Impacts of hydroclimate change on climate-resilient agriculture at the river basin management

Author:

Singha Chiranjit1ORCID,Sahoo Satiprasad2,Govind Ajit2,Pradhan Biswajeet34,Alrawashdeh Shatha5,Hamdi Aljohani Taghreed6,Almohamad Hussein7,Md Towfiqul Islam Abu Reza89,Abdo Hazem Ghassan10ORCID

Affiliation:

1. a Department of Agricultural Engineering, Institute of Agriculture, Visva-Bharati (A Central University), Sriniketan, Birbhum 731236, India

2. b International Center for Agricultural Research in the Dry Areas (ICARDA), 2 Port Said, Victoria Sq, Ismail El-Shaaer Building, Maadi, Cairo 11728, Egypt

3. c Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), School of Civil and Environmental Engineering, Faculty of Engineering and IT, University of Technology Sydney, Sydney, NSW 2007, Australia

4. d Earth Observation Centre, Institute of Climate Change, Universiti Kebangsaan Malaysia, Bangi, Selangor43600 UKM, Malaysia

5. e Department of Geography, Faculty of Art, Al-Hussein Bin Talal university, Ma'an, Jordan

6. f Geography Department, Faculty of Arts and Humanities, Taibah University, Medina, Saudi Arabia

7. g Department of Geography, College of Arabic Language and Social Studies, Qassim University, Buraydah 51452, Saudi Arabia

8. h Department of Disaster Management, Begum Rokeya University, Rangpur 5400, Bangladesh

9. i Department of Development Studie, Daffodil International University, Dhaka 1216, Bangladesh

10. j Geography Department, Faculty of Arts and Humanities, Tartous University, Tartous, Syria

Abstract

Abstract This paper focuses on exploring the potential of Climate resilient agriculture (CRA) for river basin-scale management. Our analysis is based on long-term historical and future climate and hydrological datasets within a GIS environment, focusing on the Ajoy River basin in West Bengal, Eastern India. The standardized anomaly index (SAI) and slope of the linear regression (SLR) methods were employed to analyse the spatial pattern of the climate variables (precipitation, Tmax and Tmin) and hydrological variables (actual evapotranspiration (AET), runoff (Q), vapor pressure deficit (VPD), potential evapotranspiration (PET), and climate water deficit (DEF)) using the TerraClimate dataset spanning from 1958 to 2020. Future climate trend analysis spanning 2021 to 2050 was conducted using the CMIP6 based GCMs (MIROC6 and EC-Earth3) dataset under shared socio-economic pathway (SSP2-4.5, SSP5-8.5 and historical). For spatiotemporal water storage analysis, we relied on Gravity Recovery and Climate Experiment (GRACE) from the Center for Space Research (CSR) and the Jet Propulsion Laboratory (JPL) data, covering the period from 2002 to 2021. Validation was performed using regional groundwater level data, employing various machine learning classification models. Our findings revealed a negative precipitation trend (approximately −0.04 mm/year) in the southern part, whereas the northern part exhibited a positive trend (approximately 0.10 mm/year).

Publisher

IWA Publishing

Subject

Management, Monitoring, Policy and Law,Atmospheric Science,Water Science and Technology,Global and Planetary Change

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