Search Results (8)

This study utilized a max-stable process (MSP) model with a dependence structure defined via a non-Euclidean distance metric, with the goal of modelling extreme flood data on a river network. The dataset was composed of mean daily discharge observations from 22 United States Geological Survey streamflow gaging stations for river basins in Missouri and Arkansas. The analysis included the application of the elastic-net penalty to automatically build spatially varying trend surfaces to model the marginal distributions. The dependence model accounted for the river distance between hydrologically connected gaging sites and the hydrologic distance, defined as the Euclidean distance between the centers of site’s associated drainage areas, for all stations. Modelling the marginal distributions and spatial dependence among the extremes are two key components for spatially modelling extremes. Among the 16 covariates evaluated for marginal fitting, 7 were selected to spatially model the generalized extreme value (GEV) location parameter (for each gaging station’s contributing drainage basin, its outlet elevation, centroid x coordinate, centroid elevation, area, average basin width, elevation range, and median land surface slope). The three covariates selected for the GEV scale parameter included the area, average basin width, and median land surface slope. The GEV shape parameter was assumed to be constant throughout the entire study area. Comparisons of estimates obtained from the spatial covariate model with their corresponding “at-site” estimates resulted in computed values of 0.95, 0.95, 0.94 and 0.85, 0.84, 0.90 for the coefficient of determination, Nash–Sutcliffe efficiency, and Kling–Gupta efficiency for the GEV location and scale parameters, respectively. Brown–Resnick MSP models were fit to independent multivariate events extracted from a set of common discharge data, transformed to unit Fréchet margins while considering different permutations of the non-Euclidean dependence model. Each of the fitted model’s log-likelihood values indicated improved fits when using hydrologic distance rather than Euclidean distance. They also demonstrated that accounting for flow-connected dependence and anisotropy further improved model fit. In this study, the results from both parts were illustrative; however, further research with larger datasets and more heterogeneous systems is recommended. Full article

The Missouri River Basin is the largest single river basin in the United States, and, as such, it plays an important role in natural ecosystems as well as the country’s economy, through agriculture, hydroelectric power generation, and transportation. Episodes of heavy precipitation can have a substantial negative impact on all these aspects of the basin, so understanding how well these episodes are simulated and projected to change in the future climate is important. We analyzed contemporary and projected mid-century behavior of heavy-precipitation episodes using an object-oriented analysis to diagnose short-term (≥5-day) and extended-period (≥30-day) events with substantial precipitation, using PRISM gridded, observed precipitation and RegCM4 regional-climate simulations that used outputs from two different GCMs for boundary conditions. The simulations were produced for the North American portion of the CORDEX program. A 25 km grid was used for the simulations and for aggregated PRISM precipitation. Overall, the simulated contemporary-climate events compared favorably with the PRISM events’ frequency and duration. The simulated event areas tended to be larger than the areas in the PRISM events, suggesting that the effective resolution of the simulations is greater than 25 km. Event areas and durations change little going from contemporary to scenario climate. The short-term events increase in frequency by an amount commensurate with the increase in mean precipitation simulated for the basis. However, the extended-term events showed little change in frequency, despite the average precipitation increase. Roughly half the extended-period events overlapped with at least one short-term event in both the observations and the simulations. Extended-period events that overlap a short-term event generally have larger areas and longer durations compared to their counterparts with no overlapping short-term events. Understanding the climate dynamics yielding the two types of extended-period events could be useful for assessing future changes in the Missouri River Basin’s heavy precipitation events and their impact. Full article

This article describes the opinions and perceptions of farmers on water management tools that conserve groundwater and on alternative sources of water for irrigation. The analysis is based on a survey of producers ($N=466$) across the Lower Mississippi River Basin (LMRB) areas of Arkansas, Louisiana, Mississippi, and Missouri. Summary statistics of practice usage across the region and for each state are presented. A Poisson count model is applied to the data to identify factors that influence the number of groundwater-conserving practices employed. The number of irrigated acres, years of farming, annual income level, perception of groundwater problems, and participation in conservation programs have statistically significant association with the number of practices employed. Years of farming experience is the only factor negatively associated with the number of practices employed, while participation in conservation programs has the largest magnitude effect on that number. These results provide evidence that sponsored conservation programs increase the number of conservation practices adopted by farmers. This insight is useful for producer collectives, policy makers, and program managers to design and target of conservation programs across the LMRB. Full article

Ongoing and projected changes in climate are expected to alter discharge and water temperature in riverine systems, thus resulting in degraded habitat. Climate adaptation management strategies are proposed to serve as buffers to changes in air temperature and precipitation, with these strategies potentially providing relatively stable protection for flow and thermal regimes. Using a hydrologic and water temperature modeling approach in the Meramec River basin in eastern Missouri, U.S.A., we examined the ability of forested riparian buffers to serve as a useful climate adaptation strategy against ongoing and projected changes in climate. We developed a multi-scale approach using Soil and Water Assessment Tool (SWAT) hydrologic and water temperature models as well as a Stream Network Temperature Model (SNTEMP) with different amounts of simulated riparian vegetation to estimate streamflow and water temperature variation within the Meramec River basin under both contemporary and projected future climate conditions. Our results suggest that riparian buffers offer benefits to mitigating increases in water temperature due to shading effects; however, patterns in discharge did not vary substantially based on simulations. From an ecological perspective, the addition of riparian buffers is also projected to reduce the impacts of climate change on Smallmouth Bass (Micropterus dolomieu) by decreasing the number of days water temperatures exceed the thermal tolerance of this species. Full article

This study addresses the water quantity and quality implications of greenhouse gas mitigation efforts in agriculture and forestry. This is done both through a literature review and a case study. The case study is set in the Missouri River Basin (MRB) and involves integration of a water hydrology model and a land use model with an econometric model estimated to make the link. The hydrology model (Soil and Water Assessment Tool, SWAT) is used to generate a multiyear, multilocation dataset that gives estimated water quantity and quality measures dependent on land use. In turn, those data are used in estimating a quantile regression model linking water quantity and quality with climate and land use. Additionally, a land use model (Forest and Agricultural Sector Optimization Model with Greenhouse Gases, FASOMGHG) is used to simulate the extent of mitigation strategy adoption and land use implications under alternative carbon prices. Then, the land use results and climate change forecasts are input to the econometric model and water quantity/quality projections developed. The econometric results show that land use patterns have significant influences on water quantity. Specifically, an increase in grassland significantly decreases water quantity, with forestry having mixed effects. At relatively high quantiles, land use changes from cropped land to grassland reduce water yield, while switching from cropping or grassland to forest yields more water. It also shows that an increase in cropped land use significantly degrades water quality at the 50% quantile and moving from cropped land to either forest or pasture slightly improves water quality at the 50% quantile but significantly worsens water quality at the 90% quantile. In turn, a simulation exercise shows that water quantity slightly increases under mitigation activity stimulated by lower carbon prices but significantly decreases under higher carbon prices. For water quality, when carbon prices are low, water quality is degraded under most mitigation alternatives but quality improves under higher carbon prices. Full article

Degradation of streams and associated riparian habitat across the Missouri River Headwaters Basin has motivated several stream restoration projects across the watershed. Many of these projects install a series of beaver dam analogues (BDAs) to aggrade incised streams, elevate local water tables, and create natural surface water storage by reconnecting streams with their floodplains. Satellite imagery can provide a spatially continuous mechanism to monitor the effects of these in-stream structures on stream surface area. However, remote sensing-based approaches to map narrow (e.g., <5 m wide) linear features such as streams have been under-developed relative to efforts to map other types of aquatic systems, such as wetlands or lakes. We mapped pre- and post-restoration (one to three years post-restoration) stream surface area and riparian greenness at four stream restoration sites using Worldview-2 and 3 images as well as a QuickBird-2 image. We found that panchromatic brightness and eCognition-based outputs (0.5 m resolution) provided high-accuracy maps of stream surface area (overall accuracy ranged from 91% to 99%) for streams as narrow as 1.5 m wide. Using image pairs, we were able to document increases in stream surface area immediately upstream of BDAs as well as increases in stream surface area along the restoration reach at Robb Creek, Alkali Creek and Long Creek (South). Although Long Creek (North) did not show a net increase in stream surface area along the restoration reach, we did observe an increase in riparian greenness, suggesting increased water retention adjacent to the stream. As high-resolution imagery becomes more widely collected and available, improvements in our ability to provide spatially continuous monitoring of stream systems can effectively complement more traditional field-based and gage-based datasets to inform watershed management. Full article

We evaluate performance of the Catchment Land Surface Model (CLSM) under flood conditions after the assimilation of observations of the terrestrial water storage anomaly (TWSA) from NASA’s Gravity Recovery and Climate Experiment (GRACE). Assimilation offers three key benefits for the viability of GRACE observations to operational applications: (1) near-real time analysis; (2) a downscaling of GRACE’s coarse spatial resolution; and (3) state disaggregation of the vertically-integrated TWSA. We select the 2011 flood event in the Missouri river basin as a case study, and find that assimilation generally made the model wetter in the months preceding flood. We compare model outputs with observations from 14 USGS groundwater wells to assess improvements after assimilation. Finally, we examine disaggregated water storage information to improve the mechanistic understanding of event generation. Validation establishes that assimilation improved the model skill substantially, increasing regional groundwater anomaly correlation from 0.58 to 0.86. For the 2011 flood event in the Missouri river basin, results show that groundwater and snow water equivalent were contributors to pre-event flood potential, providing spatially-distributed early warning information. Full article

Collection and investigation of flood information are essential to understand the nature of floods, but this has proved difficult in data-poor environments, or in developing or under-developed countries due to economic and technological limitations. The development of remote sensing data, GIS, and modeling techniques have, therefore, proved to be useful tools in the analysis of the nature of floods. Accordingly, this study attempts to estimate a flood discharge using the generalized likelihood uncertainty estimation (GLUE) methodology and a 1D hydraulic model, with remote sensing data and topographic data, under the assumed condition that there is no gauge station in the Missouri river, Nebraska, and Wabash River, Indiana, in the United States. The results show that the use of Landsat leads to a better discharge approximation on a large-scale reach than on a small-scale. Discharge approximation using the GLUE depended on the selection of likelihood measures. Consideration of physical conditions in study reaches could, therefore, contribute to an appropriate selection of informal likely measurements. The river discharge assessed by using Landsat image and the GLUE Methodology could be useful in supplementing flood information for flood risk management at a planning level in ungauged basins. However, it should be noted that this approach to the real-time application might be difficult due to the GLUE procedure. Full article