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Review

What Do We Know about Water Scarcity in Semi-Arid Zones? A Global Analysis and Research Trends

1
Centro de Investigaciones y Proyectos Aplicados a las Ciencias de la Tierra (CIPAT), ESPOL Polytechnic University, Guayaquil P.O. Box 09-01-5863, Ecuador
2
Facultad de Ciencias Naturales y Matemáticas (FCNM), ESPOL Polytechnic University, Guayaquil P.O. Box 09-01-5863, Ecuador
3
Geo-Recursos y Aplicaciones GIGA, ESPOL Polytechnic University, Guayaquil P.O. Box 09-01-5863, Ecuador
4
Business and Economy Department, University of Almería, Ctra. Sacramento s/n, La Cañada de San Urbano, 04120 Almeria, Spain
5
Facultad de Ingeniería en Ciencias de la Tierra (FICT), ESPOL Polytechnic University, Km 30.5 Vía Perimetral, Guayaquil P.O. Box 09-01-5863, Ecuador
*
Authors to whom correspondence should be addressed.
Water 2022, 14(17), 2685; https://doi.org/10.3390/w14172685
Received: 2 July 2022 / Revised: 21 August 2022 / Accepted: 25 August 2022 / Published: 30 August 2022
(This article belongs to the Special Issue Water Scarcity: From Ancient to Modern Times and the Future)

Abstract

:
Water supply is strategic for the development of society. The water distribution in nature follows patterns linked to geographic and territorial issues. Climate fluctuations aggravate shortage problems in semi-arid regions. This study aims to develop a systematic review of research on water scarcity in semi-arid areas through bibliometric methods that allow the analysis of its structure, performance, evolution, and future trends. The methodology considers three phases: (i) literature review, (ii) data cleaning and processing, and (iii) analysis of the research field and future trends. The intellectual structure of water scarcity in semi-arid zones covers 2206 documents with the collaboration of sixty-one countries, distributed in studies carried out in 54 years (1967 to 2021). This field of research has been growing, especially since the 21st century (93.1% of the documents). The countries that study the issue the most are those with high population rates and large consumption patterns, such as the United States and China. There are two central areas of interest led by the terms "water scarcity" and "water stress" due to the intensive use of the resource for agriculture and the management of the water–energy–climate nexus. Thus, the most significant journals studied relate remote sensing to resource management, and the most cited are related to agriculture. This research made it possible to consider future topics such as the study of anthropogenic effects and climate change, the accuracy and applicability of models, and future trends in conventional and unconventional agriculture and resources.

1. Introduction

Water scarcity is a high-impact global risk [1]. Over the last 100 years, water use has accelerated, with the current growth rate being 1% per year [2]. Water scarcity refers to the relationship between the supply of water resources and demand [3,4]. Thus, when discussing scarcity, we also discuss water’s uneven temporal and spatial variations [5,6,7]. Regions with scarcity correspond to a third of the population of developing countries, or a quarter of the world population [8,9].
Population growth, economic development, and consumption patterns intensify the problem of scarcity [9,10]. Added to this is the contamination of groundwater due to agricultural load, wastewater and salinization [11,12,13,14]. Furthermore, climate change can also affect demand and precipitation [2,15,16,17]. These problems lead to the search for solutions to conserve the quality and quantity of water, especially in semi-arid areas [18], such as the management, conservation and monitoring of groundwater [19,20]; wastewater treatment for pollution reduction, sustainable use and human development [2,21,22]; land use management [23]; and technologies for capturing and reserving water [13].
In semi-arid regions, water scarcity is aggravated, threatening food production, ecosystems and health [8,24,25,26]. A rapid expansion of semi-arid areas of the northern Mediterranean, southern Africa, and North and South America is expected [27]. Therefore, understanding the consequences of hot weather and semi-arid conditions is essential to generating development strategies. The semi-arid climate refers to the fluctuations between the dry and rainy seasons [28]. The countries with the most severe development problems are those where climate affects access to water [15,29].
Access to water to satisfy the basic needs of humanity is a fundamental condition for survival and the first step towards sustainable water use [30,31]. However, globally, water is trading on the market [32], and water resources are increasingly scarce, which causes socio-hydrological impacts on water distribution processes [33,34]. Therefore, it is essential to understand how these water–human systems evolve in the face of water scarcity [35,36] through participatory and sustainability criteria [37,38,39,40].
The studies mentioned in this article have addressed the issue of water scarcity from different perspectives, such as future scarcity, scarcity modelling and especially its interaction with climate change, food security, management policies and economics [8,17,23,28,31,41]. Nevertheless, due to the seriousness of this problem, it is necessary to explore the intellectual structure of water scarcity in semi-arid zones [42]. Therefore, a bibliometric study in this field would be an additional contribution to existing research on the subject.
This study analyses the scientific literature on water scarcity using bibliometric techniques to comprehensively assess the structures and development of the field [43,44]. The analysis of water scarcity is essential to identify current and future research areas, given the growing and aggravating need to supply, especially in semi-arid regions.
This article aims to explore: what has been the development of research trends on water scarcity in semi-arid areas? Which are the most productive and influential contributors (countries and journals) in the field of water scarcity in semi-arid zones? What are the most influential publications in this field? What are the areas of interest associated with this intellectual structure? Therefore, the aim is to develop a systematic review of research on water scarcity in semi-arid areas using bibliometric methods that allow the analysis of its structure, performance, evolution, and future trends in this field of study.

2. Materials and Methods

The research structure presents two phases, as detailed in Figure 1. The first phase corresponds to a literary review of the subject, cleaning and processing of information downloaded from the chosen databases. The second phase uses bibliometric techniques in conjunction with science mapping in VOSviewer (software version 1.6.18). Finally, this phase presents the analysis and interpretation of the data, the conclusions, and the future lines of research.

2.1. Phase I: Information Analysis and Processing

The systematic review is a methodology that allows for exploring areas of research through data collection and synthesis criteria that must be reproducible [45,46]. This procedure is like the one presented in the bibliometric analysis. One of these bibliometric studies pioneers is Derek J. de Solla Price, who considers that the network of articles creates patterns of research trends [47].
Bibliometric analysis is a quantitative method synthesising finding from the research area and representing them spatially [48,49]. This method covers various areas of knowledge such as environmental sciences [19,50,51,52], social sciences [53], geosciences [54] or interdisciplinary fields [55].
This phase encompasses two steps:

2.1.1. Search Principles and Database Criteria

The application of the bibliometric method requires the choice of a database. The most-recognised multidisciplinary databases are WoS and Scopus [56,57]. Both databases rank journals by their productivity and the total number of citations to obtain an impact value, thereby acquiring journal activity, coverage and influence [58].
In this study we employed the Scopus database, the most widely used academic database due to its broad coverage of titles, journals and areas of knowledge [59,60]. This database is critical and robust due to its coverage and impact [61,62]. In addition, Scopus has more research in the field of earth sciences than other databases [54] and has a broad coverage of journals favouring the natural sciences, biomedical and engineering [63].
The bibliographical research allowed to establish the search terms for scarcity by supply and demand. However, the search does not cover drought since it is considered a natural and transitory event [64]. Instead, the search considers the terms: water scarcity, water shortage, water stress, water crisis [7,64,65,66], lack of water, dearth of water, or water penury [28,67,68,69] and the possible variations of the semi-arid.
The database download made in Scopus, dated January 2022, had the following search formula: ((TITLE-ABS-KEY (“water shortage*”) OR TITLE-ABS-KEY (“water stress”) OR TITLE-ABS-KEY (“water crisis”) OR TITLE-ABS-KEY (“lack of water”) OR TITLE-ABS-KEY (“dearth of water”) OR TITLE-ABS-KEY (“water penur*”) OR TITLE-ABS-KEY (“water scarcit*”) AND NOT TITLE-ABS-KEY (drought*))) AND ((TITLE-ABS-KEY (“semiarid”) OR TITLE-ABS-KEY (“semi-arid”) OR TITLE-ABS-KEY (“semi arid”))), obtaining a total of 2395 documents.
This equation comprises inclusion and exclusion criteria. First, the search included English, the most frequent language [57], covering 93.1% of the documents. Additionally, the study covers all types of documents for better research results [70]. Finally, the search established exclusion criteria for the year 2022 because it is the current year. With this, the final search decreases to 2210 papers for 54 years (1967 to 2021).

2.1.2. Data Processing Software

The result of the Scopus search is a database of 2210 documents exported in CSV (Comma Separated Value) file format. The download includes citations, bibliographical information, abstract and keywords fields, and references. The data analysis included three software: Microsoft Excel, VOSviewer and ArcGIS.
i.
Microsoft Excel (software version 2207 Build 16.0.15427.20182, Microsoft Corporation, Redmond, WA, USA) allowed executing a pre-processing of the data, in which programming errors, erroneous records and documents discordant with the theme are corrected or eliminated [71,72]. Under these considerations, the pre-processing obtained 2206 papers. This software also allowed performance analysis of scientific production by reviewing authors, subject area, years, and countries [43].
ii.
VOSviewer (software version 1.6.18, Leiden University’s Centre for Science and Technology Studies (CWTS), Amsterdam, The Netherlands) is free software that allows processing information to obtain bibliometric networks maps based on bibliographic information downloaded from database (e.g., Web of Science, Scopus) or data retrieved through the Application Programming Interface (API) (e.g., Crossref). The software is used to establish relationship maps between different units of analysis (author, document, journal, country, keywords, institutions) using bibliometric techniques (bibliographic coupling, co-author, co-citation, co-word) [73]. This software categorises the themes to graphically represent the lines of research [74,75,76]. Its use covers various research areas such as management [77,78,79,80], medicine [81,82], environmental sciences [83,84,85] and the field of earth sciences [43,86,87].
iii.
ArcGIS (software version 10.5, ESRI, Redlands, CA, USA) is a visualisation tool that allows scientific publications to be geographically located [88]. As a result, the high numbers of publications show the most active countries in the field of research [89].
iv.
Bibliometrix R-Tool (software version 3.2.1, software developed by University of Naples, Naples, Italy): It is an open-source software developed in R language, which allows qualitative research of data and its visualization in the structures of conceptual, intellectual and social knowledge [90,91,92]. The software has been used in various bibliometric studies related to earth sciences, environmental sciences and management [93,94,95,96].

2.2. Phase II: Research Field Analysis

The analysis of the research field comprises two approaches [97]:
i.
The performance analysis is a descriptive method that evaluates the productivity and impact of a research area of interest [98]. Performance analysis was used to study the scientific production and evolution of the research on water scarcity in semi-arid zones, using base indicators of publications such as number of documents, countries’ contributions, institutions, journals and authors.
ii.
Scientific mapping allows spatial representation of how the different units of bibliometric analysis (e.g., documents, authors, keywords) are related to each other [99]. In this research, we used co-citation (journal) and co-occurrence (author’s keywords) analysis [60]. Co-citation analysis allows connecting documents, authors or journals, based on joint appearances in the reference list [37,48]. On the other hand, co-occurrence analysis connects keywords when they appears in the title, abstract, list of keywords or author-generated keyword lists [100]. Both analyses are used to evaluate and obtain an overview of the structure and evolution of research topics [101].
The mapping used a threshold of 40 citations to produce ordered maps [102]. Journal co-citation allows analysing of the most-cited journals, and the keywords co-occurrence analyses the themes associated with the field of study. This keyword co-occurrence analysis helps to establish future research lines.

3. Results

3.1. Performance Analysis

3.1.1. Scientific Production

Scientific production covers 2206 documents in 54 years (1967 to 2021), divided into three periods according to the behaviour of the curve—the first period is for introduction, the second for development and maturity (Figure 2).
1.
Period I (1967–1996)—Introduction.
In this period, 83 investigations were published, representing 3.71% of the scientific production of this field of study, with 2470 citations. The first investigations focused on plants’ water requirements for agricultural production efficiency—groundwater management for the supply industrial sector and human consumption [103]. Techniques for the optimal use of water resources, such as irrigation, runoff or desalination, are examined [104,105,106]. Additionally, in conditions of hydric stress, the species’ adaptability [107].
Other researchers analyzed the influence of water scarcity on trophic interactions [108], productivity [109], as well as crop yield and biomass [110]. Influence, which implies the analysis of the optimal use of water resources, especially in agriculture [111]; and in the study of the adaptation processes of plants to periods of scarcity in semi-arid and arid lands, such as fructan production [112], the gradual fall of plant leaves [113], efficient irrigation and optimal use of fertilizers [114], adaptation to saltwater consumption [115] [116], patterns of water consumption between pastures and shrubs [117], reversible photoprotective mechanisms [118].
2.
Period II (1997–2014)—Development.
This period is characterized by greater research development with 909 publications, representing 41.11% of the total. These publications concentrate the majority of citations in this field of study (70.09%). In this period, there is a growing interest in climate change adaptation, satellite mapping, modelling, water management and agriculture. Some research addresses climate change and its effects on ecosystems and species [119], grasslands [120], steppe [121], land use [122,123] and agricultural soils [124], as well as the effects of climate change on water resources [125,126], water stress [127], soil water availability [120], evapotranspiration [128], runoff farming [129]. Other researchers address the use of satellite mapping to map the use of water resources [130], evapotranspiration [131,132], vegetation dryness [133] and groundwater [134].
In this period, some relevant studies are presented on mechanisms and technologies that seek to improve water use efficiency in agriculture [135], given the food production projections [136]. One of the most important studies in this field is the satellite mapping of evapotranspiration in agriculture [131]. In addition, research studies the influence of mountainous areas on the supply of water resources [137], environmental degradation as an aggravating factor of water scarcity [138], and the places where arid lands expand and increase [27].
3.
Period III (2015–2021)—Maturity.
Finally, the third-period analysis shows a growing interest on the part of the scientific community in the subject of study, due to the increase in publications, with a total of 1214 (55.18%) and 12,937 citations (Figure 2). The average annual production exceeds 170 documents, registering a peak in 2021 (266 documents). Evidence corroborates that this field of study is booming. Some studies cover the selection of suitable vegetation for reforestation [139] and replanting species’ positive and negative effects [140]. Furthermore, food sustainability strategies improve crop yields under stress conditions [141,142]. Solutions and best practices in water resource management [143] adopt measures such as wastewater management for the circular economy [144]. Likewise, water use models and basin monitoring allow knowing their fluctuations [145] and vulnerability and promote the sustainable use of freshwater [20,146,147]). In this period, some topics observed in the previous period continue to be investigated, as well as new additions, such as water stress [148,149,150,151,152], water scarcity [153,154,155,156,157], water use efficiency [158,159,160,161,162], irrigation deficit [158,159,160,161,162,163,164], evapotranspiration [165,166,167], climate change [168,169,170] and remote sensing [158,171,172,173,174].
To assess whether the scientific production in water scarcity in semi-arid zones fits the Price’s Law of exponential scientific growth [175], it has been tested with regression models to obtain the model with the best adjustment to data. The increase in production adjusts to an exponential curve (according to the equation y = 0.845e0.1203x, Figure 2) given that the value of R2 (coefficient of determination) is 0.9875, according to Price’s law [175]. The value of the coefficient close to one guarantees that the field of research is growing [176].

3.1.2. Language and Type of Documents

About the documents analysed, the thematic area of most significant interest is agriculture and biological sciences (31.1%) since sustainable agriculture is one of the most critical challenges facing water scarcity [177,178]. The following fields are environmental sciences (29.5%) and earth and planetary sciences (12.9%). The publications comprise 10 languages, where 93.1% are written in English and 3.4% in Chinese [179,180]. The predominance of English is because it is a language that facilitates international collaborations among researchers [135,181]. Other minor languages are Portuguese, Spanish, French, Persian, German, Italian, Japanese, and Russian. Regarding the type of documents, 83.8% correspond to scientific articles. Figure 3 shows other documents used in this knowledge structure, where a smaller group of documents (0.5%) corresponds to books, notes, erratum, and short surveys.

3.1.3. Contribution by Countries

The review of scientific production by country allows knowing the regions/countries with the highest number of scientific publications related to the research field using the affiliation location of the authors [182,183]. The study covers 61 countries, with the most significant contribution coming from developed countries compared to developing countries. The map in Figure 4 presents a colour classification of production by country. ArcGIS 10.5 software generated this map.
The results indicate that the United States and China have the most considerable contribution, followed by Spain, Iran, Brazil, India, and Australia, in hierarchical order. The top-three contributing countries also have the highest citation rates, followed by Australia and France. Research indicates projected scarcity conditions for 2050 in southern Mexico, southern and midwestern United States, northern Africa and China, eastern and central Asia, the Middle East, and north-western Brazil [184,185]. These aggravating conditions estimate social impacts that require immediate actions [27].
The collaboration between the first three countries (United States, China and Spain) established an evolutionary review of irrigation techniques for sustainable agriculture [186]. The United States and China present the most significant collaboration with 74 documents. The most-cited cooperation is a study that determines the expansion of drylands [27]. In addition to the analysis of efficient reforestation in China [138], they collaborate in research on models for decision-making [145,171,187,188], especially in agricultural issues such as water absorption and optimal irrigation in plants [189,190,191,192,193,194,195].
The United States collaborates on 18 documents with Spain, the most-cited research being the treatment and use of wastewater [196]. In addition, these countries investigate the effects of climate change in the Mediterranean [197] and the interaction between plants and irrigation [198,199,200,201,202,203]. Furthermore, the United States and Iran study the effects of water stress on plants [148,204,205] and collaborate with Brazil to investigate adaptation strategies to water demands [206,207]. Finally, the collaboration with Japan on satellite mapping of evapotranspiration is its most-cited research [131].
China and Spain investigate soil moisture and plant restoration [208]. In addition, China has collaborations with other Asian countries, such as India and Pakistan, where it researches management strategies for agriculture [162,209,210], climate change [211,212], water stress mitigation, and efficient water use [213,214]. The most-cited research from China has collaboration with France [140].

3.1.4. Most-Cited Documents

Citations of publications allow the evaluation and identification of studies in the field [37]. The scientific production analysed covers 2206 documents with 51,518 citations. Table 1 presents the 10 most-cited documents. These documents represent 10.8% (5585) of the total citations. The studies investigate global satellite mapping [27,131,137], effects of climate change [119,138,140] and especially agriculture [120,135,136,215]. Of these investigations, four are from journals from the United Kingdom [119,120,140,215], three are journals from the Netherlands [135,136,138], and three were from the United States [131,137] and one from Germany [27].

3.2. Bibliometric Mapping Analysis

The VOSviewer software allows mapping the structure of the investigation. This software applies the visualization of similarities (VOS) to calculating a matrix to create two-dimensional bibliometric maps [216,217]. The force of attraction between the nodes is proportional to their similarity [97].

3.2.1. Co-Occurrence of Author Keywords

Co-occurrence analysis identifies the frequency of words that the author classifies as keywords for the article. This analysis determines the research areas and themes of the intellectual structure of a field of study [43,218,219]. Using the VOSviewer 1.6.18 software allowed the creation of the network of co-occurrences of author keywords. This network encompasses 5,424 keywords, with 90 of these keywords matching at least 10 times. These 90 words (nodes) represent relevant topics. The clusters are the nodes set, representing the research lines or topics. Figure 5 presents the semantic map with 90 nodes (author keywords) and 7 clusters (colour groups).
Cluster 1 (red colour) “water scarcity management” comprises 34 items with 1061 occurrences, where the terms water scarcity and irrigation stand out. This cluster’s articles present information on productivity improvements and water use management [187,220,221], especially for irrigation efficiency, pollution reduction, recycling and water-saving [144,187,222,223,224,225,226]. There is also evidence of human pressure due to water demand in the face of climatic effects [197,227,228,229] and its relationship with land use for water and food security [230,231,232,233].
Cluster 2 (green colour) “water use in crops” presents 14 items with 461 occurrences, where the most frequently used terms are water use efficiency and deficit irrigation. This cluster has a special interest in the efficiency of water use in agriculture in the face of emerging global changes [136,162,234]. Research for sustainable food production [159,235] encompasses water productivity [236,237], crop type studies, efficient irrigation, and nutrient demand [214,238,239,240,241,242].
Cluster 3 (blue colour) “evapotranspiration” integrates 10 items with 267 occurrences. In this cluster, the most relevant terms are evapotranspiration and irrigation scheduling. The studies investigate moisture losses by evaporation/transpiration [131,243] and their link to irrigation, given their effect on yield and plant components [242,244,245,246]. In addition, these studies assess how water depletion affects crop yields [234,245,247,248] and evapotranspiration as a function of reforestation and biomes [249,250].
Cluster 4 (yellow colour) “water stress” presents water stress and water footprint as prominent terms, out of 10 items with 365 occurrences. In this cluster, the adaptation of plants to limited water availability is studied [112,178]. The analysis of the effects of water scarcity on food and meat production [207,251,252,253] and the evaluation of the impact on water consumption and use by human activities [185,254], land use [230], rainfall variability and aquifer recharge [255,256,257].
In cluster 5 (purple colour), “water productivity”, the terms water productivity, dryland and food security stand out. This cluster comprises nine items with 145 occurrences. The research relates crop productivity prediction models to drainage simulation, evapotranspiration and nutrient regulation [150,225,258]. Also, efficient crop, water and soil management is studied [209,245,259], especially for food security [153,224,260,261].
Cluster 6 (light blue colour) “soil moisture” comprises seven items with 122 occurrences, where soil moisture and soil water content are its most relevant terms. This cluster includes water conservation, humidity and soil degradation research, given its close relationship with plant cover [194,262,263,264]. Studies suggest vegetation influences drainage networks, runoff, and hydrological patterns [265,266,267,268]. In addition, the effects on crops against nutrient content and carbon uptake are studied [269,270,271].
Cluster 7 (orange colour), called “model application”, encompasses six items with 87 occurrences and presents the terms modelling and nitrogen among the most important. The articles in this cluster analyse models that include simulations in conjunction with field observations. These models study the relationships between soil, water, atmosphere and plants for predictions of changes and behaviours [236,272,273,274,275]. In addition, the studies analyse management models for allocating water resources [188,276]. Finally, the research evaluates the relationship between soil type, water/nutrient use, and seasonal changes related to crop productivity [204,215,277,278,279].
When considering the evolution of the various topics in this field of study, it was visualized using a Sankey diagram (see Figure 6), which allows multiple attributes to be observed under the same graph [91]. This diagram was made with the Bibliometrix R-Tool software, using the Biblioshiny library. Figure 6 shows the evolution of the different themes in periods I (1967–1996), II (1997–2014) and III (2015–2021).
In the first period, it is observed how water stress and groundwater stand out as the main research topics. In the second period, these main themes are broken down into water stress related to stomach conductance and groundwater with water scarcity. The latter was the largest field of research and appeared to new topics such as irrigation, water shortage, growth, and water-use efficiency. Water shortage appears as a concept related to scarcity driven by the average availability of water per inhabitant, which differs from water stress when the demand for the resource exceeds the amount available. In the last period, the two themes of water stress and water scarcity continue to be a topic of interest. However, new themes such as precipitation appear, which are related to changes in the extreme climatic events that the planet experiences, a phenomenon that is intensified in the semi-arid region. This period is important because it shows how climate change generates other problems for the scientific community, such as increasing the irrigation deficit and its relationship with food security.
Additionally, Figure S1 exhibits the evolution of the themes that the scientific community has used with a frequency of 10 keywords. This figure highlights how germination issues are displaced by applications of Geographic Information Systems (GIS) tools. GIS has undergone advances in its use, generating new topics of interest, such as the Soil and Water Assessment Tool (SWAT). SWAT develops hydrological models to address environmental problems. His study in recent years is opening a critical potential line of research.

3.2.2. Journal Co-Citation

Co-citation is the frequency with which two journals are cited together [280]. Since citations are a measure of influence, this allows for mapping the flow of research [48,218] and insight into the intellectual structure of the field [43,281]. Thus, the more frequent the citation, the more likely there is a similarity between their research fields. This analysis results in the academic community of the area in question [43,282].
Cluster 1 (red colour) “Hydric resource management” encompasses 46 journals with 8576 citations, where the following stand out: Journal of Hydrology (J. Hydrol., 1692 citations), Desalination (600), Water Resources Management (Water Resour. Manag., 579) and Science of the Total Environment (Sci. Total Environ., 518 citations). These journals originate in the Netherlands and cover hydrology, environment, and management strategies.
Cluster 2 (green colour) “water management in agriculture” presents 10,711 citations in 42 journals. In this cluster, the journals with the most citations are Agricultural Water Management (Agr. Water Manage., Netherlands, 3484 citations), Irrigation Science (Irrig. Sci., Germany, 798), Journal of Experimental Botany (J. Exp. Bot., United Kingdom, 629). These journals address topics related to agriculture, irrigation, and plant sciences.
Cluster 3 (blue colour) “production agriculture” includes 34 journals with 6916 citations. In this cluster, the following stand out for their number of citations: Journal (Agron. J., United States, 1234), Field Crops Research (Field Crops Res., Netherlands, 842) and Plant and Soil (the Netherlands, 687). These journals present experiments and models of crops, ecology, and plant-soil interactions.
Cluster 4 (yellow colour) "natural and social water sciences" has 34 journals with 8,379 citations. His most notable journals are Water Resources Research (Water Resour. Res., United States, 911 citations), Agricultural and Forest Meteorology (Agr. Forest Meteorol., Netherlands, 900), and Remote Sensing of Environment (Remote Sens. Environ., United States, 812). These journals deal with water, plant, and soil science topics, sometimes using remote sensing as a prominent factor.
Cluster 5 (purple colour) “ecology and environment” has 28 journals that include 4,752 citations, among which the following stand out: Oecologia (Germany, 540 citations), Journal of Arid Environments (J. Arid Environ., United States, 498), Tree Physiology (the United Kingdom, 483). The studies of these journals include models and applications of ecology, botany, ecosystems, and the environment.
Cluster 6 (light blue colour) “engineering in agriculture” comprises eight journals with 929 citations. Transactions of the Asabe (Trans. Asae, United States, 222 citations), Journal of Irrigation and Drainage Engineering (J. Irrig. Drain. Eng., United States, 176), Irrigation and Drainage (Irrig. Drain., United Kingdom, 156). These journals present topics on the application of technologies for water management in agriculture.

4. Discussion

The intellectual structure of water scarcity in semi-arid zones encompasses 2206 documents with 51,518 citations, distributed over 54 years of studies (1967 to 2021) with the collaboration of 61 countries. This scientific production presents 10 languages, highlighting English and publications of the type of scientific articles.
Research in this field has shown a growing interest on the part of the academic world, given that inefficient management of water resources, soil and crops are often added to water scarcity [209]. Thus, scientific production presents two periods of progress, defined for the 20th and 21st centuries. This last period registers an accelerated increase in research (93.1%), marked by the relationship between climate change and water scarcity [187,228,283], global trends in resource consumption patterns, technological development and population growth [66,227,234,284].
The countries with the most significant contribution to this scientific production are the United States and China (Figure 4). Both are close collaborators due to their high population rates and their patterns of water resource consumption, among which massive agricultural production stands out [254,285,286]. However, the most outstanding journals and research on the subject belong to the Netherlands, United Kingdom, United States and Germany.
The networks of co-occurrence of keywords and co-citation of journals served to analyse the intellectual structure of the research.
The keyword network presents a bimodal model that exhibits two central areas of interest, led by the terms “water scarcity” and “water stress” (Figure 5). This duality may be due to the pressure exerted on water, especially by extracting this resource for agricultural consumption (70%) and managing the water–energy–climate nexus [147,227,286]. In this figure, the red cluster led by water scarcity presents 42% of the co-occurrences of the topics related to the management of conventional and unconventional water resources [187,221,226,228,233]. In turn, water stress appears as the most popular term, with 9.7% of the co-occurrences. The terms water stress, evapotranspiration and water use efficiency are closely related to the efficient use of soil-water and crop productivity [159,214,234,237,245,273,287]. The cluster themes “model application”, “soil moisture”, and “water productivity” (orange, light blue and purple) function as a link between the main themes (Figure 5) [187,246,260,288].
Four groups stand out in the network of journals (Figure 7). The first is the red and yellow groups; these relate remote sensing to water resource management and concentrate the most considerable number of journals (24%). The green and blue groups are the second; these represent journals related to agriculture. The green cluster contains the most significant citations (26.6%). The third, the purple set, shows a close relationship with the yellow and green groups, which allows relating themes of botany, forest agriculture and ecology. Furthermore, the fourth, the light blue cluster (in-engineering), functions as a link between the journals on water resource management and agriculture (red and green, respectively).

5. Conclusions

The objective of this study was to analyse research on water scarcity in semi-arid zones through bibliometric methods that allow the analysis of its structure, evolution, and performance. This analysis reveals a growing interest in the subject, skyrocketing in the 21st century, with 93.1% of scientific production. This positive trend covers 54 years of studies (1967 to 2021) and 61 countries, with a majority of production in English and published as scientific articles.
The main contributors in this field of study are (i) countries: the United States and China; (ii) journal: Agricultural Water Management; (iii) most-cited publication: Satellite-based energy balance for mapping evapotranspiration with internalised calibration (METRIC)—Model by Richard Allen and colleagues (2007).
In turn, the analysis of the research through bibliometrics allowed us to know the various areas covered by the intellectual structure of studying water scarcity in semi-arid regions.
The co-occurrence of author keywords analysis presents seven themes linked to the intellectual structure: water scarcity management, water use in crops, evapotranspiration, water stress, water productivity, soil moisture and model application. In addition, the analysis of co-citation of journals presents the research activity in topics such as management, science, and engineering of water resources.
The academic contribution of this research lies in the exploration of the intellectual structure of this field of study because (i) this research can serve as a guide for researchers who want to study the subject broadly; (ii) there is the possibility of forming collaboration networks by getting to know the countries involved; (iii) briefly covers the central themes and topics of this field of study.

6. Future Research Lines

Research on water scarcity in semi-arid zones has overgrown, causing the need to explore new research gaps. Here are topics to consider in future studies:
Anthropogenic effects and climate change. Given humans’ substantial impact on the environment, it is crucial to calculate their effects on the distribution of water resources [192,289]. In addition, the study of effective adaptation and mitigation strategies to face climate change, such as indicators and efficient public policies [230,290].
The accuracy and applicability of models by scaling up and applying various technologies and factors warrant further investigation. These are powerful and predictive tools for qualifying the fit of alternatives in areas of interest [171]. Some topics to consider are:
  • The reduction of future precipitation in arid and semi-arid zones and measurements of hydric stress [181,245].
  • 3D aquifer models and groundwater potential mapping [246,247].
  • Models for the allocation and management of water resources [248].
  • In agriculture, future trends are:
  • Accurately detecting water stress by varying environmental conditions and hydrological flow control factors [149,250].
  • Development and application of irrigation techniques for the efficient use of water, control in the use of fertilizers and mitigation of soil contamination [163,191,291].
  • Use of conventional and unconventional water resources for supply. Trends include:
  • New alternatives of unconventional resources and studying their environmental impacts [292].
  • Use of alternative energy sources, development, adaptation and improvement of desalination models and techniques, depending on the place of application [243,293].
  • Sustainable groundwater extraction, water transfer, rainwater harvesting, and aquifer recharge structures [294,295,296].
  • Recycling treated wastewater as a circular economy for irrigation and groundwater protection [157,297].

Supplementary Materials

The following are available online at https://www.mdpi.com/article/10.3390/w14172685/s1, Figure S1. The main trend topic keywords are associated with the literature on water scarcity in semi-arid zones in the Scopus database.

Author Contributions

Conceptualization, F.M.-C., N.M.-B., X.Q.-B., M.J.-M. and P.C.-M.; methodology, F.M.-C., N.M.-B., X.Q.-B. and M.J.-M.; software, N.M.-B., X.Q.-B. and M.J.-M.; validation, F.M.-C., N.M.-B., X.Q.-B., M.J.-M. and P.C.-M.; formal analysis, F.M.-C., N.M.-B., X.Q.-B., M.J.-M. and P.C.-M.; investigation, F.M.-C., N.M.-B., X.Q.-B., M.J.-M. and P.C.-M.; data curation, N.M.-B., X.Q.-B. and M.J.-M.; writing—original draft preparation, F.M.-C., N.M.-B., X.Q.-B., M.J.-M. and P.C.-M.; writing—review and editing, F.M.-C., N.M.-B., X.Q.-B., M.J.-M. and P.C.-M.; visualization, N.M.-B., X.Q.-B. and M.J.-M.; supervision, F.M.-C. and P.C.-M.; project administration, F.M.-C. and P.C.-M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

Not applicable.

Acknowledgments

This research study was possible thanks to the collaboration of the Manglaralto Regional Water Administration Board (JAAPMAN in Spanish) with the project: “Registration of geological and mining heritage and its impact on the defence and preservation of geodiversity in Ecuador” of the ESPOL University with code CIPAT-01-2018. Additionally, the project “Management and Evaluation of Scientific Research in Earth Sciences, Economy, Administration and its links with Society” with code CIPAT-7-2022. We also appreciate the support of NOVA Science Research Associates and GIGA Georesources and Applications, ESPOL. Also, the authors want to thank to reviewers for their feedback and help in the process.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. World Economic Forum. The Global Risks Report 2020 Insight Report 15th Edition. 2020. Available online: https://www.weforum.org/reports/the-global-risks-report-2020/ (accessed on 20 February 2022).
  2. UNESCO. United Nations World Water Development Report 2020: Water and Climate Change; UNESCO: Paris, France, 2019; ISBN 9789231003714. Available online: https://unesdoc.unesco.org/ark:/48223/pf0000372985 (accessed on 10 February 2022).
  3. Ibáñez, C.; Caiola, N. Impacts of Water Scarcity and Drought on Iberian Aquatic Ecosystems. In Drought in Arid and Semi-Arid Regions; Springer: Dordrecht, The Netherlands, 2013; pp. 169–184. [Google Scholar] [CrossRef]
  4. Rijsberman, F.R. Water scarcity: Fact or fiction? Agric. Water Manag. 2006, 80, 5–22. [Google Scholar] [CrossRef]
  5. Döll, P.; Kaspar, F.; Lehner, B. A global hydrological model for deriving water availability indicators: Model tuning and validation. J. Hydrol. 2003, 270, 105–134. [Google Scholar] [CrossRef]
  6. De Vera, A.R.; Hall, R.A. Domestic Water Supply; Springer: Berlin/Heidelberg, Germany, 2018; pp. 65–85. [Google Scholar]
  7. Programa de las Naciones Unidas para el Desarrollo (PNUD) Informe Sobre Desarrollo Humano 2006. Available online: https://www.undp.org/es (accessed on 20 February 2022).
  8. Seckler, D.; Barker, R.; Amarasinghe, U. Water Scarcity in the Twenty-first Century. Int. J. Water Resour. Dev. 1999, 15, 29–42. [Google Scholar] [CrossRef]
  9. Hofste, R.W.; Reig, P.; Schleifer, L. 17 Countries, Home to One-Quarter of the World’s Population, Face Extremely High Water Stress. World Resour. Inst. 2019. Available online: https://www.wri.org/insights/17-countries-home-one-quarter-worlds-population-face-extremely-high-water-stress (accessed on 5 February 2022).
  10. Dalin, C.; Konar, M.; Hanasaki, N.; Rinaldo, A.; Rodriguez-Iturbe, I. Evolution of the global virtual water trade network. Proc. Natl. Acad. Sci. USA 2012, 109, 5989–5994. [Google Scholar] [CrossRef]
  11. Paul, M.; Negahban-Azar, M.; Shirmohammadi, A.; Montas, H. Developing a Multicriteria Decision Analysis Framework to Evaluate Reclaimed Wastewater Use for Agricultural Irrigation: The Case Study of Maryland. Hydrology 2021, 8, 4. [Google Scholar] [CrossRef]
  12. Djellouli-Tabet, Y. Common Scarcity, Diverse Responses in the Maghreb Region. In Proceedings of the Water and Sustainability in Arid Regions: Bridging the Gap Between Physical and Social Sciences; Springer: Dordrecht, The Netherlands, 2010; pp. 87–102. [Google Scholar]
  13. Ricart, S.; Rico-Amorós, A.M. Constructed Wetlands to Face Water Scarcity and Water Pollution Risks: Learning from Farmers’ Perception in Alicante, Spain. Water 2021, 13, 2431. [Google Scholar] [CrossRef]
  14. Minhas, P.S.; Saha, J.K.; Dotaniya, M.L.; Sarkar, A.; Saha, M. Wastewater irrigation in India: Current status, impacts and response options. Sci. Total Environ. 2022, 808, 152001. [Google Scholar] [CrossRef]
  15. Falkenmark, M. Global Water Issues Confronting Humanity. J. Peace Res. 1990, 27, 177–190. [Google Scholar] [CrossRef]
  16. Okello, C.; Tomasello, B.; Greggio, N.; Wambiji, N.; Antonellini, M. Impact of Population Growth and Climate Change on the Freshwater Resources of Lamu Island, Kenya. Water 2015, 7, 1264–1290. [Google Scholar] [CrossRef]
  17. Alcamo, J.; Flörke, M.; Maerker, M. Future long-term changes in global water resources driven by socio-economic and climatic changes. Hydrol. Sci. J. 2007, 52, 247–275. [Google Scholar] [CrossRef]
  18. Tzanakakis, V.A.; Paranychianakis, N.V.; Angelakis, A.N. Water Supply and Water Scarcity. Water 2020, 12, 2347. [Google Scholar] [CrossRef]
  19. Cao, T.; Han, D.; Song, X. Past, present, and future of global seawater intrusion research: A bibliometric analysis. J. Hydrol. 2021, 603, 126844. [Google Scholar] [CrossRef]
  20. Carrión-Mero, P.; Montalván, F.; Morante-Carballo, F.; de Valgas, C.L.-F.; Apolo-Masache, B.; Heredia, J. Flow and Transport Numerical Model of a Coastal Aquifer Based on the Hydraulic Importance of a Dyke and Its Impact on Water Quality: Manglaralto—Ecuador. Water 2021, 13, 443. [Google Scholar] [CrossRef]
  21. De Feo, G.; Antoniou, G.P.; Mays, L.W.; Dragoni, W.; Fardin, H.F.; El-Gohary, F.; Laureano, P.; Kanetaki, E.I.; Zheng, X.Y.; Angelakis, A.N. Historical Development of Wastewater Management. In Handbook of Engineering Hydrology: Environmental Hydrology and Water Management; Taylor & Francis Group: Boca Raton, FL, USA, 2014; pp. 163–218. ISBN 9781466552500. [Google Scholar]
  22. Morante-Carballo, F.; Marcatoma-Brito, L.; Carrión-Mero, P.C.; Aguilar-Aguilar, M.; Tumbaco-Ramírez, J. Urban Wastewater Treatment through a System of Green Filters in the Montañita Commune, Santa Elena, Ecuador. In Proceedings of the WIT Transactions on Ecology and the Environment; WIT Press: Southampton, UK, 2019; Volume 239, pp. 233–249. [Google Scholar]
  23. Liu, J.; Yang, H.; Gosling, S.N.; Kummu, M.; Flörke, M.; Pfister, S.; Hanasaki, N.; Wada, Y.; Zhang, X.; Zheng, C.; et al. Water scarcity assessments in the past, present, and future. Earth’s Futur. 2017, 5, 545–559. [Google Scholar] [CrossRef]
  24. Vörösmarty, C.J.; Green, P.; Salisbury, J.; Lammers, R.B. Global Water Resources: Vulnerability from Climate Change and Population Growth. Science 2000, 289, 284–288. [Google Scholar]
  25. Kahil, M.T.; Dinar, A.; Albiac, J. Modeling water scarcity and droughts for policy adaptation to climate change in arid and semiarid regions. J. Hydrol. 2015, 522, 95–109. [Google Scholar] [CrossRef]
  26. O’Neill, B.F.; Boyer, A.-L. Water conservation in desert cities: From the socioecological fix to gestures of endurance. Ambient. Soc. 2020, 23. [Google Scholar] [CrossRef]
  27. Feng, S.; Fu, Q. Expansion of global drylands under a warming climate. Atmos. Chem. Phys. 2013, 13, 10081–10094. [Google Scholar] [CrossRef]
  28. Falkenmark, M.; Lundqvist, J.; Widstrand, C. Macro-scale water scarcity requires micro-scale approaches. Nat. Resour. Forum 1989, 13, 258–267. [Google Scholar] [CrossRef]
  29. Distefano, T.; Kelly, S. Are we in deep water? Water scarcity and its limits to economic growth. Ecol. Econ. 2017, 142, 130–147. [Google Scholar] [CrossRef]
  30. Gleick, P.H. Basic Water Requirements for Human Activities: Meeting Basic Needs. Water Int. 1996, 21, 83–92. [Google Scholar] [CrossRef]
  31. Boltz, F.; Poff, N.L.; Folke, C.; Kete, N.; Brown, C.M.; Freeman, S.S.G.; Matthews, J.H.; Martinez, A.; Rockström, J. Water is a master variable: Solving for resilience in the modern era. Water Secur. 2019, 8, 100048. [Google Scholar] [CrossRef]
  32. Boyle, D.P.; Naranjo, R.; Lamorey, G.; Bassett, S.; Gupta, H.; Brookshire, D. Development of an Integrated Hydologic Model to Explore the Feasibility of Water Banking and Markets in the Southwestern, U.S. In Proceedings of the MODSIM 2005—International Congress on Modelling and Simulation: Advances and Applications for Management and Decision Making, Melbourne, Australia, 12 December 2005; pp. 615–619. [Google Scholar]
  33. Breyer, B.; Zipper, S.C.; Qiu, J. Sociohydrological Impacts of Water Conservation Under Anthropogenic Drought in Austin, TX (USA). Water Resour. Res. 2018, 54, 3062–3080. [Google Scholar] [CrossRef]
  34. Gunda, T.; Hess, D.; Hornberger, G.M.; Worland, S. Water security in practice: The quantity-quality-society nexus. Water Secur. 2018, 6, 100022. [Google Scholar] [CrossRef]
  35. Sivapalan, M.; Savenije, H.H.G.; Blöschl, G. Socio-hydrology: A new science of people and water. Hydrol. Process. 2011, 26, 1270–1276. [Google Scholar] [CrossRef]
  36. Riaux, J.; Ogilvie, A.; Jenhaoui, Z. More than just water! Hydraulic materiality and the process of resource making: A sociohydrological reading of Tunisian hillside reservoirs. J. Rural Stud. 2020, 79, 125–135. [Google Scholar] [CrossRef]
  37. Herrera-Franco, G.; Montalván-Burbano, N.; Carrión-Mero, P.; Bravo-Montero, L. Worldwide Research on Socio-Hydrology: A Bibliometric Analysis. Water 2021, 13, 1283. [Google Scholar] [CrossRef]
  38. Herrera-Franco, G.; Alvarado-Macancela, N.; Gavín-Quinchuela, T.; Carrión-Mero, P. Participatory socio-ecological system: Manglaralto-Santa Elena, Ecuador. Geol. Ecol. Landscapes 2018, 2, 303–310. [Google Scholar] [CrossRef]
  39. Carrión, P.; Briones, J.; Herrera, G.; Sánchez, C.; Limón, J. Practical adaptations of ancestral knowledge for groundwater artificial recharge management of Manglaralto coastal aquifer, Ecuador. Sustain. Develop. Plan. 2018, 2018, 341. [Google Scholar] [CrossRef]
  40. Gricelda, H.F.; Paúl, C.M.; Niurka, A.M. Participatory Process for Local Development: Sustainability of Water Resources in Rural Communities: Case Manglaralto-Santa Elena, Ecuador. Political Sci. 2017, 2017, 663–676. [Google Scholar] [CrossRef]
  41. Herrera-Franco, G.; Carrión-Mero, P.; Aguilar-Aguilar, M.; Morante-Carballo, F.; Jaya-Montalvo, M.; Morillo-Balsera, M. Groundwater Resilience Assessment in a Communal Coastal Aquifer System. The Case of Manglaralto in Santa Elena, Ecuador. Sustainability 2020, 12, 8290. [Google Scholar] [CrossRef]
  42. Ricart, S.; Villar-Navascués, R.; Hernández-Hernández, M.; Rico-Amorós, A.; Olcina-Cantos, J.; Moltó-Mantero, E. Extending Natural Limits to Address Water Scarcity? The Role of Non-Conventional Water Fluxes in Climate Change Adaptation Capacity: A Review. Sustainability 2021, 13, 2473. [Google Scholar] [CrossRef]
  43. Carrión-Mero, P.; Montalván-Burbano, N.; Morante-Carballo, F.; Quesada-Román, A.; Apolo-Masache, B. Worldwide Research Trends in Landslide Science. Int. J. Environ. Res. Public Heal. 2021, 18, 9445. [Google Scholar] [CrossRef]
  44. Donthu, N.; Kumar, S.; Pandey, N.; Pandey, N.; Mishra, A. Mapping the electronic word-of-mouth (eWOM) research: A systematic review and bibliometric analysis. J. Bus. Res. 2021, 135, 758–773. [Google Scholar] [CrossRef]
  45. Tranfield, D.; Denyer, D.; Smart, P. Towards a Methodology for Developing Evidence-Informed Management Knowledge by Means of Systematic Review. Br. J. Manag. 2003, 14, 207–222. [Google Scholar] [CrossRef]
  46. Fahimnia, B.; Sarkis, J.; Davarzani, H. Green supply chain management: A review and bibliometric analysis. Int. J. Prod. Econ. 2015, 162, 101–114. [Google Scholar] [CrossRef]
  47. Price, D.J.D.S. Networks of scientific papers: The pattern of bibliographic references indicates the nature of the scientific research front. Science 1965, 149, 510–515. [Google Scholar] [CrossRef]
  48. Zupic, I.; Čater, T. Bibliometric methods in management and organization. Organ. Res. Methods 2015, 18, 429–472. [Google Scholar] [CrossRef]
  49. Herrera-Franco, G.; Carrión-Mero, P.; Montalván-Burbano, N.; Caicedo-Potosí, J.; Berrezueta, E. Geoheritage and Geosites: A Bibliometric Analysis and Literature Review. Geosciences 2022, 12, 169. [Google Scholar] [CrossRef]
  50. Ho, Y.-S.; Gatto, A. A bibliometric analysis of publications in Ambio in the last four decades. Environ. Sci. Pollut. Res. 2021, 28, 64345–64359. [Google Scholar] [CrossRef]
  51. Bielański, M.; Korbiel, K.; Taczanowska, K.; Pardo-Ibañez, A.; González, L.-M. How tourism research integrates environmental issues? A keyword network analysis. J. Outdoor Recreat. Tour. 2022, 37, 100503. [Google Scholar] [CrossRef]
  52. Mishra, H.G.; Pandita, S.; Bhat, A.A.; Mishra, R.K.; Sharma, S. Tourism and carbon emissions: A bibliometric review of the last three decades: 1990–2021. Tour. Rev. 2021, 77, 636–658. [Google Scholar] [CrossRef]
  53. Lema, R.; Kraemer-Mbula, E.; Rakas, M. Innovation in developing countries: Examining two decades of research. Innov. Dev. 2021, 11, 189–210. [Google Scholar] [CrossRef]
  54. Carrión-Mero, P.; Montalván-Burbano, N.; Herrera-Narváez, G.; Morante-Carballo, F. Geodiversity and Mining Towards the Development of Geotourism: A Global Perspective. Int. J. Des. Nat. Ecodynamics 2021, 16, 191–201. [Google Scholar] [CrossRef]
  55. Nettle, D.; Frankenhuis, W.E. The evolution of life-history theory: A bibliometric analysis of an interdisciplinary research area. Proc. R. Soc. B Boil. Sci. 2019, 286, 20190040. [Google Scholar] [CrossRef]
  56. Wee, S.-C.; Choong, W.-W.; Low, S.-T. Can “Nudging” Play a Role to Promote Pro-Environmental Behaviour? Environ. Challenges 2021, 5, 100364. [Google Scholar] [CrossRef]
  57. Martín-Martín, A.; Orduna-Malea, E.; Thelwall, M.; Delgado López-Cózar, E. Google Scholar, Web of Science, and Scopus: A systematic comparison of citations in 252 subject categories. J. Informetr. 2018, 12, 1160–1177. [Google Scholar] [CrossRef]
  58. Abrizah, A.; Zainab, A.N.; Kiran, K.; Raj, R.G.; Abdullah, A. LIS journals scientific impact and subject categorization: A comparison between Web of Science and Scopus. Scientometrics 2012, 94, 721–740. [Google Scholar] [CrossRef]
  59. Álvarez-García, J.; Durán-Sánchez, A.; Río-Rama, M.D.L.C.D.; García-Vélez, D.F. Active Ageing: Mapping of Scientific Coverage. Int. J. Environ. Res. Public Heal. 2018, 15, 2727. [Google Scholar] [CrossRef]
  60. Morante-Carballo, F.; Montalván-Burbano, N.; Carrión-Mero, P.; Jácome-Francis, K. Worldwide Research Analysis on Natural Zeolites as Environmental Remediation Materials. Sustainability 2021, 13, 6378. [Google Scholar] [CrossRef]
  61. Kulkanjanapiban, P.; Silwattananusarn, T. Comparative analysis of Dimensions and Scopus bibliographic data sources: An approach to university research productivity. Int. J. Electr. Comput. Eng. 2022, 12, 706–720. [Google Scholar] [CrossRef]
  62. Belmonte-Ureña, L.J.; Plaza-Úbeda, J.A.; Vazquez-Brust, D.; Yakovleva, N. Circular economy, degrowth and green growth as pathways for research on sustainable development goals: A global analysis and future agenda. Ecol. Econ. 2021, 185, 107050. [Google Scholar] [CrossRef]
  63. Mongeon, P.; Paul-Hus, A. The journal coverage of Web of Science and Scopus: A comparative analysis. Scientometrics 2016, 106, 213–228. [Google Scholar] [CrossRef]
  64. Van Loon, A.F.; Van Lanen, H.A.J. Making the distinction between water scarcity and drought using an observation-modeling framework. Water Resour. Res. 2013, 49, 1483–1502. [Google Scholar] [CrossRef]
  65. Jaeger, W.K.; Plantinga, A.J.; Chang, H.; Dello, K.; Grant, G.; Hulse, D.; McDonnell, J.J.; Lancaster, S.; Moradkhani, H.; Morzillo, A.T.; et al. Toward a formal definition of water scarcity in natural-human systems. Water Resour. Res. 2013, 49, 4506–4517. [Google Scholar] [CrossRef]
  66. Salehi, M. Global water shortage and potable water safety; Today’s concern and tomorrow’s crisis. Environ. Int. 2021, 158, 106936. [Google Scholar] [CrossRef]
  67. Venegas-Quiñones, H.L.; Thomasson, M.; Garcia-Chevesich, P.A. Water scarcity or drought? the cause and solution for the lack of water in laguna de Aculeo. Water Conserv. Manag. 2020, 4, 42–50. [Google Scholar] [CrossRef]
  68. Karanisa, T.; Amato, A.; Richer, R.; Majid, S.A.; Skelhorn, C.; Sayadi, S. Agricultural Production in Qatar’s Hot Arid Climate. Sustainability 2021, 13, 4059. [Google Scholar] [CrossRef]
  69. Daifallah, T.; Hani, A. Water Demand Management Is Solution of Water Stress? A Case Study of the Kebir-West River Basin in Northern Algeria. Water Energy Int. 2018, 60RNI, 62–66. Available online: https://www.indianjournals.com/ijor.aspx?target=ijor:wei&volume=60r&issue=11&article=010 (accessed on 10 February 2022).
  70. Serrano, L.; Sianes, A.; Ariza-Montes, A. Using Bibliometric Methods to Shed Light on the Concept of Sustainable Tourism. Sustainability 2019, 11, 6964. [Google Scholar] [CrossRef]
  71. Benckendorff, P.; Zehrer, A. A network analysis of tourism research. Ann. Tour. Res. 2013, 43, 121–149. [Google Scholar] [CrossRef]
  72. Morante-Carballo, F.; Montalván-Burbano, N.; Aguilar-Aguilar, M.; Carrión-Mero, P. A Bibliometric Analysis of the Scientific Research on Artisanal and Small-Scale Mining. Int. J. Environ. Res. Public Health 2022, 19, 8156. [Google Scholar] [CrossRef] [PubMed]
  73. Perianes-Rodriguez, A.; Waltman, L.; van Eck, N.J. Constructing bibliometric networks: A comparison between full and fractional counting. J. Inf. 2016, 10, 1178–1195. [Google Scholar] [CrossRef]
  74. Pascucci, T.; Hernández-Sánchez, B.R.; Sánchez-García, J.C. Cooperation and Environmental Responsibility as Positive Factors for Entrepreneurial Resilience. Sustainability 2021, 14, 424. [Google Scholar] [CrossRef]
  75. Van Eck, N.J.; Waltman, L. Software survey: VOSviewer, a computer program for bibliometric mapping. Scientometrics 2009, 84, 523–538. [Google Scholar] [CrossRef] [PubMed]
  76. Herrera-Franco, G.; Montalván-Burbano, N.; Mora-Frank, C.; Bravo-Montero, L. Scientific Research in Ecuador: A Bibliometric Analysis. Publications 2021, 9, 55. [Google Scholar] [CrossRef]
  77. Sabando-Vera, D.; Yonfa-Medranda, M.; Montalván-Burbano, N.; Albors-Garrigos, J.; Parrales-Guerrero, K. Worldwide Research on Open Innovation in SMEs. J. Open Innov. Technol. Mark. Complex. 2022, 8, 20. [Google Scholar] [CrossRef]
  78. Meseguer-Sánchez, V.; López-Martínez, G.; Molina-Moreno, V.; Belmonte-Ureña, L. The Role of Women in a Family Economy. A Bibliometric Analysis in Contexts of Poverty. Sustainability 2020, 12, 10328. [Google Scholar] [CrossRef]
  79. Abad-Segura, E.; Cortés-García, F.J.; Belmonte-Ureña, L.J. The Sustainable Approach to Corporate Social Responsibility: A Global Analysis and Future Trends. Sustainability 2019, 11, 5382. [Google Scholar] [CrossRef]
  80. Maldonado-Erazo, C.P.; Álvarez-García, J.; Río-Rama, M.D.L.C.D.; Correa-Quezada, R. Corporate Social Responsibility and Performance in SMEs: Scientific Coverage. Sustainability 2020, 12, 2332. [Google Scholar] [CrossRef]
  81. Liao, H.; Tang, M.; Luo, L.; Li, C.; Chiclana, F.; Zeng, X.-J. A Bibliometric Analysis and Visualization of Medical Big Data Research. Sustainability 2018, 10, 166. [Google Scholar] [CrossRef]
  82. Zyoud, S.H.; Al-Jabi, S.W.; Amer, R.; Shakhshir, M.; Shahwan, M.; Jairoun, A.A.; Akkawi, M.; Abu Taha, A. Global research trends on the links between the gut microbiome and cancer: A visualization analysis. J. Transl. Med. 2022, 20, 1–10. [Google Scholar] [CrossRef] [PubMed]
  83. Tang, M.; Liao, H.; Wan, Z.; Herrera-Viedma, E.; Rosen, M.A. Ten Years of Sustainability (2009 to 2018): A Bibliometric Overview. Sustainability 2018, 10, 1655. [Google Scholar] [CrossRef]
  84. Durán-Sánchez, A.; Álvarez-García, J.; De la Cruz Del Río-Rama, M. Sustainable Water Resources Management: A Bibliometric Overview. Water 2018, 10, 1191. [Google Scholar] [CrossRef]
  85. Herrera-Franco, G.; Carrión-Mero, P.; Montalván-Burbano, N.; Mora-Frank, C.; Berrezueta, E. Bibliometric Analysis of Groundwater’s Life Cycle Assessment Research. Water 2022, 14, 1082. [Google Scholar] [CrossRef]
  86. Morante-Carballo, F.; Montalván-Burbano, N.; Carrión-Mero, P.; Espinoza-Santos, N. Cation Exchange of Natural Zeolites: Worldwide Research. Sustainability 2021, 13, 7751. [Google Scholar] [CrossRef]
  87. Quesada-Román, A.; Torres-Bernhard, L.; Ruiz-Álvarez, M.A.; Rodríguez-Maradiaga, M.; Velázquez-Espinoza, G.; Espinosa-Vega, C.; Toral, J.; Rodríguez-Bolaños, H. Geodiversity, Geoconservation, and Geotourism in Central America. Land 2021, 11, 48. [Google Scholar] [CrossRef]
  88. Liu, C.; Gui, Q.; Duan, D.; Yin, M. Structural Heterogeneity and Proximity Mechanism of Global Scientific Collaboration Network Based on Co-Authored Papers. Acta Geogr. Sin. 2017, 72, 737–752. [Google Scholar] [CrossRef]
  89. Chen, C.; Chitose, A.; Kusadokoro, M.; Nie, H.; Xu, W.; Yang, F.; Yang, S. Sustainability and challenges in biodiesel production from waste cooking oil: An advanced bibliometric analysis. Energy Rep. 2021, 7, 4022–4034. [Google Scholar] [CrossRef]
  90. Aria, M.; Cuccurullo, C. bibliometrix: An R-tool for comprehensive science mapping analysis. J. Informetr. 2017, 11, 959–975. [Google Scholar] [CrossRef]
  91. Linnenluecke, M.K.; Marrone, M.; Singh, A. Conducting systematic literature reviews and bibliometric analyses. Aust. J. Manag. 2019, 45, 175–194. [Google Scholar] [CrossRef]
  92. Moral-Muñoz, J.A.; Herrera-Viedma, E.; Santisteban-Espejo, A.; Cobo, M.J. Software tools for conducting bibliometric analysis in science: An up-to-date review. Prof. Inf. 2020, 29, e290103. [Google Scholar] [CrossRef]
  93. Priovashini, C.; Mallick, B. A bibliometric review on the drivers of environmental migration. Ambio 2021, 51, 241–252. [Google Scholar] [CrossRef] [PubMed]
  94. Rodríguez-Soler, R.; Uribe-Toril, J.; Valenciano, J.D.P. Worldwide trends in the scientific production on rural depopulation, a bibliometric analysis using bibliometrix R-tool. Land Use Policy 2020, 97, 104787. [Google Scholar] [CrossRef]
  95. Morante-Carballo, F.; Montalván-Burbano, N.; Arias-Hidalgo, M.; Domínguez-Granda, L.; Apolo-Masache, B.; Carrión-Mero, P. Flood Models: An Exploratory Analysis and Research Trends. Water 2022, 14, 2488. [Google Scholar] [CrossRef]
  96. Yadav, S.; Lenka, U. Uncovering the intellectual structure of diversity management research: A bibliometric analysis (1990–2019). Pers. Rev. 2022, in press. [Google Scholar] [CrossRef]
  97. Cobo, M.J.; López-Herrera, A.G.; Herrera-Viedma, E.; Herrera, F. Science mapping software tools: Review, analysis, and cooperative study among tools. J. Am. Soc. Inf. Sci. Technol. 2011, 62, 1382–1402. [Google Scholar] [CrossRef]
  98. Tamala, J.K.; Maramag, E.I.; Simeon, K.A.; Ignacio, J.J. A bibliometric analysis of sustainable oil and gas production research using VOSviewer. Clean. Eng. Technol. 2022, 7, 100437. [Google Scholar] [CrossRef]
  99. Gutiérrez-Salcedo, M.; Martínez, M.A.; Moral-Munoz, J.A.; Herrera-Viedma, E.; Cobo, M.J. Some bibliometric procedures for analyzing and evaluating research fields. Appl. Intell. 2017, 48, 1275–1287. [Google Scholar] [CrossRef]
  100. 1van Eck, N.J.; Waltman, L. Visualizing Bibliometric Networks. In Measuring Scholarly Impact; Springer International Publishing: Cham, Switzerland, 2014; pp. 285–320. [Google Scholar] [CrossRef]
  101. Luc, P.T.; Lan, P.X.; Le, A.N.H.; Trang, B.T. A Co-Citation and Co-Word Analysis of Social Entrepreneurship Research. J. Soc. Entrep. 2020, 1–16. [Google Scholar] [CrossRef]
  102. Chandra, Y. Mapping the evolution of entrepreneurship as a field of research (1990–2013): A scientometric analysis. PLoS ONE 2018, 13, e0190228. [Google Scholar] [CrossRef]
  103. Coahran, G.F.; Butcher, W.S. DYNAMIC PROGRAMMING FOR OPTIMUM CONJUNCTIVE USE. JAWRA J. Am. Water Resour. Assoc. 1970, 6, 311–322. [Google Scholar] [CrossRef]
  104. Delyannis, E.; Delyannis, A. Solar applications in desalting. Desalination 1977, 23, 541–547. [Google Scholar] [CrossRef]
  105. Lehman, O.R.; Hauser, V.L. Playa Water Quality Changes with Time and Effects on Clarification. Water Resour. Res. 1970, 6, 1420–1423. [Google Scholar] [CrossRef]
  106. Wiener, A. Coping with Water Deficiency in Arid and Semi Arid Countries through High Efficiency Water Management. Ambio 1977, 6, 77–82. Available online: http://www.jstor.org/stable/4312250 (accessed on 5 February 2022).
  107. Willems, N.J.; Armitage, K.B. Thermoregulation and water requirements in semiarid and montane populations of the least chipmunk, Eutamias minimus—III. Acclimatization at a high ambient temperature. Comp. Biochem. Physiol. Part A Physiol. 1975, 52, 121–128. [Google Scholar] [CrossRef]
  108. Ingham, E.R.; Trofymow, J.A.; Ames, R.N.; Hunt, H.W.; Morley, C.R.; Moore, J.C.; Coleman, D.C. Trophic Interactions and Nitrogen Cycling in a Semi-Arid Grassland Soil. I. Seasonal Dynamics of the Natural Populations, Their Interactions and Effects on Nitrogen Cycling. J. Appl. Ecol. 1986, 23, 597. [Google Scholar] [CrossRef]
  109. Muchow, R.C. An analysis of the effects of water deficits on grain legumes grown in a semi-arid tropical environment in terms of radiation interception and its efficiency of use. Field Crop. Res. 1985, 11, 309–323. [Google Scholar] [CrossRef]
  110. Muchow, R. Comparative productivity of maize, sorghum and pearl millet in a semi-arid tropical environment II. Effect of water deficits. Field Crop. Res. 1989, 20, 207–219. [Google Scholar] [CrossRef]
  111. Hamdy, A.; Abu-Zeid, M.; Lacirignola, C. Water Crisis in the Mediterranean: Agricultural Water Demand Management. Water Int. 1995, 20, 176–187. [Google Scholar] [CrossRef]
  112. Hendry, G.A.F. Evolutionary origins and natural functions of fructans - a climatological, biogeographic and mechanistic appraisal. New Phytol. 1993, 123, 3–14. [Google Scholar] [CrossRef]
  113. Del Arco, J.M.; Escudero, A.; Garrido, M.V. Effects of Site Characteristics on Nitrogen Retranslocation from Senescing Leaves. Ecology 1991, 72, 701–708. [Google Scholar] [CrossRef]
  114. Piha, M.I. Optimizing Fertilizer Use and Practical Rainfall Capture in a Semi-Arid Environment with Variable Rainfall. Exp. Agric. 1993, 29, 405–415. [Google Scholar] [CrossRef]
  115. Mensforth, L.J.; Thorburn, P.J.; Tyerman, S.D.; Walker, G.R. Sources of water used by riparian Eucalyptus camaldulensis overlying highly saline groundwater. Oecologia 1994, 100, 21–28. [Google Scholar] [CrossRef] [PubMed]
  116. Thorburn, P.J.; Walker, G.R. Variations in stream water uptake by Eucalyptus camaldulensis with differing access to stream water. Oecologia 1994, 100, 293–301. [Google Scholar] [CrossRef] [PubMed]
  117. Pelaez, D.; Distel, R.; Boo, R.; Elia, O.; Mayor, M. Water relations between shrubs and grasses in semi-arid Argentina. J. Arid Environ. 1994, 27, 71–78. [Google Scholar] [CrossRef]
  118. Pugnaire, F.I.; Haase, P.; Incoll, L.D.; Clark, S.C. Response of the Tussock Grass Stipa tenacissima to Watering in a Semi-Arid Environment. Funct. Ecol. 1996, 10, 265. [Google Scholar] [CrossRef]
  119. Hughes, L. Climate change and Australia: Trends, projections and impacts. Austral. Ecol. 2003, 28, 423–443. [Google Scholar] [CrossRef]
  120. Liu, W.; Zhang, Z.; Wan, S. Predominant role of water in regulating soil and microbial respiration and their responses to climate change in a semiarid grassland. Glob. Chang. Biol. 2009, 15, 184–195. [Google Scholar] [CrossRef]
  121. Liancourt, P.; Spence, L.A.; Boldgiv, B.; Lkhagva, A.; Helliker, B.R.; Casper, B.B.; Petraitis, P.S. Vulnerability of the northern Mongolian steppe to climate change: Insights from flower production and phenology. Ecology 2012, 93, 815–824. [Google Scholar] [CrossRef]
  122. Montenegro, A.; Ragab, R. Hydrological response of a Brazilian semi-arid catchment to different land use and climate change scenarios: A modelling study. Hydrol. Process. 2010, 24, 2705–2723. [Google Scholar] [CrossRef]
  123. Gaál, M.; Quiroga, S.; Fernandez-Haddad, Z. Potential impacts of climate change on agricultural land use suitability of the Hungarian counties. Reg. Environ. Chang. 2013, 14, 597–610. [Google Scholar] [CrossRef]
  124. Smith, W.; Grant, B.; Desjardins, R.L.; Qian, B.; Hutchinson, J.; Gameda, S. Potential impact of climate change on carbon in agricultural soils in Canada 2000–2099. Clim. Chang. 2008, 93, 319–333. [Google Scholar] [CrossRef]
  125. Abdulla, F.; Eshtawi, T.; Assaf, H. Assessment of the Impact of Potential Climate Change on the Water Balance of a Semi-arid Watershed. Water Resour. Manag. 2008, 23, 2051–2068. [Google Scholar] [CrossRef]
  126. Cui, X.; Huang, G.; Chen, W.; Morse, A. Threatening of climate change on water resources and supply: Case study of North China. Desalination 2009, 248, 476–478. [Google Scholar] [CrossRef]
  127. Kundzewicz, Z.W.; Döll, P. Will groundwater ease freshwater stress under climate change? Hydrol. Sci. J. 2009, 54, 665–675. [Google Scholar] [CrossRef]
  128. Zhang, D.; Liu, X.; Hong, H. Assessing the effect of climate change on reference evapotranspiration in China. Stoch. Hydrol. Hydraul. 2013, 27, 1871–1881. [Google Scholar] [CrossRef]
  129. Şen, Z.; Al Alsheikh, A.; Al-Turbak, A.S.; Al-Bassam, A.M.; Al-Dakheel, A.M. Climate change impact and runoff harvesting in arid regions. Arab. J. Geosci. 2011, 6, 287–295. [Google Scholar] [CrossRef]
  130. Er-Raki, S.; Chehbouni, A.; Duchemin, B. Combining Satellite Remote Sensing Data with the FAO-56 Dual Approach for Water Use Mapping In Irrigated Wheat Fields of a Semi-Arid Region. Remote Sens. 2010, 2, 375–387. [Google Scholar] [CrossRef]
  131. Allen, R.G.; Tasumi, M.; Trezza, R. Satellite-Based Energy Balance for Mapping Evapotranspiration with Internalized Calibration (METRIC)—Model. J. Irrig. Drain. Eng. 2007, 133, 380–394. [Google Scholar] [CrossRef]
  132. Barbagallo, S.; Consoli, S.; Russo, A. A One-Layer Satellite Surface Energy Balance for Estimating Evapotranspiration Rates and Crop Water Stress Indexes. Sensors 2009, 9, 1–21. [Google Scholar] [CrossRef]
  133. Cho, J.; Lee, Y.-W.; Lee, H.-S. Assessment of the relationship between thermal-infrared-based temperature−vegetation dryness index and microwave satellite-derived soil moisture. Remote Sens. Lett. 2014, 5, 627–636. [Google Scholar] [CrossRef]
  134. Strassberg, G.; Scanlon, B.R.; Chambers, D. Evaluation of groundwater storage monitoring with the GRACE satellite: Case study of the High Plains aquifer, central United States. Water Resour. Res. 2009, 45, 892. [Google Scholar] [CrossRef]
  135. Deng, X.P.; Shan, L.; Zhang, H.; Turner, N.C. Improving agricultural water use efficiency in arid and semiarid areas of China. Agric. Water Manag. 2006, 80, 23–40. [Google Scholar]
  136. Wallace, J. Increasing agricultural water use efficiency to meet future food production. Agric. Ecosyst. Environ. 2000, 82, 105–119. [Google Scholar] [CrossRef]
  137. Viviroli, D.; Dürr, H.H.; Messerli, B.; Meybeck, M.; Weingartner, R. Mountains of the world, water towers for humanity: Typology, mapping, and global significance. Water Resour. Res. 2007, 43, 1–13. [Google Scholar] [CrossRef]
  138. Cao, S.; Chen, L.; Shankman, D.; Wang, C.; Wang, X.; Zhang, H. Excessive reliance on afforestation in China’s arid and semi-arid regions: Lessons in ecological restoration. Earth-Science Rev. 2011, 104, 240–245. [Google Scholar] [CrossRef]
  139. Jian, S.; Zhao, C.; Fang, S.; Yu, K. Effects of different vegetation restoration on soil water storage and water balance in the Chinese Loess Plateau. Agric. For. Meteorol. 2015, 206, 85–96. [Google Scholar] [CrossRef]
  140. Feng, X.; Fu, B.; Piao, S.; Wang, S.; Ciais, P.; Zeng, Z.; Lü, Y.; Zeng, Y.; Li, Y.; Jiang, X.; et al. Revegetation in China’s Loess Plateau is approaching sustainable water resource limits. Nat. Clim. Chang. 2016, 6, 1019–1022. [Google Scholar] [CrossRef]
  141. Hanin, M.; Ebel, C.; Ngom, M.; Laplaze, L.; Masmoudi, K. New Insights on Plant Salt Tolerance Mechanisms and Their Potential Use for Breeding. Front. Plant Sci. 2016, 7, 1787. [Google Scholar] [CrossRef]
  142. Sarker, U.; Oba, S. Response of nutrients, minerals, antioxidant leaf pigments, vitamins, polyphenol, flavonoid and antioxidant activity in selected vegetable amaranth under four soil water content. Food Chem. 2018, 252, 72–83. [Google Scholar] [CrossRef]
  143. Karthe, D.; Chalov, S.; Borchardt, D. Water resources and their management in central Asia in the early twenty first century: Status, challenges and future prospects. Environ. Earth Sci. 2014, 73, 487–499. [Google Scholar] [CrossRef]
  144. Voulvoulis, N. Water reuse from a circular economy perspective and potential risks from an unregulated approach. Curr. Opin. Environ. Sci. Health 2018, 2, 32–45. [Google Scholar] [CrossRef]
  145. Wang, J.; Song, C.; Reager, J.T.; Yao, F.; Famiglietti, J.S.; Sheng, Y.; Macdonald, G.M.; Brun, F.; Schmied, H.M.; Marston, R.A.; et al. Recent global decline in endorheic basin water storages. Nat. Geosci. 2018, 11, 926–932, Correction in Nat. Geosci. 2019, 12, 220. [Google Scholar] [CrossRef]
  146. Berger, M.; van der Ent, R.; Eisner, S.; Bach, V.; Finkbeiner, M. Water Accounting and Vulnerability Evaluation (WAVE): Considering Atmospheric Evaporation Recycling and the Risk of Freshwater Depletion in Water Footprinting. Environ. Sci. Technol. 2014, 48, 4521–4528. [Google Scholar] [CrossRef]
  147. Wada, Y.; Flörke, M.; Hanasaki, N.; Eisner, S.; Fischer, G.; Tramberend, S.; Satoh, Y.; van Vliet, M.T.H.; Yillia, P.; Ringler, C.; et al. Modeling global water use for the 21st century: The Water Futures and Solutions (WFaS) initiative and its approaches. Geosci. Model Dev. 2016, 9, 175–222. [Google Scholar] [CrossRef]
  148. Morshedloo, M.R.; Craker, L.E.; Salami, A.; Nazeri, V.; Sang, H.; Maggi, F. Effect of prolonged water stress on essential oil content, compositions and gene expression patterns of mono- and sesquiterpene synthesis in two oregano (Origanum vulgare L.) subspecies. Plant Physiol. Biochem. 2017, 111, 119–128. [Google Scholar] [CrossRef]
  149. Parkash, V.; Singh, S. A Review on Potential Plant-Based Water Stress Indicators for Vegetable Crops. Sustainability 2020, 12, 3945. [Google Scholar] [CrossRef]
  150. Holzman, M.E.; Carmona, F.; Rivas, R.; Niclòs, R. Early assessment of crop yield from remotely sensed water stress and solar radiation data. ISPRS J. Photogramm. Remote Sens. 2018, 145, 297–308. [Google Scholar] [CrossRef]
  151. King, B.; Shellie, K. Evaluation of neural network modeling to predict non-water-stressed leaf temperature in wine grape for calculation of crop water stress index. Agric. Water Manag. 2016, 167, 38–52. [Google Scholar] [CrossRef]
  152. Merino-Martín, L.; Courtauld, C.; Commander, L.; Turner, S.; Lewandrowski, W.; Stevens, J. Interactions between seed functional traits and burial depth regulate germination and seedling emergence under water stress in species from semi-arid environments. J. Arid Environ. 2017, 147, 25–33. [Google Scholar] [CrossRef]
  153. Nouri, H.; Stokvis, B.; Galindo, A.; Blatchford, M.; Hoekstra, A. Water scarcity alleviation through water footprint reduction in agriculture: The effect of soil mulching and drip irrigation. Sci. Total Environ. 2018, 653, 241–252. [Google Scholar] [CrossRef]
  154. Rocha, R.; Soares, R.R. Water scarcity and birth outcomes in the Brazilian semiarid. J. Dev. Econ. 2015, 112, 72–91. [Google Scholar] [CrossRef]
  155. Abu-Allaban, M.; El-Naqa, A.; Jaber, M.; Hammouri, N. Water scarcity impact of climate change in semi-arid regions: A case study in Mujib basin, Jordan. Arab. J. Geosci. 2014, 8, 951–959. [Google Scholar] [CrossRef]
  156. Yannopoulos, S.; Giannopoulou, I.; Kaiafa-Saropoulou, M. Investigation of the Current Situation and Prospects for the Development of Rainwater Harvesting as a Tool to Confront Water Scarcity Worldwide. Water 2019, 11, 2168. [Google Scholar] [CrossRef]
  157. Clemens, M.; Khurelbaatar, G.; Merz, R.; Siebert, C.; van Afferden, M.; Rödiger, T. Groundwater protection under water scarcity; from regional risk assessment to local wastewater treatment solutions in Jordan. Sci. Total Environ. 2020, 706, 136066. [Google Scholar] [CrossRef]
  158. Wu, X.; Zhou, J.; Wang, H.; Li, Y.; Zhong, B. Evaluation of irrigation water use efficiency using remote sensing in the middle reach of the Heihe river, in the semi-arid Northwestern China. Hydrol. Process. 2014, 29, 2243–2257. [Google Scholar] [CrossRef]
  159. Du, S.; Kang, S.; Li, F.; Du, T. Water use efficiency is improved by alternate partial root-zone irrigation of apple in arid northwest China. Agric. Water Manag. 2017, 179, 184–192. [Google Scholar] [CrossRef]
  160. Gheysari, M.; Loescher, H.W.; Sadeghi, S.H.; Mirlatifi, S.M.; Zareian, M.J.; Hoogenboom, G. Water-Yield Relations and Water Use Efficiency of Maize Under Nitrogen Fertigation for Semiarid Environments: Experiment and Synthesis. Adv. Agron. 2015, 2015, 175–229. [Google Scholar] [CrossRef]
  161. Song, L.; Zhu, J.; Yan, Q.; Li, M.; Yu, G. Comparison of intrinsic water use efficiency between different aged Pinus sylvestris var. mongolica wide windbreaks in semiarid sandy land of northern China. Agrofor. Syst. 2015, 89, 477–489. [Google Scholar] [CrossRef]
  162. Razzaq, A.; Qing, P.; Naseer, M.A.U.R.; Abid, M.; Anwar, M.; Javed, I. Can the informal groundwater markets improve water use efficiency and equity? Evidence from a semi-arid region of Pakistan. Sci. Total Environ. 2019, 666, 849–857. [Google Scholar] [CrossRef]
  163. Ding, Z.; Kheir, A.M.S.; Ali, M.G.M.; Ali, O.A.M.; Abdelaal, A.I.N.; Lin, X.; Zhou, Z.; Wang, B.; Liu, B.; He, Z. The integrated effect of salinity, organic amendments, phosphorus fertilizers, and deficit irrigation on soil properties, phosphorus fractionation and wheat productivity. Sci. Rep. 2020, 10, 1–13. [Google Scholar] [CrossRef]
  164. Ghannem, A.; BEN Aissa, I.; Majdoub, R. Effects of regulated deficit irrigation applied at different growth stages of greenhouse grown tomato on substrate moisture, yield, fruit quality, and physiological traits. Environ. Sci. Pollut. Res. 2020, 28, 46553–46564. [Google Scholar] [CrossRef]
  165. Fan, J.; Wu, L.; Zhang, F.; Xiang, Y.; Zheng, J. Climate change effects on reference crop evapotranspiration across different climatic zones of China during 1956–2015. J. Hydrol. 2016, 542, 923–937. [Google Scholar] [CrossRef]
  166. Rafi, Z.; Merlin, O.; Le Dantec, V.; Khabba, S.; Mordelet, P.; Er-Raki, S.; Amazirh, A.; Olivera-Guerra, L.; Hssaine, B.A.; Simonneaux, V.; et al. Partitioning evapotranspiration of a drip-irrigated wheat crop: Inter-comparing eddy covariance-, sap flow-, lysimeter- and FAO-based methods. Agric. For. Meteorol. 2018, 265, 310–326. [Google Scholar] [CrossRef]
  167. Boulet, G.; Mougenot, B.; Lhomme, J.-P.; Fanise, P.; Lili-Chabaane, Z.; Olioso, A.; Bahir, M.; Rivalland, V.; Jarlan, L.; Merlin, O.; et al. The SPARSE model for the prediction of water stress and evapotranspiration components from thermal infra-red data and its evaluation over irrigated and rainfed wheat. Hydrol. Earth Syst. Sci. 2015, 19, 4653–4672. [Google Scholar] [CrossRef]
  168. Govere, S.; Nyamangara, J.; Nyakatawa, E.Z. Review: Climate change and the water footprint of wheat production in Zimbabwe. Water SA 2019, 45. [Google Scholar] [CrossRef]
  169. Sylla, M.B.; Elguindi, N.; Giorgi, F.; Wisser, D. Projected robust shift of climate zones over West Africa in response to anthropogenic climate change for the late 21st century. Clim. Chang. 2015, 134, 241–253. [Google Scholar] [CrossRef]
  170. Lasage, R.; Aerts, J.C.J.H.; Verburg, P.H.; Sileshi, A.S. The role of small scale sand dams in securing water supply under climate change in Ethiopia. Mitig. Adapt. Strat. Glob. Chang. 2013, 20, 317–339. [Google Scholar] [CrossRef]
  171. Pan, S.; Pan, N.; Tian, H.; Friedlingstein, P.; Sitch, S.; Shi, H.; Arora, V.K.; Haverd, V.; Jain, A.K.; Kato, E.; et al. Evaluation of global terrestrial evapotranspiration using state-of-the-art approaches in remote sensing, machine learning and land surface modeling. Hydrol. Earth Syst. Sci. 2020, 24, 1485–1509. [Google Scholar] [CrossRef]
  172. Scudiero, E.; Corwin, D.L.; Anderson, R.G.; Skaggs, T.H. Moving Forward on Remote Sensing of Soil Salinity at Regional Scale. Front. Environ. Sci. 2016, 4, 65. [Google Scholar] [CrossRef]
  173. Costa-Filho, E.; Chávez, J.L.; Comas, L. Determining maize water stress through a remote sensing-based surface energy balance approach. Irrig. Sci. 2020, 38, 501–518. [Google Scholar] [CrossRef]
  174. Al-Khuzaie, M.M.; Janna, H.; Al-Ansari, N. Assessment model of water harvesting and storage location using GIS and remote sensing in Al-Qadisiyah, Iraq. Arab. J. Geosci. 2020, 13, 1–9. [Google Scholar] [CrossRef]
  175. Price, D.J.D.S. Little Science, Big Science; Columbia University Press: NewYork, NY, USA, 1963. [Google Scholar]
  176. Herrera-Franco, G.; Montalván-Burbano, N.; Mora-Frank, C.; Moreno-Alcívar, L. Research in Petroleum and Environment: A Bibliometric Analysis in South America. Int. J. Sustain. Dev. Plan. 2021, 16, 1109–1116. [Google Scholar] [CrossRef]
  177. Biswas, A.K. Water for sustainable development in the 21st century. Int. J. Water Resour. Dev. 1991, 7, 219–224. [Google Scholar] [CrossRef]
  178. Galindo, A.; Collado-González, J.; Griñán, I.; Corell, M.; Centeno, A.; Martín-Palomo, M.; Girón, I.; Rodríguez, P.; Cruz, Z.; Memmi, H.; et al. Deficit irrigation and emerging fruit crops as a strategy to save water in Mediterranean semiarid agrosystems. Agric. Water Manag. 2018, 202, 311–324. [Google Scholar] [CrossRef]
  179. Qi, Y.; Shi, H.; Li, R.; Zhao, J.; Li, B.; Li, M. Effects of Film Mulching on Maize Growth and Soil Water, Fertilizer and Heat under Fertigation of Drip Irrigation. Nongye Gongcheng Xuebao/Trans. Chin. Soc. Agric. Eng. 2019, 35, 99–110. [Google Scholar] [CrossRef]
  180. Miao, X.; Wang, A.; Sun, Y.; Wang, L.; Pu, H. Research on Basic Theory of Mining with Water Resources Protection and Its Application to Arid and Semi-Arid Mining Areas. J. Rock Mech. Eng. 2009, 28, 217–227. [Google Scholar]
  181. Gohardoust, M.R.; Bar-Tal, A.; Effati, M.; Tuller, M. Characterization of Physicochemical and Hydraulic Properties of Organic and Mineral Soilless Culture Substrates and Mixtures. Agronomy 2020, 10, 1403. [Google Scholar] [CrossRef]
  182. Kalantari, A.; Kamsin, A.; Kamaruddin, H.S.; Ebrahim, N.A.; Gani, A.; Ebrahimi, A.; Shamshirband, S. A bibliometric approach to tracking big data research trends. J. Big Data 2017, 4. [Google Scholar] [CrossRef]
  183. Zhi, W.; Yuan, L.; Ji, G.; Liu, Y.; Cai, Z.; Chen, X. A bibliometric review on carbon cycling research during 1993–2013. Environ. Earth Sci. 2015, 74, 6065–6075. [Google Scholar] [CrossRef]
  184. Greve, P.; Kahil, T.; Mochizuki, J.; Schinko, T.; Satoh, Y.; Burek, P.; Fischer, G.; Tramberend, S.; Burtscher, R.; Langan, S.; et al. Global assessment of water challenges under uncertainty in water scarcity projections. Nat. Sustain. 2018, 1, 486–494. [Google Scholar] [CrossRef]
  185. Oki, T.; Quiocho, R.E. Economically challenged and water scarce: Identification of global populations most vulnerable to water crises. Int. J. Water Resour. Dev. 2020, 36, 416–428. [Google Scholar] [CrossRef]
  186. Angelakιs, A.N.; Zaccaria, D.; Krasilnikoff, J.; Salgot, M.; Bazza, M.; Roccaro, P.; Jimenez, B.; Kumar, A.; Yinghua, W.; Baba, A.; et al. Irrigation of World Agricultural Lands: Evolution through the Millennia. Water 2020, 12, 1285. [Google Scholar] [CrossRef]
  187. Chen, C.; Ahmad, S.; Kalra, A.; Xu, Z.-X. A dynamic model for exploring water-resource management scenarios in an inland arid area: Shanshan County, Northwestern China. J. Mt. Sci. 2017, 14, 1039–1057. [Google Scholar] [CrossRef]
  188. Li, M.; Fu, Q.; Guo, P.; Singh, V.P.; Zhang, C.; Yang, G. Stochastic multi-objective decision making for sustainable irrigation in a changing environment. J. Clean. Prod. 2019, 223, 928–945. [Google Scholar] [CrossRef]
  189. Xue, Q.; Zhu, Z.; Musick, J.T.; Stewart, B.A.; Dusek, D.A. Root growth and water uptake in winter wheat under deficit irrigation. Plant Soil 2003, 257, 151–161. [Google Scholar] [CrossRef]
  190. Shangguan, Z.; Shao, M.; Horton, R.; Lei, T.; Qin, L.; Ma, J. A model for regional optimal allocation of irrigation water resources under deficit irrigation and its applications. Agric. Water Manag. 2002, 52, 139–154. [Google Scholar] [CrossRef]
  191. Zhang, T.; Zou, Y.; Kisekka, I.; Biswas, A.; Cai, H. Comparison of different irrigation methods to synergistically improve maize’s yield, water productivity and economic benefits in an arid irrigation area. Agric. Water Manag. 2020, 243, 106497. [Google Scholar] [CrossRef]
  192. Wang, H.; Li, X.; Xiao, J.; Ma, M. Evapotranspiration components and water use efficiency from desert to alpine ecosystems in drylands. Agric. For. Meteorol. 2020, 298-299, 108283. [Google Scholar] [CrossRef]
  193. Wan, C.; Sosebee, R.E.; McMichael, B.L. Does hydraulic lift exist in shallow-rooted species? A quantitative examination with a half-shrub Gutierrezia sarothrae. Plant Soil 1993, 153, 11–17. [Google Scholar] [CrossRef]
  194. Mavrodi, D.; Mavrodi, O.V.; Elbourne, L.; Tetu, S.; Bonsall, R.F.; Parejko, J.; Yang, M.; Paulsen, I.; Weller, D.M.; Thomashow, L.S. Long-Term Irrigation Affects the Dynamics and Activity of the Wheat Rhizosphere Microbiome. Front. Plant Sci. 2018, 9, 345. [Google Scholar] [CrossRef] [PubMed]
  195. Yin, W.; Chai, Q.; Zhao, C.; Yu, A.; Fan, Z.; Hu, F.; Fan, H.; Guo, Y.; Coulter, J.A. Water utilization in intercropping: A review. Agric. Water Manag. 2020, 241, 106335. [Google Scholar] [CrossRef]
  196. Pedrero, F.; Kalavrouziotis, I.; Alarcón, J.J.; Koukoulakis, P.; Asano, T. Use of treated municipal wastewater in irrigated agriculture—Review of some practices in Spain and Greece. Agric. Water Manag. 2010, 97, 1233–1241. [Google Scholar] [CrossRef]
  197. Terrado, M.; Acuña, V.; Ennaanay, D.; Tallis, H.; Sabater, S. Impact of climate extremes on hydrological ecosystem services in a heavily humanized Mediterranean basin. Ecol. Indic. 2014, 37, 199–209. [Google Scholar] [CrossRef]
  198. Armas, C.; Pugnaire, F.I. Plant interactions govern population dynamics in a semi-arid plant community. J. Ecol. 2005, 93, 978–989. [Google Scholar] [CrossRef]
  199. Torres, N.; Yu, R.; Martínez-Lüscher, J.; Kostaki, E.; Kurtural, S.K. Effects of Irrigation at Different Fractions of Crop Evapotranspiration on Water Productivity and Flavonoid Composition of Cabernet Sauvignon Grapevine. Front. Plant Sci. 2021, 12. [Google Scholar] [CrossRef]
  200. López-Urrea, R.; Sánchez, J.; de la Cruz, F.; González-Piqueras, J.; Chávez, J. Evapotranspiration and crop coefficients from lysimeter measurements for sprinkler-irrigated canola. Agric. Water Manag. 2020, 239, 106260. [Google Scholar] [CrossRef]
  201. Domingo, F.; van Gardingen, P.; Brenner, A. Leaf boundary layer conductance of two native species in southeast Spain. Agric. For. Meteorol. 1996, 81, 179–199. [Google Scholar] [CrossRef]
  202. Jimenez, M.N.; Pinto, J.; Ripoll, M.; Sánchez-Miranda, A.; Navarro, F. Impact of straw and rock-fragment mulches on soil moisture and early growth of holm oaks in a semiarid area. CATENA 2017, 152, 198–206. [Google Scholar] [CrossRef]
  203. Barron-Gafford, G.A.; Sánchez-Cañete, E.P.; Minor, R.L.; Hendryx, S.M.; Lee, E.; Sutter, L.F.; Tran, N.; Parra, E.; Colella, T.; Murphy, P.C.; et al. Impacts of hydraulic redistribution on grass–tree competition vs facilitation in a semi-arid savanna. New Phytol. 2017, 215, 1451–1461. [Google Scholar] [CrossRef]
  204. Gheysari, M.; Sadeghi, S.-H.; Loescher, H.W.; Amiri, S.; Zareian, M.J.; Majidi, M.M.; Asgarinia, P.; Payero, J.O. Comparison of deficit irrigation management strategies on root, plant growth and biomass productivity of silage maize. Agric. Water Manag. 2017, 182, 126–138. [Google Scholar] [CrossRef]
  205. Kamali, M.I.; Nazari, R. Determination of maize water requirement using remote sensing data and SEBAL algorithm. Agric. Water Manag. 2018, 209, 197–205. [Google Scholar] [CrossRef]
  206. Neto, A.R.; Scott, C.A.; Lima, E.A.; Montenegro, S.M.G.L.; Cirilo, J.A. Infrastructure sufficiency in meeting water demand under climate-induced socio-hydrological transition in the urbanizing Capibaribe River basin – Brazil. Hydrol. Earth Syst. Sci. 2014, 18, 3449–3459. [Google Scholar] [CrossRef]
  207. Souza, R.; Hartzell, S.; Feng, X.; Antonino, A.C.D.; de Souza, E.S.; Menezes, R.S.C.; Porporato, A. Optimal management of cattle grazing in a seasonally dry tropical forest ecosystem under rainfall fluctuations. J. Hydrol. 2020, 588, 125102. [Google Scholar] [CrossRef]
  208. Dang, Z.; Huang, Z.; Tian, F.; Liu, Y.; López-Vicente, M.; Wu, G. Five-year soil moisture response of typical cultivated grasslands in a semiarid area: Implications for vegetation restoration. Land Degrad. Dev. 2019, 31, 1078–1085. [Google Scholar] [CrossRef]
  209. Rockström, J.; Karlberg, L.; Wani, S.P.; Barron, J.; Hatibu, N.; Oweis, T.; Bruggeman, A.; Farahani, J.; Qiang, Z. Managing water in rainfed agriculture—The need for a paradigm shift. Agric. Water Manag. 2010, 97, 543–550. [Google Scholar] [CrossRef]
  210. Amanullah; Ilyas, M.; Nabi, H.; Khalid, S.; Ahmad, M.; Muhammad, A.; Ullah, S.; Ali, I.; Fahad, S.; Adnan, M.; et al. Integrated Foliar Nutrients Application Improve Wheat (Triticum Aestivum L.) Productivity under Calcareous Soils in Drylands. Commun. Soil Sci. Plant Anal. 2021, 52, 2748–2766. [Google Scholar] [CrossRef]
  211. Hu, J.; Wu, Y.; Sun, P.; Zhao, F.; Sun, K.; Li, T.; Sivakumar, B.; Qiu, L.; Sun, Y.; Jin, Z. Predicting long-term hydrological change caused by climate shifting in the 21st century in the headwater area of the Yellow River Basin. Stoch. Hydrol. Hydraul. 2021, 36, 1651–1668. [Google Scholar] [CrossRef]
  212. Nasim, W.; Belhouchette, H.; Ahmad, A.; Habib-Ur-Rahman, M.; Jabran, K.; Ullah, K.; Fahad, S.; Shakeel, M.; Hoogenboom, G. Modelling Climate Change Impacts and Adaptation Strategies for Sunflower in Pakistan. Outlook Agric. 2016, 45, 39–45. [Google Scholar] [CrossRef]
  213. Verma, K.K.; Song, X.-P.; Verma, C.L.; Chen, Z.-L.; Rajput, V.D.; Wu, K.-C.; Liao, F.; Chen, G.-L.; Li, Y.-R. Functional relationship between photosynthetic leaf gas exchange in response to silicon application and water stress mitigation in sugarcane. Biol. Res. 2021, 54, 1–11. [Google Scholar] [CrossRef]
  214. Ali, S.; Xu, Y.; Jia, Q.; Ma, X.; Ahmad, I.; Adnan, M.; Gerard, R.; Ren, X.; Zhang, P.; Cai, T.; et al. Interactive effects of plastic film mulching with supplemental irrigation on winter wheat photosynthesis, chlorophyll fluorescence and yield under simulated precipitation conditions. Agric. Water Manag. 2018, 207, 1–14. [Google Scholar] [CrossRef]
  215. Wand, S.J.E.; Midgley, G.F.; Jones, M.H.; Curtis, P.S. Responses of wild C4 and C3 grass (Poaceae) species to elevated atmospheric CO2 concentration: A meta-analytic test of current theories and perceptions. Glob. Chang. Biol. 1999, 5, 723–741. [Google Scholar] [CrossRef]
  216. Van Eck, N.J.; Waltman, L.; Dekker, R.; van den Berg, J. A comparison of two techniques for bibliometric mapping: Multidimensional scaling and VOS. J. Am. Soc. Inf. Sci. Technol. 2010, 61, 2405–2416. [Google Scholar] [CrossRef]
  217. Oyewola, D.O.; Dada, E.G. Exploring Machine Learning: A Scientometrics Approach Using Bibliometrix and VOSviewer. SN Appl. Sci. 2022, 4, 143. [Google Scholar] [CrossRef]
  218. Saha, V.; Mani, V.; Goyal, P. Emerging trends in the literature of value co-creation: A bibliometric analysis. Benchmarking Int. J. 2020, 27, 981–1002. [Google Scholar] [CrossRef]
  219. Duque-Acevedo, M.; Belmonte-Ureña, L.J.; Yakovleva, N.; Camacho-Ferre, F. Analysis of the Circular Economic Production Models and Their Approach in Agriculture and Agricultural Waste Biomass Management. Int. J. Environ. Res. Public Heal. 2020, 17, 9549. [Google Scholar] [CrossRef]
  220. Hamdy, A.; Ragab, R.; Scarascia-Mugnozza, E. Coping with water scarcity: Water saving and increasing water productivity. Irrig. Drain. 2003, 52, 3–20. [Google Scholar] [CrossRef]
  221. De Medeiros, I.C.; Silva, J.F.C.B.D.C.; Silva, R.M.; Santos, C.A.G. Run-off–erosion modelling and water balance in the Epitácio Pessoa Dam river basin, Paraíba State in Brazil. Int. J. Environ. Sci. Technol. 2018, 16, 3035–3048. [Google Scholar] [CrossRef]
  222. Laureti, T.; Benedetti, I.; Branca, G. Water use efficiency and public goods conservation: A spatial stochastic frontier model applied to irrigation in Southern Italy. Socio-Econ. Plan. Sci. 2020, 73, 100856. [Google Scholar] [CrossRef]
  223. Cirelli, G.; Consoli, S.; Licciardello, F.; Aiello, R.; Giuffrida, F.; Leonardi, C. Treated municipal wastewater reuse in vegetable production. Agric. Water Manag. 2012, 104, 163–170. [Google Scholar] [CrossRef]
  224. Karandish, F.; Hoekstra, A.Y.; Hogeboom, R.J. Reducing food waste and changing cropping patterns to reduce water consumption and pollution in cereal production in Iran. J. Hydrol. 2020, 586, 124881. [Google Scholar] [CrossRef]
  225. Ahmad, I.; Wajid, S.A.; Cheema, M.J.M.; Judge, J. Optimizing irrigation and nitrogen requirements for maize through empirical modeling in semi-arid environment. Environ. Sci. Pollut. Res. 2018, 26, 1227–1237. [Google Scholar] [CrossRef]
  226. Fernández García, I.; Lecina, S.; Ruiz-Sánchez, M.C.; Vera, J.; Conejero, W.; Conesa, M.R.; Domínguez, A.; Pardo, J.J.; Léllis, B.C.; Montesinos, P. Trends and Challenges in Irrigation Scheduling in the Semi-Arid Area of Spain. Water 2020, 12, 785. [Google Scholar] [CrossRef]
  227. Huang, Z.; Liu, X.; Sun, S.; Tang, Y.; Yuan, X.; Tang, Q. Global assessment of future sectoral water scarcity under adaptive inner-basin water allocation measures. Sci. Total Environ. 2021, 783, 146973. [Google Scholar] [CrossRef] [PubMed]
  228. Zarei, Z.; Karami, E.; Keshavarz, M. Co-production of knowledge and adaptation to water scarcity in developing countries. J. Environ. Manag. 2020, 262, 110283. [Google Scholar] [CrossRef]
  229. Haghighi, A.T.; Fazel, N.; Hekmatzadeh, A.A.; Klöve, B. Analysis of Effective Environmental Flow Release Strategies for Lake Urmia Restoration. Water Resour. Manag. 2018, 32, 3595–3609. [Google Scholar] [CrossRef]
  230. Daneshi, A.; Brouwer, R.; Najafinejad, A.; Panahi, M.; Zarandian, A.; Maghsood, F.F. Modelling the impacts of climate and land use change on water security in a semi-arid forested watershed using InVEST. J. Hydrol. 2020, 593, 125621. [Google Scholar] [CrossRef]
  231. Xiubin, H.; Zhanbin, L.; Mingde, H.; Keli, T.; Fengli, Z. Down-scale analysis for water scarcity in response to soil–water conservation on Loess Plateau of China. Agric. Ecosyst. Environ. 2003, 94, 355–361. [Google Scholar] [CrossRef]
  232. Bosire, C.K.; Rao, E.J.O.; Muchenje, V.; Van Wijk, M.; Ogutu, J.O.; Mekonnen, M.; Auma, J.O.; Lukuyu, B.; Hammond, J. Adaptation opportunities for smallholder dairy farmers facing resource scarcity: Integrated livestock, water and land management. Agric. Ecosyst. Environ. 2019, 284, 106592. [Google Scholar] [CrossRef]
  233. Bond, N.R.; Burrows, R.M.; Kennard, M.J.; Bunn, S.E. Water Scarcity as a Driver of Multiple Stressor Effects. In Multiple stressors in river ecosystems; Elsevier: Amsterdam, The Netherlands, 2018; pp. 111–129. [Google Scholar] [CrossRef]
  234. Abdelkhalik, A.; Pascual-Seva, N.; Nájera, I.; Giner, A.; Baixauli, C.; Pascual, B. Yield response of seedless watermelon to different drip irrigation strategies under Mediterranean conditions. Agric. Water Manag. 2018, 212, 99–110. [Google Scholar] [CrossRef]
  235. Wang, F.; Xie, R.; Ming, B.; Wang, K.; Hou, P.; Chen, J.; Liu, G.; Zhang, G.; Xue, J.; Li, S. Dry matter accumulation after silking and kernel weight are the key factors for increasing maize yield and water use efficiency. Agric. Water Manag. 2021, 254, 106938. [Google Scholar] [CrossRef]
  236. Singh, R.; van Dam, J.; Feddes, R. Water productivity analysis of irrigated crops in Sirsa district, India. Agric. Water Manag. 2006, 82, 253–278. [Google Scholar] [CrossRef]
  237. Cao, X.C.; Shu, R.; Guo, X.P.; Wang, W.G. Scarce water resources and priority irrigation schemes from agronomic crops. Mitig. Adapt. Strat. Glob. Chang. 2018, 24, 399–417. [Google Scholar] [CrossRef]
  238. Liu, Y.; Song, W. Modelling crop yield, water consumption, and water use efficiency for sustainable agroecosystem management. J. Clean. Prod. 2019, 253, 119940. [Google Scholar] [CrossRef]
  239. Lian, H.; Qin, C.; He, Z.; Niu, J.; Zhang, C.; Sang, T.; Li, H.; Zhang, S. A synergistic increase in water and nitrogen use efficiencies in winter wheat cultivars released between the 1940s and the 2010s for cultivation in the drylands of the shaanxi Province in China. Agric. Water Manag. 2020, 240, 106308. [Google Scholar] [CrossRef]
  240. Sun, L.; Wang, S.; Zhang, Y.; Li, J.; Wang, X.; Wang, R.; Lyu, W.; Chen, N.; Wang, Q. Conservation agriculture based on crop rotation and tillage in the semi-arid Loess Plateau, China: Effects on crop yield and soil water use. Agric. Ecosyst. Environ. 2018, 251, 67–77. [Google Scholar] [CrossRef]
  241. Li, Z.; Lai, X.; Yang, Q.; Yang, X.; Cui, S.; Shen, Y. In search of long-term sustainable tillage and straw mulching practices for a maize-winter wheat-soybean rotation system in the Loess Plateau of China. Field Crop. Res. 2017, 217, 199–210. [Google Scholar] [CrossRef]
  242. Pandey, R.; Maranville, J.; Admou, A. Deficit irrigation and nitrogen effects on maize in a Sahelian environment: I. Grain yield and yield components. Agric. Water Manag. 2000, 46, 1–13. [Google Scholar] [CrossRef]
  243. Angelakis, A.N.; Valipour, M.; Choo, K.-H.; Ahmed, A.T.; Baba, A.; Kumar, R.; Toor, G.S.; Wang, Z. Desalination: From Ancient to Present and Future. Water 2021, 13, 2222. [Google Scholar] [CrossRef]
  244. Payero, J.O.; Tarkalson, D.D.; Irmak, S.; Davison, D.; Petersen, J.L. Effect of irrigation amounts applied with subsurface drip irrigation on corn evapotranspiration, yield, water use efficiency, and dry matter production in a semiarid climate. Agric. Water Manag. 2008, 95, 895–908. [Google Scholar] [CrossRef]
  245. Comas, L.H.; Trout, T.; DeJonge, K.C.; Zhang, H.; Gleason, S.M. Water productivity under strategic growth stage-based deficit irrigation in maize. Agric. Water Manag. 2018, 212, 433–440. [Google Scholar] [CrossRef]
  246. Olivera-Guerra, L.; Merlin, O.; Er-Raki, S. Irrigation retrieval from Landsat optical/thermal data integrated into a crop water balance model: A case study over winter wheat fields in a semi-arid region. Remote Sens. Environ. 2020, 239, 111627. [Google Scholar] [CrossRef]
  247. Ahmadi, S.H.; Solgi, S.; Sepaskhah, A.R. Quinoa: A super or pseudo-super crop? Evidences from evapotranspiration, root growth, crop coefficients, and water productivity in a hot and semi-arid area under three planting densities. Agric. Water Manag. 2019, 225, 105784. [Google Scholar] [CrossRef]
  248. Chibarabada, T.; Modi, A.; Mabhaudhi, T. Calibration and evaluation of aquacrop for groundnut (Arachis hypogaea) under water deficit conditions. Agric. For. Meteorol. 2019, 281, 107850. [Google Scholar] [CrossRef]
  249. Lu, C.; Zhao, T.; Shi, X.; Cao, S. Ecological restoration by afforestation may increase groundwater depth and create potentially large ecological and water opportunity costs in arid and semiarid China. J. Clean. Prod. 2018, 176, 1213–1222. [Google Scholar] [CrossRef]
  250. Marques, T.V.; Mendes, K.; Mutti, P.; Medeiros, S.; Silva, L.; Perez-Marin, A.M.; Campos, S.; Lúcio, P.S.; Lima, K.; dos Reis, J.; et al. Environmental and biophysical controls of evapotranspiration from Seasonally Dry Tropical Forests (Caatinga) in the Brazilian Semiarid. Agric. For. Meteorol. 2020, 287, 107957. [Google Scholar] [CrossRef]
  251. Ridoutt, B.G.; Sanguansri, P.; Freer, M.; Harper, G.S. Water footprint of livestock: Comparison of six geographically defined beef production systems. Int. J. Life Cycle Assess. 2011, 17, 165–175. [Google Scholar] [CrossRef]
  252. Lipan, L.; García-Tejero, I.F.; Gutiérrez-Gordillo, S.; Demirbaş, N.; Sendra, E.; Hernandez, F.; Zuazo, V.H.D.; Carbonell-Barrachina, A. Enhancing Nut Quality Parameters and Sensory Profiles in Three Almond Cultivars by Different Irrigation Regimes. J. Agric. Food Chem. 2020, 68, 2316–2328. [Google Scholar] [CrossRef]
  253. Keshavarz, M. Agricultural water vulnerability in rural Iran. Water Policy 2015, 18, 586–598. [Google Scholar] [CrossRef]
  254. Liu, M.; Wei, J.; Wang, G.; Wang, F. Water resources stress assessment and risk early warning–a case of Hebei Province China. Ecol. Indic. 2017, 73, 358–368. [Google Scholar] [CrossRef]
  255. Sharma, P.J.; Patel, P.; Jothiprakash, V. Impact of rainfall variability and anthropogenic activities on streamflow changes and water stress conditions across Tapi Basin in India. Sci. Total Environ. 2019, 687, 885–897. [Google Scholar] [CrossRef] [PubMed]
  256. Adane, Z.; Zlotnik, V.A.; Rossman, N.R.; Wang, T.; Nasta, P. Sensitivity of Potential Groundwater Recharge to Projected Climate Change Scenarios: A Site-Specific Study in the Nebraska Sand Hills, USA. Water 2019, 11, 950. [Google Scholar] [CrossRef]
  257. Guermazi, E.; Milano, M.; Reynard, E.; Zairi, M. Impact of climate change and anthropogenic pressure on the groundwater resources in arid environment. Mitig. Adapt. Strat. Glob. Chang. 2018, 24, 73–92. [Google Scholar] [CrossRef]
  258. Domínguez, A.; de Juan, J.; Tarjuelo, J.; Martínez, R.; Martínez-Romero, A. Determination of optimal regulated deficit irrigation strategies for maize in a semi-arid environment. Agric. Water Manag. 2012, 110, 67–77. [Google Scholar] [CrossRef]
  259. Jing, X.; Zhang, S.; Zhang, J.; Wang, Y.; Wang, Y. Assessing efficiency and economic viability of rainwater harvesting systems for meeting non-potable water demands in four climatic zones of China. Resour. Conserv. Recycl. 2017, 126, 74–85. [Google Scholar] [CrossRef]
  260. Karandish, F.; Hoekstra, A.Y. Informing National Food and Water Security Policy through Water Footprint Assessment: The Case of Iran. Water 2017, 9, 831. [Google Scholar] [CrossRef]
  261. Röschel, L.; Graef, F.; Dietrich, O.; Schäfer, M.P.; Haase, D. Individual Local Farmers’ Perceptions of Environmental Change in Tanzania. Water 2018, 10, 525. [Google Scholar] [CrossRef]
  262. Fensholt, R.; Sandholt, I. Derivation of a shortwave infrared water stress index from MODIS near- and shortwave infrared data in a semiarid environment. Remote Sens. Environ. 2003, 87, 111–121. [Google Scholar] [CrossRef]
  263. Cao, S.; Chen, L.; Yu, X. Impact of China’s Grain for Green Project on the landscape of vulnerable arid and semi-arid agricultural regions: A case study in northern Shaanxi Province. J. Appl. Ecol. 2009, 46, 536–543. [Google Scholar] [CrossRef]
  264. Jiang, C.; Zhang, H.; Wang, X.; Feng, Y.; Labzovskii, L. Challenging the land degradation in China’s Loess Plateau: Benefits, limitations, sustainability, and adaptive strategies of soil and water conservation. Ecol. Eng. 2018, 127, 135–150. [Google Scholar] [CrossRef]
  265. Caylor, K.K.; Manfreda, S.; Rodriguez-Iturbe, I. On the coupled geomorphological and ecohydrological organization of river basins. Adv. Water Resour. 2005, 28, 69–86. [Google Scholar] [CrossRef]
  266. Gómez-Giráldez, P.J.; Aguilar, C.; Polo, M.J. Natural vegetation covers as indicators of the soil water content in a semiarid mountainous watershed. Ecol. Indic. 2014, 46, 524–535. [Google Scholar] [CrossRef]
  267. de Figueiredo, J.V.; de Araújo, J.C.; Medeiros, P.H.A.; Costa, A.C. Runoff initiation in a preserved semiarid Caatinga small watershed, Northeastern Brazil. Hydrol. Process. 2016, 30, 2390–2400. [Google Scholar] [CrossRef]
  268. Liu, J.; Zhang, Z.; Zhang, M. Impacts of forest structure on precipitation interception and run-off generation in a semiarid region in northern China. Hydrol. Process. 2018, 32, 2362–2376. [Google Scholar] [CrossRef]
  269. Valdés, M.E.; Talaverano, M.I.; Moreno, D.; Prieto, M.H.; Mancha, L.A.; Uriarte, D.; Vilanova, M. Effect of the timing of water deficit on the must amino acid profile of Tempranillo grapes grown under the semiarid conditions of SW Spain. Food Chem. 2019, 292, 24–31. [Google Scholar] [CrossRef] [PubMed]
  270. Yu, Z.; Lu, C.; Cao, P.; Tian, H.; Hessl, A.; Pederson, N. Earlier leaf-flushing suppressed ecosystem productivity by draining soil water in the Mongolian Plateau. Agric. For. Meteorol. 2018, 250-251, 1–8. [Google Scholar] [CrossRef]
  271. Gu, Y.-J.; Han, C.-L.; Fan, J.-W.; Shi, X.-P.; Kong, M.; Siddique, K.; Zhao, Y.-Y.; Li, F.-M. Alfalfa forage yield, soil water and P availability in response to plastic film mulch and P fertilization in a semiarid environment. Field Crop. Res. 2018, 215, 94–103. [Google Scholar] [CrossRef]
  272. Zettam, A.; Taleb, A.; Sauvage, S.; Boithias, L.; Belaidi, N.; Sánchez-Pérez, J.M. Modelling Hydrology and Sediment Transport in a Semi-Arid and Anthropized Catchment Using the SWAT Model: The Case of the Tafna River (Northwest Algeria). Water 2017, 9, 216. [Google Scholar] [CrossRef]
  273. Marques, M.; Ruiz-Colmenero, M.; Bienes, R.; García-Díaz, A.; Sastre, B. Effects of a Permanent Soil Cover on Water Dynamics and Wine Characteristics in a Steep Vineyard in the Central Spain. Air Soil Water Res. 2020, 13. [Google Scholar] [CrossRef]
  274. Samimi, M.; Mirchi, A.; Moriasi, D.; Ahn, S.; Alian, S.; Taghvaeian, S.; Sheng, Z. Modeling arid/semi-arid irrigated agricultural watersheds with SWAT: Applications, challenges, and solution strategies. J. Hydrol. 2020, 590, 125418. [Google Scholar] [CrossRef]
  275. Guan, K.; Good, S.P.; Caylor, K.K.; Medvigy, D.; Pan, M.; Wood, E.F.; Sato, H.; Biasutti, M.; Chen, M.; Ahlström, A.; et al. Simulated sensitivity of African terrestrial ecosystem photosynthesis to rainfall frequency, intensity, and rainy season length. Environ. Res. Lett. 2017, 13, 025013. [Google Scholar] [CrossRef]
  276. Faramarzi, M.; Abbaspour, K.C.; Adamowicz, W.; Lu, W.; Fennell, J.; Zehnder, A.J.; Goss, G.G. Uncertainty based assessment of dynamic freshwater scarcity in semi-arid watersheds of Alberta, Canada. J. Hydrol. Reg. Stud. 2017, 9, 48–68. [Google Scholar] [CrossRef]
  277. Tolk, A.J.; Howell, A.T. Water use efficiencies of grain sorghum grown in three USA southern Great Plains soils. Agric. Water Manag. 2003, 59, 97–111. [Google Scholar] [CrossRef]
  278. Badr, M.A.; El-Tohamy, W.A.; Zaghloul, A.M. Yield and water use efficiency of potato grown under different irrigation and nitrogen levels in an arid region. Agric. Water Manag. 2012, 110, 9–15. [Google Scholar] [CrossRef]
  279. Yan, S.; Wu, Y.; Fan, J.; Zhang, F.; Qiang, S.; Zheng, J.; Xiang, Y.; Guo, J.; Zou, H. Effects of water and fertilizer management on grain filling characteristics, grain weight and productivity of drip-fertigated winter wheat. Agric. Water Manag. 2018, 213, 983–995. [Google Scholar] [CrossRef]
  280. Small, H. Co-citation in the scientific literature: A new measure of the relationship between two documents. J. Am. Soc. Inf. Sci. 1973, 24, 265–269. [Google Scholar] [CrossRef]
  281. Yang, L.; Han, L.; Liu, N. A new approach to journal co-citation matrix construction based on the number of co-cited articles in journals. Scientometrics 2019, 120, 507–517. [Google Scholar] [CrossRef]
  282. Dzikowski, P. A bibliometric analysis of born global firms. J. Bus. Res. 2018, 85, 281–294. [Google Scholar] [CrossRef]
  283. Qin, Y.; Mueller, N.D.; Siebert, S.; Jackson, R.B.; AghaKouchak, A.; Zimmerman, J.B.; Tong, D.; Hong, C.; Davis, S.J. Flexibility and intensity of global water use. Nat. Sustain. 2019, 2, 515–523. [Google Scholar] [CrossRef]
  284. Whitmee, S.; Haines, A.; Beyrer, C.; Boltz, F.; Capon, A.G.; de Souza Dias, B.F.; Ezeh, A.; Frumkin, H.; Gong, P.; Head, P.; et al. Safeguarding human health in the Anthropocene epoch: Report of The Rockefeller Foundation—Lancet Commission on planetary health. Lancet 2015, 386, 1973–2028, Erratum in Lancet 2015, 386, 1944. [Google Scholar] [CrossRef]
  285. Wada, Y.; van Beek, L.P.H.; Viviroli, D.; Dürr, H.H.; Weingartner, R.; Bierkens, M.F.P. Global monthly water stress: 2. Water demand and severity of water stress. Water Resour. Res. 2011, 47. [Google Scholar] [CrossRef]
  286. Huang, Z.; Hejazi, M.; Li, X.; Tang, Q.; Vernon, C.; Leng, G.; Liu, Y.; Döll, P.; Eisner, S.; Gerten, D.; et al. Reconstruction of global gridded monthly sectoral water withdrawals for 1971–2010 and analysis of their spatiotemporal patterns. Hydrol. Earth Syst. Sci. 2018, 22, 2117–2133. [Google Scholar] [CrossRef]
  287. Patanè, C.; Tringali, S.; Sortino, O. Effects of deficit irrigation on biomass, yield, water productivity and fruit quality of processing tomato under semi-arid Mediterranean climate conditions. Sci. Hortic. 2011, 129, 590–596. [Google Scholar] [CrossRef]
  288. Scanlon, B.R.; Zhang, Z.; Rateb, A.; Sun, A.; Wiese, D.; Save, H.; Beaudoing, H.; Lo, M.H.; Müller-Schmied, H.; Döll, P.; et al. Tracking Seasonal Fluctuations in Land Water Storage Using Global Models and GRACE Satellites. Geophys. Res. Lett. 2019, 46, 5254–5264. [Google Scholar] [CrossRef]
  289. Cooley, S.W.; Ryan, J.C.; Smith, L.C. Human alteration of global surface water storage variability. Nat. 2021, 591, 78–81. [Google Scholar] [CrossRef]
  290. Singh, P.K.; Chudasama, H. Pathways for climate change adaptations in arid and semi-arid regions. J. Clean. Prod. 2020, 284, 124744. [Google Scholar] [CrossRef]
  291. Li, H.; Mei, X.; Wang, J.; Huang, F.; Hao, W.; Li, B. Drip fertigation significantly increased crop yield, water productivity and nitrogen use efficiency with respect to traditional irrigation and fertilization practices: A meta-analysis in China. Agric. Water Manag. 2020, 244, 106534. [Google Scholar] [CrossRef]
  292. Karimidastenaei, Z.; Klöve, B.; Sadegh, M.; Haghighi, A.T. Polar Ice as an Unconventional Water Resource: Opportunities and Challenges. Water 2021, 13, 3220. [Google Scholar] [CrossRef]
  293. Di Martino, M.; Avraamidou, S.; Cook, J.; Pistikopoulos, E.N. An optimization framework for the design of reverse osmosis desalination plants under food-energy-water nexus considerations. Desalination 2021, 503, 114937. [Google Scholar] [CrossRef]
  294. Makonyo, M.; Msabi, M.M. Identification of groundwater potential recharge zones using GIS-based multi-criteria decision analysis: A case study of semi-arid midlands Manyara fractured aquifer, North-Eastern Tanzania. Remote Sens. Appl. Soc. Environ. 2021, 23, 100544. [Google Scholar] [CrossRef]
  295. Dortaj, A.; Maghsoudy, S.; Ardejani, F.D.; Eskandari, Z. A hybrid multi-criteria decision making method for site selection of subsurface dams in semi-arid region of Iran. Groundw. Sustain. Dev. 2019, 10, 100284. [Google Scholar] [CrossRef]
  296. Naghibi, S.A.; Hashemi, H.; Berndtsson, R.; Lee, S. Application of extreme gradient boosting and parallel random forest algorithms for assessing groundwater spring potential using DEM-derived factors. J. Hydrol. 2020, 589, 125197. [Google Scholar] [CrossRef]
  297. Khanpae, M.; Karami, E.; Maleksaeidi, H.; Keshavarz, M. Farmers’ attitude towards using treated wastewater for irrigation: The question of sustainability. J. Clean. Prod. 2019, 243, 118541. [Google Scholar] [CrossRef]
Figure 1. Outline of the research methodology.
Figure 1. Outline of the research methodology.
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Figure 2. Annual scientific production on water scarcity in semi-arid areas.
Figure 2. Annual scientific production on water scarcity in semi-arid areas.
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Figure 3. Distribution of scientific production according to the type of document.
Figure 3. Distribution of scientific production according to the type of document.
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Figure 4. Distribution of scientific production by country.
Figure 4. Distribution of scientific production by country.
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Figure 5. Network of co-occurrences of author keywords. Cluster 1 (red colour), cluster 2 (green colour), cluster 3 (blue colour), cluster 4 (yellow colour), cluster 5 (purple colour), cluster 6 (light blue colour), cluster 7 (orange colour).
Figure 5. Network of co-occurrences of author keywords. Cluster 1 (red colour), cluster 2 (green colour), cluster 3 (blue colour), cluster 4 (yellow colour), cluster 5 (purple colour), cluster 6 (light blue colour), cluster 7 (orange colour).
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Figure 6. Sankey diagram showing the thematic evolution of water scarcity in semi-arid zones.
Figure 6. Sankey diagram showing the thematic evolution of water scarcity in semi-arid zones.
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Figure 7. Network of co-citation of journals. Cluster 1 (red colour), cluster 2 (green colour), cluster 3 (blue colour), cluster 4 (yellow colour), cluster 5 (purple colour), cluster 6 (light blue colour).
Figure 7. Network of co-citation of journals. Cluster 1 (red colour), cluster 2 (green colour), cluster 3 (blue colour), cluster 4 (yellow colour), cluster 5 (purple colour), cluster 6 (light blue colour).
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Table 1. Most cited documents.
Table 1. Most cited documents.
RankAutorArticleJournalCIT 1
1Allen R.G., et al [131]Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC) - ModelJournal of Irrigation and Drainage Engineering1095
2Feng X., et al [140]Revegetation in China’s Loess Plateau is approaching sustainable water resource limitsNature Climate Change663
3Viviroli D., et al [137]Mountains of the world, water towers for humanity: Typology, mapping, and global significanceWater Resources Research617
4Deng X.-P., et al [135]Improving agricultural water use efficiency in arid and semiarid areas of ChinaAgricultural Water Management573
5Hughes L. [119]Climate change and Australia: Trends, projections, and impactsAustral Ecology538
6Feng S., Fu Q. [27]Expansion of global drylands under a warming climateAtmospheric Chemistry and Physics458
7Wand S.J.E., et al [215]Responses of wild C4 and C3 grass (Poaceae) species to elevated atmospheric CO2 concentration: A meta-analytic test of current theories and perceptionsGlobal Change Biology455
8Liu W., et al [120]Predominant role of water in regulating soil and microbial respiration and their responses to climate change in a semiarid grasslandGlobal Change Biology412
9Cao S., et al [138]Excessive reliance on afforestation in China’s arid and semi-arid regions: Lessons in ecological restorationEarth-Science Reviews387
10Wallace J.S. [136]Increasing agricultural water use efficiency to meet future food productionAgriculture, Ecosystems and Environment387
1 CIT: Citations.
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Morante-Carballo, F.; Montalván-Burbano, N.; Quiñonez-Barzola, X.; Jaya-Montalvo, M.; Carrión-Mero, P. What Do We Know about Water Scarcity in Semi-Arid Zones? A Global Analysis and Research Trends. Water 2022, 14, 2685. https://doi.org/10.3390/w14172685

AMA Style

Morante-Carballo F, Montalván-Burbano N, Quiñonez-Barzola X, Jaya-Montalvo M, Carrión-Mero P. What Do We Know about Water Scarcity in Semi-Arid Zones? A Global Analysis and Research Trends. Water. 2022; 14(17):2685. https://doi.org/10.3390/w14172685

Chicago/Turabian Style

Morante-Carballo, Fernando, Néstor Montalván-Burbano, Ximena Quiñonez-Barzola, María Jaya-Montalvo, and Paúl Carrión-Mero. 2022. "What Do We Know about Water Scarcity in Semi-Arid Zones? A Global Analysis and Research Trends" Water 14, no. 17: 2685. https://doi.org/10.3390/w14172685

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