HYDROLOGICAL MODELLING OF UNGAUGED ARID VOLCANIC ENVIRONMENTS AT UPPER BATHAN CATCHMENT, MADINAH, SAUDI ARABIA

2016 ◽  
Vol 78 (9-4) ◽  
Author(s):  
Fahad Alahmadi ◽  
Norhan Abd Rahman ◽  
Zulkifli Yusop
Keyword(s):  
Saudi Arabia ◽  
Land Cover ◽  
Soil Conservation ◽  
Daily Rainfall ◽  
Curve Number ◽  
Hydrological Modelling ◽  
Time Interval ◽  
Storm Events ◽  
Ungauged Catchments ◽  
Rainfall Depth

Hydrological modelling of ungauged catchments is still a challenging task especially in arid regions with a unique land cover features such as highly fracture volcanic basalt rocks. In this study, upper Bathan catchment (103 km2) in Madinah, western of Saudi Arabia is selected. The aim of this paper is to simulate the hydrological responses of volcanic catchment to daily design storm events. The weighted areal average of two daily design rainfall depth scenarios are computed, which are 50 years and 100 years return period and correspondent predicted rainfall are 80.6 mm and 94.1 mm, respectively. SCS Type II temporal synthetic distribution of daily rainfall is selected to disaggregate the daily rainfall into smaller time interval. Excess rainfall is computed using Soil Conservation Services Curve Number (SCS-CN) method based on Land Cover and Land Use (LCLU) and hydrological soil groups (HSG) maps, while direct runoff hydrograph is developed using Soil Conservation Services dimensionless unit hydrograph (SCS-UH) method using lag time equation. HEC-HMS software is used, and it showed that the runoff volumes of the two rainfall scenarios are 50% and 54% of the total rainfall depth, and the peak discharges are 123 m3/sec and 158 m3/sec. This study provided an indication of the hydrograph characteristics of basaltic catchments and the result of this paper can be used for further flood studies in arid ungauged volcanic catchments.  

scholarly journals Determination of Curve Number for snowmelt-runoff floods in a small catchment

2015 ◽  
Vol 370 ◽  
pp. 167-170 ◽  
Author(s):  
L. Hejduk ◽  
A. Hejduk ◽  
K. Banasik
Keyword(s):  
Soil Conservation ◽  
Curve Number ◽  
Rainfall Runoff ◽  
Snowmelt Runoff ◽  
Ungauged Catchments ◽  
Department Of Agriculture ◽  
Small Catchment ◽  
Rainfall Depth ◽  
Runoff Events

Abstract. One of the widely used methods for predicting flood runoff depth from ungauged catchments is the curve number (CN) method, developed by Soil Conservation Service (SCS) of US Department of Agriculture. The CN parameter can be computed directly from recorded rainfall depths and direct runoff volumes in case of existing data. In presented investigations, the CN parameter has been computed for snowmelt-runoff events based on snowmelt and rainfall measurements. All required data has been gathered for a small agricultural catchment (A = 23.4 km2) of Zagożdżonka river, located in Central Poland. The CN number received from 28 snowmelt-runoff events has been compared with CN computed from rainfall-runoff events for the same catchment. The CN parameter, estimated empirically varies from 64.0 to 94.8. The relation between CN and snowmelt depth was investigated in a similar procedure to relation between CN and rainfall depth.

scholarly journals Initial abstraction ratio and Curve Number estimation using rainfall and runoff data from a tropical watershed

RBRH ◽  
2019 ◽  
Vol 24 ◽  
Author(s):  
Luiz Claudio Galvão do Valle Junior ◽  
Dulce Buchala Bicca Rodrigues ◽  
Paulo Tarso Sanches de Oliveira
Keyword(s):  
Conversion Factor ◽  
Poor Performance ◽  
Curve Number ◽  
Storm Events ◽  
Rainfall Runoff ◽  
Initial Abstraction ◽  
Rainfall Depth ◽  
Standard Value ◽  
Tropical Watershed ◽  
Runoff Events

ABSTRACT The Curve Number (CN) method is extensively used for predict surface runoff from storm events. However, remain some uncertainties in the method, such as in the use of an initial abstraction (λ) standard value of 0.2 and on the choice of the most suitable CN values. Here, we compute λ and CN values using rainfall and runoff data to a rural basin located in Midwestern Brazil. We used 30 observed rainfall-runoff events with rainfall depth greater than 25 mm to derive associated CN values using five statistical methods. We noted λ values ranging from 0.005 to 0.455, with a median of 0.045, suggesting the use of λ = 0.05 instead of 0.2. We found a S0.2 to S0.05 conversion factor of 2.865. We also found negative values of Nash-Sutcliffe Efficiency (to the estimated and observed runoff). Therefore, our findings indicated that the CN method was not suitable to estimate runoff in the studied basin. This poor performance suggests that the runoff mechanisms in the studied area are dominated by subsurface stormflow.

scholarly journals Variability of the Initial Abstraction Ratio in an Urban and an Agroforested Catchment

Water ◽  
2020 ◽  
Vol 12 (2) ◽  
pp. 415 ◽  
Author(s):  
Adam Krajewski ◽  
Anna E. Sikorska-Senoner ◽  
Agnieszka Hejduk ◽  
Leszek Hejduk
Keyword(s):  
Land Use ◽  
Curve Number ◽  
Threshold Value ◽  
Storm Events ◽  
Direct Runoff ◽  
Initial Abstraction ◽  
Land Use Types ◽  
Rainfall Depth ◽  
Storm Rainfall ◽  
Service Curve

The Curve Number method is one of the most commonly applied methods to describe the relationship between the direct runoff and storm rainfall depth. Due to its popularity and simplicity, it has been studied extensively. Less attention has been given to the dimensionless initial abstraction ratio, which is crucial for an accurate direct runoff estimation with the Curve Number. This ratio is most often assumed to be equal to 0.20, which was originally proposed by the method’s developers. In this work, storm events recorded in the years 2009–2017 in two small Polish catchments of different land use types (urban and agroforested) were analyzed for variability in the initial abstraction ratio across events, seasons, and land use type. Our results showed that: (i) estimated initial abstraction ratios varied between storm events and seasons, and were most often lower than the original value of 0.20; (ii) for large events, the initial abstraction ratio in the catchment approaches a constant value after the rainfall depth exceeds a certain threshold value. Thus, when using the Soil Conservation Service-Curve Number (SCS-CN) method, the initial abstraction ratio should be locally verified, and the conditions for the application of the suggested value of 0.20 should be established.

scholarly journals Statistical and Type II Error Assessment of a Runoff Predictive Model in Peninsula Malaysia

Mathematics ◽  
2021 ◽  
Vol 9 (8) ◽  
pp. 812
Author(s):  
Lloyd Ling ◽  
Zulkifli Yusop ◽  
Joan Lucille Ling
Keyword(s):  
Curve Number ◽  
Technological Advancement ◽  
Type Ii ◽  
Error Assessment ◽  
Type Ii Error ◽  
Storm Events ◽  
Rainfall Runoff ◽  
Scs Model ◽  
Rainfall Depth ◽  
Runoff Model

Flood related disasters continue to threaten mankind despite preventative efforts in technological advancement. Since 1954, the Soil Conservation Services (SCS) Curve Number (CN0.2) rainfall-runoff model has been widely used but reportedly produced inconsistent results in field studies worldwide. As such, this article presents methodology to reassess the validity of the model and perform model calibration with inferential statistics. A closed form equation was solved to narrow previous research gap with a derived 3D runoff difference model for type II error assessment. Under this study, the SCS runoff model is statistically insignificant (alpha = 0.01) without calibration. Curve Number CN0.2 = 72.58 for Peninsula Malaysia with a 99% confidence interval range of 67 to 76. Within these CN0.2 areas, SCS model underpredicts runoff amounts when the rainfall depth of a storm is < 70 mm. Its overprediction tendency worsens in cases involving larger storm events. For areas of 1 km2, it underpredicted runoff amount the most (2.4 million liters) at CN0.2 = 67 and the rainfall depth of 55 mm while it nearly overpredicted runoff amount by 25 million liters when the storm depth reached 430 mm in Peninsula Malaysia. The SCS model must be validated with rainfall-runoff datasets prior to its adoption for runoff prediction in any part of the world. SCS practitioners are encouraged to adopt the general formulae from this article to derive assessment models and equations for their studies.

scholarly journals A GIS Based Methodology to Obtain the Hydrological Response to Storm Events of Small Coastal Basins, Prone to Flash Flooding

2021 ◽  
pp. 163-171
Author(s):  
V. A. Kotinas
Keyword(s):  
Drainage Basin ◽  
Extreme Event ◽  
Flash Flood ◽  
Daily Rainfall ◽  
Curve Number ◽  
Hydrological Response ◽  
Storm Events ◽  
Flash Flooding ◽  
Concentration Maximum ◽  
Coastal Basins

The present study aims to investigate the hydrological response of small coastal watersheds to storm events. Areas around the Mediterranean Sea are usually characterized by streams with intermittent flows and flash floods are common. Firstly, we analyze the geomorphological, soil and land cover characteristics of the watershed in order to estimate their effect on surface runoff. Furthermore, the rainfall characteristics of an extreme event that caused flash flooding in the past are analyzed. By combining these factors, we are able to predict the response of this basin to severe storm events. The study area is located in the island of Samos, in Eastern Greece, where flash flood events are usual and pose a risk to areas located around rivers. In this area runoff is intermittent, occurring mainly during storm events and there is a lack of discharge or other instrumental measurements. By applying the SCS-CN method we estimate the response of two of the largest watersheds in Samos Island, through the construction of a Synthetic Unit Hydrograph (SUH). Firstly, we examined the record of historic floods in the area, selecting a large flash flood event (November 2001) and then obtained the daily rainfall data, which are used by the SCS method for the calculations. We applied the SCS methodology in order to estimate various parameters (e.g. lag time, time of concentration, maximum discharge), which also required the calculation of the Curve Number (CN) for each watershed. During this event (136 mm rainfall), we calculated a direct runoff (excess rainfall) of 44%-48% for these watersheds. This methodology can be particularly useful in simulating the hydrological response of small Mediterranean watersheds and to introduce better strategies for the management of the whole drainage basin.

scholarly journals Computation of Runoff by SCS-CN Method from micro watersheds of Urmodi basin in Maharashtra state using RS and GIS

Agropedology ◽  
2019 ◽  
Vol 27 (2) ◽  
Author(s):  
S.B. Nandgude ◽  
◽  
G.S. Jadhav ◽  
S.S. Shinde ◽  
D.M. Mahale ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Water Conservation ◽  
Surface Runoff ◽  
Daily Rainfall ◽  
Curve Number ◽  
Rainfall Data ◽  
Land Use Land Cover ◽  
Daily Rainfall Data

Flood is a natural or manmade phenomenon and timely and accurate forecasting of flood is very important. However forecasting of flood is a difficult task due to influence of rainfall-runoff process which depends on various factors. Estimation of surface runoff in a watershed is based on the rate of precipitation and discharge at the outlet. In this study, runoff from micro watersheds of Urmodi basin in Maharashtra state was computed by Soil Conservation Service-Curve Number method using remote sensing and Geographic Information System (GIS) techniques. Various thematic maps such as soil map, land use/land cover, stream order, slope etc. were prepared using remote sensing and GIS. Daily rainfall data was used for determining runoff. Antecedent moisture conditions were determined from daily rainfall data and for different CNs with the help of combined land use land cover and hydrologic soil group map in GIS environment. Results showed that the highest runoff for Bharatgaon and Nagthane micro watersheds was 46.20 mm and 54 mm respectively. Total runoff depth for the year 2014 was computed as 215.05 mm for Bharatgaon micro watershed and 277.68 mm for Nagthane micro watershed. Different soil and water conservation measures and water harvesting structures were recommended to control soil erosion and to harness the surface runoff.

scholarly journals Improving Urban Runoff in Multi-Basin Hydrological Simulation by the HYPE Model Using EEA Urban Atlas: A Case Study in the Sege River Basin, Sweden

Hydrology ◽  
2019 ◽  
Vol 6 (1) ◽  
pp. 28 ◽  
Author(s):  
Hiroto Tanouchi ◽  
Jonas Olsson ◽  
Göran Lindström ◽  
Akira Kawamura ◽  
Hideo Amaguchi
Keyword(s):  
Land Cover ◽  
Flow Rate ◽  
River Flow ◽  
Daily Rainfall ◽  
Added Value ◽  
Exceedance Probability ◽  
Storm Events ◽  
Hydrological Simulation ◽  
Land Cover Data ◽  
Atlas Model

In this study, the high-resolution polygonal land cover data of EEA Urban Atlas was applied for land-use characterization in the dynamic multi-basin hydrological model, HYPE. The objective of the study was to compare this dedicated urban land cover data in semi-distributed hydrological modelling with the widely used but less detailed EEA CORINE. The model was set up for a basin including a small town named Svedala in southern Sweden. In order to verify the ability of the HYPE model to reproduce the observed flow rate, the simulated flow rate was evaluated based on river flow time series, statistical indicators and flow duration curves. Flow rate simulated by the model based on Urban Atlas generally agreed better with observations of summer storm events than the CORINE-based model, especially when the daily rainfall amount was 10 mm/day or more, or the flow exceedance probability was 0.02 to 0.5. It suggests that the added value of the Urban Atlas model is higher for heavy-to-medium storm events dominated by direct runoff. To conclude, the effectiveness of the proposed approach, which aims at improving the accuracy of hydrological simulations in urbanized basins, was supported.

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