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Article

Delineation of a Groundwater Potential Zone Map for the Kızılırmak Delta by Using Remote-Sensing-Based Geospatial and Analytical Hierarchy Processes

by
Neslihan Beden
1,*,
Nazire Göksu Soydan-Oksal
2,*,
Sema Arıman
1 and
Hayatullah Ahmadzai
3
1
Department of Meteorological Engineering, Özdemir Bayraktar Faculty of Aeronautics and Astronautics, University of Samsun, 55000 Samsun, Turkey
2
Department of Civil Engineering, Faculty of Engineering, Mersin University, 33000 Mersin, Turkey
3
Department of Environmental Engineering, Faculty of Engineering, Ondokuz Mayıs University, 55000 Samsun, Turkey
*
Authors to whom correspondence should be addressed.
Sustainability 2023, 15(14), 10964; https://doi.org/10.3390/su151410964
Submission received: 25 April 2023 / Revised: 4 July 2023 / Accepted: 6 July 2023 / Published: 13 July 2023
(This article belongs to the Section Sustainable Water Management)
Browse Figures
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Abstract

:
Locating prospective groundwater recharge zones is essential for managing and planning groundwater resources. Therefore, spatial modeling of groundwater distribution is a significant undertaking that would aid groundwater’s subsequent conservation and management. The current study employs geographic information systems (GIS) and analytical hierarchy process (AHP) based on multi-criteria analysis to identify groundwater potential zones (GPZ). The AHP technique was utilized to analyze and generate the geo-environmental factor parameters, which included drainage density, lineament density, precipitation, slope, soil texture, land use/land cover, groundwater level, and geology. Each factor is weighted according to its characteristics and effects on water potential in this process. Finally, the weighted overlay method was applied in a GIS environment to gather the weighted variables and locate the map of the GPZ. The proposed GPZ map is divided into four different groundwater potential zones: poor, moderate, high, and very high. Consequently, according to the results, 38% of the basin has very high groundwater potential, 19% has high potential, 39% has moderate potential, and 4% has poor potential from the spatial distribution of the potential regions. Therefore, the study’s conclusions can be used to sustain groundwater resources by identifying areas with high groundwater potential.

1. Introduction

One of the most crucial elements for life on Earth is water. Groundwater is defined as water that is located in the saturated zone between the pore and cracks of the soil and rocks under the ground, which is formed by the infiltration of surface and precipitation water through the soil to under the ground [1]. Groundwater, one of the planet’s primary natural sources of clean water, accounts for 34% of the world’s freshwater resources [2]. However, groundwater formation depends on climatic, geological, hydrological, ecological, and physiographic factors and their interaction rather than unexpected events [3].
Groundwater has been mismanaged in many areas around the world due to poor government management, resulting in seawater intrusion or salinity of groundwater, landfill leachate to groundwater, agricultural wastewater flows, high pump discharges for various uses, land degradation, water table decline, high pumping costs, adverse effects on groundwater-dependent ecosystems, and a variety of other environmental issues [4,5,6,7,8,9,10,11,12]. In any area, as a result, it affects various sectors, including water resources in that area [13]. On the other hand, due to the factors caused by climate change, there is a significant decrease in the number of surface water resources. This situation has increased the tendency of using groundwater in semi-arid and arid regions [14].
The change or differentiation of the climate situation, which enables the determination of groundwater potential even in physically inaccessible areas, results from climate change [15,16,17,18]. Climate change can impact the quantity of soil infiltration, deeper penetration, and groundwater recharge through the hydrological cycle. Furthermore, rising temperatures increase evaporative demand over land and limit water availability to freshen groundwater [19]. Groundwater, which is a reliable water source in terms of water quality, is a preferable source for providing a regular water supply. Groundwater passes underground from areas with a high steepness and a low degree of slope to various water bodies such as streams, seas, and lakes [17]. Thus, the availability of groundwater in each area is difficult to discern and limited. Determining groundwater potential zones (GPZ) is an important topic in numerous regions of the world.
As a consequence, water conservation plans must be designed and updated to ensure the continued usage of groundwater [20]. In addition, an accurate groundwater recharge estimation is required to utilize groundwater resources properly. In this regard, mapping the groundwater potential using yield data, including extraction volume and groundwater velocity, is an essential preliminary study [21].
Groundwater mapping is used as a technique for the methodical development and management of water resources [22]. Hydrogeological maps indicate aquifers’ geological, hydrogeological, and hydro chemical features in a spatially distributed form. Groundwater maps can be used to create strategies and manage groundwater resources sustainably, allowing decision makers to identify suitable locations for finding productive wells. Furthermore, mapping helps to understand how vulnerable aquifers and their associated ecosystems are to pollution, identifying inappropriate identifying areas to be artificially recharged, and communicating information to groundwater users. In addition, groundwater maps can bring out the interaction between groundwater supplies and urbanized areas [23].
In recent years, new technologies have been widely used in hydrology studies and remote sensing (RS), and GIS has become one of the most frequently used tools for the groundwater sector [24,25]. GIS is a very effective tool for processing large amounts of spatial data and is used as an effective tool in many areas, such as water resource management and the identification of groundwater potential regions [26,27,28]. Along with the use of this effective tool, different studies have been carried out in recent years to produce potential groundwater maps [29,30,31,32,33].
Some researchers have used probabilistic models to create potential groundwater maps, such as [34,35,36], multi-criteria decision analysis [25,37], weights of evidence [21,38], logistic regression [39,40,41], evidential belief function [31,42], certainty factor [36,43], decision tree [21,39,44], artificial neural network [45,46], and Shannon’s entropy [47]. GIS and AHP integration are a potent tool for combining the evaluation of several criteria. To evaluate multiple parameters together for groundwater (GW), integrating GIS and AHP is the best option. AHP is a subjective method that allows users to determine the criteria weights in solving a problem based on multiple criteria [48].
In Turkey, most groundwater is used for drinking and irrigation purposes. Regarding groundwater, at least 500 billion m3 in Turkey is estimated to have dynamic and static reserves of 2–3 trillion m3. Notably, in the World Bank reports, it is stated that there is a water potential of 400 billion dollars in the geography of Turkey. In addition, surface and groundwater resources are used for drinking and utility water purposes in the Kızılırmak Basin. The ratio of operating reserve varies by basin; however, the transition rate from potential to reserve for Turkey is around 75% on average, and for the Kızılırmak Basin, this rate is 87% [49]. Studies on the determination of the groundwater potential in the Kızılırmak Delta have been carried out in limited numbers. Recently, Ersoy, et al. [50], identified hydro chemical properties of groundwater in the delta of the Kızılırmak River, and Arslan and Demir [51] analyzed the impact of seawater intrusion into the Bafra Plain on the quality of groundwater.
Groundwater study is essential for managing the water resources in the Kızılırmak Basin. The present study aims to identify the optimum groundwater potential zone for the Kızılırmak Delta. For that purpose, in this study, the potential zone of GW was digitized by involving different parameters such as precipitation, slope, land use and land cover (LULC), geology, drainage density (DD), lineament density (LD), and soil type. The difference between this study and other studies is that it evaluates the GPZ based on the RS and GIS approach, which is cheaper and quicker than others.

2. Materials and Methods

2.1. Study Area

Regarding the ecological system, the Kızılırmak Delta is the most significant wetland in the Black Sea Region and one of Turkey’s most prominent and wealthiest wetlands. The Kızılırmak Delta was formed by alluvions carried by Turkey’s largest river, the Kızılırmak, as it meandered to the Black Sea [52]. The total area of the delta is 56.000 hectares, and the total wetland area is 16.110 hectares. The Kızılırmak Delta has been located within the RAMSAR area since 1998, and it has rich biological diversity that contains 74% of the bird diversity in Turkey. An area of 4000 hectares in the delta was declared a Wildlife Protection Area by the Ministry of Forestry in 1979. In addition, all wetlands in the delta’s eastern part were declared as Natural Protected Areas by the Ministry of Culture and taken under protection in 1994. Wheat, corn, rice, sunflower, sugar beet, and tobacco are grown in the delta. Animal husbandry is common, especially in the villages around the wetland. Around 23,000 animals graze in the delta, of which 3000 are buffalo, and 8000 are cattle. In addition, the majority of these wetlands have changed currently as a result of various land uses (such as agriculture), hydrological changes (such as irrigation and drainage systems), and human activities such as fishing [53].
The study area lies between 41°24′10″ N to 41°16′48″ N latitude and 35°33′40″ E to 36°11′35″ E longitude and covers about 1835 km2 land area, with a coastline of 65 km (Figure 1). The average slope in the study area is around 1%, and the height above sea level ranges from 2 to 28 m. The study area has a temperate climate; the annual average precipitation is between 488 mm and 505 mm, and the annual average temperature is 14.6 °C. The aquifers in the study area are unconfined, with the water depths of the wells ranging from 5 to 20 m. The soil depth in the study area is around 1.5 m. Existing groundwater is generally used for irrigation or drinking water [54]. In this study, the GIS method determined the GPZ of the Kızılırmak Delta.

2.2. Data Set and Sources

At the beginning of the study, the selection of essential parameters for potential groundwater assessment with GPZ mapping was determined by reviewing the literature [55,56,57,58,59,60]. Regarding the literature, precipitations, LULC, lithology, slope, DD, LD, and soil type factors were considered for the present study. Figure 2 shows the general flowchart for the present study. The land-cover map was prepared by ESRI LULC 2022, a global company of geographic information systems (GIS), followed by ground-truth verification based on a satellite base map and Landsat 8 satellite images.
The precipitation data were obtained from the Turkish State Meteorological Service (MGI) for Samsun City from 1990 to 2022. Soil data were obtained from the Ministry of Agriculture and Forestry of the Republic of Turkey. The lithological map was created from the 1/50,000 geological map from the institute of Mineral Research and Exploration (MTA). The slope, LD, and DD maps were created using a digital elevation model with a spatial resolution of 30 m derived from the Shuttle Radar Topography Mission (STRM), and the digital elevation models (DEMs) were obtained from the U.S. Geological Survey (USGS).

2.2.1. Precipitation

Precipitation is one of the main factors for groundwater recharge, and it can be said that high amounts of precipitation produce high groundwater recharge [61]. The groundwater potential increases with an increase in the average precipitation amount of the region, whereas a low precipitation average may cause a decrease in the groundwater potential.
Precipitation is the major source of recharge to the groundwater. Intensity and duration of precipitation have high impact on infiltration and runoff volume. Accurate mapping of the spatial distribution of precipitation is vital in many fields, such as hydrology, meteorology, and agriculture. For this purpose, simple Kriging, ordinary Kriging, universal Kriging, ordinary coKriging, empirical Bayesian Kriging, radial basis functions, local polynomial interpolation, global polynomial interpolation, and inverse distance weighting methods are applied in the GIS environment. These methods have been compared by many researchers before, and in these comparisons, it was stated that the error rates were quite low in the inverse distance weight (IDW) method, and it was chosen as the most representative method of interpolation to characterize the annual precipitation distribution [62], especially on flat land structures [63]. In consequence, the precipitation map in this study was created utilizing the IDW technique in GIS by extracting the annual average precipitation for the study area. The data were obtained from General Directorate of Meteorology Samsun Office and cover more than 60 years (1960–2022) for Samsun City.
The precipitation map was created by interpolating the precipitation of the ten meteorological observation stations, and the map obtained was categorized into five groups. The annual precipitation for the study area exists between 716 mm to 1048 mm. The precipitation map is divided into five main categories based on the amount of precipitation per year: 716–749.9, 750–811.1, 811.2–877.5, 877.6–934.7, and 934.8–1048 mm/year (Figure 3). In this study, the high-sloping regions generally receive more rainfall per year than the lower-sloping regions.

2.2.2. Soils

Groundwater is fed by surface water that mixes with the groundwater flow through infiltration. Therefore, the soil structure directly affects the infiltration and groundwater recharge [64]. Groundwater recharge depends on the soil type and infiltration rate. Soil texture (grain form, size, permeability, etc.) substantially impacts groundwater movement [65]. Coarse-grained soils have a high infiltration potential and provide higher groundwater recharge than fine-grained soils [66]. The primary types of soil for the study were obtained as brown forest, podzolic, colluvial, alluvial, and hydromorphic soils. The soil types that cover the most area in the study area are brown forest soils and podzolic soils, as shown in Figure 4.

2.2.3. Land Use/Land Cover (LLUC)

LULC is one of the other essential factors for the recharge and availability of groundwater and affects the water quantity, which merges with groundwater [67,68]. For the present study, the selected area is divided into fourteen categories: settlement, industrial zone, mining zone, agricultural zone, rice field, orchard, pastureland, forest, grassland, moor, sand dunes, sparse vegetation, wetland, and water bodies. Groundwater formation is less in settlement, industrial zone, and mining zone areas than in cultivated areas, such as agricultural zone, rice field, orchard, pastureland, and forestlands [69,70].
In this study, the datasets of the soil characteristics were imported into ArcMap 10.8.2, and we clipped the study area from it by extraction and classified it by grid code to different classes. According to this classification, most of the delta comprises crop and forest areas (Figure 5).

2.2.4. Lithology

The geological features of the soil affect the porosity, and the porosity affects the groundwater movement; groundwater flow is higher in soils with high porosity [71]. Therefore, the groundwater storage capacity of soils with high porosity is also high. For the present study, the geological map was extracted from the 1/50,000 geological map from MTA and classified with different classes such as silt, clay, admixture (alluvium), andesite–basalt, wetland, limestone, sand, water body, volcanic sediment, and conglomerate sandstone (Figure 6) in the ArcMap 10.8.2 environment. These geological structures have a set of geologic characteristics, specific behavior, boundaries, and structures formed from different minerals. The resulting shape file was transformed to a raster layer using ArcMap 10.8.2’s conversion, i.e., the feature to raster tool, and then resampled to a cell size of 30*30 m.

2.2.5. Lineament Density (LD)

Lineament density (LD) is calculated as the total length of lineaments per unit degree. It provides valuable information about the quality of structural alteration, rupturing, and shearing and groundwater potential. Therefore, LD control is a significant and useful method to capture many related lithological features and reasonable thematic layers, and careful observation can provide additional accuracy in case of lineament convergence in an area.
Linear features such as folds, fractures, and joints form the lineaments of a field [72]. LD is another critical factor for the recharging of groundwater by facilitating the infiltration of surface water into the groundwater. The density of the LD drainage network ensures high groundwater availability [73]. The high LD corresponds to high groundwater recharge [74,75]. For the present study, the LD map was created from the DEM of the area in the ArcMap 10.8.2 environment by plotting the site’s hillside map in different resolutions. The LD values were divided into five levels of density from 0–0.226, 0.227–0.452, 0.453–0.677, 0.678–0.903, and 0.904–1.13 km/km2, which are shown in Figure 7.
For the high lineament density value, we used high-weighted value, and for low LD, we used low-weighted values for determining the GPZ map through the AHP method.

2.2.6. Drainage Density (DD)

The DD is classified into five classes; it ranges from 3.77 to 276.8 Km/km2, as shown in Figure 8. The underground structural bedrock arrangement, vegetation types, rainfall amount, soil properties, slope gradient, and infiltration are among the factors that control the drainage condition of an area.
Drainage density refers to the spacing of stream channels in an area and is calculated by dividing the total stream length by the unit area.
The proximity of the tributaries to each other is defined as the drainage density [76]. It measures the total length of all streamlines per unit area [33,77]. Drainage density and drainage patterns provide essential information regarding groundwater formation. The DD is opposite proportional to the groundwater potential. Therefore, low-DD areas have a high storage capacity, while high-DD areas have a low storage capacity. The DEM of the area was used to plot the DD map for the study area [78]. In ArcMap’s hydrology tools, the fill was first plotted with DEM, then used as the input for the flow accumulation by entering the flow accumulation for the flow direction, the stream was plotted in the flow direction, and DD was obtained. The DD is classified into five classes; it ranges from 0–0.43, 0.44–0.86, 0.87–1.3, 1.4–1.7, and 1.8–2.1 km/km2, as shown in Figure 8.

2.2.7. Slope

The slope is one of the other essential factors for groundwater recharge and directly influences the groundwater. A low-degree slope with low runoff has high infiltration capacity, and a steep slope with high runoff allows less groundwater recharge; therefore, the slope is inversely correlated to groundwater recharge potential zones [20]. The area for the present study is divided into five classes. The north part of the area has a low degree of slope, and the southern part of the study area has a high slope from 0 to 180° (Figure 9).

2.3. Multi-Criteria Decision Analysis Using AHP

Each of the parameters mentioned above has a different contribution to the occurrence and recharge of groundwater. Therefore, the weight of each thematic layer is determined by the AHP technique for their importance to groundwater recharge [48]. AHP is a GIS-based method for specifying the groundwater potential zone based on multi-criteria decision analysis (MCDA) using the AHP technique. Using GIS, the AHP weighted thematic layer quickly provides the overlay analysis for GPZ’s mapping. For the present study, the AHP was implemented in four steps: (1) selection of thematic layers and factors, (2) pairwise comparison matrix, (3) estimating the weight of each factor, and (4) assessing the method consistency, respectively.
  • The layers were selected according to the past literature review, which are precipitation, LULC, geology, slope, LD, DD, and soil;
  • A pairwise comparison matrix was employed for the input factors, and each entry shows the influence on the row relative to the column factor [59]. The assigned importance of each factor that influences the GPZ was based on nine points that are shown in Table 1;
  • The weights were given to the thematic layers based on their importance [33]. As can be indicated from Table 1, “1” represents the equal importance between the factors, and “9” represents the substantial significance of one parameter over another as the scale of importance [48,79].
Table
Table 1. AHP pairwise comparison scale [48].
Table 1. AHP pairwise comparison scale [48].
Scale of ImportanceDefinitionExplanation
1Equal importanceTwo criteria/sub-criteria each contribute equally to the level above.
3Moderate importanceThe judgement mildly favors one criterion/sub-criterion over another.
5Strong importanceOne criterion/sub-criterion is strongly favored in the judgement.
7Very strong importanceOne criterion/sub-criterion is substantially preferred over another.
9Absolute/Extreme importanceThere is evidence to support the preference of one criterion/sub-criterion over another.
2, 4, 6, 8Immediate values between the above scale valuesThere can be no absolute judgment; hence, a compromise is essential.
Precipitation strongly affects groundwater recharge, which was identified as the first important parameter for the GPZ. According to the preliminary review, LULC is the second most crucial factor because LULC changes human activities, which affects groundwater resources [80]. The third and fourth essential factors are all hydrogeological parameters (geology and lineament density).
The slope was chosen as the fifth important factor because it influences the infiltration of precipitation to the groundwater [1]. Finally, the soil texture was selected as the seventh important factor for GPZ because of the soil type of the study area, which was loamy soil and had lower infiltration rate. The consistency ratio (CR) was used for the validation of the pairwise comparison matrix for thematic layers and sub-\classes, which can be obtained by the following equation.
C R = C I R I
where “CR” is the consistency ratio, “CI” is the consistency index, and “RI” is a random index whose value is dependent on the number of parameters that have been compared. The CI can be calculated by Equation (2) [48].
C I = λ − n n − 1
where “n” is the number of thematic layers, and λ is the average eigenvalue of the consistency vector. The RI value depends upon the number of layers compared. According to [48], the RI value for “n = 7” is 1.32 (Table 2).

3. Results

3.1. Multi-Criteria Decision Analysis Results by AHP

In this section, the multi-criteria decision analysis results by AHP are given. Table 3 shows the normalized pairwise comparison matrix for the given thematic layers. As indicated in Table 3 and Figure 10, the normalized weight of precipitation is higher than other factors, which are 41% weighted, showing the significant influence of precipitation on groundwater recharge. LULC was weighted 22.5% as the second most crucial factor, and geology, with 16.3%, was the third critical factor for the GPZ’s mapping according to their behavior.
On the other hand, the soil was weighted 3.6%, and it became the lowest important factor among the thematic layers because of its lowest soil-infiltration behavior. The calculated consistency ratio (CR) of the pairwise comparison matrix for all seven thematic layers after assigning scale values resulted in a 3% CR, which is lower than the maximum of 10%, and on the other hand, the soil was weighted 3.6%, and it became the lowest important factor among the thematic layers because of the lowest infiltration behavior of the loamy soil. The calculated CR of the pairwise comparison matrix for all seven thematic layers after assigning scale values resulted in a 3% CR, which is lower than the maximum of 10% and hence shows the accuracy of the matrix. Weighted overlay analysis of the GPZ of each thematic layer was reclassified into five classes, and the thematic layers’ rasters were analyzed by weighted overlay analysis tools in the GIS environment.
The weighted overlay analysis method is based on the following equation.
G P Z M = ∑ i = 1 n W j * X i
Wj is the normalized weight (in percentage) of the indicator, xi is the relative score for the ith indicator at the ith pixel, m is the total number of thematic layers, and • n is the total number of classes. The obtained weights for each thematic layer were sub-classified and ranked 1 to 9 based on their relative GPZ occurrence. Table 4 shows the subclass of thematic layers with their relative scales. GPZ was classified into five classes based on the influence of each thematic layer with their weighted values. Table 5 shows the potential groundwater categories with their importance.

3.2. Groundwater Potential Zone Delineation

After obtaining the normalized weighted factors, each thematic layer was entered into the GIS environment and integrated with a pixel-based equation (Equation (3)). The GPZ map was created with weighted overlay analysis tools, and the map was divided into four zones: poor, moderate, high, and very high. Figure 11 shows each potential zone’s GPZ classification, area, and percentage. As shown in Table 6, 38.01% of the total area has very high potential for groundwater, with 19.37% with high potential in the second place, which has a low degree of slope with low runoff and high infiltration rate and is located in the north part of the study area near the Black Sea region. In the study area, about 68.41 km2 of total area was classified as poor potential zone, which accounts for 3.78% of the total area located in the northern part of the study area, due to the low infiltration rate and land-use form of the area. First, 687.65 km2 of the total area falls under the very high potential zone of GPZ; secondly, 350.44 km2 of the total area was located in the high zone of GPZ for the study area, and 702.38 km2 of the total area was located under the moderate zone of GPZ, which can indicate that this region has excellent and good potential or high-yielding groundwater aquifers [59]. In conclusion, precipitation, geology, LULC, LD, and slope factors are determined as strongly influencing the GPZ for the present study.

4. Discussion

Revealing the groundwater potential through creating potential groundwater maps is a significant challenge to overcome to ensure the effective management and sustainability of groundwater resources. The groundwater potential in the Kızılırmak Delta and adjacent areas was mapped by combining GIS and AHP multi-criteria decision methods. These methods make it easier to create physical and numerical models for huge regions with insufficient geological and hydrogeological data while also giving a metric for analyzing and comparing the current condition in all areas with adequate data [24,25,26,30]. The AHP method was used as the pairwise comparison analysis for the weighting of the thematic layers, and it was found that the most weighted parameter was 40.9% precipitation for the study area, which was considered in the GPZ mapping, followed by LLUC with 22.5% and geology with 16.3%. On the other hand, the soil was a low-ranked parameter for determining GPZ, as weighted 3.6%, due to the low infiltration behavior of the soil type in the study area (Table 4). Similarly, Oikonomidis, et al. [81], Das [24], and Biswas, et al. [82] concluded that precipitation, geology, and slope are the main influential factors of groundwater potential using the AHP model in the Tirnavos area of Greece, Vaitarna Basin of India, and Uttar Dinajpur area of West Bengal, respectively. Because in these areas, as in the Kızılırmak Delta and its surroundings, groundwater storage mainly depends on precipitation.
The result of the study shows that the AHP method based on the RS-GIS is one of the best and most economical methods for evaluating GPZ mapping. The GPZ map was determined in GIS by using weighted overlay analytical tools for the weighted thematic layers, which shows a good water potential zone for the study area, and more than three to four parts of the site have a moderate, high, and very high zone of groundwater.
According to the GPZ map (Figure 11), regions with very high and high potentials are close to the forest and agricultural sites due to high infiltration rate, more precipitation for the southern part of the study area, the presence of cultivated land, and porous soil type. However, in the study area, it has been observed that the groundwater potential is associated with a decrease in the regions in the coast where is high runoff, loamy soil, barren lands, settlements, and industrial zones.
These results support comprehensive groundwater exploration and groundwater recharge management. As a result, local governments and managers can effectively interpret AHP modeling results for groundwater potential to maximize management advantages. In addition, further analysis is required in other research areas to test and validate the reliability of the model results.

5. Conclusions

Different methods have been proposed for groundwater potential mapping in this study and the literature. The refinement of the modeling method used to reveal groundwater potential is a method for estimating the uncertainty of a groundwater model. The present study aimed at the assessment of the groundwater potential zones (GPZ) of the Kızılırmak Delta, which is located in the Samsun City of Turkey, by using the GIS- and RS-based AHP method. Different thematic layers, such as precipitation, LULC, geology, DD, LD, slope, and soil, were considered to determine GPZ. The groundwater potential in the Kızılırmak Delta and adjacent areas was mapped.
The resulting GPZ map can be utilized as a tool for water resource management by operators in this field. High-resolution geographical data are required to improve the accuracy of the AHP technique. Higher-accuracy models can be produced with higher -resolution data, and this is the limitation of this study. The method used in this study can be applied to all wetlands globally and, for this study, to cover the entire Kızılırmak basin, with larger and high-resolution data in different areas.

Author Contributions

Conceptualization, N.B. and N.G.S.-O.; methodology, N.B., N.G.S.-O. and S.A.; software, S.A. and formal analysis, N.B. and H.A.; investigation, N.B.; resources, N.B., N.G.S.-O., S.A. and H.A.; data curation, N.B., N.G.S.-O. and S.A.; writing—original draft preparation, N.B. and S.A.; writing—review and editing, N.B.; visualization, H.A.; supervision, S.A.; project administration, N.B. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the project SCORE (Smart Control of the Climate Resilience in European Coastal Cities) funded by European Commission’s Horizon 2020 research and innovation programme under grant agreement no.101003534.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 15 10964 g001 550
Figure 1. Geographical location of the study area.
Figure 1. Geographical location of the study area.
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Figure 2. General flowchart for the study.
Figure 2. General flowchart for the study.
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Figure 3. Annual precipitation map for study area.
Figure 3. Annual precipitation map for study area.
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Figure 4. Soil map for study area.
Figure 4. Soil map for study area.
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Figure 5. Land-use and land-cover map for study area.
Figure 5. Land-use and land-cover map for study area.
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Figure 6. Lithology map of study area.
Figure 6. Lithology map of study area.
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Figure 7. Lineament density map of study area.
Figure 7. Lineament density map of study area.
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Figure 8. Drainage density map of study area.
Figure 8. Drainage density map of study area.
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Figure 9. Slope map of study area.
Figure 9. Slope map of study area.
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Figure 10. Normalized weight of the thematic layers.
Figure 10. Normalized weight of the thematic layers.
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Figure 11. GPZ map for study area.
Figure 11. GPZ map for study area.
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Table
Table 2. RI values for different numbers of thematic layers or factors.
Table 2. RI values for different numbers of thematic layers or factors.
NRINRINRI
10.0061.24111.51
20.0071.32121.48
30.5881.41131.56
40.9091.45141.57
51.12101.49151.59
Table
Table 3. Normalized pairwise comparison matrix of thematic layer for groundwater potential zone LULC.
Table 3. Normalized pairwise comparison matrix of thematic layer for groundwater potential zone LULC.
Matrix PLULCGLDSDDSNW
1234567
P1133578940.9%
LULC21/312355722.5%
L31/31/21335516.3%
LD41/51/31/312137.4%
Sp51/71/51/31/21215.1%
DD61/81/51/511/2114.2%
S71/91/71/51/31113.6%
Precipitation (P); lithology (L); lineament density (LD), slope (Sp); drainage density (DD); soil (S); normalized weights (NW).
Table
Table 4. Normalized weights of thematic layer and sub-classes assigned ranks.
Table 4. Normalized weights of thematic layer and sub-classes assigned ranks.
Thematic LayerNormalized WeightsClassesRank
1Precipitation40.9%716–749.95
750–811.15
811.2–877.57
877.6–934.78
934.8–10489
2LULC22.5%Settlement7
Industrial zone1
Mining zone3
Agricultural zone7
Rice field9
Orchard5
Pastureland7
Forest9
Grassland7
Moor5
Sand dunes9
Sparse vegetation7
Wetland9
Water bodies9
3Lithology16.3% Alluvion1
Andesitebasalt5
Wetland9
Limestone7
Sand7
Water body9
Volcanic sediment3
Conglomerate sandstone5
4Lineament density7.4%0–0.2261
0.227–0.4523
0.453–0.6775
0.678–0.9037
0.904–1.139
5Slope5.1%0–9.69
9.7–247
25–395
40–563
57–1801
6Drainage density4.2%0–0.439
0.44–0.867
0.87–1.35
1.4–1.73
1.8–2.11
7Soil type3.6%Brown forest soil7
Podzolic soil9
Colluvial soil5
Settlement7
Water bodies9
Coastal dunes5
Alluvial soil9
Floodplains1
No data1
Hydromorphic soil3
Table
Table 5. Groundwater potential zones with categories.
Table 5. Groundwater potential zones with categories.
Groundwater Potential Categories
1Poor
2Moderate
3High
4Very high
Table
Table 6. Classification of GPZ with the percentage and area of each zone.
Table 6. Classification of GPZ with the percentage and area of each zone.
Groundwater PotentialPercentage Area Coverage (%)Area (km2)
Poor3.7868.41
Moderate38.82702.38
High19.37350.44
Very high30.01387.62
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Beden, N.; Soydan-Oksal, N.G.; Arıman, S.; Ahmadzai, H. Delineation of a Groundwater Potential Zone Map for the Kızılırmak Delta by Using Remote-Sensing-Based Geospatial and Analytical Hierarchy Processes. Sustainability 2023, 15, 10964. https://doi.org/10.3390/su151410964

AMA Style

Beden N, Soydan-Oksal NG, Arıman S, Ahmadzai H. Delineation of a Groundwater Potential Zone Map for the Kızılırmak Delta by Using Remote-Sensing-Based Geospatial and Analytical Hierarchy Processes. Sustainability. 2023; 15(14):10964. https://doi.org/10.3390/su151410964

Chicago/Turabian Style

Beden, Neslihan, Nazire Göksu Soydan-Oksal, Sema Arıman, and Hayatullah Ahmadzai. 2023. "Delineation of a Groundwater Potential Zone Map for the Kızılırmak Delta by Using Remote-Sensing-Based Geospatial and Analytical Hierarchy Processes" Sustainability 15, no. 14: 10964. https://doi.org/10.3390/su151410964

APA Style

Beden, N., Soydan-Oksal, N. G., Arıman, S., & Ahmadzai, H. (2023). Delineation of a Groundwater Potential Zone Map for the Kızılırmak Delta by Using Remote-Sensing-Based Geospatial and Analytical Hierarchy Processes. Sustainability, 15(14), 10964. https://doi.org/10.3390/su151410964

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