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Link to original content: https://doi.org/10.1007/978-981-13-7986-4_30
Rapid Precipitation Shifts in a Black Soil Region | SpringerLink
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Rapid Precipitation Shifts in a Black Soil Region

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Cognitive Systems and Signal Processing (ICCSIP 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1006))

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Abstract

Improving remote sensing precipitation products is essential important for a correct understanding of regional climate action and land surface feedbacks although, until now, influence of precipitation distribution and its evolution on retrieval accuracies remains poorly understood, especially in black soil regions, which characterize about 3% of the Earth’s total land surface. This study examines precipitation shifts in the Hulan River Basin - a cold watershed located in a black soil region in Northeast China, analyzes influences of such precipitation shifts on performance of the current remote sensing precipitation products within the considered region, and particularly in sub-regions with rapid precipitation shifts, investigates how well can precipitation occurrence, amounts and trends be detected from space. Utilizing local precipitation data and three latest TRMM products (3B42V7, 3B42RT, CHIRPS), rapid precipitation shifts in the region and their evident influences on retrieval accuracies are proved. Nevertheless, there are still considerable uncertainties associated with the mechanisms and drivers of such precipitation shifts and it remains undetermined whether such rapid precipitation shifts are representative in other black soil regions. These two unresolved issues are essentially significant, and therefore, should be future research priorities towards a better performance of remote sensing precipitation products in black soil regions.

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References

  1. Yang, J., Gong, P., Fu, R., et al.: The role of satellite remote sensing in climate change studies. Nat. Clim. Chang. 3(10), 875–883 (2013)

    Article  Google Scholar 

  2. Sapiano, M.R.P., Arkin, P.A.: An intercomparison and validation of high-resolution satellite precipitation estimates with 3-hourly gauge data. J. Hydrometeorol. 10(1), 149–166 (2009)

    Article  Google Scholar 

  3. Green, J.K., Konings, A.G., Alemohammad, S.H., et al.: Regionally strong feedbacks between the atmosphere and terrestrial biosphere. Nat. Geosci. (2017). https://doi.org/10.1038/ngeo2957

  4. Wicaksono, S.A., Russell, J.M., Holbourn, A., et al.: Hydrological and vegetation shifts in the Wallacean region of central Indonesia since the Last Glacial Maximum. Quat. Sci. Rev. 157, 152–163 (2017)

    Article  Google Scholar 

  5. Wang, G., Wang, D., Trenberth, K.E., et al.: The peak structure and future changes of the relationships between extreme precipitation and temperature. Nat. Clim. Chang. 3(7), 268–274 (2017)

    Article  Google Scholar 

  6. Wilhelm, B., Arnaud, F., Sabatier, P., et al.: 1400 years of extreme precipitation patterns over the Mediterranean French Alps and possible forcing mechanisms. Quat. Res. 78(1), 1–12 (2012)

    Article  Google Scholar 

  7. Nosetto, M.D., Jobbágy, E.G., Tóth, T., et al.: Regional patterns and controls of ecosystem salinization with grassland afforestation along a rainfall gradient. Glob. Biogeochem. Cycles 22(2), 65 (2008)

    Article  Google Scholar 

  8. Zhang, X., Zwiers, F.W., Li, G., et al.: Complexity in estimating past and future extreme short-duration rainfall. Nat. Geosci. 3(7), 423–427 (2017)

    Google Scholar 

  9. Pauluis, O., Dias, J.: Satellite estimates of precipitation-induced dissipation in the atmosphere. Science 335(6071), 953–956 (2012)

    Article  Google Scholar 

  10. Treacy, M.M., Borisenko, K.B.: The local structure of amorphous silicon. Science 335(6071), 950–953 (2012)

    Article  Google Scholar 

  11. Ye, T., Zheng, D., Disse, M., et al.: Evaluation of precipitation input for SWAT modeling in Alpine catchment: a case study in the Adige river basin (Italy). Sci. Total Environ. 573, 66–82 (2016)

    Article  Google Scholar 

  12. Zörner, J., de Vries, M.P., Beirle, S., et al.: Multi-satellite sensor study on precipitation-induced emission pulses of NOx from soils in semi-arid ecosystems. Atmos. Chem. Phys. 18(14), 1–39 (2016)

    Google Scholar 

  13. Buishand, T.A.: Tests for detecting a shift in the mean of hydrological time series. J. Hydrol. 73(1–2), 51–69 (1984)

    Article  Google Scholar 

  14. Vicente, G.A., Davenport, J.C., Scofield, R.A.: The role of orographic and parallax corrections on real time high resolution satellite rainfall rate distribution. Int. J. Remote Sens. 23(2), 221–230 (2002)

    Article  Google Scholar 

  15. Kuligowski, R.J.: A self-calibrating real-time GOES rainfall algorithm for short-term rainfall estimates. J. Hydrometeorol. 3(2), 112–130 (2002)

    Article  Google Scholar 

  16. Andermann, C., Bonnet, S., Gloaguen, R.: Evaluation of precipitation data sets along the Himalayan front. Geochem. Geophys. Geosyst. 12(7), 785–814 (2011)

    Article  Google Scholar 

  17. Schroeder, W., Csiszar, I., Morisette, J.: Quantifying the impact of cloud obscuration on remote sensing of active fires in the Brazilian Amazon. Remote Sens. Environ. 112(2), 456–470 (2008)

    Article  Google Scholar 

  18. Liang, A.Z., Zhang, X.P., Yang, X.M., et al.: Estimation of total erosion in cultivated Black soils in northeast China from vertical profiles of soil organic carbon. Eur. J. Soil Sci. 60(2), 223–229 (2009)

    Article  Google Scholar 

  19. Zhang, Y., Wang, P., Wang, L., et al.: The influence of facility agriculture production on phthalate esters distribution in black soils of Northeast China. Sci. Total Environ. 506–507, 118–125 (2015)

    Article  Google Scholar 

  20. Liu, J., Wang, G., Zheng, C., et al.: Specific assemblages of major capsid genes (g23) of T4-type bacteriophages isolated from upland black soils in Northeast China. Soil Biol. Biochem. 43(9), 1980–1984 (2011)

    Article  Google Scholar 

  21. Liang, L., Li, L., Qiang, L.: Precipitation variability in Northeast China from 1961 to 2008. J. Hydrol. 404(1–2), 67–76 (2011)

    Article  Google Scholar 

  22. Alessio, S., Taricco, C., Rubinetti, S., et al.: Temperature and precipitation in Northeast China during the last 150 years: relationship to large-scale climatic variability. Ann. Geophys. 32(7), 749–760 (2014)

    Article  Google Scholar 

  23. Wang, B., Zhang, M., Wei, J., et al.: Changes in extreme precipitation over Northeast China, 1960–2011. Quat. Int. 298(298), 177–186 (2013)

    Article  Google Scholar 

  24. Crow, W.: Improving long-term, retrospective precipitation datasets using satellite-based surface soil moisture retrievals and the soil moisture analysis rainfall tool. J. Appl. Remote Sens. 6(1), 063604 (2012)

    Article  Google Scholar 

  25. Stenz, R., Dong, X., Xi, B., et al.: Improving satellite quantitative precipitation estimation using GOES-retrieved cloud optical depth. J. Hydrometeorol. 17(2), 557–570 (2016)

    Article  Google Scholar 

  26. Kühnlein, M., Appelhans, T., Thies, B., et al.: Improving the accuracy of rainfall rates from optical satellite sensors with machine learning—a random forests-based approach applied to MSG SEVIRI. Remote Sens. Environ. 141(141), 129–143 (2014)

    Article  Google Scholar 

  27. Nastos, P.T., Kapsomenakis, J., Philandras, K.M.: Evaluation of the TRMM 3B43 gridded precipitation estimates over Greece. Atmos. Res. 169, 497–514 (2016)

    Article  Google Scholar 

  28. Chronis, T.G., Anagnostou, E.N., Dinku, T.: High-frequency estimation of rainfall from thunderstorms via satellite infrared and a long-range lightning network in Europe. Q. J. R. Meteorol. Soc. 130(599), 1555–1574 (2004)

    Article  Google Scholar 

  29. Xu, X.Z., Xu, Y., Chen, S.C., et al.: Soil loss and conservation in the black soil region of Northeast China: a retrospective study. Environ. Sci. Policy 13(8), 793–800 (2010)

    Article  Google Scholar 

  30. Meroni, M., Rembold, F., Fasbender, D., et al.: Evaluation of the Standardized Precipitation Index as an early predictor of seasonal vegetation production anomalies in the Sahel. Remote Sens. Lett. 8(4), 301–310 (2017)

    Article  Google Scholar 

  31. Domingo, F., Villagarcı́a, L., Boer, M.M., et al.: Evaluating the long-term water balance of arid zone stream bed vegetation using evapotranspiration modelling and hillslope runoff measurements. J. Hydrol. 243(1), 17–30 (2017)

    Google Scholar 

  32. Millán, H., Rodríguez, J., Ghanbarian-Alavijeh, B., et al.: Temporal complexity of daily precipitation records from different atmospheric environments: Chaotic and Lévy stable parameters. Atmos. Res. 101(4), 879–892 (2011)

    Article  Google Scholar 

  33. Kulshrestha, U.C., Engardt, L.G., Rodhe, H.: Review of precipitation monitoring studies in India—a search for regional patterns. Atmos. Environ. 39(38), 7403–7419 (2005)

    Article  Google Scholar 

  34. Buda, A.R., Dewalle, D.R.: Using atmospheric chemistry and storm track information to explain the variation of nitrate stable isotopes in precipitation at a site in central Pennsylvania, USA. Atmos. Environ. 43(29), 4453–4464 (2009)

    Article  Google Scholar 

  35. Ciabatta, L., Marra, A.C., Panegrossi, G., et al.: Daily precipitation estimation through different microwave sensors: verification study over Italy. J. Hydrol. 545, 436–450 (2017)

    Article  Google Scholar 

  36. Palerme, C., Genthon, C., Claud, C., et al.: Evaluation of current and projected Antarctic precipitation in CMIP5 models. Clim. Dyn. 48(1–2), 1–15 (2017)

    Google Scholar 

  37. Meng, X., Li, R., Luan, L., et al.: Detecting hydrological consistency between soil moisture and precipitation and changes of soil moisture in summer over the Tibetan Plateau. Clim. Dyn. 51, 1–12 (2017)

    Google Scholar 

  38. Siuki, S.K., Saghafian, B., Moazami, S.: Comprehensive evaluation of 3-hourly TRMM and half-hourly GPM-IMERG satellite precipitation products. Int. J. Remote Sens. 38(2), 558–571 (2017)

    Article  Google Scholar 

  39. Kolassa, J., Gentine, P., Prigent, C., et al.: Soil moisture retrieval from AMSR-E and ASCAT microwave observation synergy. Part 2: product evaluation. Remote Sens. Environ. 195, 202–217 (2017)

    Article  Google Scholar 

  40. Kulie, M.S., Bennartz, R., Greenwald, T.J., et al.: Uncertainties in microwave properties of frozen precipitation: implications for remote sensing and data assimilation. J. Atmos. Sci. 67(11), 3471–3487 (2010)

    Article  Google Scholar 

  41. Aghakouchak, A., Bárdossy, A., Habib, E.: Copula-based uncertainty modelling: application to multisensor precipitation estimates. Hydrol. Process. 24(15), 2111–2124 (2010)

    Google Scholar 

  42. Liu, D., Wang, Z., Zhang, B., et al.: Spatial distribution of soil organic carbon and analysis of related factors in croplands of the black soil region, Northeast China. Agric. Ecosyst. Environ. 113(1), 73–81 (2006)

    Article  Google Scholar 

  43. Wu, Y., Zheng, Q., Zhang, Y., et al.: Development of gullies and sediment production in the black soil region of northeastern China. Geomorphology 101(4), 683–691 (2008)

    Article  Google Scholar 

  44. Liang, W., Qi, L.I., Jiang, Y., et al.: Effect of cultivation on spatial distribution of nematode trophic groups in black soil. Pedosphere 13(2), 97–102 (2003)

    Google Scholar 

  45. Wen, L.L., Zheng, F.L., Yang, Q.S., et al.: Effects of rainfall patterns on hillslope farmland erosion in black soil region of Northeast China. J. Hydraul. Eng. 43(9), 1084–1091 (2012)

    Google Scholar 

  46. Stephens, G.L.: The remote sensing of clouds and precipitation from space: a review. J. Atmos. Sci. 64(11), 3742–3765 (2007)

    Article  Google Scholar 

  47. Michaelides, S., Levizzani, V., Anagnostou, E., et al.: Precipitation: measurement, remote sensing, climatology and modeling. Atmos. Res. 94(4), 512–533 (2009)

    Article  Google Scholar 

  48. Brunsell, N.A.: Characterization of land-surface precipitation feedback regimes with remote sensing. Remote Sens. Environ. 100(2), 200–211 (2006)

    Article  Google Scholar 

  49. Alexakis, D.D., Hadjimitsis, D.G., Agapiou, A.: Integrated use of remote sensing, GIS and precipitation data for the assessment of soil erosion rate in the catchment area of “Yialias” in Cyprus. Atmos. Res. 131(2), 108–124 (2013)

    Article  Google Scholar 

  50. Velmourougane, K., Venugopalan, M.V., Bhattacharyya, T., et al.: Soil dehydrogenase activity in agro-ecological sub regions of black soil regions in India. Geoderma 197–198(3), 186–192 (2013)

    Article  Google Scholar 

  51. Dwivedi, R.S., Sreenivas, K., Ramana, K.V.: Detecting soil information in a predominantly black soil region using Indian remote sensing satellite (IRS-1B) linear imaging self-scanning sensor (LISS-II) data. Int. J. Remote Sens. 21(17), 3293–3302 (2000)

    Article  Google Scholar 

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Acknowledgments

This research was financially supported by the National Natural Science Foundation of China (41571299) and the “Thousand Talents” plan (Y474161).

Competing Interests

None declared.

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Authors and Affiliations

  1. CAS Research Center for Ecology and Environment of Central Asia, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, 830011, China

    Wenfeng Wang, Xi Chen, Hongwei Zheng & Ruide Yu

  2. Laboratory of Computational Mathematics, College of Statistics and Management, Shanghai University of Finance and Economics, Shanghai, 200433, China

    Xiaoliang Zhang

  3. Environmental Change Institute, University of Oxford, Oxford, OX1 3QY, UK

    Jianjun Yu

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  1. Wenfeng Wang
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  2. Xi Chen
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  3. Xiaoliang Zhang
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  4. Hongwei Zheng
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  5. Ruide Yu
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  6. Jianjun Yu
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Correspondence to Xi Chen .

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Editors and Affiliations

  1. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Fuchun Sun

  2. Department of Computer Science and Technology, Tsinghua University, Beijing, China

    Huaping Liu

  3. College of Mechatronics and Automation, National University of Defense Technology, Changsha, Hunan, China

    Dewen Hu

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Wang, W., Chen, X., Zhang, X., Zheng, H., Yu, R., Yu, J. (2019). Rapid Precipitation Shifts in a Black Soil Region. In: Sun, F., Liu, H., Hu, D. (eds) Cognitive Systems and Signal Processing. ICCSIP 2018. Communications in Computer and Information Science, vol 1006. Springer, Singapore. https://doi.org/10.1007/978-981-13-7986-4_30

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  • DOI: https://doi.org/10.1007/978-981-13-7986-4_30

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  • Online ISBN: 978-981-13-7986-4

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