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Research on Crops

Scenario-based modelling of the economic consequences of land degradation in dryland farming systems of the Lower Volga Region 


DOI: 10.31830/2348-7542.2026.ROC-1319    | Article Id: ROC-1319 | Page : 274-279
Citation :- Scenario-based modelling of the economic consequences of land degradation in dryland farming systems of the Lower Volga Region. Res. Crop. 27: 274-279
KORNEEVA E. A korneeva.eva@list.ru
Address : Federal Scientific Center of Agroecology, Complex Melioration and Protective Afforestation, Russian Academy of Sciences, 400062, Volgograd, 97, University Ave., Russia
Submitted Date : 9-05-2026
Accepted Date : 1-06-2026
Online Published:

Abstract

Land degradation in arid and semi-arid agroecosystems is increasingly manifested through persistent crop yield declines, directly affecting agricultural economic performance. The non-linear response of yields to degradation, combined with climatic variability, complicates the accurate assessment of long-term impacts. Therefore, scenario-based modeling is required to link climatic pressures, land degradation, yield reduction, and economic consequences in dryland farming systems. This study develops a regionally calibrated scenario model to assess the economic consequences of land degradation in dryland farming of the Lower Volga region, using Volgograd oblast as a case study. Climatic pressure was quantified using four indicators–temperature anomaly, annual precipitation, number of days with wind speed ≥ 15 m/s, and moisture coefficient–each transformed into a normalised sigmoidal risk function. The integrated climatic pressure index (C), calculated as the geometric mean, was linked to a probabilistic five-level degradation scale. Three scenarios were considered: moderate, an increasing degradation pressure scenario, and extreme. The transition from moderate to increasing pressure led to a nonlinear rise in C from 0.065 to 0.500, while further deterioration resulted in saturation (C = 0.920). Total economic damage for a representative crop rotation reached 292.6 USD/ha/yr and 496.5 USD/ha/yr under the intermediate and extreme scenarios, respectively. About 59% of total losses occur already at the intermediate stage, highlighting the importance of early intervention.

Keywords

Climatic risk dryland farming economic damage land degradation sigmoidal normalization yield 

References

Bakker, M. M., Govers, G. and Rounsevell, M. D. (2004). The crop productivity–erosion relationship: An analysis based on experimental work. Catena 57: 55-76.
Belyakov A. M. (2019). Weather and harvest for 60 years (statistics and analysis of weather and harvests in the Volgograd region. Federal Scientific Center of Agroecology RAS, Volgograd, Russia. pp: 88.
IPCC. (2018). Global Warming of 1.5°C. An IPCC Special Report. Inter-governmental panel on climate change, Geneva, Switzerland. pp: 32.
Khuzhakhmetova, A. S. and Melnik K. (2024). Assessment of ecological and biological characteristics of Gleditsia triacanthos L. for agroforestry of degraded areas. Int. J. Agric. Biosci. 13: 112-17.
Korneeva, E. A. (2020). Efficiency of financing forest reclamation measures to ensure sustainable development of agricultural regions in the south of the European territory of Russia. Economic Region 16: 871-83.
Korneeva, E. A. (2026). Assessment and modelling of desertification risk and economic impacts in an arid agricultural region of Russia. Res. Crop. 27: 77-83.
Korneeva, E. A. and Belyaev, A. I. (2023). Assessment of the impact of forest reclamation measures for the adaptation of agriculture to climate change in the south of the Russian Plain. Forests 14: doi:10.3390/f14081593.
Kulik, K. N., Belyaev, A. I. and Barabanov, A. T. (2024). National action program to combat desertification in the Volgograd region. Federal Scientific Center of Agroecology RAS, Volgograd, Russia. pp. 256.
Kust, G. S., Andreeva, O. V. and Dobrynin, D. V. (2011). Desertification assessment and mapping in the Russian Federation. Arid Ecosyst. 1: 14-28.
Lenton, T. M., Laybourn, L., Armstrong McKay, D. I., Loriani, S., Abrams, J. F., Lade, S. J., Donges, J. F., Milkoreit, M., Smith, S. R., Bailey, E., Powell, T., Fesenfeld, L., Zimm, C., Boulton, C. A., Buxton, J. E., Dyke, J. G. and Ghadiali, A. (2023). Global Tipping Points Report 2023: Summary Report. University of Exeter, Exeter, UK. pp: 30.
Makarov, O. A., Demidov, V. V., Karpova, D. V., Shulga, P. S., Abdulkhanova, D. R., Yesafova, E. N., Kubarev, E. N. and Mikhailovsky, V. I. (2024). Economic assessment of eroded soils: Current state and development prospects. Moscow Univ. Soil Sci. Bull. 79: 215-25.
Manaenkov, A. S. and Korneeva, E.  A. (2016). Soil protection efficiency of forest reclamation in the sloping lands of the southern European territory of Russia. Bull. Russian Agric. Sci. 1: 24-27.
Mandal, D., Patra, S., Sharma, N. K., Alam, N. M., Jana, C. and Lal, R. (2023). Impacts of soil erosion on soil quality and agricultural sustainability in the North-Western Himalayan region of India. Sustainability 15: doi:10.3390/su15065430.
Pugacheva, A. M. and Vasilchenko, A. A. (2025). Features of the formation of arid phenomena in subarid territories (on the example of the Volgograd region). Sci. Agron. J. 4: 18-27.
Ray, D., Gerber, J., MacDonald, G. and West, P. C. (2015). Climate variation explains a third of global crop yield variability. Nature Commu. 6: 1-9.
Russian Federation Prices (2025). Average prices of agricultural producers in the Russian Federation, federal districts and subjects of the Russian Federation in 2025. Rosstat, Moscow, Russia. pp: 117.
Shashko, D. I. (1985). Agro-Climatic Resources of the USSR. Hydrometeoizdat, Leningrad, USSR. pp: 248.
Strashnaya, A. I., Berez, O. V. and Klang P. S. (2021). Forecasting grain crop yields based on the integration of ground-based and satellite data in the subjects of the Southern Federal District. Hydrometeorological Res. Forecasts 2: 110-37. doi:10.37162/2618-9631-2021-2-111-137
Tribunskaya, V. M. and Kuzmina, T. S. (1990). Economic efficiency of protective forest plantations in the soil erosion protection system. Agropromizdat, Moscow, Russia. pp: 176.
Vanin, D. E. (1985). Problems of agriculture and ways to solve them. Central Chernozem Publishing House, Voronezh, Russia. pp: 135.
Volgogradstat (2025). Volgograd region in numbers. 2024: Statistical review. Volgogradstat, Volgograd, Russia. pp: 358.
Wang, J., Wang, Yu. and Xu, D. (2024). Desertification in northern China from 2000 to 2020: The spatial–temporal processes and driving mechanisms. Ecological Informatics. 82:  doi:10.1016/j.ecoinf.2024.102769.
Zhang, L., Huang, Y., Rong, L., Duan, X., Zhang, R., Li, Y. and Guan, J. (2021). Effect of soil erosion depth on crop yield based on topsoil removal method: a meta-analysis. Agron. Sustain. Dev. 41: doi:10.1007/s13593-021-00718-8.
 
 

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