Drought and Water Scarcity: Monitoring, Modelling and Mitigation

A special issue of Hydrology (ISSN 2306-5338). This special issue belongs to the section "Water Resources and Risk Management".

Deadline for manuscript submissions: closed (15 February 2023) | Viewed by 40215

Special Issue Editor


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Guest Editor
Department of Natural Resources Management and Agricultural Engineering, Agricultural University of Athens, Iera Odos 75, Athens, Greece
Interests: irrigation; hydrology; water resources

Special Issue Information

Dear Colleagues,

It is well known that water scarcity and droughts constitute a specific scientific field of hydrology and water resources, which is currently receiving significant attention mainly due to climate change, among other reasons. Similarly, at present, technological and scientific advances, such as modelling, integrated water resources management systems, geoinformatics, remote sensing and GIS, as well as computational developments, show steadily increasing reliability and new systems possibilities occur every year with continuously improving capabilities.

The problem of water scarcity affects several parts of the world. Specifically, in semi-arid and arid regions, such as the Mediterranean region, this problem becomes of major concern. Indeed, water scarcity currently consists of the adverse result of ineffective water resources management and policies, as well as the availability of insufficient water in these regions. The ineffective water resources management and the lack of water availability analysis, along with the presence of prolonged drought periods caused by increased climate variability and possibly climate change, as well as the water overuse and misuse and the addition of new water demands lead to water scarcity. As already mentioned, extended drought periods is one of the factors and components leading to water scarcity. Indeed, drought is a natural phenomenon recurring at a regional scale throughout history. Drought is also considered as one of the major natural hazards with significant impact to environment, society, agriculture and economy. It is recognized that there is no universally accepted definition of drought, since there is a wide variety of sectors affected by drought and due to its diverse spatial and temporal distribution. Moreover, there are several special drought features, such as its non-structural effects, or its slow onset, or even the lack of a universal consideration of drought as a hazard. In addition, there are severe impacts of droughts, which are also indirect and not easily measured. This is why there are so many difficulties in drought assessment and response, which may cause delays or lack of progress on drought preparedness plans, or even mitigation measures.

The aim of this Special Issue is to foster scientific and technological advances in the field of water scarcity and droughts for a range of practical applications and research investigations.

Such contributions can be focused on various aspects, including, but not limited to, active and passive remote sensing data and methods (e.g., satellites, weather radar, SAR, UAV, sensors), applications in drought hazards affecting agriculture, water scarcity simulation and modeling, decision support systems, climate change: impact-mitigation-adaptation, agroclimatic classification, software tool development for data collection and processing, as well as their applications.

Prof. Nicholas Dercas
Guest Editor

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Keywords

  • Evapotranspiration concepts and estimation
  • Advances in features of the hydrological cycle
  • Frequency Analysis of droughts
  • Geostatistical Analysis of drought indices
  • Remote Sensing in hydrometeorological analysis
  • Hydrological Forecasting
  • Demand Forecasting
  • Water Resources Management Modelling
  • Drought forecasting and Drought Early Warning Systems (DEWS)
  • Drought Assessment
  • Water Scarcity Management
  • Rain Enhancement Framework
  • Rainwater harvesting Climate change impact assessment of hydrometeorological variables
  • Adaptation and Vulnerability of Climate Change
  • The role of ET in Agricultural Drought
  • Water Balance Estimation of ET rates Remote sensing for drought hazards in agriculture
  • Sensors systems
  • ICT in water scarcity and drought.
  • Decision Support System in water scarcity and drought
  • Agroclimatic classification of vulnerable agroecosystems
  • Water accounting

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Published Papers (12 papers)

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Editorial

Jump to: Research, Other

4 pages, 175 KiB  
Editorial
Editorial to the Special Issue “Drought and Water Scarcity: Monitoring, Modelling and Mitigation”
by Nicholas Dercas
Hydrology 2023, 10(6), 134; https://doi.org/10.3390/hydrology10060134 - 19 Jun 2023
Viewed by 2242
Abstract
Drought is considered to be among the major natural hazards faced by human society, with significant impacts on environment, society, agriculture and economy stemming from its consequences [...] Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)

Research

Jump to: Editorial, Other

17 pages, 3259 KiB  
Article
Understanding Dry and Wet Conditions in the Vietnamese Mekong Delta Using Multiple Drought Indices: A Case Study in Ca Mau Province
by Huynh Vuong Thu Minh, Pankaj Kumar, Tran Van Ty, Dinh Van Duy, Tran Gia Han, Kim Lavane and Ram Avtar
Hydrology 2022, 9(12), 213; https://doi.org/10.3390/hydrology9120213 - 28 Nov 2022
Cited by 11 | Viewed by 2471
Abstract
Globally, hydrometeorological hazards have large impacts to agriculture output, as well as human well-being. With climate change derived increasing frequency of extreme weather conditions, the situation has becoming more severe. This study strives to evaluate both dry and wet conditions in the Vietnamese [...] Read more.
Globally, hydrometeorological hazards have large impacts to agriculture output, as well as human well-being. With climate change derived increasing frequency of extreme weather conditions, the situation has becoming more severe. This study strives to evaluate both dry and wet conditions in the Vietnamese Mekong Delta (VMD), also known as the rice basket of the Southeast Asian region. Different meteorological parameters from the last three decades were used to develop drought indices for Ca Mau province to investigate their impact on agricultural output. For this purpose, the standard precipitation index (SPI), the agricultural rainfall index (ARI), and the standardized precipitation evapotranspiration index (SPEI) were used in this study. Results highlight that Ca Mau has a peculiar characteristic of the whole VMD in that dry periods persist well into the wet season extending the duration of drought events. The role of storms, including tropical storms, and El Niño cannot be ignored as extreme events, which both change humidity, as well as rainfall. It is also found that the drought situation has caused significant damage to both rice and shrimp outputs in almost 6000 hectares. The assessment contributes to an improved understanding of the pattern of unpredictable rainfall and meteorological anomaly conditions in Ca Mau. The findings of this paper are important for both policymakers and practitioners in designing more robust plans for water resource management. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
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16 pages, 2754 KiB  
Article
Growing Crops in Arid, Drought-Prone Environments: Adaptation and Mitigation
by Nicholas P. Sisto, Sergei Severinov and Gilberto Aboites Manrique
Hydrology 2022, 9(8), 129; https://doi.org/10.3390/hydrology9080129 - 22 Jul 2022
Cited by 4 | Viewed by 2051
Abstract
Drought poses significant risks to society, in particular irrigated-crop production, which accounts for a large share of global freshwater use. Given its key role in the production of food, feed and fiber crops, there exists a need for policy measures to prevent and [...] Read more.
Drought poses significant risks to society, in particular irrigated-crop production, which accounts for a large share of global freshwater use. Given its key role in the production of food, feed and fiber crops, there exists a need for policy measures to prevent and mitigate the impacts of drought on irrigated agriculture. This paper proposes that the design of drought policy should take into account actual farmer behavior in response to water scarcity. To this end, we offer a detailed analysis of land allocation and crop-choice decisions over time in an irrigation district located in the dry plains of Northern Mexico. We find that farmers systematically change their crop mix in response to water availability. In particular, in times of drought, irrigation water flows to higher-yield and higher-price crops (which also require more intense irrigation) to the detriment of less water-demanding (but lower value) crops. Farmers use water with the goal of earning a living—economizing on water per se has no relevance in that context. Policies that do not explicitly recognize this may result in ineffective, inefficient and/or unfair outcomes. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
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14 pages, 4296 KiB  
Article
Effect of Rainfall Regime on Rainwater Harvesting Tank Sizing for Greenhouse Irrigation Use
by Paraskevi A. Londra, Panagiota Gkolfinopoulou, Anastasia Mponou and Achilleas T. Theocharis
Hydrology 2022, 9(7), 122; https://doi.org/10.3390/hydrology9070122 - 7 Jul 2022
Cited by 3 | Viewed by 1994
Abstract
The use of rainwater harvesting tanks to supply human water needs is an old and sustainable practice. In the case of covering irrigation demand in greenhouse agriculture, the potential is huge. Still, the relative research worldwide is low, while it is nearly absent [...] Read more.
The use of rainwater harvesting tanks to supply human water needs is an old and sustainable practice. In the case of covering irrigation demand in greenhouse agriculture, the potential is huge. Still, the relative research worldwide is low, while it is nearly absent in Greece. In this study, the rainwater harvesting tank size for irrigation use of greenhouse tomato cultivation was investigated by applying a daily water balance model in three regions of Crete Island (Greece) with significant greenhouse areas. Daily rainfall data from three representative rainfall stations of the study areas characterized by different rainfall regime for a 12-year time series were used. Additionally, the daily irrigation water needs for a tomato crop during an 8-month cultivation period were used. The greenhouse roof was defined as catchment area of the rainwater harvesting system and greenhouse areas of 1000, 5000 and 10,000 m2 were studied. In all areas examined, a tank of 30–100 m3 per 1000 m2 of greenhouse area could reach approximately 80–90% reliability. Higher values of reliability (reaching 100%) could be achieved mainly with covered tanks. Tank size for 100% reliability in covered tanks, ranged from 200 m3 (per 1000 m2 of greenhouse area) in the study area with high mean annual rainfall depth (974.24 mm) and moderate mean longest dry period (87.67 days), to 276 m3 (per 1000 m2 of greenhouse area) in the study area with relatively low mean annual rainfall depth (524.12 mm) and high mean longest dry period (117.42 days). For uncovered tanks, a 100% reliability value could be reached only with a tank size of 520 m3 (per 1000 m2 of greenhouse area) in the study area with high mean annual rainfall depth and moderate mean longest dry period. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
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15 pages, 2437 KiB  
Article
A Procedure for Estimating Drought Duration and Magnitude at the Uniform Cutoff Level of Streamflow: A Case of the Weekly Flows of Canadian Rivers
by Tribeni C. Sharma and Umed S. Panu
Hydrology 2022, 9(6), 109; https://doi.org/10.3390/hydrology9060109 - 16 Jun 2022
Cited by 1 | Viewed by 2287
Abstract
At times, hydrological drought is defined using Q90 or Q95 (90% or 95% flows equaling or exceeding) or even at higher levels, such as Q75 as the cutoff level regardless of their seasonal variation (i.e., truncation at the uniform flow level). In the [...] Read more.
At times, hydrological drought is defined using Q90 or Q95 (90% or 95% flows equaling or exceeding) or even at higher levels, such as Q75 as the cutoff level regardless of their seasonal variation (i.e., truncation at the uniform flow level). In the past, the estimation of drought length and magnitude at the aforesaid uniform cutoff levels of flow has been a challenging issue. A procedure is presented to first estimate the drought magnitude (M), which then forms the basis for estimating the drought duration or length (L). The drought magnitude (M) and the length of the critical period (Lcr) are estimated using the concept of behavior analysis prevalent in the hydrologic design of reservoirs. This information is used for estimating the drought length (LT-e′, the estimated value of drought length for the return period of T weeks) involving a Markov chain model on the standardized weekly flow sequences. A weighted average of Lcr and LT-e′ (=0.60 Lcr + 0.40 LT-e′) results in the estimate of drought length, which is compatible to the observed counterpart. The performance of the procedure to estimate drought length was found to be satisfactory up to the truncation level of Q75, whereas the estimation of drought magnitude was rated as good. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
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20 pages, 2686 KiB  
Article
AquaCrop Simulation of Winter Wheat under Different N Management Practices
by Nicholas Dercas, Nicolas R. Dalezios, Stamatis Stamatiadis, Eleftherios Evangelou, Antonios Glampedakis, Georgios Mantonanakis and Nicholaos Tserlikakis
Hydrology 2022, 9(4), 56; https://doi.org/10.3390/hydrology9040056 - 29 Mar 2022
Cited by 3 | Viewed by 3314
Abstract
AquaCrop is a well-known water-oriented crop model. The model has been often used to simulate various crops and the water balance in the field under different irrigation treatments, but studies that relate AquaCrop to fertilization are rare. In this study, the ability of [...] Read more.
AquaCrop is a well-known water-oriented crop model. The model has been often used to simulate various crops and the water balance in the field under different irrigation treatments, but studies that relate AquaCrop to fertilization are rare. In this study, the ability of this model to simulate yield and the water balance parameters was investigated in a wheat field under different nitrogen management practices. During the 2015–2016 and 2016–2017 growing seasons, meteorological data were provided from a nearby meteorological station, and the evolution of soil water content and final yields were recorded. The model showed a very good performance at simulating the soil water content evolution in the root zone. Notwithstanding its simplicity, AquaCrop based on a semi-quantitative approach for fertility performed well at the field level for the final yield estimation under different nitrogen treatments and field topography variation. Although the correlation coefficient between simulated and measured final yields was high, increased values of variations were observed in the various zones of this experimental field (−50% to +140%). The model appears to be an efficient tool for evaluating and improving the management practices at the field level. The experiments were conducted in Thessaly, which is the largest plain and the main agricultural area of Greece. Thessaly, however, has a strong negative water balance, which has led to a strong decrease in the level of the aquifer and, at the same time, to sea intrusion. There is also a significant risk of contamination of the groundwater aquifer due to increased use of agrochemicals. This analysis is particularly important for Thessaly due to the need for improvement of agricultural practices in this area, to decrease the pressure of agricultural activities on natural resources (soil, water) and reverse the consequences of current management. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
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14 pages, 4102 KiB  
Article
Spatiotemporal Variability of Intensity–Duration–Frequency (IDF) Curves in Arid Areas: Wadi AL-Lith, Saudi Arabia as a Case Study
by Ibrahim H. Elsebaie, Mohamed El Alfy and Atef Qasem Kawara
Hydrology 2022, 9(1), 6; https://doi.org/10.3390/hydrology9010006 - 27 Dec 2021
Cited by 10 | Viewed by 4023
Abstract
In arid areas, flashflood water management is a major concern due to arid climate ambiguity. The examining and derivation of intensity–duration–frequency (IDF) curves in an urban arid area under a variety of terrain patterns and climatic changes is anticipated. Several flood events have [...] Read more.
In arid areas, flashflood water management is a major concern due to arid climate ambiguity. The examining and derivation of intensity–duration–frequency (IDF) curves in an urban arid area under a variety of terrain patterns and climatic changes is anticipated. Several flood events have been reported in the Al-Lith region of western Saudi Arabia that took away many lives and caused disruption in services and trade. To find and examine the extremities and IDF curves, daily rainfall data from 1966 to 2018 is used. The IDF curves are created for a variety of return periods and climate scenarios in three terrain variabilities. This research examines various distributions to estimate the maximum rainfall for several metrological stations with varying return periods and terrain conditions. Three main zones are identified based on ground elevation variability and IDF distributions from upstream in the eastern mountainous area to downstream in the western coastal area. These IDF curves can be used to identify vulnerable hotspot areas in arid areas such as the Wadi AL-Lith, and flood mitigation steps can be suggested to minimize flood risk. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
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16 pages, 7238 KiB  
Article
Spatial–Temporal Patterns of Historical, Near-Term, and Projected Drought in the Conterminous United States
by Susan M. Kotikot and Olufemi A. Omitaomu
Hydrology 2021, 8(3), 136; https://doi.org/10.3390/hydrology8030136 - 8 Sep 2021
Cited by 1 | Viewed by 2274
Abstract
Major droughts in the United States have heavily impacted the hydrologic system, negatively effecting energy and food production. Improved understanding of historical drought is critical for accurate forecasts. Data from global climate models (GCMs), commonly used to assess drought, cannot effectively evaluate local [...] Read more.
Major droughts in the United States have heavily impacted the hydrologic system, negatively effecting energy and food production. Improved understanding of historical drought is critical for accurate forecasts. Data from global climate models (GCMs), commonly used to assess drought, cannot effectively evaluate local patterns because of their low spatial scale. This research leverages downscaled (~4 km grid spacing) temperature and precipitation estimates from nine GCMs’ data under the business-as-usual scenario (Representative Concentration Pathway 8.5) to examine drought patterns. Drought severity is estimated using the Palmer Drought Severity Index (PDSI) with the Thornthwaite evapotranspiration method. The specific objectives were (1) To reproduce historical (1966–2005) drought and calculate near-term to future (2011–2050) drought patterns over the conterminous USA. (2) To uncover the local variability of spatial drought patterns in California between 2012 and 2018 using a network-based approach. Our estimates of land proportions affected by drought agree with the known historical drought events of the mid-1960s, late 1970s to early 1980s, early 2000s, and between 2012 and 2015. Network analysis showed heterogeneity in spatial drought patterns in California, indicating local variability of drought occurrence. The high spatial scale at which the analysis was performed allowed us to uncover significant local differences in drought patterns. This is critical for highlighting possible weak systems that could inform adaptation strategies such as in the energy and agricultural sectors. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
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16 pages, 4575 KiB  
Article
Reliability Analysis of Rainwater Harvesting Tanks for Irrigation Use in Greenhouse Agriculture
by Paraskevi A. Londra, Ioannis-Eleftherios Kotsatos, Nikolaos Theotokatos, Achilleas T. Theocharis and Nicholas Dercas
Hydrology 2021, 8(3), 132; https://doi.org/10.3390/hydrology8030132 - 2 Sep 2021
Cited by 9 | Viewed by 2556
Abstract
Rainwater harvesting is an ancient water management practice that has been used to cover potable and non-potable water needs. In recent years, this practice is adopted as a promising alternative and sustainable source of water to meet irrigation needs in agriculture in arid [...] Read more.
Rainwater harvesting is an ancient water management practice that has been used to cover potable and non-potable water needs. In recent years, this practice is adopted as a promising alternative and sustainable source of water to meet irrigation needs in agriculture in arid and semi-arid regions. In the present study, a daily water balance model was applied to investigate the size of rainwater tanks for irrigation use in greenhouse begonia and tomato cultivation in two regions of Greece with significant greenhouse areas. For the application of the water balance model, daily rainfall depth values of a 12-year time series (2008–2020) from representative rainfall stations of the study areas were used, as well as the daily water needs of the crops. The greenhouse roof was assumed to be the water collection area of the rainwater harvesting system with values ranging from 1000 to 10,000 m2. The analysis of the results showed that in the case of the begonia crop, the covered tanks ranged from 100 to 200 m3 per 1000 m2 greenhouse area with a reliability coefficient that ranged from 65 to 72%, respectively, to meet the water needs of plants. Further increase of the reliability coefficient was carried out with disproportionately large volumes of tanks. In the case of the tomato crop, covered tank volumes ranged from 100 to 290 m3 per 1000 m2 of greenhouse area, and had a reliability coefficient of 90% to 100%, respectively, while uncovered tanks had a maximum reliability coefficient of 91% for a critical tank volume of 177 m3 per 1000 m2 of greenhouse area and decreased for any further increase of tank volume. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
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26 pages, 7446 KiB  
Article
A Global-Scale Investigation of Stochastic Similarities in Marginal Distribution and Dependence Structure of Key Hydrological-Cycle Processes
by Panayiotis Dimitriadis, Demetris Koutsoyiannis, Theano Iliopoulou and Panos Papanicolaou
Hydrology 2021, 8(2), 59; https://doi.org/10.3390/hydrology8020059 - 31 Mar 2021
Cited by 90 | Viewed by 6295
Abstract
To seek stochastic analogies in key processes related to the hydrological cycle, an extended collection of several billions of data values from hundred thousands of worldwide stations is used in this work. The examined processes are the near-surface hourly temperature, dew point, relative [...] Read more.
To seek stochastic analogies in key processes related to the hydrological cycle, an extended collection of several billions of data values from hundred thousands of worldwide stations is used in this work. The examined processes are the near-surface hourly temperature, dew point, relative humidity, sea level pressure, and atmospheric wind speed, as well as the hourly/daily streamflow and precipitation. Through the use of robust stochastic metrics such as the K-moments and a second-order climacogram (i.e., variance of the averaged process vs. scale), it is found that several stochastic similarities exist in both the marginal structure, in terms of the first four moments, and in the second-order dependence structure. Stochastic similarities are also detected among the examined processes, forming a specific hierarchy among their marginal and dependence structures, similar to the one in the hydrological cycle. Finally, similarities are also traced to the isotropic and nearly Gaussian turbulence, as analyzed through extensive lab recordings of grid turbulence and of turbulent buoyant jet along the axis, which resembles the turbulent shear and buoyant regime that dominates and drives the hydrological-cycle processes in the boundary layer. The results are found to be consistent with other studies in literature such as solar radiation, ocean waves, and evaporation, and they can be also justified by the principle of maximum entropy. Therefore, they allow for the development of a universal stochastic view of the hydrological-cycle under the Hurst–Kolmogorov dynamics, with marginal structures extending from nearly Gaussian to Pareto-type tail behavior, and with dependence structures exhibiting roughness (fractal) behavior at small scales, long-term persistence at large scales, and a transient behavior at intermediate scales. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
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21 pages, 4131 KiB  
Article
Quantitative Classification of Desertification Severity for Degraded Aquifer Based on Remotely Sensed Drought Assessment
by Pantelis Sidiropoulos, Nicolas R. Dalezios, Athanasios Loukas, Nikitas Mylopoulos, Marios Spiliotopoulos, Ioannis N. Faraslis, Nikos Alpanakis and Stavros Sakellariou
Hydrology 2021, 8(1), 47; https://doi.org/10.3390/hydrology8010047 - 17 Mar 2021
Cited by 24 | Viewed by 3652
Abstract
Natural and anthropogenic causes jointly lead to land degradation and eventually to desertification, which occurs in arid, semiarid, and dry subhumid areas. Furthermore, extended drought periods may cause soil exposure and erosion, land degradation and, finally, desertification. Several climatic, geological, hydrological, physiographic, biological, [...] Read more.
Natural and anthropogenic causes jointly lead to land degradation and eventually to desertification, which occurs in arid, semiarid, and dry subhumid areas. Furthermore, extended drought periods may cause soil exposure and erosion, land degradation and, finally, desertification. Several climatic, geological, hydrological, physiographic, biological, as well as human factors contribute to desertification. This paper presents a methodological procedure for the quantitative classification of desertification severity over a watershed with degraded groundwater resources. It starts with drought assessment using Standardized Precipitation Index (SPI), based on gridded satellite-based precipitation data (taken from the CHIRPS database), then erosion potential is assessed through modeling. The groundwater levels are estimated with the use of a simulation model and the groundwater quality components of desertification, based on scattered data, are interpolated with the use of geostatistical tools. Finally, the combination of the desertification severity components leads to the final mapping of desertification severity classification. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
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Other

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14 pages, 3012 KiB  
Technical Note
Incorporating aSPI and eRDI in Drought Indices Calculator (DrinC) Software for Agricultural Drought Characterisation and Monitoring
by Dimitris Tigkas, Harris Vangelis, Nikolaos Proutsos and George Tsakiris
Hydrology 2022, 9(6), 100; https://doi.org/10.3390/hydrology9060100 - 5 Jun 2022
Cited by 17 | Viewed by 4712
Abstract
The agricultural sector is vulnerable to extreme phenomena such as droughts, particularly in arid and semi-arid environments and in regions where water infrastructure is limited. Devising preparedness plans, including means for efficient monitoring and timely identification of drought events, is essential for informed [...] Read more.
The agricultural sector is vulnerable to extreme phenomena such as droughts, particularly in arid and semi-arid environments and in regions where water infrastructure is limited. Devising preparedness plans, including means for efficient monitoring and timely identification of drought events, is essential for informed decision making on drought mitigation and water management, especially for the water-dependant agricultural sector. This paper presents the incorporation of two new drought indices, designed for agricultural drought identification, in Drought Indices Calculator (DrinC) software. These indices, namely the Agricultural Standardized Precipitation Index (aSPI) and the Effective Reconnaissance Drought Index (eRDI), require commonly available meteorological data, while they employ the concept of effective precipitation, taking into account the amount of water that contributes productively to plant development. The design principles of DrinC software leading to the proper use of the indices for agricultural drought assessment, including the selection of appropriate reference periods, calculation time steps and other related issues, are presented and discussed. The incorporation of aSPI and eRDI in DrinC enhances the applicability of the software towards timely agricultural drought characterisation and analysis, through a straightforward and comprehensible approach, particularly useful for operational purposes. Full article
(This article belongs to the Special Issue Drought and Water Scarcity: Monitoring, Modelling and Mitigation)
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