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.     

Beyond the “General Public”: Implications of Audience Characteristics for Promoting Species Conservation in the Western Ghats Hotspot,India

Understanding how different audience groups perceive wildlife is crucial for the promotion of biodiversity conservation, especially given the key role of flagship species in conservation campaigns. Although the heterogeneity in preferences reinforces the need for campaigns tailored to specific target audiences, many conservation education and awareness campaigns still claim to target the “general public”. Audiences can be segmented according to social, economic, and cultural criteria across which species perceptions are known to vary. Different studies have investigated the preferences of different groups towards certain wildlife species, but these are largely confined to a single conservation stakeholder group, such as tourists, local communities, or potential donors in western countries. In this study, we seek to determine from a multi-stakeholder perspective, audience characteristics that influence perceptions towards wildlife at Valparai, a fragmented plateau in the Western Ghats region of the Western Ghats-Sri Lanka Hotspot. We found that stakeholder group membership was the most important characteristic followed by gender. While some characteristics had a wide-scale effect others were restricted to a few species. Our results emphasize the need to design conservation campaigns with specific audiences in mind, instead of the very often referred to “general public”.     

Approximating SWAT Model Using Artificial Neural Network and Support Vector Machine1

Abstract: With the popularity of complex, physically based hydrologic models, the time consumed for running these models is increasing substantially. Using surrogate models to approximate the computationally intensive models is a promising method to save huge amounts of time for parameter estimation. In this study, two learning machines [Artificial Neural Network (ANN) and support vector machine (SVM)] were evaluated and compared for approximating the Soil and Water Assessment Tool (SWAT) model. These two learning machines were tested in two watersheds (Little River Experimental Watershed in Georgia and Mahatango Creek Experimental Watershed in Pennsylvania). The results show that SVM in general exhibited better generalization ability than ANN. In order to effectively and efficiently apply SVM to approximate SWAT, the effect of cross‐validation schemes, parameter dimensions, and training sample sizes on the performance of SVM was evaluated and discussed. It is suggested that 3‐fold cross‐validation is adequate for training the SVM model, and reducing the parameter dimension through determining the parameter values from field data and the sensitivity analysis is an effective means of improving the performance of SVM. As far as the training sample size, it is difficult to determine the appropriate number of samples for training SVM based on the test results obtained in this study. Simple examples were used to illustrate the potential applicability of combining the SVM model with uncertainty analysis algorithm to save efforts for parameter uncertainty of SWAT. In the future, evaluating the applicability of SVM for approximating SWAT in other watersheds and combining SVM with different parameter uncertainty analysis algorithms and evolutionary optimization algorithms deserve further research.     

GIS‐Based Spatial Precipitation Estimation: A Comparison of Geostatistical Approaches1

Abstract: As one of the primary inputs that drive watershed dynamics, the estimation of spatial variability of precipitation has been shown to be crucial for accurate distributed hydrologic modeling. In this study, a Geographic Information System program, which incorporates Nearest Neighborhood (NN), Inverse Distance Weighted (IDW), Simple Kriging (SK), Ordinary Kriging (OK), Simple Kriging with Local Means (SKlm), and Kriging with External Drift (KED), was developed to facilitate automatic spatial precipitation estimation. Elevation and spatial coordinate information were used as auxiliary variables in SKlm and KED methods. The above spatial interpolation methods were applied in the Luohe watershed with an area of 5,239 km², which is located downstream of the Yellow River basin, for estimating 10 years’ (1991‐2000) daily spatial precipitation using 41 rain gauges. The results obtained in this study show that the spatial precipitation maps estimated by different interpolation methods have similar areal mean precipitation depth, but significantly different values of maximum precipitation, minimum precipitation, and coefficient of variation. The accuracy of the spatial precipitation estimated by different interpolation methods was evaluated using a correlation coefficient, Nash‐Sutcliffe efficiency, and relative mean absolute error. Compared with NN and IDW methods that are widely used in distributed hydrologic modeling systems, the geostatistical methods incorporated in this GIS program can provide more accurate spatial precipitation estimation. Overall, the SKlm_EL_X and KED_EL_X, which incorporate both elevation and spatial coordinate as auxiliary into SKlm and KED, respectively, obtained higher correlation coefficient and Nash‐Sutcliffe efficiency, and lower relative mean absolute error than other methods tested. The GIS program developed in this study can serve as an effective and efficient tool to implement advanced geostatistics methods that incorporate auxiliary information to improve spatial precipitation estimation for hydrologic models.     

Assessment of Groundwater Quality in a Structurally Deformed Granitic Terrain in Hyderabad, India

Geochemical study of groundwater from a structurally deformed granitic terrain near Hyderabad (India) was carried out to understand and evaluate the hydrogeochemical processes and quality of groundwater. Several trace elements (Fe, Mn, Be, Al, V, Cr, Co, Ni, Cu, Zn, As, Sr, Mo, Cd, Sb, Ba, Pb, U) along with major ions and minor elements were precisely estimated in shallow and drilled wells to know the suitability of water for drinking and irrigation purposes. Analytical data shows that pH and major ion chemistry in dug wells and bore wells do not vary significantly, while some trace elements (Fe, Mn, Al, Be, Co, Pb, U and Zn) vary in dug wells and bore wells, which can be attributed to differential mineral weathering and dissolution/precipitation reactions along fractures/joints. Although the water is not potable, it was found to be suitable for irrigation with little danger in the development of harmful level of exchangeable sodium. It is inferred that the chemical composition of the groundwater in this region is likely to have its origin from silicate weathering reactions and dissolution/precipitation processes supported by rainfall and groundwater flow.     

GROUPWISE MODELING STUDY OF BACTERIALLY IMPAIRED WATERSHEDS IN TEXAS: CLUSTERING ANALYSIS1

ABSTRACT: Under the Clean Water Act (CWA) program, the Texas Commission on Environmental Quality (TCEQ) listed 110 stream segments in the year 2000 with pathogenic bacteria impairment. A study was conducted to evaluate the probable sources of pollution and characterize the watersheds associated with these impaired water bodies. The primary aim of the study was to group the water bodies into clusters having similar watershed characteristics and to examine the possibility of studying them as a group by choosing models for total maximum daily load (TMDL) development based on their characteristics. This approach will help to identify possible sources and determine appropriate models and hence reduce the number of required TMDL studies. This in turn will help in reducing the effort required to restore the health of the impaired water bodies in Texas. The main characteristics considered for the classification of water bodies were land use distribution within the watershed, density of stream network, average distance of land of a particular use to the closest stream, household population, density of on‐site sewage facilities (OSSFs), bacterial loading from different types of farm animals and wildlife, and average climatic conditions. The climatic data and observed instream fecal coliform bacteria concentrations were analyzed to evaluate seasonal variability of instream water quality. The grouping of water bodies was carried out using the multivariate statistical techniques of factor analysis/principal component analysis, cluster analysis, and discriminant analysis. The multivariate statistical analysis resulted in six clusters of water bodies. The main factors that differentiated the clusters were found to be bacterial contribution from farm animals and wildlife, density of OSSFs, density of households connected to public sewers, and land use distribution.     

Laser tempering based turning process for efficient machining of hardened AISI 52100 steel

Cost-effective machining of hardened steel components such as a large wind turbine bearing has traditionally posed a significant challenge. This paper presents an approach to machine hardened steel parts efficiently at higher material removal rates and lower tooling cost. The approach involves a two-step process consisting of laser tempering of the hardened workpiece surface followed by conventional machining at higher material removal rates with lower cost ceramic tools to efficiently remove the tempered material. The laser scanning parameters that yield the highest depth of tempered layer are obtained from a kinetic phase change model. Machining experiments are performed to demonstrate the possibility of higher material removal rates and improved tool wear behavior compared to the conventional hard turning process. Tool wear performance, cutting forces, and surface finish of Cubic Boron Nitride (CBN) tools as well as low cost ceramic tools are compared in machining of hardened AISI 52100 steel (~63 HRC). In addition, cutting forces and surface finish are compared for the laser tempering based turning and conventional hard turning processes. Experimental results show the potential benefits of the laser tempering based turning process over the conventional hard turning process.     

Diclofenac residues in carcasses of domestic ungulates available to vultures in India

Gyps vulture populations across the Indian subcontinent are declining rapidly and evidence indicates that veterinary use of the non-steroidal anti-inflammatory drug (NSAID) diclofenac is the major cause. Exposure of vultures to diclofenac is likely to arise from the consumption of livestock carcasses that have been treated shortly before death, however, detailed information regarding the prevalence and residual levels of diclofenac in carcasses available to vultures in India remains unreported. Here, we present data on diclofenac residues in 1848 liver samples taken from carcasses of dead livestock sampled at 67 sites in 12 states within India, between May 2004 and July 2005. Diclofenac residues were detected in carcasses in all states except Orisa, where only one site was sampled. The overall prevalence of detectable diclofenac (>10 microg kg(-1)) across all states was 10.1% and varied significantly among states, with up to 22.3% prevalence determined in Bihar. The geometric mean concentration of diclofenac found in samples in which the drug was detected was 352 microg kg(-1). The prevalence of carcasses containing diclofenac is similar to that previously proposed to be required to have caused the observed Gyps vulture declines in India. On the 11th of May 2006, the Drug Controller General (India) ordered the withdrawal of all licenses granted for the manufacture of diclofenac for veterinary use within India. However, if Gyps vultures are to be protected, potentially substantial existing stocks now need to be quickly and effectively removed from the Indian veterinary market.