Chaitanya B. Pande

Indian Institute of Tropical Meteorology

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Fahad Alshehri

King Saud University

Kanak N. Moharir

Banasthali University

Ahmed Elbeltagi

Mansoura University

Subodh Chandra Pal

University of Burdwan

Abebe Debele Tolche

Haramaya University

Ismail Elkhrachy

Najran University

Abu Reza Md. Towfiqul Islam

Begum Rokeya University

Nitin Liladhar Rane

Swami Vivekanand College of Pharmacy

Muhammad Rashid

University of Engineering and Technology Lahore

Saif Haider

University of Engineering and Technology Lahore

Cooperative Institutions

King Saud University

Maharana Pratap University of Agriculture and Technology

Ministry of Earth Sciences

Mahatma Phule Krishi Vidyapeeth

University of Burdwan

Indian Institute of Tropical Meteorology

Indian Institute of Technology Roorkee

King Abdulaziz University

Purdue University West Lafayette

University of Engineering and Technology Lahore

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Assessment of land-use and land-cover changes in Pangari watershed area (MS), India, based on the remote sensing and GIS techniques

Applied Water Science (2021)

Chaitanya B. Pande Kanak N. Moharir S. Khadri

Abstract In this paper, we focus on the assessment of land-use and land-cover change detection mapping to the effective planning and management policies of environment, land-use policy and hydrological system in the study area. In this study the soil and water conservation project has been applied during the five years and after five years what changes have been found in the land-use and land-cover classes and vegetation. In this view, this land-use and land-cover mapping is a more important role to decide the policy for watershed planning and management project in the semiarid region. In an emerging countries, fast industrialization and urbanization impose a significant threat to the natural atmosphere. The remote sensing and GIS techniques are crucial roles in the study of land-use and land-cover mapping during the years of 2007, 2014, and 2017. The main objective of this is to prepare the land-use and NDVI maps in the years of 2008, 2014 and 2017; these maps have prepared from satellite data using the supervised classification method. A normalized difference vegetation index map (NDVI) was done by using Landsat 8 and LISS-III satellite data. NDVI values play a major role in monitoring the vegetation and variation in land-use and land-cover classes. In these maps, four types of land are divided into four classes as agriculture, built-up, wasteland, and water body. The results of study show that agriculture land of 18.71% (158.24 Ha), built-up land of 0.62% (5.31 Ha), wasteland of 40.33% (341.02 Ha), and water body land of 17.39% (147 Ha) are increased. Land-use and land-cover maps and NDVI values show that agriculture land of 22.97% (194.29 Ha), 5.46% (14.59 Ha), and 0.08% (0.22 Ha) decreases during the years of 2008, 2014, and 2017. The results directly indicate that the supervised classification method has been the accurate identified feature in the land-use map classes. This classification method has been given the better accuracy (95%) from spatiotemporal satellite data. The accuracy was also tally with ground-truth and Google earth information. These results can be a very useful for the land-use policy, watershed planning, and management with natural resources, animals, and ecological systems.

Land Cover

Land information system

Agricultural land

10.1007/s13201-021-01425-1

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Citations (61)

A comprehensive review on water pollution, South Asia Region: Pakistan

Urban Climate (2023)

Rabeea Noor Aarish Maqsood Azhar Baig Chaitanya B. Pande Syeda Mishal Zahra

CITES

10.1016/j.uclim.2023.101413

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Citations (59)

Exploration of groundwater potential zones using analytical hierarchical process (AHP) approach in the Godavari river basin of Maharashtra in India

Applied Water Science (2021)

J. Rajesh Chaitanya B. Pande S. A. Kadam S. D. Gorantiwar Mukund G. Shinde

Abstract Total natural and groundwater resources play the most crucial role in developing ecological, biological and socioeconomic doings. Various parameters like land use, geology, elevation, slope, lineament, lineament density, drainage density and geomorphology affect the groundwater development of recharge and its accessibility. In this research, geographical information system (GIS), remote sensing, weighted overlay analysis and analytical hierarchy process (AHP) methods have been used for groundwater prospects mapping, and identifying suitable solutions site for soil and water conservation structures. To calculate the weights were assigned to every layers component in the determination of affecting factors. The weighted overlay analysis (WOA) tool is applied to give the sub-parameter ratings based on the scientific literature. The final map of potential groundwater zone map has prepared using Arc GIS 10.1 software and AHP methods. About 49.71% of the areas fall under the 'good potential zone, 41.05% falls under the 'moderate potential zone', and 9.22% falls under the 'poor zone by using AHP technique. Groundwater potential zone map is depend on the weighted overlay analysis and analytical hierarchy process (AHP) methods. The highest GWP is located in the lower part of the basin due to the best surface runoff gathering, infiltration situations and subsurface storage volume. The present study procedure, methods and outcomes can be valuable to estimate the suitable groundwater zones parallel to improve the dry land area in the semi-arid and arid regions of India.

Drainage density

Lineament

10.1007/s13201-021-01518-x

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Citations (59)

Drought indicator analysis and forecasting using data driven models: case study in Jaisalmer, India

Stochastic Environmental Research and Risk Assessment (2022)

Ahmed Elbeltagi Manish Kumar Nand Lal Kushwaha Chaitanya B. Pande Pakorn Ditthakit

RSS

Irrigation scheduling

10.1007/s00477-022-02277-0

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Citations (65)

Developing flood mapping procedure through optimized machine learning techniques. Case study: Prahova river basin, Romania

Journal of Hydrology Regional Studies (2024)

Daniel Constantin Diaconu Romulus Costache Abu Reza Md. Towfiqul Islam Manish Pandey Subodh Chandra Pal

Prahova river basin located in the central-southern region of Romania. This study aims to assess the susceptibility to flooding by using state-of-the-art machine learning and optimization procedures. To achieve this goal, we employed ten flood-related variables as independent variables in our machine learning models. These variables include slope angle, convergence index, distance from the river, elevation, plan curvature, hydrological soil group, lithology, topographic wetness index, rainfall, and land use. We used 158 flood locations as dependent variables in the training of four hybrid models: Deep Learning Neural Network-Statistical Index (DLNN-SI), Particle Swarm Optimization-Deep Learning Neural Network-Statistical Index (PSO-DLNN-SI), Support Vector Machine-Statistical Index (SVM-SI), and Particle Swarm Optimization-Support Vector Machine-Statistical Index (PSO-SVM-SI). Utilizing the Statistical Index method, we calculated coefficients for each flood predictor class or category. The PSO-DLNN-SI model demonstrated the best performance, achieving an AUC-ROC curve of 0.952. It's worth noting that the application of the PSO algorithm significantly enhanced the model's performance. Additionally, it's crucial to highlight that approximately 25 % of the study region exhibits a high to very high susceptibility to flood events. Taking into account the very precise results of the models applied in the present study, we can state that from a hydrological point of view, the current research contributes to a better understanding of the intensity with which floods can affect the different areas of the Prahova river basin.

Topographic Wetness Index

10.1016/j.ejrh.2024.101892

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Citations (4)

Mapping Groundwater Prospective Zones Using Remote Sensing and Geographical Information System Techniques in Wadi Fatima, Western Saudi Arabia

Sustainability (2023)

Mohamed Abdelkareem Fathy Abdalla Fahad Alshehri Chaitanya B. Pande

Integration of remote sensing (RS) and GIS methods has allowed for the identification of potential water resource zones. Here, climatic, ecological, hydrologic, and topographic data have been integrated with microwave and multispectral data. Sentinel-2, SRTM, and TRMM data were developed to characterize the climatic, hydrologic, and topographic landscapes of Wadi Fatima, a portion of western Saudi Arabia that drains to the Red Sea. The physical characteristics of Wadi Fatima’s catchment area that are essential for mapping groundwater potential zones were derived from topographic data, rainfall zones, lineaments, and soil maps through RS data and GIS techniques. Twelve thematic factors were merged with a GIS-based knowledge-driven approach after providing a weight for every factor. Processing of recent Sentinel-2 data acquired on 4 August 2023 verified the existence of a zone of vegetation belonging to promising areas of groundwater potential zones (GPZs). The output map is categorized into six zones: excellent (10.98%), very high (21.98%), high (24.99%), moderate (21.44%), low (14.70%), and very low (5.91%). SAR CCD derived from Sentinel-1 from 2022 to 2023 showed that the parts of no unity are in high-activity areas in agricultural and anthropogenic activities. The model predictions were proven with the ROC curves with ground data, existing wells’ locations, and the water-bearing formations’ thickness inferred from geophysical data. Their performance was accepted (AUC: 0.73). The outcomes of the applied methodologies were excellent and important for exploring, planning, managing, and sustainable development of resources of water in desert areas. The present study successfully provided insights into the watershed’s hydrologic, climatic, vegetated variation, and terrain database information using radar, optical, and multi-temporal InSAR data. Furthermore, the applied multi-criteria overlay technique revealed promising areas for groundwater abstraction, which can be applied elsewhere in various environmental situations.

Wadi

Thematic map

Lineament

10.3390/su152115629

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Citations (4)

Monitoring of wetland turbidity using multi-temporal Landsat-8 and Landsat-9 satellite imagery in the Bisalpur wetland, Rajasthan, India

Environmental Research (2023)

Raj Singh Vara Saritha Chaitanya B. Pande

Turbidity

10.1016/j.envres.2023.117638

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Citations (18)

Quantifying the Impacts of Climate and Land Cover Changes on the Hydrological Regime of a Complex Dam Catchment Area

Sustainability (2023)

Muhammad Umer Masood Saif Haider Muhammad Rashid Mohammed Suleman Aldlemy Chaitanya B. Pande

In this study, hydrological modeling at the watershed level is used to assess the impacts of climate and land use changes on the catchment area of the Khanpur Dam, which is an important water source for Rawalpindi and Islamabad. The hydrological impact of past and anticipated precipitation in the Khanpur Dam watershed was forecast by using a HEC-HMS model. After calibration, the framework was employed to analyze the effects of changes in land cover and climate on the hydrological regime. The model used information from three climatic gauge stations (Murree, Islamabad Zero Point, and Khanpur Dam) to split the Khanpur Dam catchment area into five sub-basins that encompass the entire watershed region, each with distinctive characteristics. The model was evaluated and checked for 2016–2018 and 2019–2020, and it produced an excellent match with the actual and anticipated flows. After statistical downscaling with the CMhyd model, the most effective performing GCM (MPI-ESM1-2-HR) among the four GCMs was chosen and used to forecast projections of temperature and precipitation within two shared socioeconomic pathways (SSP2 and SSP5). The predictions and anticipated changes in land cover were incorporated into the calibrated HEC-HMS model to evaluate the potential impact of climate change and land cover change at the Khanpur Dam. The starting point era (1990–2015) and the projected period (2016–2100), which encompassed the basis in the present century, were analyzed annually. The results indicated a spike in precipitation for the two SSPs, which was predicted to boost inflows all year. Until the end of the twenty-first century, SSP2 predicted a 21 percent rise in precipitation in the Khanpur Dam catchment area, while SSP5 predicted a 28% rise in precipitation. Increased flows were found to be projected in the future. It was found that the calibrated model could also be used effectively for upcoming studies on hydrological effects on inflows of the Khanpur Dam basin.

Land Cover

Hydrological modelling

10.3390/su152115223

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Citations (17)

Hydrogeology and Hydrogeochemistry of Saline Groundwater Seepage Zones in Wadi Bani Malik Basin, Jeddah, Saudi Arabia: Impacts on Soil and Water Resources

Water (2023)

Mohamed ElKashouty Mohd Yawar Ali Khan Khalid H. Alharbi Chaitanya B. Pande Ali M. Subyani

The water seepage zone affects dryland salinity, soil sodicity, land degradation, waterlogging, and rainfall pollution. The priority in terms of the remediation measures was determining the cause of the seepages. Nine water and six soil samples were collected from the Al Tayseer area of the Wadi Bani Malik, Jeddah, Saudi Arabia (SA). The water samples were analyzed for major and toxic metals. For the soil samples, granulometric analysis and infiltration rate analysis were performed. The total dissolved solids (TDS) in water seepages ranged from 1880 to 54,499, whereas boron (B) and iron (Fe) values ranged from 1.9 to 38 mg/L and 0.02 and 0.47 mg/L, respectively. These concentrations were the same for the aquifer in Lake Al Misk, confirming that groundwater infiltration from the lake area was the main reason for the water seepage. The concentrations of silica (Si), aluminum (Al), cobalt (Co), nickel (Ni), zinc (Zn), arsenic (As), cadmium (Cd), chromium (Cr), copper (Cu), and lead (Pb) were low, indicating that there was no contamination. The nitrate (NO32−) value ranged from 2.2 to 35 mg/L, indicating agricultural wastewater contribution. According to the granulometric examination, most sediment was sand, followed by gravel, with few fine-grain particles. The infiltration rate ranged from 85 to 864 cm/d, indicating significant leakage. The percentage of ferrugination, ferromagnesian, OH-bearing, and carbonate (CO₃2−) minerals is determined by the 4/2, 5/6, and 6/7 band ratios.

Infiltration (HVAC)

Total dissolved solids

10.3390/w15193464

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Citations (2)

Dynamics of LULC changes, LST, vegetation health and climate interactions in Wetland buffer zone: A remote sensing perspective

Physics and Chemistry of the Earth Parts A/B/C (2024)

Raj Singh Vara Saritha Chaitanya B. Pande

Buffer zone

10.1016/j.pce.2024.103660

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Citations (2)