Risk Assessment of Runoff Generation Using Artificial Neural Network and Field Plots in The Area of Roads and Forest Lands

Runoff generation potential (RGP) on hillslopes is an important issue in the forest roads network monitoring process. In this study, the artificial neural network (ANN) was used to predict RGP in forest road hillslopes. We trained, optimized, and tested the ANN by using field plot data from the Shirghalaye watershed located in the southern part of the Caspian Sea (Iran). 45 plots were installed to measure actual runoff volume (RFP) in different environmental conditions including land cover, slope gradient, soil texture, and soil moisture. A multi-layer perceptron (MLP) network was implemented. The runoff volume was the output variable and the ground cover, slope gradient, initial moisture of soil, soil texture (clay, silt, and sand percentage) were the network inputs. The results showed that ANN can predict runoff volume within the values of an appropriate level in the training (R2=0.95, MSE= 0.009) and test stages (R2=0.80, MSE= 0.01). Moreover, the tested network was used to predict the runoff volume on the forest road hillslopes in the study area. Finally, an RGP map was generated based on the results of the prediction of the ANNs and the GIS capabilities. The results showed that using both an ANN and a GIS is a good tool to predict the RGP in the forest road hillslopes.

Increased vegetation ground cover reduces water, sediment and phosphorus losses in Cambisol treated with swine slurry

This study aims to evaluate the influence of the ground cover rate by crop residues and the rain time elapsed after the application of liquid swine slurry (LSS) under losses of water, sediments, and phosphorus (P). The study was carried out under a Humic Cambisols. Two areas were delimited: with and without the application of LSS. Each area was subdivided into four levels of crop residues: 5%, 35%, 65%, and 95%. Vegetable residues present in the area, from corn and black oat, were used. Three collecting gutters of 0.60 m² were installed in each subplot. Simulated rain was carried out on these, and the runoff volume collected for quantification and determination of losses. With LSS application, increase in the cover rate by crop residues reduces 0.3 mm h-1 the runoff volume and 1.67 mg m-2 reactive soluble P (H2O-P). The sediment losses in the first collection after the beginning of the rain were 23 times lower in the soil with 95% ground cover than in the soil with 5% ground cover. The loss of total P (total-P) decreases with the increase of the ground cover of the soil and increases in the same way with the increase of the time.

The Application of Low Impact Development Facility Chain on Storm Rainfall Control: A Case Study in Shenzhen, China

In recent decades, low impact development (LID) has become an increasingly important concern as a state-of-the-art stormwater management mode to treat urban flood, preferable to conventional urban drainage systems. However, the effects of the combined use of different LID facilities on urban flooding have not been fully investigated under different rainfall characteristics. In this study, a residential, neighborhood-scale catchment in Shenzhen City, southern China was selected as a case study, where the effects of four LID techniques (bio-retention, bio-swale, rain garden and pervious pavement) with different connection patterns (cascaded, semi-cascaded and paralleled) on runoff reduction efficiency were analyzed by the storm water management model (SWMM), promoted by the U.S. EPA. Three kinds of designed storm events with different return periods, durations and time-to-peak ratios were forced to simulate the flood for holistic assessment of the LID connection patterns. The effects were measured by the runoff coefficient of the whole storm–runoff process and the peak runoff volume. The results obtained indicate that the cascaded connect LID chain can more effectively reduce the runoff than that in the paralleled connect LID chain under different storms. The performances of the LID chains in modeling flood process in SWMM indicate that the runoff coefficient and the peak runoff volume increase with the increase in the rain return periods and the decrease in rain duration. Additionally, the move backward of the peak rain intensity to the end of the storm event slightly affects the peak runoff volume obviously while gives slight influence on the total runoff volume. This study provides an insight into the performance of LID chain designs under different rainfall characteristics, which is essential for effective urban flood management.

Comparison between different infiltration models to describe the infiltration of permeable brick pavement system via lab-scale experiment

Permeable brick pavement system (PBPs) is one of a widely used low impact development (LID) measures to alleviate runoff volume and pollution caused by urbanization. The performance of PBPs on decreasing runoff volume is decided by its permeability, and it was general described by hydraulic conductivity based on Darcy's law. But there is large error when using hydraulic conductivity to describe the infiltration of PBPs, and which infiltration process is not following to the Darcy's law, so it is important to found a more accurate infiltration models to describe the infiltration of PBPs. The Horton, Philip, Green-Ampt, and Kostiakov infiltration models were selected to found an optimal model to investigate infiltration performance of PBPs via lab-scale experiment, and the maximum absolute error (MAE), Bias, and coefficient of determination (R2) were selected to evaluate the models' errors via fitting with experiment data. The results showed that the fitting accuracy of Kostiakov, Philip, and Green-Ampt models was significantly affected by the monitoring area and hydraulic gradients. Meanwhile, Horton model is fitting well (MAE = 0.25–0.32 cm/h, Bias = 0.07–0.11 cm/h, and R2 = 0.98–0.99) with the experiment data, and the parameters of Horton model often can be achieved by monitoring, such as the maximum infiltration rate and the stable infiltration rate. Therefore, the Horton model is an optimal model to describe the infiltration performance of PBPs, which can also be adopt to evaluate hydrological characterization of PBPs.

Assessment of Pollutants from Diffuse Pollution through the Correlation between Rainfall and Runoff Characteristics Using EMC and First Flush Analysis

Urban stormwater runoff is an important source of pollution in receiving water bodies, mainly in cities in development. However, strategies to deal with the impacts caused by the runoff discharges, such as implementing a sustainable urban drainage system (SUDS) with optimized management, need information usually obtained through monitoring studies. Brasília is a city that has one of the highest urban growth rates in Brazil, with significant impacts on urban water resources, including diffuse pollution, generated by new unregulated urban developments that initially start being built with precarious sanitation infrastructure. The Vicente Pires (VP) watershed is highly urbanized and comprises two areas that have been intensively occupied more recently, at a fast pace, and do not have yet basic sanitation systems fully implemented. Stormwater quality at the outlet of the VP watershed was analyzed by monitoring the rainfall, runoff flows, and pollutant concentration. Event Mean Concentration (EMC) and first-flush (FF) phenomenon were calculated, and hydrologic characteristics were compared for different events through correlation analysis. During dry periods the flow varied between 0.5 and 1.29 m3/s, while in flood periods the maximum value was 72.17 m3/s, forming floods with great volume. Nitrate during dry periods stands out with its high concentration; the maximum was 1.49 mg/L, while the maximum concentration during the flood events was 0.43 mg/L, probably due to dilution. Ammonia results showed very low values, probably because nitrification is occurring up to the collection point. The EMC values of solids in flood events were higher and can be attributed to river bed scour along the VP watershed. The EMC SS values for the VP watershed are also similar to areas in the initial stages of building development. The EMC values in the dry season indicate strong correlations between some water quality parameters such as NH+3-N and SS, TS and NO−3-N; NO−3-N, and COD. These correlations indicate that these pollutants are probably being generated by the same source, probably sewage discharges. During flood events, the correlation between pollutant loads and peak flow can be associated with the scouring during surface washing off, because greater concentrations of solids and organic matter occur in events with greater flow rates. For the first 30% of the initial runoff volume, about 29% of SS, 38% of NH+3-N, and 35% of reactive P were carried during flood events. It was verified that large values of maximum or mean rainfall intensity are related to the occurrence of First Flush (FF) for most pollutants. Antecedent dry days (ADD) did not influence build-up processes in this watershed; however, they are related to FF occurrence. Data indicate that the sewage and stormwater collection networks were being installed caused a high impact on observed water quality, with high concentrations of solids during flood events. On the other hand, the wastewater collection after the sewer network installation led to a decrease in COD concentrations over time. For sustainable management of diffuse pollution, the adoption of distributed SUDS to enhance runoff volume reduction is a recommended solution for the case.