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Sustainability
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Land Evapotranspiration and Groundwater Recycling
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Land Evapotranspiration and Groundwater Recycling

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: closed (10 April 2023) | Viewed by 4627

Special Issue Editors

Dr. Zhenhua Di

E-Mail Website
Guest Editor
State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China
Interests: evapotranspiration modeling; hydrological process simulation; land-atmosphere interaction; parameter optimization
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jianguo Liu

E-Mail Website
Guest Editor
School of Mathematics and Computational Sciences, Huaihua University, Huaihua 418000, China
Interests: ensemble forecasting of land evapotranspiration; numerical simulaiton of groundwater; drought
Prof. Dr. Keqiang Dong

E-Mail Website
Guest Editor
College of science, Civil Aviation University of China, Tianjin 300399, China
Interests: land evapotranspiration monitoring; groundwater monitoring; terrestrial water budget
Dr. Shenglei Zhang

E-Mail Website
Guest Editor
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Interests: remote sensing monitoring of land evapotranspiration; land data assimilation

Special Issue Information

Dear Colleagues,

Land evapotranspiration is a critical variable in land–atmosphere coupling, and therefore, its accurate estimation is very important for understanding land–atmosphere interaction. Because of this, contemporary studies have shifted their focus from land surface visible variables such as surface streamflow, soil moisture, and leaf area index to the invisible variable of land evapotranspiration. Groundwater is another invisible variable that is difficult to obtain because of its storage location. However, the variation of groundwater significantly affects land evapotranspiration by transmitting water content from the unsaturated soil column. Overall, land evaporation and groundwater are important variables of land–atmosphere interaction, but their estimations include great uncertainties.

At present, an increasing number of new techniques have been used to estimate and demonstrate the variations of land evaporation and groundwater, such as station instrument observation, satellite remote sensing inversion, land surface data assimilation, complex numerical algorithm, land model simulation, and ensemble forecasting. As a result, the demands for estimating land evapotranspiration and groundwater data or demonstrating their variation attributions using these new technologies are growing in many parts of the world. This Special Issue of Sustainability focuses on advances on land evapotranspiration and groundwater recycling. Potential topics include but are not limited to the following:

  • Satellite-based land evapotranspiration estimation;
  • Evaluation of multiple land evapotranspiration products;
  • Generation and assessment of land evapotranspiration and groundwater products;
  • GRACE gravity satellite estimation method;
  • Land surface data assimilation
  • Remote sensing data fusion;
  • Land surface simulation;
  • Ensemble simulation and forecasting;
  • Model parameter optimization;
  • Machine learning for model simulation and application
  • Global and regional land evapotranspiration and groundwater evaluation.

Dr. Zhenhua Di
Prof. Dr. Jianguo Liu
Prof. Dr. Keqiang Dong
Dr. Shenglei Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • land evapotranspiration
  • groundwater
  • satellite data evaluation
  • modelling simulation
  • data assimilation
  • ensemble forecasting
  • numerical algorithm
  • uncertainty analysis
  • machine learning
  • water energy budget

Published Papers (2 papers)

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Research

18 pages, 1003 KiB  
Article
Vector Autoregression Model-Based Forecasting of Reference Evapotranspiration in Malaysia
by Phon Sheng Hou, Lokman Mohd Fadzil, Selvakumar Manickam and Mahmood A. Al-Shareeda
Sustainability 2023, 15(4), 3675; https://doi.org/10.3390/su15043675 - 16 Feb 2023
Cited by 4 | Viewed by 2146
Abstract
Evapotranspiration is one of the hydrological cycle’s most important elements in water management across economic sectors. Critical applications in the agriculture domain include irrigation practice improvement and efficiency, as well as water resource preservation. The main objective of this research is to forecast [...] Read more.
Evapotranspiration is one of the hydrological cycle’s most important elements in water management across economic sectors. Critical applications in the agriculture domain include irrigation practice improvement and efficiency, as well as water resource preservation. The main objective of this research is to forecast reference evapotranspiration using the vector autoregression (VAR) model and investigate the meteorological variables’ causal relationship with reference evapotranspiration using a statistical approach. The acquired 20-year, 1-year, and 2-month research climate datasets from Penang, Malaysia, were split into 80% training data and 20% validation data. Public weather data are used to train the initial VAR model. A Raspberry Pi IoT device connected to a DHT11 temperature sensor was outfitted at the designated experimental crop site. In situ data acquisition was done using DHT11 temperature sensors to measure the ambient temperature and humidity. The collected temperature and humidity data were used in conjunction with the vector autoregression (VAR) model to calculate the reference evapotranspiration forecast. The results demonstrated that the 20-year dataset showed better performance and consistent results in forecasting general reference evapotranspiration, derived using root mean square error (RMSE) and correlation coefficient (CORR) of 1.1663 and −0.0048, respectively. As for the 1-year dataset model, RMSE and CORR were recorded at 1.571 and −0.3932, respectively. However, the 2-month dataset model demonstrated both positive and negative performance due to seasonal effects in Penang. The RMSE ranged between 0.5297 to 2.3562 in 2020, 0.8022 to 1.8539 in 2019, and 0.8022 to 2.0921 in 2018. As for CORR, it ranged between −0.5803 to 0.2825 in 2020, −0.3817 to 0.2714 in 2019, and −0.3817 to 0.2714 in 2018. In conclusion, the model tested using 20-year, 1-year, and 2-month meteorological datasets for estimating reference evapotranspiration (ET0) based on smaller RMSEs demonstrates better performance at predicting the true values, as well as producing both positive and negative CORR performance due to seasonal variations in Penang. Full article
(This article belongs to the Special Issue Land Evapotranspiration and Groundwater Recycling)
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17 pages, 5651 KiB  
Article
Impact of Noah-LSM Parameterizations on WRF Mesoscale Simulations: Case Study of Prevailing Summer Atmospheric Conditions over a Typical Semi-Arid Region in Eastern Spain
by Igor Gómez, Sergio Molina, Juan José Galiana-Merino, María José Estrela and Vicente Caselles
Sustainability 2021, 13(20), 11399; https://doi.org/10.3390/su132011399 - 15 Oct 2021
Cited by 1 | Viewed by 1623
Abstract
The current study evaluates the ability of the Weather Research and Forecasting Model (WRF) to forecast surface energy fluxes over a region in Eastern Spain. Focusing on the sensitivity of the model to Land Surface Model (LSM) parameterizations, we compare the simulations provided [...] Read more.
The current study evaluates the ability of the Weather Research and Forecasting Model (WRF) to forecast surface energy fluxes over a region in Eastern Spain. Focusing on the sensitivity of the model to Land Surface Model (LSM) parameterizations, we compare the simulations provided by the original Noah LSM and the Noah LSM with multiple physics options (Noah-MP). Furthermore, we assess the WRF sensitivity to different Noah-MP physics schemes, namely the calculation of canopy stomatal resistance (OPT_CRS), the soil moisture factor for stomatal resistance (OPT_BTR), and the surface layer drag coefficient (OPT_SFC). It has been found that these physics options strongly affect the energy partitioning at the land surface in short-time scale simulations. Aside from in situ observations, we use the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) sensor to assess the Land Surface Temperature (LST) field simulated by WRF. Regarding multiple options in Noah-MP, WRF has been configured using three distinct soil moisture factors to control stomatal resistance (β factor) available in Noah-MP (Noah, CLM, and SSiB-types), two canopy stomatal resistance (Ball–Berry and Jarvis), and two options for surface layer drag coefficients (Monin–Obukhov and Chen97 scheme). Considering the β factor schemes, CLM and SSiB-type β factors simulate very low values of the latent heat flux while increasing the sensible heat flux. This result has been obtained independently of the canopy stomatal resistance scheme used. Additionally, the surface skin temperature simulated by Noah-MP is colder than that obtained by the original Noah LSM. This result is also highlighted when the simulated surface skin temperature is compared to the MSG-SEVIRI LST product. The largest differences between the satellite data and the mesoscale simulations are produced using the Noah-MP configurations run with the Monin–Obukhov parameterization for surface layer drag coefficients. In contrast, the Chen97 scheme shows larger surface skin temperatures than Monin–Obukhov, but at the expense of a decrease in the simulated sensible heat fluxes. In this regard, the ground heat flux and the net radiation play a key role in the simulation results. Full article
(This article belongs to the Special Issue Land Evapotranspiration and Groundwater Recycling)
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