On the Application of Probabilistic Hydrometeorological Simulation of Soil Moisture across Different Stations in India

Sarit Kumar Das, Rajib Maity

Department of Civil Engineering, Indian Institute of Technology, Kharagpur, India.

DOI: 10.4236/gep.2014.23021                

Abstract

An application of a proposed hydrometeorological approach for probabilistic simulation of soil moisture is carried out. The time series of in-situ soil moisture and meteorological variables at monthly scale from a few monitoring stations having different soil-hydrologic properties across India are utilized. Preliminary investigation with both precipitation and near-surface air-tempera- ture as meteorological variables to establish that the strength of association between soil moisture and precipitation is more significant as compared to that between soil moisture and temperature. Precipitation-based probabilistic estimation of soil moisture using the proposed hydrometeorological approach is tested with in-situ observed soil moisture, CPC model output and with soil moisture data of the Climate Change Initiative (CCI) project. The parameter of the developed model is linked to the soil-hydrologic characteristics through Hydrologic Soil Group (HSG) classification. Higher values of model parameter (dependence parameter (θ) for the selected copula) correspond to HSG A and B having higher soil porosity, whereas, lower values correspond to HSG B and C having lower soil porosity.

Keywords

Soil Moisture, Probabilistic Modelling, Copula, Hydrometeorology, Hydroclimatology

Conflicts of Interest

The authors declare no conflicts of interest.

References

[1]	Albergel, C., Dorigo, W., Balsamo, G., Mu?oz-Sabater, J., de Rosnay, P., Isaksen et al. (2013a). Monitoring Multi-Decadal Satellite Earth Observation of Soil Moisture Products through Land Surface Reanalyses. Remote Sensing of Environment, in press.
[2]	Albergel, C., Brocca, L., Wagner, W., De Rosnay, P., & Calvet, J.-C. (2013b). Selection of Performance Metrics for Global Soil Moisture Products: The Case for the ASCAT Soil Moisture Product. In: G. P. Petropoulos (Ed.), Remote Sensing of Energy Fluxes and Soil Moisture Content (pp. 427-444). CRC Press.
[3]	Bormann, H. (2012). Assessing the Soil Texture-Specific Sensitivity of Simulated Soil Moisture to Projected Climate Change by SVAT Modelling. Geoderma, 185-186, 73-83. http://dx.doi.org/10.1016/j.geoderma.2012.03.021
[4]	Central Ground Water Board (CGWB) (2007). Manual on Artificial Recharge of Groundwater. Ministry of Water Resources, Government of India, Farida-bad.
[5]	Chowdhary, H., Escobar, L. A., & Singh, V. P. (2011). Identification of Suitable Copulas for Bivariate Frequency Analysis of Flood Peak and Flood Volume Data. Hydrology Research, 42, 193-216. http://dx.doi.org/10.2166/nh.2011.065
[6]	Das, S. K., & Maity, R. (2013), Probabilistic Simulation of Surface Soil Moisture using Hydrometeorological Inputs. ISH Journal of Hydraulic Engineering, 19, 227-234. http://dx.doi.org/10.1080/09715010.2013.798907
[7]	Dripps, W. R., & Bradbury, K. R. (2007). A Simple Daily Soil-Water Balance Model for Estimating the Spatial and Temporal Distribution of Groundwater Recharge in Temperate Humid Areas. Hydrogeology Journal, 15, 433-444. http://dx.doi.org/10.1007/s10040-007-0160-6
[8]	Drusch, M. (2007). Initializing Numerical Weather Prediction Models with Satellite-Derived Surface Soil Moisture: Data Assimilation Experiments with ECMWF’s Integrated Forecast System and the TMI Soil Moisture Data Set. Journal of Geophysical Research, 112, D03102. http://dx.doi.org/10.1029/2006JD007478
[9]	Ek, M. B., & Holtslag, A. A. M. (2004). Influence of Soil Moisture on Boundary Layer Cloud Development. Journal of Hydrometeorology, 5, 86-99. http://dx.doi.org/10.1175/1525-7541(2004)005<0086:IOSMOB>2.0.CO;2
[10]	Entekhabi, D., Rodriguez-Iturbe, I., and Castelli, F. (1996). Mutual Interaction of Soil Moisture State and Atmospheric Processes. Journal of Hydrology, 184, 3-17. http://dx.doi.org/10.1016/0022-1694(95)02965-6
[11]	Fan, Y., & van den Dool, H. (2004). Climate Prediction Center Global Monthly Soil Moisture Data Set at 0.5 Resolution for 1948 to Present. Journal of Geophysical Research, 109, D10102. http://dx.doi.org/10.1029/2003JD004345
[12]	Gaur, N., & Mohanty, B. P. (2013). Evolution of Physical Controls for Soil Moisture in Humid and Subhumid Watersheds. Water Research, 49, 1244-1258. http://dx.doi.org/10.1002/wrcr.20069
[13]	GCOS (2010). Global Climate Observing System (GCOS). Implementation Plan for the Global Climate Observing System in Support of the UNFCCC (2010 Update), GCOS-138. UNEP and Intl. Council for Science.
[14]	Genest, C., Remillard, B., & Beaudoin, D. (2009). Goodness-of-Fit Tests for Copulas: A Review and a Power Study. Insurance: Mathematics and Economics, 44, 199. http://dx.doi.org/10.1016/j.insmatheco.2007.10.005
[15]	Huang, J, van den Dool, H. M., & Georgakakos, K. P. (1996). Analysis of Model Calculated Soil Moisture over the United States (1931-1993) and Applications to Long Range Temper-ature Forecasts. J. of Cli., 9, 1351-1362. http://dx.doi.org/10.1175/1520-0442(1996)009<1350:AOMCSM>2.0.CO;2
[16]	Kao, S. C., & Govindraju, S. C. (2008). Trivariate Statistical Analysis of Extreme Rainfall Events via the Plackett Family of Copulas. Water Resources Research, 44, W02415. http://dx.doi.org/10.1029/2007WR006261
[17]	Kendall, M. G. (1962). Rank Correlation Methods (4th ed.). London: Griffin.
[18]	Maity, R., & Kashid S. S. (2011), Importance Analysis of Local and Global Climate Inputs for Ba-sin-Scale Streamflow Prediction. Water Resources Research, 47, W11504. http://dx.doi.org/10.1029/2010WR009742
[19]	Maity, R., & Nagesh Kumar, D. (2008). Probabilistic Prediction of Hy-droclimatic Variables with Nonparametric Quantification of Uncertainty. Journal of Geophysical Research, 113, D14105, 12.
[20]	Nelsen, R. B. (2006). An Introduction to Copulas (2nd ed.). New York: Springer, 269.
[21]	Oyedele, D. J., & Tijani, F. O. (2010). Spatial and Temporal Variability of Soil Water Content. International Agrophysics, 24, 171-176.
[22]	Panareda, A. A., Balsamo, G., & Beljaars, A. (2010). Impact of Improved Soil Moisture on the ECMWF Precipitation Forecast in West Africa. Geophysical Research Letters, 37, L20808.
[23]	Pandey, V., & Pandey, P. K. (2010). Spatial and Temporal Variability of Soil Moisture. International Journal of Geosciences, 1, 87-98. http://dx.doi.org/10.4236/ijg.2010.12012
[24]	Porporato, A., Daly, E., & Rodriguez-Iturbe, I. (2004). Soil Water Balance and Ecosystem Response to Climate Change. The American Naturalist, 164, 625-632. http://dx.doi.org/10.1086/424970
[25]	Rodriguez-Iturbe, I., Porporato, A., Liao, F., & Ridolfi L. (2001). Plants in Wa-ter-Controlled Ecosystem: Active Role in Hydrologic Process and Response to Water Stress, I. Scope and general outline. Advances in Water Resources, 24, 695-705. http://dx.doi.org/10.1016/S0309-1708(01)00004-5
[26]	Rosenbaum, U., Bogena, H. R., Huisman, J. A., Peterson, T. J., Weuthen, A., Western, A. W., & Vereecken, H. (2012). Seasonal and Event Dynamics of Spatial Soil Moisture Patterns at the Small Catchment Scale. Water Resources Research, 48, W10544. http://dx.doi.org/10.1029/2011WR011518
[27]	Schmidt, T. (2006). Coping with Copulas in “Copulas: From Theory to Applications in Finance”. London: Risk Books.
[28]	Seneviratne, S. I., Corti, T., Davin, E. L., Hirschi, M., Jaeger, E. B., Lehner, I., Orlowsky, B., & Teuling, A. J. (2010). Investigating Soil Moisture–Climate Interactions in a Changing Climate: A Review. Earth Science Reviews, 99, 125-161. http://dx.doi.org/10.1016/j.earscirev.2010.02.004
[29]	USDA (2009). Chapter 7 Hydrologic Soil Groups, Part 630 Hy-drology, National Engineering Handbook. National Resources Conservation Service, United States Department of Agri-culture. 210-VI-NEH.
[30]	Willmott, C. J., Robesonb, S. M., & Matsuuraa, K. (2012). Short Communication: A Refined Index of Model Performance. Intl. Journal of Climate.