Development and Use of a Sedimentation Risk Index for Unpaved Road‐Stream Crossings in the Choctawhatchee Watershed1

Abstract: Unpaved road‐stream crossings increase sediment yields in streams and alter channel morphology and stability. Before restoration and sedimentation reduction strategies can be implemented, a priority listing of unpaved road‐stream crossings must be created. The objectives of this study were to develop a sedimentation risk index (SRI) for unpaved road‐stream crossings and to prioritize 125 sites in the Choctawhatchee watershed (southeastern Alabama) using this model. Field surveys involved qualitative and quantitative observations of 73 metrics related to waterway conditions, crossing structures, road approaches, and roadside soil erosion. The road‐stream crossing risk analyses involved elimination of candidate metrics based on redundancy, skewness, lack of data, professional judgment, lack of nonzero values, unbalanced box plots, and limited ranges of values. A final selection of 12 metrics formed the SRI and weighed factors involving soil erodibility, road sedimentation abatement features, and stream morphology alteration. The SRI was organized into narrative categories (excellent, good, fair, poor, and very poor) based on the distribution of scores. No excellent sites (scores ≥55) were found in this study, 17 (20.7%) were good (low sedimentation risk), 37 (45.1%) were fair (moderate sedimentation risk), 26 (31.7%) were poor (high sedimentation risk), and two (2.5%) were very poor (high sedimentation risk). There was no significant difference in SRI scores among crossing structure type (round culverts, box culverts, and bridges) (H = 4.31, df = 2, p = 0.058). A future study of the Choctawhatchee watershed involving the same study sites could assess the success of restoration plans and activities based on site score improvement or decline.     

Development of a Quantitative Pasture Phosphorus Management Tool Using the SWAT Model1

Abstract: Assessment tools to evaluate phosphorus loss from agricultural lands allow conservation planners to evaluate the impact of management decisions on water quality. Available tools to predict phosphorus loss from agricultural fields are either: (1) qualitative indices with limited applicability to address offsite water quality standards, or (2) models which are prohibitively complex for application by most conservation planners. The purpose of this research was to develop a simple interface for a comprehensive hydrologic/water quality model to allow its usage by farmers and conservation planners. The Pasture Phosphorus Management (PPM) Calculator was developed to predict average annual phosphorus (P) losses from pastures under a variety of field conditions and management options. PPM Calculator is a vastly simplified interface for the Soil and Water Assessment Tool (SWAT) model that requires no knowledge of SWAT by the user. PPM Calculator was validated using 33 months of data on four pasture fields in northwestern Arkansas. This tool has been extensively applied in the Lake Eucha/Spavinaw Basin in northeastern Oklahoma and northwestern Arkansas. PPM Calculator allows conservation planners to take advantage of the predictive capacity of a comprehensive hydrologic water quality model typically reserved for use by hydrologists and engineers. This research demonstrates the applicability of existing water quality models in the development of user friendly P management tools.     

Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation1

Young, Charles A., Marisa I. Escobar‐Arias, Martha Fernandes, Brian Joyce, Michael Kiparsky, Jeffrey F. Mount, Vishal K. Mehta, David Purkey, Joshua H. Viers, and David Yates, 2009. Modeling the Hydrology of Climate Change in California’s Sierra Nevada for Subwatershed Scale Adaptation. Journal of the American Water Resources Association (JAWRA) 45(6):1409‐1423. Abstract: The rainfall‐runoff model presented in this study represents the hydrology of 15 major watersheds of the Sierra Nevada in California as the backbone of a planning tool for water resources analysis including climate change studies. Our model implementation documents potential changes in hydrologic metrics such as snowpack and the initiation of snowmelt at a finer resolution than previous studies, in accordance with the needs of watershed‐level planning decisions. Calibration was performed with a sequence of steps focusing sequentially on parameters of land cover, snow accumulation and melt, and water capacity and hydraulic conductivity of soil horizons. An assessment of the calibrated streamflows using goodness of fit statistics indicate that the model robustly represents major features of weekly average flows of the historical 1980‐2001 time series. Runs of the model for climate warming scenarios with fixed increases of 2°C, 4°C, and 6°C for the spatial domain were used to analyze changes in snow accumulation and runoff timing. The results indicated a reduction in snowmelt volume that was largest in the 1,750‐2,750 m elevation range. In addition, the runoff center of mass shifted to earlier dates and this shift was non‐uniformly distributed throughout the Sierra Nevada. Because the hydrologic model presented here is nested within a water resources planning system, future research can focus on the management and adaptation of the water resources system in the context of climate change.     

Evaluation of a Watershed Model for Estimating Daily Flow Using Limited Flow Measurements1

Abstract: The Soil and Water Assessment Tool (SWAT) model was evaluated for estimation of continuous daily flow based on limited flow measurements in the Upper Oyster Creek (UOC) watershed. SWAT was calibrated against limited measured flow data and then validated. The Nash‐Sutcliffe model Efficiency (NSE) and mean relative error values of daily flow estimations were 0.66 and 15% for calibration, and 0.56 and 4% for validation, respectively. Also, further evaluation of the model’s estimation of flow at multiple locations was conducted with parametric paired t‐test and nonparametric sign test at a 95% confidence level. Among the five main stem stations, four stations were statistically shown to have good agreement between predicted and measured flows. SWAT underestimated the flow of the fifth main stem station possibly because of the existence of complex flood control measures near to the station. SWAT estimated the daily flow at one tributary station well, but with relatively large errors for the other two tributaries. The spatial pattern of predicted flows matched the measured ones well. Overall, it was concluded from the graphical comparisons and statistical analyses of the model results that SWAT was capable of reproducing continuous daily flows based on limited flow data as is the case in the UOC watershed.     

Constraints to Watershed Planning: Group Structure and Process1

Floress, Kristin, Jean C. Mangun, Mae A. Davenport, and Karl W.J. Williard, 2009. Constraints to Watershed Planning: Group Structure and Process. Journal of the American Water Resources Association (JAWRA) 45(6):1352‐1360. Abstract: The roles that agencies and other partners play in collaborative watershed management are not always clearly identified. Key factors contributing to group‐level outcomes in watershed groups include both structural and procedural elements. Structural elements include membership systems, project partners, and funding, while procedural elements include leadership, shared vision, and mission development. The current research reports on a case study conducted with a Midwestern watershed group that received Clean Water Act Section 319 funds to undertake a watershed planning process. Data come from focus groups, interviews, public comments, and meeting observation, and were analyzed using grounded theory. Findings of this study indicate that homogenous skill set, discord over group and partner roles, and failed problem identification contributed to the organizational inertia experienced by the watershed group. Implications of this research for groups receiving 319 funds are provided.     

三峡库区腹地草堂溪小流域土地功能格局变化

探讨三峡库区腹地土地功能格局动态特征是促进库区土地功能优化、土地利用可持续发展的重要途径之一。以草堂溪小流域为研究区,基于1990~2015年4期遥感影像和1∶5万DEM数据,借助ArcGIS 10.2与Fragstats 4.2软件,依据土地提供主要服务的差异性将土地功能划分为3个大类5个亚类,并分析研究区土地功能格局时空演变特征。结果表明:近25 a,研究区生态功能用地占绝对优势,面积增长1 541.96 hm~2,生产功能用地面积缩减1 844.19 hm~2,生活功能用地面积扩展302.24 hm~2;生物质生产功能用地和人工/天然生态功能用地间的转移关系是研究区土地功能转移网络的关键关系,决定着研究区土地功能变化特征;土地功能变化空间集聚特征时空差异性显著,生物质生产功能用地和人工/天然生态功能用地附近为土地功能变化热点区域,1990~2015年土地功能变化热点区向研究区西部推移;生物质生产功能用地、交通功能用地和住宅功能用地优势区间为中低地形位,中高地形位是非生物生产功能用地优势区间,人工/天然生态功能用地在高地形位占优势;较低地形位上景观异质性高、形状复杂,较高地形位上景观类型单一、聚集程度高。     

基于小流域尺度的目标抗生素排放量估算方法——以梅江流域为例

抗生素的大量使用和排放造成的环境污染和生态风险问题日益突出,抗生素排放量的估算是评价流域内抗生素污染程度的重要指标,但目前抗生素排放量估算方法尚不完善。本研究以梅江流域为例,建立了适合小流域尺度的典型抗生素排放量估算方法,计算了四环素类抗生素(TCs)向不同环境相的排放量并分析了其主要来源。结果表明:2016年梅江流域TCs排放量为8 558.1 kg,不同行政区抗生素排放量差异较大,其中梅江镇受人口密度及养殖密度影响,抗生素排放量最大,高达1 224.4 kg;同时流域内不同抗生素的排放量也有所不同,其大小顺序为强力霉素(DXC)土霉素(OTC)四环素(TC)金霉素(CTC);TCs受排放源、排放途径等因素影响,以进入环境水相及土壤相为主,其中进入水相中的抗生素主要来自人类及生猪粪便,进入土壤相中的抗生素主要来自生猪及三黄鸡粪便。梅江小流域抗生素具有潜在的生态风险,应加强抗生素使用管理。该研究为我国小尺度流域目标抗生素排放量的估算提供了十分有效的方法。     

Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model1

Moore, R.D. (Dan), J.W. Trubilowicz, and J.M. Buttle, 2011. Prediction of Streamflow Regime and Annual Runoff for Ungauged Basins Using a Distributed Monthly Water Balance Model. Journal of the American Water Resources Association (JAWRA) 48(1): 32‐42. DOI: 10.1111/j.1752‐1688.2011.00595.x Abstract: Prediction of streamflow in ungauged basins is a global challenge, but is particularly an issue in physiographically complex regions like British Columbia (BC), Canada. The objective of this study was to assess the accuracy of a simple water balance model that can be run using existing spatial datasets. The model was developed by modifying an existing monthly water balance model to account for interception loss from forest canopy, glacier melt, and evaporation from lakes. The model was run using monthly climate normals from the ClimateBC application, which have a horizontal resolution of 400 m. Each ClimateBC grid cell was classified as forest, open land, glacier or water surface based on provincial scale digital maps of biogeoclimatic zones, glaciers, and water. The output was monthly mean runoff from each grid cell. These values were integrated within the catchment boundaries for streams gauged by the Water Survey of Canada. Annual runoff was predicted with modest accuracy: after updating the predicted runoff by interpolating errors from neighboring gauged streams, the mean absolute error was 25.4% of the gauged value, and 52% of the streams had errors less than 20%. However, the model appears to be quite robust in distinguishing between pluvial, hybrid, and melt‐dominated hydroclimatic regimes, and therefore has promise as a tool for catchment classification.     

An Ex Post Evaluation of Ohio’s Great Miami Water Quality Trading Program1

Newburn, David A. and Richard T. Woodward, 2011. An Ex Post Evaluation of Ohio’s Great Miami Water Quality Trading Program. Journal of the American Water Resources Association (JAWRA) 48(1): 156‐169. DOI: 10.1111/j.1752‐1688.2011.00601.x Abstract: Market‐based approaches to address water quality problems have resulted in only limited success, especially in trading programs involving both point and nonpoint sources. We analyze one of the largest point‐nonpoint trading programs – the Great Miami Trading Program in Ohio, administered by the Miami Conservancy District (MCD). Our evaluation focuses on the economic and institutional aspects of the program, including cost effectiveness, efficiency of bidding, transaction costs, trading ratios, and innovation. We use a unique dataset consisting of all bids from agricultural nonpoint sources and interviews of soil and water conservation district (SWCD) agents in the watershed. We find that the MCD’s reliance on county‐level SWCD offices to recruit and advise farmers has been essential to achieve relatively high rates of farmer participation. Additionally, the MCD is able to partly free ride on the administrative costs that SWCD offices receive to assist federal conservation programs, which is helpful to lower costs for a fledgling trading program. However, the involvement of SWCD offices reduced the potential cost savings from the reverse auction structure because some agents were able to learn about the threshold price over the six rounds of bidding and help farmers bid strategically. Overall, the program structure serves as an effective model for future trading programs in other regions that seek to involve agricultural nonpoint sources.     

Comparison of Stream Invertebrate Response Models for Bioassessment Metrics1

Waite, Ian R., Jonathan G. Kennen, Jason T. May, Larry R. Brown, Thomas F. Cuffney, Kimberly A. Jones, and James L. Orlando, 2012. Comparison of Stream Invertebrate Response Models for Bioassessment Metrics. Journal of the American Water Resources Association (JAWRA) 48(3): 570-583. DOI: 10.1111/j.1752-1688.2011.00632.x Abstract: We aggregated invertebrate data from various sources to assemble data for modeling in two ecoregions in Oregon and one in California. Our goal was to compare the performance of models developed using multiple linear regression (MLR) techniques with models developed using three relatively new techniques: classification and regression trees (CART), random forest (RF), and boosted regression trees (BRT). We used tolerance of taxa based on richness (RICHTOL) and ratio of observed to expected taxa (O/E) as response variables and land use/land cover as explanatory variables. Responses were generally linear; therefore, there was little improvement to the MLR models when compared to models using CART and RF. In general, the four modeling techniques (MLR, CART, RF, and BRT) consistently selected the same primary explanatory variables for each region. However, results from the BRT models showed significant improvement over the MLR models for each region; increases in R² from 0.09 to 0.20. The O/E metric that was derived from models specifically calibrated for Oregon consistently had lower R² values than RICHTOL for the two regions tested. Modeled O/E R² values were between 0.06 and 0.10 lower for each of the four modeling methods applied in the Willamette Valley and were between 0.19 and 0.36 points lower for the Blue Mountains. As a result, BRT models may indeed represent a good alternative to MLR for modeling species distribution relative to environmental variables.