Augmenting Watershed Model Calibration with Incorporation of Ancillary Data Sources and Qualitative Soft Data Sources

Watershed simulation models such as the Soil & Water Assessment Tool (SWAT) can be calibrated using “hard data” such as temporal streamflow observations; however, users may find upon examination of model outputs, that the calibrated models may not reflect actual watershed behavior. Thus, it is often advantageous to use “soft data” (i.e., qualitative knowledge such as expected denitrification rates that observed time series do not typically exist) to ensure that the calibrated model is representative of the real world. The primary objective of this study is to evaluate the efficacy of coupling SWAT‐Check (a post‐evaluation framework for SWAT outputs) and IPEAT‐SD (Integrated Parameter Estimation and Uncertainty Analysis Tool‐Soft & hard Data evaluation) to constrain the bounds of soft data during SWAT auto‐calibration. IPEAT‐SD integrates 59 soft data variables to ensure SWAT does not violate physical processes known to occur in watersheds. IPEAT‐SD was evaluated for two case studies where soft data such as denitrification rate, nitrate attributed from subsurface flow to total discharge ratio, and total sediment loading were used to conduct model calibration. Results indicated that SWAT model outputs may not satisfy reasonable soft data responses without providing pre‐defined bounds. IPEAT‐SD provides an efficient and rigorous framework for users to conduct future studies while considering both soft data and traditional hard information measures in watershed modeling.     

Evaluation of Existing and Modified Wetland Equations in the SWAT Model

The ability to accurately simulate flow and nutrient removal in treatment wetlands within an agricultural, watershed‐scale model is needed to develop effective plans for meeting nutrient reduction goals associated with protection of drinking water supplies and reduction of the Gulf of Mexico hypoxic zone. The objectives of this study were to incorporate new equations for wetland hydrology and nutrient removal in Soil and Water Assessment Tool (SWAT), compare model performance using original and improved equations, and evaluate the ramifications of errors in watershed and tile drain simulation on prediction of NO₃‐N dynamics in wetlands. The modified equations produced Nash‐Sutcliffe Efficiency values of 0.88 to 0.99 for daily NO₃‐N load predictions, and percent bias values generally less than 6%. However, statistical improvement over the original equations was marginal and both old and new equations provided accurate simulations. The new equations reduce the model's dependence on detailed monitoring data and hydrologic calibration. Additionally, the modified equations increase SWAT's versatility by incorporating a weir equation and an irreducible nutrient concentration and temperature coefficient. Model improvements enhance the utility of SWAT for simulating flow and nutrients in wetlands and other impoundments, although performance is limited by the accuracy of inflow and NO₃‐N predictions from the contributing watershed. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

How to Constrain Multi‐Objective Calibrations of the SWAT Model Using Water Balance Components

Accurate discharge simulation is one of the most common objectives of hydrological modeling studies. However, a good simulation of discharge is not necessarily the result of a realistic simulation of hydrological processes within the catchment. We propose an evaluation framework that considers both discharge and water balance components as evaluation criteria for calibration of the Soil and Water Assessment Tool (SWAT). In this study, we integrated average annual values of surface runoff, groundwater flow, and evapotranspiration in the model evaluation procedure to constrain the selection of good model runs for the Little River Experimental Watershed in Georgia, United States. For evaluating water balance and discharge dynamics, the Nash‐Sutcliffe efficiency (NSE) and percent bias (PBIAS) were used. In addition, the ratio of root mean square error and standard deviation of measured data (RSR) was calculated for individual segments of the flow duration curve to identify the best model runs in terms of discharge magnitude. Our results indicate that good statistics for discharge do not guarantee realistic simulations of individual water balance components. Therefore, we recommend constraining the ranges of water balance components to achieve a more realistic simulation of the entire hydrological system, even if tradeoffs between good statistics for discharge simulations and reasonable amounts of the water balance components are unavoidable. Editor's note : This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Implications of Conceptual Channel Representation on SWAT Streamflow and Sediment Modeling

Hydrologic modeling outputs are influenced by how a watershed system is represented. Channel routing is a typical example of the mathematical conceptualization of watershed landscape and processes in hydrologic modeling. We investigated the sensitivity of accuracy, equifinality, and uncertainty of Soil and Water Assessment Tool (SWAT) modeling to channel dimensions to demonstrate how a conceptual representation of a watershed system affects streamflow and sediment modeling. Results showed the amount of uncertainty and equifinality strongly responded to channel dimensions. On the other hand, the model performance did not significantly vary with the changes in the channel representation due to the degree of freedom allowed by the conceptual nature of hydrologic modeling in the parameter calibration. Such findings demonstrated good modeling performance statistics do not necessarily mean small output uncertainty, and partial improvements in the watershed representation may neither increase modeling accuracy nor reduce uncertainty. We also showed the equifinality and uncertainty of hydrologic modeling are case‐dependent rather than specific to models or regions, suggesting great caution should be used when attempting to transfer uncertainty analysis results to other modeling studies, especially for ungauged watersheds. Editor's note: This paper is part of the featured series on SWAT Applications for Emerging Hydrologic and Water Quality Challenges. See the February 2017 issue for the introduction and background to the series.     

Integrating soil carbon cycling with that of nitrogen and phosphorus in the watershed model SWAT: Theory and model testing

In this paper we describe and test a sub-model that integrates the cycling of carbon (C), nitrogen (N) and phosphorus (P) in the Soil Water Assessment Tool (SWAT) watershed model. The core of the sub-model is a multi-layer, one-pool soil organic carbon (S_C) algorithm, in which the decomposition rate of S_C and input rate to S_C (through decomposition and humification of residues) depend on the current size of S_C. The organic N and P fluxes are coupled to that of C and depend on the available mineral N and P, and the C:N and N:P ratios of the decomposing pools. Tillage explicitly affects the soil organic matter turnover rate through tool-specific coefficients. Unlike most models, the turnover of soil organic matter does not follow first order kinetics. Each soil layer has a specific maximum capacity to accumulate C or C saturation (S_x) that depends on texture and controls the turnover rate. It is shown in an analytical solution that S_x is a parameter with major influence in the model C dynamics. Testing with a 65-yr data set from the dryland wheat growing region in Oregon shows that the model adequately simulates the S_C dynamics in the topsoil (top 0.3 m) for three different treatments. Three key model parameters, the optimal decomposition and humification rates and a factor controlling the effect of soil moisture and temperature on the decomposition rate, showed low uncertainty as determined by generalized likelihood uncertainty estimation. Nonetheless, the parameter set that provided accurate simulations in the topsoil tended to overestimate S_C in the subsoil, suggesting that a mechanism that expresses at depth might not be represented in the current sub-model structure. The explicit integration of C, N, and P fluxes allows for a more cohesive simulation of nutrient cycling in the SWAT model. The sub-model has to be tested in forestland and rangeland in addition to agricultural land, and in diverse soils with extreme properties such high or low pH, an organic horizon, or volcanic soils.     

Ecology of subtropical hermit crabs in S.W. Madagascar: cluster structure and function

The Madagascar coast (both) has a higher density and diversity of hermit crabs than is known from any other locality in the western Indian Ocean. Of the 20 species occurring at Anakao (S.W. Madagascar), 11 aggregated into clusters, including all but one of the species above the subtidal zone. The mean number of hermit crabs and species in clusters varied with several spatial parameters and time. Over 80% of the community clustered in certain habitats in particular tidal zones, whilst as low as 3% clustered in others. The highest intensity of clustering with shore zone was coincident with peak numbers of hermit crabs. The initiation and duration of clusters of hermit crabs above the eulittoral was driven by circadian rhythms, whilst those in the eulittoral were governed by tidal state. Clusters above and below the eulittoral were longer in duration, and those in the subtidal were more temporally variable than those above it. Certain pairs of species showed positive correlations of occurrence and (more rarely) of abundance, and all the correlations (of occurrence) of one, Clibanarius eurysternus, were negative. Positive correlations of occurrence were related to the degree of shell-use commonality between species pairs. Eulittoral species clustered with other individuals of approximately similar size and exchanged shells upon cluster disintegration. There was evidence of a dehydration-reduction function to shell clustering in addition to shell-exchange facilitation. The highly variable species-specific strategies of clustering may be important in alleviating both intra- and interspecific competition in assemblages of similar and highly abundant species.     

The Influence of Varying Algal Biomass On Contaminant Exposure in Benthic-Planktonic Mesocosms: Copper (Ii)

A series of mesocosms was exposed to a suite of light treatments and nutrient enrichment in order to generate algal communities of varying biomass. the influence of this biomass on the speciation of copper (II) was studied. Distribution coefficients (_Kd,Lkg-1) were relatively high (log_Kd = 5 to 7), indicative of robust trace metal sequestration, and were likely controlled by the particulate organic carbon content (foc). Differences in _Kd over time and among treatments were significant, as was the relationship between _Kd and foc. Fluorescence quenching was used to determine binding capacities (_Lt, M) and their associated binding constants (_Kcond,M^-1) in order to model the solid phase copper speciation. the _Kcond ranged between 2.1 and 5.2 × 10¹²M^-1, indicating a very strong copper-ligand complex, and was higher in mesocosms that received more light. the light _Lt increased over time, dramatically after the nutrient enrichment, but did not vary systematically among light treatments. _Lt ranged from 7.2 × 10- 7 to 4.9 × 10- 5 M. the large magnitudes of _Kd, _Kcond and _Lt ensured that greater than 97% of total copper in the mesocosms was complexed by organic matter. the total copper concentration ([Cu]_T, M) needed to reach a target dissolved copper concentration of 10^-12.5 M (pCu = 12.5) was determined for each mesocosm over time. [Cu]_T was between 8.02 × 10^-5 and 3.41 × 10^-2 M, and increased over time. the [Cu]_T normalized to the target pCu (Effective Dose Ratio, EDR) increased directly with increases in algal biomass, indicating a direct link between system productivity and copper exposure. Approximately 45% of the variance in EDR was explained by variance in total biomass, while the residual variance in EDR was due likely to differences in the strengths of particle associations and magnitude of binding capacities.     

Urban tracer dispersion experiments during the second DAPPLE field campaign in London 2004

As part of the DAPPLE programme two large scale urban tracer experiments using multiple simultaneous releases of cyclic perfluoroalkanes from fixed location point sources was performed. The receptor concentrations along with relevant meteorological parameters measured are compared with a three screening dispersion models in order to best predict the decay of pollution sources with respect to distance. It is shown here that the simple dispersion models tested here can provide a reasonable upper bound estimate of the maximum concentrations measured with an empirical model derived from field observations and wind tunnel studies providing the best estimate. An indoor receptor was also used to assess indoor concentrations and their pertinence to commonly used evacuation procedures.     

Flimmerverschmelzungsfrequenz und Arbeitsbeanspruchung

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