Strategies of Parameter Optimization and Soil Moisture Sensor Deployment for Accurate Estimation of Evapotranspiration Through a Data-driven Method

被引:4
|
作者
Chai, Yuanyuan [1 ,2 ,3 ]
Liu, Hu [1 ,2 ,3 ]
Yu, Yang [4 ]
Yang, Qiyue [1 ,2 ]
Zhang, Xiaoyou [1 ,2 ]
Zhao, Wenzhi [1 ,2 ]
Guo, Li [5 ]
Yetemen, Omer [6 ]
机构
[1] Chinese Ecosyst Res Network, Linze Inland River Basin Res Stn, Lanzhou 730000, Peoples R China
[2] Chinese Acad Sci, Northwest Inst Ecoenvironm & Resources, Lanzhou 730000, Peoples R China
[3] Univ Chinese Acad Sci, Beijing 100029, Peoples R China
[4] Beijing Forestry Univ, Sch Soil & Water Conservat, Beijing 100038, Peoples R China
[5] Sichuan Univ, State Key Lab Hydraul & Mt River Engn, Chengdu 610000, Peoples R China
[6] Istanbul Tech Univ, Eurasia Inst Earth Sci, TR-34469 Istanbul, Turkiye
基金
中国国家自然科学基金;
关键词
Soil moisture; Data -driven method; Richards ? equation; Evapotranspiration; Installation depth; ROOT-WATER-UPTAKE; IRRIGATED AGRICULTURAL FIELD; ENERGY-BALANCE CLOSURE; RICHARDS EQUATION; HYDRAULIC CONDUCTIVITY; NUMERICAL-SOLUTION; MODEL; FOREST; GROWTH; WHEAT;
D O I
10.1016/j.agrformet.2023.109354
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
A soil moisture data-driven method through inversely solving the Richards' equation was tested, and proved to be a reliable alternative estimator of actual evapotranspiration (ETa) for relatively homogeneous soils in an arid region. Few studies have examined the feasibility of the method using soil moisture for soils with more heterogeneities, which may lead to biased parameters and varied root depths, and thus inaccurate estimates of ETa. We used a genetic algorithm to optimize the parameters most sensitive to ETa estimation, then estimated daily and seasonal ETa using hourly soil moisture data, measured from four sites (from surface to 2-m depth at 20-cm intervals) with different soil textures and crop species in desert-oasis farmlands in northwest China. The seasonal ETa values were 487, 574, 436, and 377 mm at the sites cropped with field maize, spring wheat, seed maize, and seed maize, respectively, in 2018. The daily rates from one site were validated against the eddy-covariance measurements, and the daily rates from all the sites were compared against the estimations from a simple water balance method, and both showed good consistency (R2 = 0.72-0.93). The inverse method has great potential for relatively accurate estimates of ETa in the middle and late growing stages but may induce a slight underestimation in the initial growing season. To determine the minimum monitoring depths of sensors for relatively accurate estimates, ETa values were estimated using soil moisture data at various observation depths, and were compared with eddy-covariance measurements and hypothetical ETa-observed depth curves. The results showed that inaccurate stratification of soil types in the profiles may cause great uncertainty in the estimates, and if texture-contrasting interlayers exist in the profiles, the lowest soil moisture sensor should be placed sufficiently deep, with all the interlayers fully included.
引用
收藏
页数:15
相关论文
共 37 条
  • [1] PARAMETER ESTIMATION AND DATA-DRIVEN METHOD FOR FOREST FIRE PREDICTION
    Li, X.
    Tang, C.
    Zhang, M.
    Zhang, S.
    Li, S.
    Wang, Y.
    Sun, S.
    Liu, J.
    MATHEMATICAL AND COMPUTATIONAL FORESTRY & NATURAL-RESOURCE SCIENCES, 2023, 15 (01): : 7 - 16
  • [2] PARAMETER ESTIMATION AND DATA-DRIVEN METHOD FOR FOREST FIRE PREDICTION
    Li, X.
    Tang, C.
    Zhang, M.
    Zhang, S.
    Li, S.
    Wang, Y.
    Sun, S.
    Liu, J.
    Mathematical and Computational Forestry and Natural-Resource Sciences, 2023, 15 (01): : 7 - 16
  • [3] An Automated Data-Driven Irrigation Scheduling Approach Using Model Simulated Soil Moisture and Evapotranspiration
    Zhao, Haoteng
    Di, Liping
    Guo, Liying
    Zhang, Chen
    Lin, Li
    SUSTAINABILITY, 2023, 15 (17)
  • [4] Simulation Failure-Robust Bayesian Optimization for Data-Driven Parameter Estimation
    Chakrabarty, Ankush
    Bortoff, Scott A. A.
    Laughman, Christopher R. R.
    IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2023, 53 (05): : 2629 - 2640
  • [5] Data-driven sensor placement optimization for accurate and early prediction of stochastic complex systems
    Farid, Maor
    Solav, Dana
    JOURNAL OF SOUND AND VIBRATION, 2023, 543
  • [6] Estimation of Evapotranspiration Rates and Root Water Uptake Profiles From Soil Moisture Sensor Array Data
    Li, Weiyu
    Wainwright, Haruko M.
    Yan, Qina
    Zhou, Haiyan
    Dafflon, Baptiste
    Wu, Yuxin
    Versteeg, Roelof
    Tartakovsky, Daniel M.
    WATER RESOURCES RESEARCH, 2021, 57 (11)
  • [7] A dynamic data-driven method for dealing with model structural error in soil moisture data assimilation
    Zhang, Qiuru
    Shi, Liangsheng
    Holzman, Mauro
    Ye, Ming
    Wang, Yakun
    Carmona, Facundo
    Zha, Yuanyuan
    ADVANCES IN WATER RESOURCES, 2019, 132
  • [8] Data-Driven Feedforward Parameter Tuning Optimization Method Under Actuator Constraints
    Yang, Liangliang
    Zhang, Hui
    IEEE-ASME TRANSACTIONS ON MECHATRONICS, 2022, 27 (05) : 3429 - 3439
  • [9] Data-driven spatio-temporal estimation of soil moisture and temperature based on Lipschitz interpolation
    Manzano, J. M.
    Orihuela, L.
    Pacheco, E.
    Pereira, M.
    ISA TRANSACTIONS, 2025, 156 : 535 - 550
  • [10] Investigating the capabilities of evolutionary data-driven techniques using the challenging estimation of soil moisture content
    Elshorbagy, Amin
    El-Baroudy, Ibrahim
    JOURNAL OF HYDROINFORMATICS, 2009, 11 (3-4) : 237 - 251