Long-Term Hydrologic Impact Assessment Model Research Articles

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.

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.

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.

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.

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.

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 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.

Long-term effects of land use/land cover change on surface runoff in urban areas of Beijing, China

The objective of this paper is to present a case study to derive land use/land cover (LULC) maps and investigate the long-term effects of LULC change on surface runoff in the fast urbanizing Beijing city. The LULC maps were derived from Landsat TM/ETM+ imagery (acquired in 1992, 1999, 2006, and 2009) using support vector machine method. A long-term hydrologic impact assessment model was applied to assess the impact of LULC change on surface runoff. Results indicated that the selected study area experienced rapid urbanization from 1992 to 2009. Because of urbanization, from 1992 to 2009, modeled runoff increased 30% for the whole area and 35% for the urban portion. Our results also indicated that the runoff increase was highly correlated with urban expansion. A strong relationship (R 2 =0.849 ) was observed between the impervious surface percent and the modeled runoff depth in the study area. In addition, a strong positive relationship was observed between runoff increase and percentage of urban areas (R 2 =0.997 for the whole area and R 2 =0.930 for the urban portion). This research can provide a simple method for policy makers to assess potential hydrological impacts of future urban planning and development activities.

L-THIA를 이용한 낙동강수계 임하댐유역 비점오염원의 공간적 분포해석

Long-Term Hydrologic Impact Assessment (L-THIA) model which is a distributed watershed model was applied to analyze the spatial distribution of surface runoff and nonpoint source pollutant loading from Imha watershed during 2001~2010. L-THIA CN Calibration Tool linked with SCE-UA was developed to calibrate surface runoff automatically. Calibration (2001~2005) and validation (2006~2010) of monthly surface runoff were represented as 'very good' model performance showing 0.91 for calibration and 0.89 for validation as Nash-Sutcliffe (NS) values. Average annual surface runoff from Imha watershed was 218.4 mm and Banbyun subwatershed was much more than other watersheds due to poor hydrologic condition. Average annual nonpoint source pollutant loading from Imha wateshed were 2,295 ton/year for <TEX>$BOD_5$</TEX>, 14,752 ton/year for SS, 358 ton/year for T-N, and 79 ton/year for T-P. Amount of pollutant loading and pollutant loading rates from Banbyun watershed were much higher than other watersheds. As results of analysis of loading rate from grid size (<TEX>$30m{\times}30m$</TEX>), most of high 10 % of loading rate were generated from upland. Therefore, major hot spot area to manage nonpoint source pollution in Imha watershed is the combination of upland and Banbyun subwatershed. L-THIA model is easy to use and prepare input file and useful tool to manage nonpoint source pollution at screening level.

Simulation and Validation of Non-point Source Nitrogen and Phosphorus Loads under Different Land Uses in Sihu Basin, Hubei Province, China

Abstract Many water quality models have been extensively used to evaluate non-point source pollution, such as SWMM (Storm Water Management Model), AnnAGNPS (Annualized Agricultural Non-point Source), HSPF (Hydrological Simulation Program– Fortran), SWAT (Soil and Water Assessment Tool) and so on. However, these models’ construction tended to be complex, only used well in the condition of many parameters and normative data can be obtained. There were much problem to use these models in tidal plain, where topography were flat, stream network were complex and controlled by many water conservancy systems. The L-THIA (Long-Term Hydrologic Impact Assessment) model can be used in the areas with uncompleted data, evaluate the effects of land use on non-point source pollution, because it only needs land use, soil types and some rainfall data. But the output results of L-THIA model are the annual average runoff volume and pollution load, which cannot be obtained easily in in-site observation. In this paper, one of typical tidal plain, Sihu basin in Hubei province of China, was studied. The annual average runoff volume and the non-point source nitrogen and phosphorus load of each grid (16m*16m) and the spatial distribution were estimated by L-THIA model. The average load of non-point source nitrogen and phosphorus at each exit of the units were calculated based on the suppose that the pollution load is inverse to the distance of water flow. Model validation was executed by comparing calculated results and observed water quality data for study area. The results demonstrated that there were highly significant linear correlation between the calculated average load of non-point source nitrogen and phosphorus and the measured concentrations of TP and TN (TN: R=0.828; TP: R=0.957). These suggested that the average load of non-point source nitrogen and phosphorus were reliable to evaluate non-point source pollution. Moreover, the simulation results illustrated that the non-point source nitrogen and phosphorus loads under different land uses were quite different. The impact of dry lands on the non-point source nitrogen and phosphorus was the highest; that of paddy fields and residential areas were secondary; and the impact of woodlands to non-point source nitrogen and phosphorus was the minimum.

Study on the Non-point Source Pollution in the Upper and Middle Reaches of the Taoer River Basin

Abstract The Taoer River basin is the epitome in the west of Northeast China and it is one of the most fragile and sensitive ecoregions. Thus, protection of water quality of the Taoer River is important. Not only point source pollution but non-point source (NPS) pollution results in deteriorating water quality. In this study, longterm hydrologic impact assessment model was used to evaluate the impacts of land use change impacts on NPS pollution, and the replacement cost method was used to calculate the economic loss caused by NPS pollution. Through analyzing the NPS pollutant loads of different land categories and the economic loss, the article puts forward that there exists a close relationship between landuse types and NPS pollution, and agricultural pollution is the main component of the NPS pollution in this area. The results of this study can provide decision-making basis for agricultural development and land-use change.

Development of genetic algorithm-based optimization module in WHAT system for hydrograph analysis and model application

Many hydrologic and water quality computer models have been developed and applied to assess hydrologic and water quality impacts of land use changes. These models are typically calibrated and validated prior to their application. The Long-Term Hydrologic Impact Assessment (L-THIA) model was applied to the Little Eagle Creek (LEC) watershed and compared with the filtered direct runoff using BFLOW and the Eckhardt digital filter (with a default BFI max value of 0.80 and filter parameter value of 0.98), both available in the Web GIS-based Hydrograph Analysis Tool, called WHAT. The R 2 value and the Nash–Sutcliffe coefficient values were 0.68 and 0.64 with BFLOW, and 0.66 and 0.63 with the Eckhardt digital filter. Although these results indicate that the L-THIA model estimates direct runoff reasonably well, the filtered direct runoff values using BFLOW and Eckhardt digital filter with the default BFI max and filter parameter values do not reflect hydrological and hydrogeological situations in the LEC watershed. Thus, a BFI max GA-Analyzer module (BFI max Genetic Algorithm-Analyzer module) was developed and integrated into the WHAT system for determination of the optimum BFI max parameter and filter parameter of the Eckhardt digital filter. With the automated recession curve analysis method and BFI max GA-Analyzer module of the WHAT system, the optimum BFI max value of 0.491 and filter parameter value of 0.987 were determined for the LEC watershed. The comparison of L-THIA estimates with filtered direct runoff using an optimized BFI max and filter parameter resulted in an R 2 value of 0.66 and the Nash–Sutcliffe coefficient value of 0.63. However, L-THIA estimates calibrated with the optimized BFI max and filter parameter increased by 33% and estimated NPS pollutant loadings increased by more than 20%. This indicates L-THIA model direct runoff estimates can be incorrect by 33% and NPS pollutant loading estimation by more than 20%, if the accuracy of the baseflow separation method is not validated for the study watershed prior to model comparison. This study shows the importance of baseflow separation in hydrologic and water quality modeling using the L-THIA model.

An investigation into the extent and impacts of hard surfacing of domestic gardens in an area of Leeds, United Kingdom

There is limited information available on the scale and potential impacts of increasing imperviousness in suburban areas, despite significant evidence which suggests that such changes could have severe consequences, particularly for urban flooding. In this investigation, aerial photographs from 1971 to 2004 were used to map changes in the impervious cover of a 1.16 km 2 suburban area of Leeds in northern England. A 13% increase in impervious surfaces was observed over the 33-year study period. Of the increase in impervious surfaces, 75% was due to paving of residential front gardens. To allow an assessment of annual runoff sensitivity to the increased imperviousness in the study area, an empirically based model, L-THIA (long-term hydrologic impact assessment model) was applied. The L-THIA hydrologic model predicts that average annual runoff increased by 12% over the period of study. The L-THIA model is also used to create a graph from which increases in annual runoff due to increased imperviousness can be predicted. These results show significant increases in imperviousness and suggest that this will cause an increase in the frequency and magnitude of flooding in the area.

Effects of calibration on L-THIA GIS runoff and pollutant estimation

Urbanization can result in alteration of a watershed's hydrologic response and water quality. To simulate hydrologic and water quality impacts of land use changes, the Long-Term Hydrologic Impact Assessment (L-THIA) system has been used. The L-THIA system estimates pollutant loading based on direct runoff quantity and land use based pollutant coefficients. The accurate estimation of direct runoff is important in assessing water quality impacts of land use changes. An automated program was developed to calibrate the L-THIA model using the millions of curve number (CN) combinations associated with land uses and hydrologic soil groups. L-THIA calibration for the Little Eagle Creek (LEC) watershed near Indianapolis, Indiana was performed using land use data for 1991 and daily rainfall data for six months of 1991 (January 1–June 30) to minimize errors associated with use of different temporal land use data and rainfall data. For the calibration period, the Nash–Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The calibrated CN values were used for validation of the model for the same year (July 1–December 31), and the Nash–Sutcliffe coefficient was 0.60 for estimated and observed direct runoff. The Nash–Sutcliffe coefficient was 0.52 for January 1, 1991 to December 31, 1991 using uncalibrated CN values. As shown in this study, the use of better input parameters for the L-THIA model can improve accuracy. The effects on direct runoff and pollutant estimation of the calibrated CN values in the L-THIA model were investigated for the LEC. Following calibration, the estimated average annual direct runoff for the LEC watershed increased by 34%, total nitrogen by 24%, total phosphorus by 22%, and total lead by 43%. This study demonstrates that the L-THIA model should be calibrated and validated prior to application in a particular watershed to more accurately assess the effects of land use changes on hydrology and water quality.

Reestablishing public health and land use planning to protect public water supplies.

This study measured the extent to which land use, design, and engineering practices could reduce contamination of major public water supplies. Key parcels of land were identified in New Jersey, and the potential uncontrolled loading of contaminants was estimated with the US Environmental Protection Agency's Long-Term Hydrologic Impact Assessment model for a variety of land use, design, and engineering scenarios. High-density per-acre development and engineering controls, along with housing and light commercial activity near main railroads, would substantially reduce runoff. In New Jersey, government and purveyor action is being taken as a result of, and in support of, these findings.

IMPACTS OF URBANIZATION ON SURFACE HYDROLOGY, LITTLE EAGLE CREEK, INDIANA, AND ANALYSIS OF LTHIA MODEL SENSITIVITY TO DATA RESOLUTION

Land-use change in urbanizing areas can significantly alter the hydrology of a watershed and can have serious impacts on wetland water balances, downstream flooding, and groundwater recharge. Most currently available models used in determining the hydrologic impacts of urbanization are not well suited to long-term hydrologic analysis or are too complex and data intensive for widespread practical application. The Long-Term Hydrologic Impact Assessment (LTHIA) model run on a Geographic Information System (GIS) is a relatively simple, user-friendly model that uses the Curve Number method to estimate changes in surface runoff between different stages of development. Application of the model to a large, rapidly urbanizing watershed near Indianapolis, Indiana, suggests that average annual runoff depths increased by more than 60% from 1973 to 1991, with even greater increases for some individual sub-basins. These results are consistent with runoff changes estimated from historical stream flow data in the watershed. A sensitivity analysis to determine minimum data requirements shows that a precipitation record length of 15 years or more is required to produce consistent results with LTHIA and that the highest possible resolution land-use and soils data should be used. The LTHIA model is now available on the Internet at http://www.ecn.purdue.edu/runoff. [Key words: hydrology, urbanization, modeling, GIS.]

Long-Term Hydrologic Impact of Urbanization: A Tale of Two Models

At a watershed scale, land-use change can increase runoff, flooding, and nonpoint source pollution and degrade downstream water bodies. Thus it is important to assess the potential hydrologic impacts of land-use change prior to watershed development. The L-THIA (Long-Term Hydrologic Impact Assessment) model is a tool to initially assess how land-use change affects annual average runoff and is based only on readily available data. Because L-THIA is relatively new, it is important to test it against other, well-accepted methods. The U.S. Environmental Protection Agency's SWMM (Storm Water Management Model), a well-known and widely used model, was used to perform runoff calculations for comparison with L-THIA. Applications of L-THIA and SWMM to two small watersheds in Chicago show that L-THIA predicts annual average runoff between 1.1 and 23.7% higher than SWMM. The agreement between the results is higher for larger watersheds. Both models predict a linear relationship between average annual runoff and increasing imperviousness. However, for a 10% increase in imperviousness, SWMM predicts an increase between 9.8 and 10.2% in annual average runoff, whereas L-THIA predicts an increase between 6.1 and 7.8%. Overall, L-THIA was easier and quicker to use than SWMM, because SWMM required time-consuming input data collection and formatting. Results of this and other analyses suggest that L-THIA can be an appropriate tool for initial assessment of the relative impacts of land-use change scenarios.