Assessment and modelling of desertification risk and economic impacts in an arid agricultural region of Russia

Desertification poses a critical constraint to sustainable crop production in arid and semi-arid zones, where conventional linear risk assessments often fail to capture threshold-driven ecosystem shifts. This study develops and validates a nonlinear desertification risk model grounded in the tipping-point concept, integrating key soil and topographic drivers–specifically, the expansion rates of eroded and secondary saline soils, slope gradient, and humus depletion. Each driver is transformed via sigmoidal functions to explicitly represent the nonlinear transition from stable baseline conditions through a critical threshold into a degradation regime. Validated at the municipal level in the Volgograd region of Russia, the model shows strong concordance with independent Land Degradation Neutrality (LDN) metrics and official economic damage assessments, identifying areas with the most negative LDN values as actively degrading. Scenario analysis further demonstrates that agroecological interventions are most effective during the transitional phase, capable of reducing integrated risk by up to 40%. The framework thus provides a practical, decision‑support tool for spatially targeted risk diagnosis, land‑use prioritisation, and enhancing the ecological and economic resilience of dryland cropping systems.