Laboratory Study of Watershed Hydrology (HES 14)

National Science Foundation, Research Grant GP-1464unpublishednot peer reviewe

Spatial characteristics of thunderstorm rainfall fields and their relation to runoff

The main aim of this study was to assess the ability of simple geometric measures of thunderstorm rainfall in explaining the runoff response from the watershed. For calculation of storm geometric properties (e.g. areal coverage of storm, areal coverage of the high-intensity portion of the storm, position of storm centroid and the movement of storm centroid in time), spatial information of rainfall is needed. However, generally the rainfall data consists of rainfall depth values over an unevenly spaced network of raingauges. For this study, rainfall depth values were available for 91 raingauges in a watershed of about 148 km2. There was a question about which interpolation method should be used for obtaining uniformly gridded data. Therefore, a small study was undertaken to compare cross-validation statistics and computed geometric parameters using two interpolation methods (kriging and multiquadric). These interpolation methods were used to estimate precipitation over a uniform 100 m × 100 m grid. The cross-validation results from the two methods were generally similar and neither method consistently performed better than the other did. In view of these results we decided to use multiquadric interpolation method for the rest of the study. Several geometric measures were then computed from interpolated surfaces for about 300 storm events occurring in a 17-year period. The correlation of these computed measures with basin runoff were then observed in an attempt to assess their relative importance in basin runoff response. It was observed that the majority of the storms (observed in the study) covered the entire watershed. Therefore, it was concluded that the areal coverage of storm was not a good indicator of the amount of runoff produced. The areal coverage of the storm core (10-min intensity greater than 25 mm/h), however, was found to be a much better predictor of runoff volume and peak rate. The most important variable in runoff production was found to be the volume of the storm core. It was also observed that the position of the storm core relative to the watershed outlet becomes more important as the catchment size increases, with storms positioned in the central portion of the watershed producing more runoff than those positioned near the outlet or near the head of the watershed. This observation indicates the importance of interaction of catchment size and shape with the spatial storm structure in runoff generation. Antecedent channel wetness was found to be of some importance in explaining runoff for the largest of the three watersheds studied but antecedent watershed wetness did not appreciably contributed to runoff explanation. © 2002 Elsevier Science B.V. All rights reserved

Nitrogen retention in the riparian zone of watersheds underlain by discontinuous permafrost

Thesis (M.S.) University of Alaska Fairbanks, 2005Riparian zones function as important ecotones for reducing nitrate concentration in groundwater and inputs into streams. In the boreal forest of interior Alaska, permafrost confines subsurface flow through the riparian zone to shallow organic horizons, where plant uptake of nitrate and denitrification are typically high. Two research questions were addressed in this study: 1) how does riparian zone nitrogen retention vary in watersheds underlain by discontinuous permafrost, and 2) what is the contribution of denitrification to riparian zone nitrogen retention? To estimate the contribution of the riparian zone to watershed nitrogen retention, I analyzed groundwater chemistry using an end-member mixing model. To assess the importance of denitrification as a mechanism of nitrogen retention, I conducted field denitrification assays using the acetylene block technique. Over the summer, nitrogen retention averaged 0.75 and 0.22 mmol N m⁻² d⁻¹ in low and high permafrost watersheds, respectively. Compared with the fluvial export of nitrogen, the retention rate of nitrogen in the riparian zone is 10 - 15% of the loss rate in stream flow. Denitrification accounted for a small proportion (3%) of total nitrogen retention in the riparian zone. Variation in nitrogen retention between watersheds did not account for differences in stream nitrate concentration between watersheds.Introduction -- Factors controlling denitrification -- Riparian zones as nutrient filters -- Models of riparian zone function -- Permafrost and hydrology -- Caribou Poker Creeks Research Watershed (CPCRW) -- References -- Nitrogen retention in the riparian zone of watersheds underlain by discontinuous permafrost -- Conclusions -- References

Simulations of snow distribution and hydrology in a mountain basin

We applied a version of the Regional Hydro‐Ecologic Simulation System (RHESSys) that implements snow redistribution, elevation partitioning, and wind‐driven sublimation to Loch Vale Watershed (LVWS), an alpine‐subalpine Rocky Mountain catchment where snow accumulation and ablation dominate the hydrologic cycle. We compared simulated discharge to measured discharge and the simulated snow distribution to photogrammetrically rectified aerial (remotely sensed) images. Snow redistribution was governed by a topographic similarity index. We subdivided each hillslope into elevation bands that had homogeneous climate extrapolated from observed climate. We created a distributed wind speed field that was used in conjunction with daily measured wind speeds to estimate sublimation. Modeling snow redistribution was critical to estimating the timing and magnitude of discharge. Incorporating elevation partitioning improved estimated timing of discharge but did not improve patterns of snow cover since wind was the dominant controller of areal snow patterns. Simulating wind‐driven sublimation was necessary to predict moisture losses

Hydrologic Simulations of the Maquoketa River Watershed Using SWAT Working Paper 09-WP 49,June 2009

This paper describes the application of the Soil and Water Assessment Tool (SWAT) model to the Maquoketa River watershed, located in northeast Iowa. The inputs to the model were obtained from the Environmental Protection Agency’s geographic information/database system called Better Assessment Science Integrating Point and Nonpoint Sources (BASINS). Climatic data from six weather stations located in and around the watershed, and measured streamflow data from a U.S. Geological Survey gage station at the watershed outlet were used in the sensitivity analysis of SWAT model parameters as well as its calibration and validation for watershed hydrology and streamflow. A sensitivity analysis was performed using an influence coefficient method to evaluate surface runoff and base flow variations in response to changes in model input hydrologic parameters. The curve number, evaporation compensation factor, and soil available water capacity were found to be the most sensitive parameters among eight selected parameters when applying SWAT to the Maquoketa River watershed. Model calibration, facilitated by the sensitivity analysis, was performed for the period 1988 through 1993, and validation was performed for 1982 through 1987. The model performance was evaluated by well-established statistical methods and was found to explain at least 86% and 69% of the variability in the measured stream flow data for the calibration and validation periods, respectively. This initial hydrologic modeling analysis will facilitate future applications of SWAT to the Maquoketa River watershed for various watershed analysis, including water quality

A Conceptualized Groundwater Flow Model Development for Integration with Surface Hydrology Model

A groundwater system model was developed and calibrated in the study area of Lehman Creek watershed, eastern Nevada. The model development aims for integrating the surface hydrologic model - precipitation runoff modeling system (PRMS) model - with the three-dimensional (3D) finite-difference model MODFLOW. A two-layer groundwater model was developed with spatial discretization of 100 x 100 m grid. The water balance was estimated with inflows of gravity drainage and initial streamflow estimated from a calibrated PRMS model, and with outflows of spring discharges, boundary fluxes, and stream base flow. A steady-state model calibration was performed to estimate the hydraulic properties. The modeling results were able to represent the geographic relieves, simulate water balance components, and capture the hydrogeologic features. The preliminary results presented in this study provide insights into the local groundwater flow system and lay groundwork for future study of interactive influences of surface hydrologic variation

The essential value of long-term experimental data for hydrology and water management

We would like to thank the European Research Council ERC for funding the VeWa project and most of Tetzlaff's time (project GA 335910 VeWa). No data were used in producing this manuscript.Peer reviewedPublisher PD

Bringing Statistical Learning Machines Together for Hydro-Climatological Predictions - Case Study for Sacramento San Joaquin River Basin, California

Study region: Sacramento San Joaquin River Basin, California Study focus: The study forecasts the streamflow at a regional scale within SSJ river basin with largescale climate variables. The proposed approach eliminates the bias resulting from predefined indices at regional scale. The study was performed for eight unimpaired streamflow stations from 1962–2016. First, the Singular Valued Decomposition (SVD) teleconnections of the streamflow corresponding to 500 mbar geopotential height, sea surface temperature, 500 mbar specific humidity (SHUM500), and 500 mbar U-wind (U500) were obtained. Second, the skillful SVD teleconnections were screened non-parametrically. Finally, the screened teleconnections were used as the streamflow predictors in the non-linear regression models (K-nearest neighbor regression and data-driven support vector machine). New hydrological insights: The SVD results identified new spatial regions that have not been included in existing predefined indices. The nonparametric model indicated the teleconnections of SHUM500 and U500 being better streamflow predictors compared to other climate variables. The regression models were capable to apprehend most of the sustained low flows, proving the model to be effective for drought-affected regions. It was also observed that the proposed approach showed better forecasting skills with preprocessed large scale climate variables rather than using the predefined indices. The proposed study is simple, yet robust in providing qualitative streamflow forecasts that may assist water managers in making policy-related decisions when planning and managing watersheds