Mark S. Wigmosta

A distributed hydrology‐vegetation model for complex terrain

A distributed hydrology-vegetation model is described that includes canopy interception, evaporation, transpiration, and snow accumulation and melt, as well as runoff generation via the saturation excess mechanisms. Digital elevation data are used to model topographic controls on incoming solar radiation, air temperature, precipitation, and downslope water movement. Canopy evapotranspiration is represented via a two-layer Penman-Monteith formulation that incorporates local net solar radiation, surface meteorology, soil characteristics and moisture status, and species-dependent leaf area index and stomatal resistance. Snow accumulation and ablation are modeled using an energy balance approach that includes the effects of local topography and vegetation cover. Saturated subsurface flow is modeled using a quasi three-dimensional routing scheme. The model was applied at a 180-m scale to the Middle Fork Flathead River basin in northwestern Montana. This 2900-km2, snowmelt-dominated watershed ranges in elevation from 900 to over 3000 m. The model was calibrated using 2 years of recorded precipitation and streamflow. The model was verified against 2 additional years of runoff and against advanced very high resolution radiometer based spatial snow cover data at the 1-km2 scale. Simulated discharge showed acceptable agreement with observations. The simulated areal patterns of snow cover were in general agreement with the remote sensing observations, but were lagged slightly in time.

Evaluating runoff simulations from the Community Land Model 4.0 using observations from flux towers and a mountainous watershed

[1] Previous studies using the Community Land Model (CLM) focused on simulating land-atmosphere interactions and water balance on continental to global scales, with limited attention paid to its capability for hydrologic simulations at watershed or regional scales. This study evaluates the performance of CLM 4.0 (CLM4) for hydrologic simulations and explores possible directions of improvement. Specifically, it is found that CLM4 tends to produce unrealistically large temporal variations of runoff for applications at a mountainous catchment in the northwest United States, where subsurface runoff is dominant, as well as at a few flux tower sites spanning a wide range of climate and site conditions in the United States. Runoff simulations from CLM4 can be improved by (1) increasing spatial resolution of the land surface representations and (2) calibrating model parameter values. We also demonstrate that runoff simulations may be improved by implementing alternative runoff generation schemes such as those from the variable infiltration capacity (VIC) model or the TOPMODEL formulations with a more general power law-based transmissivity profile, which will be explored in future studies. This study also highlights the importance of evaluating both energy and water fluxes in the application of land surface models across multiple scales.

A Physically Based Runoff Routing Model for Land Surface and Earth System Models

AbstractA new physically based runoff routing model, called the Model for Scale Adaptive River Transport (MOSART), has been developed to be applicable across local, regional, and global scales. Within each spatial unit, surface runoff is first routed across hillslopes and then discharged along with subsurface runoff into a “tributary subnetwork” before entering the main channel. The spatial units are thus linked via routing through the main channel network, which is constructed in a scale-consistent way across different spatial resolutions. All model parameters are physically based, and only a small subset requires calibration. MOSART has been applied to the Columbia River basin at ⅙°, ⅛°, ¼°, and ½° spatial resolutions and was evaluated using naturalized or observed streamflow at a number of gauge stations. MOSART is compared to two other routing models widely used with land surface models, the River Transport Model (RTM) in the Community Land Model (CLM) and the Lohmann routing model, included as a post...

Integrated Evaluation of Cost, Emissions, and Resource Potential for Algal Biofuels at the National Scale

Costs, emissions, and resource availability were modeled for the production of 5 billion gallons yr(-1) (5 BGY) of renewable diesel in the United States from Chlorella biomass by hydrothermal liquefaction (HTL). The HTL model utilized data from a continuous 1-L reactor including catalytic hydrothermal gasification of the aqueous phase, and catalytic hydrotreatment of the HTL oil. A biophysical algae growth model coupled with weather and pond simulations predicted biomass productivity from experimental growth parameters, allowing site-by-site and temporal prediction of biomass production. The 5 BGY scale required geographically and climatically distributed sites. Even though screening down to 5 BGY significantly reduced spatial and temporal variability, site-to-site, season-to-season, and interannual variations in productivity affected economic and environmental performance. Performance metrics based on annual average or peak productivity were inadequate; temporally and spatially explicit computations allowed more rigorous analysis of these dynamic systems. For example, 3-season operation with a winter shutdown was favored to avoid high greenhouse gas emissions, but economic performance was harmed by underutilized equipment during slow-growth periods. Thus, analysis of algal biofuel pathways must combine spatiotemporal resource assessment, economic analysis, and environmental analysis integrated over many sites when assessing national scale performance.

Application of a subgrid orographic precipitation/surface hydrology scheme to a mountain watershed

A regional climate model including a physically based parameterization of the subgrid effects of topography on clouds and precipitation is driven by observed meteorology on its lateral boundaries for a period of 12 months. The meteorology simulated by the model for each subgrid elevation class is distributed across a mountain watershed according to the surface elevation within the watershed. The simulated meteorology is used to drive a detailed model of hydrology-vegetation dynamics at the topographic scale described by digital elevation data, 180 m. The watershed model, which includes a two-layer canopy model for evapotranspiration, an energy-balance model for snow accumulation and melt, a two-layer rooting zone model, and a quasi-three-dimensional saturated subsurface flow model, is used to simulate the seasonal cycle of the accumulation and melt of snow and the accumulation and discharge of surface water within a mountain watershed in northwestern Montana. Comparisons between the simulated and the recorded snow cover and river discharge at the base of the watershed indicate comparable if not better agreement than between the recorded fields and those simulated by the watershed model driven by meteorology observed at two stations within the watershed. The agreement with the recorded discharge, precipitation, and snow water equivalent is also clearly superior to simulations driven by the regional climate model run without the subgrid parameterization but with one-third the grid size of the simulation with the subgrid parameterization.

An adaptive modeling and monitoring approach to describe the hydrologic behavior of small catchments

Abstract An adaptive combination of field mapping, simple hydrologic monitoring, and hydrologic modeling was used to describe the hydrologic behavior of two zero-order catchments: one undeveloped forest, the other suburban. Field mapping was used to delineate hydrologic process zones and provide guidance for the location of monitoring stations. Hydrologic monitoring included continuous streamflow and precipitation, as well as limited piezometer information. The hydrologic model was developed in conjunction with the measurement program to assure that the level of model detail was consistent with the level of field measurements used for model input and testing. At the start of the work it was anticipated that saturation overland flow would drive peak discharge in the forested catchment and Horton overland flow from impervious surfaces would dominate storm runoff in the suburban catchment. Instead, subsurface flow was found to dominate both annual and peak discharge in the forested site, and discharge from lawns and other pervious areas accounted for roughly 60% of annual and storm runoff from the suburban catchment. The adaptive combination of modeling and measurements was essential to elucidate the various components of flow production and flow paths in these catchments.

A GIS Cost Model to Assess the Availability of Freshwater, Seawater, and Saline Groundwater for Algal Biofuel Production in the United States

A key advantage of using microalgae for biofuel production is the ability of some algal strains to thrive in waters unsuitable for conventional crop irrigation such as saline groundwater or seawater. Nonetheless, the availability of sustainable water supplies will provide significant challenges for scale-up and development of algal biofuels. We conduct a partial techno-economic assessment based on the availability of freshwater, saline groundwater, and seawater for use in open pond algae cultivation systems. We explore water issues through GIS-based models of algae biofuel production, freshwater supply (constrained to less than 5% of mean annual flow per watershed) and costs, and cost-distance models for supplying seawater and saline groundwater. We estimate that, combined, these resources can support 9.46 × 10(7) m(3) yr(-1) (25 billion gallons yr(-1)) of renewable biodiesel production in the coterminous United States. Achievement of larger targets requires the utilization of less water efficient sites and relatively expensive saline waters. Despite the addition of freshwater supply constraints and saline water resources, the geographic conclusions are similar to our previous results. Freshwater availability and saline water delivery costs are most favorable for the coast of the Gulf of Mexico and Florida peninsula, where evaporation relative to precipitation is moderate. As a whole, the barren and scrub lands of the southwestern U.S. have limited freshwater supplies, and large net evaporation rates greatly increase the cost of saline alternatives due to the added makeup water required to maintain pond salinity. However, this and similar analyses are particularly sensitive to knowledge gaps in algae growth/lipid production performance and the proportion of freshwater resources available, key topics for future investigation.

Development of Hourly Meteorological Values From Daily Data and Significance to Hydrological Modeling at H. J. Andrews Experimental Forest

Hydrologic modeling depends on having quality meteorological input available at the simulation time step. Often two needs arise: disaggregation from daily to subdaily and extend an available subdaily record. Simple techniques were tested for generating hourly air temperature, precipitation, solar radiation, relative humidity, and wind speed from limited daily data at the H. J. Andrews Experimental Forest, Oregon. Skill of the daily to hourly methods ranged from poor to very good. The best method for each variable had mean error ,4% and first-degree efficiency.0.5, with the exception of wind speed, which had a bias problem related to change in measurement height. Significance of the disaggregation assumptions for simulated hydrology was evaluated by driving the Distributed Hydrology Soil Vegetation Model (DHSVM) with alternative meteorological inputs. The largest differences in streamflow simulation efficiency were related to differences in precipitation phase, which followed from the air temperature method used. The largest differences in annual water balance were related to the humidity model used; the common fallback assumption that daily dewpoint temperature equals minimum air temperature led to sharply higher evapotranspiration. Hourly streamflow and annual water balance were less sensitive to the method of distributing precipitation throughout the day and parameterization of solar radiation.

Siting Algae Cultivation Facilities for Biofuel Production in the United States: Trade-Offs between Growth Rate, Site Constructability, Water Availability, and Infrastructure

Locating sites for new algae cultivation facilities is a complex task. The climate must support high growth rates, and cultivation ponds require appropriate land and water resources, as well as transportation and utility infrastructure. We employ our spatiotemporal Biomass Assessment Tool (BAT) to select promising locations based on the open-pond cultivation of Arthrospira sp. and strains of the order Sphaeropleales. A total of 64,000 sites across the southern United States were evaluated. We progressively applied screening criteria and tracked their impact on the number of potential sites, geographic location, and biomass productivity. Both strains demonstrated maximum productivity along the Gulf of Mexico coast, with the highest values on the Florida peninsula. In contrast, sites meeting all selection criteria for Arthrospira were located along the southern coast of Texas and for Sphaeropleales were located in Louisiana and southern Arkansas. Results were driven mainly by the lack of oil pipeline access in Florida and elevated groundwater salinity in southern Texas. The requirement for low-salinity freshwater (<400 mg L(-1)) constrained Sphaeropleales locations; siting flexibility is greater for salt-tolerant species like Arthrospira. Combined siting factors can result in significant departures from regions of maximum productivity but are within the expected range of site-specific process improvements.

Scalability of grid‐ and subbasin‐based land surface modeling approaches for hydrologic simulations

This paper investigates the relative merits of grid-and subbasin-based land surface modeling approaches for hydrologic simulations, with a focus on their scalability (i.e., ability to perform consistently across spatial resolutions) in simulating runoff generation. Simulations are produced by the grid- and subbasin-based Community Land Model at 0.125°, 0.25°, 0.5°, and 1° spatial resolutions over the U.S. Pacific Northwest. Using the 0.125° simulation as the “reference” solution, statistical metrics are calculated by comparing simulations at 0.25°, 0.5°, and 1° resolutions with the 0.125° simulation for each approach. Statistical significance test results suggest significant scalability advantage for the subbasin-based approach compared to the grid-based approach. Basin level annual average relative errors of surface runoff at 0.25°, 0.5°, and 1° resolutions compared to the 0.125° simulation are 3%, 4%, and 6% for the subbasin-based configuration and 4%, 7%, and 11% for the grid-based configuration, respectively. The scalability advantages are more pronounced during winter/spring and over mountainous regions. The source of runoff scalability is found to be related to the scalability of major meteorological and land surface parameters of runoff generation. More specifically, the subbasin-based approach is more consistent across spatial scales than the grid-based approach in snowfall/rainfall partitioning because of scalability related to air temperature and surface elevation. Scalability of a topographic parameter used in runoff parameterization also contributes to improved scalability of the rain-driven saturated surface runoff component, particularly during winter. Hence, this study demonstrates the importance of spatial structure for multiscale modeling of hydrological processes.