Document Type : Research Paper

Authors

1 Associate Professor, Department of Water Engineering, University of Birjand, Birjand, Iran & Research Group of Drought and Climate Change, University of Birjand, Birjand, Iran.

2 MSc in Water Resources, Department of Water Engineering, University of Birjand, Birjand, Iran.

3 Associate Professor, Department of Remote Sensing Division, Surveying and Geomatics Engineering, University of Zabol, Zabol, Iran.

4 Assistant Professor, Department of Soil Engineering, University of Birjand, Birjand, Iran & Research Group of Drought and Climate Change, University of Birjand, Birjand, Iran.

Abstract

Drought begins with a lack of rainfall and depending on its duration and severity, Drought can affect parameters such as soil moisture, volume of surface and subsurface water, and human and ecosystem activities. For this purpose, in this research, by using the estimated soil moisture data by the SWAP model and the data of the fifth climate change report, agricultural drought was determined by using of the soil moisture deficit index for the future period (2020-2039) and then they compared with the base period (1992-2011). The results showed that the climatic parameters such as minimum temperature, maximum temperature and precipitation have increased in the future period compared to the base period. The RCP8.5 scenario has estimated the temperature is higher and the precipitation is lower compared to the RCP4.5 scenario. Moisture changes at a soil depth (30 cm) showed that the percentage of soil moisture increases slightly for each scenario in the future period (2020-2039) compared to the base period (1992-2011). The presence of error values of R2=0.81, NS=0.79 and RMSE=0.02 showed that there is a high correlation between the measured and observed results of soil moisture obtained from calibration and validation of the SWAP model. The results show that calculated SMDI drought index values in the future period (2020-2039) for RCP4.5 scenario has higher than the RCP8.5 scenario, and the predicted SMDI value for the future period is higher than the base period. The results of SMDI drought index uncertainty under RCP4.5 and RCP8.5 scenarios showed that CanEsm2 model has the most certainty and IPSL models have the least certainty compared to other models. The results of this research determined that drought can be estimated in the future by using the vegetation model.

Keywords

Main Subjects

Chan, S.S., Seidenfaden, I.K., Jensen, K.H., & Sonnenborg, T.O. (2021). Climate change impacts and uncertainty on spatiotemporal variations of drought indices for an irrigated catchment, Journal of Hydrology, 601, 126814.
Chen. X., Li, Y., Yao, N., Liu, D.L., Javed, T., Liu, C., & Liu, F. (2020). Impacts of multi-timescale SPEI and SMDI variations on winter wheat yields, Agricultural Systems, 185, 102955.
Delghandi, M., Joorablou, S., & Ganji, N.Z. (2023). The impact of climate change on severity, duration, and magnitude of drought using SPI and RDI in the Semnan region, Journal of Drought and Climate Change Research, 1(1), 1-18. (In Persian)
Dubrovsky, M., Svoboda, M.D., Trnka, M., Hayes, M.J., Wilhite, D.A., Zalud, Z., & Hlavinka, P. (2009). Application of relative drought indices in assessing climate-change impacts on drought conditions in Czechia. Theoretical and Applied Climatology, 96(1-2), 155-171.
Fang, B., Kansara, P., Dandridge, C., & Lakshmi, V. (2021), Drought monitoring using high spatial resolution soil moisture data over Australia in 2015–2019, Journal of Hydrology, 594, 125960.
Guo, Y., Zhang, J., Li, K., Aru, H., Feng, Z., Liu, X., & Tong, Z. (2023). Quantifying hazard of drought and heat compound extreme events during maize (Zea mays L.) growing season using Magnitude Index and Copula, Weather and Climate Extremes, 40, 100566.
Hauser, M., Orth, R., & Seneviratne, S. (2016). Investigating soil moisture-climate interactions with prescribed soil moisture experiments: an assessment with the Community Earth System Model (version 1.2). Geoscientific Model Development, 10(4), 1665-1677.
Hejazizadeh, Z., & Parvin, N. (2007). Rainfall Modeling and Forecasting Using SARIMA Models and Drought Monitoring Using BMI Index and PDRI Index of Urmia Lake Watershed. Journal of Geographical Research, 1(87), 97-124. (In Persian)
Helmi, M., & Shahidi, A. (2023). The using of SPI and SPEI indices in evaluating the effect of drought on quality of surface water resources (Case study: Kashafroud river), Journal of Drought and Climate Change Research, 1(1), 83-96. (In Persian)
Hou, M., Yao, N., Li, Y., Liu, F., Biswas, A., Pulatov, A. & Hassan, I. (2022). Better Drought Index between SPEI and SMDI and the Key Parameters in Denoting Drought Impacts on Spring Wheat Yields in Qinghai, China. Agronomy, 12, 1552.
IPCC-TGICA. (2007). General guidelines on the use of scenario data for climate impact and adaptation assessment. In: Carter TR (Eds.), Intergovernmental Panel on Climate Change, Task Group on Data and Scenario Support for Impact and Climate Assessment.
Jalali, L., Bazrafshan, J., & Tavakoli, A.R. (2013). Evaluation of Soil Moisture Deficiency Index (SMDI) in Agricultural Drought Monitoring (Case Study: Maragheh). The First National Conference on Agricultural Sciences, Payame Noor University West Azerbaijan, West Azerbaijan, Iran, 18-19 September 2013. (In Persian)
Leeper, R.D., Petersen, B., Michael A., Palecki, M.A. & Diamond, H. (2021). Exploring the Use of Standardized Soil Moisture as a Drought Indicator, Journal of Applied Meteorology and Climatology, 60, 1021-1033.
 Masaedi, A., Mohammadimoghaddam, S., & Coqueby, GH. (2016). Determination of drought characteristics based on RDI drought identification index and its variation in different time zones and periods. Journal of Soil and Water Conservation Research, 23(6), 27-52. (In Persian)
 Mohammadi, H., & Taghavi, F. (2005). Trend of Temperature and Precipitation Indicators in Tehran. Geographical Space Scientific-Research Quarterly, 38(1), 151-171. (In Persian)
Narasimhan, B., & Srinivasan, R. (2005). Development and evaluation of Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) for agricultural drought monitoring. Agricultural and Forest Meteorology, 133(1-4), 69-88.
Nepal, S., Pradhananga, S., Shrestha, N. K., Kralisch, S., Shrestha, J. P., & Fink, M. (2021). Space–time variability in soil moisture droughts in the Himalayan region. Hydrology and Earth System Sciences25(4), 1761-1783.
Ramazanietedali, H., Lyaghat, A.M., & Parsinejad, M. (2011). Survey of Agricultural Drought Status Based on Soil Moisture in Qazvin Province. The First National Conference on Meteorology and Agricultural Water Management, Pardis Agriculture and Natural Resources, University of Tehran, Tehran, Iran. (In Persian)
Sayari, N., Bannayan, M., Alizadeh, A., & Farid, A. (2013). Using drought indices to assess climate change impacts on drought conditions in the northeast of Iran (case study: Kashafrood basin). Meteorological Applications, 20(1), 115-127.
Semenov, M. A. (2009). Impacts of climate change on wheat in England and Wales. Journal of the Royal Society Interface6(33), 343-350.
Shin, Y., & Jung, Y. (2014). Development of irrigation water management model for reducing drought severity using remotely sensed soil moisture footprints. Irrigation and Drainage Engineering, 140(7), 04014021.
 Sohrabi, R., Sohrabi, A.H., & Arab, D.R. (2008 October). Investigation of drought monitoring indices from the perspective of evolution, nature and performance and suggesting an index selection process appropriate to the conditions of the regions. The Third Water Resources Management Conference, Tabriz University, Tabriz, Iran, 14-16 October 2008. (In Persian).
Van Dam, J. C., Huygen, J., Wesseling, J. G., Feddes, R. A., Kabat, P., Van Walsum, P. E. V., ... & Van Diepen, C. A. (1997). Theory of SWAP version 2.0; Simulation of water flow, solute transport and plant growth in the soil-water-atmosphere-plant environment (No. 71). DLO Winand Staring Centre.
Watson, A., Miller, J., Künne, A., & Kralisch, S. (2022). Using soil-moisture drought indices to evaluate key indicators of agricultural drought in semi-arid Mediterranean Southern Africa. Science of the Total Environment812, 152464.
Wondie, M., & Terefe, T. (2016). Assessment of drought in Ethiopia by using self-calibrated Palmer Drought Severity Index. Irrigation and Drainage Engineering, 7(2), 108-117.
Yaghoobzadeh, M. (2015). Simulation of Soil Evapotranspiration and Transpiration to Evaluate Agricultural Drought for Basic and Future Periods Using Remote Sensing Technique. PhD Thesis on Irrigation and Drainage, Faculty of Water Engineering, Chamran martyr of Ahwaz University, Ahwaz, Iran. (In Persian)
Yaghoobzadeh, M. (2022). Selecting the best general circulation model and historical period to determine the effects of climate change on precipitation, IDŐJÁRÁS/Quarterly journal of the Hungarian meteorological service, 126, 247-265.
Yao, N., Yi Li, Y., Liu, Q., Zhang, S., Chen, X., Ji, Y., Liu, F., Pulatov, A., & Fenge, P. (2022). Response of wheat and maize growth-yields to meteorological and agricultural droughts based on standardized precipitation evapotranspiration indexes and soil moisture deficit indexes, Agricultural Water Management, 266, 107566.