Analyzing the impacts of topographic factors and land cover characteristics on waterlogging events in urban functional zones.

Rapid urbanization and climate changes result in frequent occurrence of urban waterlogging disasters, which cause serious economic damage and pose a threat to residents' safety. Understanding the spatial characteristic and the key influencing factors of urban waterlogging has significant implications for mitigating waterlogging. In this study, the officially issued representative waterlogging points were obtained, as well as the topographic factors and land cover characteristics were selected to compare their impacts on the waterlogging event density in a highly urbanized area at urban functional zone (UFZ) scale, and to quantify the contributions of the key influencing factors on urban waterlogging events. Results showed the average density of urban waterlogging events in the study area is 9.2 points/km2, and 38.4 % of the waterlogging events are distributed in REZ. The distribution of waterlogging points in the study area revealed a significant multi-core and multilevel spatial aggregation pattern, and 12.1 % of the study area was high-density waterlogging area. In the total UFZs, the correlation coefficients of topographic indices with waterlogging density were relatively weaker than the other land cover characteristic metrics. The impervious surface ratio had significant contributions in all UFZ types. The larger ratio of impervious surface significantly increased the density of waterlogging events. The increase in the ratio of green space can effectively decrease the density of urban waterlogging. In the total UFZs, the top 3 key influencing factors of urban waterlogging were PR (35.9 %), COHESION (32.5 %) and DIVISION (11.8 %). The higher connectivity of landscape patches in REZ, INZ and COZ, as well as the increase of landscape dispersion or diversity in REZ, EGZ, INZ and GSZ can effectively reduce the occurrence of urban waterlogging. This study provides a better understanding of the formation mechanism of urban waterlogging disasters and potential implications for prioritized waterlogging mitigation strategies.

Cyanophage-cyanobacterial interactions for sustainable aquatic environment.

Cyanobacteria are a type of bloom-forming phytoplankton that cause environmental problems in aquatic ecosystems worldwide. Cyanobacterial harmful algal blooms (cyanoHAB) often produce cyanotoxins that affect public health by contaminating surface waters and drinking water reservoirs. Conventional drinking water treatment plants are ineffective in treating cyanotoxins, even though some treatment methods are available. Therefore, innovative and advanced treatment methods are required to control cyanoHABs and their cyanotoxins. The goal of this review paper is to provide insight into the use of cyanophages as an effective form of biological control method for the removal of cyanoHABs in aquatic systems. Moreover, the review contains information on cyanobacterial blooms, cyanophage-cyanobacteria interactions, including infection mechanisms, as well as examples of different types of cyanobacteria and cyanophages. Moreover, the real-life application of cyanophages in marine and freshwater environments and the mode of action of cyanophages were compiled.

Cyanophage technology in removal of cyanobacteria mediated harmful algal blooms: A novel and eco-friendly method.

Cyanophages are highly abundant specific viruses that infect cyanobacterial cells. In recent years, the cyanophages and cyanobacteria interactions drew attention to environmental restoration due to their discovery in marine and freshwater systems. Cyanobacterial harmful algal blooms (cyanoHABs) are increasing throughout the world and contaminating aquatic ecosystems. The blooms cause severe environmental problems including unpleasant odors and cyanotoxin production. Cyanotoxins have been reported to be lethal agents for living beings and can harm animals, people, aquatic species, recreational activities, and drinking water reservoirs. Biological remediation of cyanoHABs in aquatic systems is a sustainable and eco-friendly approach to increasing surface water quality. Therefore, this study compiles the fragmented information with the solution of removal of cyanoHABs using cyanophage therapy techniques. To date, scant information exists in terms of bloom formation, cyanophage occurrence, and mode of action to remediate cyanoHABs. Overall, this study illustrates cyanobacterial toxin production and its impacts on the environment, the mechanisms involved in the cyanophage-cyanobacteria interaction, and the application of cyanophages for the removal of toxic cyanobacterial blooms.

Cost-effectiveness analysis of extensive green roofs for urban stormwater control in response to future climate change scenarios.

Green roof, as a popular low impact development practice, has become important to mitigate adverse impacts of future climate change on urban stormwater. However, there is limited information regarding assessment of the effectiveness of green roofs in response to uncertain future climate change challenges. In this study, the validated model was used to simulate the reduction performance of green roofs on urban catchment outflow and assess their cost-effectiveness in response to design storms under climate change scenarios. Results showed that the median runoff volume of urban catchments increased by 12.5 %-14.6 % and 15.5 %-18.1 % and the median peak flow rate increased by 14.4 %-17.8 % and 17.9 %-22.1 % under SSP2-4.5 and SSP5-8.5 scenarios, respectively. This indicated the variability of runoff volume and peak flow changes for short return storm events caused by climate change was relatively high. Green roof implementation had reasonable mitigation effects on runoff volume and peak flow amplification in urban catchments caused by climate change. The median runoff volume reduction of green roofs for the 1-year storm was 15.2 % under SSP2-4.5 scenario. As rainfall intensity increased, the median runoff volume reduction of green roofs significantly declined to 5.6 % for the 100-year storm. However, the variations of runoff volume and peak flow reduction of green roofs were relatively smaller for longer return periods under climate change scenarios. Runoff reduction percentages of green roofs increased linearly with their implementation cost. The average value of the cost-effectiveness (C/E) index for green roofs was 91.2 %/million $ under base climate condition, and it decreased to 88.9 %/million $ and 88.4 %/million $ for SSP2-4.5 and SSP5-8.5 scenarios, respectively. The C/E values decreased with increasing storm return period, and the values were relatively lower in SSP5-8.5 scenarios. These results could help to understand the potential role of green roofs to mitigate the impacts of future climate change.

Multi-scale analysis of hydrological connectivity and plant response in the Yellow River Delta.

The Yellow River Delta is one of the International Important Wetlands on the west coastline of the Pacific Ocean in China. Despite its importance for regional and global ecological security, it is vulnerable because of human activities and climate change. Local government is trying to identify a more efficient way to conserve the delta thereby reducing a potential environmental crisis. The framework of hydrological connectivity provides a new perspective to study hydrological related ecological processes, while the method is highly exclusive because of environment and scale heterogeneity. This study collaborated with managers to develop a new algorithm to parameterize the hydrological connectivity on plot, point and landscape scales. Then the interspecific and conspecific structures of two dominate species (Phragmites communis and Suaeda salsa) are linked to these indices. The results show: (1) According to the point and plot scale results, AP (semi-artificial pond) and IF (intertidal flat) has the strongest hydrological connectivity followed by TM (tidal marsh). The average positive point-scale index values in AP, IF RS (river side wetland) and TM are 0.610, 0.495, 1.162 and 1.217 and the average plot-scale index values in AP, IF RS and TM are 1.53, 0.87, 0.48 0.55. At the landscape scale, index values show high collinearity with plot density and lack of hydrological significance because of low data resolution and scale effects. (2) At the individual level, P. communis and S. salsa showed a higher interspecific and conspecific competitive strength to respond to environmental stress in the weak hydrological connectivity area. (3) At the community level, in higher salinity wetland classes, biomass, plant coverage and biodiversity showed a positive linear correlation with plot-scale indices. Future study will improve the current parametrization method at the landscape scale and reveal the response of other important plant species to hydrological connectivity in this area.

A bi-level multiobjective stochastic approach for supporting environment-friendly agricultural planting strategy formulation.

In this study, integration of analytic hierarchy process method and entropy method (AHP-EW) for quantifying the knowledge and experience accumulated by regional managers as well as the socioeconomic situation, the partial least squares regression (PLS) for reflecting the relationship between irrigation water use efficiency and agronomic inputs, and the ecosystem service value for measuring environmental impacts of changing crop planting area were considered in one framework simultaneously. With help of these efforts, a bi-level multiobjective stochastic approach to improve irrigation water use efficiency and decrease the pollution production of agronomic measures in the process of agricultural production. The proposed framework integrate bi-level multiobjective programming and stochastic expectation programming to not only make tradeoffs among multiple concerns from two-level decision makers, but also deal with the randomness of runoff. Then, the proposed approach was applied to a real-world case in the middle reaches of the Heihe River basin, northwest China. Results show that the developed approach can improve irrigation water use efficiency, reduce CO2 emission, expand ecosystem service values, and provide more profitable and environment-friendly agricultural planting strategies to decision makers, which can further contribute to the sustainable development of agriculture. Furthermore, by comparing the bi-level multiobjective stochastic programming (BMSP) model with the other six models originated from developed model, it can be found that 1) the single objective model can obtain the best value of that objective, but cannot readily consider other important aspects; 2) the multiobjective models can make tradeoffs among multiple objectives; 3) the BMSP model can reflect the leader-follower relationship in the optimization process. The approach is applicable for arid and semiarid regions that face similar problems to determine agricultural planting strategies.

A SWAT-based optimization tool for obtaining cost-effective strategies for agricultural conservation practice implementation at watershed scales.

To address the harmful algal blooms problem in Lake Erie, one solution is to determine the most cost-effective strategies for implementing agricultural best management practices (BMPs) in the Maumee River watershed. An optimization tool, which combines multi-objective optimization algorithms, SWAT (Soil and Water Assessment Tool), and a computational efficient framework, was created to optimally identify agricultural BMPs at watershed scales. The optimization tool was demonstrated in the Matson Ditch watershed, an agricultural watershed in the Maumee River basin considering critical areas (25% of the watershed with the greatest pollutant loadings per area) and the entire watershed. The initial implementation of BMPs with low expenditures greatly reduced pollutant loadings; beyond certain levels of pollutant reductions, additional expenditures resulted in less significant reductions in pollutant loadings. Compared to optimization for the entire watershed, optimization in critical areas can greatly reduce computational time and obtain similar optimization results for initial reductions in pollutant loadings, which were 10% for Dissolved Reactive Phosphorus (DRP) and 38% for Total Phosphorus (TP); however, for greater reductions in pollutant loadings, critical area optimization was less cost-effective. With the target of simultaneously reducing March-July DRP/TP losses by 40%, the optimized scenario that reduced DRP losses by 40% was found to reduce 51.1% of TP; however, the optimized scenario that reduced TP losses by 40% can only decrease 11.3% of DRP. The optimization tool can help stakeholders identify optimal types, quantities, and spatial locations of BMPs that can maximize reductions in pollutant loadings with the lowest BMP costs.

Optimal adaptation pathway for sustainable low impact development planning under deep uncertainty of climate change: A greedy strategy.

Robustness and cost effectiveness are major concerns for sustainable stormwater management under deep uncertainty of climate change. Given that many traditional static planning strategies are not working with unpredictable future conditions, the possibility of system failure, and the lock-in effects, the Adaptation Pathway (AP) approach was adopted for dynamically robust and cost-effective planning in this paper. In order to increase optimization accuracy of multi-staged planning, a continuous definition of the AP optimization problem was raised by improving the simplified versions in existing studies. A case study in Suzhou, a provincial pilot Sponge City in China undergoing increasing annual rainfall and severe water environment deterioration, was included by integrating Long-Term Hydrologic Impact Assessment-Low Impact Development model with optimization methods, aiming to persistently control the non-point source total phosphorus loading below an acceptable amount in the following unforeseen 20 years via multi-staged low-impact development (LID) construction. A novel optimization method developed by the authors in a companion paper, namely marginal-cost-based greedy strategy (MCGS), was successfully applied to efficiently solve the continuous version of the AP optimization problem. The popular genetic algorithm (GA) was used as a contrast. A weather generator was elaborated based on four Representative Concentration Pathway scenarios and 17 spatial downscaled general circulation models to simulate the unforeseen future annual rainfalls that helped with evaluating cost effectiveness of each prospective LID plan. Results showed that the adaptation pathways optimized by MCGS could save the whole life net present cost of an LID plan by 1%-60% compared with those optimized by GA, and the computational efficiency of MCGS was over 13 times faster than GA.

Runoff Response to Soil Moisture and Micro-topographic Structure on the Plot Scale.

Structural hydrological connectivity has been proposed to describe the geological structure of the landscape as well as to explain hydrological behaviors. Indices based on the topological or soil condition were developed to interpret their relationships. While previous studies mainly focused on well-instrumented catchments which are narrow in humidity or temperate zone, the hydrological responses to structural connectivity at the plot and hill slope scale as well as in arid or semi-arid climate conditions remain unclear. This study was conducted in the semi-arid mountainous region of northern China in Haihe Basin which is the source of water of about 350 million people. Experiments were conducted during the rainy season in 2012 and 2013 using four runoff plots. Two indices, flow path length (FL) based on topography and integral connectivity scale length (ICSL) based on soil moisture conditions, developed to represent hydrological connectivity structure and the runoff response to rainfall were analyzed. The results showed that the surface runoff coefficient was strongly and positively linearly correlated to FL, and the correlation between subsurface flow and ICSLs was quadratic. Plots with shorter FL required more rainfall to generate surface runoff. In the shallow soil layer, when the ICSLs are relatively low, the soil can store more water and less rainfall feeds subsurface runoff. Further analysis indicated that improved shallow soil connectivity conditions might enhance the water-holding capacity and lead to lower water yields for each event. This study demonstrated that hydrological structure connectivity could explain the mechanism of runoff generation in semi-arid areas while further experiments should be undertaken to find the threshold-like relationship between FL and surface runoff as well as the influence of plant cover on hydrological behaviors.

Evaluation of the effectiveness of green infrastructure on hydrology and water quality in a combined sewer overflow community.

Evaluation of the effectiveness of green infrastructure (GI) practices on improving site hydrology and water quality and their associated cost could provide valuable information for decision makers when creating development/re-development strategies. In this study, a watershed scale rainfall-runoff model (the Long-Term Hydrologic Impact Analysis - Low Impact Development model, the L-THIA-LID 2.1 model) was enhanced to improve its simulation of urban water management practices including GI practices. The enhanced model (L-THIA-LID 2.2) is capable of: simulating in more detail impervious surfaces including sidewalks, roads, driveways, and parking lots; conducting cost calculations for converting these impervious surfaces to porous pavements; and, selecting suitable areas for bioretention in the study area. The effectiveness of GI practices on improving hydrology and water quality in a combined sewer overflow urban watershed-the Darst Sewershed in the City of Peoria, IL-was examined in eleven simulation scenarios using 8 practices. The total cost and the cost effectiveness for each scenario considering a 20-year practice lifetime were calculated. Results showed: combined implementation of GI practices performed better than applying individual practices alone; adoption levels and combinations of GI practices could potentially reduce runoff volume by 0.2-23.5%, TSS by 0.18-30.8%, TN by 0.2-27.9%, and TP by 0.2 to 28.1%; adding more practices did not necessarily achieve substantial runoff and pollutant reductions based on site characteristics; the most cost-effective scenario out of eleven considered had an associated cost of $9.21 to achieve 1 m3 runoff reduction per year and $119 to achieve 1 kg TSS reduction per year assuming residents' cooperation in implementing GI practices on their properties; adoption of GI practices on all possible areas could potentially achieve the greatest runoff and pollutant reduction, but would not be the most cost-effective option. This enhanced model can be applied to different locations to support assessing the beneficial uses of GI practices.

Green infrastructure practices simulation of the impacts of land use on surface runoff: Case study in Ecorse River watershed, Michigan.

As an urban fringe district, the Ecorse River watershed is faced with increased impervious area caused by urban expansion. Effects of Green Infrastructure (GI) practice implementation were simulated with the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 model (L-THIA-LID 2.1). Suitable locations of each GI practice were identified, based on construction condition requirements and demand on GI practices in the study area. Using the data of 2011, various GI practice combination scenarios were explored according to the cost-efficiency of each GI practice. GI practice implementation scenarios in 2050 were also simulated based on projected land use and rainfall data. Results show that grassed swales, rain barrels (residential areas) and dry ponds were the top three most cost-efficient GI practices, with the cost at $1.5/m³/yr, $3.0/m³/yr and $3.4/m³/yr, respectively. Green roofs with rain cisterns (industrial and commercial area) were the most expensive GI practices, with the cost at $92.9/m³/yr. With the increase of investment in GI practices, the changing curves of the annual runoff volume, Total Nitrogen (TN) load and Total Phosphorus (TP) load reduction ratios match the law of diminishing marginal utility. The scenario with grassed swales, rain barrels, dry ponds and porous pavement would be the most cost-efficient scenario for runoff water quantity reduction. In addition, the scenario with additional wet ponds would be the most cost-efficient one for TN load and TP load reduction. GI practices in each scenario for expected 2050 conditions show better effectiveness on water quantity and quality management.

Towards sustainable water resources planning and pollution control: Inexact joint-probabilistic double-sided stochastic chance-constrained programming model.

This study presents an inexact joint-probabilistic double-sided stochastic chance-constrained programming (IJDSCCP) model for sustainable water resources planning and pollution control in water quality management systems under uncertainty. Techniques of interval parameter programming (IPP), joint-probabilistic programming (JPP) and double-sided stochastic chance-constrained programming (DSCCP) are incorporated into a modeling framework. The IJDSCCP can not only address uncertainties presented as interval parameters and double-sided randomness (i.e. both left-hand and right-hand sides) that are characterized as normal distributions, but also examine the reliability level of satisfying the entire system constraints. It further improves upon conventional stochastic chance-constrained programming for handing random uncertainties in the left-hand and right-hand sides of constraints. Moreover, a non-equivalent but sufficient linearization form of the IJDSCCP is presented to solve such a problem. Then, the model is applied to a representative case for water resources planning and pollution control. The results including water resources planning solutions, pollution control plans and system benefits under the combinations of different joint and individual probability levels will be obtained. The solutions are expressed as combinations of deterministic, interval and distributional information, which can facilitate analysis of different forms of uncertainties. After investigating and comparing the variations of results, it is found that an increasing joint probability level can lead to higher system benefits, i.e., [13,841.68, 21,801.81] × 106 Yuan (p = 0.01, p1 = 0.0033, p2 = 0.0033 and p3 = 0.0033), [14,150.26, 22,260.06] × 106 Yuan (p = 0.05, p1 = 0.0166, p2 = 0.0166 and p3 = 0.0166) and [14,280.55, 22,415.52] × 106 Yuan (p = 0.10, p1 = 0.033, p2 = 0.033 and p3 = 0.033). A set of decreased individual probability levels gives rise to the maximum system benefits at the same joint probability level. Furthermore, the results of the IJDSCCP are compared with a general interval-based optimization framework as well. Therefore, the results from the IJDSCCP are valuable for assisting managers in generating and identifying decision alternatives under different scenarios.

Marginal-cost-based greedy strategy (MCGS): Fast and reliable optimization of low impact development (LID) layout.

Cost effectiveness is a major concern when implementing low impact development (LID) practices for urban stormwater management (USWM). To optimize LID layout, an efficient and more reliable method, namely, the Marginal-Cost-based Greedy Strategy (MCGS) was developed based on the economic law of increasing marginal costs (MCs) and the stepwise minimization of MCs. To verify its broad applicability, MCGS was applied in three case studies in China with different system settings and environmental goals. Both Cases I and II were watershed-scale studies in Suzhou City urban districts, but in Case II, the impact of future uncertainties (i.e., climate change, urban expansion, and LID performance degradation) on USWM system performance was considered. Case III was a block-scale study of the Xixian New District (a pilot "Sponge City" in China), which involved a rainwater pipe network and a complicated environmental goal. Compared with the extensively used but complicated NSGA-II, the MCGS performed better in terms of yielding more converged performance trade-offs, providing more choices for city planners, and requiring much less computational resources in all three cases. Meanwhile, MCGS established an optimal pathway for multi-stage LID layout planning. The success of MCGS indicated that the MC of a LID practice determined its favorability in an USWM system.

Accurately early warning to water quality pollutant risk by mobile model system with optimization technology.

A fast and accurate water quality pollutant risk assessment and early warning system, which has great practical significance for decision making in accident management, is urgently needed for water protection and management. Based on a fast mobile early warning system named MEWSUB, this paper modified its framework to make it generate data more automatically and accurately. By adapting manning formula and particle swarm optimization (PSO) for parameters optimization, the accuracy of water quantity and water quality simulation results has been improved. The modified system was successfully applied in an antimony tailings dam leakage accident that happened in China. The coefficient of determination (R2) of the prediction result was higher than 0.9 and relative error (ree) was less than 0.1, which indicated that the accuracy of MEWSUB was high enough for realistic water quality pollutant risk early warning.

Assessment of debris inputs from land into the river in the Three Gorges Reservoir Area, China.

Riverine debris in the Three Gorges Reservoir Area (TGRA) poses a threat to electricity generation, ship navigation, and water environment. Quantifying riverine debris inputs from land into the river is a foundation for modeling of the transport and accumulation of floating debris on the water surface in the TGRA. However, this has not been researched to date. In this study, debris inputs from land into the river in the TGRA were assessed according to the response relationship between debris inputs and surface runoff. The land-based debris inputs in the TGRA were estimated using simulated surface runoff which was simulated by the Soil and Water Assessment Tool (SWAT) model. Results showed that 15.32 × 106 kg of land-based debris was inputted into the main channel of the TGRA in 2015 which accounted for 9.74% of total debris inputs (the monitoring data of river-sourced and land-sourced debris inputs was 157.27 × 106 kg). Debris inputs varied seasonally and peaked in the summer season (July to September). Compared with monthly measured data, the average relative errors in 2015 were below 30%. In addition, areas with higher debris pollution inputs were mainly located in the upper section of the TGRA, between the Tang River Basin and the Long River Basin. The proposed method was tested and determined to be reliable; thus, it can be used to quickly estimate debris inputs from land into the river by surface runoff of the outlets in a river basin. Moreover, this method provides new insight into the estimation of land-based debris inputs into rivers.

Evaluation of bioenergy crop growth and the impacts of bioenergy crops on streamflow, tile drain flow and nutrient losses in an extensively tile-drained watershed using SWAT.

Large quantities of biofuel production are expected from bioenergy crops at a national scale to meet US biofuel goals. It is important to study biomass production of bioenergy crops and the impacts of these crops on water quantity and quality to identify environment-friendly and productive biofeedstock systems. SWAT2012 with a new tile drainage routine and improved perennial grass and tree growth simulation was used to model long-term annual biomass yields, streamflow, tile flow, sediment load, and nutrient losses under various bioenergy scenarios in an extensively agricultural watershed in the Midwestern US. Simulated results from bioenergy crop scenarios were compared with those from the baseline. The results showed that simulated annual crop yields were similar to observed county level values for corn and soybeans, and were reasonable for Miscanthus, switchgrass and hybrid poplar. Removal of 38% of corn stover (3.74Mg/ha/yr) with Miscanthus production on highly erodible areas and marginal land (17.49Mg/ha/yr) provided the highest biofeedstock production (279,000Mg/yr). Streamflow, tile flow, erosion and nutrient losses were reduced under bioenergy crop scenarios of bioenergy crops on highly erodible areas and marginal land. Corn stover removal did not result in significant water quality changes. The increase in sediment and nutrient losses under corn stover removal could be offset with the combination of other bioenergy crops. Potential areas for bioenergy crop production when meeting the criteria above were small (10.88km2), thus the ability to produce biomass and improve water quality was not substantial. The study showed that corn stover removal with bioenergy crops both on highly erodible areas and marginal land could provide more biofuel production relative to the baseline, and was beneficial to water quality at the watershed scale, providing guidance for further research on evaluation of bioenergy crop scenarios in a typical extensively tile-drained watershed in the Midwestern U.S.

Optimal implementation of green infrastructure practices to minimize influences of land use change and climate change on hydrology and water quality: Case study in Spy Run Creek watershed, Indiana.

Nutrient loading from the Maumee River watershed is a significant reason for the harmful algal blooms (HABs) problem in Lake Erie. The nutrient loading from urban areas needs to be reduced with the installation of green infrastructure (GI) practices. The Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 (L-THIA-LID 2.1) model was used to explore the influences of land use (LU) and climate change on water quantity and quality in Spy Run Creek watershed (SRCW) (part of Maumee River watershed), decide whether and where excess phosphorus loading existed, identify critical areas to understand where the greatest amount of runoff/pollutants originated, and optimally implement GI practices to obtain maximum environmental benefits with the lowest costs. Both LU/climate changes increased runoff/pollutants generated from the watershed. Areas with the highest runoff/pollutant amount per area, or critical areas, differed for various environmental concerns, land uses (LUs), and climates. Compared to optimization considering all areas, optimization conducted only in critical areas can provide similar cost-effective results with decreased computational time for low levels of runoff/pollutant reductions, but critical area optimization results were not as cost-effective for higher levels of runoff/pollutant reductions. Runoff/pollutants for 2011/2050 LUs/climates could be reduced to amounts of 2001 LU/climate by installation of GI practices with annual expenditures of $0.34 to $2.05 million. The optimization scenarios that were able to obtain the 2001 runoff level in 2011/2050, can also reduce all pollutants to 2001 levels in this watershed.

A review on effectiveness of best management practices in improving hydrology and water quality: Needs and opportunities.

Best management practices (BMPs) have been widely used to address hydrology and water quality issues in both agricultural and urban areas. Increasing numbers of BMPs have been studied in research projects and implemented in watershed management projects, but a gap remains in quantifying their effectiveness through time. In this paper, we review the current knowledge about BMP efficiencies, which indicates that most empirical studies have focused on short-term efficiencies, while few have explored long-term efficiencies. Most simulation efforts that consider BMPs assume constant performance irrespective of ages of the practices, generally based on anticipated maintenance activities or the expected performance over the life of the BMP(s). However, efficiencies of BMPs likely change over time irrespective of maintenance due to factors such as degradation of structures and accumulation of pollutants. Generally, the impacts of BMPs implemented in water quality protection programs at watershed levels have not been as rapid or large as expected, possibly due to overly high expectations for practice long-term efficiency, with BMPs even being sources of pollutants under some conditions and during some time periods. The review of available datasets reveals that current data are limited regarding both short-term and long-term BMP efficiency. Based on this review, this paper provides suggestions regarding needs and opportunities. Existing practice efficiency data need to be compiled. New data on BMP efficiencies that consider important factors, such as maintenance activities, also need to be collected. Then, the existing and new data need to be analyzed. Further research is needed to create a framework, as well as modeling approaches built on the framework, to simulate changes in BMP efficiencies with time. The research community needs to work together in addressing these needs and opportunities, which will assist decision makers in formulating better decisions regarding BMP implementation in watershed management projects.

Optimal selection and placement of green infrastructure to reduce impacts of land use change and climate change on hydrology and water quality: An application to the Trail Creek Watershed, Indiana.

The adverse impacts of urbanization and climate change on hydrology and water quality can be mitigated by applying green infrastructure practices. In this study, the impacts of land use change and climate change on hydrology and water quality in the 153.2 km(2) Trail Creek watershed located in northwest Indiana were estimated using the Long-Term Hydrologic Impact Assessment-Low Impact Development 2.1 (L-THIA-LID 2.1) model for the following environmental concerns: runoff volume, Total Suspended Solids (TSS), Total Phosphorous (TP), Total Kjeldahl Nitrogen (TKN), and Nitrate+Nitrite (NOx). Using a recent 2001 land use map and 2050 land use forecasts, we found that land use change resulted in increased runoff volume and pollutant loads (8.0% to 17.9% increase). Climate change reduced runoff and nonpoint source pollutant loads (5.6% to 10.2% reduction). The 2050 forecasted land use with current rainfall resulted in the largest runoff volume and pollutant loads. The optimal selection and placement of green infrastructure practices using L-THIA-LID 2.1 model were conducted. Costs of applying green infrastructure were estimated using the L-THIA-LID 2.1 model considering construction, maintenance, and opportunity costs. To attain the same runoff volume and pollutant loads as in 2001 land uses for 2050 land uses, the runoff volume, TSS, TP, TKN, and NOx for 2050 needed to be reduced by 10.8%, 14.4%, 13.1%, 15.2%, and 9.0%, respectively. The corresponding annual costs of implementing green infrastructure to achieve the goals were $2.1, $0.8, $1.6, $1.9, and $0.8 million, respectively. Annual costs of reducing 2050 runoff volume/pollutant loads were estimated, and results show green infrastructure annual cost greatly increased for larger reductions in runoff volume and pollutant loads. During optimization, the most cost-efficient green infrastructure practices were selected and implementation levels increased for greater reductions of runoff and nonpoint source pollutants.