SOIL CONSERVATION SERVICE-CURVE NUMBER METHODOLOGY MODIFIED FOR IMPROVED DIRECT RUNOFF ESTIMATION

Abstract

Water, a natural resource of paramount importance, is vital for all beings on Earth. It is essentially required for the sustainability of the ecosystem and prosperity of the nation as well. For sustainability, water management is needed and it, in turn, involves the assessment of water availability. Management issues can be more effectively addressed by employing watershed models used to assess quantity and quality of surface and sub-surface flows, erosion, and sediment yield. Such an assessment aids a range of water resources management activities. The hydrologic cycle consists of major processes: evaporation, evapotranspiration, interception, infiltration, percolation, overland flow, base flow etc., and runoff depends on climatic and catchment characteristics of a watershed which vary both spatially and temporally. Thus, for reliable predictions of runoff from the land surface into streams and rivers is very important to understand the existing rainfall-runoff relationship for making reliable runoff estimates from a watershed. There exists a multitude (several thousand) of published/unpublished rainfall-runoff models in the literature. The SCS-CN methodology has been utilized by numerous researchers for runoff estimation worldwide since its inception in 1954. As a result, it has been a subject of intense and extensive exploration for its formation, rationality, applicability and extendibility, physical significance, and so on soon after it came into being. Besides others, the existing SCS-CN method still requires improvement for more accurate runoff estimation by incorporating storm duration and its intensity in its mathematical formulation. Since its primary parameter Curve Number (CN) also varies from storm to storm in a watershed, the related parameter potential maximum retention also varies and requires appropriate treatment for its variation in the model structure. Thus, there is a need to revisit the SCS-CN methodology for its improvement. The aims and objectives of the present study are: 1. To review the chronological evolution of the SCS-CN methodology and its applications in various scientific fields. 2. Performance evaluation using a large rainfall-runoff dataset of US watersheds and sensitivity analysis of (a) an SCS-CN model incorporating rainfall duration, (b) an SCS-CN inspired model incorporating parameter potential maximum retention that decays with rainfall intensity, and (c) an SCS-CN-inspired model incorporating both rainfall duration and intensity -dependent potential maximum retention parameter. 3. Comparative performance evaluation of all the above models and suggestion for field application of the best performing model based on several available performance indicators.