Comparison of satellite reflectance algorithms for estimating turbidity and cyanobacterial concentrations in productive freshwaters using hyperspectral aircraft imagery and dense coincident surface observations.

We analyzed 37 satellite reflectance algorithms and 321 variants for five satellites for estimating turbidity in a freshwater inland lake in Ohio using coincident real hyperspectral aircraft imagery converted to relative reflectance and dense coincident surface observations. This study is part of an effort to develop simple proxies for turbidity and algal blooms and to evaluate their performance and portability between satellite imagers for regional operational turbidity and algal bloom monitoring. Turbidity algorithms were then applied to synthetic satellite images and compared to in situ measurements of turbidity, chlorophyll-a (Chl-a), total suspended solids (TSS) and phycocyanin as an indicator of cyanobacterial/blue green algal (BGA) abundance. Several turbidity algorithms worked well with real Compact Airborne Spectrographic Imager (CASI) and synthetic WorldView-2, Sentinel-2 and Sentinel-3/MERIS/OLCI imagery. A simple red band algorithm for MODIS imagery and a new fluorescence line height algorithm for Landsat-8 imagery had limited performance with regard to turbidity estimation. Blue-Green Algae/Phycocyanin (BGA/PC) and Chl-a algorithms were the most widely applicable algorithms for turbidity estimation because strong co-variance of turbidity, TSS, Chl-a, and BGA made them mutual proxies in this experiment.

An approach to measure parameter sensitivity in watershed hydrological modelling.

Hydrological responses vary spatially and temporally according to watershed characteristics. In this study, the hydrological models that we developed earlier for the Little Miami River (LMR) and Las Vegas Wash (LVW) watersheds in the USA were used for detailed sensitivity analyses. To compare the relative sensitivities of the hydrological parameters of these two models, we used normalized root mean square error (NRMSE). By combining the NRMSE index with the flow duration curve analysis, we derived an approach to measure parameter sensitivities under different flow regimes. Results show that the parameters related to groundwater are highly sensitive in the LMR watershed, whereas the LVW watershed is primarily sensitive to near-surface and impervious parameters. The high and medium flows are more impacted by most of the parameters. The low flow regime was highly sensitive to groundwater-related parameters. Moreover, our approach is found to be useful in facilitating model development and calibration.

Modeling the impacts of farming practices on water quality in the Little Miami River Basin.

Since intensive farming practices are essential to produce enough food for the increasing population, farmers have been using more inorganic fertilizers, pesticides, and herbicides. Agricultural lands are currently one of the major sources of non-point source pollution. However, by changing farming practices in terms of tillage and crop rotation, the levels of contamination can be reduced and the quality of soil and water resources can be improved. Thus, there is a need to investigate the amalgamated hydrologic effects when various tillage and crop rotation practices are operated in tandem. In this study, the Soil Water Assessment Tool (SWAT) was utilized to evaluate the individual and combined impacts of various farming practices on flow, sediment, ammonia, and total phosphorus loads in the Little Miami River basin. The model was calibrated and validated using the 1990-1994 and 1980-1984 data sets, respectively. The simulated results revealed that the SWAT model provided a good simulation performance. For those tested farming scenarios, no-tillage (NT) offered more environmental benefits than moldboard plowing (MP). Flow, sediment, ammonia, and total phosphorus under NT were lower than those under MP. In terms of crop rotation, continuous soybean and corn-soybean rotation were able to reduce sediment, ammonia, and total phosphorus loads. When the combined effects of tillage and crop rotation were examined, it was found that NT with continuous soybean or corn-soybean rotation could greatly restrain the loss of sediments and nutrients to receiving waters. Since corn-soybean rotation provides higher economic revenue, a combination of NT and corn-soybean rotation can be a viable system for successful farming.

Modeling the relationship between land use and surface water quality.

It is widely known that watershed hydrology is dependent on many factors, including land use, climate, and soil conditions. But the relative impacts of different types of land use on the surface water are yet to be ascertained and quantified. This research attempted to use a comprehensive approach to examine the hydrologic effects of land use at both a regional and a local scale. Statistical and spatial analyses were employed to examine the statistical and spatial relationships of land use and the flow and water quality in receiving waters on a regional scale in the State of Ohio. Besides, a widely accepted watershed-based water quality assessment tool, the Better Assessment Science Integrating Point and Nonpoint Sources (BASINS), was adopted to model the plausible effects of land use on water quality in a local watershed in the East Fork Little Miami River Basin. The results from the statistical analyses revealed that there was a significant relationship between land use and in-stream water quality, especially for nitrogen, phosphorus and Fecal coliform. The geographic information systems (GIS) spatial analyses identified the watersheds that have high levels of contaminants and percentages of agricultural and urban lands. Furthermore, the hydrologic and water quality modeling showed that agricultural and impervious urban lands produced a much higher level of nitrogen and phosphorus than other land surfaces. From this research, it seems that the approach adopted in this study is comprehensive, covering both the regional and local scales. It also reveals that BASINS is a very useful and reliable tool, capable of characterizing the flow and water quality conditions for the study area under different watershed scales. With little modification, these models should be able to adapt to other watersheds or to simulate other contaminants. They also can be used to study the plausible impacts of global environmental change. In addition, the information on the hydrologic effects of land use is very useful. It can provide guidelines not only for resource managers in restoring our aquatic ecosystems, but also for local planners in devising viable and ecologically-sound watershed development plans, as well as for policy makers in evaluating alternate land management decisions.