MATHAMALI SPRING AS A SIMPLE DYNAMIC SYSTEM

Abstract

Water is a pivotal part for every living being, which is nowadays becoming scarce due to anthropogenic activities. Global warming and climate change have brought about a change in the patterns of rainfall, snowfall, stream/spring flow, evaporation in a catchment area. This study emphasizes on the exploration of spring discharge and rainfall data in the contact and fracture type Mathamali spring located in Garhwal, Lesser Himalaya. The rainfall is maximum in the monsoon season i.e., in the months of July and August, the spring discharge shows peak values with a lag of a few days from rainfall. In winter, the discharge is due to the storage property of the spring. The methodology adopted in this study is based on the water-budget equation. When the rainfall is zero and evapotranspiration is negligible, the storage is a function of discharge and vice versa. The discharge value, when rainfall is zero, is part of the recession curve of the hydrograph. The recession curve discharge values are fitted using power law and used in the estimation of evaporation using fitted discharge and rainfall data bypassing the use of storage. In order to develop the spring as a simple dynamic storage system, Mathamali rainfall-runoff data is used. A set of discharge data corresponding to zero rainfall is the foundation of SDS i.e., Simple Dynamic System. The above discharge values are the key features to formulate and shape the recession curve. This feature is graphically more provident in data sets and a new term “Sensitivity Function” is used for representing the discharge response to changes in catchment storage. The sensitivity function is calculated on the basis of mean or median value of fitted equation coefficients in log-log plot of (-dQ/dt) and Q. In this study we have found variations in flow coefficient b which suggests different aspects of geology as well as storage characteristics of Mathamali spring. This is evident in scatter plot of −𝑑𝑄/𝑑𝑡 vs 𝑄. The value of coefficients b in power law varies significantly according to events (as explained in chosen events 6 and 52; g(Q)6 = 0.01, g(Q)52 = 0.03. This is because of different aquifer properties which leads to water storage of spring. The analysis of power law provides valuable information about Storage-Discharge relationship. The results of this study are interpreted in terms of Storage-Discharge relation which comes as 𝑄=0.0831∗𝑆0.61763. The so far developed relationship is utilised to find out other important hydrological parameters. It will be further helpful in analyzing storage and spring discharge behavior patterns for managing local domestic demand and flood management.