Pascal Storck

Application of a GIS-based distributed hydrology model for prediction of forest harvest effects on peak stream flow in the Pacific Northwest

Spatially distributed rainfall–runoff models, made feasible by the widespread availability of land surface characteristics data (especially digital topography), and the evolution of high power desktop workstations, are particularly useful for assessment of the hydrological effects of land surface change. Three examples are provided of the use of the Distributed Hydrology-Soil–Vegetation Model (DHSVM) to assess the hydrological effects of logging in the Pacific Northwest. DHSVM provides a dynamic representation of the spatial distribution of soil moisture, snow cover, evapotranspiration and runoff production, at the scale of digital topographic data (typically 30–100 m). Among the hydrological concerns that have been raised related to forest harvest in the Pacific Northwest are increases in flood peaks owing to enhanced rain-on-snow and spring radiation melt response, and the effects of forest roads. The first example is for two rain-on-snow floods in the North Fork Snoqualmie River during November 1990 and December 1989. Predicted maximum vegetation sensitivities (the difference between predicted peaks for all mature vegetation compared with all clear-cut) showed a 31% increase in the peak runoff for the 1989 event and a 10% increase for the larger 1990 event. The main reason for the difference in response can be traced to less antecedent low elevation snow during the 1990 event. The second example is spring snowmelt runoff for the Little Naches River, Washington, which drains the east slopes of the Washington Cascades. Analysis of spring snowmelt peak runoff during May 1993 and April 1994 showed that, for current vegetation relative to all mature vegetation, increases in peak spring stream flow of only about 3% should have occurred over the entire basin. However, much larger increases (up to 30%) would occur for a maximum possible harvest scenario, and in a small headwaters catchment, whose higher elevation leads to greater snow coverage (and, hence, sensitivity to vegetation change) during the period of maximum runoff. The third example, Hard and Ware Creeks, Washington, illustrates the effects of forest roads in two heavily logged small catchments on the western slopes of the Cascades. Use of DHSVMs road runoff algorithm shows increases in peak runoff for the five largest events in 1992 (average observed stream flow of 2·1 m3 s−1) averaging 17·4% for Hard Creek and 16·2% for Ware Creek, with a maximum percentage increase (for the largest event, in Hard Creek) of 27%.

Modeling snow accumulation and ablation processes in forested environments

[1] The effects of forest canopies on snow accumulation and ablation processes can be very important for the hydrology of midlatitude and high-latitude areas. A mass and energy balance model for snow accumulation and ablation processes in forested environments was developed utilizing extensive measurements of snow interception and release in a maritime mountainous site in Oregon. The model was evaluated using 2 years of weighing lysimeter data and was able to reproduce the snow water equivalent (SWE) evolution throughout winters both beneath the canopy and in the nearby clearing, with correlations to observations ranging from 0.81 to 0.99. Additionally, the model was evaluated using measurements from a Boreal Ecosystem-Atmosphere Study (BOREAS) field site in Canada to test the robustness of the canopy snow interception algorithm in a much different climate. Simulated SWE was relatively close to the observations for the forested sites, with discrepancies evident in some cases. Although the model formulation appeared robust for both types of climates, sensitivity to parameters such as snow roughness length and maximum interception capacity suggested the magnitude of improvements of SWE simulations that might be achieved by calibration.

Hydrologic effects of logging in western Washington, United States

Possible changes in streamflow associated with logging were analyzed for 23 western Washington catchments with drainage areas from 14 to 1600 km2. Statistically significant trends in annual streamflow minima, uncorrected for climatic influences, are all decreasing and are apparently dominated by a regional climate signal associated with the Pacific Decadal Oscillation, rather than land cover change. Using paired catchment analysis, the number of statistically significant trends detected for the peak flow series is largely within the range of statistical noise. Only in the case of the annual minima were more trends detected than could be attributed to chance, owing in part to the lower relative variability, hence greater detectability of trends in low flows. Investigation of the effect of return period on peak flow changes shows an apparent increase in flood peaks for treatment relative to control catchments, the mean magnitude of which decreases with increasing return interval up to about the 10-year return period. In large part, owing to the small number of catchment pairs available, this analysis cannot be considered conclusive. An alternative approach to evaluating trends in peak flows based on time series residuals of observed flows from hydrology model predictions detected increasing trends in peak flow series, which were largely absent in the paired catchment analysis. This is attributed both to the ability of the model, which acts as the control, to filter out natural variability and to a larger trend “signal” in the residuals analysis resulting from the ability of the method to fix the vegetation condition in the model control.

Regional Environmental Prediction Over the Pacific Northwest

Abstract This paper examines the potential of regional environmental prediction by focusing on the local forecasting effort in the Pacific Northwest. A consortium of federal, state, and local agencies have funded the development and operation of a multifaceted numerical prediction system centered at the University of Washington that includes atmospheric, hydrologic, and air quality models, the collection of real-time regional weather data sources, and a number of realtime applications using both observations and model output. The manuscript reviews northwest modeling and data collection systems, describes the funding and management system established to support and guide the effort, provides some examples of regional real-time applications, and examines the national implications of regional environmental prediction.

A method for the optimal location of monitoring wells for detection of groundwater contamination in three‐dimensional heterogenous aquifers

We present an optimization method for the design of monitoring well networks to detect initial groundwater contamination in three-dimensional heterogenous aquifers. A Monte Carlo–based approach generates a large number of equally likely realizations of a random hydraulic conductivity field and a contaminant leak location. A finite difference groundwater flow model and a particle-tracking model generate a contaminant plume for each realization. Information from the flow and transport simulations is passed to an optimization model based upon a facility location analogy. The optimization model is a large integer programming problem which is solved approximately by the method of simulated annealing to determine optimal trade-off curves among the following three conflicting objectives: (1) maximum detection probability, (2) minimum cost (i.e., number of monitoring wells), and (3) minimum volume of contaminated groundwater at the time of detection. The method is applied to a unit-scaled hypothetical three-dimensional site to determine the sensitivity of the trade-off curves to various model parameters. Application to an existing landfill site reveals that the existing well network is suboptimal with respect to the considered objectives.

Description and Evaluation of a Hydrometeorological Forecast System for Mountainous Watersheds

Abstract This paper describes and evaluates an automated riverflow forecasting system for the prediction of peak flows during the cool season of 1998–99 over six watersheds in western Washington. The forecast system is based on the Pennsylvania State University–National Center for Atmospheric Research (Penn State–NCAR) fifth-generation Mesoscale Model (MM5) and the University of Washington Distributed-Hydrology-Soil-Vegetation Model (DHSVM). The control simulation used the forecasts produced by the University of Washingtons real-time MM5 forecasts system as input to the hydrologic model. A second set of simulations applied a correction scheme that reduced the long-term precipitation bias identified in the MM5 precipitation field. A third set of simulations used only those observations that are available in real time for forcing the hydrologic model. The various MM5–DHSVM forecasts are also compared with those issued by the National Weather Service Northwest River Forecast Center. Results showed that the ...