SCS Curve Number Research Articles

Evaluation of hydrological and erosive effects at the basin scale in relation to the severity of forest fires

This study aimed to assess the hydrological and erosive effects of different levels of the fire severity in the drainage basin of the Trionto River (Calabria, southern Italy), which was partially burned by intense fires during the summer 2017. The analysis focused on the identification of wildfire areas using a supervised classification of remote sensing images with the minimum distance algorithm. The level of severity of each fire was then discriminated based on a procedure proposed by the U.S. Department of Agriculture and adapted to the study area. To evaluate how wildfire occurrence affects the hydrological behaviour at the basin scale, the SCS-Curve Number model was used to document pre- and post-fire conditions in relation with the level of fire severity. Finally, the influence on erosion was analysed for analogous conditions at the basin scale using the RUSLE equation. The effects on hydrological balance and soil loss were evaluated by comparing the pre-fire value with three different post-fire scenarios: (a) different levels of severity on the surface covered by the fire (real case); (b) maximum level of severity on the surface covered by the fire; (c) total loss of the canopy and formation of a hydrophobic layer on the surface soil. The results confirmed that the level of severity of the forest fires, combined with climatic factors, morphological conditions, and the pedological characteristics of the basin, significantly influence changes to the hydrology and rates of erosion. Moreover, these impacts proved to be mainly dependent on the consequent, often notable, heterogeneity in the spatial distribution of burned areas with different severity.

Simulation of extreme event-based rainfall–runoff process of an urban catchment area using HEC-HMS

Flood is ranked as the deadliest natural disaster that has been experienced by the urban basins in the world. Its detrimental effects can be minimized by appropriate modeling, analysis and management methods. Such modeling and analysis techniques help in flood risk assessment predicting flood occurrence, aid in the emergency preparation for evacuation and reduce damage from the impact of floods. Numerous modeling techniques are available for analyzing flood events, of which HEC-HMS software is chosen for this explorative study because of its simplicity and as it is a freely available open-source software. The present study aims to develop a rainfall–runoff simulation model by generating peak flow and volume of the extreme rainfall event that occurred on 22 November 1999 in the ungauged Koraiyar basin located south of Tiruchirappalli City in South India. The hydrographs are generated for the basin by using specified hyetograph and frequency storm method to identify the best method to be adopted in the study. Digital elevation model processed with geographic information system (GIS) and HEC-Geo HMS, which is an extension of GIS, is used for the analysis. Using the terrain processing tools in ArcGIS, the basin delineation and parameters such as slope and river length are extracted from the basin. The data generated during the HEC-Geo HMS process are the hydrologic parameters of Koraiyar basin, and it is imported to HEC-HMS modeling for generating peak flow and volume. In the modeling process, HEC-HMS has three modules, namely transform, loss and base flow. SCS curve number and SCS unit hydrograph are used to determine the losses and transformation of rainfall into the runoff process in the present study. The SCS method is adopted because of its simplicity and requirement of limited data approach for modeling. The peak flow and volume prepared from the model are compared with the standard Nash–Sutcliffe values. The frequency storm method has a Nash value of 0.7, which is higher than the value obtained from the specified hyetograph process, and it is chosen as a better model for generating flood peak and volume for different return periods in the basin. It can therefore be adopted for other studies of similar basin conditions.

Estimation of Runoff Potential by the Application of Curve Number Method in GIS Platform

Estimation of direct runoff is essential for planning and development of watershed. In this study estimation of the same is carried out by applying Soil Conservation Service-Curve Number (SCS-CN) model technique with Geographic Information System (GIS) approach. The SCS-Curve Number model is a hydrological model which is widely used for estimation of runoff volume generated from the rainfall event. The said model mathematically describe the rainfall – runoff relationship and uses rainfall data and Curve Number (CN) as the inputs. The Curve Number is an empirical index depends on the soil complex, land use and hydrological condition of the area. The SCS-CN method with GIS approach has been adopted for predicting the runoff volume in the catchment of upper Mahanadi, which is upstream of the confluence of Mahanadi and Pairi River. The catchment area under consideration is 8086 sq.km. The study area climate condition is tropical monsoon type which receives the normal annual rainfall of 1360 mm. The maximum precipitation about 86% of the total precipitation, observed in the monsoon period from July to Mid of September. Survey of India (SOI) topographic sheets and Indian Remote Sensing satellite image LISS-III were used to prepare thematic maps of the study area. Thematic maps and hydrological data were used to generate Curve Number map and Hydrological Soil Group map. The SCS-CN method is very useful to compute runoff volume from the land, which quatify the direct drain to the river or streams. The outcome of this study is useful for watershed planning and development effectively for the study area.

Influence analysis of peak rate factor in the flood events’ calibration process using HEC–HMS

In flood management, analysis and modelling are needed, especially for the analysis of the occurrence of floods and decision making. One method for analyzing flood events can use the HEC–HMS software. In HEC–HMS, there are three sub-models, namely, losses, transform, and baseflow. In the development of the use of the HEC–HMS model, it still utilizes sub-model transform, where the peak rate factor (PRF) value is constant at 484 in modelling. The value of PRF is very dependent on the slope of the land (basin slope), where the value of this parameter is very varied depending on the physical condition of the area under study. Because of the fact, where the value of PRF should be varied depends on the slope in modelling stage; while the reality is still constant, this research is done. The research result shows that the role of PRF makes the modelling carried out using HEC–HMS produce comparable results as indicated by the objective function values in two study areas. The following is the comparison of the objective function of the Selorejo watershed in the March 2007 flood event between constant PRF 484 with variations in the values of PRF, RMSE (0.63 m; 0.59 m), CORREL (0.977; 0.976), and DELTAPEAK (43.04%; 41.46%). Whereas in the PDA Cipasang watershed, Nash–Sutcliffe (0.818; 0.820), RMSE (66.20 m3/s; 65.91 m3/s), CORREL (0.916; 0.917), and DELTAPEAK (15.55%; 15.35%). To utilize the variation of PRF into the model, based on the results of this study, the sub-model used is SCS Curve Number for Losses, SCS Units Hydrograph for Transform, and Recession Constant for Baseflow. It can be concluded that by including the influence of variations in PRF values resulting not a better model but only a slight improvement which is insignificant and a more complete model.

SCS Curve Number and Green-Ampt Infiltration Models

AbstractSoil Conservation Service curve number (SCS-CN) and Green-Ampt (GA) infiltration models are probably the most applied equations in practical hydrology to compute the amount of direct runoff...

A Generic Approach for Live Prediction of the Risk of Agricultural Field Runoff and Delivery to Watercourses: Linking Parsimonious Soil-Water-Connectivity Models With Live Weather Data Apis in Decision Tools

This paper describes the development and application of a novel and generic framework for parsimonious soil-water interaction models to predict the risk of agro-chemical runoff. The underpinning models represent two scales to predict runoff risk in fields and the delivery of mobilized pesticides to river channel networks. Parsimonious field and landscape scale runoff risk models were constructed using a number of pre-computed parameters in combination with live rainfall data. The precomputed parameters included spatially-distributed historical rainfall data to determine long term average soil water content and the sensitivity of land use and soil type combinations to runoff. These were combined with real-time live rainfall data, freely available through open data portals and APIs, to determine runoff risk using SCS Curve Numbers. The rainfall data was stored to provide antecedent, current and future rainfall inputs. For the landscape scale model, the delivery risk of mobilized pesticides to the river network included intrinsic landscape factors. The application of the framework is illustrated for two case studies at field and catchment scales, covering acid herbicide at field scale and metaldehyde at landscape scale. Web tools were developed and the outputs provide spatially and temporally explicit predictions of runoff and pesticide delivery risk at 1 km2 resolution. The model parsimony reflects the driving nature of rainfall and soil saturation for runoff risk and the critical influence of both surface and drain flow connectivity for the risk of mobilized pesticide being delivered to watercourses. The novelty of this research lies in the coupling of live spatially-distributed weather data with precomputed runoff and delivery risk parameters for crop and soil types and historical rainfall trends. The generic nature of the framework supports the ability to model the runoff and field-to-channel delivery risk associated with any in-field agricultural application assuming application rate data are available.

Simulating the impact of climate change on soil erosion in sub-tropical monsoon dominated watershed based on RUSLE, SCS runoff and MIROC5 climatic model

Climate change due to precipitation is one of the important dominant variables that determine the trend of soil loss in future period. In the present study the MIROC5 model of RCP 2.6, 4.5, 6.0 and 8.5 scenarios have been used to estimate the future period precipitation in storm rainfall event. Statistical downscaling approaches have been applied to estimate the precipitation for the time period of 1900 to 2010 and 2070 to 2100. Then the rainfall and runoff erosivity (R) factor has been estimated from the predicted precipitation scenario with the help of Modified Fourier Index from 2070 to 2100 in different return period such as 5 year, 10 year and 15 year return period. SRTM (Shuttle Radar Topographic Mission) DEM (Digital Elevation Model) and Landsat 8 OLI (Operational Land Imager) have been used to prepare the necessary thematic inputs for RUSLE (Revised Universal Soil Loss Equation) model in GIS environment. In this study the information regarding the soil characteristics have been accounted based on the primary information. In the present study, 2 sq km * 2 sq km grids of the entire basin have been taken into consideration randomly for collecting the soil samples within this region. Then the soil texture has been estimated and identified through the automatic sieve shaker in laboratory. Despite the soil texture, the soil pH and organic matter have also been estimated in the laboratory for estimating the soil erodibility factor (Kfactor) more accurately. Slope length and steepness factor (LS) have been estimated from the SRTM DEM in GIS environment. NDVI (Normalized Difference Vegetation Index) was derived from the Landsat 8 OLI data for estimating the cover and management factor (C), support practice factor (P) related to slope direction has been estimated based on the primary observation during the field visit. Apart from that the SCS curve number values and the weighted curve number values for each and every individual LULC classes have been derived to estimate the R factor. It was revealed that the average annual soil loss in the severe region (very high) in the base year is 12.6% and it would be 25.12% (5 year return period), 26.48% (10 year return period), 27.59% (15 year return period) in RCP 2.6 scenario. The average annual soil loss in this region would be28.53% (5 year return period), 30.00% (10 year return period), 30.97% (15 year return period) in RCP 4.5 scenario. The amount of soil in the severe region would be 32.19% (5 year return period), 33.48% (10 year return period), 34.05% (15 year return period) in RCP 6.0 scenario. In the RCP 8.5 scenario the average annual soil loss would be32.78% (5 year return period), 32.97% (10 year return period), 33.28% (15 year return period). This type of study is more helpful for the decision makers and regional planner for adopting the suitable measures with keeping in the view the local environment.

Development of a new method for estimating SCS curve number using TOPMODEL concept of wetness index (case study: Kasilian and Jong watersheds, Iran)

In recent years, several empirical and mathematical methods have been developed to estimate runoff, among which the SCS curve number (SCS-CN) method is one of the simplest and most widely used methods. The SCS-CN depends mainly on a CN parameter which corresponds to various soil, land cover, and land management conditions, selected from look-up tables. An application of GIS and RS techniques along with filed investigations made it possible to enhance the method from a lumped one to the level of semi-distributed models in which a specific value can be assigned to each cell in raster maps. The up-to-date procedures require several datasets, field measurements and overlying issues which limits the use of SCS-CN in data-scarce regions. In this research a new method has been developed which estimates the SCS-CN over the catchment with a minimum input dataset and acceptable accuracy and is based on the saturation-excess concept, which is used in the semi-distributed model: TOPMODEL. The proposed method depends on three parameters, including ndrain (soil porosity), $${\bar{\text{z}}}$$ (average distance to watershed water table surface) and m (which controls the effective depth of the saturated soil) and one input dataset, the so-called topographic index. Results showed that the maximum and minimum differences between the basin-averaged CN based on the GIS and RS techniques and the proposed method for Kasilian and Jong watersheds are 12% and 0.3%, respectively. Also, the findings indicated that, of the three parameters of proposed method, the m parameter plays a key role and that by increasing this parameter the basin-averaged CN tends to decrease and vice versa. Because of the dependence on a topographic index, the proposed method is strongly affected by DEM resolution and there are significant differences between low and high-resolution DEMs. However, for a small scale watershed, similar to Kasilian, using DEMs with resolution lower than 100 m considerably decreases the above differences. As an overall conclusion, the proposed method provides acceptable values of SCS-CN which is important for running rainfall-runoff model in a data-limited or data-scarce regions. In addition, creating the gridded map for CN, which is required in most hydrological models, is one of the most important advantages of the proposed method.

Simulation of Rainfall Runoff Process Using HEC-HMS Model for Upper Godavari Basin Maharashtra, India

The Hydrologic Engineering Centers Hydrologic Modeling System (HEC-HMS) is a popularly used watershed model to simulate rainfall- runoff process. Hydrological modeling is a commonly used tool to estimate the basin’s hydrological response due to precipitation. It allows to predict the hydrologic response to various watershed management practices and to have a better understanding of the impacts of these practices. It is evident from the extensive review of the literature that the studies on comparative assessment of watershed models for hydrologic simulations are very much limited in developing countries including India. In this study, modified SCS Curve Number method is applied to determine loss model as a major component in rainfall-runoff modeling. The study of HEC-HMS model is used to simulate rainfallrunoff process in Nashik region (Upper Godavari basin), Maharashtra. To compute runoff volume, peak runoff rate, and flow routing methods SCS curve number, SCS unit hydrograph, Exponential recession and Muskingum routing methods are chosen, respectively. The results of the present study indicate that HEC-HMS tool applied to watershed proved to be useful in achieving the various objectives. The study confirmed a significant increase in runoff as a result of urbanization. It is a powerful tool for flood forecasting Index

Simulation of Rainfall Runoff Process Using HEC-HMS Model for Upper Godavari Basin Maharashtra, India

The Hydrologic Engineering Centers Hydrologic Modeling System (HEC-HMS) is a popularly used watershed model to simulate rainfall- runoff process. Hydrological modeling is a commonly used tool to estimate the basin’s hydrological response due to precipitation. It allows to predict the hydrologic response to various watershed management practices and to have a better understanding of the impacts of these practices. It is evident from the extensive review of the literature that the studies on comparative assessment of watershed models for hydrologic simulations are very much limited in developing countries including India. In this study, modified SCS Curve Number method is applied to determine loss model as a major component in rainfall-runoff modeling. The study of HEC-HMS model is used to simulate rainfallrunoff process in Nashik region (Upper Godavari basin), Maharashtra. To compute runoff volume, peak runoff rate, and flow routing methods SCS curve number, SCS unit hydrograph, Exponential recession and Muskingum routing methods are chosen, respectively. The results of the present study indicate that HEC-HMS tool applied to watershed proved to be useful in achieving the various objectives. The study confirmed a significant increase in runoff as a result of urbanization. It is a powerful tool for flood forecasting Index

Correlating soil and urban planning for sustainable water cycle

Abstract Hydrological modelling and processes using modern hydrological models like SCS Curve Number, HCS, HSPF (Hydrologic Simulation Package-Fortran) and kinematic wave models are widely used nowadays in various researches. But using these modelling in drawing the attention of urban planners for challenges and multiple interactions in heterogeneous urban catchments and water systems is still a shortcoming in water sensitive, planning principle. The art of urban planning and technical implementation using behavioural changes in water responses to urban catchments is the need of present urban planning. The complexities of effects and behavioural changes in the water system or urban catchments and incomplete knowledge of these interactions result in failures of sustainable urban developments. Urban planning needs water sensitive methodology to synchronize soil, water and land cover operational with the population over it. The paper reviews the water sensitive urban planning considering the role of soil in urban planning for water and lands correlations, with the purpose of identifying current limitations and opportunities for future urban planning. Data availability and simplified methods are still a strong limitation for urban planners. Therefore, urban hydrology is often simplified either as a study of surface runoff over impervious surfaces or hydraulics of piped systems. Hence the paper provides approach and universal solution to forecast the behaviour of urban catchment for urbanization in terms of natural land-water cycles and its application in planning existing or new urban catchments. The methodology consists of observing Urban watershed catchment areas with different soil groups and built-up induction over them. A detailed study of water levels in hydrological wells and runoff pattern for the period of 40 years have provided a linear correlation of soil, roughness, land cover, infiltration, ground water and built upon the basis of soil behaviours. These correlations conclude to make regression equations as the blueprint for future urban planning norms to be followed by the planners, engineers, and hydrologists for planning.

Estimating flow rate in gauged and ungauged stations in Kuantan river basin using Clark method in Hec-HMS

Hydrologic simulation that engages incomputer models is the cutting edge to boost the understanding and provide further reliable outcomes in estimating flow rate. US Army Corps of Engineers has taken an initiative to develop a stable and dependent model, HEC-HMS that can be used for many hydrological simulations. The value of parameter needed for the simulation basically depends on the method chosen for loss, transform and base flow. In this study, the model parameters are changed and the model calibration had been performed separately for the three selected methods, the Soil Conservation Service Curve Number (SCS CN) loss method, the Constant Monthly base flow and the Clark Unit Hydrograph for transform method, to determine the most suitable simulation and to obtain the highest peak discharge for every sub-basin of the Kuantan River. Every flow simulated undergoes the validation and calibration process, with the Nash-Sutcliffe index used as a criterion to compare the outcomes between observed and simulated hydrographs. At the end of the study, it can be concluded that SCS Curve Number, Constant Monthly and Clark Unit Hydrograph is the best method for loss, base flow and transform method consecutively in estimating the flow rate in Kuantan River Basin.

Rainfall-runoff estimation of Bojiang lake watershed using SCS-CN model coupled with GIS for watershed management

A proper understanding of watershed spatio-temporal hydrological characteristics is critical to the management of a watershed and its natural resources such as water and vegetation. Rainfall runoff estimation plays an important role as an integral part of watershed management. Runoff volume and distribution data provides valuable information for water management strategies such as selection of artificial water abstraction sites, water storage facilities, and soil erosion control strategies. In the present study Bojiang lake watershed was used to indicate the application of Soil Conservation Service Curve Number method (SCS-CN) coupled with Geographic Information System (GIS) and Remote Sensing (RS) techniques. The watershed falls within Erdos Larus Relictus National Nature Reserve (ELRNNR) which was listed under the wetlands of international importance in 2002. Rainfall runoff is influenced by a variety of factors within a watershed such as soil and land use/cover types, soil moisture content, rainfall, drainage density, and shape and size of the watershed. The SCS Curve number is the most popular and widely applied method for runoff estimation. GIS and Remote Sensing play an important role in estimating surface runoff by SCS-CN method. ArcGIS 10.2 software was used to overlay different thematic layers and develop an attribute table and calculate a weighted curve number. The weighted curve number was applied to the SCS-CN equations to estimate daily, monthly, and yearly runoff. Correlation coefficient (r) was used to test for the relationship between rainfall and runoff, and verify the computation of the method. The results show an average runoff of 17.78 mm which is about 7.18% of the annual average rainfall for the years 2001-2016. The derived output maps can assist in identifying suitable areas for water recharge/abstraction. The study demonstrates that SCS-CN in conjunction with GIS and RS can be used to calculate runoff for ungagged watersheds and assist in watershed management strategies.

Application of the LDN concept for quantification of the impact of land use and land cover changes on Mediterranean watersheds - Al Awali basin - Lebanon as a case study

Recognized by the United Nations Convention to Combat Desertification (UNCCD) as a global developmental and environmentally threatening process, land degradation (LD) is initiated by natural factors but aggravated by unsustainable anthropogenic activities and absence of proper management plans. Therefore, in response to the UN 2030 Agenda on Sustainable Development for restoring degraded lands, this research targets the impact of land use and land cover changes (LU/LC), under the UNCCD's Land Degradation Neutrality (LDN) concept, to identify the extent of LD, and to prospect the potential to counterbalance/neutralize ongoing degradation as a first approach to Lebanon, at the scale of the 301 Km2 Awali basin. By achieving this task, the proposed method will serve as a first step in building an inventory of LD and proposing measures to adapt or even overcome LD for applications in the Mediterranean basin's countries.The proposed sequential methodological approach consists of tracking detailed LU/LC changes from 1998 to 2016 using multitemporal satellite images. Generated maps are input to the Soil Conservation Service SCS-Curve Number (CN) method to determine surface runoff in complementarity to Pedological properties of the study area. Soil types are then classified under the USDA Land Capability Classification method to determine extent of degraded lands. Results intersected with LU/LC revealed the source and nature of mismanagement and the proposed counterbalancing steps.Two main findings result: the Awali watershed displays countable LU/LC changes translated in CN increases. Additionally, due to these changes, the basin displays a 36% LD that may continue to alarming rates if no intervention takes place. The proposed workflow combining existing methodologies enabled the application of the LDN concept to counterbalance losses by gains thus reducing degradation to 2% from alternative land planning, and near null from proposed soil corrective actions highlighting the importance of LDN usage.

Watershed Delineation and Estimation of Groundwater Recharge for Ras Gharib Region, Egypt

The present work tried to estimate the runoff discharge and groundwater recharge volumes for the catchments of Ras Gharib area using the Soil Conservation Service curve number (SCS-curve number) and the water balance methods. The two methods were selected among other methods used by hydrologists due to simplicity and popularity for application in arid and semi-arid areas like Egypt. The watershed delineation and streamlines for Ras Gharib region have been accomplished using ArcMap 10 GIS and the 1-arc second DEM which demonstrated three basins in the study area. The rainfall data points nearby the study area, extracted from the TRMM data, have been used as input for the Log-Pearson III distribution in order to calculate the design storm for different return periods (100, 50, 25, and 10 years). The results of applying the SCS model estimated the runoff depths as 19.86, 8.00, 2.32, and 0.06 mm for the different return periods, respectively. The total surface runoff volumes reached the study area are 34.78, 14.02, 4.07, and 0.11 Mm3, respectively for the selected return periods, whereas the total groundwater recharge volumes for the selected storm return periods are 58.16, 31.34, 18.14, 3.18 Mm3, respectively.

A new probability density function for spatial distribution of soil water storage capacity leads to the SCS curve number method

Abstract. Following the Budyko framework, the soil wetting ratio (the ratio between soil wetting and precipitation) as a function of the soil storage index (the ratio between soil wetting capacity and precipitation) is derived from the Soil Conservation Service Curve Number (SCS-CN) method and the variable infiltration capacity (VIC) type of model. For the SCS-CN method, the soil wetting ratio approaches 1 when the soil storage index approaches ∞, due to the limitation of the SCS-CN method in which the initial soil moisture condition is not explicitly represented. However, for the VIC type of model, the soil wetting ratio equals the soil storage index when the soil storage index is lower than a certain value, due to the finite upper bound of the generalized Pareto distribution function of storage capacity. In this paper, a new distribution function, supported on a semi-infinite interval x∈[0,∞), is proposed for describing the spatial distribution of storage capacity. From this new distribution function, an equation is derived for the relationship between the soil wetting ratio and the storage index. In the derived equation, the soil wetting ratio approaches 0 as the storage index approaches 0; when the storage index tends to infinity, the soil wetting ratio approaches a certain value (≤1) depending on the initial storage. Moreover, the derived equation leads to the exact SCS-CN method when initial water storage is 0. Therefore, the new distribution function for soil water storage capacity explains the SCS-CN method as a saturation excess runoff model and unifies the surface runoff modeling of the SCS-CN method and the VIC type of model.

Determination of Watershed Characteristics and Curve Number (CN) for Ponnaniyaru Dam Catchment Area

In SCS-CN method, curve number is significant parameter in estimating runoff from the catchment of the reservoir or inflow to the reservoir. As this curve number is function of several parameters like hydrological soil group, LULC, land treatment, hydrologic conditions and AMC, the selection of CN for prediction of inflow to the lake or reservoir is considered as a crucial in the hydrological studies. LULC, micro-watershed, drainage density, and catchment slope are obtained using spatial analysis and also SCS Curve Number value for Ponnaniyaru dam catchment area is derived from the LULC data. Further, CN value is evaluated from actual rainfall data and runoff volume collected at the reservoir. The study reveals the significant variation of CN value among each event. The present case study highlights the sensitiveness of CN value in the computation of runoff from the watershed. Keywords: Curve number, LULC, AMC, drainage density.

Estimation of SCS Curve Number variation following forest fires

ABSTRACTThe Soil Conservation Service Curve Number (CN) method is routinely used to estimate the effects of forest fires on hydrological response. However, despite recent efforts, CN values are still not well known for burned conditions. A major forest fire in Attica, Greece, which affected the Lykorrema stream experimental watershed, provided an opportunity for the estimation of post-fire CN variation using detailed pre-fire and post-fire rainfall–runoff datasets. The CN values for both periods were estimated and compared using a wide range of available methods. Methods considering the spatial variability of soil-cover complexes were also used to investigate the effect of spatial heterogeneity. The post-fire watershed response changed from complacent to standard. Direct runoff depths and peak flows increased by a factor of more than 7.7 and 11.8, respectively. On average, the estimated post-fire CN values for the studied soil-cover complexes increased by about 25 units. This study may assist the improvement of existing post-fire hydrological assessment tools.

ESTIMATION OF SURFACE RUNOFF FOR AL-MAHALAH CATCHMENT'S USING SCS CURVE NUMBER METHOD AND GEOGRAPHIC INFORMATION SYSTEM TOOLS

Natural resources and their sustainable management are key issues for the future development of national agricultural Strategy in Jordan. Similarly, vegetative cover, particularly rangelands, and its sustainable management are key concern in combating land degradation.
 The study area is located in the northern eastern area of Jordan and classified as Marginal area between with average annual rainfall less than 200mm. It suffers from land degradation due to overgrazing and mismanagement of vegetation cover, which has a substantial impact on the production system. Although it has a potential for water management.
 The main objective of this study is to estimate the runoff for Al-Mahalah watershed (using SCS Curve Number method) to construct an earth dam at suitable location in the watershed in order to harvest water for the benefit of local community and conserve soil.
 Data integration, analysis and processing for available and collected data were carried out in GIS environment. Runoff amounts were estimated at the watershed's outlet and the proposed location of an earth dam.
 The total amounts of runoff that could be derived from Al-Mahalah catchment's area at the catchment's outlet and an earth dam were estimated to be approximately 40000, 15000 m3, respectively.

A Modified LAPSUS Model to Enhance the Effective Rainfall Estimation by SCS-CN Method

In this study, LAPSUS model is modified to enhance the effective rainfall estimation by SCS curve number method. The LAPSUS model calculates discharge based on effective rainfall and routs it towards lower neighbouring grid cells following the multiple flow direction principle. Then, the sediment transport capacity and sediment transport rate are calculated in each grid cell. Finally, erosion or sedimentation is calculated by comparing the sediment transport rate with the sediment already in the transport of each grid cell. The amount of rainfall, curve number, convergence factor, discharge exponent, slope exponent, erodibility factor, and sedimentation ability factor are inputted to the application page of the modified model that was created in the C++ programming. The outputs of the model are runoff and erosion maps in ASCII format. Evaluating performance of the modified model showed a high accuracy of its results. The value of the coefficient of determination (R2) calculated 0.99 for runoff and 0.97 for erosion. The Nash-Sutcliffe efficiency was 0.96 for runoff and 0.97 for erosion. The value of the precision index calculated 0.81 for both runoff and erosion. Also, the nRMSE calculated 3% for both runoff and erosion. The result showed that the modified model capable to estimate the runoff and erosion on a landscape in a micro sub-catchment scale.