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Summary

Landscape composition has a central role in water cycling and managing the quality and availability of water in the region. However, in recent decades, human activities have significantly altered the landscape composition; major reason being the disturbance and fragmentation of landscape which are the outcomes of unplanned development and the growing demand of the burgeoning population. This has resulted in decline in both quality as well as quantity of the pristine forest which has led to the changes in regional hydrology, raising the concern to understand the impact of landscape degradation on the hydrological regime. Thus the need to understand the coupled interaction between land use and water resources, which is essential to enhance the sustainability of water resources in a region, is of paramount importance. In this context, present study has been carried out to explore and quantify the hydrological components of the Aghanashini River Basin of Karnataka, India and determine the consequences of the land use changes, at the sub-basin level, on the water availability of the region. Global availability of temporal remote sensing data has helped in analyzing the land use condition of the region at different epochs. The result of the investigation suggests groundwater recharge to be a function of the structure of landscape in the region. It also underscores that the sub surface flow which is responsible for the low flows in the river, is a function of vegetation cover in the region.
Key Words: Land Use, Hydrological Cycle, Fragmentation, Interior forest, Groundwater Recharge and Water Yield
1. Introduction
Landscape is any heterogeneous area comprising of different interacting ecosystems that are repeated in a similar fashion (Forman & Godron, 1986). Landscape is seen as a spatial expression of the ecosystem (Burel, 2004).Different units or different elements like patch of forest and stream corridor present in a landscape constitute landscape structure. The interactions between these different elements results in flow of nutrients, energy, water, etc between the different ecosystems, which constitute the landscape function. These interactions maintain the dynamisms in the ecosystems. Changes in any of the landscape structure caused either due to natural disturbances (floods, volcanic eruptions, etc) or anthropogenic factors result in the changes in the functioning of the landscape and vice-versa.
Human activities have caused explicit changes in the landscape on a global scale. Human led deforestation, urbanization and increase in other land use activities are important contributors to the myriad of changes in landscape pattern and processes (Turner et al., 2001).The causes of these changes are multifaceted but are driven by population growth, politics and pattern of economic development (Paulson, 1994; Gretchen, C D 1995 and Ruder & Roper, 1996). These factors have resulted in the fragmentation of the landscape (Forman & Godron, 1986).
Fragmentation is regarded as the breaking of a landscape into small parcels of land which is mostly human guided, like encroaching of forest area for agriculture or plantation, building of roads and impoundments, coming up of urban areas in undisturbed forest area, etc. Thus, fragmentation is considered as the dissection of the earth’s surface into spatially isolated parts; rearranges the structure of the ecosystem and shapes their function worldwide (Hobbs et al., 2008). Hence it has emerged as a central force in driving global change
Fragmented landscapes, now common in existence, consist of remnant forest patches and various human-disturbed land covers, which are degraded both ecologically and physically (Ziegler et al., 2004). This structural degradation has influenced the functioning of landscape on a global scale.
One of the major functions of the landscape is the cycling of water between terrestrial ecosystem, aquatic ecosystem and the atmosphere which is essential for the sustenance of life on Earth. Evaluating the impact of land use change on water and matter fluxes is a major challenge in hydrological research (Breuer et al., 2009).
A hydrologic cycle is an assemblage of various components that include precipitation, evaporation, runoff, subsurface flow and ground water flow. Although the concept is simple, but the phenomenon is enormously complex and intricate as it is influenced by various meteorological phenomenon (like intensity of rainfall) as well as physical factors like topography, geology and vegetation. Apart from this, in recent decades human activities have significantly altered the dynamic equilibrium of hydrological cycle as these responses are highly sensitive to land use changes. Hence manifestation of land use and its management may have significant hydrological impacts by either enhancing or retarding infiltration, thereby reducing or enhancing the stream flows (Schulze, 2000). Thus, understanding the consequences of land-use change for hydrological processes and integrating this understanding into planning is an emerging focus of land-change science (Turner et al., 2003). These consequences include changes in water demand from changed land-use practices, changes in water supply from altered hydrological processes like infiltration, groundwater recharge, stream flow, etc and changes in water quality from agricultural runoff and suburban development (DeFries, 2004).
Various studies (Sikka et al., 1998; Van Lill et al., 1980 and Scott & Lesch, 1997) provide evidence to support the assumption that conversion of natural forests to other land use practices (agriculture, pasture land & horticulture) have led to soil compaction, reduced infiltration, groundwater recharge & discharge and rapid & excessive runoff which ultimately affect the flow of water from the landscape. Bruijnzeel (1989) establishes that, following clearance of tropical forest land, there is an increase in annual runoff. The actual increase depends on numerous factors such as forest types, rainfall regime, soil type, soil depth and topography (Bosch & Hewlett, 1982). Thus concerns about the impact on water resources on changing patterns of land-use associated with deforestation and agricultural transformation have created social and political tensions from local to national level (Rattanaviwatpong et al., 2005). Schulze (2000) found out that intensification of LU, like conversion of natural grass cover to exotic plantation may increase the canopy interception, enhances the infiltration and consequently higher transpiration, resulting in lesser storm runoff generation as well as lesser water percolating the ground zone to feed the base flow store, which ultimately results in lesser flows in the stream. On the other hand, degradation of vegetation in the land reduces the infiltration capacity of the region which may increase the risk of flash flood in the catchment with enhanced peak discharges and sediment yield. James et al., (1987), also found out that the sediment yield from the exploited basins is much more than the basins that have dense forest cover. Thus forest and water are intrinsically intertwined (Bruijnzeel, 2001) and forest removal produces wide range of hydrological responses (Hibbert, 1967; Dunne & Leopold, 1978; Bosh & Hewlett, 1982 and Bruijnzeel, 2001).

Despite of these studies, realm of hydrological consequences associated with the degradation of forest or conversion of forests to other land use categories and fragmentation is not clearly understood (Ziegler et al., 2004) and still a cause of controversy and debate. In addition, there is worldwide concern about the detrimental effect associated with the exotic monoculture plantations, which are often done on the degraded and open land in forests, with the focus on the changes in the water yield that these monoculture species cause in the catchment (Purandara et al., 2010).With this intent, the objective of the present study is to focus on the influence of land use on amount of water available in various sub systems of hydrological cycle.
Analysis of the hydrological impacts of land use change has been made feasible by observing land-cover changes through the availability of satellite data which was not possible a decade ago. Information of land-use over larger areas allows new kind of investigations, such as, the effects of spatial patterns of land-use within a watershed on hydrological processes and also mapping and modeling of large drainage basins (DeFries, 2004). Satellite remote sensing now has a potential of providing extensive coverage of key variables such as precipitation (Smith et al., 1996; Sturdevant-Rees et al., 2001), soil moisture (Sano et al., 1998), flooding (Townsend & Foster, 2002), imperviousness (Slonecker et al., 2001), etc which can be used as input to various hydrological models. Thus, recent studies also focus on the potential of an integrated modeling approach to evaluate the impact of land use changes on water resources (Lin et al., 2007 and Bithell & Brasington, 2009). Further, with the aid of Geographic Information System (GIS) it is possible to combine all the spatial layers and bring them in one domain for holistic analysis.

2. Material
2.1 Study Area: The study has been conducted for Aghanashini River, which is one of the westwards flowing rivers in Western Ghats, in Uttara Kannada district of Karnataka, India; lying between 14.39° to 14.58°N latitude and 74.30° to 74.51°E longitude. The Western Ghats form an area of hectic activity as far as water resources development is concerned (Putty & Prasad, 2000). This signifies the importance of simulating various components of hydrological cycle (as affected from land use) in this catchment.

 
Fig. 1: Study region, Aghanashini river basin in Uttara Kannada District, Western Ghats, Karnataka, India

Aghanashini River originates in Sirsi taluk of Uttara Kannada district at an elevation of about 1800ft above the sea level and it encompasses a catchment area of 1370sq.km. with a length of 121km (Fig. 2a). During its course, it forms beautiful falls like Lushington (or Unchalli) falls and Burude falls and flows thorough three major taluks of the district namely Kumta, Sirsi and Siddapur. After making a 13km long estuarine expanse in the coastal zone of Kumta taluk, it finally discharges into the Arabian Sea. Since the River has a large catchment area, hence for the analysis purpose it was divided into seven sub catchments, where each sub catchment was considered as a hydrological response unit (HRU), assumed to be homogenous in hydrologic response to land cover change (Fig. 2b).

Topographic information about the region was obtained from the Shuttle Radar Topography Mission (SRTM) data from the CGIAR Consortium for Spatial Information (CGIAR-CSI) at 90m spatial resolution. Digital Elevation Model (Fig. 3a) and Slope Map (Fig. 3b) was generated from this data.

Other ancillary data include Geology/soil texture map (Fig. 4a) and Lithology/ Rock type map (Fig. 4b) of the region obtained at 1:250,000 scale from French Institute.

Fig. 4: Soil Texture Map (a) and Rock type Map (b) of the Aghanashini River Basin

3. Methodology
The overall methodology is shown in Figure 5 and briefly described in the following section.

Fig. 5: Methodology adopted in the study

Obtained satellite images were first processed, wherein all the acquired data sets were georectified, resampled and then cropped using the delineated watershed boundary. For land cover analysis, Normalized Difference Vegetation Index (NDVI) of the region was generated using NIR and Red band, which gives the information about the vegetated and non-vegetated (crop land, barren land, water body, etc) areas.
Supervised classified of the images (corresponding to the watershed area) was done through maximum likelihood classifier (MLC) for Land Use (LU) analysis. Obtained LU maps were assessed for their accuracy through generation of error/confusion matrix, referring to the data collected from the field, which was selected in such a way that they are uniformly distributed over the region and can be easily identified on the satellite imagery.
LU maps indicate only the location and type of forest, and further analysis is required to quantify the forest fragmentation (Ramachandra et al., 2009). Thus, for the fragmentation analysis of the region, model developed by Ritters et al., (2000) was considered, whose details are specified elsewhere (Hurd et al., 2001 & 2002). The model calculates Pf (Proportion of forest) and Pff (Connectivity of the forest) values in the region based on a moving window analysis which helps in characterizing the forest pixel located at the centre of the window.  It allows easy visualization of the extent of forest fragmentation and also tracks the changes in the fragmentation over time.
Based on Pf and Pff values, forest area is classified into six different categories (Ritters et al., 2000) namely, Interior forest (Pf=1, where all the pixels surrounding the centre pixel are forest); Edge forest (Pf>0.6 and Pf-Pff<0); Perforated forest (Pf>0.6 and Pf-Pff>0); Transition forest 0.4<Pf<0.6); Patch forest (Pf<0.4) and Undetermined forest (Pf>0.6 and Pf-Pff=0).
Hydrological phenomenon vary in all the three space dimensions and thus explicit accounting of all the variables makes modeling a cumbersome approach. Hence empirical method is considered, where a real world situation is represented through some mathematical equations and statistical analysis is done to find relationship between different variables.
In general, water cycle is guided by the law of conservation of mass in which no water is gained or lost, but the amount of water available to the user may fluctuate, due to variation in the source or in delivering system (Raghunath, 1985) and is given by:

I= O + ∆S                                                                             (1)

Where I= inflow, O= outflow and ∆S is the change in the storage.
The output from a watershed system includes various abstractions like Interception (amount of rainfall held by the vegetation canopy); Evaporation (loss of water from the free water and soil surface); Transpiration (loss of water from plant leaves); Evapo-transpiration (from irrigated or cropped land); Infiltration loss (entry of surface water into the soil and held within the soil pores); Surface Runoff (Infiltration excess rainfall that flows over the surface) and Sub surface flow (interflow which is flow of water from the vadose/unsaturated zone to the stream and baseflow which is groundwater flow to the stream), that are deducted from the precipitation (input) to compute the net storage amount. Equations used to compute various hydrological parameters are enlisted in table 2 along with the values (table 3-5).

Table 2: Hydrologic parameters and the equations to compute them

Table 3: Values considered for the computation of hydrological parameters for different land use types

Table 4: Values for Field Capacity (FC) and Available Water Capacity (AWC) for different soil types

FAO: Food and Agriculture Organization; USDA: United States Department of Agriculture

Table 5: Different coefficient values based on characteristics of the sub-basins

4. Results and Discussion
4.1 Land Cover Analyses:
Land Cover analysis of the year 2010 (Fig.6) shows that 65.76% (997.61 sq.km.) of the entire catchment area is vegetated (forest and plantations) while the remaining 34.24% is non-vegetated (crop land, barren land, water body, aquaculture, etc).

Fig. 6: Land Cover Analysis of the Aghanashini river basin

4.2 Land Use Analyses
LU details of each sub-basin of the region since 1971 are shown in Fig 7. The change in area of each class for the entire watershed (Table 6) shows that evergreen forest decreased drastically (29.82%) in all the sub-basins during the period of 1972-1989, but remained almost stagnant after that. While deciduous forest initially increased by 21% but thereafter no significant change was observed. Areca plantations have increased manifold by 2010 due to their great economic value.

Table 6: Change in land use classes

4.3 Fragmentation Analyses
Temporal fragmentation index maps obtained after computing Pf and Pff for all the sub-basins has been shown in figure 8 which qualitatively shows the status of forests in the region.

Results showed that the sub-basins like sub-basin 1 (which is near the coast) and sub-basin 6 and 7 (which include densely populated taluks like Sirsi and Siddapur) have witnessed significant decline in interior forest and increase in patch and edge forest due to greater human exploitation in these areas. Whereas sub basins 3 and 4 which have steep slopes and difficult terrain (evident from figure 3b) and thus less exposed to anthropogenic activities, still have 40% of the area under interior forest.
4.4 Hydrological Investigation
For the hydrological assessment, rainfall of the taluks Kumta, Sirsi and Siddapur were analyzed for annual as well as monthly variation (Fig. 9). Annual rainfall analysis shows that the rainfall in the region follows a periodic pattern within a time span of 5-10 years.

Monthly rainfall analysis of the taluks shows that the region receives quantifiable amount of rainfall (input) during the period of June-Oct and for the rest of the months there is only withdrawal (output). Hence only these months were considered for the computation of different parameters.
Subtracting the different abstractions (interception, evapotranspiration, surface runoff, sub surface flow, infiltration loss), determined by various equations specified in the methodology section, from the rainfall gives the net amount of recharge. Figure 10 shows the spatial distribution of rainfall and recharge over the entire region for the time periods corresponding to the available land use data.

It can be seen in figure 10 that sub-basin 4 having greater area under evergreen forest has comparatively higher recharge for all the years while sub-basin 1 which has least percentage of area under evergreen forest has lowest recharge among all the sub-basins for all the years.

Following this, statistical analysis was done to understand the relationship between various independent parameters. Paired t-test analysis conducted at 5% significance level (95% confidence level) showed that the rainfall and interior forests (considered to be independent parameters) have significantly changed over the time period in the region. Further the link between various hydrological parameters and land use (primarily interior forest and plantation) has been estimated by generating the correlation matrix (Table  7).

Table 7: Correlation matrices of different parameters for different years

*Water Yield is sum of surface runoff, interflow and baseflow
In the correlation matrices, values on the right above the diagonal values show the p-value (significance level) for the null hypothesis stated as the variable are not inter-related. The values on the left below the diagonal values show the correlation coefficient. The highlighted values are those that have p-value below 0.05 (5% significance level) for which null hypothesis can be rejected and the alternate hypothesis stating that the variables are significantly correlated can be accepted.
From the matrices it can be inferred that interior forests, plantations are strongly positively correlated to the rainfall. Thus it verifies the rarely documented but often stated fact (LØrup et. al., 1998) that “forests attract rainfall”. Recharge is also strongly positively related to rainfall throughout; giving the evidence that groundwater recharge is always dependent on the amount of rainfall that a region receives. Also there is strong positive relation between interior forests and infiltration and consequently with recharge for 2006 and 2010 implying that core/pristine forests promote percolation of water into sub surface system and thus ground water recharge. Plantations also have shown positive correlation with the recharge throughout the time period. In addition, for all the years, runoff has shown negative correlation with the interior forests and positive with plantations inferring that the deep roots of the forests prevent surface runoff while plantations having shallow rooting system lack that capability. As a consequence, plantations were found to have strong positive relation with the water yield (dominated by runoff) obtained from the system.
On plotting land use with individual hydrological parameter (figure 11), it was observed that the sub-basins having greater proportion of area under Interior forest have higher rainfall, lesser runoff but higher interflow which contribute to greater water yield (sum of surface runoff, interflow and baseflow) from such sub-basins. Baseflow was found to be higher for the sub­­-basin 5 in comparison to other sub-basins due to higher specific yield of the Greywacke rock type.

Fig. 11: Relationship between Rainfall and Runoff (a); Interior forest, Runoff, Interflow and Base flow (b); Rainfall, Interior forest and Water Yield (c) and Interior forest, Rainfall, Runoff and Recharge (d)

4.5 Water Balance Analysis
Water balance is analysis done with respect to the demand and supply of water to understand the deficit and surplus water. The main stakeholders considered for this analysis are population of the region, livestock, agriculture area to be irrigated and areca plantations (Fig. 12 and Fig. 13). Table 8 shows that, for the entire watershed area, available water was surplus in 2010.

Fig. 12(a) Number of household in a village, (b) Population density of each village

Fig. 13 (a) Water requirement of (a) human population, (b) livestock

Table 8: Water Balance for the year 2010

4.6 Sustainability of the catchment yield
Irrigation water requirement for the non-monsoon season was computed for each sub-basin for the year 2010 and compared with the water yield (only interflow and baseflow, as they are responsible for the non-monsoon flow in the stream) in the sub-basin. Figure 14 shows that the sub-basin 4 and 5 having greater proportion of area under interior forest have very high water yield in comparison to the irrigation requirement, while sub-basin 1 and 2 having negligible area under interior forest has very less water yield. Due to excessive water yield in the sub-basins 4 and 5, the streams are perennial here while the streams of sub-basins 1 and 2 get dry after the cessation of monsoon, which has been verified through field visits as well.

Table 9: Irrigation requirement at the sub-basin level in 2010

Fig. 14: Water Budget at the sub-basin level for 2010

5. Conclusion
From the analysis, done to assess the effect of land use on water resources in the region in non-experimental (empirical) way, it can be concluded that the status of landscape has significant effect on controlling the water availability in the region. The results obtained show that, whilst the overall percentage of interior forest in the catchment has shrunk since 1972, still the sub-basins having relatively greater proportion of area under interior forest have greater water yield in comparison to sub basins with fragmented forest. Furthermore, from the correlation analysis it was established that pristine forests have lesser surface runoff and higher groundwater recharge that result in higher low flows. As a consequence, the streams are perennial in such regions. In addition, water balance analysis shows that catchment yield of only those sub-basins is sustainable that have greater proportion of area under interior forest. Thus landscape structure has much important role in determining the water resources in the region, rather than just acting as a driver of hydrological cycle.

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