Browsing by Author "Sreejith, K.S."

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A Critical Review of the Soil Conservation Services – Curve Number Method in Hydrological Modelling
(Springer Science and Business Media B.V., 2024) Sreejith, K.S.; Kumar, G.P.; Dwarakish, G.S.
The Soil Conservation Service Curve Number (SCS-CN) method is popular for predicting surface runoff due to its simplicity, ease of application, and widespread acceptance. However, it has limitations, such as the neglect of storm duration, a lack of guidance on antecedent moisture conditions, and the assumption of a constant initial abstraction coefficient (λ = 0.2), leading to uncertainty. Its reliance on static land use classifications and empirical assumptions limits its accuracy across diverse geographic regions and complex hydrological scenarios, particularly under extreme weather conditions. Furthermore, selecting the most suitable watershed CN values remains a subject of global debate. Moreover, the model is widely applied beyond its originally intended purpose. Its basic assumptions, flexibility in dealing with different hydrological conditions, and susceptibility to variables including soil type, land use, and antecedent moisture conditions have all drawn criticism for the method. To overcome the original curve number method limitations, many studies have been made on improving the SCS-CN method. Despite these advancements, significant gaps remain, particularly in the method's applicability across diverse geographic regions and its accuracy in extreme weather events. This paper revisits the popular SCS-CN method, its history, development of methodology, limitations, and refinements that occurred to the original method with the progress of science and technology. It also explores the need for further research to improve its applicability, highlighting opportunities for more robust, flexible runoff estimation models. © The Author(s), under exclusive licence to Society of Wetland Scientists 2024.
Analysis of Land Use Land Cover Change Detection Using Remotely Sensed Data for Kali River Basin
(Springer Science and Business Media Deutschland GmbH, 2024) Sreejith, K.S.; Kumar, G.P.; Dwarakish, G.S.
For the last two centuries, the Earth's land cover has undergone fast change, and all indications indicate that this trend will continue. This shift is being driven by economic development and population expansion. For the management of natural resources and the observation of environmental changes, land use and land cover (LULC) change has become a key element. Natural landscapes have undergone significant change as a result of anthropogenic activity, particularly in areas where population increase and climate change have a significant impact. To effectively manage the environment, especially water management, it is essential to understand how trends in land use and land cover (LULC) change. This study used remote sensing and geographic information systems (GIS) to examine changes in LULC patterns during a 20-year period in the Kali River Basin. LULC changes were mapped using multitemporal Landsat series satellite images. Landsat-5 image of 2002 and Landsat-8 image of 2022 were obtained for the purpose of the study. Maximum likely hood algorithm was used to detect areas of change with supervised classification, performed in ERDAS Imagine 2014 and took minimum of 100 samples and maximum of 250 samples of ground truth data for each class. The supervised classification produced good results with overall accuracies of 91.58% and 89.47% for the 2002 and 2022, respectively. The results of the change detection analysis conducted between 2002 and 2022 demonstrate the extent of LULC changes that have taken place in various LULC classes, while the majority of the river basin's grassland, barren land, and open forest have undergone intensive conversion to cultivated land and built-up areas. These modifications show that population growth was responsible for the rise in cultivated land and built-up areas. Â© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
Runoff retention characteristics of forested and deforested catchments: an analysis using a spatially lumped model
(Taylor and Francis Ltd., 2023) Sreejith, K.S.; Varaparambil, P.
This study investigates the runoff characteristics of forested and deforested catchments using the Soil Conservation Services–curve number (SCS-CN) model from the perspective of the Kerala floods in 2018 and 2019. The forested and deforested catchments chosen for the study are the drainage area of the Kakkayam Dam and Punoor River respectively of Kozhikode District, Kerala. The study used input variables such as rainfall, land use/land cover (LU/LC) and soil data to estimate the runoff depth from these catchments during the floods in 2018 and 2019 using the SCS-CN model. Here, the hydrological response of these catchments is examined by different scenarios of rainfall and LU/LC change. It is found that the deforested catchment generates more runoff compared to the forested catchment under identical rainfall conditions. However, the study shows that, the runoff depth in the deforested catchment is expected to reduce if certain portion of plantations and barren land converts into the forest cover. The ability of runoff retention of the forested catchment is expected to lose if the forest-covered land is utilized for the plantation activities. © 2023 Indian Society for Hydraulics.
The Influence of Land Use and Land Cover Transitions on Hydrology in a Tropical River Basin of Southwest India
(Springer Nature, 2024) Kumar, G.P.; Sreejith, K.S.; Dwarakish, G.S.
The Kali River basin in Karnataka, India, is a vital hydropower resource, crucial to the state’s economy. Understanding the region’s hydrological processes and the factors influencing water availability is essential, with land use and land cover (LULC) change being a significant driver of these impacts. This study focuses on detecting LULC changes in the Kali River basin and assessing their effects on hydrological processes within the Supa Dam catchment area. Using satellite images from 1992, 2002, 2013, and 2022 and the ERDAS imagine tool, LULC classification was done with a supervised classification algorithm. The analysis revealed that from 1992 to 2022, the basin experienced a 5.97% decline in dense forest and a 5.64% decrease in open forest cover, while agricultural land expanded by 7.03%, and tree plantations increased by 1.49%. Water bodies increased by 1.44%, built-up areas and barren land rose by 0.97% and 0.76%, respectively, with grassland remaining stable. The impact of these LULC changes on hydrological processes was evaluated using the Soil and Water Assessment Tool (SWAT) model. Between 1992 and 2013, the model, which showed a surface flow increase of 212.83 mm, a water yield decrease of 46.10 mm, an increase in lateral flow by 37.95 mm, and a decrease in groundwater flow by 180.90 mm, with R2 and NSE values exceeding 0.60 for both calibration and validation, demonstrates satisfactory model performance. These findings underscore the importance of understanding LULC change impacts on streamflow to guide effective land management strategies and mitigate adverse effects on the watershed’s hydrology. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.