Online Submission!

Open Journal Systems

PERFORMANCE ASSESSMENT OF PSO AND GA IN ESTIMATING SOIL HYDRAULIC PROPERTIES USING NEAR-SURFACE SOIL MOISTURE OBSERVATIONS

Navsal Kumar, Arunava Poddar, Ashish Dobhal, Vijay Shankar

Abstract


Quantification of soil moisture movement and water uptake dynamics in the vadose zone for sound irrigation management requires the knowledge of soil hydraulic properties. Non-availability of complex and expensive instrumentation hinders identification of soil hydraulic and retention characteristics. The study presents the application of Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) in identifying soil moisture retention θ(h) and hydraulic conductivity K(h) functions by inverting a SWAP model using observed near-surface soil moisture (0-10 cm). Two hydrologic cases, i.e. homogenous soil column with free drainage and with Shallow Groundwater Table (SGT) at the lower boundary, are considered. Study takes into account the agro-climatic data of Palampur (Himachal Pradesh), India. Results for both cases establish the applicability of GA and PSO in identifying soil hydraulic parameters. The identification of soil hydraulic parameters is more accurate when the soil column is draining in comparison to that with SGT. The comparative evaluation of simulated to the field observed soil moisture content indicates root mean square error of 0.0163 and 0.0297 for GA and PSO respectively. GA provides an effective alternative to estimate soil hydraulic properties using inverse approach in absence of experimental values.

Keywords


Genetic algorithm, Particle Swarm Optimization, soil properties

Full Text:

PDF

References


Mohanty B P and Zhu J 2007 Effective averaging schemes for hydraulic parameters in horizontally and vertically heterogeneous soils J. Hydrometeorol. 8(4) 715– 729

Poddar A, Kumar N and Shankar V 2018 Evaluation of two irrigation scheduling methodologies for potato (Solanum tuberosum L.) in north-western mid-hills of India ISH Journal of Hydraulic Engineering 1-10 (https://doi.org/10.1080/09715010.2018.1518733)

Ojha C S P, Hari Prasad K S, Shankar V and Madramootoo C A 2009 Evaluation of a non-linear root water uptake model ASCE Journal of Irrigation and Drainage Engineering 135(3) 302-312

Shankar V, Hari Prasad K S, Ojha C S P and Govindaraju R S 2012 Model for Non-Linear Root Water Uptake Parameter ASCE Journal of Irrigation and Drainage Engineering 138(10) 905-917

Kumar R, Shankar V and Jat M K 2013 Soil moisture dynamics modelling considering multi-layer root zone Water Science and Technology 67(8) 1778-1785

Xevi E, Gilley J and Feyen J 1996 Comparative study of two crop yield simulation models Agric. Water Manage. 30 155 – 173

Poddar A, Kumar N, and Shankar V 2019 Computation of moisture uptake based irrigation schedules to counter ill effects of saline irrigation on agricultural productivity. IASR Journal of Advanced Research in Dynamical and Control Systems 11 1004-1013

Dirksen C 1991 Unsaturated hydraulic conductivity. In: Soil analysis: Physical methods Smith K A and Mullins C E New York Marcel Dekker 209–269

Shankar V 2007 Modelling of moisture uptake by plants Ph.D. dissertation Dept. of Civil Engineering Indian Institute of Technology Roorkee India

Abbaspour K C, Schulin R and van Genuchten M T 2001 Estimating soil hydraulic parameters using ant colony optimization Adv. Water Resour. 24 827–841

Antonopolous V Z 2000 Modelling of soil water dynamics in an irrigated corn field using direct and pedo-transfer functions for hydraulic properties Irrig. Drainage Syst. 14 325–342

Wosten J H M, Lilly A, Nemes A and Le Bas C 1998 Using existing soil data to derive hydraulic parameters for simulation models in environmental studies and in land use planning Report 156 DLO Winand Staring Centre Netherlands

Yeh W W G 1986 Review of parameter identification procedures in groundwater hydrology: The inverse problem Water Resour. Res. 22 95–108

Van Dam J C, Huygen J, Wesseling J G, Feddes R A, Kabat P, Waslum P E V, Groenendjik P and Van Diepen C A 1997 Theory of SWAP version 2.0: Simulation of water flow and plant growth in the soil water-atmosphere-plant environment Tech. Doc. 45 Wageningen Agric. Univ. and DLO Winand Staring Cent. Wageningen Netherlands

Mualem Y 1976 A new model for predicting the hydraulic conductivity of unsaturated porous media. Water Resour. Res. 12 513–522

Van Genuchten M T 1980 A closed form equation for predicting the hydraulic conductivity of unsaturated soils Soil Sci. Soc. Amer. J. 44 349–386

Shin Y, Mohanty B P and Ines A V M 2012 Soil hydraulic properties in one dimensional layered soil profile using layer-specific soil moisture assimilation scheme Water Resour. Res. 48 W06529

Sonkar I, Kaushika G S and Hari Prasad K S 2018 Modelling Moisture Flow in Root Zone: Identification of Soil Hydraulic and Root Water Uptake Parameters ASCE Journal of Irrigation and Drainage Engineering 144(10) 04018029

Ines A V M and Mohanty B P 2008 Near-surface soil moisture assimilation for quantifying effective soil hydraulic properties using genetic algorithm: I. Conceptual modeling. Water Resour. Res. 44 W06422

Li C Y, Ren L and Li B G 2001 Parametric estimation of the Van Genuchten's equation by the optimization method Advances in Water Science 12(4) 473-478

Chen D and Ma Y 2006 Optimized algorithm for estimating parameters by solving Van Genuchten equation based on stochastic particle swarm optimization Nongye Gongcheng Xuebao (Transactions of the Chinese Society of Agricultural Engineering) 22(12) 82-85

Ines A V M and Droogers P 2002 Inverse modelling in estimating soil hydraulic functions: A genetic algorithm approach Hydrol. Earth Syst. Sci. 6 49– 65

Richards L A 1931 Capillary conduction of liquids through porous medium Physics 1 318-333

Belmans C, Wesseling J G and Feddes R A 1983 Simulation of water balance of a cropped soil: SWATRE J. Hydrol. 63 271– 286

Feddes R A, Kowalik P J and Zarandy H 1982 Simulation of field water use and crop yield Pudoc Wageningen The Netherlands

Poddar A, Gupta P, Kumar N, Shankar V and Ojha C S P 2018 Evaluation of reference evapotranspiration methods and sensitivity analysis of climatic parameters for sub-humid sub-tropical locations in western Himalayas (India) ISH Journal of Hydraulic Engineering 1-11 ()

Goldberg D E 1989 Genetic algorithms in search and optimization and machine learning Addison-Wesley Publ. Reading MA

Vrugt J A, Hopmans J W and Simunek J 2001 Calibration of a two-dimensional root water uptake model Soil Sci. Soc. Am. J. 65 1027–1037

Savic D and Khu S T 2005 Evolutionary computing in hydrological sciences, in Encyclopedia of Hydrological Sciences Anderson M G New Jersey John Wiley chap. 22 1 –22

Leij F J, Alves W J, Van Genuchten M T and Williams J R 1999 The UNSODA unsaturated soil hydraulic database, In Characterization and Measurement of the Hydraulic Properties of Unsaturated Porous Media Van Genuchten M T et al. Univ. of Calif. Riverside 1269– 1281

Kennedy J and Eberhart R November 1995 Particle swarm optimization (PSO) In Proc. IEEE International Conference on Neural Networks Perth Australia 1942-1948

Zhang Y, Wang S and Ji G 2015 A comprehensive survey on particle swarm optimization algorithm and its applications Mathematical Problems in Engineering 2015 931256

Shi Y and Eberhart R 1998 Parameter selection in particle swarm optimization. In: Proc. of the 1998 annual conference on evolutionary computation New York Springer-Verlag 591–600

Ines A V M and Mohanty B P 2009 Near-surface soil moisture assimilation for quantifying effective soil hydraulic properties using genetic algorithms: II. Using airborne remote sensing during SGP97 and SMEX02 Water Resources Research 45(1)

Trout T J, Garcia-Castillas I G and Hart W E 1982 Soil water engineering: field and laboratory manual Jaipur, India Academic Publishers

Numerical Algorithms Group (NAG) 1990 Routine name E04FDF Numerical Algorithms Group FORTRAN Library Manual Mark 14

de Jesus W C, do Vale F X R, Coelho R R and Costa L C 2001 Comparison of two methods for estimating leaf area index on common bean Agron. J. 93(5) 989–991

Vashist, S.K. and Chhabra, D., 2014, March. Optimal placement of piezoelectric actuators on plate structures for active vibration control using genetic algorithm. In Active and Passive Smart Structures and Integrated Systems 2014 (Vol. 9057, p. 905720). International Society for Optics and Photonics.

Dhingra, A., Chandna, P 2010 Multi-objective flow shop scheduling using hybrid simulated annealing Measuring Business Excellence 14(3), pp. 30-41




DOI: http://dx.doi.org/10.6084/ijact.v8i8.996

Refbacks

  • There are currently no refbacks.




Copyright (c) 2019 COMPUSOFT: An International Journal of Advanced Computer Technology