Water constitutes a fundamental element crucial for sustaining all forms of livelihood and represents the predominant natural resource distributed across the globe. Regions reliant on agriculture within a transboundary river basin encounter a multitude of challenges. Teesta, a crucial transboundary river shared by Bangladesh and India, holds significant importance in the bilateral relationship and sustains the livelihoods of over 30 million people in Bangladesh through subsistence agriculture (Prasai & Mandakini, 2013; Regmi et al., 2014). The basin, in particular, grapples with a multifaceted hydrological crisis characterized by the occurrence of recurring floods during the monsoon season and, conversely, droughts or acute water scarcity in the winter months (Das et al., 2022; Goyal & Goswami, 2018; Tamang, 2023). This complex situation is further exacerbated by extensive anthropogenic activities and the impact of climate change, culminating in a worrisome escalation of the frequency and intensity of these hydrological events on a daily basis (Ficklin et al., 2022; Knoesen, 2012; Tamang, 2023).
Land use and land cover (LULC) in the transboundary basin area are influenced by various factors like population growth, communication networks, technology, socioeconomic and institutional setup, ecology, altitude, geology, and slope ( Uddin et al., 2023; Guzha et al., 2018; L. Zhang et al., 2016). Development activities in the basin alter the hydrological cycle, water balance, radiation budget, and biodiversity, impacting climate, biogeochemical cycles, energy flow, and livelihoods (Guzha et al., 2018; Kiruki et al., 2017; Lambin & Meyfroidt, 2011; Yang et al., 2017; L. Zhang et al., 2016). Precisely assessing and predicting LULC change with complex human-natural interactions is challenging. LULC models, found in multiple disciplines, exhibit different characteristics such as static/dynamic, spatial/non-spatial, deductive/inductive, and agent-based/pattern-based (Girma et al., 2022; Kafy et al., 2021; Verburg et al., 2006; Noszczyk, 2019). The Cellular Automata-Markov (CA-Markov) model is widely used for simulating forest cover, urban development, and land use changes (Adhikari & Southworth, 2012).
Numerous studies have examined the impacts of LULC change on runoff. In the Andassa watershed of the Blue Nile Basin, Ethiopia, Gashaw et al. (2018) used SWAT to identify significant hydrological impacts of LULC changes. From 1985 to 2015, the basin experienced an increase in annual flow (2.2%), wet seasonal flow (4.6%), surface runoff (9.3%), and water yield (2.4%). Conversely, the dry season flow, lateral flow, groundwater flow, and evapotranspiration decreased by 2.8%, 5.7%, 7.8%, and 0.3%, respectively, during the same period. Guzha et al. (2018) showed that attributed increased stream discharges and surface runoff to forest cover loss. They estimates indicated that forest cover loss resulted in a 16 ± 5.5% increase in annual discharges and a 45 ± 14% increase in surface runoff. Peak flows showed a mean increase of 10 ± 2.8%, while low flows experienced a mean decrease of 7 ± 5.3%. Additionally, an increase in forest cover led to a reduction of 13 ± 1.9% in annual discharges and 25 ± 5% in surface runoff within the basin area.
H. Zhang et al. (2020) examining Land use change (four scenarios-based vegetation cover) and their impact on hydrological variables, it was observed that surface runoff experienced the most significant annual-scale changes (8.9%, 5.7%, − 9.5%, and 15.9% for scenarios 1, 2, 3 and 4, respectively). During the wet season (December to May), the absolute change in runoff resulting from land use changes was observed to be 1.2 ~ 6.6 mm, 1.0 ~ 3.5 mm, − 7.3 ~ -1.1 mm, and 3.0 ~ 9.0 mm for scenarios 1, 2, 3 and 4, respectively. The study also revealed that urbanization increased surface runoff (5.7% and 15.9% for scenarios 2 and 4, respectively) while causing a decrease in lateral runoff (− 0.7% and − 1.3%) and groundwater (-0.9% and − 3.5%). Gao et al. (2020) explore the prediction of hydrological responses to land-use change. Their findings suggested that projected land use in 2028 would lead to varying degrees of increase in flood peak and volume. For small-scale floods, a 3.5% increase in flood peak and a 2.9% increase in flood volume were projected., while the large-scale floods exhibited a decrease in peak and volume. Urbanization was identified as a factor contribution to flood occurrence.
Recent studies are confirming that the relationship between climate and the hydrological cycle is more intense day by day (Dutta et al., 2020; Islam et al., 2018; Khan & Ali, 2019; Mohammed et al., 2018; Mohammed, Islam, et al., 2017; Mohammed et al., 2017; Samjwal Ratna Bajracharya et al., 2007; R. Xu et al., 2019; Zannah et al., 2020). The magnitude and time of the river discharge are influenced by the changes in frequency and total precipitation, leading to modifications in mean discharges and variations in the intensity of floods and droughts (Immerzeel, 2008). Runoff changes over the basin area reflect the effects of climate change. In previous studies, the impact of climate change was analyzed using the Coupled Model Intercomparison Project Phase 5 (CMIP5) datasets, considering various climate change scenarios (Apurv et al., 2015; Gain et al., 2011; Mohammed et al., 2018; Pervez & Henebry, 2015). According to (Alam et al., 2016), the occurrence of 100-year return period flood is expected to increase by 3%, 7%, and 14% for the Ganges river basin, 4%, 5%, and 22% for the Brahmaputra, and 9%, 12%, and 42% for the Meghna basin at 1.5°C, 2°C, and 4°C temperature increase. While projections indicate a decrease in mean precipitation, some regions experience a substantial increase in extreme precipitation events( Islam et al., 2018; Mohammed et al., 2017).
This study will attempt to comprehensively analyze the combined effects of future LULC change and climate change on the runoff of the Teesta basin. Unlike previous research, which focused on either LULC changes or climate impacts separately, this study takes both into account. The overall objective of this study is to investigate and predict the impacts of LULC changes and climate on future runoff for the Teesta Basin at Dalia Point. To achieve this objective, the study encompasses the following three steps (i) To determine the existing LULC using satellite images and assess the runoff of the Teesta basin for the baseline (1995–2014) period (ii) To predict the LULC of the two future periods: 2050s (2035–2064) and 2080s (2071–2100) (iii) To assess combined impacts of LULC changes and climate change scenarios (SSP245 and SSP585) on future runoff for future periods (the 2050s and 2080s). The findings will enhance our understanding of potential flow pattern changes, aiding water resources management and adaptation strategies in the Teesta Basin.