Soil-Moisture Estimation of Root Zone through Vegetation-Index-Based Evapotranspiration-Fraction and Soil-Properties (SERVES) Users Manual Version 1.0

reportActive / Technical Report | Accesssion Number: AD1207471 | DOI: 10.21079/11681/47399 | Open PDF

Abstract:

PURPOSE: The purpose of this users guide is to provide background methods and implementation guidance on the Soil-moisture Estimation of Root Zone through Vegetation-Index-Based Evapotranspiration-Fraction and Soil-Properties (SERVES) model (Pradhan 2019). INTRODUCTION: Research and development of an effective method for obtaining effective rootzone soil moisture content from remotely sensed aerial and satellite data significantly aids in measuring and monitoring water-related stress in plants and the environment (Berg et al. 2017; Kang et al. 2009; Mananze et al. 2019). Realistic root-zone soil moisture initial condition is a primary driver for an effective simulation of surface water and groundwater interaction, through infiltration or exfiltration, and land atmospheric interaction, through evapotranspiration (ET) in a physics-based hydrological model (Pradhan 2019; Pradhan et al. 2020). Satellite-based digital soil-moisture data represent the top few centimeters (less than 10 cm*) of the soil column. Such shallow-depth soil moisture observations do not inform about the effective root-zone wetness. SERVES (Pradhan 2019, 2021) was developed to improve the estimation of root-zone soil moisture distribution at a fine spatial resolution through globally available, remotely sensed digital data and soil physical properties. It is a useful method, especially in the arid and semiarid climatic regions where the topography is less dominant in the distribution of soil moisture as compared to that in humid catchments (Pradhan 2019, 2021). The SERVES method is simple and computationally straightforward, which bypasses the complexity of ground-based auxiliary measurements, especially in an ungauged environment. The methods application and verification are shown in Pradhan (2019). Pradhan et al. (2020) shows the effect of input initial soil moisture resolution on hydrological modeling.

Author(s):
Pradhan, Nawa R.
Author Organization(s):
ENGINEER RESEARCH AND DEVELOPMENT CENTER VICKSBURG MS
Funding Organization(s):
ENGINEER RESEARCH AND DEVELOPMENT CENTER VICKSBURG MS, VICKSBURG, MS
Document Type:
Technical Report/Technical Note
Publication Date:
2023 Aug 07
Pagination:
13

Security Markings

DOCUMENT & CONTEXTUAL SUMMARY

Distribution Code:
A - Approved For Public Release
Distribution Statement: Public Release.
Copyright: Not Copyrighted

RECORD

Collection: TRECMS
Subject Terms
Descriptor(s):
water resources, geographic information systems, moisture content, engineering, natural resources, physical properties, soil surveys, artificial satellites, data sets, drainage basins, engineers, equations, remote sensing, satellite imaging, water, databases, digital data
Keyword(s):
serves (Soil-Moisture Estimation of Root Zone through Vegetation-Index-Based Evapotranspiration-Fraction and Soil Properties), aet (Actual evapotranspiration), pet (plant-specific potential evapotranspiration), sm (soil moisture)
Subject Categories:
Mathematical and Computer Sciences; Earth Sciences and Oceanography
Modernization Areas:
Space
Communities of Interest:
;
Descriptor(s):
water resources, moisture content, physical properties, engineering, natural resources, artificial satellites, data sets, drainage basins, environment, equations, satellite imaging, water, databases, digital data, engineers, geography, moisture
Creation Date:
2023 Aug 11
Update Date:
2023 Oct 23