Albeit numerous benefits of adding cover crops to existing cropping systems, there is an existing knowledge gap regarding the magnitude and long-term effect of regional cover crop installation. 

• Along with the positive environmental impacts of cover crops, what are their effects on agricultural water balance?

• Is a regional installation of cover crops a viable option to counteract the negative impacts of climate change on agricultural water availability? 

To address this questions, we utilized a calibrated Soil and Water Assessment Tool (SWAT) to model some scenarios

Enhancing resilience in agricultural systems involves implementing Agricultural Water Management (AWM) practices to mitigate risks, improve resource management, and promote adaptive strategies that ensure sustainable productivity despite vulnerabilities. 

This study employed a water footprint (WF) accounting framework to quantify water usage and allow an assessment of the fluctuations brought about by changes in land use (winter cover crop installation) under changing climate conditions

We examined how the resilience of an agricultural watershed can be impacted by strategic AWM specifically the use of cover crops. 

Presently, most research tends to focus on the one-way impact of anthropogenic factors such as groundwater pumping and land use on the water cycle. There is an absence of literature that documents the feedbacks and unanticipated emergent dynamics between social and hydrologic systems. Social system models often neglect the heterogeneity of individuals’ objectives, knowledge, and risk tolerances, resulting in oversimplified behavioral modeling and thereby unrealistic social interactions with physical models . This leaves an incomplete understanding of many critical questions, such as how attitudes, norms (such as awareness, and a sense of personal responsibility, perceived behavioral control, or peer pressure influence decisions, how environmental elements influence decision making, and how humans respond to policies that constrain water use. Answering these questions requires an examination of a complex interplay of sociological factors and environmental elements in irrigation decision-making processes. 

We developed an agent-based model (ABM) in order to simulate irrigation behaviors in response to physical constraints and surface and groundwater dynamics. The ABM allows the representation of complex decision-making processes by defining collective actions using predefined behavioral rules. 

We employed a two-stage multivariate analytical approach, using Principal Component Analysis (PCA) and cluster analysis, to construct the farmer typologies. Thus, PCA was used to reduce 54 different variables into a new set of components measuring key latent constructs

Using PCA, selected scale variables were used to construct factors. These factors were rotated using the varimax method (this process tries to load a smaller number of highly correlated variables onto each component resulting in easier interpretation).