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Remote Sensing of Water Resources in Semi-Arid Regions/Drought Areas

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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Biogeosciences Remote Sensing".

Deadline for manuscript submissions: closed (31 August 2020) | Viewed by 16035

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Special Issue Editors

Prof. Dr. Martin Kappas

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Guest Editor

Division of Cartography, GIS and Remote Sensing, Faculty of Geoscience and Geography, Georg-August University Goettingen, 37077 Goettingen, Germany
Interests: land use/cover change; integrated watershed analysis; desertification in drylands; multi-sensor remote sensing; monitoring concepts; land surface and vegetation dynamics
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Dr. Ammar Rafiei

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Guest Editor

Institute of Geography, Department of Cartography, GIS & Remote Sensing, University of Göttingen, Goldschmidt Street 5, 37077 Goettingen, Germany
Interests: integrated watershed analysis; multi-sensor remote sensing; hydrological modeling; flooding and drought; climate change; water resources management

Special Issue Information

Dear Colleagues,

The population and water demand are rapidly growing in the dryland regions of the world. More than 25% of the world’s population, at least 1.5 billion people, currently live in areas with a physical scarcity of water. Arid and semi-arid regions occur in about 30% of the total land area of the world. An intensification of the desertification caused by global warming and poor land management practices endanger water resources. In arid lands the exploration and monitoring of water resources is a prerequisite for water accessibility, rational use and management. To investigate large arid areas for water, conventional land-based techniques have to be supplemented using satellite and airborne remote sensors. Surface water systems can be surveyed using multispectral and radar sensors; soil moisture in the unsaturated zone can be remotely sensed with thermal remote sensing and microwave radiometers (e.g. ASCAT, SMOS) using indirect indicators, such as microwave emissivity. Wetlands with freshwater can be surveyed using multispectral sensors and freshwater sources can be detected using thermal infrared radiometers (TIR). All remote sensors and satellite gravitational mappings can be linked with ancillary data analysis to infer groundwater behaviour from surface expressions and to estimate groundwater aquifer storage. This Special Issue provides an overview of state-of-the-art remote sensing techniques for analysing water resources in arid and semiarid regions. All research on the use of remote sensing for surface water hydrology, groundwater hydrology, flood extent, soil moisture, water quality, evapotranspiration estimation, and the calibration and validation of hydrological modelling are welcome.

Prof. Dr. Martin Kappas
Dr. Ammar Rafiei
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. Remote Sensing 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 2700 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

Surface water remote sensing
Wetland mapping
Groundwater remote sensing
Soil moisture sensing
Evapotranspiration sensing
Integration of remote sensing in hydrological modelling

Published Papers (4 papers)

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Research

35 pages, 13971 KiB

Open AccessArticle

Soil Moisture Estimation for the Chinese Loess Plateau Using MODIS-derived ATI and TVDI

by Lina Yuan, Long Li, Ting Zhang, Longqian Chen, Jianlin Zhao, Sai Hu, Liang Cheng and Weiqiang Liu

Remote Sens. 2020, 12(18), 3040; https://doi.org/10.3390/rs12183040 - 17 Sep 2020

Cited by 21 | Viewed by 3574

Abstract

Timely and effective estimation and monitoring of soil moisture (SM) provides not only an understanding of regional SM status for agricultural management or potential drought but also a basis for characterizing water and energy exchange. The apparent thermal inertia (ATI) and Temperature Vegetation Dryness Index (TVDI) are two widely used indices to reflect SM from remote sensing data. While the ATI-based model is routinely used to estimate the SM of bare soil and sparsely vegetated areas, the TVDI-based model is more suitable for areas with dense vegetation coverage. In this study, we present an iteration procedure that allows us to identify optimal Normalized Difference Vegetation Index (NDVI) thresholds for subregions and estimate their relative soil moisture (RSM) using three models (the ATI-based model, the TVDI-based model, and the ATI/TVDI joint model) from 1 January to 31 December 2017, in the Chinese Loess Plateau. The initial NDVI (NDVI₀) was first introduced to obtain TVDI value and two other thresholds of NDVI_ATI and NDVI_TVDI were designed for dividing the whole area into three subregions (the ATI subregion, the TVDI subregion, and the ATI/TVDI subregion). The NDVI values corresponding to maximum R-values (correlation coefficient) between estimated RSM and in situ RSM measurements were chosen as optimal NDVI thresholds after performing as high as 48,620 iterations with 10 rounds of 10-fold cross-calibration and validation for each period. An RSM map of the whole study area was produced by merging the RSM of each of the three subregions. The spatiotemporal and comparative analysis further indicated that the ATI/TVDI joint model has higher applicability (accounting for 36/38 periods) and accuracy than the ATI-based and TVDI-based models. The highest average R-value between the estimated RSM and in situ RSM measurements was 0.73 ± 0.011 (RMSE—root mean square error, 3.43 ± 0.071% and MAE—mean absolute error, 0.05 ± 0.025) on the 137th day of 2017 (DOY—day of the year, 137). Although there is potential for improved mapping of RSM for the entire Chinese Loess Plateau, the iteration procedure of identifying optimal thresholds determination offers a promising method for achieving finer-resolution and robust RSM estimation in large heterogeneous areas. Full article

(This article belongs to the Special Issue Remote Sensing of Water Resources in Semi-Arid Regions/Drought Areas)

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15 pages, 6059 KiB

Open AccessArticle

Estimation of Actual Evapotranspiration in a Semiarid Region Based on GRACE Gravity Satellite Data—A Case Study in Loess Plateau

by Miao Sun, Qin’ge Dong, Mengyan Jiao, Xining Zhao, Xuerui Gao, Pute Wu and Ai Wang

Remote Sens. 2018, 10(12), 2032; https://doi.org/10.3390/rs10122032 - 14 Dec 2018

Cited by 9 | Viewed by 4461

Abstract

Jointly influenced by natural factors and artificial protection measures in recent years, the vegetation coverage of the Loess Plateau has significantly increased. However, extensive vegetation recovery can result in massive water consumption and a severe soil water deficit, which poses a great threat to the sustainable development of the regional ecological system. Maintaining the balance between precipitation and water consumption is an important foundation of ecological security in the Loess Plateau. Based on this, the present study used the GRACE (Gravity Recovery and Climate Experiment) gravity satellite data to simulate the annual actual water consumption from 2003 to 2014 and to analyze the temporal and spatial evolution of the regional precipitation and the actual evapotranspiration (AET). This study also applied the newly developed rainwater utilization potential index (IRUP) to quantify the sustainability of the water balance in the Loess Plateau. The spatial-temporal patterns of precipitation, potential evapotranspiration, and AET from 2003 to 2014 in the Loess Plateau were all analyzed in this study. Based on the results, the annual average precipitation (AAP) and AET in the entire Loess Plateau had significant increasing trends. The analysis of the spatial distribution reveals that the AET was decreasing from the southeast to the northwest in the Loess Plateau. However, the average values of potential evapotranspiration did not obviously change. Based on the estimated AET result, it was determined that the average IRUP had an increasing trend. The increase in the IRUP is due to an increased rate of precipitation that is statistically higher than that of the AET. Consequently, the Loess Plateau experienced a wetting trend during the period of 2003–2014, especially after the Grain for Green project was implemented. The results in this paper were proven by using three different depths of ERA-Interim (a global atmospheric reanalysis product created by the European Centre for Medium-Range Weather Forecasts) soil water content data from the same period and the observed runoff data from 18 different hydrological sites. Consequently, it seems that the vegetation could maintain a sustainable growth with the implementation of the Grain for Green Project. Full article

(This article belongs to the Special Issue Remote Sensing of Water Resources in Semi-Arid Regions/Drought Areas)

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17 pages, 14717 KiB

Open AccessArticle

Monitoring of Land Use/Land-Cover Changes in the Arid Transboundary Middle Rio Grande Basin Using Remote Sensing

by Stanley Mubako, Omar Belhaj, Josiah Heyman, William Hargrove and Carlos Reyes

Remote Sens. 2018, 10(12), 2005; https://doi.org/10.3390/rs10122005 - 11 Dec 2018

Cited by 29 | Viewed by 3842

Abstract

Expanding urbanization in highly fragile desert environments requires a thorough understanding of the current state and trends of land uses to achieve an optimal balance between development and the integrity of vital ecosystems. The objectives of this study are to quantify land use change over the 25-year period 1990–2015 and analyze temporal and spatial urbanization trends in the Middle Rio Grande Basin. We conclude by indicating how the results can inform on-going water resource research and public policy discussion in an arid region. Results show that the predominant upland mixed vegetation land cover category has been steadily declining, giving up land to urban and agricultural development. Urban development across the region of interest increased from just under three percent in 1990 to more than 11 percent in 2015, mainly around the major urban areas of El Paso, Ciudad Juárez, and Las Cruces. Public policy aspects related to results from this study include transfer of water rights from agriculture to land developers in cities, higher risk of flooding, loss of natural ecosystems, and increased water pollution from point and non-point sources. Various stakeholders can find the study useful for a better understanding of historical spatial and temporal aspects of urban development and environmental change in arid regions. Such insights can help municipal authorities, farmers, and other stakeholders to strike a balance between development needs and protecting vital ecosystems that support the much needed development, especially in regions that are endowed with transboundary natural resources that often are incompletely represented in single nation data. Full article

(This article belongs to the Special Issue Remote Sensing of Water Resources in Semi-Arid Regions/Drought Areas)

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19 pages, 3122 KiB

Open AccessArticle

Hydrological Evaluation of PERSIANN-CDR Rainfall over Upper Senegal River and Bani River Basins

by Khalidou M. Bâ, Luis Balcázar, Vitali Diaz, Febe Ortiz, Miguel A. Gómez-Albores and Carlos Díaz-Delgado

Remote Sens. 2018, 10(12), 1884; https://doi.org/10.3390/rs10121884 - 27 Nov 2018

Cited by 13 | Viewed by 3531

Abstract

This study highlights the advantage of satellite-derived rainfall products for hydrological modeling in regions of insufficient ground observations such as West African basins. Rainfall is the main input for hydrological models; however, gauge data are scarce or difficult to obtain. Fortunately, several precipitation products are available. In this study, Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks–Climate Data Record (PERSIANN-CDR) was analyzed. Daily discharges of three rivers of the Upper Senegal basin and one of the Upper Niger basin, as well as water levels of Manantali reservoir were simulated using PERSIANN-CDR as input to the CEQUEAU model. First, CEQUEAU was calibrated and validated using raw PERSIANN-CDR, and second, rainfalls were bias-corrected and the model was recalibrated. In both cases, ERA-Interim temperatures were used. Model performance was evaluated using Nash–Sutcliffe efficiency (NSE), mean percent bias (MPBIAS), and coefficient of determination (R²). With raw PERSIANN-CDR, most years show good performance with values of NSE > 0.8, R² > 0.90, and MPBIAS < 10%. However, bias-corrected PERSIANN-CDR did not improve the simulations. The findings of this study can be used to improve the design of dam projects such as the ongoing dam constructions on the three rivers of the Upper Senegal Basin. Full article

(This article belongs to the Special Issue Remote Sensing of Water Resources in Semi-Arid Regions/Drought Areas)

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