Assessment of the Impacts of Land Use/Cover Change and Rainfall Change on Surface Runoff in China

Enhancing the SWAT model for creating efficient rainwater harvesting and reuse strategies to improve water resources management

Rain barrels/cisterns are a type of green infrastructure (GI) practice that can help restore urban hydrology. Roof runoff captured and stored by rain barrels/cisterns can serve as a valuable resource for landscape irrigation, which would reduce municipal water usage and decrease runoff that other stormwater infrastructures need to treat. The expected benefits of rainwater harvesting and reuse with rain barrels/cisterns are comprehensive but neither systematically investigated nor well documented. A comprehensive tool is needed to help stakeholders develop efficient strategies to harvest rainwater for landscape irrigation with rain barrels/cisterns. This study further improved the Soil and Water Assessment Tool (SWAT) in simulating urban drainage networks by coupling the Storm Water Management Model (SWMM)'s closed pipe drainage network (CPDN) simulation methods with the SWAT model that was previously improved for simulating the impacts of rainwater harvesting for landscape irrigation with rain barrels/cisterns. The newly improved SWAT or SWAT-CPDN was applied to simulate the urban hydrology of the Brentwood watershed (Austin, TX) and evaluate the long-term effects of rainwater harvesting for landscape irrigation with rain barrels/cisterns at the field and watershed scales. The results indicated that the SWAT-CPDN could improve the prediction accuracy of urban hydrology with good performance in simulating discharges (15 min, daily, and monthly), evapotranspiration (monthly), and leaf area index (monthly). The impacts of different scenarios of rainwater harvesting and reuse strategies (rain barrel/cistern sizes, percentages of suitable areas with rain barrels/cisterns implemented, auto landscape irrigation rates, and landscape irrigation starting times) on each indicator (runoff depth, discharge volume, peak runoff, peak discharge, combined sewer overflow-CSO, freshwater demand, and plant growth) at the field or watershed scale varied, providing insights for the long-term multi-functional impacts (stormwater management and rainwater harvesting/reuse) of rainwater harvesting for landscape irrigation with rain barrels/cisterns. The varied rankings of scenarios found for achieving each goal at the field or watershed scale indicated that tradeoffs in rainwater harvesting and reuse strategies exist for various goals, and the strategies should be evaluated individually for different goals to optimize the strategies. Efficient rainwater harvesting and reuse strategies at the field or watershed scale can be created by stakeholders with the assist of the SWAT-CPDN to reduce runoff depth, discharge volume, peak runoff, peak discharge, CSO, and freshwater demand, as well as improve plant growth.

Development and Application of a QGIS-Based Model to Estimate Monthly Streamflow

Changes in rainfall pattern and land use have caused considerable impacts on the hydrological behavior of watersheds; a Long-Term Hydrologic Impact Analysis (L-THIA) model has been used to simulate such variations. The L-THIA model defines curve number according to the land use and hydrological soil group before calculating the direct runoff based on the amount of rainfall, making it a convenient method of analysis. Recently, a method was proposed to estimate baseflow using this model, which may be used to estimate the overall streamflow. Given that this model considers the spatial distribution of land use and hydrological soil groups and must use rainfall data at multiple positions, it requires the usage of a geographical information system (GIS). Therefore, a model that estimates streamflow using land use maps, hydrologic soil group maps, and rain gauge station maps in QGIS, a popular GIS software, was developed. This model was tested in 15 watersheds.

Land cover change and its implication to hydrological regimes and soil erosion in Awash River basin, Ethiopia: a systematic review

The Awash River basin is one of the most developed basins in Ethiopia, and its water resources are crucial to development. The collective impact of land cover (LC) changes has driven a difference in the hydrological components, substantially impacting the availability of water resources and demand. This review aimed (i) to examine the extent of change quantitatively and its effects; (ii) to analyze the relationship with a mean annual rainfall that would further reveal the causes and potential LC type response to hydrologic variables in the Awash River basin, Ethiopia. The results have revealed that urbanization and agricultural activities in the basin are the most trending types of LC, while the forest, shrubland, grassland, and pasture land have been decreasing significantly in the subbasins. As a result, the change in these subbasins has triggered hydrologic variations (runoff, groundwater flow, base flow, and evapotranspiration), and its impacts on downstream basins have mostly been flood and drought. In addition, farmland, urbanization, and shrubland trends showed a significant positive interaction, while forest and water bodies had a substantial and slight negative relation to mean annual rainfall, respectively. Vegetation, bareland, urbanization, and agriculture/farmland are directly responsible for the hydrologic variation. LC change significantly affected hydrologic regimes and the distribution of spatial rainfall is correlated significantly to LC change pattern. Besides, due to the lack of LC management practices, the impact continues to propagate. Hence, this review helps to portray the potential implications and extent of effects of changes in LC on the hydrological regimes. As a result, the implementation of sound water management strategies and practices in response to changing environments to resurrect water scarcity and mitigate flood and sediment are needed straightaway.

A Study to Suggest Monthly Baseflow Estimation Approach for the Long-Term Hydrologic Impact Analysis Models: A Case Study in South Korea

Changes in both land use and rainfall patterns can lead to changes in the hydrologic behavior of the watershed. The long-term hydrologic impact analysis (L-THIA) model has been used to predict such changes and analyze the changes in mitigation scenarios. The model is simple as only a small amount of input data are required, but it can predict only the direct runoff and cannot determine the streamflow. This study, therefore, aimed to propose a method for predicting the monthly baseflow while maintaining the simplicity of the model. The monthly baseflows for 20 watersheds in South Korea were estimated under different land use conditions. Calibration of the monthly baseflow prediction method produced values for R2 and the Nash–Sutcliffe efficiency (NSE) within the ranges of 0.600–0.817 and 0.504–0.677, respectively; during validation, these values were in the ranges of 0.618–0.786 and 0.567–0.727, respectively. This indicates that the proposed method can reliably predict the monthly baseflow while maintaining the simplicity of the L-THIA model. The proposed model is expected to be applicable to all the various forms of the model.

Assessing the Effectiveness and Cost Efficiency of Green Infrastructure Practices on Surface Runoff Reduction at an Urban Watershed in China

Studies on the assessment of green infrastructure (GI) practice implementation effect and cost efficiency on an urban watershed scale helps the GI practice selection and investment decisions for sponge city construction in China. However, few studies have been conducted for these topics at present. In this study, the Long-Term Hydrologic Impact Assessment—Low Impact Development (L-THIA-LID) 2.1 model was applied to assess the effectiveness and cost efficiency of GI practices on surface runoff volume reduction in an urban watershed—the Hexi watershed, Nanjing City, China. Grassed swales, bioretentions, green roofs, rain cisterns, permeable pavements, wet ponds, dry ponds, and wetlands were chosen as potential GI practices for sponge city construction based on feasibility analysis. Results showed that grassed swales were the most cost-effective practice (0.7 CNY/m3/yr), but the total implementation effect of grassed swales was not obvious due to the small area of suitable locations. Permeable pavements performed best on runoff reduction, but the cost efficiency was much lower. Correspondingly, bioretentions were compromise practices. Green roofs were the least cost-effective practices, with the cost efficiency at 122.3 CNY/m3/yr, but it was much lower for rain cisterns, which were 3.2 CNY/m3/yr. Wet ponds, dry ponds, and wetlands were potential practices implemented in development areas, of which dry ponds were the most cost-effective (2.7 CNY/m3/yr), followed by wet ponds (10.9 CNY/m3/yr). The annual runoff volume of the total area could be reduced by up to 47.01% by implementing GI practices in buildup areas. Rain cisterns (RC) and permeable pavements (PP) were the best combination for this area, and bioretentions (BR) and green roofs (GR) followed. Grassed swales (GS1), dry ponds (DP), wet ponds (WP), and wetlands (WL) were not wise choices due to the small suitable location areas. This study also demonstrated the feasibility of the L-THIA-LID 2.1 model for the evaluation of GI practice implementation effects and cost efficiency on urban runoff in sponge city construction in China.

Hydrological Image Building Using Curve Number and Prediction and Evaluation of Runoff through Convolution Neural Network

This study developed a runoff model using a convolution neural network (CNN), which had previously only been used for classification problems, to get away from artificial neural networks (ANNs) that have been extensively used for the development of runoff models, and to secure diversity and demonstrate the suitability of the model. For this model’s input data, photographs typically used in the CNN model could not be used; due to the nature of the study, hydrological images reflecting effects such as watershed conditions and rainfall were required, which posed further difficulties. To address this, the method of a generating hydrological image using the curve number (CN) published by the Soil Conservation Service (SCS) was suggested in this study, and the hydrological images using CN were found to be sufficient as input data for the CNN model. Furthermore, this study was able to present a new application for the CN, which had been used only for estimating runoff. The model was trained and generalized stably overall, and R2, which indicates the relationship between the actual and predicted values, was relatively high at 0.82. The Pearson correlation coefficient, Nash–Sutcliffe efficiency (NSE), and root mean square error (RMSE), were 0.87, 0.60, and 16.20 m3/s, respectively, demonstrating a good overall model prediction performance.

Using SCS-CN and Earth Observation for the Comparative Assessment of the Hydrological Effect of Gradual and Abrupt Spatiotemporal Land Cover Changes

In this study a comparative assessment of the impacts of urbanization and of forest fires as well as their combined effect on runoff response is investigated using earth observation and the Soil Conservation Service Curve Number (SCS-CN) direct runoff estimation method in a Mediterranean peri-urban watershed in Attica, Greece. The study area underwent a significant population increase and a rapid increase of urban land uses, especially from the 1980s to the early 2000s. The urbanization process in the studied watershed caused a considerable increase of direct runoff response. A key observation of this study is that the impact of forest fires is much more prominent in rural watersheds than in urbanized watersheds. However, the increments of runoff response are important during the postfire conditions in all cases. Generally, runoff increments due to urbanization seem to be higher than runoff increments due to forest fires affecting the associated hydrological risks. It should also be considered that the effect of urbanization is lasting, and therefore, the possibility of an intense storm to take place is higher than in the case of forest fires that have an abrupt but temporal impact on runoff response. It should be noted though that the combined effect of urbanization and forest fires results in even higher runoff responses. The SCS-CN method, proved to be a valuable tool in this study, allowing the determination of the direct runoff response for each soil, land cover and land management complex in a simple but efficient way. The analysis of the evolution of the urbanization process and the runoff response in the studied watershed may provide a better insight for the design and implementation of flood risk management plans.