Estimation of a Unique Pair of Nash Model Parameters: An Optimization Approach

Abstract

Water resources planning and management requires hydrologic models to estimate runoff from a catchment. For catchments with limited data, the choice of model and identification of its parameters is very important for development of a direct runoff hydrograph. A method is presented to determine a unique pair of hydrologic parameters of the Nash Model, number of linear cascade (n) and storage coefficient (k), using optimization based on Downhill Simplex technique. In this study physical parameters of the catchment are derived from (SPOT) satellite imageries of the basin using ERDAS software. Four different objective functions of varying complexity are tested to find the best solution. Weighted root mean square error (RMSE) and Model Efficiency (Nash-Sutcliffe coefficient) are used to evaluate the model performance. Using the NASH model, a direct surface runoff hydrograph (DSRH) is developed. Kaha catchment is part of Indus river system and is located in the semi-arid region of Pakistan. This catchment is dominated by hill torrent flows and is used in this work to demonstrate the applicability of the proposed method. Ten randomly selected rainfall-runoff events are used for calibration and five events are used for validation. Model results during validation are very promising with model efficiency exceeding 93% and error in peak discharge under 8%. The sensitivity of the Nash model output in response to variation in hydrologic parameters n and k is also investigated. When evaluating the hydrologic response of large catchments, 2972 M.M. Ahmad et al.model output is more sensitive to n as compared to k indicating that the runoff diffusion phenomenon is dominant compared to translation flow effects.

Using large‐scale climatic patterns for improving long lead time streamflow forecasts for Gunnison and San Juan River Basins

“…Direct impacts have been realized by means of the hydrologic cycle, which is driven primarily by climate. This has caused climatic extremes, such as floods (Ahmad and Simonovic, 2006;Ahmad et al, 2009;Ahmad et al, 2010a) and droughts (Puri et al, 2011;Stephen et al, 2010), which result in damages greater than any other form of natural disaster (Wilhite, 1997). In light of these concerns, skilful streamflow forecasts are required for the long-term planning, development, and management of water resources.…”

Development of geomorphologic instantaneous unit hydrograph for a large watershed

“…Solution to such a problem requires evaluation of the intensity of floods for various rainfall events. The rainfall-runoff process is very complicated and the problem of finding the flood magnitudes becomes more challenging when the data is limited or scantily available (Ahmad et al 2010;Bekele and Knapp 2010;Bahremand and De Smedt 2010;Ahmad 2009;Bahremand and De Smedt 2008). It requires a hydrologic model which may provide the flood magnitudes using limited parameters and data.…”

“…Due to the above-mentioned facts, the use of geomorphology GIS, remote sensing GIUH for rainfall-runoff models for poorly gauged basins has attracted the attention of many researchers and presently a lot of work is being published in this regard (Ahmad et al 2010;Dave et al 2010;Coskun et al 2010;Cao et al 2010;Ahmad 2009;Rai et al 2009;Nguyen 2008;Sarangi et al 2007). Bhaskar et al (1997) showed that temporal distribution of rainfall excess has no marked effect on GIUH simulation.…”

“…Singh et al (2007) developed synthetic unit hydrograph by concept of a number of linear cascades with different storage coefficient "k" values. Ahmad et al (2010) have done extensive work on GIUH; however, the dynamic velocity parameter was not addressed. In GIUH, the dynamic velocity is one of the very important parameters.…”

Optimal Parameter Estimation for Muskingum Model Using a CSS-PSO Method

“…Limited availability of hydrologic data is a major hurdle for implementation of detailed hydrologic models. In cases where available data is limited, simple hydrologic models consisting of a minimum number (one or two) of model parameters are more desirable [8]. A simple conceptual model like the Muskingum model is very effective in the estimation of the hydrograph of the rise and fall of a river at any given point on the river during the course of a flood event.…”