ESTIMATION THE EFFECTIVE TIME OF ANTECEDENT PRECIPITATION ON OUTPUT DISCHARGE OF TANGRAH PASTURE WATERSHED
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A deterministic hydrologic watershed model that simulates the watershed discharge and soil moisture status continuously throughout the crop season was developed for drainage watersheds with depressional storage. The model simulates the processes of interception, surface storage, infiltration, surface runoff, soil profile storage, percolation to the water table, subsurface tile drainage, soil moisture redistribution, evapotranspiration, and routing through depressions, tile mains, and the drainage ditch. The resulting outputs are daily evapotranspiration, soil moisture status in the crop root zone, and watershed discharge. The model simulated the watershed discharge and soil moisture status of the 24‐mi 2 East Fork Hardin Creek watershed near Jefferson, Iowa, for the 1964 crop season as well as could be expected with the input data that were available. Discrepancies between the measured discharge and the predicted discharge were in part due to spatial variations in precipitation over the watershed, which were not accounted for in the model input data.
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Estimation and quantification of catchment surface runoff an important hydrologic variable used in most of the water resources applications watershed development and management problems. In this study, rainfall-runoff relationship of Hemavathy river basin is determined using Soil Conservation Services-Curve Number (SCS-CN) method for runoff estimation for ungauged watersheds. The important parameters considered include land use/land cover, soil, vegetation, drainage, precipitation, contour, slope, daily rainfall data. From the 11year daily rainfall data daily runoff was estimated using SCS CN equation considering antecedent moisture conditions. Daily runoff depth in the watershed was then computed using SCS-CN equation was later converted to runoff volume. It was observed in runoff potential of the watershed about 41% of area having high CN value interprets in more runoff. The runoff thus calculated was compared with gauged flow at dam site observed that regression coefficient is almost same for both estimated and observed data and an increase of about 15% in inflow data as per project authorities in the catchment which may be due to regenerated water from irrigation and presences of perennial streams in the catchment even during non-monsoon months there is inflow observed.
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Due to climate change, extreme rainfall is more frequent, and the phenomenon of drought and desertification in some parts of the world is accentuated. Scientists forecast that these trends to continue as the planet continue to warm. An increasingly common phenomenon is the occurrence of flash floods in areas where human intervention on natural conditions has been significant. Over this intervention is superimposed the modification of the characteristics of extreme rainfalls (duration, intensity, height), resulting a series of negative consequences on the ecosystems of the watersheds. For their protection, a more accurate forecast of the size and times of occurrence of the maximum water flows and levels in different sections are needed. This forecast must be made with appropriate methods, such as the use of advanced hydroinformatic tools. This paper analyses the influence of rainfall characteristics on runoff in a small watershed, using rainfall-runoff phenomenon modelling. The modelling is realized using advanced hydroinformatic tool MIKE11, developed by Danish Hydraulic Institute (DHI).
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Abstract The Soil Conservation Service Curve Number (SCS-CN) method is one of the popular methods for calculating storm depth from a rainfall event. The previous research identified antecedent rainfall as a key element that controls the non-linear behaviour of the model. The original version indirectly uses five days antecedent rainfall to identify the land condition as dry, normal or wet. This leads to a sudden jump once the land condition changes. To obviate this, the present work intends to improve the performance of antecedent rainfall-based SCS-CN models. Two forms of SCS-CN model (M1 and M2), two recently developed P-P5 based models (M3 and M4), and an alternate approach of considering P5 in the SCS-CN model (M5 and M6), as proposed here, were investigated. Based on the evaluation of several error metrics, the new proposed model M6 has performed better than other models. The performance of this model is evaluated using rainfall-runoff events of 114 watersheds located in the USA. The median value of Nash-Sutcliffe Efficiency was found as 0.78 for the M6 model followed by M5 (0.75), M3 (0.73), M4 (0.72), M2 (0.63) and M1 (0.61) model.
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