Study of the Impact of Landforms on the Groundwater Level Based on the Integration of Airborne Laser Scanning and Hydrological Data

Abstract

This article presents a methodology for examining the impact of terrain on the level of groundwater in a well with an unconfined table aquifer. For this purpose, data from the groundwater observation and research network of the National Hydrogeological Service; airborne laser scanning technology; an SRTM height raster; orthophoto maps; and a WMTS raster were used and integrated for the specific parcels of Warmia and Mazury County. Groundwater is the largest and most important source of fresh drinking water. Apart from the influence of precipitation amount on groundwater level, the terrain is also important and is often omitted in comprehensive assessments. The research undertaken in this study provides new insights and a new methodology for the interpretation of hydrological data by taking into account the terrain, and it can be expanded with new data and increased research area or resolution. Research has shown that the attractiveness of the parcel in terms of construction development and excavation possibilities is greatly influenced by the groundwater level.

1. Introducción

Terrain is one of the most important land features that should be taken into account when designing communication networks and land infrastructure networks and when purchasing land and determining its purpose. Landforms influence land use. During landform analysis, we should not only pay attention to the elements of above-ground infrastructure but also the underground utilities and water supply of parcels. Therefore, before purchasing a parcel, one should check all factors affecting its value and subsequent use. One of the often overlooked aspects is the depth of groundwater which, in addition to the type of soil, its stratification, and the condition of the soil in the building parcel, is important when, for example, building a house. The amount of groundwater is dynamic, resulting from the amount of rainfall, surface runoff, and evapotranspiration. These elements determine changes in water retention in the water balance. Originally, the amount of water resources solely depended on natural factors, including climatic, geological, and terrain factors.

The high level of groundwater necessitates the use of non-standard construction and insulation solutions for the building, which consequently results in a significant increase in, for example, the costs of building. Groundwater is located in the saturation zone, i.e., it fills this zone and its pores. Groundwater lies just below the surface of the land, below the aeration zone. The groundwater level depends on [1] an increase in extreme weather phenomena, including long droughts and unexpected storms, amount of precipitation, geographical location of the property, and soil type.

The location of the property has a significant impact on the groundwater level. Parcels located in depressed areas and near rivers or lakes are characterized by high groundwater levels. Groundwater in such areas occurs just below the top layer of soil. Plants on the parcel can also be an indicator of the groundwater level. Currently, groundwater is the source of approximately 33% of the total water supplied to households and enterprises; it constitutes approximately 30% of the global freshwater content, and its resources in the first period of the 21st century contributed as much as 25% to the increase in global mean sea level. According to the latest research, almost 5 billion people currently live in areas at risk of lack of access to fresh water. Over the last few decades, due to the rapid increase in water demand, the rate of groundwater depletion has more than doubled, and as a result, groundwater depletion has been recognized as a global phenomenon [2]. Groundwater is monitored by in situ point measurements that, due to their high cost and time-consuming nature, are collected only for selected time epochs and areas. To analyze the quality and quantity of global and regional groundwater resources, hydrological models are used, wherein groundwater is defined as one of several components; some examples are land surface models (LSMs) or global hydrological and water resources models (GHWRMs) [3,4]. In addition to the hydrological model which, based on the flow continuity equation, presents a model of the hydrological cycle or its part as well as a model of a river or open channel section, describing the movement of water mass in a simplified way, some hydrodynamic models describe some hydrodynamic models that describe the movement of water with equations based on the physics of the process [5]. Numerical hydrodynamic models of groundwater flow constitute the most advanced research and forecasting tool for most hydrogeological issues [6,7].

Systematic measurements of groundwater levels are of fundamental importance for assessing the storage of water resources, but also for identifying recharge and discharge areas, determining flow directions, and establishing the water balance [8]. The Polish groundwater measurement net contains in situ observation results of well depths, efficiency, and chemical composition tests. The groundwater of unconfined mirror (Figure 1) observations were obtained from the Polish hydrogeological annual reports from 2002 to 2023 [9]. The reported measures were recomputed into appropriate GWLs [10,11].

To a large extent, groundwater is charged by atmospheric precipitation. However, the location where the water is infiltrated into the ground is not the place where the actual rainfall occurred. This is influenced by the slope of the terrain, which causes surface water runoff to another place. Of course, this is not the only reason, but it is an important reason and is one that should be taken into account, especially as this aspect is often omitted in research.

The terrain is analyzed based on models such as the digital terrain model (DTM), digital elevation model (DEM), and other studies based on spatial 3D data, which can be obtained, for example, using airborne laser scanning (ALS) technology. DTMs form the basis for distributed hydrologic models as well as two-dimensional hydraulic river flood models, especially for large and difficult-to-access areas [12]. Airborne laser scanners provide data for describing the landscape roughness of the earth’s surface. Landscape roughness affects the transport of hydro-meteorological fluxes between the land surface and atmosphere as well as below the surface. Therefore, precise topographic information can be used to understand and calculate the effects of landscape roughness on evapotranspiration, soil moisture, runoff, and soil erosion at the field and landscape scales [13]. ALS technology also provides an opportunity to monitor floodplain vegetation, which should be carried out in the period with the highest chance of flooding [14].

The Shuttle Radar Topography Mission (SRTM) model is an 11-day mission of the Space Shuttle Endeavor, which was a collaboration between the National Aeronautics and Space Administration (NASA), Jet Propulsion Laboratory (JPL), German Space Center DLR (Deutsche Zentrum fur Luft- und Raumfahrt), and Italian Space Agency (ASI). The mission’s goal was to interferometrically recreate the relief of most of the earth’s surface. As part of the measurements, a model was implemented that covered almost 80% of the land surface between 60° north latitude and 56° south latitude. Two terrain models were created in a regular grid with a mesh of 3″ × 3″ and 1′ × 1′, for which the average height bias, with a probability of 90%, does not exceed 16 m [15].

This topic is not often discussed in scientific publications. Taking into account the specific objectives, some articles include the impact of vegetation on the groundwater level, but also in terms of the sterilization of natural vegetation for crops and the impact of this phenomenon on the groundwater level, thus detailing their impact on droughts (e.g., [16]). Study [16] focused on assessing agricultural land use intensification and its impact on the overexploitation of groundwater resources. The influence of agriculture was noticed, in particular, on the actual evapotranspiration (AET), and an attempt was made to determine the influence of local AET on the groundwater level. It was noted how extremely important it is to take into account the impact of climate change on the reduction in groundwater levels resulting from the intensification of land use. Of course, there are also numerous studies on the impact of meteorological phenomena on the groundwater level, e.g., temperature, precipitation, evapotranspiration [17,18,19], soil and geologic properties [20], anthropogenic factors [21], or land cover, (e.g., [22]). In [17], it was noticed that the hydrological processes regulating the replenishment and sustainable development of groundwater, and therefore their connection with climate change, are poorly limited. Based on the research, it was discovered that in humid locations, the water supply does not change significantly, while already dry regions are characterized by a linear relationship between precipitation and water loss. In [18], it was noted that groundwater is of strategic and crucial importance for global water and food security. And this importance will increase even more in light of the changing climate. This will be related to more frequent and more intense climate extremes, such as droughts and floods. The study also included an explanation of the seasonal impact of rainfall and temperature on changes in groundwater levels [19]. A huge relationship was observed between groundwater level fluctuations and rainfall intensity, evapotranspiration, surface runoff, and drainage. Mathematical statistics and analytical-graphic methods were used for the analysis. The greatest influence of autumn and winter rainfall was noticed; however, in spring and summer, the groundwater level depends on the air temperature. In [20], it was noted that there is a lack of research that synthesizes the impact of sources and factors threatening the quality of groundwater. It has been found that groundwater around the world is mainly contaminated with microorganisms, heavy metals, trace elements, organic compounds, and agrochemicals. The first study of microbial contamination of groundwater was shown in [21]. The study took into account the dependencies on the type of aquifer and the season in the region in measuring wells. It was noted that fully potable water comes from karst-fissured aquifers. A logistic regression model was also used to show the probability of groundwater being available for consumption. It was found to depend on the season and type of aquifer. In most cases, clean water was found in the autumn and winter periods and from karst-cracked aquifers, not porous ones. Study [22] assessed the impact of land cover on the quality of groundwater. For this purpose, physicochemical data and satellite images were integrated, taking into account the land cover, concentration of settlements and urban development, green cover, and land use. Based on the research, it was suggested to consider a large scale to determine the factors controlling groundwater degradation.

The topic of the influence of slope and topography is not often discussed in scientific publications, as mentioned earlier. This is an extremely important topic, both in a large-scale sense when it comes to examining resources and also in a small-scale sense in terms of examining the attractiveness of an area, e.g., a parcel.

In study [23], research was carried out on the identification of geological structure diversity based on ALS. The result of the work was the development of a conceptual model of hydrogeological conditions, which then formed the basis of a mathematical model of water filtration. However, the study took into account the flow of groundwater from the river from the embanked river through slot channels. It was noted that this flow was 800 times greater than the normal groundwater flow in another aquifer (not caused by flood waters).

This paper aims to integrate ALS data and groundwater levels followed by the SRTM height raster in the aspect of assessing the attractiveness of the parcel. The specific objectives achieved as part of the study are: (1) an assessment of the flooding of plots or their long-term waterlogged condition as a result of rising water levels in the ground; and (2) an assessment of the impact of terrain slope and the presence of high vegetation on the filling or drying of the measuring well analysis of the terrain inclination and well embedment depth in the stratified test objects. The area considered for research had not been previously examined in this respect. No scientific articles show the attractiveness of a parcel depending on the DTM and groundwater level.

2. Materials and Methods

2.1. Case Study

Olsztyn County is located in the central part of the Warmian-Masurian voivodeship in north-eastern Poland (Figure 2). Olsztyn County is characterized by a large diversity of land use forms in individual communes. In the entire district, agricultural land constitutes over 51%, while forest land accounts for nearly 40% and land under water accounts for approximately 4.6% of the district’s area. The district’s climate is characterized by relatively cool summers and not very severe winters, as well as frequent weather changes related to the movement of atmospheric fronts. The average annual temperature was about 9.0 °C; the lowest average temperatures were recorded in January, and the highest were recorded in September. Annual rainfall amounts to 567 mm, with a maximum in October (118 mm) and a minimum in February (9 mm) [24] (www.stat.gov.pl; accessed on 4 February 2024). The selected area, although small, is characterized by a significant coverage of water reservoirs (155 lakes over 1 hectare in the county, which is over 11,730 ha). The vast majority of the area of Olsztyn County lies in the water region of Łyna and Węgorapa in the Pregoła basin. The western part and south-eastern parts of the county lie in the Vistula basin.

There are three aquifers in the Warmian-Masurian voivodeship: Quaternary, Paleogene-Neogene, and Cretaceous. In Olsztyn County, groundwater is found in the Quaternary and Paleogene-Neogene levels. Of the existing aquifers, Quaternary formations are of greatest economic importance.

2.2. Methodology

This study adopted the methodology presented in Figure 3.

Four parcels were selected for the study. The basis for the choice was the proximity of measuring wells and the diverse location and development of the parcels and their surroundings. The presence of ponds (permanent water), the distance from the forest, and compact development were also taken into account. The research attempts to integrate four types of data to study the influence of the slope and vegetation presence of the parcel on the groundwater level. Hydrological measurement data from the National Hydrogeological Service, ALS point cloud data from the Information System of Country Protection Against Extraordinary Hazards (ISOK) project, height raster data from the SRTM mission, and orthophoto map and raster data from geoportal were used (step 1). ALS point cloud data let us prepare the presentation of vegetation presence (divided into three groups: ground, low vegetation, and high vegetation). This classification lets us determine the influence of vegetation and also the possibility of transpiration and shadow occurrence in the localization (step 2). Based on the hydrological data, well depth and groundwater level in wells were computed (step 2). We also used additional data for integration for a wider analysis and assessment: orthophoto maps and an SRTM height raster. The given SRTM height raster allows us to isolate some fragments, which were then recomputed into given raster heights (step 2); this allows us to then assess the threat of the long-term wetness of the area or long-term droughts, which reduces the value and attractiveness of the parcel in terms of construction, use, and transformation. From geoportal resources, an orthophoto map and raster were acquired, from which specific tiles were isolated, that were necessary for data evaluation and integration (step 2). A novelty in the presented research is the attempt to integrate all data in four areas. After integration, in step 3, a DTM with terrain slopes, contour maps, and floodplain maps was carried out. The assessment of the impact of terrain on groundwater level is discussed in step 4.

The analyzed detailed objectives are reflected in Figure 4.

2.3. Data Collection

Five plot locations were selected for the study near the National Hydrogeological Service’s measurement wells (Kobulty, Radostowo, Groszkowo, Tomaryny, and Barcikowo) in the area of Olsztyn County. The locations of the measuring wells are diverse—Radostowo and Barcikowo are located in a forest area, Kobulty in a rural area, and Groszkowo in an area of meadows and pastures. Interestingly, Barcikowo and Tomaryny are located in an area influenced by violent or long-lasting rainfall but also long-lasting drought. The selected wells are also located in areas with various crumbly rock substrates. The localization of the selected wells is presented in Figure 2.

Detailed information about the selected wells is provided in

Table 1. Parameters describing the wells.

No.	Localization	Well Number	Type of Research Well	Year of Localization	Ground Elevation [m a.s.l.]	Well Depth [m]	Lithology
1	Kobulty	II/250/1	drilled well	1966	170	29.5	sand + gravel
2	Radostowo	I/250/3	drilled well	1978	146.54	89.5	gravel
3	Groszkowo	II/986/1	drilled well	1986	150	29.2	various-grained sands
4	Barcikowo	II/1872/1	piezometer	2014	121.85	26.1	various-grained sands
5	Tomaryny	II/1577/1	drilled well	1999	123	–	sand

.

Well no. 5 of Tomaryny is disabled and therefore has not been analyzed. Because this well is located within the county, it is mentioned in the table.

Taking into account the location of the hydrological wells, four parcels (Kobulty—parcel_1, Radostowo—parcel_2, Groszkowo—parcel_3, Bracikowo—parcel_4), located in towns/counties where wells are located, were selected for analysis.

Following the study titled “Announcements and Forecasts of the National Hydrogeological Service” (https://www.pgi.gov.pl/psh/zadania-psh/9052-zadania-psh-ocena-i-prognozowanie-sytuacji-hydrogeologicznej.html, accessed on 2 April 2024), for which 31 representative measurement wells were selected in Poland, in the Olsztyn County, it was found that the hydrological situation is one of the worst among the studied areas. For the average lowest annual rate depth of the Kobulty well surface for over a multi-year period since 2015, it significantly exceeded the minimum level established (like half of the tested wells), but it is one of the three wells that fell below the lowest level of annual depth value water tables for the multi-year period. Therefore, the mentioned well and its closest ones were selected for further research. This area has been covered by a hydrogeological low flow since 2015 and is also characterized by one of the largest amounts of low flows since 1951.

ALS datasets containing these parcels were obtained for free from the website https://pzgik.geoportal.gov.pl/imap/ (date of data download: 5 February 2024). The data were collected as part of the ISOK project (IT system for protecting the country against extraordinary threats). The following datasets were downloaded:

• parcel_1: 6017_642948_N-34-79-C-a-1-3-2.laz, 6017_642950_N-34-79-C-a-1-3-4.laz
• parcel_2: 65514_702575_N-34-78-A-a-2-4-2.laz
• parcel_3: 65954_736812_N-34-78-D-c-1-3-2.las, 65954_736814_N-34-78-D-c-1-3-4.laz
• parcel_4: 4801_441798_N-34-77-B-b-3-2-4.laz

The statistics of the obtained datasets and the distance of each parcel from the nearest well are presented in

Table 2. Parameters describing the ALS data for parcels.

Parcel No.	Distance of the Well from the Parcel [m]	Number of ALS Data
		Total Classes	Ground (Class No. 2)	Vegetation (Class No. 3–4)	High Vegetation (Class No. 5)
parcel_1	515	529,280	375,551	152,812	101,676
parcel_2	1495	71,993	32,450	32,741	4261
parcel_3	386	45,918	25,529	9089	11,069
parcel_4	1510	69,567	48,138	7443	19

.

The next step in preparing the data for data integration with hydrological data was the separation of individual classes of objects on the plots, namely land, low, medium, and high vegetation. The distinguished classes of points are presented in Figure 5, Figure 6, Figure 7 and Figure 8.

2.4. Data Processing and Integration

QGIS software (Version 3.28.3 Firenze) was used to integrate the datasets—a multi-platform, free, and open geoinformation software. The QGIS project is part of the Open-Source Geospatial Foundation. QGIS allows us to manage the geographic data. The integrated datasets are presented in Figure 9.

3. Results

Using the Bulletins of the State Hydrological Service, an analysis of the month-by-month groundwater level at the researched points was carried out (Figure 10).

In comparison, the other two wells, Radostowo and Barcikowo, have small amplitude changes (about 15 cm). As a reference level for each well individually, the level of the unconfined groundwater table was referred to at the time of drilling. It is worth noting that the wells in Radostowo and Barcikowo are located in a forest area. Naturally, the superficial outflow of surface and groundwater through forests experiences the greatest delay. The time series for the Kobulty and Radostowo wells were determined for the hydrological years ranging the period of November 2003–October 2022; the time series for the Groszkowo and Barcikowo wells have data recorded from January 2015 to October 2022. Particularly large amplitudes of changes are noticeable in the case of the Kobulty and Groszkowo wells (they reach 1.8 m for the Kobulty well and 1.2 m for the Groszkowo well). The highest levels are visible in all four wells examined, where the maxima were found for all wells in April 2018, and the minima were found in January 2016. The well in Kobulty reached the maximum groundwater level in April 2011, but at that time, not all wells recorded measurements yet. Generally, the highest water values were recorded in the Kobulty well (June 2011), but in this period, not all wells had complete time series.

To test the parcel’s waterlogging, the following factors were taken into account:

• Location (mainly slope) of the plot around the well;
• Height of the well foundation;
• Well drilling depth;
• The depth of stabilization of the free mirror;
• Distance of the analyzed plot from the well.

The following diagrams have been developed and are presented in Figure 11.

Water reservoir levels (e.g., ponds) follow the groundwater level. Hence, it can be concluded that changes in the water level in the well will be reflected in the groundwater level on the parcel, especially in the case of plots with ponds. Based on the diagrams, water level heights were determined which, if they reach the same height on the parcel, will cause waterlogging and consequently cause difficulties in use and, above all, in building. For each parcel, the level of filling the well with water and raising the water to the limit values (maximum levels of groundwater levels in the well) was determined.

The parcel in Kobulty, although located close to the measuring groundwater well, is located at a much higher a.s.l. than the location of the well. Moreover, it is characterized by a significant slope of the terrain.

The next step in data processing was to generate a DTM from clouds of points representing the ground along with the directions of terrain inclination, for example showing in which direction rainwater flows. In addition to the DTM, contour maps were also generated for each plot, which in turn illustrates the terrain forms.

Based on the analyses presented in Figure 11, a simulation was also performed to check how the water level in the well affects the water level on the parcel. Values of 154 m a.s.l. and 170 m as. l. for the Kobulty area, 121 m a.s.l. and 146 m a.s.l. for the Radostowo area, 145 m a.s.l. and 150 m a.s.l. for the Groszkowo area, and 104 m a.s.l. and 121 m a.s.l. for the Barcikowo area were adopted for the analyses.

The obtained DTMs and simulations are presented in Figure 12, Figure 13, Figure 14 and Figure 15.

The characteristics of the DTMs presented in Figure A1a, Figure A2a, Figure A3a and Figure A4a are summarized in

Table 3. DTM characteristics.

Parcel no.	Grid Size [m]	Zmin [m]	Zmax [m]	R = Zmax − Zmin [m]
parcel_1	0.5	164.72	180.96	16.24
parcel_2	0.5	145.48	148.05	2.57
parcel_3	0.5	141.73	145.62	3.89
parcel_4	0.5	101.43	109.34	7.91

.

Table 3 shows that the largest differences in height were observed for parcel_1 at as much as 16.24 m. Hence, the answer in Figure A1c is that for a groundwater level of 154 m a.s.l., parcel_1 will not be flooded, and for the maximum value of 170 m a.s.l., only partial flooding will occur. Approximately 20% of the plot is covered by tall trees, which will also affect the state of groundwater.

The smallest R parameter was recorded for parcel_2 and is 2.57 m. In this case, parcel_2 will be flooded at both tested elevated groundwater levels. For parcel_3 located closest to the hydrological well with a small R parameter, there will be no flooding in both analyzed cases.

parcel_4 will not be flooded—this is the result of the presented analysis for 104 m, and for the groundwater level of 121 m a.s.l., only a small fragment of the eastern border will be flooded. This parcel is also the furthest from the hydrological well, and the distance of the hydrological wells from the plot may introduce some uncertainty as groundwater recharge rates can vary spatially.

4. Discussion

The research showed the dependence of the groundwater level on many factors occurring in the area of the tested well. High groundwater level can be correlated with moderate slopes; on the other hand, low groundwater level is connected with dense vegetation and steep slopes. According to [25], topographical factors that most influence groundwater level are the slope degree, profile curvature, and plan curvature. The study in [25] was carried out to assess the availability of groundwater resources to optimize the selection of future drilling locations. The research described in the mentioned study is the opposite of the one described in this paper for Olsztyn County. However, it shows how important it is to install a well to monitor groundwater, which is the basis of drinking water resources. Additionally, in addition to the slope of the terrain, which affects the escape of water on the surface, as noted, it is extremely important to know the lithology of the terrain.

Considering the research conducted and presented in the article, it is important to take into account in further work the ground on which the measurement well is located. This is of great importance, in addition to the porosity coefficient, for water permeability in the soil and underground flow. Preliminary analysis showed that each well is located in an area that is easily permeable to water and that has quite high porosity (Table 1). This is only a superficial analysis, resulting from the fact that all tested wells are located in an area with a similar soil structure. However, there is no soil analysis for the parcels examined. In further similar work, it is necessary to analyze the soil structure. Groundwater, which constitutes approximately 1% of the total earth’s water resources, is water found in the pores and cracks of rocks under the ground surface. Groundwater reservoirs are recharged by rain or snowfall, which then infiltrates through the soil into the groundwater system. That is why it is so important to analyze the soil structure, which provides an image of the speed of water seeping into the ground, as noted in [26,27,28].

In the past, only surface waters were subject to monitoring, forgetting that they are closely related to groundwater, and activities that change one resource often affect the other (inferred in [26,28,29]). In the research studies, it was observed that the depth of the stabilized groundwater table may change in reference to the general level of groundwater and surface water in the study area. The groundwater level in the study area may be approximately 1.0 m higher after heavy and long-lasting rainfall precipitation or during the melting of snow cover. Such water fluctuations are also indicated by the observations presented in Figure 10. When analyzing parcels around wells, it needs to be remembered that lakes and ponds follow groundwater levels. Therefore, all earthworks should be carried out in good time to prevent the soil from b wet at the bottom of the excavation and on the slopes. Foundation works should be carried out in dry periods when the groundwater level is the lowest, especially on plots where the water level may rise significantly as a result of rainfall, which may result in the plot becoming wet (e.g., the Radostowo site—Figure 13c).

An additional aspect that should be taken into account is that vegetation dries the ground to the depth to which the roots reach—coniferous forests are the strongest, with deciduous forests, meadows, agricultural fields, gradually decreasing in strength. Two of the researched wells are located in a forest area (Radostowo—Figure A2/Figure A1; and Barcikowo—Figure A4/Figure A1); therefore, groundwater in this area is certainly largely absorbed by trees, which causes its decrease. On the other hand, the forest area near the well results in a greater stability of the water level as it stabilizes temperature fluctuations and therefore reduces evapotranspiration. Moreover, the outflow of surface and groundwater into river arteries is naturally delayed the most by forests; i.e., forest areas provide much less water to sources than wilderness and agricultural areas. Figure 10 clearly shows much smaller amplitudes of changes in the groundwater level in the case of these two wells. Analyzing the parcels, it can be noticed, based on Figure 5c and Figure 9 regarding parcel_1 (Kobulty) and Figure 7c and Figure 9 regarding parcel_3 (Groszkowo), that these are the objects with the highest proportion of tall vegetation among those surveyed. This vegetation shades the plot (i.e., less evaporation, more stable temperature), but the tree roots absorb part of the groundwater (similar to the analysis of the tree cover around the measuring well). Vegetation is also related to the dependence on the slope of the ground. The superficial outflow of water from a sloped area is greater, and the vegetation is weaker (from an area covered by a forest, it is the smallest). In the examined cases, the parcel with the greatest slope is parcel_1 (Kobulty), followed by parcel_4 (Barcikowo) (Table 3). As already mentioned, Kobulty is also characterized by the largest amount of tall vegetation. The parcel in Kobulty can be characterized as the one that is least susceptible to waterlogging (Figure 9).

5. Conclusions

Research in hydrology often yields insights into the availability, distribution, and quality of water resources. Practical applications include optimizing water allocation for agricultural, industrial, and domestic use, especially in regions experiencing water stress or facing challenges due to climate change. Understanding hydrological processes helps with examples of developing effective flood management strategies. Research might identify vulnerable areas prone to flooding and inform emergency response plans. Hydrological research can also aid in predicting drought patterns, assessing water availability during drought conditions.

The research undertaken in the article provides new insights and a new methodology for the interpretation of hydrological data by taking into account the terrain.

Hydrological research based on landform analysis guides the design and management of water-related infrastructure, especially for parcel owners. Research allows us conduct the attractiveness of the parcel in terms of construction development, and excavation possibilities are greatly influenced by the groundwater level. The level in the studied area is variable, but the amplitudes of these changes are different depending on the studied unit. A significant influence of the slope of the terrain, but also tall vegetation (with deep roots), on the level and fluctuations of groundwater was demonstrated.