Watershed Parameters Research Articles

Ambient sediment quality conditions in Minnesota lakes, USA: Effects of watershed parameters and aquatic health implications

Surficial sediments were collected from 50 randomly selected Minnesota lakes, plus four a priori reference lakes, in 2007. The lakes encompassed broad geographic coverage of the state and included a variety of major land uses in the surrounding watersheds. Sediment samples were analyzed for a suite of metals, metalloids, persistent organic pollutants, total organic carbon, and particle size fractions. In addition, a small fish survey was conducted to assess PBDEs in both whole fish and fish tissues. Sediment quality in this set of lakes ranged from good (43%) to moderate (57%) based on an integrative measure of multiple contaminants. On an individual basis, some contaminants (e.g., arsenic, lead, DDD, and DDE) exceeded benchmark values in a small number of lakes that would be detrimental to benthic invertebrates. The sediments in two developed lakes tended to be more contaminated than sediments in lakes from other major watershed land uses. These differences were often statistically significant (p<0.05), particularly for lakes with developed versus cultivated land uses for arsenic, lead, zinc, and numerous PAH compounds. Multivariate statistical approaches were used on a subgroup of contaminants to show the two urban lakes, as well as a few northeastern Minnesota lakes, differed from the rest of the data set. Background threshold values were calculated for data with <80% nondetects. Source apportionment modeling of PAHs revealed that vehicle emissions and coal-related combustion were the most common sources. A general environmental forensic analysis of the PCDD/F data showed that ubiquitous combustion sources appeared to be important. BDE-209, a decaBDE, was detected in 84% of lake sediment samples, whereas fish at the top of the food chain (i.e., predator trophic group) had significantly higher (p<0.05) mean lipid-normalized concentrations of BDEs-47, 100, and 153 than lower trophic fish. These results will be used for future status and trends work.

Research in the calculation of the debris flow prevention and Geographic Information System control engineering

SummaryCurrently, it is very hard and low effective to collect watershed characteristic data when calculating debris flow to prevent and control it. This article identifies that the optimum resolution in the study area is 10 m in digital elevation model. And on the base of this, using the MATLAB digital software has implemented the relatively new “three‐direction algorithm” to fill the bottom land and has extinguished the phenomenon of river “parallel” in the traditional calculation. It is good at keeping the original terrain information and successfully builds up the hydrologically correct digital elevation model. Extracting the water network and related watershed parameters, after organic combination treatment, and combining with the feature of debris flow in the study area, a point of prevention and control project is set up at the upstream of Subao River. Using Geographic Information System technology, we have achieved to extracting the data of the debris flow valley area F, main gully length L, and the main gully bed average longitudinal shrinking slope J, automatically, rapidly, and accurately. In the MATLAB platform, we design an automatic algorithm to calculate the flood peak flow and debris flow peak flow in rainstorm. Combining with the practical situation of the study area, it can finally calculate the debris flow.

River runoff evaluation for ungauged watersheds by SWAP model. 2. Application of methods of physiographic similarity and spatial geostatistics

The efficiency of the methods of spatial proximity and geostatistics, as well as physico-geographic similarity, is studied as applied to the evaluation of the key model parameters of ungauged watersheds to be used in river runoff calculation by SWAP model. The target geographic objects were 323 experimental watersheds of MOPEX project. The quality of model parameter estimates and reproduction of river runoff hydrographs was analyzed in the case of the use of different similarity methods, and the order of decisions to be made was developed for the problem of river runoff calculation from an ungauged watershed for the entire area under study.

Morphometric Evaluation and Sub Basin Analysis in Hanur Watershed, Kollegal Taluk, Chamarajanagar District, Karnataka, India, using Remote Sensing and GIS Techniques

The study area covers 1026 sq km comprising of 15 sub-watersheds, namely Saggiyam (SB-1), Mudoldoddi (SB-2), Halgapuram (SB-3), Deverabetta (SB-4), Mattugaudanadoddi (SB-5), Handgalli (SB-6), Manchepura (SB-7), Lokkanahalli (SB-8), Chinchalli (SB-9), Prakash palya (SB-10), Naripura (SB-11), Adugulpodu (SB-12), Ramayanadoddi (SB-13), Jodukara hatti (SB-14), Depudisahibradoddi (SB-15) which range in area from 16.87 to 180.02 sq km. Different morphometric parameters were evaluated to understand the drainage characteristics. The drainage pattern of these sub basins have been delineated using Geocoded FCC bands 2, 3 and 4, of IRS 1C and 1D (LISS 111+ PAN merged) on 1:50,000 scale and Survey of India Toposheets as reference. The morphometric parameters are computed using Arc Info and Arc View GIS software’s. The drainage pattern of the study has shown dendritic to sub-dendritic drainage pattern with stream orders ranging from 4th to 5th order. The Drainage density ranges from 1.51 to 4.83 km/km 2 suggesting coarse to moderate drainage texture. The change in values of stream length ratio indicates their late youth stage of geomorphic development. The values of bifurcation ratio are ranging from 0.11 to 20.75 indicating that the study area is having strong structural control over the drainage pattern and all the sub basins fall under normal basin category. The values of form factor and circulatory ratio, suggest that the sub basins are elongated to circular in shape. Geographic Information System, when used with satellite images, could help in determining the morphometric parameters of watershed and river basins. It is concluded that remote sensing ground and GIS have been proved to be efficient tools in drainage delineation and updation.

A Quantitative Morphometric Analysis of Barhar River Watershed of Mahoba district, U.P., India using Remote Sensing and GIS

Objectives: The quantitative morphometric analysis is found to be vital study in understanding hydrological aspects and its interaction with the environment of any watershed system. The main objective of the study is to calculate the morphometric parameters of the Barhar river watershed. Methods/Statistical Analysis: The study area lies between 79° 32′ E to 79° 37′ E longitude and 25° 22′ N to 25° 30′ 30′′ N latitude covering an area of about 48.75 km2 belonging to Bundelkhand region. The drainage of the region has been prepared using Survey of India (SOI) toposheet (No.54O/11), Landsat TM and Digital Elevation Model (DEM) of the area. Remote Sensing (RS), Geographical Information System (GIS) and Global Positioning System (GPS) have been used in the study as efficient tools in our various modern geographical and geological studies. Findings: Barhar river watershed belonging to the northern part of Mahoba district is a hard rock terrain consisting mostly granite and granitoids. Rivers flowing in such terrains are mostly found to follow the fractures and lineaments. The watershed is of forth order drainage having drainage density and stream frequency of 2.281 and 2.481 respectively. The watershed shows elongated in nature. The method applied to the river basin gave a recent calculation of the morphometric parameters of the region. Application/Improvements: The drainage morphometric analysis is important in selection of water recharge sites, watershed modelling and groundwater prospect mapping. The study would provide an important information collection regarding future watershed prospects of the area.

Hydrological investigations in the semi-arid Makhawan watershed, using morphometry

In order to understand the hydrological behavior of a catchment area, morphometric analysis of the drainage basin plays an important role to expresses the geology, geomorphology and structural antecedents. In the present study, morphometric analysis and its influence on hydrology were carried out in Makhawan watershed, Central India, using SRTM, remote sensing and GIS. SRTM data were used for preparation of DEM, slope and aspect maps. DEM was used to delineate the watershed limits and to extract the channel network, which was later updated using IRS 1D LISS III data. The hydrological module in ArcGIS was used for calculation of watershed and morphometric parameters, under linear, relief and aerial aspects. The watershed shows dendritic-to-sub-dendritic drainage pattern; however, parallel-to-sub-parallel pattern developed locally which may be due to rejuvenation of streams in mature stage with moderate drainage texture. High drainage density in the watershed is observed over impermeable subsurface material, sparse vegetation with high relief; whereas, low drainage density is found over permeable subsurface material and low relief. It has been found that low relief with low drainage density areas are favorable sites for more groundwater prospects.

Climate change forecasting in a mountainous data scarce watershed using CMIP5 models under representative concentration pathways

Hydrology cycle of river basins and available water resources in arid and semi-arid regions are highly affected by climate changes. In recent years, the increment of temperature due to excessive increased emission of greenhouse gases has led to an abnormality in the climate system of the earth. The main objective of this study is to survey the future climate changes in one of the biggest mountainous watersheds in northeast of Iran (i.e., Kashafrood). In this research, by considering the precipitation and temperature as two important climatic parameters in watersheds, 14 models evolved in the general circulation models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. For the historical period of 1992–2005, four evaluation criteria including Nash–Sutcliffe (NS), percent of bias (PBIAS), coefficient of determination (R2) and the ratio of the root-mean-square-error to the standard deviation of measured data (RSR) were used to compare the simulated observed data for assessing goodness-of-fit of the models. In the primary results, four climate models namely GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM, and NorESM1-M were selected among the abovementioned 14 models due to their more prediction accuracies to the investigated evaluation criteria. Thereafter, climate changes of the future periods (near-century, 2006–2037; mid-century, 2037–2070; and late-century, 2070–2100) were investigated and compared by four representative concentration pathways (RCPs) of new emission scenarios of RCP2.6, RCP4.5, RCP6.0, and RCP8.5. In order to assess the trend of annual and seasonal changes of climatic components, Mann–Kendall non-parametric test (MK) was also employed. The results of Mann–Kendall test revealed that the precipitation has significant variable trends of both positive and negative alterations. Furthermore, the mean, maximum, and minimum temperature values had significant positive trends at 90, 99, and 99.9 % confidence level. On the other hand, in all parts of the Kashafrood Watershed (KW), the average temperature of watershed will be increased up to 0.56–3.3 °C and the mean precipitation will be decreased up to 10.7 % by the end of the twenty-first century comparing to the historical baselines. Also, in seasonal scale, the maximum and minimum precipitations will occur in spring and summer, respectively, and the mean temperature is higher than the historical baseline in all seasons. The maximum and minimum values of the mean temperature will occur in summer and winter, respectively, and the amount of seasonal precipitation in these seasons will be reduced.

Contamination Vulnerability Analysis of Watershed for Water Quality Monitoring

This research is an early step to determine the location of rain gauge station for artificial neural network modeling. The implementation of this model is very useful for water quality monitoring. The objectives of this study are: 1) to study the distribution of watershed parameter, that are average annual precipitation, land use and land-surface slope, 2) to conduct vulnerability analysis of watershed contamination, 3) to determine the location of rain gauge station. The study was performed by weighing and rating method of watershed parameters. The vulnerability degree of watershedtocontaminationispresentedasvulnerabilityindex.Thisindexisdeterminedbyoverallsumofallmultiplication between score and weigh number of each parameter. All data manipulation and data analysis were performed by using Geographic Information System (ArcView version by 3.2). The vulnerability of watershed contamination map had been generated using overlay operation of parameters. The results show that vulnerability index are varies between 10 up to 40 intervals. Hence, the indexes were categorized into three levels of watershed vulnerability, namely low (10 – 20), moderate (20 – 30) and high (30 – 40). It is found that the study area covered more by high vulnerability of watershed to contamination. The zoning of watershed vulnerability meant to determine the rain gauge location. There are three rain gauge stations on the area that they are in a high vulnerability level, whereas the other vulnerability level area has one rain gauge station. Each level of vulnerability area is able to represent the source of contaminant that it maybe influence the water quality of Gajahwong river.

Identifying Watershed, Landscape, and Engineering Design Factors that Influence the Biotic Condition of Restored Streams

Restored stream reaches at 79 sites across North Carolina were sampled for aquatic macroinvertebrates using a rapid bioassessment protocol. Morphological design parameters and geographic factors, including watershed and landscape parameters (e.g., valley slope, substrate), were also compiled for these streams. Principal component regression analyses revealed correlations between design and landscape variables with macroinvertebrate metrics. The correlations were strengthened by adding watershed variables. Ridge regression was used to find the best-fit model for predicting dominant taxa from the “pollution sensitive” orders of Ephemeroptera (mayflies), Plecoptera (stoneflies), and Trichoptera (caddisflies), or EPT taxa, resulting in coefficient weights that were most interpretable relative to site selection and design parameters. Results indicate that larger (wider) streams located in the mountains and foothills where there are steeper valleys, larger substrate, and undeveloped watersheds are expected to have higher numbers of dominant EPT taxa. In addition, EPT taxa numbers are positively correlated with accessible floodplain width and negatively correlated with width-to-depth ratio and sinuosity. This study indicates that both site selection and design should be carefully considered in order to maximize the resulting biotic condition and associated potential ecological uplift of the stream.

Can Rapid Assessments Predict the Biotic Condition of Restored Streams?

Five rapid visual stream assessment methods were applied to 65 restored streams in North Carolina, and the results were correlated with measured macroinvertebrate community metrics to evaluate predictive ability. The USEPA Rapid Bioassessment Protocol (RBP), USDA Stream Visual Assessment Protocol (SVAP), Peterson’s Riparian Channel and Environmental Inventory (RCE), NCSU Eco-Geomorphological Assessment (EGA), and NCSU Stream Performance Assessment (SPA) were applied by teams with expertise in hydrology, fluvial geomorphology, and aquatic ecology. Predictions of most macroinvertebrate metrics were improved by re-weighting assessment variables using principal component analysis (PCA) and including watershed factors (e.g., size, slope, land use). The correlations of EGA, RCE, SPA and SVAP assessment results to macroinvertebrate metrics were most improved by variable re-weighting using PCA, while the correlations of RBP were most improved by adding watershed parameters. Akaike’s Information Criterion (AIC) indicates that PCA re-weighting including watershed parameters improves the predictor model for the total number of dominant EPT taxa more than using the sum total raw points for all five assessment methods. To demonstrate the application of the study results, a single-value index was generated for the RBP method using principal component regression (PCR) based on the EPT (Ephemeroptera, Plecoptera and Trichoptera) taxa metric.

Unravel biophysical factors on river water quality response in Chilean Central-Southern watersheds.

Identifying the key anthropogenic (land uses) and natural (topography and climate) biophysical drivers affecting river water quality is essential for efficient management of water resources. We tested the hypothesis that water quality can be predicted by different biophysical factors. Multivariate statistics based on a geographical information system (GIS) were used to explore the influence of factors (i.e., precipitation, topography, and land uses) on water quality (i.e., nitrate (NO 3 (-)), phosphate (PO 4 (3-)), silicate (Si(OH)4), dissolved oxygen (DO), suspended solids (TSS), biological oxygen demand (DO), temperature (T), conductivity (EC), and pH) for two consecutive years in the Itata and Biobío river watersheds, Central Chile (36° 00' and 38° 30'). The results showed that (NO 3 (-)), (PO 4 (3-)), Si(OH)4, TSS, EC, and DO were higher during rainy season (austral fall, winter, and spring), whereas BOD and temperature were higher during dry season. The spatial variation of these parameters in both watersheds was related to land use, topography (e.g., soil moisture, soil hydrological group, and erodability), and precipitation. Soil hydrological group and soil moisture were the strongest explanatory predictors for PO 4 (3-) , Si(OH)4 and EC in the river, followed by land use such as agriculture for NO 3 (-) and DO and silviculture for TSS and Si(OH)4. High-resolution water leaching and runoff maps allowed us to identify agriculture areas with major probability of water leaching and higher probability of runoff in silviculture areas. Moreover, redundancy analysis (RDA) revealed that land uses (agriculture and silviculture) explained in 60 % the river water quality variation. Our finding highlights the vulnerability of Chilean river waters to different biophysical drivers, rather than climate conditions alone, which is amplified by human-induced degradation.

Potential implications of pre-storm soil moisture on hydrological prediction

Numerous hydrological models with various complexities, strengths, and weaknesses are available. Despite technological development, the association of runoff accuracy with the underlying model's parameters in watersheds with limited data remains elusive. Evaluating the soil moisture impacts at the watershed scale is often a difficult task, but it can be vital to optimally managing water resources. Incorporating pre-storm soil moisture accounting (PSMA) procedures into hydrologic models affects the watershed response to generate runoff from storm rainfall. This study demonstrated the impact of pre-storm and post-storm soil moisture in order to circumvent major obstacles in accurate runoff estimation from watersheds employing the conventional curve number (CN) model. The proposed hydrological lumped model was tested on a data set (1,804 rainfall-runoff events) from 39 watersheds in South Korea. Its superior performance indicates that the reconciliation of pre- and post-storm conceptualization has the potential to be a solution for efficient hydrological predictions and to demonstrate the complex and dynamic nature of tractable hydrological processes. The statistically significant results reveal that the proposed model can more effectively predict runoff from watersheds in the study area than the conventional CN model and its previously proposed modifications.

Analysis and Evaluation of Flash Flood Disasters: A Case of Lingbao County of Henan Province in China

Disasters caused by flash floods with casualties have occurred frequently in China in recent years. In order to effectively prevent and control them, the government initiated the project of building up a comprehensive non-structural measure system in 103 pilot counties from 2009. Based on the pilot experience, this project involved 2058 counties of 29 provinces and Xinjiang Production and Construction Corp from 2013. Analysis and evaluation of flash flood disaster is an important element task of this project. According to analyze the characteristics of rainstorm, basic parameters of the small watershed, social economy, the historical flood, etc. in the mountain areas possibly occur flash flood, this task aims to assess the flood control capacity of villages, towns and cities along the mountain rivers, declare the distribution of population and housings in the areas with different hazard grades, estimate the early-warning indexes such as rainfall and water level and their threshold values. The results can support and guide the warning system, forecasting, regional planning, land use and emergency response, and so on for flash flood disaster prevention. This paper will use a case of two small watersheds in Lingbao County of Henan Province to introduce the conceptual framework, methodology, process, key technology, rationality analysis and results of analysis and evaluation on flash flood disaster.

Simulation of Runoff and Sediment Yield for a Kaneri Watershed Using SWAT Model

Watershed as an entry point acts as a beginning to address the issues of sustainable rainwater management for improving livelihoods. Extraction of watershed parameters using Geographical Information System (GIS) and use of simulation models is the current trend for hydrologic evaluation of watersheds. In the present study, the open Source Tool Quantum GIS 2.2.0 was used for preparation of maps to verify the spatial extent of the area. The Soil and Water Assessment Tool (SWAT) having an interface with Arc-View GIS software (ArcGIS 10.1 with Arc SWAT 2012 extension) was selected for the estimation of runoff and sediment yield from Kaneri watershed, located in Western Maharashtra region. The coefficient of determination (R2) for the monthly and yearly runoff was obtained as 0.849 and 0.951 respectively for the calibration period 1979 to 2000 and 0.801 and 0.950 respectively for the validation period 2001-2013. The R2 value in estimating the monthly and yearly sediment yield during calibration period was computed as 0.722 and 0.788 respectively. The R2 for monthly and yearly sediment yield values for validation period was observed to be 0.565 and 0.684 respectively.

OPTIMIZATION OF RUNOFF PARAMETERS OF A WATERSHED BY GENETIC ALGORITHM AND VISUALIZING THE RUNOFF IN 4D GIS ENVIRONMENT

The Genetic Algorithm has been integrated with Finite Element Method (FEM) based distributed rainfall runoff model. It optimizes the four parameters i.e. saturated hydraulic conductivity, initial water content, suction head and saturated water content which generates the simulated runoff, which is then compared with the observed runoff data of actual site. The model has been applied to Harsul watershed located in Nashik district of Maharashtra, India. The objective function used in Genetic Algorithm is Nash-Sutcliffe Model Efficiency Constant objective function, and this combination produced good results. It performed well for many rainfall events except for those which have high rainfall intensity and low runoff. The Genetic Algorithm proved to be capable and robust in terms of maximising the objective function. Within 50 generations of 10 populations each, it has provided satisfactory results. GIS has been used to prepare all the thematic maps of the study area. The simulated runoff data generated from the model has been imported to GIS environment where it is visualized dynamically in 3D format with time series animation. The methodology developed in the present study can be used to simulate flow parameters of watershed.

Runoff Prediction in Ungauged Watersheds Using Remote Sensor Datasets

Runoff prediction in ungauged watersheds is regarded as one of the major issues in contemporary hydrology. This study examined the utility of remote sensor datasets for parameter regionalization. A distributed hydrologic model, the Coupled Routing and Excess Storage (CREST) model, was employed to simulate runoff conditions in the mountainous watersheds over South Korea. In gauged watersheds, the relationships between the optimized parameter set of the hydrologic model and the physiographic properties of the gauged watersheds were investigated using multiple linear regressions. The regression parameters for the ungauged watersheds were then validated and assessed. Results demonstrated that the hydrologic model and the proposed regression equations could acceptably simulate the discharge in both gauged and ungauged watersheds. However, they provided somewhat biased discharge for all the ungauged watersheds. In further studies, these biases should be reduced by investigating other watersheds and finding physiographic properties highly related to the model parameters. KeywordRunoff Prediction; Ungauged Watersheds; TRMM; Multi-satellite; Regionalization

Improved Methods of Parameterization for Estimating the Magnitude and Frequency of Peak Discharges in Rural Ungaged Streams

AbstractFor the past several decades, the United States Geological Survey (USGS) and others have been tasked with development of regional predictor equations to determine flood peaks in unregulated and ungaged rural locations. This study tests several new watershed parameters not commonly used in past studies that have been extracted from available geomorphologic and climatic data using both manual and programmatic methods with the goal of improving the predictive power of the regional equations. Parameters include a derived basin slope corresponding to surface flow direction, discrete travel time for each location in a watershed to the outlet, and development of a watershed subarea correlated with the location of the maximum length isochrone line within each watershed. A case study is presented that tests these parameters in the Valley and Ridge physiographic region of Virginia. Results indicate that the proposed parameters tend to reduce standard model error in predictor equations ranging between 0.97 a...

English

Biodiversity of aquatic insect and physicochemical water quality parameters in Mae Tao and Mae Ku watersheds were assessed bi-monthly from February 2011 to February 2012. A total of 59 families representing 9 orders were recorded. At order level, Trichoptera was found at the highest frequency in total abundance (45.75%) followed by Ephemeroptera (18.06%), Hemiptera (13.45%), Odonata (9.62%), Diptera (8.17%), Coleoptera (4.6%), Megaloptera (0.17%), Lepidoptera (0.11%) and Plecoptera (0.07%). The family Hydropsychidae was the most prominent and the most abundant aquatic insect taxa followed by Chironomidae. Water temperature, dissolved oxygen and ammonia-nitrogen were similar at all sampling stations. Significant variations in pH, electrical conductivity, total dissolved solids, sulfate, nitrate-nitrogen and alkalinity were found at all sampling stations. Taxa richness and diversity index significantly correlated with dissolved oxygen, sulfate, nitrate-nitrogen and ammonia-nitrogen (p<0.05, p<0.01). Physicochemical data and biological data showed that mostly the surface water quality in Mae Tao and Mae Ku watersheds were within Type III of The Surface Water Standard for Agriculture and Water Quality for Protection of Aquatic Resources in Thailand.

Organic carbon concentrations and transport in small mountain rivers, Panama

Tropical small mountainous rivers (SMRs) are increasingly recognized for their role in the global export of dissolved organic carbon (DOC) to the oceans. Here we utilize the Isthmus of Panama as an ideal place to provide first-order estimates of DOC yields across a wide assemblage of bedrock lithologies and land cover practices. Samples for dissolved organic carbon (DOC) analysis were collected across Panama along an E–W transect from the central Panama area to the Costa Rican border for 24 mainstem rivers, 3 large tributary rivers, and one headwater stream. Sampling occurred during both the wet and the dry seasons. DOC concentrations during the wet season are higher than during the dry season in all but three of the rivers. Concentrations vary greatly from river to river and from season to season, with values as low as 0.64mgl−1 to greater than >25mgl−1 with the highest concentrations observed for the rivers draining Tertiary marine sedimentary rocks in the Burica and Azuero peninsulas. DOC yields from Panamanian rivers (2.29–7.97tons/km2/y) are similar to or slightly lower than those determined for other tropical SMR systems. Areas underlain by Tertiary aged sediments exhibited significantly higher mean DOC yields compared to their igneous counterparts, despite maintaining substantially lower aboveground carbon densities, suggesting the important influence of lithology. Finally, regression analyses between DOC yields and select watershed parameters revealed a negative and statistically significant relationship with maximum and mean gradient suggesting lower soil retention times may be linked to lower DOC yields.

Modified SCS-CN and Green-Ampt Methods in Surface Runoff Modelling for the Kundahpallam Watershed, Nilgiris, Western Ghats, India

Kundapallam watershed is located in Nilgiris District of south India. This ungauged watershed has an areal extension of 14.37 km2. There are increasing numbers of rainfall induced landslide occurrences in this area. The causes of rainfall induced landslides require a thorough understanding of runoff characteristics of the watershed. In this respect, the runoff of the study area is estimated with two approaches such as modified Soil Conservation Curve Number (SCS-CN) and Green-Ampt loss method. By these approaches, the related thematic factors on runoff characteristics are prepared with satellite images by using ARCGIS and IDRISI image processing software. The catchment delineation is generated for the Kundapallam watershed to get watershed parameters by using HEC-GeoHMS extension in ARCGIS. Curve number is assigned based on Soil Wetness Index (SWI). Sixteen soil samples were collected from different localities for the determination of hydraulic conductivity, moisture content, wetting front capillary pressure, bulk density, porosity etc. The infiltration rate of sample locations is determined by using double ring infiltrometer. Then all the parameters are assigned to models applied in this study to determine runoff characteristics of the study area. The accuracy and goodness of fit of the model are tested by determining the correlation coefficient (SCS-CN = 0.979 and Green-Ampt = 0.985) and coefficient determination (SCS-CN = 0.958 and Green-Ampt = 0.97) and it indicates statically positive correlations and perfect fit between the results of the study. The results showed that the modified SCS-CN provides low runoff estimation compared than Green-Ampt loss method.