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Towards a framework for quantifying water resources in india
In this paper, we assemble tools to meet the above requirements. At the core of this framework is a hydrological routing algorithm (HYDRA (Coe, 2000,1998)) that, given the distribution of local precipitation and evapotranspiration, can route the runoff to its destination, the sea or an inland lake. HYDRA was developed at the Center for Sustainability and the Global Environment (SAGE: http://www.sage.wisc.edu/) in the University of Wisconsin. It uses a linear reservoir model to transport local surface runoff and sub-surface drainage (or baseflow) through a river network to its destination, the sea or an inland lake. The linear reservoir model simulates water transport in terms of local flow directions derived from the local topography, residence times within a grid cell, and effective flow velocities. A potential river drainage basin is defined as the sum of the area of all grid cells potentially draining through a common outlet to the ocean. HYDRA uses the elevation and local flow directions in an iterative procedure to do this; the iterative procedure also identifies the lakes and wetlands that form a part of the watershed (Coe, 2000,1998). HYDRA is highly scalable, and the basic data required by the model are a digital elevation model (DEM) that maps the topography on the required scale, and data on precipitation and evapotranspiration. DEMs on a range of scales are now available through satellite remote sensing. Data on evapotranspiration are available from climate models and atmospheric general circulation models (AGCMs); an example is the NCEP/NCAR (National Centers for Environmental Prediction / National Center for Atmospheric Research) Reanalyses (Kalnay et al., 1996) data set. These models also provide continuous (in both space and time) precipitation data, permitting an estimate of local runoff even in regions without direct precipitation measurements; the hydrological models, in turn, serve as a stringent test to evaluate the performance of these AGCMs (Coe, 2000). For analysing the model results, a powerful tool is a GIS because the variables associated with hydrology are inherently geographical. We choose the GRASS (Geographical Resource Analysis Support System) GIS (Neteler and Mitasova, 2002), preferring it to other available GISs because it meets the requirements listed above. The framework is described in detail in Coe (2000) and Shankar et al. (2003). Here, we demonstrate its viability by applying it to a river basin. Our choice for testing the framework is the Mandovi river (also called Mahadayi and Mhadei over some stretches), which has its source in the Sahyadri range and flows into the eastern Arabian Sea (Figure 1). Its catchment area is mostly in Goa, but also extends into the neighbouring states of Karnataka and Maharashtra. This choice is dictated by the following considerations. First, being one of the two rivers that flow past Panaji, the capital of Goa and the location of the National Institute of Oceanography, it is one of the best studied estuarine stretches in India, and is typical of the rivers along the west coast of India. Second, it is a small river, with a channel width less than 1 km over much of its 105 km length, making it a rigorous test of the DEM's accuracy: a DEM that works in this region should also work elsewhere in India. Third, discharge data are available for the Mandovi at one point, about 50 km from the mouth, making it possible to validate the framework. We conclude the paper by discussing the potential of this quantitative framework for quantifying the water resources of India. Figure 1: The topography of the region, as seen in GLOBE data (after editing the DEM). The superimposed rivers were digitised from the maps of the Survey of India. The domain of the simulations described in this paper lies mostly in Goa. The Mandovi and the Zuari are the two main rivers of Goa. The Mandovi flows into the Aguada Bay near Panaji, the capital of Goa and the location of its main meteorological observatory. A stream-flow gauge is located on the Mandovi at Ganjem; Valpoi has the easternmost rain gauge in Goa, but data for 1959 from Kulem, farther east, are available for 1959 (Anon, 1964). Application to the mandovi river in Goa The Mandovi is one of the two major rivers located in Goa, the other being the Zuari (Figure 1). The two rivers are connected by a narrow channel, the Kumbarjua Canal (Shetye et al., 1995); many tributaries also feed into the two rivers. The Mandovi, the Zuari, the Kumbarjua Canal, and the tributaries form a network. The cross-sectional area of both rivers decreases rapidly upstream (Shetye et al., 1995). Tidal influence is felt in the Mandovi just a little downstream of Ganjem (Figure 1), approximately 50 km inland, during the dry season (Shetye et al., 1995). The estuarine stretches (where at least some salinity intrusion occurs during the dry season) receive freshwater primarily from rivers that originate in the Sahyadris (or Western Ghats), but there is additional inflow at several points along the main channels. A stream-flow gauge is located on the Mandovi at Ganjem, just upstream of the limit of tidal and salt incursion. We use the GLOBE (GLOBE Task Team and others, eds., 1999) (Global Land One-km Base Elevation; see the GLOBE web site http://www.ngdc.noaa.gov/seg/topo/globe.shtml for more information) DEM, which has a  resolution of 30 arc seconds (~ 1 km). The topography of the region, as seen in the GLOBE data, is shown in Figure 1; the superimposed rivers were digitised from Survey of India maps and the good match shows that the GLOBE DEM is able to capture the watershed geometry fairly well. The elevation data are used to determine the local flow directions for each grid cell. Once the basin geometry is defined, HYDRA can be forced by prescribing the surface runoff and sub-surface drainage at each grid cell and integrating forward in time; for the GLOBE DEM used here, the model time step is 5 minutes. We force the model with the precipitation and evapotranspiration data from the NCEP/NCAR Reanalyses (Kalnay et al., 1996) (Case 1; see Table 1 for a brief description of the simulation cases). Since the NCEP/NCAR model resolution is 2.5o, a single NCEP/NCAR grid cell encompasses the entire basin, yielding a spatially uniform forcing field; its temporal variation is shown in Figure 2. The runoff required to force the model is the difference between precipitation and evapotranspiration (runoff is zero when the latter is greater), and the partition between surface runoff and sub-surface drainage is assumed to be the same as in Coe (Coe, 2000): 30% surface runoff and 70% sub-surface drainage. The result is that there is almost no discharge into the sea, most of the local runoff tending to accumulate in lakes 30-50 m deep! Since no such ``potential water areas'' (PWAs: regions where water can pile up, such as lakes or wetlands, and slow the flow through the river) are observed in the Mandovi basin upstream of Ganjem, this is due to the failure of the DEM to channel the runoff into and through the river.
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