Natural Resources Conservation Service Curve Number Research Articles

The significance of basin slope for curve number estimation and the impact on flood prediction in arid basins

The Natural Resources Conservation Service (NRCS) method was developed in agricultural basins with slopes less than or equal to 5%. Extension of the method to arid regions and at higher slopes is needed. This research aims to investigate the relationship between the basin slope and runoff depth in arid basins by using the Natural Resources Conservation Service Curve Number (NRCS-CN). The results show that there is a clear effect of the proposed curve number equation with slope (the slope adjusted CN, CNIIα ) on the runoff depth in the studied basins, and this is consistent with the literature. However, large basin areas with a high percentage of alluvium area, vegetation, and high infiltration rates countereffects the slope of the basin, and consequently, the basin slope will not have a significant effect on runoff. The correlation coefficient of various developed equations varies between (0.89-0.93) and the root mean square error of runoff depth varies between 11 mm for λ=0.2 and 5.2 mm for λ=0.01.

Estimation of Equivalent Rainfall for Ungauged Reservoir Using Satellite-Based High-Resolution Terrain Data

Equivalent rainfall refers to the amount of precipitation required to reach a specific water level from the current water level in a reservoir. It serves as a flood forecasting and warning system that allows for the rapid assessment of the reservoir’s maximum water level at the moment of rainfall forecast. In reservoirs where terrain and survey data can be obtained, deriving equivalent rainfall is not difficult. However, without terrain data, satellite imagery and global topographic data are the only available options. In this study, high-resolution topographic data based on satellites were utilized to estimate the equivalent rainfall in the ungauged reservoir, Hwanggang Dam, located in the upper stream of the Imjin River in North Korea. To calculate the inflow into the reservoir, the Natural Resources Conservation Service-Curve Number method was used to determine the effective rainfall, taking into account the antecedent conditions, as the inflow into the reservoir can be changed for the same amount of rainfall depending on the soil moisture content of the watershed.

GIS based NRCS-CN modeling of rainfall-runoff in river Thamirabarani sub-basin, Southern India

River Thamirabarani sub-basin lies in the southern part of the Western Ghats in the Kanyakumari district of Tamil Nadu, India. The basin’s landforms are formed by swift surficial characteristics with undulated terrains composed of steep-sloped valleys, valley fills, and short-length streams with intensive flows that makes-up site-specific hydro-morphological characteristics. In this study, the GIS-based Natural Resource Conservation Service-Curve Number (NRCS-CN) model is used to assess rainfall-induced runoff by analyzing various hydrological parameters. The curve number (CN) is assigned to each hydrologic soil group (HSGs) based on the measurement of initial abstraction (Ia) and potential maximum retention (S) derived from soils, landuse/ land cover, antecedent soil moisture, etc. The resulting map shows the estimated runoff at the rate of 2.27 – 5.94 mm/m2/yr for the whole study area, whereas the higher runoff rate (4.83 – 5.94 mm/m2/yr) is noted in the upland range of the swift surficial terrains in the north and north-eastern parts that encompasses undulated structural hills, steep-sloped valleys, inselberg, and denudational hills, etc., whereas the work of swift surficial terrains and associated slope gradient of the landforms are considered to be higher runoff rate than the other parts. The moderate runoff rate (2.92 – 3.98 mm/m2/yr) is estimated in the middle parts of pediplains that consist of croplands, plantations, riverbanks, fallows, and built-up areas. Significantly, the lower runoff rate (<2.92 mm/m2/yr) sparsely occurred in the different landforms of the middle and southern parts that include pediplains, riverbanks, natural vegetative covers, valley-filled sediment deposits, etc. Overall results indicate that the higher runoff found over the swift surficial landforms in the north and north-eastern parts due to intensive flow through short-length stream orders. This study is mainly used for understanding hydro-morphological processes and their impacts on basin environments.

Determination of Runoff Curve Numbers for the Growing Season Based on the Rainfall–Runoff Relationship from Small Watersheds in the Middle Mountainous Area of Romania

The NRCS-CN (Natural Resources Conservation Service curve number) method, developed by the USDA (U.S. Department of Agriculture) is among the most widely used for the estimation of surface runoff from watersheds. Ever since its introduction in the 1950s, although it has been used to a great extent by engineers and hydrologists, the applicability of the original procedure used to determine its main parameter, the curve number (CN), to various regions with diverse environmental conditions, is still subject to many uncertainties and debates. This study presents a comparative analysis of different methods applied to determine curve numbers from local data in four watersheds located in the central part of Romania, within the mountain region surrounding the Brașov Depression. The CN values were not only computed using rainfall–runoff records from 1991 to 2020, but also determined from the standard NRCS tables documented in the National Engineering Handbook part 630 (NEH-630), for comparison purposes. Thus, a total of 187 rainfall–runoff data records from the study watersheds and five different methods were used to assess the accuracy of various procedures for determining the CN values, namely: tabulated CN (CN values selected from NRCS tables, TAB), asymptotic fitting (AF) of both natural and ordered data, median CN (MD), geometric mean CN (GM) and the arithmetic mean CN (AM) methods. The applicability of the aforementioned methods was investigated both for the original fixed initial abstraction ratio λ = 0.2 and its adjustment to λ = 0.05. Relatively similar results were found for the curve number-based runoff estimates related to the field data analysis methods, yet slightly better when the λ was reduced to 0.05. A high overall performance in estimating surface runoff was achieved by most CN-based methods, with the exception of the asymptotic fitting of natural data and the tabulated CN method, with the latter yielding the lowest results in the study area.

A modified NRCS-CN method for eliminating abrupt runoff changes induced by the categorical antecedent moisture conditions

The popular Natural Resources Conservation Service Curve Number (NRCS-CN) (earlier known as Soil Conservation Service Curve Number (SCS-CN) method of rainfall-runoff modeling has often faced the criticism of exhibiting quantum jumps in runoff computations because of the sudden jumps appearing in CN-values derived from NEH-4 tables for three antecedent moisture conditions (AMC), viz., AMC-I, AMC-II, and AMC-III valid for dry, normal, and wet conditions, respectively. The variability of antecedent soil moisture within an AMC category is responsible for the abrupt jump and other deficiencies in the CN method for runoff estimation. This paper suggests a novel procedure to account for the antecedent moisture (M), preventing quantum jumps and eliminating deficiencies in determination of CN and, in turn, estimation of direct runoff. Its validity was verified utilizing the observed rainfall (P)-runoff (Q) events from 36 US watersheds, four sub-catchments of the Godavari basin, and small agricultural plots at Roorkee, India. The performance of the proposed model (M5) for runoff prediction was compared with the existing NRCS-CN (M1), Mishra and Singh (2002) (M2), Singh et al. (2015) (M3), and Verma et al. (2021) (M4) model using various performance indices. Using the CNs derived from observed events, model M5 was seen to have performed better than M1-M4 in terms of Nash Sutcliffe Efficiency (NSE), Root Mean Square Error (RMSE), and Percent Bias (PBIAS) for the data of US watersheds, and CN-P correlation improved as the coefficient of determination (R2) enhanced. Similarly, using the RS & GIS-based CNs on natural watersheds of the Godavari basin and considering AMC-I, the performance of M5 was again better than M1-M4 in terms of RMSE, Mean Bias Error (mBIAS), Mean Absolute Error (MAE), and Normalized-Nash Sutcliffe Efficiency (NNSE). Interestingly, there existed a significant (p < 0.05) relationship between the in-situ water content (w) measured for the experimental plots of Roorkee and the model input variable antecedent moisture (M), offering a physical touch to the conceptual model.

Can slope adjusted Curve Number models compensate runoff underestimation in steep watersheds?: A study over experimental plots in India

The Natural Resources Conservation Service - Curve Number (NRCS-CN) model was originally developed to simulate runoff from a given storm on small agricultural watersheds having mild terrain slope (≤5%), but it has been applied in diverse field conditions and even much beyond its intended scope. The use of published CN table without slope adjustment and with a fixed initial abstraction ratio (λ = 0.2) has resulted in severe underestimation of runoff. In this study, the effect of slope on CN and λ was investigated using the measured rainfall-runoff data from small experimental plots in India. The investigation corroborated the requirement of a slope-adjusted CN equation suited for Indian hydro-climatic conditions, so three slope-adjusted CN models (CN2θ) having λ decaying with slope (θ) were proposed to improve the surface runoff prediction. The proposed models were calibrated and validated using 390 and 127 rainfall-runoff events, respectively, from 39 plots having different land-uses and slopes varying from 5% to 16%. The performance of new models was evaluated using Nash-Sutcliffe Efficiency (NSE), Coefficient of Determination (R2), Normalized Root Mean Square Error (nRMSE), Mean Bias Error (mBIAS), and 1:1 plot. The proposed models exhibited superior performance statistics to existing CN adjustment models for both λ = 0.2 and 0.03. Also, the use of proposed CN2θ significantly improved the values of NSE, R2, nRMSE, mBIAS and regression slope from −0.37, 0.33, 0.960, 10.72 mm and 0.335 to 0.53, 0.61, 0.562, −0.40 mm and 0.865, respectively, as compared to handbook CN values without any slope adjustment.

Effect of Hydrologic Soil Groups on Runoff Generation in Reservoir Catchments in Northern Ghana

The study was carried out in northern Ghana to estimate surface runoff in nine (9) reservoir catchments for a period of 20 years (1999–2018) using the United States Department of Agriculture Natural Resource Conservation Service-Curve Number (USDA-NRCS-CN) method. The key input parameters of the method were hydrologic soil group, antecedent moisture condition, rainfall amount, landuse/landcover, weighted curve number and potential maximum soil moisture retention. The annual rainfall within the reservoir catchments was found to vary between 617.2 and 1,382.3 mm. The estimated annual runoff depths ranged from 68.5 ± 7.5 to 98.0 ± 13.3 mm and the percentage annual rainfall converted into runoff varied between 9.8 ± 0.7 and 13.7 ± 0.9 %. Hydrologic soil groups accounted for about 67.2 % and 62.5 % of the variation in runoff depth and percentage runoff respectively, in the reservoir catchments. Catchment size accounted for only 2.7 % and 3.9 % of the variation in runoff depth and the percentage of the amount of rainfall converted into runoff respectively, in the reservoir catchments. Therefore, hydrologic soil groups should be used by reservoir managers as a primary indicator of the potential runoff generation in reservoir catchments.

Improving runoff estimation by raster‐based Natural Resources Conservation Service‐Curve Number adjustment for a new initial abstraction ratio in semi‐arid climates

AbstractThe Natural Resources Conservation Service Curve Number (NRCS‐CN) is a popular rainfall‐runoff modeling method. In this study the performance of the NRCS‐CN method in runoff estimation for single storms based on a new initial abstraction ratio ( in the semi‐arid climate of Khorasan Razavi, Iran, is presented. The method utilizes public domain Geographic Information Systems (GIS) software for the Geospatial analysis and generating the CN map of the study area. CN values provided in the standard Service Curve Number‐tables (CN0.2) were found to overestimate runoff potential compared to modified tables of CN0.05. Evaluation of the performance of CN0.05 for runoff estimation was undertaken using data collected in thirty‐five rainfall‐runoff events in the Kardeh watershed. A strong correlation (R = 0.97) was found between the observed and estimated direct runoff when CN0.05 was used for the runoff estimation as well as between the observed and estimated runoff based on Nash‐Sutcliffe efficiency (0.88). Overall, runoff predictions were improved with the revised NRCS‐CN method in semi‐arid climatic settings when is set to 0.05. We provide an easy‐to‐use relationship between CN0.2 and CN0.05 that improves Runoff estimation from NRCS‐CN.

Hydropower potential assessment using spatial technology and hydrological modelling in Nigeria river basin

This paper describes the procedure for an extensive survey of hydropower potential locations to be employed at the originating hydropower development planning stage in a basin. The approach utilized spatial tools such as Arc-Hydro, Remote Sensing (RS), and GIS to characterize the Osse Sub-basin (OSB) and Natural Resources Conservation Service - Curve Number (NRCS-CN) hydrological model to compute the stream Peak discharge Qp. This method permits identification of Small Hydropower (SHP) potential locations by considering obtained catchment parameters along the drainage network in a run-of-river project that satisfies the requirement of establishing hydropower plants, which is difficult to achieve in traditional survey study. Results indicate 18 out of 148 points examined in OSB can produce between 677.485 kW and 7622.877 kW clean energy at 92% flow exceedance annually, preventing between 555.8 and 6543.0 tCO2/yr emission from polluting the environment if developed against GHG emission sources. The calculated project cost range is £ 937,167.48–4,048,733.99. This study establishes first clean development mechanism (CDM) procedure in Nigeria to help future activation of SHP resources by identifying SHP promising project sites that can earn saleable certified emission reduction (CER) credits in the optimization model named SHP Resource Assessment and Sustainability Analysis (SHPRASA).

Exponent determination in a poorly gauged basin system in Nigeria based on flow characteristics investigation and regionalization method

In this study, a method for estimating the exponent “n” values of the catchment-area equations of four sub-basins within the poorly gauged Benin-Owena River Basin Development Authority (BORBDA) in Nigeria is presented to enable the estimation of flows at ungauged sites within the basin and the determination of small hydropower (SHP) potential at different locations in each sub-basin and the entire basin. Optimal prediction of streamflow characteristics in poorly gauged basin requires developing a methodology for extrapolation of data from gauged to ungauged sites within the basin. Four sub-catchments of BORBDA, a poorly gauged basin in Nigeria, were investigated using Remote Sensing (RS), Geographic Information System (GIS), statistical techniques, and Natural Resources Conservation Service-Curve Number (NRCS-CN) hydrological model. Discharge values at gauged sites (Qg) were obtained from recorded discharge values collected for 12 months at an established gauging station in each sub-basin. RS and GIS techniques were used to develop classification maps and obtain crucial data like curve number (CN), elevation, Hydrologic Soil Group (HSG), rainfall intensity, slope, area of gauged and ungauged required for evaluating spatial discharge (ungauged) utilizing NRCS-CN model. From the established model for each sub-basin, exponent “n” in the relationship between discharge and catchment area was obtained to be 0.23, 0.41, 0.71, and 0.74. Using the lumped modeling approach, which considers a watershed as a single unit for computation, where watershed parameters and variables were to be averaged produced “n” = 0.52 for BORBDA area, which is within the range of 0.5–0.85 suggested by previous researchers. Obtained BORBDA exponent “n” was validated for use in the entire basin through soil homogeneity test by generating BORBDA soil map which confirms the four sub-basins investigated share similar HSG A, B, and D with BORBDA. The exponent “n” value is useful for predicting flows in ungauged parts of the basin. The exponent “n” value obtained for the basin is helpful in the assessment of discharge and determination of SHP potential at different locations within the poorly gauged BORBDA basin, and the dissemination of the research findings will find practical use and guide to practicing hydrologists in Nigeria and locations around the world with similar challenges of poorly gauged basins particularly Africa and other developing countries.

Assessing impact of urbanisation on surface runoff using vegetation-impervious surface-soil (V-I-S) fraction and NRCS curve number (CN) model

The progressive decrease in natural surfaces to create space for urban dwellers with the consequential changes caused to hydrological regime of an area is taking a toll on environmental resources. The Natural Resources Conservation Service (NRCS) Curve Number (CN) model (earlier known as Soil Conservation Service Curve Number, SCS-CN) is used in the present study for assessing temporal variations in surface runoff in upper catchment of Rispana River, Dehradun city, India. Also, the composite CN is calculated using vegetation-impervious surface-soil (V-I-S) fraction derived from spectral normalisation and linear spectral mixture analysis method while assigning initial CN for hydrologic soil-cover complex for five years during 1991 to 2018. The results indicated a steady rise in impervious surface fraction and consequent surface runoff (8.25%) from 1991 to 2018, while urban green space fraction has shown depleting trends in north and central part of the city. The level of imperviousness highlighted an over 60% of central part of the city as impervious, which gradually decreases outwards from the city. A positive correlation is observed between surface runoff and ISA (R2 varies between 0.62 and 0.89, p < 0.05), whereas inverse relationship is observed with vegetative cover in all sub-basins (R2 varies between 0.61 and 0.91, p < 0.05). The study demonstrates the potential of NRCS-CN model with inputs drawn from V-I-S fraction for simulating surface runoff and understanding the urban flood risk. The work would be useful for the urban dwellers, administrators and planners for better planning and sustainable development of urban areas.

Spatial distribution and landscape impact analysis of quarries and waste dumpsites

This work aimed to develop an assessment tool that can help local officials and the public understanding the main effects surrounding location of quarrying activities and improper disposal of CDW. The specific objectives were to (1) assess the visual impact of quarries and CDW dumpsites at the landscape level and (2) investigate the effect of land conversion to quarries and CDW dumpsites on water runoff volume. The methodology of work involved digitization of individual quarries and CDW dumpsites using very high-resolution satellite imagery. The volume of exploited material was estimated with the use of a Digital Elevation Model. Geographic Object-Based Image Analysis was employed to assess the state of soil cover on identified sites. Visual impact maps were developed using Geographic Information System analysis. The Natural Resource Conservation Service-Curve Number model was adopted to estimate changes in volume of annual surface water runoff. The assessment resulted in mapping individual quarries (i.e., 1,425 quarries over an area of 61,723,800 m2) and CDW dumpsites (i.e., 219 dumpsites over an area of 5,012,100 m2) showing (1) low to complete absence of vegetation recovery on identified sites, (2) improper location of quarries and large extent of visually polluted landscape and (3) increase in surface water runoff. This work demonstrated the ability of using an operational tool to spatially characterize quarries and CDW dumpsites and their impacts on the landscape in the absence of extensive site-specific datasets. The transferability and replicability of this tool count on systematic use of the investigated geospatial techniques.

Feasibility assessment of SHP potential using GIS-enhanced RS approach in poorly gauged river basin in Nigeria

• Combination of Remote Sensing, Geographic Information System and Natural Resources Conservation Service – Curve Number model is helpful in effective planning and management of watershed in the absence of information on hydrological, topographical and geological characteristics • Run of river (ROR) hydropower plants , utilizing instantaneous river flow were suggested for the identified sites in the study area. • 11 points out of the 58 points examine at 2 km interval were classified as a feasible potential site for hydropower development . In this paper, we present the result obtained by application of Remote Sensing (RS) data & Geographic Information System (GIS) procedure in the identification and selection of feasible sites for small hydropower (SHP) projects in Oyanmi River in the Benin-Owena drainage Basin in Nigeria, using Natural Resource Conservation Service-Curve Number (NRCS-CN) model. Catchment delineation, Sub-basin Area size, slope, Curve Number (CN), Land Use Land Cover (LULC), Digital Elevation Model (DEM), rainfall intensity, etc. were obtained by RS and Arc GIS tools. Data on rainfall were obtained from Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR) for the year 2018 and validated using Nigerian Meteorological Services Agency (NIMET) Lokoja synoptic station data and then utilized for the computation of simulated discharge. The simulated discharge were correlated with observed data obtained from a gauging station in the study area. The correlation between observed and simulated data yielded a good correlation result of 65% and 63% for rainfall and discharge respectively with good statistical significance P-value. Elevation values extracted from the DEM were used in calculating the available head utilized in evaluating the hydropower potentials across the 58 hydrometric mapped-out points. Based on the criteria that a viable SHP should have a minimum slope of 2% and 10 m available head, 11 points were identified in Oyanmi sub-basin with feasible power potential ranging from 393.849 kW to 16038.194 kW at 92% annual flow exceedance which if developed would improve access to energy and socio-economic development of the study area.

Potential and net recharge assessment in paddy dominated Hirakud irrigation command of eastern India using water balance and geospatial approaches

Spatially distributed potential and net recharge rates were assessed in the paddy dominated Hirakud command area (Eastern India) at 100 m grid resolution using surface water balance and Water Table Fluctuation (WTF) methods, respectively, for the period 2001–05. Net recharge estimated using the WTF method corresponding to observation well locations was further interpolated using kriging technique available in the ArcGIS software. Net recharge to potential recharge ratios (%) were also assessed spatially. Water balance components (i) runoff was estimated using the Natural Resources Conservation Service-Curve Number (NRCS-CN) method (ii) reference evapotranspiration by (Hargreaves and Samani, Applied Engineering Agriculture ASABE 1:96–99, 1985)), crop evapotranspiration by (Allen et al., Crop evapotranspiration: Guidelines for computing crop water requirements, FAO Irrigation and Drainage, Food and Agriculture Organization, Rome, Italy, 1998) and evaporation from uncultivated lands by Ritchie (1972) approaches, and (iii) canal seepage using simple canal flow model. Annual groundwater draft during Kharif and Rabi was found to be 144.41 and 112.49 ha-m, respectively. Nearly, 90% of the study area contributed runoff in the range of 200–400 mm during the years 2002–03, 2003–04, and 2004–05. The estimated seepage losses vary between 5 and 15% of irrigation depth for all distributaries. Potential groundwater recharge during wet, normal, and dry years ranges between 650 and 1033 mm, and equivalent to 67%, 78%, and 60% of annual rainfall, respectively. Net recharge ranges between 8 and 11% of the annual rainfall. Mean ratio between net recharge to potential recharge is nearly 30%, indicating that nearly 70% of potential recharge is accounted as outflow from the study area. Parmanpur distributary canal located at the centre of the study area that exhibited higher potential recharge can be scheduled at the end to avoid water logging problem. Further, extraction of groundwater during non-monsoon period for irrigation purpose not only helps in controlling waterlogging but also helps in maintaining stable groundwater level. Overall, spatio-temporal distribution of recharge in the command area indicated that the irrigation demands during non-monsoon season can be met through sustainable management of underexploited groundwater resources. Such an integrated management of surface and groundwater can help in improving water use efficiencies as well as agricultural productivity.

Spatiotemporal Analysis of Water Resources in the Haridwar Region of Uttarakhand, India

Watershed management plays a dynamic role in water resource engineering. Estimating surface runoff is an essential process of hydrology, since understanding the fundamental relationship between rainfall and runoff is useful for sustainable water resource management. To facilitate the assessment of this process, the Natural Resource Conservation Service-Curve Number (NRCS-CN) and Geographic Information Systems (GIS) were integrated. Furthermore, land use and soil maps were incorporated to estimate the temporal variability in surface runoff potential. The present study was performed on the Haridwar city, Uttarakhand, India for the years 1995, 2010 and 2018. In a context of climate change, the spatiotemporal analysis of hydro meteorological parameters is essential for estimating water availability. The study suggested that runoff increased approximately 48% from 1995 to 2010 and decreased nearly 71% from 2010 to 2018. In turn, the weighted curve number was found to be 69.24, 70.96 and 71.24 for 1995, 2010 and 2018, respectively. Additionally, a validation process with an annual water yield model was carried out to understand spatiotemporal variations and similarities. The study recommends adopting water harvesting techniques and strategies to fulfill regional water demands, since effective and sustainable approaches like these may assist in the simultaneous mitigation of disasters such as floods and droughts.

Identification of Owan Catchment Run-of-River Hydropower Potential Sites in Benin Owena River Basin Nigeria Using GIS And RS Procedures

Hydropower is recognized internationally as a source of clean, affordable, and reliable energy that has contributed in a significant way to the global energy supply mix but unfortunately, this is not the case in Nigeria considering hydropower potential of 15 GW where only approximately 2 GW (13%) has been harnessed. Nigeria Small Hydropower (SHP) level is low, as less than 0.1 GW out of 3.5 GW SHP potential is available in a country of over 200 million people with potentials of 333BCM of surface water annually which can be used to increase energy access especially in the rural area where the percentage in 2018 is 34. In this study, Natural Resources Conservation Service - Curve Number (NRCS-CN) method which calculates surface runoff volume for a particular rainfall event in a watershed was applied in conjunction with Remote Sensing (RS) and Geographic Information System (GIS). Land Use Land Cover (LULC) classes of Owan Sub-basin were delineated from Landsat 8 satellite Image using Image Classification procedure and integrated with the hydrologic soil group (HSG) of the sub-basin in a GIS environment to obtain runoff Curve Numbers (CNs) for this study. The estimated CNs and rainfall data of Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks - Climate Data Record (PERSIANN – CDR) of the study area for the year 2018 were used to calculate the peak discharges over 125 mapped out points at 2km interval in Owan river. The gauging station data correlates NRCS-CN with a coefficient of 68 % while the Nigerian Meteorological Services Agency (NIMET) data compared with PERSIANN-CDR yielded a 70 % correlation. Using the basin hydrometric indicators of 2% minimum slope and 10m available head which must exist between two points before a site can be considered for ROR hydropower, 20 points were identified in Owan with power range from 423.015kW to 5,456.646kW at 92% available flow exceedance annually. This study revealed that NRCS-CN method combined with RS and GIS can simulate discharge successfully using watershed hydrometry in the absence of weak hydrological data. Also, owing to a significant degree of agreement between the observed and calculated runoff, the method, and models employed for this study are recommended for field applications in Benin-Owena River Basin, Nigeria at large, and other regions with data scarcity challenges hydrologically. Keywords : run-of-river, hydropower potential, Remote Sensing, Geographic Information System, NRCS-CN model. DOI: 10.7176/CER/12-10-05 Publication date: October 31 st 2020

NRCS-CN Estimation from Onsite and Remote Sensing Data for Management of a Reservoir in the Eastern Pyrenees

Onsite and Earth observation (EO) data are used for the calibration of the Natural Resources Conservation Service curve number (NRCS-CN) value in a hydrological simulation model. The model was developed for La Muga catchment (eastern Pyrenees) highly vulnerable to flood and drought episodes. It is an integral part of a regional reservoir management tool, which aims at minimizing the flood risk while maximizing the preservation of water storage. The CN values were optimized for five recorded events for the model to match the observed hydrographs at the reservoir when supported with the measured rainfall intensities. This study also investigates the possibilities of using antecedent moisture conditions (AMC) retrieved from satellite data to inform the selection of the NRCS-CN losses parameter. A good correlation was found between the calibrated CN values and the AMC obtained from satellite data. This correlation highlights the interest in using EO data to update NRCS-CN estimates. This advances in hydrologic-hydraulic coupled modeling combined with new remote sensing datasets present valuable opportunities and potential benefits for flood risk management and water resources preservation.

Evaluation and validity of the antecedent moisture condition (AMC) of Natural Resources Conservation Service-Curve Number (NRCS-CN) procedure in undeveloped arid basins

The available conversion formulae for AMC-CN are estimated in an environment that is not arid. The validity of these formulae in arid regions is questionable. Therefore, in the current study, a focus is made on studying the validity of the NRCS-CN theory, its AMC, formulas, and derivation of conversion formulae of CN for some arid basins in the southwest Saudi Arabia (SA). One hundred sixty-one rainfall-runoff events have been collected over a period of 4 years on 19 sub-basins in the study area. The results show that in arid regions the AMCI antecedent moisture condition at (dry) conditions is dominant. It has been shown that the abstraction ratio, λ = 0.01, is the best to fit the NRCS-CN theory when compared with λ = 0.2 or 0.3. The observed and estimated runoff show that the root mean square error (RMSE) is the lowest for λ = 0.01 (1.8 mm, 3.69 mm, and 1.36 mm) when compared with λ = 0.2 (4.21 mm, 12.13 mm, and 3.15 mm) and λ = 0.3 (5.74 mm, 13.92 mm, and 3.1 mm) for CNI (CN at dry condition), CNII (CN at normal condition), and CNIII (CN at wet condition) respectively. The upper and lower limits of λ, in SA, are 0.02 (90% probability) and 0.00001 (10% probability) respectively. The runoff coefficient is less than 0.4. This is due to high transmission losses which is typical in arid regions. The study recommends using λ = 0.01 and the developed AMC-CN formulae for enhanced runoff predictions in SA.

Assessment of modified curve number method by evaluation of runoff depth in Sulak basin-Iraq

Traditional hydrological analysis used maps and ground survey as tools to obtain the basic parameters of the watershed. However, for large catchment area the above criteria are both costly and time consuming. In this research, a hydrological model modified natural resources conservation service curve number (NRCS-CN) and geographical information system GIS technique are used together to obtain the runoff depth for Sulak catchment area that located in the northern western part of Iraq. The basin divided into three sub-basins, runoff has been estimate for each sub-basin by three approaches. The research detect that the slope parameter affects runoff estimation significantly also its found that for each sub-watershed runoff varies drastically from sub-watershed to sub-watershed of Sulak basin. The analysis of variance test showed that there was significant difference between each curve number value for each sub-watershed, accordingly runoff calculated by Williams method gives valves above the average comparing with other methods. Total runoff estimated by three approaches for entire catchment area which shows that around 51% of total runoff is generated in months January and February, That because of heavy rainfall and high soil moisture content (antecedent moisture content AMC-III) during that period.

Developing quantifiable approaches for delineating suitable options for irrigating fallow areas during dry season-a case study from Eastern India.

Harvesting surface runoff during monsoon season for further utilization in crop production during the post-monsoon season is now becoming an effective solution to mitigate water scarcity problems. In this study, multi-criteria analysis-analytic hierarchy process (MCA-AHP)-based approach was envisaged for rainwater harvesting (RWH) zoning for a case study area, i.e., two districts of Odisha state situated in Eastern India. In spite of having a large irrigation network in the study area, major portion of these two densely populated and agriculture dominated districts remains fallow during dry seasons. Suitable locations for RWH structures such as farm pond, check dam, and percolation tanks were identified through Boolean conditions. RWH potential map was generated using different thematic layers namely land use/land cover (LU/LC), geomorphology, slope, stream density, soil type, and surface runoff. AHP-based MCA technique was used to integrate these thematic layers by assigning weights to the thematic layers and ranks to the individual theme features on 1-9 AHP Saaty's scale, considering their relative importance on RWH potential of the study area. The Natural Resources Conservation Service-Curve Number method was used to derive surface runoff using Climate Hazards Group Infra-Red Precipitation with Station rainfall data, satellite-derived LU/LC and FAO soil maps. In comparison to single cropped areas in 48% of the total study area, only 4% area was under double and triple cropped areas during 2016-2017. Moderate runoff was observed in > 50% of the study area dominated by agricultural landscape. Nearly 40%, 25.11%, and 32.45% of the study area indicated very high, high, and moderate RWH potentials, respectively. Particularly, very high RWH potential is observed in the eastern and central portion of the study area. The use of appropriate RWH structures in less irrigated areas will facilitate multiple cropping and will substitute the use of sub-surface water harvesting practices. In these two districts, 73 check dams and 153 percolation tanks are prescribed along the 2nd- and 3rd-order streams. In coarser textured soil, nearly 306km2 and 608km2 areas are identified as moderate and highly suitable zones for percolation tank construction on ground, while in fine soil, around 786km2 area is identified as suitable for farm pond construction. Majority of the suitable zones for percolation tanks is found in Jajpur district, while suitability for adoption of farm pond and check dam is more in Bhadrak district. It is expected that implementation of the prescribed RWH structures can mitigate the threats of flood, drought, soil erosion, and enhance the soil moisture and cropping intensity significantly. The use of GIS platform with the spatial layers and the methodology adopted can be updated and replicated in larger regions in a shorter time. The spatially explicit maps are offering insights to different themes, providing useful information to the water resource managers, and may improve the decision-making process.