Model Calculations of Total Maximum Daily Loads of Mercury for Drainage Lakes1

Abstract: The Watershed Analysis Risk Management Framework watershed model was enhanced to simulate the transport and fate of mercury and to calculate the fish mercury concentrations (FMC) attained by fish through the food web. The model was applied to Western Lake Superior Basin of Minnesota, which has many peat lands and lakes. Topographic, land use, and soil data were used to set up the model. Meteorology and precipitation chemistry data from nearby monitoring stations were compiled to drive the model. Simulated flow and mercury concentrations for several stream stations were comparable to available data. The model was used to perform mercury total maximum daily load calculations for two contrasting drainage lakes (Wild Rice Lake and Whiteface Reservoir). The model results for wet deposition, dry deposition, evasion, watershed yield, and soil sequestration of mercury were comparable with available actual data. The model predicted lake ice cover from November to April and weak stratification in summer, typical of shallow lakes in cold regions. The simulated sulfate decrease and methylmercury increase near the lake bottom in late summer are caused by sulfate reduction and mercury methylation that occur in the surficial sediment. Simulated FMC were within the range of observed values and the R² of correlation between the simulated and observed FMC was 0.77. Under the 1989‐2004 base condition, the average simulated FMC of four‐year‐old walleye was 0.31 μg/g for Whiteface Reservoir and 0.15 μg/g for Wild Rice Lake. The FMC criterion in Minnesota is 0.2 μg/g. Wild Rice Lake already meets this criterion without any load reduction. The model showed that a 65% reduction in atmospheric mercury deposition will not, by itself, allow Whiteface Reservoir to meet the criterion in 15 years. Additional best management practices will be needed to reduce 50% of the watershed input.     

Sensitivity of Stream flow and Water Table Depth to Potential Climatic Variability in a Coastal Forested Watershed1

Dai, Zhaohua, Carl C. Trettin, Changsheng Li, Devendra M. Amatya, Ge Sun, and Harbin Li, 2010. Sensitivity of Streamflow and Water Table Depth to Potential Climatic Variability in a Coastal Forested Watershed. Journal of the American Water Resources Association (JAWRA) 1–13. DOI: 10.1111/j.1752-1688.2010.00474.x Abstract: A physically based distributed hydrological model, MIKE SHE, was used to evaluate the effects of altered temperature and precipitation regimes on the streamflow and water table in a forested watershed on the southeastern Atlantic coastal plain. The model calibration and validation against both streamflow and water table depth showed that the MIKE SHE was applicable for predicting the streamflow and water table dynamics for this watershed with an acceptable model efficiency (E > 0.5 for daily streamflow and >0.75 for monthly streamflow). The simulation results from changing temperature and precipitation scenarios indicate that climate change influences both streamflow and water table in the forested watershed. Compared to current climate conditions, the annual average streamflow increased or decreased by 2.4% with one percentage increase or decrease in precipitation; a quadratic polynomial relationship between changes in water table depth (cm) and precipitation (%) was found. The annual average water table depth and annual average streamflow linearly decreased with an increase in temperature within the range of temperature change scenarios (0-6°C). The simulation results from the potential climate change scenarios indicate that future climate change will substantially impact the hydrological regime of upland and wetland forests on the coastal plain with corresponding implications to altered ecosystem functions that are dependent on water.     

WATERSHED AND LAKE WATER QUALITY ASSESSMENT: AN INTEGRATED MODELING APPROACH1

Watershed planning groups and action agencies seek to understand how lake water quality responds to changes in watershed management. This study developed and demonstrated the applicability of an integrated modeling approach for providing this information. An integrated model linking watershed conditions to water-quality of the receiving lake incorporated the following components: (1) an event-based AGNPS model to estimate watershed pollutant losses; (2) annualization of AGNPS results to produce annual lake pollutant loadings; (3) a base flow separation package, SAM, to estimate base flow; (4) estimates of nutrients in base flow and point sources; and (5) linkage of watershed loadings directly to EUTROMOD lake water quality algorithms. Results are presented for Melvern Lake, a 28-km² multipurpose reservoir with a 900-km² agricultural watershed in east central Kansas. Reasonable estimates of current lake quality were attained using an average phosphorus availability factor of 31 percent to calibrate model results to measured in-lake phosphorus. Comparison of a range of possible scenarios, including all cropland changed to no-till (best case) and all CRP and good-condition grasslands changed to cropland (worst case), indicated only a (4 percent change for in-lake phosphorus and a (2 percent change for chlorophyll a. These results indicated that this watershed is not sensitive to projected changes in land use and management.     

A New Open‐Access HUC‐8 Based Downscaled CMIP‐5 Climate Model Forecast Dataset for the Conterminous United States

Watershed‐scale hydrologic simulation models generally require climate data inputs including precipitation and temperature. These climate inputs can be derived from downscaled global climate simulations which have the potential to drive runoff forecasts at the scale of local watersheds. While a simulation designed to drive a local watershed model would ideally be constructed at an appropriate scale, global climate simulations are, by definition, arbitrarily determined large rectangular spatial grids. This paper addresses the technical challenge of making climate simulation model results readily available in the form of downscaled datasets that can be used for watershed scale models. Specifically, we present the development and deployment of a new Coupled Model Intercomparison Project phase 5 (CMIP5) based database which has been prepared through a scaling and weighted averaging process for use at the level of U.S. Geological Survey (USGS) Hydrologic Unit Code (HUC)‐8 watersheds. The resulting dataset includes 2,106 virtual observation sites (watershed centroids) each with 698 associated time series datasets representing average monthly temperature and precipitation between 1950 and 2099 based on 234 unique climate model simulations. The new dataset is deployed on a HydroServer and distributed using WaterOneFlow web services in the WaterML format. These methods can be adapted for downscaled General Circulation Model (GCM) results for specific drainage areas smaller than HUC‐8. Two example use cases for the dataset also are presented.     

Comparison and Evaluation of Gridded Precipitation Datasets in a Kansas Agricultural Watershed Using SWAT

Gridded precipitation datasets are becoming a convenient substitute for gauge measurements in hydrological modeling; however, these data have not been fully evaluated across a range of conditions. We compared four gridded datasets (Daily Surface Weather and Climatological Summaries [DAYMET], North American Land Data Assimilation System [NLDAS], Global Land Data Assimilation System [GLDAS], and Parameter‐elevation Regressions on Independent Slopes Model [PRISM]) as precipitation data sources and evaluated how they affected hydrologic model performance when compared with a gauged dataset, Global Historical Climatology Network‐Daily (GHCN‐D). Analyses were performed for the Delaware Watershed at Perry Lake in eastern Kansas. Precipitation indices for DAYMET and PRISM precipitation closely matched GHCN‐D, whereas NLDAS and GLDAS showed weaker correlations. We also used these precipitation data as input to the Soil and Water Assessment Tool (SWAT) model that confirmed similar trends in streamflow simulation. For stations with complete data, GHCN‐D based SWAT‐simulated streamflow variability better than gridded precipitation data. During low flow periods we found PRISM performed better, whereas both DAYMET and NLDAS performed better in high flow years. Our results demonstrate that combining gridded precipitation sources with gauge‐based measurements can improve hydrologic model performance, especially for extreme events.     

Effect of Watershed Subdivision and Filter Width on SWAT Simulation of a Coastal Plain Watershed1

Cho, Jaepil, Richard R. Lowrance, David D. Bosch, Timothy C. Strickland, Younggu Her, and George Vellidis, 2010. Effect of Watershed Subdivision and Filter Width on SWAT Simulation of a Coastal Plain Watershed. Journal of the American Water Resources Association (JAWRA) 46(3):586-602. DOI: 10.1111/j.1752-1688.2010.00436.x Abstract: The Soil and Water Assessment Tool (SWAT) does not fully simulate riparian buffers, but has a simple filter function that is responsive to filter strip width (FILTERW). The objectives of this study were to (1) evaluate SWAT hydrology and water quality response to changes in watershed subdivision levels and different FILTERW configurations and (2) provide guidance for selecting appropriate watershed subdivision for model runs that include the riparian buffer feature through the FILTERW parameter. Watershed subdivision level is controlled by the critical source area (CSA) which defines the minimum drainage area required to form the origin of a stream. SWAT was calibrated on a 15.7 km² subdrainage within the Little River Experimental Watershed, Georgia. The calibrated parameter set was applied to 32 watershed configurations consisting of four FILTERW representations for each of eight CSA levels. Streamflow predictions were stable regardless of watershed subdivision and FILTERW configuration. Predicted sediment and nutrient loads from upland areas decreased as CSA increased when spatial variations of riparian buffers are considered. Sediment and nutrient yield at the watershed outlet was responsive to different combinations of CSA and FILTERW depending on selected in-stream processes. CSA ranges which provide stable sediment and nutrient yields at the watershed outlet was suggested for avoiding significant modifications in selected parameter set.     

Effects of Forest Composition and Spatial Patterns on Storm Flows of a Small Watershed1

Abstract: The PRMS_Storm model was built as a storm event, distributed hydrological model for studying the hydrological effects of forest composition and spatial distribution on storm‐flow volume and peakflow rates in the Xiangshuixi Watershed in the Three Gorges Reservoir Area, in the Yangtze River Basin in southwestern China. We developed three simulation scenarios based on forest composition and their spatial arrangements across the watershed, including all mixed conifer‐evergreen broadleaf forests (Scenario 1), all mixed evergreen broadleaf forests (Scenario 2), and mixed conifer + evergreen broadleaf + shrub forests (Scenario 3). We examined 11 storm events observed during 2002‐2005. Compared with the existing forest covers, modeling results suggested that the amount of overland flow was reduced by 21, 23, and 22%, and the interflow increased by 16, 88, and 30%, for Scenarios 1, 2, and 3, respectively. During the same time, peakflow rates were reduced by 20.8, 9.6, and 18.9%, respectively. The reduction of peakflow rates was most significant when rainfall intensity exceeded 0.8 mm/min and events with a short duration and effect was minor when rainfall intensity was below 0.5 mm/min. In general, we found that Scenarios 1 and 3 were preferred for reducing storm‐flow volume and peakflow rates due to their higher interception rates, large soil water holding capacity, and higher soil infiltration capacity. The modeled results suggested soil properties are important in affecting the flow processes and thus forest composition and forest spatial distributions will affect storm‐flow volume and peakflow rates at the watershed scale. To maximize flood reduction functions of a watershed, high priority should be given to those forest types (Scenarios 1 and 3) in reforestation practices in the study region. This study suggests both forest composition and spatial pattern are important reforestation designs for flood reduction in the Three Gorges Reservoir Area.     

Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho1

Stratton, Benjamin T., Venakataramana Sridhar, Molly M. Gribb, James P. McNamara, and Balaji Narasimhan, 2009. Modeling the Spatially Varying Water Balance Processes in a Semiarid Mountainous Watershed of Idaho. Journal of the American Water Resources Association (JAWRA) 45(6):1390‐1408. Abstract: The distributed Soil Water Assessment Tool (SWAT) hydrologic model was applied to a research watershed, the Dry Creek Experimental Watershed, near Boise Idaho to investigate its water balance components both temporally and spatially. Calibrating and validating SWAT is necessary to enable our understanding of the water balance components in this semiarid watershed. Daily streamflow data from four streamflow gages were used for calibration and validation of the model. Monthly estimates of streamflow during the calibration phase by SWAT produced satisfactory results with a Nash Sutcliffe coefficient of model efficiency 0.79. Since it is a continuous simulation model, as opposed to an event‐based model, it demonstrated the limited ability in capturing both streamflow and soil moisture for selected rain‐on‐snow (ROS) events during the validation period between 2005 and 2007. Especially, soil moisture was generally underestimated compared with observations from two monitoring pits. However, our implementation of SWAT showed that seasonal and annual water balance partitioning of precipitation into evapotranspiration, streamflow, soil moisture, and drainage was not only possible but closely followed the trends of a typical semiarid watershed in the intermountain west. This study highlights the necessity for better techniques to precisely identify and drive the model with commonly observed climatic inversion‐related snowmelt or ROS weather events. Estimation of key parameters pertaining to soil (e.g., available water content and saturated hydraulic conductivity), snow (e.g., lapse rates, melting), and vegetation (e.g., leaf area index and maximum canopy index) using additional field observations in the watershed is critical for better prediction.     

Assessing Spatial Scale Effects on Hydrometric Network Design Using Entropy and Multi‐objective Methods

In order to facilitate water resources decisions, it is important that accurate and informative hydrometric data are collected. Combining information theory with multi‐objective optimization has led to methods of optimizing the information content provided by hydrometric networks; however, there is no available study on the effects of spatial scale and data limitation on these methods. Herein, a dual entropy multi‐objective optimization (DEMO) and a transinformation (TI) analysis were done to recommend optimal locations for additional hydrometric stations in the Madawaska Watershed. This analysis was designed to be comparative to a similar study conducted on the Ottawa River Basin which encompasses the Madawaska Watershed to allow for an investigation of the spatial scale effects in this type of network design. This study concludes that TI analysis is not adversely affected by scaling; however, the DEMO analysis is sensitive to the placement of potential station locations and the size of the study area. This study also examines the benefit of including nearby stations when the area of interest does not have a sufficient number of existing hydrometric stations for analysis. It is shown that these stations can provide useful information because their inclusion in the analysis increased the average TI in the watershed. Recommendations were made as to the ideal locations of additional stations in the Madawaska Watershed hydrometric network.     

On the Role of Spatial,Temporal, and Climatic Forces on Stream Sediment Loading from Rural and Urban Ecosystems

In this study, we characterize the greatest sediment loading events by their sediment delivery behavior; dominant climate, watershed, and antecedent conditions; and their seasonal distribution for rural and urban land uses. The study area is Paradise Creek Watershed, a mixed land use watershed in northern Idaho dominated by saturation excess processes in the upstream rural area and infiltration excess in the downstream urban area. We analyzed 12 years of continuous streamflow, precipitation, and watershed data at two monitoring stations. We identified 137 sediment loading events in the upstream rural section of the watershed and 191 events in the downstream urban section. During the majority of these events conditions were transport limited and the sediment flush occurred early in the event, generally in the first 20% of elapsed event time. Statistical analysis including two dozen explanatory variables showed peak discharge, event duration, and antecedent baseflow explained most of the variation in event sediment load at both stations and for the watershed as a whole (R² = 0.73‐0.78). In the rural area, saturated soils combined with spring snowmelt in March led to the greatest loading events. The urban area load contribution peaked in January, which could be a re‐suspension of streambed sediments from the previous water year. Throughout the study period, one event contributed, on average, 33% of the annual sediment load but only accounted for 2% of the time in a year.     

Effectiveness of Multi‐Site Weather Generator for Hydrological Modeling1

Khalili, Malika, François Brissette, and Robert Leconte, 2011. Effectiveness of Multi‐site Weather Generator for Hydrological Modeling. Journal of the American Water Resources Association (JAWRA) 1‐12. DOI: 10.1111/j.1752‐1688.2010.00514.x Abstract: A multi‐site weather generator has been developed using the concept of spatial autocorrelation. The multi‐site generation approach reproduces the spatial autocorrelations observed between a set of weather stations as well as the correlations between each pair of stations. Its performance has been assessed in two previous studies using both precipitation and temperature data. The main objective of this paper is to assess the efficiency of this multi‐site weather generator compared to a uni‐site generator with respect to hydrological modeling. A hydrological model, known as Hydrotel, was applied over the Chute du Diable watershed, located in the Canadian province of Quebec. The distributed nature of Hydrotel accounts for the spatial variations throughout the watershed, and thus allows a more in‐depth assessment of the effect of spatially dependent meteorological input on runoff generation. Simulated streamflows using both the multi‐site and uni‐site generated weather data were statistically compared to flows modeled using observed data. Overall, the hydrological modeling using the multi‐site weather generator significantly outperformed that using the uni‐site generator. This latter combined to Hydrotel resulted in a significant underestimation of extreme streamflows in all seasons.     

A WATER QUALITY‐BASED APPROACH FOR WATERSHED WIDE BMP STRATEGIES1

ABSTRACT: Watershed management strategies generally involve controlling nonpoint source pollution by implementing various best management practices (BMPs). Currently, stormwater management programs in most states use a performance‐based approach to implement onsite BMPs. This approach fails to link the onsite BMP performance directly to receiving water quality benefits, and it does not take into account the combined treatment effects of all the stormwater management practices within a watershed. To address these issues, this paper proposes a water quality‐based BMP planning approach for effective nonpoint source pollution control at a watershed scale. A coupled modeling system consisting of a watershed model (HSPF) and a receiving water quality model (CE‐QUAL‐W2) was developed to establish the linkage between BMP performance and receiving water quality targets. A Monte Carlo simulation approach was utilized to develop alternative BMP strategies at a watershed level. The developed methodology was applied to the Swift Creek Reservoir watershed in Virginia, and the results show that the proposed approach allows for the development of BMP strategies that lead to full compliance with water quality requirements.     

Rainfall Runoff Relationships for a Cloud Forest Watershed in Central America: Implications for Water Resource Engineering1

Caballero, Luis A., Alon Rimmer, Zachary M. Easton, and Tammo S. Steenhuis, 2012. Rainfall Runoff Relationships for a Cloud Forest Watershed in Central America: Implications for Water Resource Engineering. Journal of the American Water Resources Association (JAWRA) 48(5): 1022‐1031. DOI: 10.1111/j.1752‐1688.2012.00668.x Abstract: Understanding the basic relationships between rainfall and runoff is vital for effective management and utilization of scarce water resources. Especially, this is important in Central America with widespread potable water shortage during the dry months of the monsoon. Potential good water sources are cloud forests, but little information concerning its potential is available to water supply engineers. Our objective is to define rainfall‐runoff‐base flow relationships for a cloud forest catchment. Flumes were installed for measuring river flow in four subwatersheds in La Tigra National Park, Honduras. One of the four watersheds was a 636‐ha subwatershed (WS1) with 60% cloud forest coverage. Precipitation averaged 1,130 mm/yr over the entire basin. About half of the total rainfall became runoff for the cloud forest watershed whereas, for the adjacent undisturbed forested watershed, the total discharge was <20% of the amount of precipitation. Infiltration rates were generally greater than rainfall rates. Therefore, most rainfall infiltrated into the soil, especially in the upper, steep, and well‐drained portions of the watershed. Direct runoff was generated from saturated areas near the river and exposed bedrock. This research provides compelling evidence that base flow is the primary contributor to streamflow during both wet and dry seasons in cloud forest catchments. Protecting these flow processes over time is critical for the sustained provision of potable water.     

GIS-based spatial regression and prediction of water quality in river networks: A case study in Iowa

Nonpoint source pollution is the leading cause of the U.S.’s water quality problems. One important component of nonpoint source pollution control is an understanding of what and how watershed-scale conditions influence ambient water quality. This paper investigated the use of spatial regression to evaluate the impacts of watershed characteristics on stream NO₃NO₂-N concentration in the Cedar River Watershed, Iowa. An Arc Hydro geodatabase was constructed to organize various datasets on the watershed. Spatial regression models were developed to evaluate the impacts of watershed characteristics on stream NO₃NO₂-N concentration and predict NO₃NO₂-N concentration at unmonitored locations. Unlike the traditional ordinary least square (OLS) method, the spatial regression method incorporates the potential spatial correlation among the observations in its coefficient estimation. Study results show that NO₃NO₂-N observations in the Cedar River Watershed are spatially correlated, and by ignoring the spatial correlation, the OLS method tends to over-estimate the impacts of watershed characteristics on stream NO₃NO₂-N concentration. In conjunction with kriging, the spatial regression method not only makes better stream NO₃NO₂-N concentration predictions than the OLS method, but also gives estimates of the uncertainty of the predictions, which provides useful information for optimizing the design of stream monitoring network. It is a promising tool for better managing and controlling nonpoint source pollution.     

MODELING OF NONPOINT SOURCE POLLUTION OF NITROGEN AT THE WATERSHED SCALE1

ABSTRACT: The Watershed Nutrient Transport and Transformation (NTT-Watershed) model is a physically based, energy-driven, multiple land use, distributed model that is capable of simulating water and nutrient transport in a watershed. The topographic features and subsurface properties of the watershed are refined into uniform, homogeneous square grids. The vertical discretization includes vegetation, overland flow, soil water redistribution and groundwater zones. The chemical submodel simulates the nitrogen dynamics in terrestrial and aquatic systems. Three chemical state variables are considered (NO₃^-_-, NH₄⁺, and Org-N). The NTT-Watershed model was used to simulate the fate and transport of nitrogen in the Muddy Brook watershed in Connecticut. The model was shown to be capable of capturing the hydrologic and portions of the nitrogen dynamics in the watershed. Watershed planners could use this model in developing strategies of best management practices that could result in maximizing the reductions of nitrogen export from a watershed.     

Stochastic Watershed Water Quality Simulation for TMDL Development – A Case Study in the Newport Bay Watershed1

Abstract: Systematic consideration of uncertainty in data, model structure, and other factors is generally unaddressed in most Total Maximum Daily Load (TMDL) calculations. Our previous studies developed the Management Objectives Constrained Analysis of Uncertainty (MOCAU) approach as an uncertainty analysis technique specifically for watershed water quality models, based on a synthetic case. In this study, we applied MOCAU to analyze diazinon loading in the Newport Bay watershed (Southern California). The study objectives included (1) demonstrating the value of performing stochastic simulation and uncertainty analysis for TMDL development, using MOCAU as the technique and (2) evaluating the existing diazinon TMDL and generating insights for the development of scientifically sound TMDLs, considering uncertainty. The Watershed Analysis Risk Management Framework model was used as an example of a complex watershed model. The study revealed the importance and feasibility of conducting stochastic watershed water quality simulation for TMDL development. The critical role of management objectives in a systematic uncertainty assessment was well demonstrated. The results of this study are intuitive to TMDL calculation, model structure improvement and sampling strategy design.     

Water quality assessment and meta model development in Melen watershed – Turkey

Istanbul, being one of the highly populated metropolitan areas of the world, has been facing water scarcity since the past decade. Water transfer from Melen Watershed was considered as the most feasible option to supply water to Istanbul due to its high water potential and relatively less degraded water quality. This study consists of two parts. In the first part, water quality data covering 26 parameters from 5 monitoring stations were analyzed and assessed due to the requirements of the “Quality Required of Surface Water Intended for the Abstraction of Drinking Water” regulation. In the second part, a one-dimensional stream water quality model with simple water quality kinetics was developed. It formed a basic design for more advanced water quality models for the watershed. The reason for assessing the water quality data and developing a model was to provide information for decision making on preliminary actions to prevent any further deterioration of existing water quality. According to the water quality assessment at the water abstraction point, Melen River has relatively poor water quality with regard to NH₄⁺, BOD₅, faecal streptococcus, manganese and phenol parameters, and is unsuitable for drinking water abstraction in terms of COD, PO₄^3?, total coliform, total suspended solids, mercury and total chromium parameters. The results derived from the model were found to be consistent with the water quality assessment. It also showed that relatively high inorganic nitrogen and phosphorus concentrations along the streams are related to diffuse nutrient loads that should be managed together with municipal and industrial wastewaters.     

SIMULATING THREE-DIMENSIONAL GROUND WATER RESPONSE IN A SMALL MOUNTAINOUS WATERSHED1

ABSTRACT: Snowmelt from deep mountainous snowpacks is seldom rapid enough to exceed infiltration rates; thus, the source of streamflow in many mountainous watersheds is snowmelt recharge through shallow ground water systems. The hydrologic response and interaction between surface and sub-surface flow processes in these watersheds, which is controlled by basin structure, the spatial distribution of snowmelt, and the hydrogeology of the subsurface, are not well understood. The purpose of this study was to test a three-dimensional ground water model using simulated snowmelt input to simulate ground water response to spatially distributed snowmelt on the Upper Sheep Creek Watershed located within the Reynolds Creek Experimental Watershed in Southwestern Idaho. The model was used to characterize the mountainous aquifer and to delineate the subsurface flow mechanisms. Difficulty in finding a reasonable combination of grid spacing and time stepping within the model was encountered due to convergence problems with the Picard solution to the non-linear variably saturated ground water flow equations. Simulation results indicated that flow may be either unconfined or confined depending on inflow rate and hydrogeologic conditions in the watershed. The flow mechanism had a much faster response time when confined flow occurred. Response to snowmelt from a snow drift approximately 90 m away took only a few hours when flow was confined. Simulated results showed good agreement with piezometer measurements both in magnitude and timing; however, convergence problems with the Picard solution limited applicability of the model.