The sustainability of grazing lands lies in the nexus of human consumption behavior, livestock productivity, and environmental sustainability. Due to fast growing global food demands, many grazing lands have suffered from overgrazing, leading to soil degradation, air and water pollution, and biodiversity losses. Multidisciplinary efforts are required to understand how grazing lands can be better monitored, assessed and managed to attain predictable outcomes of optimal benefit to society. This paper synthesizes our understanding based on previous work done on impacts of grazing on ecosystem goods and services, identifies current knowledge gaps, and formulates a plan forward. We review the impacts of two contrasting grazing systems, continuous and multi-paddock rotational grazing, on soil carbon (C), nutrient cycling and greenhouse gas emissions (GHGs). We then extend our review to explore challenges of incorporating spatial heterogeneity and temporal variability into monitoring and modelling C and nutrient cycling in grazing lands. We revisit two process-based models (i.e., DNDC and DayCent) and two watershed models (i.e., SWAT and VIC) widely used to simulate C, nutrient and water cycles of these lands. Finally we identify research directions for improving the knowledge base which is essential to conserve grazing lands and maintain their ecosystem goods and services.

Groundwater is a vital resource for human welfare. However, due to various factors, groundwater pollution is one of the main environmental concerns facing. Yet, it is challenging to simulate groundwater quality dynamics due to the insufficient representation of nutrient percolation processes in the soil and Water Assessment Tool model. The objectives of this study were extending the SWAT module to predict groundwater quality. The results proved a linear relationship between observed and calculated groundwater quality considering No3 and TDS with R2, NSE and PBIAS values in the satisfied ranges, albeit underestimation and overestimation were observed due to limited data availability. These results highlight that nitrate and TDS concentrations and variability in groundwater may used as a tool in surface water quality that have to be assumed for designing adaptive management scenarios. Hence, extended SWAT model could be a powerful tool for future regional to global scale modelling of nutrient loads supporting effective surface and groundwater management.