta. For this study, a method was developed to measure suspended‐sediment concentration (SSC) and turbidity along the MMR and the lower MOR using Landsat imagery. Data from nine United States Geological Survey water‐quality monitoring stations were used to create a model‐development dataset and a model‐validation dataset. Concurrent gaging data were identified for available Landsat images to generate the datasets. Surface‐reflectance filters were developed to eliminate images with cirrus cloud coverage or vessel traffic. Using the filtered model‐development dataset, unique reflectance‐SSC and reflectance‐turbidity models were developed for three Landsat sensors: Landsat 8 Operational Land Imager, Landsat 7 Enhanced Thematic Mapper Plus, and Landsat 4–5 Thematic Mapper. Coefficient of determination values for the models ranged from 0.72 to 0.88 for the model‐development dataset. The model‐validation dataset was used to evaluate the performance of the models and had coefficient of determination values ranging from 0.62 to 0.79.     

Temporal and Spatial Trends in Nutrient and Sediment Loading to Lake Tahoe,California‐Nevada,USA

Since 1980, the Lake Tahoe Interagency Monitoring Program (LTIMP) has provided stream‐discharge and water quality data—nitrogen (N), phosphorus (P), and suspended sediment—at more than 20 stations in Lake Tahoe Basin streams. To characterize the temporal and spatial patterns in nutrient and sediment loading to the lake, and improve the usefulness of the program and the existing database, we have (1) identified and corrected for sources of bias in the water quality database; (2) generated synthetic datasets for sediments and nutrients, and resampled to compare the accuracy and precision of different load calculation models; (3) using the best models, recalculated total annual loads over the period of record; (4) regressed total loads against total annual and annual maximum daily discharge, and tested for time trends in the residuals; (5) compared loads for different forms of N and P; and (6) tested constituent loads against land use‐land cover (LULC) variables using multiple regression. The results show (1) N and P loads are dominated by organic N and particulate P; (2) there are significant long‐term downward trends in some constituent loads of some streams; and (3) anthropogenic impervious surface is the most important LULC variable influencing water quality in basin streams. Many of our recommendations for changes in water quality monitoring and load calculation methods have been adopted by the LTIMP.