The agricultural sector is evolving with the adoption of smart farming technologies, where Digital Twins (DTs) offer new possibilities for real-time monitoring, simulation, and decision-making. While previous research has explored the Internet of Things (IoT), UAVs, machine learning (ML), and remote sensing (RS) in enhancing agricultural efficiency, a systematic approach to integrating these technologies within a DTs ecosystem remains underdeveloped. This paper presents a systematic review of 167 studies published between 2018 and 2025. The objective of this study is to examine recent advancements in DTs-enabled precision agriculture and propose a comprehensive framework for designing, integrating, and optimizing DTs in smart farming. The study systematically examines the current state of DT adoption, identifies key barriers, and computational efficiency challenges, and provides a step-by-step methodology for DT implementation. The review sheds light on potential future research direction and implications for policy, with the aim to speed up the adoption of DTs-based farm management systems in their operational success and commercial viability through analysis of practical applications and future perspectives. This study presents an innovative strategy for integrating digital and physical systems into agriculture and is an important contribution to existing literature.

The fate of agriculture in Pakistan is predominantly concerned with excessive water mining threats to the subsurface water resources. The current study integrates the Visual MODFLOW-2000 application to estimate the water balance of an aquifer bounded by the Chenab River in the West and the Ravi River in the East, which covers an area of about 2.98 million hectares. An assimilated method of groundwater flow is employed to characterize the flow dynamics of the Rechna Doab aquifer. The Digital Elevation Model (DEM) produced by the Shuttle Radar Topography Mission (SRTM) and a mesh of discretized cell size (2500 m) were incorporated into the model design. The conceptual model of the alluvial aquifer involves trifold vertical boundaries (an initial fold thickness set up to 150 m). The model input parameters are precipitation, seepage through irrigation, return flow, recharge, hydraulic conductivity and evapotranspiration. Empirical relations are established (at the basin scale) for the discharge input of irrigation canals. Model results confirm that groundwater flow follows the topographic configuration of the study area (i.e., northeast to southwest), and the seepage from irrigating canals and rainfall appeared to be the main source of groundwater recharge among various resources. The zone budget study under steady state simulation showed that the total direct recharge to the aquifer is calculated as 522,910 acre foot. The simulated water balance of the studied aquifer reflects more fluctuations in river leakage. The predictive optimized model reflects an adaptation of canal lining and installation of additional tube wells that will minimize canal seepage by 70% and lead to the reclamation of 37,000 acres of water-logged land for normal cropping.

Mitigating climate change by reducing heat-trapping greenhouse gas (GHG) emissions in the Earth’s atmosphere is a critical global challenge. In response to this urgency, the Canadian government has set a target of achieving zero emissions by 2050. The Government of Prince Edward Island (PEI) has committed to becoming Canada’s first net-zero province by 2040. Achieving this goal requires an extensive knowledge of emissions arising from ecosystem dynamics in PEI. Therefore, this study aims to quantify the carbon fluxes of these ecosystems, offering insights into their role in GHG emissions and removals. Through an extensive literature review and analysis, this research provides a detailed assessment of the potential carbon flux contributions from various ecosystems across PEI. High-resolution maps for carbon emissions, removals, and flux for the years 2010 and 2020 were developed, highlighting key findings on carbon dynamics. Additionally, a web-based tool was developed to allow decision makers and the general public to explore these carbon flux maps interactively. This work aims to inform policy decisions and enhance strategies for effective climate change mitigation in PEI.