Groundwater recharge modeling for sustainable agriculture in the context of climate change | |
| Author | Jimenez, Julius Incillo |
| Call Number | AIT Diss. no.RS-25-02 |
| Subject(s) | Groundwater recharge--Mathematical models Sustainable agriculture Climatic changes |
| Note | A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Remote Sensing and Geographic Information Systems |
| Publisher | Asian Institute of Technology |
| Abstract | This study addresses the pressing issue of groundwater sustainability in the context of climate change, employing remote sensing, geospatial amalysis, and hydrological modeling to evaluate groundwater recharge within the Padsan River Watershed (PRW), located in Northern Philippines. The methodology incorporates bias-corrected satellite climate datasets, such as CHIRPS for precipitation and ERAS-Land for temperature, processed via Quantile Mapping (QM) and simulated using the Soil and Water Assessment Tool (SWAT). The research assesses seasonal and long-term groundwater recharge, evapotranspiration (ET), river flow, and water balance under both historical and projected future climate scenarios. CHIRPS achieved a post- correction PBIAS of -0%, KGE of 0.927, and SDR near 1.0, while corrected ERA5-Land temperature metrics improved significantly, with TMAX NSE rising from -2.71 to 0.51, TMIN from 0.61 to 0.71,and TMEAN from 0.0065 to 0.69. These enhanced inputs led to a well- calibrated SWAT model (NSE = 0.57, R2= 0.66 0.71), enabling realistic hydrological simulations from 2003 to 2021. Results show that average annual groundwater recharge was 427.18 mm (18.18%) of the annual precipitation (2,312.09 mm),with the highest recharge observed in pasturelands (585.99 mm) and the lowest in range-grasses and agricultural areas. Spatial analysis revealed that only 11.06% of the watershed has high recharge potential, while 48.79% falls under unsuitable to less suitable classes. Climate projections using CMIP6 Shared Socioeconomic Pathways (SSPs) indicated a warming of up to +4°C and erratic rainfall shifts by 2100 under SSP585. Recharge increases were moderate across scenarios, with relative changes ranging from 24.32% (SSP370) to 27.68% (SSP126), though much of the gain risks becoming surface runoff without managed aquifer recharge (MAR) interventions. Seasonal imbalances were prominent: wet season residuals were positive, while dry seasons experienced deficits of-10 to-35 mm/month. ET was identified as the dominant hydrological loss, peaking during dry months, and soil moisture declined to 17.35 mm, posing critical stress for crops and shallow aquifers. To support climate-resilient groundwater and agricultural planning, the study developed a web-based Interactive Decision Support Framework I-DSF) hosted at https://geospadahub.com. Built with Django, PostGIS, and GeoServer, the I-DSF integrates recharge maps, climate projections, and sWAT outputs to aid farmers, irrigation managers, and policymakers in identifying high-recharge zones, scheduling irrigation, and guiding MAR investments. With only 27.85%ofagricultural lands under formal irrigation, the platform offers an cvidencc-bascd approach to cxpand cquitablc water access. The findings providc robust and transferable insights to inform integrated Water Resourcess Management (IWRM) in tropical, monsoon-influenced watersheds facing increasing climatic and anthropogenic pressures. |
| Year | 2025 |
| Type | Dissertation |
| School | School of Engineering and Technology |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Remote Sensing and Geographic Information Systems (RS) |
| Chairperson(s) | Tripathi, Nitin Kumar;Pandey, Ashish (Co-chairperson) |
| Examination Committee(s) | Shrestha, Sangam;Chao, Kuo Chieh |
| Scholarship Donor(s) | DOST-SEI Foreign Graduate Scholarships;AIT Scholarship;IIT Roorkee Scholarship |
| Degree | Thesis (Ph.D.) - Asian Institute of Technology, 2025 |