Areas of Research

 

 

Soil Moisture Variability and Topography

 

Soil moisture is a key variable in hydrology because it influences the production of runoff at the surface, transpiration rates from crops and other vegetation, and recharge to shallow aquifers.  Unfortunately, direct measurement of soil moisture is difficult.  In-situ methods observe soil moisture only at the sampling locations, and extrapolating these measurements to the spatial scales of most practical applications is unreliable.  In contrast, remote sensing methods typically observe soil moisture near the ground surface and at coarse spatial resolutions.  Dr. Niemannís research group is studying the physical processes that control soil moisture, statistical properties of soil moisture patterns, impacts of soil moisture on regional hydrology, methods to estimate soil moisture from remote sensing, and methods to interpolate and downscale soil moisture observations. Understanding the spatial patterns and temporal dynamics of soil moisture is important to water resources planning, flood forecasting, land management, and other applications.

 

 

Channel Networks and Hydrologic Response

 

Basin morphology plays a key role in both the production of runoff and the transfer of storm flows out of watersheds.  Basic characteristics of basin geometry are commonly used to forecast storm flow hydrographs for hydrologic design, but detailed consideration of the geometric structure of the basin is usually neglected.  Dr. Niemannís research group is examining the role that channel network structure plays in hydrologic response.  This research topic includes identification of different classifications of channel networks, understanding the origins of those classifications, and using the characteristics of those network classifications to better predict hydrologic response.  This research is important to developing improved models for simulating basin hydrology in both natural and urban basins.

 

Snow and Frozen Ground Modeling

 

Snowpack is an important source for water supply and flood prediction in many parts of the world.† In the western U.S., for example, runoff from snowmelt provides a large majority of annual water supplies.† Similarly, the presence of frozen ground can impede infiltration and enhance flood production.† Both snowpack and frozen ground are often heterogeneous within watersheds due to spatial variations in the topography, ground cover, and soil properties.† Dr. Niemannís research group is developing improved methods to model the spatial and temporal patterns of snowpack and frozen ground in watersheds.† These tools are expected to improve the accuracy of water supply and flood forecasting methods.

 

Uncertainty in Geomorphic Modeling

 

Many governmental agencies face decisions that involve the potential for economic losses, environmental impacts, and even loss of life if made incorrectly. These decisions are often based on the results of numerical models that simulate watershed hydrology, channel flow, and/or sediment transport. However, it is well-known that the predictions from these models have significant uncertainty associated with them.  Dr. Niemann's research group is developing practical tools to quantify and ultimately reduce the uncertainty associated with hydrologic, hydraulic, and geomorphic models. These tools aim to identify and characterize uncertainties due to the assumed mathematical structure of the model as well as the uncertainty due to parameter estimation and other sources. Ultimately, these tools could result in more reliable predictions and more efficient designs.

 

Scaling Invariance and Basin Morphology

 

River basin topography commonly appears similar when viewed at different magnifications.  Without an indication of scale, it is difficult to determine whether a photograph of a river basin displays one hundred square kilometers or ten thousand square kilometers. This property is known as scaling invariance and is closely related to the notions of fractals and chaos. Many hydrologic variables exhibit this tendency including precipitation rates, soil moisture patterns, and hydrologic conductivity.  In fact, a wide variety of natural objects have fractal geometry.  Scaling invariance is a useful property for hydrologists because it relates the statistical properties of small features to those of large features.  Thus, it can help characterize, simulate, and interpolate hydrologic variables.  Dr. Niemannís research group is examining the scaling invariant properties of topography and soil moisture.  They are quantitatively characterizing the scaling invariance, understanding its dynamic origin (as well as the origin of deviations from scaling), and exploring the interconnections between the scaling of topography and soil moisture.

 

Evapotranspiration from Shallow Groundwater

 

Numerous regions with irrigated agricultural have water tables that are near the ground surface.  Shallow water tables can reduce crop productivity not only due to waterlogging but also due to the high salinity that sometimes occurs in groundwater.   In addition, evapotranspiration from uncropped areas, which can be supplied by shallow groundwater, may represent a significant non-beneficial consumptive use of water.  Dr. Niemannís research group is studying how evapotranspiration from uncropped areas with shallow water tables depends on the water table depth and other factors such as the vegetation cover and soil salinity.  This research couples evapotranspiration estimates from a remote-sensing method with measurements of water table depth, soil moisture, soil salinity, and vegetation properties.  Ultimately, this research is expected to improve our understanding of the water balance in agri-ecological systems and to improve numerical models that are being used to evaluate potential solutions to waterlogging and salinization problems.

 

River Basin Evolution and Modeling

 

One of the more exciting advances in geomorphological research is the emergence of computer models that simulate the evolution of river basins over long periods of time.  While these models are still rudimentary, they successfully reproduce many empirical features of river basin topography including dendritic river networks, concave profiles of stream courses, and convex profiles of hillslopes.  Eventually, these models could be used to understand the long-term impacts of climate and land-use changes, as well as the movement of sediment and long-lived pollutants in basins.  Dr. Niemannís research group is developing better representations of hydrologic processes in these models and studying the role these processes play in landscape evolution. They are also investigating how the historical persistence of hydrologic processes impacts the current hydrologic behavior of basins.