Development of Synthetic Unit Hydrograph for Ungauged Catchments – A Review

This paper primarily focusses on the development of synthetic unit hydrographs for ungauged catchments that are hydrologically homogeneous. The scope of this study is to review the efforts made by the researchers to develop suitable models for such catchments that can be used by planners for flood risk assessment and adoption of flood prediction and warning systems downstream. In this study, probabilistic distribution function-based models have been focused because of their good performance in previous applications to different catchments. We found that the probabilistic distribution function-based models that use a parametric approach and employ basin geomorphology and homogeneity to minimize the parameters offers a better approach. These models are robust, involve few parameters and provide good results for ungauged basins. Their main advantage is that once the regional homogeneity is established, standardzed data from different sites within a region can be pooled together and a single frequency curve can be made applicable to the entire region. Introduction Unit hydrograph (UH) is a powerful tool in hydrology most widely used to assess flood risk and the adoption of flood prediction and warning systems for gauged basins. The accuracy of the prediction depends upon the sufficiency and accuracy of historical data. Sherman [1] was perhaps the first to evolve the procedure to develop the UH for a basin or watershed from its rainfall-runoff data. While developing the UH, Sherman assumed that the catchment is linear and time-invariant but failed to describe the runoff distribution precisely. This limits the application of UHs to gauged watersheds only. But the theory is being recognized as a good predictive tool and the UH is seen to reflect the characteristics of the basin it represents. The basin characteristics that can be reflected in a UH are the drainage area, size and shape, drainage density and its distribution, length of the main stream, and storage due to the surface or channel obstructions. The theory of UH for gauged basins can be extended to hydrological prediction in ungauged catchments but require the construction of UH from the basin characteristics it represents and the observed rainfall-runoff data [2]. In this background, several studies have been made to synthesize a UH for ungauged basins. An excellent review of theories proposed for extension of UH to ungauged basins has been provided by Singh et al. [3]. However, in many parts of the world, rainfall and runoff data are seldom adequate to develop UH for a basin. The paucity of such data led to the concept of the © 2018 IJRAR November 2018, Volume 5, Issue 4 www.ijrar. org (E-ISSN 2348-1269, PISSN 2349-5138) IJRAR1BHP183 International Journal of Research and Analytical Reviews (IJRAR) www.ijrar. org 1191 synthetic unit hydrograph (SUH). The term “synthetic” here denotes the hydrograph derived from basin characteristics rather than from measured rainfall-runoff data. The synthetic unit hydrograph can be classified into four categories – traditional, conceptual, probabilistic, and geomorphological. The traditional SUH models are based on empirical equations and have certain region-specific constants/coefficients. These coefficients represent the physical characteristics of the catchments and vary over a wide range even within the same region. The notable traditional models include Snyder [4], Tailor and Schwarz [5] and Soil Conservation Service [6]. To determine the precise hydrologic response of both gauged and ungauged catchments, significant efforts have been made by the scientific community to reduce the number of such parameters. The probabilistic or probability distribution function-based models use a parametric approach and employ basin geomorphology and homogeneity to minimize the parameters and derive the hydrologic response of the catchments by developing different models. These models are robust, involve a few parameters and provide good results. Their main advantage is that once the regional homogeneity is established, standardized data from different sites within a region can be pooled together and a single frequency curve can be made applicable to the entire region. This paper primarily focusses on the development of synthetic unit hydrographs for ungauged catchments that are hydrologically homogeneous. The scope of this study is to review the efforts made by the researchers to develop suitable models for such catchments that can be used for flood risk assessment and adoption of flood prediction and warning systems downstream. Probabilistic distribution function-based models have been focused in this study because of their good performance in previous applications to different catchments. Traditional Synthetic Unit Hydrograph Methods The beginning of the SUH concept can be traced back to the distribution graph proposed by Bernard [7] to synthesize SUH from watershed characteristics. Since then, numerous models have been developed. Some of the methods developed during the early stages are discussed below. Snyder Method In many parts of the world, rainfall and runoff data are seldom adequate to develop a unit hydrograph for a basin or watershed. Snyder [4] was perhaps the first to propose a method for the development of SUH by analyzing a larger number of basins in the Appalachian mountain region of the United States. To synthesize SUH Snyder evolved a set of empirical relations using watershed characteristics, i.e. the catchment area (A) (km 2 ); length of main stream (L) (km); the distance from the watershed outlet to a point on the main stream nearest to the center of the area of the watershed (Lc), and five characteristics the UH, i.e. the basin lag tl, the peak direct runoff rate Qp (m 3 /s), the base time Tb (days), and the widths at 50 and 75 percent of the peak discharge, represented as W50 and W75 respectively. © 2018 IJRAR November 2018, Volume 5, Issue 4 www.ijrar. org (E-ISSN 2348-1269, PISSN 2349-5138) IJRAR1BHP183 International Journal of Research and Analytical Reviews (IJRAR) www.ijrar. org 1192 These relationships can be expressed as: