Long-Term Hydrologic Impact Assessment Research Articles

Calculating the Environmental Impacts of Low-Impact Development Using Long-Term Hydrologic Impact Assessment: A Review of Model Applications.

Low-impact development (LID) is a planning and design strategy that addresses water quality and quantity while providing co-benefits in the urban and suburban landscape. The Long-Term Hydrologic Impact Assessment (L-THIA) model estimates runoff and pollutant loadings using simple inputs of land use, soil type, and climatic data for the watershed-scale analysis of average annual runoff based on curve number analysis. Using Scopus, Web of Science, and Google Scholar, we screened 303 articles that included the search term "L-THIA", identifying 47 where L-THIA was used as the primary research method. After review, articles were categorized on the basis of the primary purpose of the use of L-THIA, including site screening, future scenarios and long-term impacts, site planning and design, economic impacts, model verification and calibration, and broader applications including policy development or flood mitigation. A growing body of research documents the use of L-THIA models across landscapes in applications such as the simulations of pollutant loadings for land use change scenarios and the evaluation of designs and cost-effectiveness. While the existing literature demonstrates that L-THIA models are a useful tool, future directions should include more innovative applications such as intentional community engagement and a focus on equity, climate change impacts, and the return on investment and performance of LID practices to address gaps in knowledge.

A Framework for Evaluating the Effects of Green Infrastructure in Mitigating Pollutant Transferal and Flood Events in Sunnyside, Houston, TX

There is a growing and critical need to develop solutions for communities that are at particular risk of the impacts of the nexus of hazardous substances and natural disasters. In urban areas at high risk for flooding and lacking proper land-use controls, communities are vulnerable to environmental contamination from industrial land uses during flood events. This research uniquely applied a series of landscape pzerformance models to evaluate such associations including (1) the Green Values National Stormwater Calculator, (2) the Value of Green Infrastructure Tool, and (3) the Long-Term Hydrologic Impact Assessment Model. This paper presents a framework for combining landscape performance models, which are often only individually applied, to evaluate green infrastructure impacts on flood mitigation and pollutant transfer during flooding events using the Sunnyside neighborhood in Houston, Texas, USA, as a case site. The results showed that the plan reduced the risk of flooding, decreased stormwater runoff contaminants, and provided a possible direction to protect vulnerable communities.

The projected impacts of smart decline on urban runoff contamination levels

There has been mounting interest about how the repurposing of vacant land (VL) through green infrastructure (the most common smart decline strategy) can reduce stormwater runoff and improve runoff quality, especially in legacy cities characterized by excessive industrial land uses and VL amounts. This research examines the long-term impacts of smart decline on both stormwater amounts and pollutants loads through integrating land use prediction models with green infrastructure performance models. Using the City of St. Louis, Missouri, USA as the study area, we simulate 2025 land use change using the Conversion of Land Use and its Effects (CLUE-S) and Markov Chain urban land use prediction models and assess these change’s probable impacts on urban contamination levels under different smart decline scenarios using the Long-Term Hydrologic Impact Assessment (L-THIA) performance model. The four different scenarios are: (1) a baseline scenario, (2) a 10% vacant land re-greening (VLRG) scenario, (3) a 20% VLRG scenario, and (4) a 30% VLRG scenario. The results of this study illustrate that smart decline VLRG strategies can have both direct and indirect impacts on urban stormwater runoff and their inherent contamination levels. Direct impacts on urban contamination include the reduction of stormwater runoff and non-point source (NPS) pollutants. In the 30% VLRG scenario, the annual runoff volume decreases by 11%, both physical, chemical, and bacterial pollutants are reduced by an average of 19%, compared to the baseline scenario. Indirect impacts include reduction of the possibility of illegal dumping on VL through mitigation and prevention of future vacancies.

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.

Review of Watershed-Scale Water Quality and Nonpoint Source Pollution Models.

Watershed-scale nonpoint source (NPS) pollution models have become important tools to understand, evaluate, and predict the negative impacts of NPS pollution on water quality. Today, there are many NPS models available for users. However, different types of models possess different form and structure as well as complexity of computation. It is difficult for users to select an appropriate model for a specific application without a clear understanding of the limitations or strengths for each model or tool. This review evaluates 14 more commonly used watershed-scale NPS pollution models to explain how and when the application of these different models are appropriate for a given effort. The models that are assessed have a wide range of capacities that include simple models used as rapid screening tools (e.g., Long-Term Hydrologic Impact Assessment (L-THIA) and Nonpoint Source Pollution and Erosion Comparison Tool (N-SPECT/OpenNSPECT)), medium-complexity models that require detail data input and limited calibration (e.g., Generalized Watershed Loading Function (GWLF), Loading Simulation Program C (LSPC), Source Loading and Management Model (SLAMM), and Watershed Analysis Risk Management Frame (WARMF)), complex models that provide sophisticated simulation for NPS pollution processes with intensive data and rigorous calibration (e.g., Agricultural Nonpoint Source pollution model (AGNPS/AnnAGNPS), Soil and Water Assessment Tool (SWAT), Stormwater Management Model (SWMM), and Hydrologic Simulation Program Fortran (HSPF)), and modeling systems that integrate various sub-models and tools, and contain the highest complexity to solve all phases of hydrologic, hydraulic, and chemical dynamic processes (e.g., Automated Geospatial Watershed Assessment Tool (AGWA), Better Assessment Science Integrating Point and Nonpoint Sources (BASINS) and Watershed Modeling System (WMS)). This assessment includes model intended use, components or capabilities, suitable land-use type, input parameter type, spatial and temporal scale, simulated pollutants, strengths and limitations, and software availability. Understanding the strengths and weaknesses of each watershed-scale NPS model will lead to better model selection for suitability and help to avoid misinterpretation or misapplication in practice. The article further explains the crucial criteria for model selection, including spatial and temporal considerations, calibration and validation, uncertainty analysis, and future research direction of NPS pollution models. The goal of this work is to provide accurate and concise insight for watershed managers and planners to select the best-suited model to reduce the harm of NPS pollution to watershed ecosystems.

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

Assessment of the impacts of land use/cover change (LUCC) and rainfall change on surface runoff depth can help provide an understanding of the temporal trend of variation of surface runoff and assist in urban construction planning. This study evaluated the impacts of LUCC and rainfall change on surface runoff depth by adopting the well-known Soil Conservation Service-Curve Number (SCS-CN) method and the widely used Long-Term Hydrologic Impact Assessment (L-THIA) model. National hydrologic soil group map of China was generated based on a conversion from soil texture classification system. The CN values were adjusted based on the land use/cover types and soil properties in China. The L-THIA model was configured by using the adjusted CN values and then applied nationally in China. Results show that nationwide rainfall changes and LUCC from 2005 to 2010 had little impact on the distribution of surface runoff, and the high values of runoff depth were mainly located in the middle and lower reaches of the Yangtze River. Nationally, the average annual runoff depths in 2005, 2010 and 2015 were 78 mm, 83 mm and 90 mm, respectively. For the 2015 land use data, rainfall change caused the variation of surface runoff depth ranging from −203 mm to 476 mm in different regions. LUCC from 2005 to 2015 did not cause obvious change of surface runoff depth, but expansion of developed land led to runoff depth increases ranging from 0 mm to 570 mm and 0 mm to 742 mm from 2005 to 2010 and 2010 to 2015, respectively. Potential solutions to urban land use change and surface runoff control were also analyzed.

Mitigating Runoff: Improving the Accuracy of the Long-Term Hydrologic Impact Assessment (L-THIA) Model

Mitigating Runoff: Improving the Accuracy of the Long-Term Hydrologic Impact Assessment (L-THIA) Model

Suitability of CLIGEN precipitation estimates based on an updated database and their impacts on urban runoff: a case study of the Great Lakes Region, USA

ABSTRACTWeather generators rely on historical meteorological records to simulate time series of synthetic weather sequences, the quality of which has direct influence on model applications. The climate generator CLIGEN’s database has recently been updated to comprise consistent historical records from 1974 to 2013 (updated CLIGEN database, UCD) compared to the current database in which records are of different lengths. In this study, CLIGEN’s performance in estimating precipitation using UCD (eight stations) and the subsequent impact on urban runoff simulations (371 stations) were evaluated in the Great Lakes Region, USA. Generally, UCD-based precipitation could replicate observed daily precipitation up to the 99.5th percentile, but maximum precipitation was underestimated. Results from the Long-Term Hydrologic Impact Assessment model using UCD-based precipitation showed about 0.57 billion cubic meters more (14.9%) average annual runoff being simulated compared with simulations based on the current CLIGEN database. Overall, CLIGEN with the updated database was found suitable for providing precipitation estimates and for use with modeling urban runoff or urbanization effects.

Long-Term Hydrologic Impact Assessment of Non-point Source Pollution Measured Through Land Use/Land Cover (LULC) Changes in a Tropical Complex Catchment

The contribution of non-point source pollution (NPS) to the contamination of surface water is an issue of growing concern. Non-point source (NPS) pollutants are of various types and altered by several site-specific factors making them difficult to control due to complex uncertainties involve in their behavior. Kelantan River basin, Malaysia is a tropical catchment receiving heavy monsoon rainfall coupled with intense land use/land cover (LULC) changes making the area consistently flood prone thereby deteriorating the surface water quality in the area. This study was conducted to determine the spatio-temporal variation of NPS pollutant loads among different LULC changes and to establish a NPS pollutant loads relationships among LULC conditions and sub-basins in each catchment. Four pollutants parameters such as total suspended solids (TSS), total phosphorus (TP), total nitrogen (TN) and ammonia nitrogen (AN) were chosen with their corresponding event mean concentration values (EMC). Soil map and LULC change maps corresponding to 1984, 2002 and 2013 were used for the calculation of runoff and NPS pollutant loads using numeric integration in a GIS environment. Analysis of Variance (ANOVA) was conducted for the comparison of NPS pollutant loads among the three LULC conditions used and the sub-basins in each catchment. The results showed that the spatio-temporal variation of pollutant loads in almost all the catchments increased with changes in LULC condition as one moves from 1984 to 2013, with 2013 LULC condition found as the dominant in almost all cases. NPS pollutant loads among different LULC changes also increased with changes in LULC condition from 1984 to 2013. While urbanization was found to be the dominant LULC change with the highest pollutant load in all the catchments. Results from ANOVA reveals that statistically most significant (p < 0.05) pollutant loads were obtained from 2013 LULC conditions, while statistically least significant (p < 0.05) pollutant loads were obtained under 1984 LULC condition. This reveals the clear effect of LULC changes on NPS pollution. The findings of this study may be useful to water resource planners in controlling water pollution for future planning.

Development and evaluation of ArcGIS based watershed-scale L-THIA ACN-WQ system for watershed management

Abstract The Long-term Hydrologic Impact Assessment Model with Asymptotic Curve Number Regression Equation and Water Quality model (L-THIA ACN-WQ) has been developed to simulate streamflow as well as instream water quality using fewer parameters, compared to other watershed models. However, since model input parameters (i.e. hydraulic response unit (HRU) map, stream network, database (DB), etc.) should be built by user manually, it is difficult to use the model for a nonprofessional or environmental policy decision-maker. In addition, it is difficult to analyze model outputs in time and space because the model does not provide geographic information system (GIS) information for the simulation results. To overcome the limitations, an advanced version of L-THIA ACN-WQ system which is based on ArcGIS interface was developed in this study. To evaluate the applicability of the developed system, it was applied to the Banbyeon A watershed in which total maximum daily load (TMDL) has been implemented. The required model input datasets were automatically collected in the system, and stream flow, T-N and T-P pollutant loads were simulated for the watershed. Furthermore, flow duration curve (FDC) and load duration curve (LDC) were generated to analyze hot spot areas in the system through automatic processes included in the system. The system can establish the model input data easily, automatically provide the graphs of FDC and LDC, and provide hot spot areas which indicate high pollutant loads. Therefore, this system can be useful in establishing various watershed management plans.

Comparison of Computer Models for Estimating Hydrology and Water Quality in an Agricultural Watershed

Various computer models, ranging from simple to complex, have been developed to simulate hydrology and water quality from field to watershed scales. However, many users are uncertain about which model to choose when estimating water quantity and quality conditions in a watershed. This study compared hydrologic/water quality models including Spreadsheet Tool for the Estimation of Pollutant Load (STEPL)-Purdue, Soil and Water Assessment Tool (SWAT), High Impact Targeting (HIT), Long-Term Hydrologic Impact Assessment (L-THIA), Pollutant Load (PLOAD), Spatially and Temporally Distributed Model for Phosphorus Management (STEM-P), Region 5, and ensemble modeling (using STEPL-Purdue, SWAT, L-THIA, PLOAD, and STEM-P). Model capabilities, inputs, and underlying methods to estimate streamflow, surface runoff, baseflow, nutrients, and sediment were examined. Uncalibrated, calibrated, and validated outputs of these models and uncalibrated ensemble modeling in estimating water quantity and quality for a 41.5 km2 agricultural watershed in Northeastern Indiana were explored, and suggestions were provided on the selection and use of models. Models need to be selected carefully based on the simulation objectives, data availability, model characteristics, time constraints, and project budgets.

Modeling of Non-Point Source Pollution by Long-Term Hydrologic Impact Assessment (L-THIA) (Case Study: Zayandehrood Watershed) in 2015‎

Modeling of Non-Point Source Pollution by Long-Term Hydrologic Impact Assessment (L-THIA) (Case Study: Zayandehrood Watershed) in 2015‎

Assessment of impacts of land use changes on surface water using L-THIA model (case study: Zayandehrud river basin).

Land use changes in a basin are the most important factors affecting its hydrology and water quality. A hydrological model is an effective tool in assessing the effects of land use change on surface water. In this study, the effects of land use changes in the Zayandehrud basin are estimated using long-term hydrologic impact assessment model. This model is applicable using long-term data on climate, soil hydrological groups, and land use maps. The study covered three land uses across 18years (from 1997 to 2015), and we used data on 30years of precipitation (from 1985 to 2015) in the model. The results of modeling revealed that the average runoff volume increased from around 5,765,034m3 in 1997 to 8,894,525m3 in 2015. The results also showed an increase in runoff depth. Land use changes over the study period showed an increase of residential areas, bare land, and agricultural lands and a decrease of pasture and forests. The results can be used to make decisions and monitor changes in land use to control the depth and volume of runoff. Using output maps helps in delimitation of the areas that have high runoff average and in implementation of the management plans for controlling the amount of runoff in these areas. Appropriate land use design can decrease impacts of land use changes including hydrologic effects.

Non-Point Source Pollutant Load Variation in Rapid Urbanization Areas by Remote Sensing, Gis and the L-THIA Model: A Case in Bao'an District, Shenzhen, China.

Urban sprawl is a major driving force that alters local and regional hydrology and increases non-point source pollution. Using the Bao'an District in Shenzhen, China, a typical rapid urbanization area, as the study area and land-use change maps from 1988 to 2014 that were obtained by remote sensing, the contributions of different land-use types to NPS pollutant production were assessed with a localized long-term hydrologic impact assessment (L-THIA) model. The results show that the non-point source pollution load changed significantly both in terms of magnitude and spatial distribution. The loads of chemical oxygen demand, total suspended substances, total nitrogen and total phosphorus were affected by the interactions between event mean concentration and the magnitude of changes in land-use acreages and the spatial distribution. From 1988 to 2014, the loads of chemical oxygen demand, suspended substances and total phosphorus showed clearly increasing trends with rates of 132.48 %, 32.52 % and 38.76 %, respectively, while the load of total nitrogen decreased by 71.52 %. The immigrant population ratio was selected as an indicator to represent the level of rapid urbanization and industrialization in the study area, and a comparison analysis of the indicator with the four non-point source loads demonstrated that the chemical oxygen demand, total phosphorus and total nitrogen loads are linearly related to the immigrant population ratio. The results provide useful information for environmental improvement and city management in the study area.

Correction: Ryu, J., et al. Development of a Watershed-Scale Long-Term Hydrologic Impact Assessment Model with the Asymptotic Curve Number Regression Equation. Water 2016, 8, 153

The authors wish to make the following corrections to this paper [1]: The author name “Bernard A. Engle” should be “Bernard A. Engel”[...]

Development of Field Pollutant Load Estimation Module and Linkage of QUAL2E with Watershed-Scale L-THIA ACN Model

The Long Term Hydrologic Impact Assessment (L-THIA) model was previously improved by incorporating direct runoff lag time and baseflow. However, the improved model, called the L-THIA asymptotic curve number (ACN) model cannot simulate pollutant loads from a watershed or instream water quality. In this study, a module for calculating pollutant loads from fields and through stream networks was developed, and the L-THIA ACN model was combined with the QUAL2E model (The enhanced stream water quality model) to predict instream water quality at a watershed scale. The new model (L-THIA ACN-WQ) was applied to two watersheds within the Korean total maximum daily loads management system. To evaluate the model, simulated results of total nitrogen (TN) and total phosphorus (TP) were compared with observed water quality data collected at eight-day intervals. Between simulated and observed data for TN pollutant loads in Dalcheon A watershed, the R2 and Nash–Sutcliffe efficiency (NSE) were 0.81 and 0.79, respectively, and those for TP were 0.79 and 0.78, respectively. In the Pyungchang A watershed, the R2 and NSE were 0.66 and 0.64, respectively, for TN and both statistics were 0.66 for TP, indicating that model performed satisfactorily for both watersheds. Thus, the L-THIA ACN-WQ model can accurately simulate streamflow, instream pollutant loads, and water quality.

Development of a Watershed-Scale Long-Term Hydrologic Impact Assessment Model with the Asymptotic Curve Number Regression Equation

In this study, 52 asymptotic Curve Number (CN) regression equations were developed for combinations of representative land covers and hydrologic soil groups. In addition, to overcome the limitations of the original Long-term Hydrologic Impact Assessment (L-THIA) model when it is applied to larger watersheds, a watershed-scale L-THIA Asymptotic CN (ACN) regression equation model (watershed-scale L-THIA ACN model) was developed by integrating the asymptotic CN regressions and various modules for direct runoff/baseflow/channel routing. The watershed-scale L-THIA ACN model was applied to four watersheds in South Korea to evaluate the accuracy of its streamflow prediction. The coefficient of determination (R2) and Nash–Sutcliffe Efficiency (NSE) values for observed versus simulated streamflows over intervals of eight days were greater than 0.6 for all four of the watersheds. The watershed-scale L-THIA ACN model, including the asymptotic CN regression equation method, can simulate long-term streamflow sufficiently well with the ten parameters that have been added for the characterization of streamflow.

Retrofitting LID Practices into Existing Neighborhoods: Is It Worth It?

Low-impact development (LID) practices are gaining popularity as an approach to manage stormwater close to the source. LID practices reduce infrastructure requirements and help maintain hydrologic processes similar to predevelopment conditions. Studies have shown LID practices to be effective in reducing runoff and improving water quality. However, little has been done to aid decision makers in selecting the most effective practices for their needs and budgets. The long-term hydrologic impact assessment LID model was applied to four neighborhoods in Lafayette, Indiana using readily available data sources to compare LID practices by analyzing runoff volumes, implementation cost, and the approximate period needed to achieve payback on the investment. Depending on the LID practice and adoption level, 10-70% reductions in runoff volumes could be achieved. The cost per cubic meter of runoff reduction was highly variable depending on the LID practice and the land use to which it was applied, ranging from around $3 to almost $600. In some cases the savings from reduced runoff volumes paid back the LID practice cost with interest in less than 3 years, while in other cases it was not possible to generate a payback. Decision makers need this information to establish realistic goals and make informed decisions regarding LID practices before moving into detailed designs, thereby saving time and resources.

Modeling the impacts of urbanization on lake water level using L-THIA

Land use change can have substantial impacts on hydrology and the environment. The long-term hydrologic impact assessment (L-THIA) model was used to quantify the impacts that urbanization has on Lake Maxinkuckee in northern Indiana. Three land use datasets (for the years 1951, 1972, and 1997) were utilized to generate four scenarios, which were used to simulate water level in the lake from 1957-01-01 to 1997-12-31. The model was calibrated to daily lake levels from 1957-01-01 to 1974-12-31 and validated with data from 1975-01-01 to 1997-12-31, with daily R2 and Nash–Sutcliffe (NSE) coefficient values of 0.61 and 0.51, and 0.44 and 0.32, respectively. Simulation results showed the daily lake level gage heights, simulated with the 1951 land use (i.e. the base case), varied between 0.69m and 1.56m with an average of 0.97m with the 1951 land use. Scenario comparison revealed that long-term average and maximum lake level increased slightly with urbanization, due to increase in runoff over the study period. Land use change (defined in this study as urban development) can affect lake level, and should be considered in planning of residential development and recreational areas.

Assessing the long-term impact of urbanization on run-off using a remote-sensing-supported hydrological model

Land use/land cover (LULC) change in Dongguan, a city belonging to the Pearl River Delta metropolitan area, and its impact on the run-off of this city since the rapid urbanization period starting in 1979 are analysed in this article. Historic remote-sensing imagery (acquired in 1979, 1989, 2000, 2006, and 2013) was processed by the Support Vector Machine (SVM) method to obtain LULC data, and a long-term hydrologic impact assessment (L-THIA) model was applied to evaluate the long-term effects of LULC changes on surface run-off. The results show the urbanized area in Dongguan has increased more than 52% from 1979 to 2013 and the percentages of annual surface run-off depth and annual surface run-off coefficient are 58% and 5.83%, respectively. The increase in annual surface run-off is related to urbanization, and the centre area of the city has experienced the largest increase in annual surface run-off. The 32 towns’ local indicators of spatial association show centre towns are hot spots of increases in annual surface run-off in Dongguan city.