Evaluation Of Best Management Practices Research Articles

An Open Source GIS‐Based Decision Support System for Watershed Evaluation of Best Management Practices

AbstractEconomic costs, water quantity/quality benefits, and cost effectiveness of agricultural best management practices (BMPs) at a watershed scale are increasingly examined using integrated economic‐hydrologic models. However, these models are typically complex and not user‐friendly for examining the effects of various BMP scenarios. In this study, an open source geographic information system (GIS)‐based decision support system (DSS), named the watershed evaluation of BMPs (WEBs), was developed for creating BMP scenarios and simulating economic costs and water quantity/quality benefits at farm field, subbasin, and watershed scales. This DSS or WEBs interface integrated a farm economic model, the Soil and Water Assessment Tool (SWAT), and an optimization model within Whitebox Geospatial Analysis Tools (GAT), an open source GIS software. The DSS was applied to the 14.3‐km2 Gully Creek watershed, a coastal watershed in southern Ontario, Canada that drains directly into Lake Huron. BMPs that were evaluated included conservation tillage, nutrient management, cover crop, and water and sediment control basins. In addition to assessing economic costs, water quantity/quality benefits, and cost effectiveness of BMPs, the DSS can be also used to examine prioritized BMP types/locations and corresponding economic and water quantity/quality tradeoffs in the study watershed based on environmental targets or budget constraints. Further developments of the DSS including interface transfer to other watersheds are also discussed. 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.

Field data-based implementation of land management and terraces on the catchment scale for an eco-hydrological modelling approach in the Three Gorges Region, China

In this study, an innovative method to generate spatially-distributed data sets on land management and terraces based on sparse field data for a steep-sloping catchment in the Three Gorges Region in China is introduced and tested using the eco-hydrological model SWAT. The generation of such data sets is necessary for the development and evaluation of Best Management Practices (BMP) towards a reduction of high inputs of sediment and nutrients in water bodies. It is hypothesized that the inclusion of land management as well as terraces in the eco-hydrological modelling approach are individually as well as combined able to increase the model efficiency regarding streamflow and sediment. The results of the study show that the field data sets on land management and terraces can be used to generate useful SWAT input data sets to represent management and conservation practices and the model results are plausible. The effect of land management and terraces on streamflow is identified to be rather small. At the same time a strong effect of the inclusion of the terrace dataset on sediment yields can be observed, which can be seen as an improvement of the process representation within the model. By introducing the new method the study contributes to an improved representation of land management and terraces in data-scarce study regions in eco-hydrological models. At the same time the study confirms the importance of the consideration of BMPs in eco-hydrological modelling, especially towards the representation of the dynamics of sediment and sediment-bound substances.

Evaluation of best management practices under intensive irrigation using SWAT model

Land management practices such as conservation tillage and optimum irrigation are routinely used to reduce non-point source pollution and improve water quality. The calibrated and validated SWAT-IRRIG model is the first modified SWAT version that reproduces well the irrigation return flows (IRF) when the irrigation source is outside of the watershed. The application of this SWAT version in intensive irrigated systems permits to better evaluate the best management practices (BMPs) in such systems. This paper evaluates several BMPs on IRF, total suspended sediment (TSS), organic P (ORG_P), soluble P (SOL_P), and total P (TP) at the outlet Del Reguero stream watershed (Spain). Economic impacts of the BMPs on crop gross margin were also evaluated. In total, 20 BMPs scenarios were tested. The BMPs proposed considered tillage (conservation and no-tillage), fertilizer application (incorporated, recommended, and reduced), and irrigation (adjusted to crop needs). The measured data series corresponding to 2008 and 2009 years were considered to estimate IRF, TSS, ORG_P, SOL_P and TP losses as a reference to assess the effects of the considered BMPs. The results indicate that the best individual BMP (adjusted irrigation water use) reduced IRF by 31.4%, TSS loads by 33.5% and TP loads by 12.8%. When individual BMPs were combined, the load reductions were even increased. The BMP scenario combining optimum irrigation application, conservation tillage and reduced P fertilizer dose was the best, leading to a TP load reduction of about 22.6%. For corn and alfalfa, the best BMP scenario was the combination between conservation tillage and reduced P fertilizer dose, increasing the crop gross margin by 309€ha−1 and 188€ha−1, respectively. For sunflower and barley, the best scenario combined the adjusted irrigation water use, conservation tillage and reduced P fertilizer dose (gross margin increase of 171€ha−1 and 307€ha−1, respectively).

Evaluation of Best Management Practices in Millsboro Pond Watershed Using Soil and Water Assessment Tool (SWAT) Model

The Inland Bays in southern Delaware (USA) are facing eutrophication due to the nutrient loading from its watershed. The source of nutrients in the watershed is predominantly agriculture. The Millsboro Pond, a sub-watershed within the Inland Bays basin, was modeled using the Soil and Water Assessment Tool (SWAT) model. It was found that the contribution of ground water from outside the watershed had a signifi-cant impact on the hydrology of the region. Once the model was calibrated and validated, five management scenarios were implemented, one at a time, to measure its effectiveness in reducing the nutrient loading in the watershed. Among the Best Management Practices (BMPs), planting winter cover crops on the agricul-ture land was the most effective method in reducing the nutrient loads. The second most effective method was to provide grassland riparian zones. The BMPs alone were not able to achieve the nutrient load reduc-tion as required by the Total Maximum Daily Loads (TMDLs). Two extra scenarios that involved in replac-ing agriculture land with forest, first with deciduous trees and then with high yielding trees were considered. It is suggested that to achieve the required TMDL for the watershed, some parts of the agricultural land may have to be effectively converted into the managed forest with some high yielding trees such as hybrid poplar trees providing cellulose raw material for bio fuels. The remaining agriculture land should take up the prac-tice of planting winter cover crops and better nutrient management. Riparian zones, either in form of forest or grasslands, should be the final line of defense for reducing nutrient loading in the watershed.

Application of the WEPP model for prioritization and evaluation of best management practices in an Indian watershed

AbstractThe pre‐calibrated and validated physically based watershed model, water erosion prediction project (WEPP) was used as a modelling tool for the identification of critical watersheds and evaluation of best management practices for a small hilly watershed (Karso) of India. The land use/cover of the study area was generated using IRS‐1C LISS‐III (linear imaging self scanner) satellite data. The watershed and sub‐watershed boundaries, drainage, slope and soil map of the study area were generated using ARC/INFO geographic information system (GIS). The WEPP model was finally applied to the Karso watershed which lies within Damodar Barakar catchment of India to identify the critical sub‐watersheds on the basis of their simulated average annual sediment yields. Priorities were fixed on the basis of ranks assigned to each critical sub‐watershed based on the susceptibility to erosion. The sub‐watershed having the highest sediment yield was assigned a priority number 1, the next highest value was assigned a priority number 2, and so on. Subsequently, the model was used for evaluating the effectiveness of best management practices (crop and tillage) for conservation of soil for all the sub‐watersheds. On the basis of this study, it is realized that cash crops like soyabean should be encouraged in the upland portion of the sub‐watersheds, and the existing tillage practice (country plough/mould board plough) may be replaced by a field cultivation system for conservation of soil and water in the sub‐watersheds. Copyright © 2009 John Wiley & Sons, Ltd.

Evaluating the Success of Phosphorus Management from Field to Watershed

Studies have demonstrated some P loss reduction following implementation of remedial strategies at field scales. However, there has been little coordinated evaluation of best management practices (BMPs) on a watershed scale to show where, when, and which work most effectively. Thus, it is still difficult to answer with a degree of certainty, critical questions such as, how long before we see a response and where would we expect to observe the greatest or least response? In cases where field and watershed scales are monitored, it is not uncommon for trends in P loss to be disconnected. We review case studies demonstrating that potential causes of the disconnect varies, from competing sources of P at watershed scales that are not reflected in field monitoring to an abundance of sinks at watershed scales that buffer field sources. To be successful, P-based mitigation strategies need to occur iteratively, involve stakeholder driven programs, and address the inherent complexity of all P sources within watersheds.

AVGWLF‐Based Estimation of Nonpoint Source Nitrogen Loads Generated Within Long Island Sound Subwatersheds1

Abstract: The Generalized Watershed Loading Functions (GWLF) model and its ArcView interface (AVGWLF) were used to estimate and examine the components of the total nitrogen (TN) nonpoint source (NPS) load generated within New York and Connecticut (CT) watersheds surrounding Long Island Sound (LIS, the Sound). The majority of data used as model inputs were generally available from online sources, and the work involved an overall calibration to streamflow and TN data in accordance with generic guidelines recommended in the GWLF manual. The GWLF model performance for three calibration and two validation watersheds in CT was compared with results of a detailed model, Hydrological Simulation Program in Fortran, developed in a previous study. The results of the application illustrate the usefulness of the relatively simpler, less parameter‐intensive GWLF model in performing exploratory loading analysis in preparation for adaptive nutrient management in the LIS watersheds. The presented methodology is valuable for identification of priority watersheds for NPS pollution reduction and also for planning‐level evaluation of best management practices to achieve the desired reductions. It is estimated that ground‐water base flow may be the largest pathway for NPS TN to the Sound, contributing about 54% of the total NPS TN load, a finding with significant implications for LIS total maximum daily load reduction scenarios. In addition to ground water, septic systems are estimated to contribute about 17% of the total load, with the remaining TN load being mostly runoff from urban (17%), agricultural (5%), and low impact (e.g., forest) areas (6%).

Evaluating cell-based components of DANSAT for predicting surface and subsurface transport of pesticides

Accurate simulation of cell-based processes is important for evaluating the impacts of best management practices (BMPs) on surface and ground water. The objective of this study was to evaluate the cell-based component of the Dynamic Agricultural Non-point Source Assessment Tool (DANSAT) for simulating water, sediment, and pesticide movement both in surface and through the soil profile. DANSAT was applied to a maize field in Virginia cultivated by conventional tillage. The model performed well in predicting seasonal and total surface runoff, sediment load, and pesticides loads. Movements of percolated water and pesticides in the soil profile were also well reproduced by the model with 0.57 and 0.82 average index of agreements, respectively. However, the model had difficulty in predicting the temporal changes in sediment load using the dynamic erodibility approach for estimating daily variable rill and interrill erodibility parameters. The overall result showed that the cell-based component of DANSAT could be used for further evaluation of BMP impacts on surface and ground water at the watershed-scale.

Evaluation of Best Management Practices for N fertilisation in regional field vegetable production with a small-scale simulation model

Assessing the environmental impact of field vegetable production on a regional basis is a challenging task, since vegetable farms are often scattered. In order to use a soil–plant–environment–economics model as an assessment tool, a method is suggested that allows Best Management Practices (BMPs) for N-efficient field vegetable production to be tested and evaluated on different spatial entities. The model farm concept was exemplarily demonstrated on field vegetable production in the region of Baden-Wurttemberg, Germany. Two scenarios using different fertiliser strategies illustrate how the implementation of BMP can be evaluated at regional, sub-regional and farm level. Simulated results show how the area-wide enforcement of the N min method in Baden-Wurttemberg, as the first step to implement BMP, would lower the N leaching potential of field vegetable production by 66%. At sub-regional level, the results reveal that current targets stipulated by German legislation may still not be achieved in smaller areas with intensive field vegetable production.

Evaluation of Best Management Practices for Urban Stormwater Management

Evaluation of Best Management Practices for Urban Stormwater Management

Performance reconnaissance of stormwater proprietary best management practices

This paper presents a study to investigate the relative pollutant removal effectiveness of three proprietary end-of-pipe Best Management Practices (BMPs), namely, Baysaver, CDS, and Stormceptor. In this study, controlled conditions were used in order to provide documentation for the performance of the BMPs. For that purpose, a prototype facility was constructed at the University of Central Florida. For each BMP, five tests were conducted with five different flow rates: 1.6, 1.28, 0.96, 0.64, and 0.32 cfs. The monitored pollutants were sediments, nutrients, metals, and litters such as organic leaves, soda cans, plastic bottles, and cigarette butts and boxes. The results showed that some of the pollutants decreased in concentration while others increased between the influent and the effluent of the units. TSS load reductions for Baysaver, CDS and Stormceptor were 62.2%, 71.2%, and 83%, respectively. The performances of the studied BMPs for the pollutants were different. All the studied BMPs had good performance in removing the large sediment particles and litter. However, CDS had lower average inflow velocities in all tests than Baysaver and Stormceptor, causing sediment accumulation in the CDS inlet pipe. This study also showed that there was an increase in the total nitrogen concentration in Stormceptor while the nitrate/nitrite concentration increased in Baysaver and CDS. Other factors that should be considered in BMP evaluation are also presented in this paper.

Education campaigns to reduce stormwater pollution in commercial areas: Do they work?

A monitoring and evaluation program was undertaken, involving six different styles of evaluation to determine whether a low-cost, eight month education campaign that operated within a small commercial district was successful at changing people's behavior and reducing stormwater litter loads. This project also tested newly developed guidelines for monitoring and evaluating all types of non-structural stormwater quality best management practices (BMPs). The project evaluated: the extent and quality of the campaign's implementation; the degree to which it changed the awareness, attitudes, self-reported behavior and actual behavior of merchants and the public; and the nature of changes in stormwater litter loads. Overall, the education campaign produced mixed results, with the net result being modestly positive. Specifically, it was: unsuccessful at significantly influencing the knowledge or attitudes of merchants or the public; modestly successful at influencing the behavior of merchants and the public; and modestly successful at reducing litter loads in stormwater. At a theoretical level, the project highlights how using different ‘styles’ of BMP evaluation can help to build a more complete picture of a BMP's performance. At a practical level, the project helped to improve the monitoring and evaluation guidelines and produced evidence-based design guidelines for future campaigns that aim to reduce littering in commercial areas.

ROLE OF WATERSHED SUBDIVISION ON MODELING THE EFFECTIVENESS OF BEST MANAGEMENT PRACTICES WITH SWAT

Distributed parameter watershed models are often used for evaluating the effectiveness of various best management practices (BMPs). Streamflow, sediment, and nutrient yield predictions of a watershed model can be affected by spatial resolution as dictated by watershed subdivision. The objectives of this paper are to show that evaluation of BMPs using a model is strongly linked to the level of watershed subdivision; to suggest a methodology for identifying an appropriate subdivision level; and to examine the efficacy of different BMPs at field and watershed scales. In this study, the Soil and Water Assessment Tool (SWAT) model was calibrated and validated for streamflow, sediment, and nutrient yields at the outlet of the Dreisbach (623 ha) and Smith Fry (730 ha) watersheds in Maumee River Basin, Indiana. Grassed waterways, grade stabilization structures, field borders, and parallel terraces are the BMPs that were installed in the study area in the 1970s. Sediment and nutrient outputs from the calibrated model were compared at various watershed subdivision levels, both with and without implementation of these BMPs. Results for the study watersheds indicated that evaluation of the impacts of these BMPs on sediment and nutrient yields was very sensitive to the level of subdivision that was implemented in SWAT. An optimal watershed subdivision level for representation of the BMPs was identified through numerical simulations. For the study watersheds, it would appear that the average subwatershed area corresponding to approximately 4 percent of total watershed area is needed to represent the influence of these BMPs when using the SWAT model.

Utility of biological monitoring for detection of timber harvest effects on streams and evaluation of Best Management Practices: a review

Best Management Practice (BMP) guidelines have been developed to reduce the negative impacts of timber harvest on streams. BMPs are widely implemented, but the effectiveness of timber harvest BMPs has not been evaluated using modern biological monitoring techniques. Most current biological monitoring is based on 1 of 2 main approaches: multimetric monitoring or predictive modeling. These approaches differ considerably, and their respective merits and failings have been debated extensively in the literature. Our review evaluated the ability of these biological monitoring approaches to detect timber harvest effects and to assess the effectiveness of BMPs. Both techniques detect impairment via changes in macroinvertebrate community structure, despite their differences in approach. Most of the negative effects of timber harvest result in changes in the macroinvertebrate community, so we have concluded that both techniques should be effective for the evaluation of timber harvest and BMPs.

Role of the Tennessee Master Logger Program in Implementation of Best Management Practices on Non-Industrial Private Forests

Abstract A field evaluation of Best Management Practices (BMPs) was used to determine the effectiveness of the Tennessee Master Logger Program (TMLP) in 1997–1998. The study was conducted on non-industrial private forestland (NIPF) and excluded harvests on land owned by forest industry or public forests. Completed logging jobs were evaluated in relation to four components of timber harvesting: (1) haul roads, (2) skid trails, (3) log decks, and (4) Streamside Management Zones (SMZs). The scores assigned during evaluation to each of the four components were added together to yield an overall score. An overall percentage score was calculated because some sites did not have all four components, for example, SMZs are not necessary on sites without streams. Of 191 randomly chosen logging sites across the state of Tennessee, 38, or 19.9%, were harvested by trained Master Loggers. A significant association (P < 0.05) was found between overall percentage score and logger training. The mean overall percentage score for Master Loggers was 75.1%, and the mean score for untrained loggers was 60.4%. Only 17 of the 627 possible scores or 2.6%, exhibited threats to water quality. Of these 17, Master Loggers were only responsible for 3. Point biserial correlations indicated that a substantial association (P < 0.05) existed between harvests completed by Master Loggers and the scores of haul roads, skid trails, log decks, and SMZ grades. This study indicates that loggers who received training from the TMLP were more likely to implement BMPs during harvesting operations on NIPF than loggers who did not participate in the Tennessee Master Logger Program. South. J. Appl. For. 27(1):36–40.

GIS to Estimate Storm-Water Pollutant Mass Loadings

In order to develop a monitoring program for the Santa Monica Bay, Calif., watershed, a land-use runoff model was developed using a geographic information system (GIS) coupled with an empirical runoff model. The GIS/model has simple data requirements as compared to more complex models that require routing information; and it is useful for predicting receiving-water loading on an annual basis or for single-storm events. Its approach can also be used to graphically present model results in simple and intuitive ways that provide better insight to managers and planners in evaluating pollution sources and control strategies. The GIS/model was used to locate monitoring stations in the most economical way. The model predictions can be used to improve the evaluation of best management practices to control pollutant discharges. Receiving-water pollutant contributions from point and nonpoint sources can be compared to develop more economical strategies for overall pollutant minimization.

Biological Monitoring: The Dilemma of Data Analysis

Biological Monitoring: The Dilemma of Data Analysis