Characteristic of Soil Moisture in Indonesia Using ESA CCI Satellites Products

https://doi.org/10.22146/ijg.43905

Fatkhuroyan Fatkhuroyan(1*), Trinah Wati(2), Roni Kurniawan(3)

(1) Indonesia Agency for Meteorology Climatology and Geophysics, BMKG, Kemayoran, Central Jakarta, Indonesia
(2) Indonesia Agency for Meteorology Climatology and Geophysics, BMKG, Kemayoran, Central Jakarta, Indonesia
(3) Indonesia Agency for Meteorology Climatology and Geophysics, BMKG, Kemayoran, Central Jakarta, Indonesia
(*) Corresponding Author

Abstract


Soil moisture (SM) is one of the energy and water exchange main drivers between the atmosphere and land surface. The study aims to analyze the soil moisture characteristics in Indonesia on monthly and seasonal time scales. The analysis uses mapping of monthly and seasonal ESA CCI SM satellite products of mean daily from 1979 to 2016. The results showed the spatial and temporal variability of SM in Indonesia. Sumatera has SM values > 0.3 m3/m3 almost throughout the year. Besides, Java has SM values > 0.3 m3/m3 from January to April and October to December while 0.2-0.3 m3/m3 from May to September. In Borneo, the SM value > 0.3 m3/m3 from February to June and November to December, while from July to September are 0.2-0.3 m3/m3. Sulawesi has SM values > 0.3 m3/m3 from January to July, on December, and 0.2-0.3 m3/m3 from august to November. Bali to Nusa Tenggara have SM values between 0.2-0.3 m3/m3 throughout the year, except <0.2 m3/m3 in Sumba, Timor Island, and Central Lombok from June to November. Maluku has SM values between 0.2-0.3 m3/m3 throughout the year, while Papua has SM values >0.3 m3/m3 throughout the year, except in Jayawijaya Mountain and South Papua. The ESA CCI SM product is essential for monitoring SM in Indonesia.


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References

Aldrian, E., & Dwi Susanto, R. (2003). Identification of three dominant rainfall regions within Indonesia and their relationship to sea surface temperature. International Journal of Climatology: A Journal of the Royal Meteorological Society, 23(12), 1435-1452.

Brocca, L., Ciabatta, L., Massari, C., Camici, S., & Tarpanelli, A. (2017). Soil moisture for hydrological applications: Open questions and new opportunities. Water, 9(2), 140.

Carlson, T.N.; Dodd, J.K.; Benjamin, S.G.; Cooper, J.N. (1981). Satellite estimation of the surface energy balance, moisture availability and thermal inertia. J. Appl. Meteor. 1981, 20, 67–87.

Carlson, T.N. (1986). Regional-scale estimates of surface moisture availability and thermal inertia using remote thermal measurements. Remote Sens. Rev. 1986, 1, 197–247.

Chen, X.Z.; Chen, S.S.; Zhong, R.F.; Su, Y.X.; Liao, J.S.; Li, D.; Han, L.; Lia, Y.; Li, X. (2012). A semi-empirical inversion model for assessing surface soil moisture using AMSR-E brightness temperatures. J. Hydrol. 2012, 456, 1–11.

Dee, D.P., Uppala, S.M., Simmons, A.J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M.A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A.C.M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A.J., Haimberger, L., Healy, S.B., Hersbach, H., Hólm, E.V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A.P., Monge-Sanz, B.M., Morcrette, J.J., Park, B.K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.N., Vitart, F. (2011). The ERA-interim reanalysis: configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc. 137, 553–597.

Dorigo, W.A., Scipal, K., Parinussa, R.M., Liu, Y.Y., Wagner, W., de Jeu, R.A.M., Naeimi, V. (2010). Error characterisation of global active and passive microwave soil moisture data sets. Hydrol. Earth Syst. Sci. 14, 2605–2616.

Dorigo, W.A., Xaver, A., Vreugdenhil, M., Gruber, A., Hegyiová, A., Sanchis-Dufau, A.D., Wagner, W., Drusch, M. (2013). Global automated quality control of in-situ soil moisture data from the International Soil Moisture Network. Vadose Zone Journal. Vol. 12, No.3.

Dorigo,W. A., Gruber, A., De Jeu, R. A. M.,Wagner,W., Stacke, T., Loew, A., Albergel, C., Brocca, L., Chung, D., Parinussa, R. M., and Kidd, R. (2015). Evaluation of the ESA CCI soil moisture product using ground-based observations. Remote Sens. Environ., 162, 380–395, doi:10.1016/j.rse.2014.07.023, 2015.

Dorigo, W., De Jeu, R. (2016). Satellite soil moisture for advancing our understanding of earth system processes and climate change. Int. J. Appl. Earth Obs. Geoinf. 48, 1–4.

Dorigo, W., Wagner, W., Albergel, C., Albrecht, F., Balsamo, G., Brocca, L., Chung, D., Ertl, M., Forkel, M., Gruber, A. and Haas, E., (2017). ESA CCI Soil Moisture for improved Earth system understanding: State-of-the art and future directions. Remote Sensing of Environment, 203, pp.185-215.

El Hajj, M.; Baghdadi, N.; Zribi, M.; Belaud, G. (2016). Soil moisture retrieval over irrigated grassland using X-band SAR data. Remote Sens. Environ. 2016, 176, 202–218.

Findell, K.L., Gentine, P., Lintner, B.R., Guillod, B.P. (2015). Data length requirements for observational estimates of land–atmosphere coupling strength. J. Hydrometeorol. 16, 1615–1635.

Idso, S.B.; Jackson, R.D.; Reginato, R.J. (1976). Compensating for environmental variability in the thermal inertia approach to remote sensing of soil moisture. J. Appl. Meteor. 1976, 15, 811–817

Larson, K.M., E.E. Small, E. Gutmann, A. Bilich, P. Axelrad, and J. Braun. (2008). Using GPS multipath to measure soil moisture fluctuations: Initial results. GPS Solut. 12:173–177. doi:10.1007/s10291-007-0076-6

Liang, W.L.; Hung, F.X.; Chan, M.C.; Lu, T.H. (2014). Spatial structure of surface soil water content in a natural forested headwater catchment with a subtropical monsoon climate. J. Hydrol. 2014, 516, 210–221.

Liu, Y. Y., Parinussa, R. M., Dorigo, W. A., De Jeu, R. A. M., Wagner, W., van Dijk, A. I. J. M., McCabe, M. F., and Evans, J. P. (2011). Developing an improved soil moisture dataset by blending passive and active microwave satellite-based retrievals. Hydrol. Earth Syst. Sci., 15, 425–436, doi:10.5194/hess-15-425-2011.

Liu, Y. Y., Dorigo, W. A., Parinussa, R. M., de Jeu, R. A. M., Wagner, W., McCabe, M. F., Evans, J. P., and van Dijk, A. I. J. M. (2012). Trend-preserving blending of passive and active microwave soil moisture retrievals. Remote Sens. Environ., 123, 280–297, doi:10.1016/j.rse.2012.03.014, 2012.

Loew, A. (2013). Terrestrial satellite records for climate studies: how long is long enough? A test case for the Sahel. Theor. Appl. Climatol. 115, 427–440.

Moran, M.S.; Clarke, T.R.; Inoue, Y.; Vidal, A. (1994). Estimating crop water deficit using the relation of between surface air temperature and spectral vegetation index. Remote Sens. Environ. 1994, 49, 246–263.

Ochsner, T.E., Cosh,M., Cuenca, R., Dorigo,W., Draper, C., Hagimoto, Y., Kerr, Y., Larson, K., Njoku, E., Small, E., Zreda, M. (2013). State of the art in large-scale soil moisture monitoring. Soil Sci. Soc. Am. J. 77.

Porporato, A.; Daly, E.; Rodriguez-Iturbe, I. (2004). Soil water balance and ecosystem response to climate change. Amer. Nat. Society. 2004, 164, 625–632.

Rahmani, A., Golian, S., & Brocca, L. (2016). Multiyear monitoring of soil moisture over Iran through satellite and reanalysis soil moisture products. International Journal of Applied Earth Observation and Geoinformation, 48, 85–95. doi:10.1016/j.jag.2015.06.009

Riley, W.J.; Shen, C. (2014). Characterizing coarse-resolution watershed soil moisture heterogeneity using fine-scale simulations. Hydrol. Earth Syst. Sci. 2014, 18, 2463–2483.

Robinson, D.A.; Campbell, C.S. (2008). Soil Moisture Measurement for Ecological and Hydrological Watershed-Scale Observatories: A Review. Vadose Zone Journal. 2008, 7, 358–389.

Rodell, M., Houser, P.R., Jambor, U., Gottschalck, J., Mitchell, K., Meng, C.J., Arsenault, K., Cosgrove, B., Radakovich, J., Bosilovich, M., Entin, J.K., Walker, J.P., Lohmann, D., Toll, D. (2004). The global land data assimilation system. Bull. Am. Meteorol. Soc. 85, 381–394.

Rodriguez-Iturbe, I.; D’Odorico, P.; Porporato, A.; Ridolfi, L. (1999). On the spatial and temporal links between vegetation, climate, and soil moisture. Water Resour. Res. 1999, 35, 3709–3722.

Rosenbaum, U.; Bogena, H.R.; Herbst, M.; Huisman, J.A.; Peterson, T.J.; Weuthen, A.;Western, A.; Vereecken, H. (2002). Seasonal and event dynamics of spatial soil moisture patterns at the small catchment scale.Water Resour. Res. 2002, 48, W10544.

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. 2002, 79, 213–224.

Sayde, C., C. Gregory, M. Gil-Rodriguez, N. Tufillaro, S. Tyler, N. van de Giesen, et al. (2010) . Feasibility of soil moisture monitoring with heated fiber optics. Water Resour. Res. 46:W06201. doi:10.1029/2009WR007846

Seneviratne, S.I., Corti, T., Davin, E.L., Hirschi, M., Jaeger, E.B., Lehner, I., Orlowsky, B. and Teuling, A.J., (2010). Investigating soil moisture–climate interactions in a changing climate: A review. Earth-Science Reviews, 99(3-4), pp.125-161.

Steele-Dunne, S.C., M.M. Rutten, D.M. Krzeminska, M. Hausner, S.W. Tyler, J. Selker, et al. (2010). Feasibility of soil moisture estimation using passive distributed temperature sensing. Water Resour. Res. 46:W03534. doi:10.1029/2009WR008272

Takagi, K.; Lin, H.S. (2011). Temporal dynamics of soil moisture spatial variability in the shale hills critical zone observatory. Vadose Zone Journal. 2011, 10, 832–842.

Yuan, X., Ma, Z., Pan, M., Shi, C.C.G.L. (2015). Microwave remote sensing of short-term

droughts during crop growing seasons. Geophysical Research Letter. http://dx.doi.org/10.1002/2015GL064125

Ulaby, F.T.; Moore, R.K.; Fung, A.K. Microwave Remote Sensing: Active and Passive; Artech House Inc.: Dedham, MA, USA, 1986

Wagner, W., Dorigo, W., de Jeu, R., Fernandez, D., Benveniste, J., Haas, E., and Ertl, M. (2012). Fusion of active and passive microwave observations to create an essential climate variable data record on soil moisture, ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci., I-7, 315–321, doi:10.5194/isprsannals-I-7-315-2012.

Zhang, D.; Li, Z.L.; Tang, R.; Tang, B.H.; Wu, H.; Lu, J.; Shao, K. (2015). Validation of a practical normalized soil moisture model with in situ measurements in humid and semi-arid regions. Int. J. Remote Sens. 2015, 36, 5015–5030.

Zheng, X., Zhao, K., Ding, Y., Jiang, T., Zhang, S., & Jin, M. (2016). The spatiotemporal patterns of surface soil moisture in Northeast China based on remote sensing products. Journal of Water and Climate Change, 7(4), 708–720. doi:10.2166/wcc.2016.106

Zreda, M., D. Desilets, T.P.A. Ferré, and R.L. Scott. (2008). Measuring soil moisture content non-invasively at intermediate spatial scale using cosmic-ray neutrons. Geophys. Res. Lett. 35:L21402. doi:10.1029/2008GL035655



DOI: https://doi.org/10.22146/ijg.43905

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