METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL1

ABSTRACT: The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.     

THE VULNERABILITY OF WETLANDS TO CLIMATE CHANGE: A HYDROLOGIC LANDSCAPE PERSPECTIVE1

ABSTRACT: The vulnerability of wetlands to changes in climate depends on their position within hydrologic landscapes. Hydrologic landscapes are defined by the flow characteristics of ground water and surface water and by the interaction of atmospheric water, surface water, and ground water for any given locality or region. Six general hydrologic landscapes are defined; mountainous, plateau and high plain, broad basins of interior drainage, riverine, flat coastal, and hummocky glacial and dune. Assessment of these landscapes indicate that the vulnerability of all wetlands to climate change fall between two extremes: those dependent primarily on precipitation for their water supply are highly vulnerable, and those dependent primarily on discharge from regional ground water flow systems are the least vulnerable, because of the great buffering capacity of large ground water flow systems to climate change.     

Spatiotemporal variability of wet atmospheric nitrogen deposition to the Neuse River Estuary, North Carolina

Excessive nitrogen (N) loading to N-sensitive waters such as the Neuse River estuary (North Carolina) has been shown to promote changes in microbial and algal community composition and function (harmful algal blooms), hypoxia and anoxia, and fish kills. Previous studies have estimated that wet atmospheric deposition of nitrogen (WAD-N), as deposition of dissolved inorganic nitrogen (DIN: NO3-, NH3/NH4+) and dissolved organic nitrogen, may contribute at least 15% of the total externally supplied or "new" N flux to the coastal waters of North Carolina. In a 3-yr study from June 1996 to June 1999, we calculated the weekly wet deposition of inorganic and organic N at eleven sites on a northwest-southeast transect in the watershed. The annual mean total (wet DIN + wet organics) WAD-N flux for the Neuse River watershed was calculated to be 956 mg N/m2/yr (15026 Mg N/yr). Seasonally, the spring (March-May) and summer (June-August) months contain the highest total weekly N deposition; this pattern appears to be driven by N concentration in precipitation. There is also spatial variability in WAD-N deposition; in general, the upper portion of the watershed receives the lowest annual deposition and the middle portion of the watershed receives the highest deposition. Based on a range of watershed N retention and in-stream riverine processing values, we estimate that this flux contributes approximately 24% of the total "new" N flux to the estuary.     

Respiration and lipid content of the Arctic copepod<Emphasis Type="Italic"> Calanus hyperboreus</Emphasis> overwintering 1 m above the seafloor at 2,300 m water depth in the Fram Strait

In August 2000 high concentrations of the dominant herbivorous copepod Calanus hyperboreus were detected in the Arctic Fram Strait, west of Spitsbergen, 1 m above the seafloor at 2,290 m water depth. Individuals from that layer were sampled by a hyper-benthic net attached to the frame of an epi-benthic sledge. For comparison, the vertical distribution of C. hyperboreus in the water column was studied simultaneously by a multiple opening/closing net haul from 2,250 m depth to the surface. Maximum abundance was found close to the surface with 6.6 and 10.0 ind. m^?3 at 0–50 m and 50–100 m depth, respectively. However, the major fraction of the population (>40%) occurred between 1,000 and 1,500 m depth. In the deepest layer (2,000–2,250 m) abundance measured 2.2 ind. m^?3 and was twice as high as between 100 and 1,000 m depth. In comparison to individuals from surface waters, copepods from the hyper-benthic layer were torpid and did not react to mechanical stimuli. Stage CV copepodids and females from the deep sample contained 4–10% less lipid and showed significantly reduced respiration rates of 0.24 and 0.26 ml O₂ h^?1 g^?1 dry mass (DM) as compared to surface samples (0.49 and 0.43 ml O₂ h^?1 g^?1 DM). All these observations indicate that the hyper-benthic part of the population had already started a dormant overwintering phase at great depth. Based on the lipid deposits and energy demands, the potential maximum duration of the non-feeding dormant phase was estimated at 76–110 days for females and at 98–137 days for CV copepodids, depending on what indispensable minimum lipid content was assumed. In any case, the estimated times could not meet the necessary requirements for a starvation period of >6 months until the next phytoplankton bloom in the following spring. The ecological implications of these results are discussed with respect to the life cycle and eco-physiological adaptations of C. hyperboreus to its high-Arctic habitat.     

Rechts- und naturwissenschaftliche Kooperation im Umweltrecht am Beispiel des Chemikalien- und Naturschutzrechts

Der Beitrag ist aus einem Vortrag hervorgegangen, den der Verfasser am 23. 9. 2009 bei der Jahrestagung der Gesellschaft Deutscher Chemiker, Fachgruppe Umweltchemie und ?kotoxikologie, in Trier gehalten hat. Wenngleich gewichtige Sachgründe für eine fachübergreifende rechts- und naturwissenschaftliche Kooperation sprechen, so stellt sie doch in der gegenw?rtigen universit?ren Forschungslandschaft eher eine Rarit?t dar. Zu den Ursachen hierfür geh?rt, dass eine derartige Kooperation mit erheblichen Schwierigkeiten verbunden ist, die aus der zunehmenden Spezialisierung der Wissenschaft und der damit einhergehenden Herausbildung divergierender F?cherkulturen resultieren. Hinzu kommt, dass die aktuelle Drittmittelf?rderung, die nicht zuletzt auf die Initiierung und Intensivierung von Interdisziplinarit?t zielt, auf Rechtswissenschaftler nur eine vergleichsweise geringe Anreizwirkung ausübt. Doch mehren sich die Anzeichen dafür, dass sich hier alsbald ein Wandel vollzieht. Das Chemikalienrecht bietet jedenfalls (ebenso wie beispielsweise das Naturschutzrecht) etliche Ansatzpunkte für sachlich ertragreiches kooperatives Zusammenwirken von Rechts- und Naturwissenschaftlern.     

Global sensitivity analysis of a process-based model for ammonia emissions from manure storage and treatment structures

The development of process-based models to estimate ammonia emissions from animal feeding operations (AFOSs) is sought to replace costly and time-consuming direct measurements. Critical to process-based model development is conducting sensitivity analysis to determine the input parameters and their interactions that contribute most to the variance of the model output. Global and relative sensitivity analyses were applied to a process-based model for predicting ammonia emissions from the surface of anaerobic lagoons for treating and storing manure. The objectives were to compare global sensitivity analysis (GSA) to relative (local) sensitivity analysis (RSA) on a process-based model for ammonia emissions. Based on the first-order coefficient, both GSA and RSA showed the model input parameters in order of importance in process model for ammonia emissions from lagoon surfaces were: (i) pH, (ii) lagoon liquid temperature, (iii) wind speed above the lagoon surface, and (iv) the concentration of ammoniacal nitrogen in the lagoon. The GSA revealed that interactions between model parameters accounted for over two-thirds of the model variance, a result that cannot be achieved using traditional RSA. Also, the GSA showed that parameter interactions involving liquid pH had more impact on the model output variance than the single parameters: (i) temperature, (ii) wind speed, or (iii) total ammoniacal nitrogen. This study demonstrates that GSA provides a more complete analysis of model input parameters and their interactions on the model output compared to RSA. A comprehensive tutorial regarding the application of GSA to a process model is presented.