Assessment of Groundwater Age in the Upper Chao Phraya River Basin Using Tritium and Carbon-14 Isotope Analysis

Abstract

Groundwater is a critical resource in the Upper Chao Phraya basin, providing consistent water supplies for agricultural, domestic, and industrial activities, especially during the dry season. This study utilized tritium and carbon-14 dating techniques to investigate groundwater age, analyzing 273 samples collected in 2021 from various wells and depths across the basin. Tritium and carbon-14 were measured using liquid scintillation counting (LSC). The results revealed a wide range of groundwater ages, including recently recharged water with tritium concentrations up to 2.4 TU, corresponding to groundwater ages ranging from a few months to 44.17 years BP (Before Present), with an average of 18.26 years BP. Older groundwater was identified with carbon-14 concentrations as low as 3.22 pMC, indicating ages of up to 22,899 years, with a mean age of 6687 years BP. Correlation analysis showed a positive relationship between tritium and carbon-14 concentrations (r = 0.52). Spatial distribution patterns indicated that tritium concentrations were higher in northern and mountainous areas, identifying these as critical recharge zones. In contrast, lower carbon-14 concentrations in the central and southern areas suggested the presence of older groundwater, emphasizing the need for careful management of these ancient water reserves. The spatial variation in tritium and carbon-14 concentrations highlights differences in groundwater circulation and recharge patterns, enabling the identification of key recharge zones in the northern and highland regions. This highlights the importance of conserving these areas from pollution and over-extraction. The presence of old groundwater in the central and southern areas further emphasizes the need for ongoing monitoring to sustainably manage these long-term water resources. This study enhances the understanding of groundwater dynamics in the Upper Chao Phraya basin and provides valuable insights for improving water resource management strategies.

1. Introduction

Groundwater plays a key role in serving all the water demands of humans and ecosystems, especially in areas where surface water sources are scarce or polluting. The Upper Chao Phraya River basin, located in northern Thailand, is a major hydrological area that sustains extensive agricultural practices and supplies water for domestic and industrial purposes [1,2,3]. The basin is characterized by its heterogeneous geology and complicated aquifer systems, which feature shallow and deep groundwater sources. Effectively managing these water resources is essential to ensuring a sustainable water supply in the region, particularly during the dry season when surface water availability is limited [1,4,5].

Previous studies have investigated the hydrochemical properties of groundwater in the Chao Phraya River basin [6,7], focusing on aspects such as source identification [6,7,8], distribution patterns [9,10,11], and quality assessment [12,13]. Stable isotope fingerprinting techniques were employed to assess the spatial and temporal distribution of rainfall and the interactions between surface water and groundwater in the region [14,15]. Their findings revealed that groundwater is primarily recharged by river water, contributing 54% of the groundwater, with the remaining 46% derived from precipitation. These works highlighted the importance of seasonal variations in precipitation, with distinct isotopic compositions observed between wet and dry seasons. Additional studies have further corroborated these findings, demonstrating that groundwater in the basin is heavily influenced by river water infiltration, particularly during the wet season, and that isotope hydrology is an essential tool for tracing groundwater recharge sources and understanding the dynamics of water flow in this region [5,13]. However, there remains a need for further research on the mechanisms controlling groundwater age and recharge patterns, particularly in the Upper Chao Phraya basin. Understanding these factors is essential for developing effective management strategies that ensure the long-term availability and quality of groundwater resources.

Several approaches have been employed to evaluate groundwater age in complex aquifers, including geophysical techniques [16,17], hydrochemical analysis [18], and radioisotope methods [19,20,21]. Among these, radioactive dating has proven to be a valuable tool for understanding hydrological processes such as groundwater recharge, mixing, and residence time [22,23,24,25,26]. It makes use of radiation that occurs naturally [27,28,29,30]. Tritium (H-3) and carbon-14 (C-14) are frequently employed for this objective [28,30,31,32]. Tritium, with a half-life of 12.32 years, is capable of reliably identifying the age of young groundwater, particularly up to 50 years old [32]. Nuclear bomb testing undertaken in the mid-twentieth century significantly increased the presence of this chemical [33]. This makes it a useful instrument for tracking water that has existed since the 1950s [34]. Carbon-14, which has a half-life of 5730 years, is used to date older groundwater up to about 50,000 years [35]. It is produced in the atmosphere when solar neutrinos absorb nitrogen-14. Wet deposition produces precipitation that seeps into the groundwater by dissolving carbonates and reacting with organic materials.

In recent years, studies utilizing tritium and carbon-14 for groundwater age dating have provided significant advancements in understanding groundwater dynamics across various geological settings, particularly those analogous to the Upper Chaophraya basin [29,30,31,36]. Research conducted in regions such as Romania, New Zealand, and Southern Africa demonstrates that the combined use of tritium and carbon-14 allows for a more comprehensive and accurate determination of groundwater recharge rates, the extent of mixing between different water bodies, and the delineation of modern versus ancient water sources within an aquifer. For instance, in Romania, the integration of carbon-14 and tritium data facilitated the identification of the contributions from modern precipitation to groundwater recharge while also accounting for the impact of historical mining activities on groundwater quality and flow patterns [29]. Similarly, studies in New Zealand have shown how tritium and carbon-14 data can be used to quantify the age gradients in exploited aquifers, revealing the extent of anthropogenic impacts on groundwater systems [31]. These studies highlight the importance of considering multiple isotopic tracers in heterogeneous aquifers, like those found in the Upper Chaophraya basin, where groundwater systems are often complex due to variations in geology, recharge conditions, and human activities.

This study utilizes tritium and carbon-14 dating techniques to investigate the groundwater age in the Upper Chao Phraya basin. Tritium, with a half-life of 12.32 years, is particularly useful for dating young groundwater (up to 50 years old), while carbon-14, with a half-life of 5730 years, is used to date older groundwater (up to 50,000 years). By examining the concentrations of these isotopes in groundwater samples, this research aims to answer the following questions: (1) What are the concentrations of tritium and carbon-14 in groundwater samples collected from the Upper Chao Phraya basin? (2) How do these concentrations relate to other variables, such as groundwater depth? (3) What insights can isotope data provide regarding the replenishment and residence time of groundwater in the research area? The outcomes of this study will enhance our understanding of groundwater dynamics in the Upper Chao Phraya basin and offer significant insights into regional water resource management. By identifying key recharge zones and understanding groundwater age distribution, this research will contribute to the development of sustainable groundwater management practices in the region.

2. Materials and Methods

2.1. Study Area and Hydrogeological Conditions

The Upper Chao Phraya basin is in northern Thailand. Figure 1a illustrates the basin, which covers an area of 103,833 square kilometers. The region experiences a tropical monsoon climate, characterized by distinct wet and dry seasons [37,38,39,40]. The average annual precipitation ranges from 1021 to 1275 mm (during 2014–2023), with the majority occurring during the monsoon season from May to October (Figure 1b). These precipitation fluctuations significantly influence river flow and groundwater recharge within the basin (Figure 1c). The basin is subdivided into four main sub-basins: Ping, Wang, Yom, and Nan, each with unique hydrological characteristics that impact the underlying aquifers [14].

The Ping Basin has a watershed area of 33,989 square kilometers and receives an average annual rainfall of 1021 mm. Groundwater levels in this basin typically range from 10 to 15 m below the surface.

Table 1. Detailed information on the catchment characteristics.

Details	Ping Basin	Wang Basin	Yom Basin	Nan Basin
Watershed area (km2)	33,989	10,791	24,089	34,964
Average rainfall (mm/year)	1021	1065	1115	1275
Average groundwater level (m depth)	10–15	8–15	14–20	11–14
Average elevation (msl)	1524	1228	1134	1500
Highest elevation (msl)	2580	2004	1763	2100
Lowest elevation (msl)	16	120	14	14

Note: 10-year average from 2014 to 2023 for annual rainfall and groundwater level.

clarifies that the Ping Basin has an average elevation of 1524 m above sea level (msl). The Wang Basin, covering 10,791 square kilometers, experiences an average annual rainfall of 1065 mm. Groundwater levels in this basin range from 8 to 15 m, and the average elevation is 1228 msl (with a range from 120 msl to 2004 msl). In the Yom Basin, which spans 24,089 square kilometers, the average annual rainfall is 1115 mm. Groundwater levels here range from 14 to 20 m deep, with an average elevation of 1134 msl (ranging from 14 msl to 1763 msl). The Nan Basin receives the highest average annual rainfall, at 1275 mm, and covers a watershed area of 34,964 square kilometers (Table 1). Groundwater levels in the Nan Basin range from 11 to 14 m, with an average elevation of 1500 msl (ranging from 14 msl to 2100 msl). These variations in groundwater levels, elevation, and precipitation have significant implications for water resource management in the basins.

In regions where groundwater is relatively close to the surface, typically around 10 m deep, there is a higher potential for groundwater recharge due to the shallow depth. This proximity allows for more efficient infiltration of rainwater and surface runoff, which is particularly beneficial in areas with intensive agricultural activity. Conversely, in areas where groundwater is deeper, around 20 m, the recharge process is slower, making these zones more susceptible to water scarcity during dry periods. Higher elevation areas, averaging 1524 m above sea level, typically experience cooler temperatures and potentially greater precipitation [39], which can contribute to increased recharge rates in these regions.

The hydrogeology of the Upper Chao Phraya basin is complex, consisting of several aquifer systems that vary in depth and composition (Figure 2). These aquifers are categorized into shallow and deep types based on their depth and characteristics [11]. The shallow aquifers are generally located at depths from the surface down to approximately 50 m. These aquifers are composed of alluvial deposits (Qfd) and young terraces (Qyt), primarily located in the central part of the basin [2]. These alluvial sediments, consisting of clay, sand, silt, and gravel, have a thickness of 5 to 10 m and are encountered at depths of 15 to 50 m. The pumping rates for these aquifers range from 3 to 8 cubic meters per hour. The young terraces (Qyt) consist of clay sequences interspersed with silts and very fine-grained sandstones. These terraces are 20 to 50 m thick. Due to the high clay content and the fine grain size of the sands, the pumping rates of these aquifers are limited to between 3 and 5 cubic meters per hour. Due to their shallow depth, these unconsolidated aquifers are highly vulnerable to pollution from surface activities [13].

The deep aquifers, composed of old terraces (Qot), are located at depths ranging from 50 to over 200 m. These aquifers are composed of more consolidated materials, such as sandstone and limestone, and are the most productive in the basin, with well pumping rates between 5 and 10 cubic meters per hour [7]. These deep groundwater sources are often confined.

2.2. Laboratory Analysis of Samples

Groundwater samples were collected from 214 wells in the Upper Chao Phraya basin, including both shallow and deep wells, during 2021 (Figure 1). Wells were selected to ensure representative coverage of varying depths and geographical locations. Groundwater was pumped at approximately 18 L/min using a submersible pump, and samples were taken after sufficient flushing of the wells, as determined by stable electrical conductivity (EC) readings. Samples were stored in 1 L high-density polyethylene (HDPE) bottles, which were pre-cleaned and rinsed with the sampled groundwater prior to collection. For C-14 analysis, samples were collected by adding excess BaCl₂ to 120 L of water, pre-adjusted to a pH of ≥12 using CO₂-free NaOH, resulting in the precipitation of BaCO₃ within 1 L HDPE bottles. To prevent contamination, samples were filtered through 0.45-micron filters and refrigerated until analysis [41]. Detailed records of sampling dates, locations, and depths were meticulously maintained to ensure accurate data analysis.

Tritium analysis was performed using liquid scintillation counting (LSC, Model Quantulus 1220 from Perkin Elmer) following an electrolytic enrichment process [42]. Groundwater samples were distilled in the laboratory to concentrate the tritium. The distilled water was then mixed with a scintillation cocktail, and the samples were analyzed in the LSC to quantify tritium activity. Tritium concentrations were measured in tritium units (TU), where each TU corresponds to one tritium atom per 10¹⁸ hydrogen atoms. The method had a detection limit of approximately 0.1 TU, representing the smallest measurable concentration. Additionally, tritium data from rainfall observations at the Bangkok station, part of the Global Network of Isotopes in Precipitation (GNIP) campaign, provided critical reference values for determining recharge water concentration, which was then used in groundwater age calculations.

For carbon-14 (C-14) analysis, LSC was employed after the direct absorption (DA) method [43]. The initial phaseinvolved precipitating carbonate of groundwater sample. The groundwater carbonatewas then converted to carbondioxide (¹⁴CO₂) and then using DA method for analysis via LSC to determine the C-14activity. Results were expressed as percent modern carbon (pMC), indicating the proportion of C-14 relative to a modern standard. The minimum detectable quantity of C-14 was approximately 2.0 pMC. Additionally, δ¹³C values of Total Dissolved Inorganic Carbon (TDIC) were measured in permil (‰) relative to the Pee Dee Belemnite (PDB) standard. These δ¹³C values serve as part of the correction method, helping to account for potential carbonate dissolution from rock formations or soil CO₂. Accurate measurement of δ¹³C provides essential insights for refining groundwater age estimates and understanding geochemical processes within the aquifers.

2.3. Groundwater Dating Using Tritium and Carbon-14

2.3.1. Tritium (H-3) Dating

Tritium, a radioactive isotope of hydrogen with a half-life of approximately 12.32 years, is commonly used to determine the age of young groundwater, typically less than 50 years old (

Table 2. Tritium units (TU) ranges for groundwater age.

Tritium Units (TU)	Groundwater Age
<5	>50 years
5–8	10–50 years
8–12	5–10 years
12–30	Fusion explosion tritium
>30	Recharge in the 1960s

Source: Lindsey et al. [45].

). Its presence in groundwater often indicates recent recharge, especially due to the significant fluctuations in tritium concentrations in precipitation over the past few decades, primarily driven by nuclear testing. By measuring the tritium concentration in groundwater samples, the residence time of the water can be estimated. In this study, tritium dating was applied to samples from shallow and intermediate aquifers (<50 m depth) using the following equation:

$$\mathrm{Groundwater} \mathrm{age}={\displaystyle \frac{1}{\mathsf{\lambda }}}\ln {\displaystyle \frac{{\mathrm{A}}_0}{{\mathrm{A}}_{\mathrm{t}}}}$$

(1)

where groundwater age is expressed in years BP (Before Present), and λ is the decay constant (0.0563 year⁻¹). The natural logarithm (ln) is dimensionless. A₀ represents the initial tritium concentration in tritium units (TU). In this study, the initial tritium concentration (A₀) in precipitation, obtained from the Global Network of Isotopes in Precipitation (GNIP), was 2.4 TU [44]. A_t is the measured tritium concentration in the groundwater sample, also expressed in TU, and was determined through laboratory analysis.

2.3.2. Carbon-14 (C-14) Dating

Carbon-14 is suitable for dating groundwater up to 50,000 years old due to its half-life of 5730 years [35]. Groundwater can acquire carbon-14 through the dissolution of atmospheric CO₂ and soil carbonates (CO₃). The decay of carbon-14 in groundwater allows for estimating the time that has passed since the water last interacted with the atmosphere [46]. However, accurate groundwater age calculations require corrections for the reservoir effect, which may be influenced by the dissolution of rock carbonates or soil CO₂. This necessitates the inclusion of additional data, such as carbon-13 (C-13) isotope values and chemical analyses.

In this study, the corrected groundwater dating method was applied using the Pearson model [47], which relies on an isotopic mixing balance to determine A₀, the initial carbon-14 concentration in the recharge area. The model considers the mixing of carbon derived from soil gas CO₂ and dissolved calcite. The δ¹³C of TDIC (Total Dissolved Inorganic Carbon) was also measured. The δ¹³C value of soil gas CO₂ was −23‰, while the δ¹³C of solid calcite was 2‰, attributable to recrystallization or the influence of organic matter. [47,48]. This correction method accounts for the influence of dissolved carbonates and ensures more accurate age estimations by adjusting the apparent carbon-14 activity in the groundwater. The Pearson model applies the following equations for correction:

$${\mathrm{A}}_0={\displaystyle \frac{\left({\mathsf{\delta }}_{\mathrm{t}}-{\mathsf{\delta }}_{\mathrm{s}}\right)}{\left({\mathsf{\delta }}_{\mathrm{g}}-{\mathsf{\delta }}_{\mathrm{s}}\right)}}\times \left({\mathrm{A}}_{\mathrm{g}}-{\mathrm{A}}_{\mathrm{s}}\right)+{\mathrm{A}}_{\mathrm{s}}$$

(2)

where A_g and δ_g are the carbon-14 activity (100 pMC) and δ¹³C value (−23‰) of soil gas CO₂, respectively. The A_s (0 pMC) and δ_s (2‰ of typical marine carbonate sources.) are the corresponding values for dissolved calcite, indicating that the carbon contribution from the dissolution of old calcite does not add any modern carbon-14 to the system. The model thus estimates A₀ (pMC), the corrected initial carbon-14 concentration, based on the measured δ¹³C of TDIC, δ_t (‰).

$$\mathrm{Groundwater} \mathrm{age} \left(\mathrm{years} \mathrm{BP}\right)={\displaystyle \frac{1}{\mathsf{\lambda }}}\ln {\displaystyle \frac{{\mathrm{A}}_0}{{\mathrm{A}}_{\mathrm{t}}}}$$

(3)

Here, λ is the decay constant for carbon-14 (0.0001209 year⁻¹). A_t is the current carbon-14 concentration (expressed as a percent of modern carbon, pMC) in the groundwater, and A₀ is the corrected initial carbon-14 concentration (pMC) in the recharge area [47,49].

3. Results and Discussion

3.1. Tritium and Carbon-14 Concentrations in Groundwater

Groundwater samples were analyzed for tritium and carbon-14 concentrations and δ¹³C (

Table A1. Supplementary data for groundwater dating using tritium and carbon-14.

No	Easting	Northing	Sampling Date	Developing Depth (m)	H-3 (TU)	Stdev H-3	C-14 (pMC)	Stdev C-14	δ13C (‰ PDB)
1	602295	1839904	4-Jan-2021	14	1.4	0.2
2	600407	1842006	4-Jan-2021	50	0.9	0.2
3	616923	1851267	4-Jan-2021	30	0.1	0.2
4	613255	1851023	4-Jan-2021	67	0.2	0.2
5	608606	1848613	4-Jan-2021	30	0.1	0.2
6	606620	1843865	4-Jan-2021	15	1.2	0.2
7	605476	1847506	4-Jan-2021	40	0.9	0.2	89.84	1.30	−18.05
8	601125	1851004	4-Jan-2021	59	0.4	0.3	12.39	1.33	−14.22
9	605204	1850300	5-Jan-2021	56	0.4	0.3
10	609197	1850982	5-Jan-2021	52	0.1	0.1
11	616346	1855177	5-Jan-2021	30	1.1	0.2	101.18	1.06	−18.94
12	614400	1857277	5-Jan-2021	76	0.3	0.2
13	615984	1856135	5-Jan-2021	25	1.8	0.3
14	619555	1853641	8-Jan-2021	23	1.9	0.3
15	611270	1855997	8-Jan-2021	80	0.7	0.3
16	608074	1856158	8-Jan-2021	42	0.3	0.4	67.58	0.96	−16.76
17	602538	1855320	8-Jan-2021	60	0.4	0.2
18	603576	1859119	8-Jan-2021	90	0.0	0.3
19	606887	1858930	9-Jan-2021	18	1.2	0.3
20	610687	1858179	9-Jan-2021	18	0.0	0.2
21	623533	1846509	9-Jan-2021	18	1.8	0.2
22	609873	1841337	9-Jan-2021	40	0.4	0.3
23	609873	1841337	9-Jan-2021	51	1.8	0.4
24	602317	1851835	9-Jan-2021	70	0.0	0.3
25	620689	1845633	9-Jan-2021	8	1.0	0.2
26	617375	1850958	8-Jan-2021	70			101.92	1.99	−19.07
27	612589	1843856	8-Jan-2021	30			96.87	1.77	−18.01
28	494565	2090158	17-Mar-2021	124			23.70	4.10	−16.23
29	494565	2090158	18-Mar-2021	387	0.1	0.1	32.40	4.20	−17.49
30	502177	2086173	19-Mar-2021	58	0.5	0.2
31	506367	2083422	20-Mar-2021	90	0.1	0.2
32	513656	2077663	19-Mar-2021	103			33.90	4.50	−13.77
33	513656	2077663	19-Mar-2021	44	0.2	0.2	44.20	1.90	−15.06
34	515698	2069886	19-Mar-2021	186	0.4	0.2
35	515698	2069886	19-Mar-2021	129			46.10	4.70	−17.31
36	492321	2067271	13-Mar-2021	62	1.1	0.1	85.40	3.90	−16.46
37	492321	2067271	13-Mar-2021	120			90.20	2.60	−15.51
38	478978	2028598	13-Mar-2021	140			41.70	2.20	−14.42
39	478969	2028628	13-Mar-2021	130			63.20	2.40	−17.93
40	502240	2062079	15-Mar-2021	78			69.30	4.50	−16.95
41	502241	2062080	15-Mar-2021	148	0.1	0.1	44.00	3.00	−15.55
42	507631	2056658	15-Mar-2021	52			19.00	2.50	−14.65
43	507631	2056658	15-Mar-2021	136	1.6	0.2
44	491602	2072337	14-Mar-2021	195	0.2	0.2
45	481127	2056059	15-Mar-2021	62	2.1	0.2
46	481127	2056059	16-Mar-2021	116	2.0	0.2
47	488740	2054271	17-Mar-2021	134			21.10	2.70	−14.48
48	488736	2054268	18-Mar-2021	48	1.0	0.1
49	494401	2047786	15-Mar-2021	199	0.1	0.1
50	494065	2048101	15-Mar-2021	243			6.20	2.30	−11.25
51	494406	2047788	16-Mar-2021	73	0.2	0.2
52	497379	2043209	20-Mar-2021	194	0.1	0.1
53	497379	2043209	21-Mar-2021	119	0.2	0.1
54	497379	2043209	22-Mar-2021	152	0.7	0.2
55	497379	2043209	23-Mar-2021	52	0.8	0.2
56	467857	2040043	24-Mar-2021	122	0.5	0.2
57	473326	2033863	25-Mar-2021	172	0.2	0.1
58	480200	2026500	26-Mar-2021	140			41.70	2.20	−15.68
59	480200	2026500	27-Mar-2021	102			47.13	2.40	−18.22
60	607206	1812732	23-Jan-2021	60	0.2	0.2
61	612462	1813254	24-Jan-2021	39	0.4	0.1
62	631393	1809331	24-Jan-2021	30	0.1	0.1
63	640001	1802824	25-Jan-2021	32	2.0	0.2
64	651576	1800782	26-Jan-2021	18	0.1	0.1
65	607339	1824512	23-Jan-2021	42	0.1	0.1
66	617885	1825744	24-Jan-2021	60	0.1	0.1
67	631745	1823245	24-Jan-2021	60	0.1	0.2
68	622514	1839511	23-Jan-2021	46	0.1	0.1
69	640387	1809586	26-Jan-2021	56	0.2	0.2
70	640378	1802037	24-Jan-2021	48	0.4	0.1
71	666284	1808527	24-Jan-2021	42	0.2	0.1
72	560033	1828331	12-Sep-2021	142	1.6	0.1
73	598284	1820327	12-Sep-2021	148	0.8	0.1
74	630620	1822037	12-Oct-2021	80	2.4	0.1	71.90	2.00	−17.77
75	642749	1857853	12-Oct-2021	56			99.40	3.40	−17.74
76	628401	1859572	12-Oct-2021	60	0.5	0.1	48.10	1.70	−18.12
77	615894	1842075	12-Nov-2021	60	0.9	0.1	78.20	3.20	−19.46
78	606460	1854500	12-Nov-2021	149			29.50	2.60	−15.37
79	606450	1854524	12-Nov-2021	30	1.1	0.1	29.50	2.60	−16.54
80	565464	1797140	13-Dec-2021	104			22.90	1.40	−16.45
81	565464	1797139	13-Dec-2021	84	0.2	0.1	17.50	3.70	−14.48
82	565466	1797138	13-Dec-2021	46	0.9	0.1
83	588931	1803041	13-Dec-2021	102	1.2	0.1	46.80	1.70	−14.61
84	588923	1803030	13-Dec-2021	98	0.2	0.1	52.20	4.20	−15.36
85	575680	1803513	13-Dec-2021	30	0.7	0.1	12.83	1.06	−14.43
86	569101	1835841	14-Dec-2021	45	0.8	0.1
87	587830	1837715	14-Dec-2021	70	0.2	0.1
88	587753	1837671	14-Dec-2021	32	1.7	0.1
89	570318	1892276	14-Dec-2021	96	1.0	0.1	30.50	4.10	−17.84
90	600424	1878180	15-Dec-2021	70	1.1	0.1	14.60	2.50	−13.44
91	601285	1874112	15-Dec-2021	186	0.2	0.1
92	592532	1878578	15-Dec-2021	168	1.3	0.1	5.50	1.30	−11.06
93	624927	1888363	16-Dec-2021	162			33.10	4.00	−16.78
94	624930	1888358	16-Dec-2021	52	1.8	0.1	99.60	3.40	−17.74
95	596811	1891242	17-Jan-2021	52			8.10	1.60	−10.42
96	590809	1906861	18-Jan-2021	52			82.80	2.45	−18.40
97	568164	1914424	18-Jan-2021	20			99.10	3.80	−19.92
98	615890	1946465	18-Jan-2021	30			79.79	3.37	−14.90
99	606000	1945234	18-Jan-2021	42			59.72	4.83	−14.61
100	618401	1903197	20-Jan-2021	30			47.94	2.81	−17.27
101	613402	1883313	21-Jan-2021	42			51.94	1.92	−14.67
102	637176	1831754	21-Jan-2021	60			61.41	5.18	−15.24
103	621900	1834170	22-Jan-2021	113			30.18	4.51	−13.81
104	621900	1834170	22-Jan-2021	56			68.26	2.16	−19.00
105	605416	1798633	16-Jan-2021	50			63.16	2.75	−14.75
106	638241	1798138	22-Jan-2021	65			71.93	5.52	−14.97
107	667092	1807303	22-Jan-2021	30			81.63	2.20	−18.37
108	653553	1782015	23-Jan-2021	48			6.99	1.60	−13.92
109	616797	1711149	27-Jan-2021	42			80.40	2.40	−15.45
110	618191	1732662	26-Jan-2021	78			69.37	2.54	−19.44
111	661351	1771511	23-Jan-2021	67			81.96	2.16	−16.45
112	606054	1765319	26-Jan-2021	89	0.1	0.2	51.65	2.20	−16.31
113	609659	1774818	26-Jan-2021	40	0.5	0.2
114	575150	1780492	16-Jan-2021	32	1.2	0.2	52.43	2.24	−14.75
115	604589	1753438	2-May-2021	21	0.6	0.2	31.70	1.45	−15.40
116	569524	1806608	24-Apr-2021	33	0.1	0.2
117	555708	1823182	24-Apr-2021	42	2.2	0.3
118	596115	1917118	26-Apr-2021	39	1.7	0.2	89.90	1.90	−16.56
119	631390	1870695	30-Apr-2021	33	0.2	0.2
120	640586	1845299	30-Apr-2021	42	0.6	0.2
121	622871	2039417	14-Sep-2021	32	0.2	0.3	97.00	2.00	−19.66
122	623253	2038825	14-Sep-2021	72	1.5	0.3	99.77	2.32	−17.67
123	621272	2036557	14-Sep-2021	12	2.3	0.3
124	621832	2034942	14-Sep-2021	36	1.7	0.2
125	621233	2046692	14-Sep-2021	14	1.8	0.2	120.30	10.41	−16.52
126	621317	2046591	14-Sep-2021	4			106.35	5.32	−17.94
127	621317	2046591	15-Sep-2021	20	2.1	0.2
128	621586	2046636	15-Sep-2021	180	0.2	0.2	15.50	2.39	−13.70
129	627648	2043450	15-Sep-2021	76	1.8	0.2	65.50	1.95	−17.74
130	626116	2050358	15-Sep-2021	36	0.5	0.2
131	627180	2046388	15-Sep-2021	9	2.0	0.2
132	626816	2047687	15-Sep-2021	30	0.6	0.2
133	625751	2043475	15-Sep-2021	40	0.8	0.2
134	626165	2042467	15-Sep-2021	45	1.4	0.2	76.02	1.59	−15.57
135	626165	2042467	15-Sep-2021	10	2.2	0.2
136	625092	2041359	16-Sep-2021	90	1.7	0.2	100.45	0.86	−15.42
137	625827	2041013	16-Sep-2021	180	1.6	0.2
138	626211	2038685	16-Sep-2021	30	1.0	0.2
139	626211	2038685	16-Sep-2021	132	0.3	0.2	76.53	2.50	−19.54
140	626090	2034632	16-Sep-2021	132	1.0	0.2
141	624927	2035484	16-Sep-2021	90	0.1	0.2	3.22	0.92	−12.45
142	624927	2035484	16-Sep-2021	69	0.1	0.2	3.99	0.33	−13.92
143	624927	2035484	16-Sep-2021	64	0.2	0.2
144	627022	2032091	17-Sep-2021	63	0.8	0.3	57.33	1.91	−17.01
145	627380	2031290	17-Sep-2021	123	0.1	0.1
146	627184	2031357	17-Sep-2021	18	1.6	0.2
147	627385	2030987	17-Sep-2021	60	1.0	0.2
148	607872	2023187	17-Sep-2021	27	1.6	0.2
149	607872	2023187	17-Sep-2021	12	2.3	0.2
150	607872	2023187	17-Sep-2021	16	1.9	0.3
151	621846	2024819	17-Sep-2021	29	1.8	0.2	109.64	2.97	−19.85
152	623843	2023736	17-Sep-2021	47	1.0	0.2	102.45	2.63	−16.85
153	625848	2025284	17-Sep-2021	12	1.7	0.2
154	624088	2029109	17-Sep-2021	30	1.3	0.2
155	624385	2028802	17-Sep-2021	48	1.7	0.2
156	628901	2029253	18-Sep-2021	33	1.2	0.2
157	625938	2025702	18-Sep-2021	53	1.7	0.2
158	621317	2034606	18-Sep-2021	50	1.5	0.2	99.07	1.54	−17.31
159	621317	2034606	18-Sep-2021	18	1.7	0.2
160	620954	2036112	18-Sep-2021	5	2.0	0.2
161	624512	2034019	18-Sep-2021	30	1.9	0.3	99.11	2.09	−18.10
162	624512	2034019	18-Sep-2021	60	1.4	0.3	41.06	0.76	−17.39
163	624195	2034007	18-Sep-2021	46	0.8	0.2	27.84	2.00	−13.16
164	624195	2034010	18-Sep-2021	23	1.8	0.2
165	624865	2041542	18-Sep-2021	45	0.8	0.2	129.93	1.85	−16.93
166	625276	2040475	18-Sep-2021	78	1.3	0.2
167	623572	2033733	18-Sep-2021	6	1.7	0.2
168	625764	2034591	18-Sep-2021	30	0.8	0.2	96.78	1.64	−17.79
169	639889	20266232	18-Sep-2021	60	1.2	0.2
170	638076	2026324	18-Sep-2021	10	1.1	0.2
171	634709	2026451	18-Sep-2021	200	0.5	0.2	18.35	0.79	−14.04
172	632112	2024152	18-Sep-2021	19	2.0	0.2
173	632112	2024152	18-Sep-2021	198	0.4	0.2	65.35	1.47	−16.16
174	630702	2023828	18-Sep-2021	50	0.5	0.1	39.39	0.84	−14.30
175	634864	2022890	20-Sep-2021	230	1.3	0.2	73.62	1.26	−17.65
176	634864	2022890	20-Sep-2021	8	1.7	0.2
177	636183	2024199	20-Sep-2021	7	2.0	0.2
178	636183	2024199	20-Sep-2021	198	0.2	0.2	17.11	0.66	−13.77
179	623236	2022710	20-Sep-2021	30	1.4	0.2
180	624372	2019089	20-Sep-2021	44	0.2	0.3	99.56	1.63	−19.98
181	624377	2019080	20-Sep-2021	150	0.1	0.2	83.03	1.34	−19.05
182	626117	2019793	21-Sep-2021	72	1.8	0.3	101.68	2.72	−15.61
183	622460	2024278	21-Sep-2021	27	1.8	0.3
184	627971	2019533	21-Sep-2021	30	1.8	0.2
185	63877	2020145	21-Sep-2021	100	1.4	0.8	98.70	1.74	−19.34
186	623797	2023797	21-Sep-2021	4	1.2	0.3
187	624442	2021436	21-Sep-2021	70	1.4	0.3	98.85	2.66	−19.80
188	627414	2019269	21-Sep-2021	24	1.1	0.2
189	630972	2020641	21-Sep-2021	30	0.9	0.2
190	632484	2021391	21-Sep-2021	180	1.9	0.3	98.33	2.00	−15.66
191	627953	1999735	22-Sep-2021	100	1.2	0.3
192	628202	1999506	22-Sep-2021	100	0.9	0.2	52.09	1.18	−15.00
193	628202	1999506	22-Sep-2021	87	0.6	0.2
194	628129	1999875	22-Sep-2021	99	0.5	0.3	7.55	0.43	−10.42
195	628059	1999959	22-Sep-2021	78	0.8	0.4
196	628476	1998685	22-Sep-2021	120	0.5	0.3
197	624664	2004721	22-Sep-2021	86	0.7	0.2	82.02	2.22	−17.31
198	625402	2005049	22-Sep-2021	60	0.1	0.2
199	623993	2002952	22-Sep-2021	79	0.1	0.3
200	622338	2004296	22-Sep-2021	112	0.1	0.4	12.82	0.55	−14.46
201	622195	2005224	22-Sep-2021	120	0.1	0.3
202	620634	2006310	22-Sep-2021	56	1.2	0.2
203	620634	2006310	22-Sep-2021	64	1.2	0.2
204	620634	2006310	22-Sep-2021	98	0.7	0.2	89.03	2.41	−17.18
205	618553	2006553	22-Sep-2021	77	0.5	0.2
206	617397	2006751	22-Sep-2021	100	1.2	0.2
207	618770	2006243	22-Sep-2021	65	1.0	0.2
208	624442	2021436	22-Sep-2021	102			42.93	1.32	−18.20
209	627414	2019269	22-Sep-2021	143			26.11	0.89	−13.34
210	630972	2020641	22-Sep-2021	136			22.35	1.17	−16.66
211	632484	2021391	22-Sep-2021	96			42.33	1.19	−15.94
212	627953	1999735	22-Sep-2021	94			47.61	0.93	−16.70
213	628202	1999506	22-Sep-2021	65			69.54	2.02	−19.36
214	628202	1999506	22-Sep-2021	51			87.63	1.74	−16.60

). The mean tritium concentration was 1.08 tritium units (TU), with values ranging from 0.10 to 2.40 TU. Carbon-14 concentrations averaged 39.78 percent modern carbon (pMC), varying from 3.22 to 83.03 pMC. These isotopic values indicate a broad spectrum of groundwater ages, from recent recharge to water that has been isolated from atmospheric contact for thousands of years. The δ¹³C (‰ PDB) values from groundwater samples provided critical insights into the geochemical processes affecting carbon isotopic composition. These values ranged from −19.98‰ to −10.42‰, with an average of −16.24‰ ± 2.13‰ (Table A1), indicating variability in the sources of dissolved inorganic carbon (DIC) within the aquifers [27,36]. The most negative δ¹³C values, around −19.98‰, suggest contributions from biogenic carbon, typically associated with organic matter degradation. In contrast, less negative values, approaching −10.42‰, reflect the influence of carbonate dissolution, indicative of interactions with carbonate minerals present in the aquifers.

Several variables significantly influence the variation in tritium and carbon-14 concentrations across the region [30]. These factors include climatic conditions, geohydrological characteristics, and land use practices. The watershed experiences diverse rainfall patterns [38,39] (Figure 1b), which affect recharge rates (Figure 1c) and contribute to variable tritium levels. Furthermore, the complexity of the aquifer systems, which include deeper consolidated aquifers and shallower unconsolidated aquifers (Figure 2), contributes to the observed variability in isotopic concentrations. Agricultural activities, urbanization, and industrial processes also introduce contaminants that alter the concentrations of both isotopes, further contributing to this variability [13,49].

3.2. Tritium Concentration in Precipitation

Significant temporal variability was observed in the recorded tritium concentrations in rainfall at the Bangkok station between 1984 and 1991. An average concentration of 2.4 TU, with an average uncertainty of 0.3 TU, was observed during this period, with tritium levels ranging from 2.2 to 5.7 TU (Figure 3). The peak tritium concentration of 5.7 TU, recorded in June 1984, directly reflects the residual impact of historical atmospheric nuclear testing, primarily conducted during the mid-20th century [33]. These tests, particularly those from the 1950s and 1960s, introduced substantial amounts of tritium into the atmosphere [34]. Following these events, tritium was incorporated into the global hydrological cycle, resulting in elevated levels in precipitation and groundwater.

The elevated tritium levels recorded in the mid-1980s, including the peak in 1984, represent the lingering effects of atmospheric contamination. Although large-scale atmospheric nuclear testing had ceased by this time, the tritium released in earlier decades remained in the atmosphere, continuing to be deposited via precipitation. The gradual decline in tritium concentrations observed from the late 1980s onwards can be attributed to two primary factors: the natural radioactive decay of tritium and the cessation of atmospheric nuclear testing. As tritium decayed, its levels in the atmosphere and hydrosphere diminished, leading to a corresponding reduction in tritium concentrations in precipitation and groundwater.

The initial tritium level of recharge water is determined by the tritium concentration in precipitation [32]. Based on the fitted trend line in Figure 3, the lowest tritium value observed (2.4 TU) was used as the initial tritium concentration of recharge water in this study. This baseline is critical for estimating the age of groundwater in the Upper Chao Phraya basin. Lower tritium levels in groundwater indicate ancient water that has undergone radioactive decay, while higher levels correspond to more recent recharge events [50].

3.3. Correlation Analysis

The relationship between tritium and carbon-14 concentrations in groundwater samples was explored through a plotted analysis (Figure 4a). The correlation coefficient (r = 0.52) indicates a moderately positive correlation, suggesting that tritium and carbon-14 exhibit certain shared behavioral patterns within the hydrological system, despite their distinct environmental origins and residence times. This correlation implies that some groundwater samples contain both tritium and carbon-14 in measurable quantities, indicating the presence of waters that have experienced a mix of recent and older recharge events [51]. Such a phenomenon can occur in aquifers where waters from different recharge periods mix or in areas with complex flow patterns that allow partial renewal of older groundwater with newer inputs. The positive correlation suggests that processes contributing to recent recharge also facilitate the incorporation of atmospheric carbon, likely through mechanisms such as precipitation infiltration, which introduces both tritium and carbon-14 into the groundwater system [52]. Therefore, using multiple isotopic tracers is critical to capturing the full range of recharge dynamics. Incorporating both tritium and carbon-14 data can offer a more comprehensive understanding of groundwater age distributions and flow patterns.

A negative correlation (r = −0.41) was observed between tritium concentrations and groundwater depth (Figure 4b). This relationship suggests that shallower groundwater tends to have higher tritium concentrations, indicating more recent recharge. In contrast, deeper groundwater exhibits lower tritium concentrations, reflecting reduced exposure to recent atmospheric inputs and indicating older water.

Additionally, Figure 4c shows a negative correlation (r = −0.69) between carbon-14 concentrations and δ¹³C values. This strong negative correlation suggests that as carbon-14 concentrations decrease, δ¹³C values become more positive. This relationship reflects geochemical processes within the aquifer. Groundwater with lower carbon-14 concentrations tends to show more positive δ¹³C values, indicating a greater influence of biogenic carbon sources, such as the decomposition of organic matter [53]. Conversely, groundwater with higher carbon-14 concentrations typically exhibits more negative δ¹³C values, suggesting a stronger influence of inorganic carbon sources, such as carbonate dissolution [28].

Similar correlations between tritium and carbon-14 concentrations have been documented in other studies [27,29,31]. Likewise, the negative correlation between isotopic concentrations and groundwater depth has been observed in various regions [28,30,50]. However, the strong correlation between carbon-14 and δ¹³C underscores the significance of site-specific geochemical conditions in influencing isotopic signatures. Different geological settings and carbon sources can substantially affect the retention, mixing, and movement of isotopes within an aquifer.

3.4. Spatial Distribution of Tritium and Carbon-14

The spatial distribution of carbon-14 and tritium concentrations in the Upper Chao Phraya River Basin was analyzed. As shown in Figure 5a, the northern and upland regions of the basin have experienced more recent recharge, with higher tritium concentrations observed in these areas. In contrast, lower carbon-14 concentrations were noted in the central and southern parts of the basin (Figure 5b), indicating a longer residence time for groundwater in these regions, where atmospheric carbon has been absent from the system for extended periods [49].

The observed spatial patterns in tritium and carbon-14 distribution can be explained by the hydrogeological characteristics of the Upper Chao Phraya River Basin. The basin is primarily composed of alluvial deposits (Figure 5b), which facilitate the rapid recharge and movement of shallow groundwater. The presence of unconsolidated sediments allows for vertical percolation, explaining the higher tritium concentrations in shallow zones [54]. In deeper zones, however, vertical recharge is restricted by less permeable geological formations, resulting in lower tritium and carbon-14 levels, suggesting that groundwater in these areas is likely older [55].

The basin features diverse land use types (Figure 5a), including agriculture, urban development, and natural vegetation, each exerting distinct influences on groundwater quality and recharge [13]. Agricultural activities, particularly irrigation and fertilizer application, can enhance water infiltration into the soil, potentially increasing tritium levels in surrounding areas. In urban zones, where impervious surfaces dominate, recharge rates are typically lower, leading to isotopic signatures that differ from those in rural areas. Undisturbed natural vegetation zones offer valuable reference points for studying isotopic concentrations under natural recharge conditions [2,14].

Prioritizing the conservation of northern and upland areas in land use planning is essential for the long-term sustainability of groundwater resources in the Upper Chao Phraya River Basin. These regions are crucial to natural recharge processes due to their higher elevations, which typically receive more precipitation and contain geological formations that support vertical percolation. Consequently, these areas serve as primary recharge zones, where rainwater and surface runoff infiltrate the ground, replenishing aquifers that provide water for downstream use.

Maintaining the integrity of these recharge zones is critical to ensuring continuous and efficient aquifer replenishment. Land use planning should focus on conserving northern and upland areas to protect these vital zones from degradation caused by urbanization, deforestation, and agricultural expansion. Preserving natural vegetation and minimizing impervious surfaces, such as roads and buildings, can maximize water infiltration into the soil, thereby supporting the natural recharge processes that are essential for sustaining groundwater levels.

3.5. Groundwater Age and Recharge Patterns

Tritium concentrations in the Upper Chao Phraya River Basin indicate shallow groundwater ages, reflecting recent recharge events. A histogram (Figure 6a) shows groundwater ages for shallow depths (less than 50 m), ranging from a few months to 44.17 years BP (Before Present), with an average age of 18.26 years BP. A negative correlation between tritium levels and groundwater age was observed (Figure 6b), as expected given tritium’s half-life of 12.32 years [26].

The corrected carbon-14 ages for deep groundwater (greater than 50 m) show significant variability. A histogram of deep groundwater ages (Figure 6c) reveals a range from 115 to 22,899 years BP, with a mean age of 6688 years BP and a standard deviation of 5797 years BP. This wide distribution suggests complex recharge histories and prolonged residence times for deep groundwater. Many deep groundwater samples fall between 5000 and 15,000 years BP, indicating long periods of isolation from atmospheric carbon, consistent with the basin’s hydrogeological features (Figure 2). The carbon-14 content is inversely correlated with groundwater age (Figure 6d), with younger samples having higher carbon-14 levels and older samples showing significant decay over time [46]. This relationship validates carbon-14 as a tracer for long-term groundwater dating. The distribution of carbon-14 is influenced by geological and geochemical factors in the basin, where lower permeability at greater depths limits recharge, leading to older groundwater.

Corrected carbon-14 ages, calculated using the Pearson model, differ significantly from uncorrected values (Figure 6d). These differences highlight the importance of accounting for local geochemical conditions in isotopic age estimations. Groundwater’s dissolved inorganic carbon, sourced from the atmosphere, gradually decreases in carbon-14 concentration as it moves through subsurface environments due to radioactive decay [31]. Geochemical processes, such as carbonate dissolution and precipitation, further alter carbon-14 levels, affecting the accuracy of age determinations [11,46]. Interactions with carbonate-rich formations can introduce additional carbon-14, leading to artificially high concentrations and skewed age estimates, suggesting more recent recharge than occurred. Conversely, carbonate precipitation can reduce carbon-14 levels, giving the appearance of older groundwater than is accurate. The variability in environmental conditions—such as pH, temperature, and carbonate solubility—complicates groundwater age estimations based solely on carbon-14 concentrations.

Table 3. Groundwater age variability in the Upper Chao Phraya River Basin.

Depth (m Below the Surface)	Mean Pearson’s Model Age (Year BP)
50–100	2515 ± 845
100–150	5854 ± 2292
150–200	8121 ± 3293
200–250	9542 ± 3034
250–300	16,513 ± 4627

illustrates the progression of groundwater ages with depth in the Upper Chao Phraya River Basin. Groundwater at depths of 50 to 100 m has an average age of 2515 years BP. This age increases to 5854 years BP at depths of 100 to 150 m and rises to 8121 years BP at depths of 150 to 200 m. At depths of 200 to 250 m, the average groundwater age reaches 9542 years BP, and at depths of 250 to 300 m, it can reach up to 16,513 years BP. This trend highlights the impact of depth on groundwater residence time and the limited influence of recent recharge at greater depths. The geochemical evolution of groundwater is driven by processes such as mineral dissolution, ion exchange, and radioactive decay, which alter water composition over time [26,28].

Radiocarbon dating in groundwater systems is complex, especially in aquifers with intricate hydrogeological conditions. One challenge is the mixing of waters with different carbon-14 levels, leading to “apparent ages” that do not represent the true recharge history. Mixing older groundwater with low carbon-14 levels and younger water with higher concentrations can result in intermediate ages that obscure the actual dynamics of the aquifer. Variations in initial carbon-14 activity, due to changes in atmospheric carbon or localized geochemical processes, further complicate age determinations [46]. These variations create different baseline concentrations, making it difficult to establish a consistent reference for age estimates across the aquifer.

4. Conclusions

The study identified tritium concentrations ranging from 0.10 to 2.40 TU, with a mean of 1.08 TU, and carbon-14 concentrations ranging from 3.22 to 83.03 pMC, with an average of 39.78 pMC. These values suggest a wide range of groundwater ages, from recent recharge to water that has been isolated from atmospheric carbon for thousands of years. A positive correlation (R = 0.52) was observed between tritium and carbon-14 concentrations, indicating a relationship influenced by various factors, including well depth and geological properties. Tritium concentrations point to a shallow groundwater age distribution in the basin, with ages ranging from a few months to 44.17 years BP (Before Present) and an average of 18.26 years BP, indicating recent recharge, particularly in the northern and upland areas where tritium levels are higher. The corrected carbon-14 age using Pearson’s Model for deep groundwater (greater than 50 m) shows significant variability, with ages ranging from 114.95 years BP to 22,899 years BP and a mean age of 6688 years BP. A significant portion of the deep groundwater, with ages ranging from 5000 to 15,000 years, indicates long-term isolation from atmospheric carbon, consistent with the region’s hydrogeological characteristics.

Tritium and carbon-14 tracers effectively identify key recharge zones and assess long-term water reserves, providing critical insights into groundwater age and flow patterns. However, the dynamic nature of groundwater systems, driven by climate variability and human activities, necessitates continuous monitoring. Ongoing isotope tracing is essential for detecting changes and guiding management decisions. Strategies such as protected recharge areas, sustainable land use incentives, and public awareness campaigns can further enhance groundwater conservation and ensure long-term resource sustainability.