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Special Issue "Remote Sensing for Water Monitoring in Agricultural Management and Development"

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A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 3174

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Special Issue Editor

Dr. Alla Yurova

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Guest Editor

V.V. Dokuchaev Soil Science Institute, Pyzhevskiy Pereulok 7, Moscow 119017, Russia
Interests: climate; environment; biogeochemistry; vegetation; climate modeling; hydrology

Special Issue Information

Dear Colleagues,

Remote Sensing is indispensable source of data for the water resources management for sustainable development and is a primary source where the in-situ data collection is challenging due to sparse monitoring networks. Optimizing long-term agricultural land planning and achieving water security and increased resilience to hydrological extremes requires a good understanding of water resources dynamics at the basin scale. Satellite-based sensors are now capable of making direct and indirect measurements of nearly all components of the hydrological cycle. The reconstructed variables are precipitation, evaporation, lake and river levels, soil moisture, overland water, snow, and ground water storage. Although some of these satellite remote sensing products are less theoretically grounded and numerically developed than others, and limitations are posed by the inverse nature of the reconstructing of multi-component system, large spatial coverage and the high temporal resolution means that they can provide near global information in near real time. There is a clear need to share approaches and cutting-edge ideas that can be used to strengthen the approach of investigating mean state of water resources, to improve seasonal forecasts of hydrologic variables and prepare for potential agricultural impacts of hydrological hazards. To meet this urgent need, a Special Issue on “Remote Sensing for Water Monitoring in Agricultural Management and Development’” has been accepted by the leading international journal Sensors, to address the technical challenges for satellite monitoring or estimating of water resources.

We sincerely solicit your contributions in this field to our Sensors Special Issue. Research or review articles with respect to the following topics are welcome:

Reconstructing the components of water balance by remote sensing;
Soil moisture estimation by remote sensing;
Vegetation processes indicators derived from remote sensing evapotranspiration retrievals;
Solving agricultural planning optimization problem based on satellite data;
Assimilation of remote sensing data in the forecast hydrological models;
The research basins with long-term in situ monitoring for the satellite product validation;
Novel mathematical methods for interpretation of the remote sensing data in water management;
Flood control drought preparedness and mitigation and irrigation planning based on remote sensing data.

Dr. Alla Yurova
Guest Editor

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Published Papers (3 papers)

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Research

Open AccessArticle

Estimation of Reference Evapotranspiration in a Semi-Arid Region of Mexico

Gerardo Delgado-Ramírez

Martín Alejandro Bolaños-González

Abel Quevedo-Nolasco

Adolfo López-Pérez

and

Juan Estrada-Ávalos

Sensors 2023, 23(15), 7007; https://doi.org/10.3390/s23157007 - 07 Aug 2023

Viewed by 680

Abstract

Reference evapotranspiration (ET₀) is the first step in calculating crop irrigation demand, and numerous methods have been proposed to estimate this parameter. FAO-56 Penman–Monteith (PM) is the only standard method for defining and calculating ET₀. However, it requires radiation, air temperature, atmospheric humidity, and wind speed data, limiting its application in regions where these data are unavailable; therefore, new alternatives are required. This study compared the accuracy of ET₀ calculated with the Blaney–Criddle (BC) and Hargreaves–Samani (HS) methods versus PM using information from an automated weather station (AWS) and the NASA-POWER platform (NP) for different periods. The information collected corresponds to Module XII of the Lagunera Region Irrigation District 017, a semi-arid region in the North of Mexico. The HS method underestimated the reference evapotranspiration (ET₀) by 5.5% compared to the PM method considering the total ET₀ of the study period (26 February to 9 August 2021) and yielded the best fit in the different evaluation periods (daily, 5-day mean, and 5-day cumulative); the latter showed the best values of inferential parameters. The information about maximum and minimum temperatures from the NP platform was suitable for estimating ET₀ using the HS equation. This data source is a suitable alternative, particularly in semi-arid regions with limited climatological data from weather stations. Full article

(This article belongs to the Special Issue Remote Sensing for Water Monitoring in Agricultural Management and Development)

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Open AccessArticle

Application of the Concept of Land Degradation Neutrality for Remote Monitoring of Agricultural Sustainability of Irrigated Areas in Uzbekistan

German Kust

Olga Andreeva

and

Darya Shklyaeva

Sensors 2023, 23(14), 6419; https://doi.org/10.3390/s23146419 - 14 Jul 2023

Viewed by 357

Abstract

A scientific approach to the assessment of trends in land changes based on the novel concept of Land Degradation Neutrality (LDN) was applied to monitor the sustainability of irrigated farmlands in test areas in Uzbekistan (the Andijan, Namangan, Fergana, and Syrdarya regions). The tool “Trends.Earth”, which was recommended by the UN Convention to Combat Desertification and developed as a special plugin for the Quantum GIS platform, was used to describe the dynamics of land degradation in the period 2001–2020. This study demonstrates the results of monitoring land productivity dynamics that reflect the investments in irrigation improvement during the last 10–15 years. A comparison between changes in land productivity measured via Normalized Difference Vegetation Index and its average value for the entire observation period is more informative than comparison with the initial 5-year period. More details could be noted through application of the “moving average” calculation method. The described trends demonstrate that the use of sustainable land management practices in the last decade led to a decreasing proportion of degraded lands compared to the average figure for the period 2001–2020 (from 25–40% to 10–20%). This trend is confirmed by reviewing state statistics and indicates the success of national policies and approaches to adaptation. However, the dynamics of land productivity in the study areas is diverse and includes “dry” and “humid” extremes, depending on climate fluctuations. Despite the generally positive trends identified across regions, the high dynamics of degraded hotspots and improved lands within certain areas confirm the instability of ongoing changes. Full article

(This article belongs to the Special Issue Remote Sensing for Water Monitoring in Agricultural Management and Development)

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Open AccessArticle

Evapotranspiration in Semi-Arid Climate: Remote Sensing vs. Soil Water Simulation

and

Sensors 2023, 23(5), 2823; https://doi.org/10.3390/s23052823 - 04 Mar 2023

Viewed by 1542

Abstract

Estimating crop evapotranspiration (ET_a) is an important requirement for a rational assessment and management of water resources. The various remote sensing products allow the determination of crops’ biophysical variables integrated in the evaluation of ET_a by using surface energy balance (SEB) models. This study compares ET_a estimated by the simplified surface energy balance index (S-SEBI) using Landsat 8 optical and thermal infra-red spectral bands and transit model HYDRUS-1D. In semi-arid Tunisia, real time measurements of soil water content (θ) and pore electrical conductivity (EC_p) were made in the crop root zone using capacitive sensors (5TE) for rainfed and drip irrigated crops (barley and potato). Results show that HYDRUS model is a fast and cost-effective assessment tool for water flow and salt movement in the crop root layer. ET_a estimated by S-SEBI varies according to the available energy resulting from the difference between the net radiation and soil flux G₀, and more specifically according to the assessed G₀ from remote sensing. Compared to HYDRUS, the ET_a from S-SEBI was estimated to have an R² of 0.86 and 0.70 for barley and potato, respectively. The S-SEBI performed better for rainfed barley (RMSE between 0.35 and 0.46 mm·d⁻¹) than for drip irrigated potato (RMSE between 1.5 and 1.9 mm·d⁻¹). Full article

(This article belongs to the Special Issue Remote Sensing for Water Monitoring in Agricultural Management and Development)

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