Monitoring spatial-temporal dynamics of drought over Yok Don National Park using Temperature-soil Moisture Dryness Index (TMDI)

Le Mai Son; Hung Nguyen Manh; Toan Dao Duy; Duc- Tu Dinh; Thai Binh Tran; Thi Kim Le Dung

doi:10.15625/2615-9783/22704

Author affiliations

Authors

Mai Son Le Space Technology Institute, Vietnam Academy of Science and Technology, Hanoi, Vietnam
Manh Hung Nguyen 1-Vietnam National Space Center, Vietnam Academy of Science and Technology, Hanoi, Vietnam; 2-Graduate University of Science and Technology, Vietnam Academy of Science and Technology, Hanoi, Vietnam
Duy Toan Dao Department of Geodesy & Geomatics Engineering, Faculty of Bridge and Road, Hanoi University of Civil Engineering, Hanoi, Vietnam
Duc-Tu Dinh Ninh Binh Hydro-Meteorological Center, Northern Delta and Midland Regional Hydro-Meteorological Center, Ninh Binh province, Vietnam
Thai Binh Tran Vietnam National Space Center, Vietnam Academy of Science and Technology, Hanoi, Vietnam
Thi Kim Dung Le Faculty of Land Administration, Hanoi University of Natural Resources and Environment, Hanoi, Vietnam

DOI:

https://doi.org/10.15625/2615-9783/22704

Keywords:

Drought Monitoring, Yok Don National Park (Vietnam), Temperature-Soil Moisture Dryness Index (TMDI), Landsat-8 images

Abstract

This study investigates the spatio-temporal patterns of drought and their teleconnection with land surface properties in Yok Don National Park during the dry season using the Temperature-Soil Moisture Dryness Index (TMDI). This index is derived from the relationship between the Normalized Difference Land Heat Index and Land Surface Temperature, extracted from Landsat-8 data acquired in the mid-dry season from 2014 to 2023. Results reveal increasing drought severity starting in 2014, peaking during 2015–2016, and decreasing from 2017 to 2020. Drought conditions escalated again during 2021–2022 before moderating by 2023. These trends align with in-situ precipitation data recorded at a nearby meteorological station, highlighting varied impacts on forest types. Areas covered by deciduous broadleaf forests experienced pronounced drought effects, whereas evergreen broadleaf forests showed greater resilience. Land surface evapotranspiration rates obtained from NASA’s MOD16A2GF dataset were used to evaluate TMDI performance. During the dry seasons from 2014 to 2023, TMDI exhibited a consistent negative correlation with evapotranspiration, with coefficients ranging from -0.55 to -0.70. This demonstrates TMDI's effectiveness in capturing land surface water availability and assessing drought conditions. The findings provide crucial insights into drought monitoring and management for Yok Don National Park and other water-scarce regions, reinforcing TMDI’s value in sustainable forest management and drought mitigation.

Downloads

Download data is not yet available.

References

Asefjah B., Fanian F., Feizi Z., Abolhasani A., Paktinat H., Naghilou M., Cabello D., Asadollahi M., Babakhani M., Salehi F., Kourosh Niya A., 2014. Meteorological drought monitoring using several drought indices (case study: Salt Lake Basin in Iran). Desert, 19, 155–165. Doi: 10.22059/JDESERT.2014.52344.

Belal A.A., El-Ramady H.R., Mohamed E.S., Saleh A.M., 2014. Drought risk assessment using remote sensing and GIS techniques. Arab. J. Geosci., 7, 35–53. https://doi.org/10.1007/s12517-012-0707-2. DOI: https://doi.org/10.1007/s12517-012-0707-2

Cai S., Zuo D., Wang H., Xu Z., Wang G.Q., Yang H., 2023. Assessment of agricultural drought based on multi-source remote sensing data in a major grain producing area of Northwest China. Agric. Water Manag., 278, 108142. https://doi.org/10.1016/j.agwat.2023.108142. DOI: https://doi.org/10.1016/j.agwat.2023.108142

CCAFS-SEA, 2016. The drought crisis in the Central Highlands of Vietnam. url: https://cgspace.cgiar.org/rest/ bitstreams/78532/retrieve.

Das A.C., Shahriar S.A., Chowdhury M.A., Hossain M.L., Mahmud S., Tusar M.K., Ahmed R., Salam M.A., 2023. Assessment of remote sensing-based indices for drought monitoring in the north-western region of Bangladesh. Heliyon, 9(2), 1–14. https://doi.org/10.1016/j.heliyon.2023.e13016. DOI: https://doi.org/10.1016/j.heliyon.2023.e13016

EVNNPT, 2021. Environmental and Social Management Framework (ESMF). url: http://www.sppmb.npt.evn.vn/wp-content/uploads/2021/04/ESMF_P174460-REACH_14-Apr-2021.pdf.

Fung K., Huang Y., Koo C., Soh Y., 2020. Drought forecasting: A review of modelling approaches 2007–2017. J. Water Clim. Change., 11(3), 771–799. https://doi.org/10.2166/wcc.2019.236. DOI: https://doi.org/10.2166/wcc.2019.236

Gu Y., Brown J.F., Verdin J.P., Wardlow B., 2007. A five-year analysis of MODIS NDVI and NDWI for grassland drought assessment over the central Great Plains of the United States. Geophys. Res. Lett., 34(6), L06407. https://doi.org/10.1029/2006GL029127. DOI: https://doi.org/10.1029/2006GL029127

Ishida A., Yamazaki J.-Y., Harayama H., Yazaki K., Ladpala P., Nakano T., Adachi M., Yoshimura K., Panuthai S., Staporn D., Maeda T., Maruta E., Diloksumpun S., Puangchit L., 2013. Photoprotection of evergreen and drought-deciduous tree leaves to overcome the dry season in monsoonal tropical dry forests in Thailand. Tree Physiol., 34(1), 15–28. Doi: 10.1093/treephys/tpt107. DOI: https://doi.org/10.1093/treephys/tpt107

Jimenez-Munoz J.C., Sobrino J.A., Skoković D., Mattar C., Cristobal J., 2014. Land surface temperature retrieval methods from Landsat-8 thermal infrared sensor data. IEEE Geosci. Remote Sens. Lett., 11(10), 1840–1843. Doi: 10.1109/LGRS.2014.2312032. DOI: https://doi.org/10.1109/LGRS.2014.2312032

Le Mai Son, Liou Y.A., 2021. Spatio-Temporal Assessment of Surface Moisture and Evapotranspiration Variability Using Remote Sensing Techniques. Remote Sens., 13(9), 1667. https://doi.org/10.3390/rs13091667. DOI: https://doi.org/10.3390/rs13091667

Le Mai Son, Liou Y.A., 2022. Temperature-Soil Moisture Dryness Index for Remote Sensing of Surface Soil Moisture Assessment. IEEE Geosci. Remote Sens. Lett., 19, 1–5. Doi: 10.1109/LGRS.2021.3095170. DOI: https://doi.org/10.1109/LGRS.2021.3095170

Le Mai Son, Liou Y.A., Pham M.T., 2023. Crop Response to Disease and Water Scarcity Quantified by Normalized Difference Latent Heat Index. IEEE Access, 11, 55938–55946. Doi: 10.1109/ACCESS.2023.3283033. DOI: https://doi.org/10.1109/ACCESS.2023.3283033

Le Tien, Sun C., Choy S., Kuleshov Y.J.G., 2021. Regional drought risk assessment in the Central Highlands and the South of Vietnam. Geomatics Nat. Hazards Risk., 12(1), 3140–3159. Doi: 10.1080/19475705.2021.1998232. DOI: https://doi.org/10.1080/19475705.2021.1998232

Lesk C., Rowhani P., Ramankutty N., 2016. Influence of extreme weather disasters on global crop production. Nature 529, 84–87. https://doi.org/10.1038/nature16467. DOI: https://doi.org/10.1038/nature16467

Liou Y.A., Le Mai Son, Chien H., 2019. Normalized Difference Latent Heat Index for Remote Sensing of Land Surface Energy Fluxes. IEEE Trans. Geosci. Remote Sens., 57(3), 1423–1433. Doi: 10.1109/TGRS.2018.2866555. DOI: https://doi.org/10.1109/TGRS.2018.2866555

Maes W.H., Steppe K., 2012. Estimating evapotranspiration and drought stress with ground-based thermal remote sensing in agriculture:

a review. J. Exp. Bot., 63(13), 4671–4712. Doi: 10.1093/jxb/ers165. DOI: https://doi.org/10.1093/jxb/ers165

Mishra A.K., Ines A.V., Das N.N., Khedun C.P., Singh V.P., Sivakumar B., Hansen J.W., 2015. Anatomy of a local-scale drought: Application of assimilated remote sensing products, crop model, and statistical methods to an agricultural drought study. J. Hydrol., 526, 15–29.

https://doi.org/10.1016/j.jhydrol.2014.10.038. DOI: https://doi.org/10.1016/j.jhydrol.2014.10.038

MONRE, 2019. Vietnam national communi cation submission 3 to the United nations framework convention on climate change. Vietnam: Ministry of Natural Resources and Environment. url: https://unfccc.int/documents/192805.

Mullapudi A., Vibhute A.D., Mali S., Patil C.H., 2023. A review of agricultural drought assessment with remote sensing data: methods, issues, challenges and opportunities. Appl. Geomatics, 15(1), 1–13. https://doi.org/10.1007/s12518-022-00484-6. DOI: https://doi.org/10.1007/s12518-022-00484-6

Nguyen Manh Hung, Dao Duy Toan, Le Mai Son, Le Trung Hung, 2024. A modification of normalized difference drought index to enhance drought assessment using remotely sensed imagery. Environ. Monit. Assess., 196(10), 883. Doi: 10.1007/s10661-024-13060-9. DOI: https://doi.org/10.1007/s10661-024-13060-9

Nguyen Thuy Cuong, Huynh Van Chuong, Luu The Anh, 2022. Environmental Efficiency of Dipterocarp forest land management at Yok Don National Park. Hue Univ. J. Sci.: Agric. Rural Dev., 131(3C), 65–82. https://doi.org/10.26459/hueunijard.v131i3C.6992. DOI: https://doi.org/10.26459/hueunijard.v131i3C.6992

Nguyen Viet Luong, Ryutaro T., Akihiko K., Ngo Duc Anh, Nguyen Thanh Loan, Luu The Anh, 2017. Land cover mapping in Yok Don National Park, Central Highlands of Viet Nam using Landsat 8 OLI images. Vietnam J. Earth Sci., 39(4), 393–406. Doi: 10.15625/0866-7187/39/4/10773. DOI: https://doi.org/10.15625/0866-7187/39/4/10773

Nguyen Viet Luong, Ryutaro T., Nguyen Thanh Hoan, To Trong Tu, 2015. Forest change and its effect on biomass in Yok Don National Park in Central Highlands of Vietnam using ground data and geospatial techniques. Adv. Remote Sens., 4(2), 108–118. Doi: 10.4236/ars.2015.42010. DOI: https://doi.org/10.4236/ars.2015.42010

Nguyen Viet Luong, Ryutaro T., Nguyen Thanh Hoan, To Trong Tu, Le Mai Son, 2015. An analysis of forest biomass changes using geospatial tools and ground survey data: a case study in Yok Don national park, Central Highlands of Vietnam. Vietnam J. Earth Sci., 36(4), 439–450. https://doi.org/10.15625/0866-7187/36/4/6432. DOI: https://doi.org/10.15625/0866-7187/36/4/6432

Pham-Duc Binh, Nguyen Ho, Phan Hien, Tran-Anh Quan, 2023. Trends and applications of google earth engine in remote sensing and earth science research: a bibliometric analysis using scopus database. Earth Sci. Inform., 16(3), 2355–2371. Doi: 10.1007/s12145-023-01035-2. DOI: https://doi.org/10.1007/s12145-023-01035-2

Philip S.Y., Kew S.F., van der Wiel K., Wanders N., Jan van Oldenborgh G., 2020. Regional differentiation in climate change induced drought trends in the Netherlands. Environ. Res. Lett., 15(9), 094081. Doi: 10.1088/1748-9326/ab97ca. DOI: https://doi.org/10.1088/1748-9326/ab97ca

Phung Thai Duong, Do Xuan Son, 2024. Assessing forest changes in Yok Don National Park and surrounding areas, Dak Lak province, Vietnam.

J. Degrad. Min. Lands Manag., 11(2), 5521–5531. Doi: 10.15243/jdmlm.2024.112.5521. DOI: https://doi.org/10.15243/jdmlm.2024.112.5521

Ru C., Duan S.B., Jiang X.G., Li Z.L., Jiang Y., Ren H., Leng P., Gao M., 2021. Land surface temperature retrieval from Landsat 8 thermal infrared data over urban areas considering geometry effect: Method and application. IEEE Trans. Geosci. Remote Sens., 60, 1–16. Doi: 10.1109/TGRS.2021.3088482. DOI: https://doi.org/10.1109/TGRS.2021.3088482

Sandholt I., Rasmussen K., Andersen J., 2002. A simple interpretation of the surface temperature/vegetation index space for assessment of surface moisture status. Remote Sens. Environ., 79(2), 213–224. https://doi.org/10.1016/S0034-4257(01)00274-7. DOI: https://doi.org/10.1016/S0034-4257(01)00274-7

Shahabfar A., Eitzinger J., 2013. Spatio-Temporal Analysis of Droughts in Semi-Arid Regions by Using Meteorological Drought Indices. Atmosphere, 4(2), 94–112. https://doi.org/10.3390/atmos4020094. DOI: https://doi.org/10.3390/atmos4020094

UNDP, 2016. Vietnam drought and saltwater intrusion: Transitioning from emergency to recovery. url: https://www.undp.org/sites/g/files/zskgke326/files/migration/vn/Recovery-draft-Sep-2016_final.pdf.

UNESCAP, 2019. Ready for the dry years: building resilience to drought in Southeast Asia. url: https://repository.unescap.org/handle/20.500.12870/3003.

Van Hoek M., Jia L., Zhou J., Zheng C., Menenti M., 2016. Early Drought Detection by Spectral Analysis of Satellite Time Series of Precipitation and Normalized Difference Vegetation Index (NDVI). Remote Sens., 8, 422. https://doi.org/10.3390/rs8050422. DOI: https://doi.org/10.3390/rs8050422

Vicente-Serrano S.M., Cabello D., Tomás-Burguera M., Martín-Hernández N., Beguería S., Azorin-Molina C., Kenawy A.E., 2015. Drought Variability and Land Degradation in Semiarid Regions: Assessment Using Remote Sensing Data and Drought Indices (1982–2011). Remote Sens., 7(4), 4391–4423. https://doi.org/10.3390/rs70404391. DOI: https://doi.org/10.3390/rs70404391

Wilhite D., Glantz M., 1985. Understanding: the Drought Phenomenon: The Role of Definitions. Water Int., 10, 111–120. https://www.tandfonline.com/doi/pdf/10.1080/02508068508686328. DOI: https://doi.org/10.1080/02508068508686328

World Bank, 2021. Climate Risk Country Profile: Vietnam. url: https://climateknowledgeportal.worldbank.org/sites/default/files/2021-04/15077-Vietnam%20Country%20Profile-WEB.pdf.

Zhang S., Wu Y., Sivakumar B., Mu X., Zhao F., Sun P., Sun Y., Qiu L., Chen L., Meng X., Han J., 2019. Climate change-induced drought evolution over the past 50 years in the southern Chinese Loess Plateau. Environ. Model. Softw., 122, 104519. https://doi.org/10.1016/j.envsoft.2019.104519. DOI: https://doi.org/10.1016/j.envsoft.2019.104519

Zhong R., Chen X., Lai C., Wang Z., Lian Y., Yu H., Wu X., 2019. Drought monitoring utility of satellite-based precipitation products across mainland China. J. Hydrol., 568, 343–359. https://doi.org/10.1016/j.jhydrol.2018.10.072.s. DOI: https://doi.org/10.1016/j.jhydrol.2018.10.072