Estimation of root zone soil moisture using passive microwave remote sensing: A case study for rice and wheat crops for three states in the Indo-Gangetic basin.

Clicks: 265
ID: 24150
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #162 of 276 articles by views in Journal of environmental management

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 276 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract
This paper investigates estimation of root zone soil moisture using two passive microwave remote sensing datasets, Advanced Microwave Scattering Radiometer - 2 and Soil Moisture Active Passive satellites sensors. The study is focused on two crops, namely rice and wheat for the Indo-Gangetic basin, India, having a dynamic crop and soil type and land use land cover. A total of 21 rice crop and 23 wheat crop locations are chosen from the states of Uttar Pradesh, Madhya Pradesh and Bihar falling in the basin. The root zone soil moisture information is derived by estimating soil wetness index from surface soil moisture at 10 and 40 cm depths using a recursive exponential filter. The soil wetness index based algorithm is implementable even in the absence of ground information for a basin level study. The reference soil moisture dataset is obtained from the Global Land Database Assimilation System - NOAH at 10 and 40 cm depth. The research has also demonstrated significant potential of GLDAS-NOAH soil moisture data in the absence of ground (in-situ) soil moisture data. Of the various factors affecting surface and root zone soil moisture, this work evaluates the control of soil constituents on root zone soil moisture. The Spearman rank correlation coefficient is estimated for characteristic time delay with sand, silt and clay percentage at different locations. Coupling between and trends of surface and root zone soil moisture for rice and wheat crop locations are studied. The accuracy of estimated soil wetness index at 10 and 40 cm from two different satellite sensors at two different acquisition times (ascending and descending passes) is investigated by calculating the coefficient of determination, mean absolute error and mean biased error. This work highlights the significant difference in surface soil moisture estimation by two satellite sensors to derive root zone soil moisture for rice and wheat crops. Coefficient of determination is more (∼0.9) for SMAP derived soil wetness index whereas it is lower (∼0.65) for AMSR-2 derived soil wetness index for both crops. Characteristic time delay variation is observed at two different times and at both the depths, with characteristic time delay increasing with depth. Also, at the descending pass characteristic time delay is lower as compared to the ascending pass. A strong relationship between root zone soil moisture and soil texture is observed. For rice crop, a positive correlation with sand and clay is observed for Uttar Pradesh, Madhya Pradesh and Bihar locations having loam and sandy loam as the major soil class. And, for wheat locations, a positive correlation is observed for silt and clay for Uttar Pradesh locations and sand for Madhya Pradesh locations having loam and clay (light) soil texture. This work delivers essential information in understanding sustainable irrigation scheduling and increasing irrigation potential for rice and wheat crop locations. Having the knowledge of all the factors influencing crop cultivation and the derived root zone soil moisture, crop production can be optimized.
Reference Key
sure2019estimationjournal Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Sure, Anudeep;Dikshit, Onkar;
Journal Journal of environmental management
Year 2019
DOI
S0301-4797(18)31537-8
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.