Mapping of flood affected agricultural land of Kahalgaon sub division of Bhagalpur district, Bihar

Introduction

The land, being a finite and non-renewable resource, plays a vital role in sustaining agriculture and livelihoods, especially in regions prone to natural calamities such as floods. Floods, as recurrent events in the Gangetic plains, drastically alter the agricultural potential of affected areas, disrupting cropping patterns and soil properties. The increasing frequency and intensity of floods, possibly exacerbated by climate change, call for robust land resource management to ensure food security and rural resilience (FAO, 1976; Halder, 2013) [7,8] . In this context, remote sensing (RS) and geographic information systems (GIS) have emerged as pivotal tools for spatial analysis and resource management (Bodaghabadi et al., 2019) [3] . Their integration allows for dynamic monitoring, risk assessment, and planning by utilizing satellite-derived information alongside topographic and soil data (Dwivedi, 2001; Kalra et al., 2010; De la Rosa, et al., 2004) [5,9,4] . Thematic maps over flood affected lands played a crucial role in aiding agricultural planners by providing essential information, ultimately contributing to the reduction of land degradation and facilitating assessments of sustainable land use. In supporting data base and within the framework of digital soil mapping, Multi Criteria Decision Making (MCDM) model was employed to establish connections between soil observations and auxiliary variables (Manna, et al., 2009) [11] . Auxiliary variables necessary for these models can be sourced from digital elevation models (DEM), remotely sensed data (RS), and other geospatial data sources (Mosleh, et al., 2017) [12] . Hence, remote sensing and GIS techniques were use used to prepare soil resources maps by using the satellite data of IRS-P6, LISS-IV, Cartosat-1 and Cartosat-2 for their database (Pereira, et al., 2022) [13] . However, GPS receiver was employed to collect soil samples from various locations together with their latitudes, longitudes, and other geospatial features to create soil fertility maps under the RS-GIS domain (Rawal, et al., 2018) [14] . Advanced geostatistical methods, including Inverse Distance Methods (IDW), variogram, krigging, and nugget algorithm was used for grid based soil resource mapping and their database generation (Rentschler, et al., 2019) [15] . GIS-based mapping of flood inundation, elevation and cultivated lands under lowland ecosystem were mapped for sustainable crop production, and better management of soil resources (Sys, et al., 1991) [16] . [1,12] . These methodologies also aided in transforming raw geospatial data into actionable insights for land use planning, mitigation, and restoration strategies (Manna et al., 2009; Pereira et al., 2022) [11,13] .

In Bihar, particularly in Bhagalpur district, flood-prone areas such as Kahalgaonand Pirpainti blocks require tailored interventions for sustainable agricultural management. Hence, the present study is based on RS-GIS tools to map the flood-affected lands, interpret spatial variability in elevation and slope, and identify agricultural land use transitions from Kharif to Rabi seasons. These insights are crucial not only for current land use planning but also for guiding future development strategies under stress conditions. Keeping of these facts in mind, the present study was carried out to trace out the flood prone areas and their temporal change in cultivated land for Rabi season.

Materials and Methods Study area

Satellite images, hard ware and software used

The multi spectral images of Landsat-8, MODIS V5 and SRTM data were used to map the flood affected lands, elevation, slope and water logged conditionof the area of interest. However, the administrative boundaries of the area of interest were traced out using topographical sheets with scales of 1:250000 and 1:50000, and the GPS receiver was used to ground truth and validation of data. In context of digital image processing, the computer system (HP Platinum 4 core processor) and QGIS software (Version 3.8.2) were used for the visual interpretation of satellite imagery, digitization and mapping. In order to validate the derived data, soil survey reports, topographical maps and auxiliary data were also used as references.

Methodology

In context of preparation of different thematic maps, satellite data of land sat 8 (2024) and Shuttle Radar Topographic Mission (SRTM) for elevation and slope analysis were downloaded, layer stacked and visually interpreted by using visual interpretation keys for the characterization of different land features and their mapping. However, digital image processing was applied for unsupervised classification, spectral enhancement and NDVI generation. In terms of analysis of crop response and water bodies analysis, spectral enhancement techniques were applied and mapped the flood affected area and related attributes. Finally, all the geodatabase were assessed, evaluated and ground truth for final map reparation towards assessment of the flood inundation and crop land. Hence, details of the methodology is summarized in a flow chart.

Results and Discussion

The spatial analysis revealed that the Kahalgaon subdivision (Kahalgaon and Pirpainti blocks) encompasses a heterogeneous terrain ranging from 25 to 61 meters above mean sea level. The elevation gradient showed a consistent decline from south to north, which aligns with the flow direction of the Ganges and makes the northern zones naturally more susceptible to flood water. Using Shuttle Radar Topographic Mission (SRTM) data, slope analysis categorized a significant portion of the land as having 0-1.5% gradient, indicated a gentle or flat terrain cause highly vulnerable to water stagnation during monsoons (Fig. 2 and Fig. 3). Flood mapping based on Landsat-8 imagery from September 2024, which was analyzed using unsupervised classification and spectral enhancement techniques indicated that approximately 16.27% of the total area was highly flood-affected. A further 24.56% was moderately impacted. These zones were primarily located in the northern parts of Kahalgaon and Pirpainti blocks, where meandering of the Ganges, combined with low elevation and poor drainage, results in repeated inundation. Such patterns are consistent with findings from similar studies in other parts of the Indo-Gangetic plains (Kalra et al., 2010; Rawal et al., 2018) [9,14] . Interestingly, post-monsoon NDVI imagery revealed the significant vegetative recovery in many of the flood-affected areas during the Rabi season, highlighting the resilience of alluvial soils and local cropping practices (Fig. 6). Crops such as wheat, lentils, and mustard were observed to grow in full swing on previously inundated fields, suggesting that these lands, although seasonally affected, remain agriculturally productive with appropriate water management and crop scheduling (FAO, 1976; Bera et al., 2017) [7,2] . In contrast, the southern part of the subdivision exhibited higher elevation and more rugged topography, with medium to upland zones supporting Kharif rice and maize cultivation. These areas showed no signs of flood inundation, thereby indicating their potential as floodresilient agricultural zones. Patches of degraded forest on hillocks in this region were also observed in NDVI imagery and could benefit from reforestation or agroforestry interventions to prevent further land degradation. The use of geostatistical techniques such as inverse distance weighting (IDW) and kriging enabled the generation of soil fertility maps and flood vulnerability maps, which together provide a valuable decision-making tool for stakeholders. These maps can help in delineating zones for crop diversification, introducing flood-tolerant varieties, or developing community-based watershed management systems (Pereira et al., 2022; Manna et al., 2009) [13,11] . Furthermore, the integration of satellite-derived data with ancillary sources such as topographic maps, soil surveys, and GPS-based field observations ensured the reliability and accuracy of the analysis. The thematic maps generated from this study not only support immediate disaster response but also aid in long-term land use planning, conservation agriculture, and sustainable development in flood-prone ecosystems (Behrens & Scholten, 2006; Mosleh et al., 2017) [1, 12] .

Conclusion

The present study was conducted to analyse the flood inundation impact on agricultural lands of Kahalgaon subdivision using RS-GIS-techniques. Analysed topographical features, and flood inundated lands using the interpretation of satellite image of land sat 8 of September 2024, it was observed that16.27% of the total area was found to be highly affected due to flood followed by was moderately affected (24.56%) and the rest of the land was not affected due to flood specially uplands of the Kahalgaon and Pirpainti blocks. The findings of this study can be also used by policymakers to develop an appropriate plan towards providing special agricultural incentive policies.

Future Scope of the Study

Research findings may be helpful to trace out the flood affected lands and their mitigation option through land suitability or land use planning. Outcomes will also be helpful to support to providing the supplementary data source for the initiation of the same type of research work in stressed land situation.

Acknowledgement

AcknowledgmentThe authors thankfully acknowledge to the Chairman of the Department of Soil Science and Agricultural Chemistry, BAU, Sabour for his kind support and laboratory facility during the academic research.

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