This study takes a three-pronged approach to study and understand the water quality in inland water bodies – first, by developing and evaluating a methodology for monitoring nutrient contamination and its changes in inland water bodies using remote sensing satellite data; second, to hypothesize and study the probable source of the contamination as land use and its practices; and three, to understand, analyze and model the interactions between the land use changes in the contributing watershed and the water quality to help improve the regional-scale decision making capabilities. The case study area is Nagarjuna Sagar (NS) reservoir in the Krishna River basin, one of the largest inland water bodies in India. NS is a multipurpose dam and inland water body (reservoir) with a spatial spread of 285 Km2 and a catchment area of 215,000 Km2. In addition to Irrigation and Power generation, it is also a primary source of drinking water to Hyderabad, a large metropolis in India with nearly 10million population. All these make it essential to study and maintain the water quality of the NS water body.
The unique spectral signature of Chl-a was used to detect and identify its spatial spread across the water body. The research studied Lake Taihu (TL, with an area of 2250 Km2) and Lake Bebe (LB, with an area of 24 Km2) with different concentrations of Chl-a were used to test the sensitivity of the method. The Manasarovar Lake (ML) (area of 411 Km2) was used as a zero baseline case as it is free of any Chl-a contamination to check if the method was working without any false positives. The results from TL showed that more than 50% of the water body indicates the presence of Chl-a content which matched with the data given in the literature.
On applying the technique to study the contamination in the case study region of NS, the results indicated an increase in contamination from 21 Sq Km in 2005 to 205 Sq Km in 2018, showing nearly a ten times rise in contamination spread. In NS, large areas are covered by moderate Chl-a content with some patches of high concentrations. If necessary steps are not taken, then there is a risk that NS can get highly polluted like TL, a similar water body.
A Land use change in the watershed of NS was carried out to understand land use change and land use intensification practices like fertilizer application for the period 2005 to 2015 in the NS watershed was mapped and compared against the maximum Chl-a spatial spread observed in the water body measured using the MODIS data. The results show that over this period, the agricultural land use in the watershed increased by 40% or more than 1000 Sq Km in the area, and the fertilizer consumption increased by 50% in the same period. Correspondingly, the Chl-a spatial spread in the water body increased five times, from 21 Sq Km in 2005 to 106 Sq Km in 2015. This shows that there is indeed a strong relationship between the intensification of anthropogenic land use and its practices on inland water body nutrient contamination. In addition, the Sentinel data based analysis of Chl-a spatial spread area from 2016 to 2018 revealed that the contamination spread has further increased to 205 Km2.
Further SWAT hydrological model was used to quantify and assess the impact on the contamination levels for changing land use scenarios. The SWAT model was set up for the entire Krishna River basin. Then, to quantify the extent of the impact that land use and its practices can have on contamination levels, different land-use scenarios were developed and given input to the model. The four land use scenarios are – (1) Business As Usual scenario with and without fertilizers (BAUF and BAUNF), (2) Natural Forest Scenario (NFS), and (3) Anthropogenic Land use Scenario (ALS). While BAUF and BAUNF show the variations in nutrient output for current land use practices under varying hydrological conditions, NFS and ALS provide the lower and upper bound of the contaminants that could enter the water body. The simulations showed that the maximum yield of TN and Chl-a under the BAUF scenario was around 800 and 107 tonnes, respectively. While for BAUNF scenario, the maximum production of contaminants decreased by three times and 0.25 times that of the BAUF scenario, respectively, indicating that the application of fertilizers has a significant role on the water quality of the inland water body as it influences the production of the contaminants from the watershed. Thus, establishing the hypothesis proposed in this study. While the potential scenario analysis of NFS delivered the lowest TN and Chl-a content, the ALS scenario displayed a meteoric increase in the production of contaminants compared to BAUF. The maximum Chl-a output from the ALS scenario increased by around 6.5 times of the maximum Chl-a production simulated for BAUF conditions and TN increased by about two times.
The study was able to establish that the land use and the land use practices in the contributing watershed are mainly responsible for the changing levels of nutrient contamination in these land-locked water bodies, especially due to the excessive nutrient yield from the contributing watershed caused due to increased agricultural land use and excessive fertilizer application. Using a hydrological model SWAT and correlating its results with the remote sensing derived observations provides an opportunity to develop water quality monitoring systems to keep a watch on the deteriorating conditions of the water bodies and provide valuable inputs to the decision-makers to understand the regional land-water interactions. Future work in this direction can look at integrating these multiple approaches over a geospatial platform.
For the full PhD thesis, pls refer to IIITH Publications page.