Adaptive pressure-driven multi-criteria spatial decision-making for a targeted placement of green and grey runoff control infrastructures.

Traditional runoff control measures ignore the spatial imbalance of regional pressures, thereby failing to achieve a site-specific placement for green and grey infrastructure simultaneously. A multi-criterion decision-making framework for runoff control infrastructure spatial planning was therefore developed in this study. The pressure-state-response framework was applied to creatively match the pressure induced adjustment demands with the infrastructure effectiveness. The pressures were quantified from the perspective of environment, economy, and ecology on a grid scale. States were considered as the relative priority of regional pressure adjustment demand in multiple perspectives. Responses were presented as state-targeted green and grey infrastructure placement. Multi-perspective effectiveness of different green and grey infrastructure was simultaneously evaluated at an effective scale of controlling 1 m3/s runoff for comparison. Methods such as data mining, hydrological model simulation, and remote sensing inversion were combined to quantify the regional pressures. The capital investment and ecological impact of infrastructures were quantified from a life cycle perspective. A case study was carried out in Wuhan, China. The study area was clustered by gridded pressure into three regions. In region Ⅰ, ecological and environmental pressure were of higher weight. In region Ⅱ, the environmental pressure was dominant. In region Ⅲ, the ecological pressure took precedence over the environmental and economic constraints. The area ratios of the region Ⅰ, Ⅱ, and Ⅲ were 43%, 36%, and 21% respectively. The result indicated a synergy and spatial heterogeneity of multi-perspective pressures, and further demonstrating that expert experience tends to fail to weigh the multi-function of green and grey infrastructures for coping with the pressures. Results also stated that green infrastructures were more acceptable in areas that aspire to achieve simultaneous runoff control and ecological improvement. The decision-making framework developed in this study can maximize the overall performance by providing targeted infrastructure placement solutions.

The influence of extensive green roofs on rainwater runoff quality: a field-scale study in southwest China.

Green roofs of young age (≤ 5 years old) have boomed in China since the Sponge City Construction initiative was implemented. To use green roofs for better urban stormwater management, it is necessary to investigate the runoff quality of field-scale young green roofs as well as to examine common plant-media combination in green roof projects of China. The influence of two Sedum-vegetated extensive green roofs of different designs at the early stage of operation on runoff water quality was investigated by a field-scale study in Chengdu, southwest China. The water quality parameters of pH, suspended solids (SS), chemical oxygen demand (COD), total phosphorus (TP), and total nitrogen (TN) of rainwater (that is, input water for roofs), runoff from the two green roofs, and runoff from a conventional concrete control roof were compared. The results indicate that both green roofs mainly act as pollutant sources with greater concentrations of SS, COD, and TP when compared with rainwater quality. When compared with runoff quality from the control roof, greater TP concentrations in runoff from one green roof with commercially available substrate were observed. Attention should be paid to TP leaching in runoff for retrofitted green roofs with imported commercial substrates in that region. Adoption of pre-cultivated S. lineare mats of low fertility and localized soils may reduce nutrient leaching in green roof runoff. A nitrogen-rich substrate is not recommended for a plant community of a single species. Investigation of the effect of green roofs on water quality involving various pollutants in the long run is recommended.

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.

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.

Field monitoring of a LID-BMP treatment train system in China.

In order to assess the urban runoff control effectiveness of a low-impact development best management practice (LID-BMP) treatment train system, a field test of selected LID-BMPs was conducted in China. The LID-BMPs selected include three grassed swales, a buffer strip, a bioretention cell, two infiltration pits, and a constructed wetland. The test site is in a campus in southern China. The LID-BMPs, connected in a series, received stormwater runoff from four tennis courts with an area of 2808 m(2) and eight basketball courts with an area of 4864 m(2). Construction of the LID-BMPs was completed in early spring of 2012, and the sampling was conducted during May of 2012 to September of 2013. During the sampling effort, besides the performance evaluations of grassed swales and the bioretention cell in controlling runoff quantity as well as quality, the emphasis was also on determining the performance of the LID-BMP treatment train system. A total of 19 storm events were monitored, with nine producing no runoff and ten producing runoff. Data collected from the ten storm events were analyzed for estimating runoff quantity (peak flow rate and total runoff volume) and quality reduction by the LID-BMPs. The sum of loads (SOL) method was used for calculating the water quality performance of LID-BMPs. Results indicated that, for peak flow rate, a bioretention cell reduction of 50-84 % was obtained, and grassed swale reduction was 17-79 %, with a runoff volume reduction of 47-80 and 9-74 %, respectively. For water quality, the bioretention cell in general showed good removal for zinc (nearly 100 %), copper (69 %), NH3-N (ammonia nitrogen) (51 %), and total nitrogen (TN) (49 %); fair removal for chemical oxygen demand (COD) (18 %); and poor removal for total suspended solids (TSS) (-11 %) and total phosphorus (TP) (-21 %). And its performance effectiveness for pollutant removal increased in the second year after 1 year of stabilizing. When considering the aggregated effect of the LID-BMP treatment train system, it showed excellent removal for NH3-N (73 %), TN (74 %), and TP (95 %) and fair removal for COD (19 %) and TSS (35 %). The assessment results of the LID-BMP treatment train system provide valuable information on how to link the different types of LID-BMP facilities and maximize the integrated effectiveness on urban runoff control.

LID-BMPs planning for urban runoff control and the case study in China.

Low Impact Development Best Management Practices (LID-BMPs) have in recent years received much recognition as cost-effective measures for mitigating urban runoff impacts. In the present paper, a procedure for LID-BMPs planning and analysis using a comprehensive decision support tool was proposed. A case study was conducted to the planning of an LID-BMPs implementation effort at a college campus in Foshan, Guangdong Province, China. By examining information obtained, potential LID-BMPs were first selected. SUSTAIN was then used to analyze four runoff control scenarios, namely: pre-development scenario; basic scenario (existing campus development plan without BMP control); Scenario 1 (least-cost BMPs implementation); and, Scenario 2 (maximized BMPs performance). A sensitivity analysis was also performed to assess the impact of the hydrologic and water quality parameters. The optimal solution for each of the two LID-BMPs scenarios was obtained by using the non-dominated sorting genetic algorithm-II (NSGA-II). Finally, the cost-effectiveness of the LID-BMPs implementation scenarios was examined by determining the incremental cost for a unit improvement of control.

Development of a multi-criteria index ranking system for urban runoff best management practices (BMPs) selection.

Low impact development best management practices (LID-BMPs) are considered to be cost-effective measures for mitigating the water quantity and quality impact of urban runoff. Currently, there are many types of LID-BMPs, and each type has its own intrinsic technical and/or economical characteristics and limitations for implementation. The selection of the most appropriate BMP type(s) for a specific installation site is therefore a very important planning step. In the present study, a multi-criteria selection index system (MCIS) for LID-BMP planning was developed. The selection indexes include 12 first-level indices and 26 second-level indices which reflect the specific installation site characteristics pertaining to site suitability, runoff control performance, and economics of implementation. A mechanism for ranking the BMPs was devised. First, each individual second-level index was assigned a numeric value that was based on site characteristics and information on LID-BMPs. The quantified indices were normalized and then integrated to obtain the score for each of the first-level index. The final evaluation scores of each LID-BMP were then calculated based on the scores for the first-level indices. Finally, the appropriate BMP types for a specific installation site were determined according to the rank of the final evaluation scores. In order to facilitate the application of the MCIS BMP ranking system, the computational process has been coded into a software program, BMPSELEC. A case study demonstrating the MCIS methodology, using an LID-BMP implementation planning at a college campus in Foshan, Guangdong Province, is presented.

A storm event-based approach to TMDL development.

It is vitally important to define the critical condition for a receiving water body in the total maximum daily load (TMDL) development process. One of the major disadvantages of using a continuous simulation approach is that there is no guarantee that the most critical condition will be covered within the subjectively selected representative hydrologic period, which is usually several years depending on the availability of data. Another limitation of the continuous simulation approach, compared to a design storm approach, is the lack of an estimate of the risk involved. Because of the above limitations, a storm event-based critical flow-storm (CFS) approach was previously developed to explicitly address the critical condition as a combination of a prescribed stream flow and a storm event of certain magnitude, both having a certain frequency of occurrence and when combined, would create a critical condition. The CFS approach was tested successfully in a TMDL study for Muddy Creek in Virginia. The present paper reports results of a comparative study on the applicability of the CFS approach in Taiwan. The Dy-yu creek watershed in northern Taiwan differs significantly from Muddy Creek in terms of climate, hydrology, terrain, and other characteristics. Results show that the critical condition for different watersheds might be also different, and that the CFS approach could clearly define that critical condition and should be considered as an alternative method for TMDL development to a continuous simulation approach.

Field evaluation of an innovative stormwater treatment device--the Stormvault system.

Stormvault is a new volume-control-based underground stormwater treatment system, which is well suited for implementation in urban areas. In order to evaluate the hydrologic and hydraulic function of the system and assess the pollutant removal capacity of the system, a field monitoring program was implemented during both wet and dry weather conditions for 2 years. The pollutants of interest were total suspended solids (TSS), chemical oxygen demand (COD), total phosphorus (TP), and orthophosphate (OP). Data of 35 storms obtained were then analyzed by using several methods, such as the efficiency ratios, the summation of loads, and the relative achievable efficiency (RAE) methods to obtain estimates for the pollutant removal efficiencies of the Stormvault unit. Results show the following average efficiencies: TSS 82.46%, COD 73.10%, TP 47.37%, and OP 52.54%. Statistical significance and variation of removal efficiency with inlet concentration were also examined.

Phosphorus load reduction goals for Feitsui Reservoir Watershed, Taiwan.

The present paper describes an effort for developing the total maximum daily load (TMDL) for phosphorus and a load reduction strategy for the Feitsui Reservoir in Northern Taiwan. BASINS model was employed to estimate watershed pollutant loads from nonpoint sources (NPS) in the Feitsui Reservoir watershed. The BASINS model was calibrated using field data collected during a 2-year sampling period and then used to compute watershed pollutant loadings into the Feitsui Reservoir. The simulated results indicate that the average annual total phosphorus (TP) loading into the reservoir is 18,910 kg/year, which consists of non-point source loading of 16,003 kg/year, and point source loading of 2,907 kg/year. The Vollenweider mass balance model was used next to determine the degree of eutrophication under current pollutant loading and the load reduction needed to keep the reservoir from being eutrophic. It was estimated that Feitsui Reservoir can becoming of the oligotrophic state if the average annual TP loading is reduced by 37% or more. The results provide the basis on which an integrated control action plan for both point and nonpoint sources of pollution in the watershed can be developed.

The parameter optimization in the inverse distance method by genetic algorithm for estimating precipitation.

The inverse distance method, one of the commonly used methods for analyzing spatial variation of rainfall, is flexible if the order of distances in the method is adjustable. By applying the genetic algorithm (GA), the optimal order of distances can be found to minimize the difference between estimated and measured precipitation data. A case study of the Feitsui reservoir watershed in Taiwan is described in the present paper. The results show that the variability of the order of distances is small when the topography of rainfall stations is uniform. Moreover, when rainfall characteristic is uniform, the horizontal distance between rainfall stations and interpolated locations is the major factor influencing the order of distances. The results also verify that the variable-order inverse distance method is more suitable than the arithmetic average method and the Thiessen Polygons method in describing the spatial variation of rainfall. The efficiency and reliability of hydrologic modeling and hence of general water resource management can be significantly improved by more accurate rainfall data interpolated by the variable-order inverse distance method.

Implementation of a best management practice (BMP) system for a clay mining facility in Taiwan.

The present paper describes the planning and implementation of a best management practice (BMP) system for a clay mining facility in Northern Taiwan. It is a challenge to plan and design BMPs for mitigating the impact of clay mining operations due to the fact that clay mining drainage typically contains very high concentrations of suspended solids (SS), Fe-ions, and [H+] concentrations. In the present study, a field monitoring effort was conducted to collect data for runoff quality and quantity from a clay mining area in Northern Taiwan. A BMP system including holding ponds connected in series was designed and implemented and its pollutant removal performance was assessed. The assessment was based on mass balance computations and an analysis of the relationship between BMP design parameters such as pond depth, detention time, surface loading rate, etc. and the pollutant removal efficiency. Field sampling results showed that the surface-loading rate is exponential related to the removing rate. The results provide the basis for a more comprehensive and efficient BMP implementation plan for clay mining operations.

Role of geographic information system (GIS) in watershed simulation by WinVAST model.

The uncertainty of modeling input will increase the simulation error, and this situation always happens in a model without user-friendly interface. WinVAST model, developed by the University of Virginia in 2003, treats an entire multi-catchment by a tree-view structure. Its extra computer programs can connect geographic information system (GIS). Model users can prepare all the necessary information in ArcGIS. Extracting information from GIS interface can not only decrease the inconvenience of data input, but also lower the uncertainty due to data preparation. The Daiyuku Creek and Qupoliao Creek in the Fei-tsui reservoir watershed in Northern Taiwan provided the setting for the case study reported herein. The required information, including slope, stream length, subbasin area, soil type and land-use condition, for WinVAST model should be prepared in a Microsoft Access database, which is the project file of WinVAST with extension mdb. In ArcGIS interface, when the soil layer, land-use layer, and Digital Elevation Model (DEM) map are prepared, all the watershed information can be created as well. This study compared the simulation results from automatically generated input and manual input. The results show that the relative simulation error resulting from the rough process of data input can be around 30% in runoff simulation, and even reach 70% in non-point source pollution (NPSP) simulation. It could conclude that GIS technology is significant for predicting watershed responses by WinVAST model, because it can efficiently reduce the uncertainty induced by input errors.

Interpolating precipitation and its relation to runoff and non-point source pollution.

When rainfall spatially varies, complete rainfall data for each region with different rainfall characteristics are very important. Numerous interpolation methods have been developed for estimating unknown spatial characteristics. However, no interpolation method is suitable for all circumstances. In this study, several methods, including the arithmetic average method, the Thiessen Polygons method, the traditional inverse distance method, and the modified inverse distance method, were used to interpolate precipitation. The modified inverse distance method considers not only horizontal distances but also differences between the elevations of the region with no rainfall records and of its surrounding rainfall stations. The results show that when the spatial variation of rainfall is strong, choosing a suitable interpolation method is very important. If the rainfall is uniform, the precipitation estimated using any interpolation method would be quite close to the actual precipitation. When rainfall is heavy in locations with high elevation, the rainfall changes with the elevation. In this situation, the modified inverse distance method is much more effective than any other method discussed herein for estimating the rainfall input for WinVAST to estimate runoff and non-point source pollution (NPSP). When the spatial variation of rainfall is random, regardless of the interpolation method used to yield rainfall input, the estimation errors of runoff and NPSP are large. Moreover, the relationship between the relative error of the predicted runoff and predicted pollutant loading of SS is high. However, the pollutant concentration is affected by both runoff and pollutant export, so the relationship between the relative error of the predicted runoff and the predicted pollutant concentration of SS may be unstable.