[1]DU Xiaotong,FANG Xiuqin,WANG Wei,et al.Estimation of Soil Moisture in Root Zone of Semiarid Area Based on SMAR Model[J].Research of Soil and Water Conservation,2020,27(03):119-127,133.
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Estimation of Soil Moisture in Root Zone of Semiarid Area Based on SMAR Model
Research of Soil and Water Conservation[ISSN 1005-3409/CN 61-1272/P] Volume:
27
Number of periods:
2020 03
Page number:
119-127,133
Column:
目次
Public date:
2020-04-20
- Title:
- Estimation of Soil Moisture in Root Zone of Semiarid Area Based on SMAR Model
- Keywords:
- CDF matching; SMAR model; surface layer; root zone; soil moisture
- CLC:
- S152.7
- DOI:
- -
- Abstract:
- Soil moisture in root zone controls the process of water absorption and transpiration of vegetation, which is an important variable in land-atmosphere interaction. In order to obtain the spatial and temporal distribution of soil moisture in root zone, we select the Laohahe River Basin located in the semiarid area as the research area, and examine the patterns of soil moisture in root zones by using the physical soil moisture analytical relationship(SMAR)model and the remote sensing soil moisture products. The results show that the equation for estimating the parameters of SMAR model (p<0.05, two-tailed t-test)can be established by using soil physical properties, the normalized vegetation index and the actual evapotranspiration as independent variables for multivariate linear regression analysis. The combination of remote sensing soil moisture products and SMAR model has a good performance for the estimation of soil moisture in the root zones of the region. Compared the estimation results based on the remotely sensed SM products with the ones based on the field measurements, the correlation coefficients mainly distributed in range of 0.5～0.9, with the average value of 0.692 (p<0.05, two-tailed t-test). The mean absolute error, the mean relative error, the mean square root error, and the standard deviation are generally less than 0.1. In general, the combination of SMAR model and remote sensing data products can well estimate the spatial distribution of soil moisture in root zones at the regional scale. This study can provide the support for the estimation of soil moisture in the root zones at larger scale, and can improve agricultural planning, drought monitoring and other hydrological simulation in the arid and semi-arid areas.
- References:
-
[1] Manfreda S, Brocca L, Moramarco T, et al. A physically based approach for the estimation of root-zone soil moisture from surface measurements[J]. Hydrology and Earth System Sciences, 2014,18(3):1199-1212.
[2] Zohaib M, Kim H, Choi M. Evaluating the patterns of spatiotemporal trends of root zone soil moisture in major climate regions in East Asia[J]. Journal of Geophysical Research-Atmospheres, 2017,122(15):7705-7722.
[3] Schnur M T, Xie H J, Wang X W. Estimating root zone soil moisture at distant sites using MODIS NDVI and EVI in a semi-arid region of southwestern USA[J]. Ecological Informatics, 2010,5(5):400-409.
[4] Calvet J C, Noilhan J, Bessemoulin P. Retrieving the root-zone soil moisture from surface soil moisture or temperature estimates:a feasibility study based on field measurements[J]. Journal of Applied Meteorology, 1998,37(4):371-386.
[5] Manfreda S, Caylor K K, Good S. An Ecohydrological framework to explain shifts in vegetation organization across climatological gradients[J]. Ecohydrology, 2016,10(3):1809-1823.
[6] Baldwin D, Manfreda S, Keller K, et al. Predicting root zone soil moisture with soil properties and satellite near-surface moisture data across the conterminous United States[J]. Journal of Hydrology, 2017,546:393-404.
[7] Faridani F, Farid A, Ansari H, et al. A modified version of the SMAR model for estimating root-zone soil moisture from time-series of surface soil moisture[J]. Water Sa, 2017,43(3):492-498.
[8] Shi C X, Xie Z H, Qian H, et al. China land soil moisture EnKF data assimilation based on satellite remote sensing data[J]. Science China(Earth Sciences),2011,54(9):1430-1440.
[9] Dumedah G, Coulibaly P. Evolutionary assimilation of streamflow in distributed hydrologic modeling using in-situ soil moisture data[J]. Adv. Water Resour.,2012,53:231-241.
[10] Reichle R, Crow W T, Koster R T, et al. Algorithm Theoretical Basis Document Level 4 Surface and Root Zone Soil Moisture(L4_SM)Data Product[J]. National Aerounautics and Space Administration(NASA),2014:1-65.
[11] Albergel C, Pellarin T, Fritz N, et al. From near-surface to root-zone soil moisture using an exponential filter:an assessment of the method based on in-situ observations and model simulations[J]. Hydrology and Earth System Sciences, 2008,12(6):1323-1337.
[12] Ford T W, Harris E, Quiring S M. Estimating root zone soil moisture using near-surface observations from SMOS[J]. Hydrology and Earth System Sciences, 2014,18(1):139-154.
[13] Gao X D, Zhao X N, Zhang B Q, et al. Estimation of root-zone soil moisture over gullies using an exponential filter[J]. Advances in Water Science, 2014,25(5):684-694.
[14] Faridani F, Farid A, Ansari H, et al. Estimation of the Root-Zone Soil Moisture Using Passive Microwave Remote Sensing and SMAR Model[J]. Journal of Irrigation and Drainage Engineering, 2017,143(1):1-9.
[15] Wagner W, Lemoine G, Rott H. A method for estimating soil moisture from ERS scatterometer and soil data[J]. Remote Sensing of Environment, 1999,70(2):191-207.
[16] 张玲,安如,王喆.主/被动微波遥感数据融合的土壤湿度产品的CDF改进研究[J].科学技术与工程,2015,15(30):1-8.
[17] 席承藩,朱克贵,李象榕,等.中国土种志(第二卷)[M].北京:中国农业出版社,1994.
[18] 席承藩,朱克贵,李象榕,等.中国土种志(第四卷)[M].北京:中国农业出版社,1995.
[19] 席承藩,朱克贵,李象榕,等.中国土种志(第五卷)[M].北京:中国农业出版社,1995.
[20] 张苹苹.集合卡尔曼滤波方法在密云潮河流域洪水预报中的应用研究[D].北京:中国地质大学,2018.
[21] 涂启玉,梅亚东.Matlab遗传算法工具GUI率定马斯京根模型参数[J].水文,2008(5):33-35,70.
[22] Goldberg D E. Genetic Algorithms in Search, Optimization and Machine Learning[M]. Boston: Addison-Wesley, 1989.
[23] 吴凯,舒红.基于CCI资料与EnKF方法的单点土壤湿度同化[J].水资源与水工程学报,2017,28(1):236-243.
[24] 郭焘,于红博,马梓策,等.基于MODIS的土壤含水量时空变化及干旱化程度分析[J].水土保持研究,2019,26(4):185-189.
[25] 刘苏峡,邢博,袁国富,等.中国根层与表层土壤水分关系分析[J].植物生态学报,2013,37(1):1-17.
[26] Pan F F, Nieswiadomy M, Qian S. Application of a soil moisture diagnostic equation for estimating root-zone soil moisture in arid and semi-arid regions[J]. Journal of Hydrology, 2015,524:296-310.
[27] Pan F F, Peters-Lidard C D, Sale M J. An analytical method for predicting surface soil moisture from rainfall observations[J]. Water Resources Research, 2003,39(11):1314-1334.
[28] 方秀琴,任立良,李琼芳.近40年老哈河流域土地利用变化监测与分析[J].国土资源遥感,2012(2):125-131.
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Last Update:
2020-04-30