Natural and anthropogenic factors influence the entry of pollutants into surface waters and their accumulation in aquatic ecosystems. This study aimed to investigate precipitation and sediment concentration on the outflow of different forms of phosphorus (P) and nitrogen (N) in three primary land-use types along the Pasikhan River, the biggest river entering the Anzali Wetland in the Southern Caspian sea. Water sampling was performed on a monthly basis during the time bracket of 2017–2018. Different forms of P including total, soluble, particulate, total reactive, and dissolved reactive, and total Kjeldahl N, soluble N, particulate N, and were determined in the water samples. Total phosphorus and total Kjeldahl nitrogen contents lay within the range of 2.2–4.7 and from 0.14 to 0.33 mg l−1, respectively, downstream of the river. The highest monthly outflow of P from the watershed at the Agriculture station was recorded in October. Substantial conformity was found between the monthly trends of and and the trend of precipitation. The results indicated that sediment load intensified after an increase in the rainfall rate, leading to elevated N and P concentrations in the river water, mainly as particulate phosphorus and soluble nitrogen. It can also be inferred from the result that the concentration of N and P is directly related to the sediment concentration increase due to the rainfall. Increasing levels of nutrients such as N and P in the Pasikhan River can cause eutrophication in the Anzali Wetland, which needs conservative measures for reducing these elements' dynamic in the watershed.
The nitrogen and phosphorus concentrations in river water increase with precipitation.
The presence of agricultural lands is a detrimental key factor in contamination of Anzali Wetland.
The contamination of Anzali Wetland and river water is a time-dependent process, which reaches its highest level in the month of October.
Anzali Wetland is in an unfavorable condition.
total reactive phosphorus
dissolved reactive phosphorus
total Kjeldahl nitrogen
total suspended solid
trophic state index
The entry of pollutants into surface waters and their accumulation in the aquatic environment is influenced by natural and anthropogenic factors (Badruzzaman et al. 2012; Zhang et al. 2017; Ahmed & Ismail 2018; Dunca 2018). Many parameters affect the input load of pollutants to surface waters, including the source and location in the watershed, concentration, seasonal variations, and the bioavailability of the pollutants. Atmospheric precipitations, fertilizers application, industrial and domestic wastewaters, and agricultural effluents can serve as pollutant sources (Badruzzaman et al. 2012; Varol 2013; Alabdeh et al. 2020; Habeeb & Weli 2021).
Soil erosion and its transfer to the surface waters are complex multi-physics processes controlled by soil properties, hydrological conditions, and climatology. Erosion and delivery of field sediments (rill and inter-rill erosion) are considerably affected by the energy of raindrops and surface streams. Raindrops generate the main driving force to separate soil particles and surface streams carry those particles to the slopes. The contribution of these processes is strongly influenced by the topsoil nature, rainfall duration, and the amount of vegetation and crop residues at the ground level. Erosion is inversely related to soil cover and vegetation. Therefore, soil conservation will reduce soil erosion (Kilk & Rosner 1997). During the occurrence of surface runoff in cultivated lands, 80% of phosphorus losses were in the form of sediment bound (Sharpley et al. 1992).
On the contrary, less sediment is transferred through runoff flowing from grasslands, meadows, uncultivated soils, and forests. Hence, most of the transferred phosphorus (P) to the downstream is water soluble in that situation (Sharpley et al. 2003). During the movement of water on the inclined surfaces and slopes, soil and plant debris stemmed P dissolves in water and enters runoff. Schoumans & Chardon (2003) have concluded that biochemical changes of P and its degree of mobility in the soil determine the total amount of P loss. Li et al. (2020) showed that the concentration of nitrogen (N) and P in the river is directly related to sediment concentration and rainfall. As minerals and organic fertilizers, N and P are essential elements for plant growth (Fan et al. 2018; Mogollon et al. 2018; Li et al. 2020). On the other hand, they are also critically harmful elements for water systems. They reduce water quality due to the eutrophication phenomenon (Elser et al. 2007; Conley et al. 2009; Schindler et al. 2016; Longley et al. 2019). However, P is recognized as the most limiting factor for aquatic life (Sharpley et al. 2003; Davis et al. 2018). According to many local studies, P concentration showed spatial and temporal variations in some river waters in Guilan province, North of Iran (Asadi et al. 2018; Latifi et al. 2018). Many studies have also shown that P is transported in stream waters in various forms (Shoja et al. 2017; Asadi et al. 2018; Zhou et al. 2020). It is crucial to get a comprehensive insight into the status of different forms of N and P and their variations in the rivers' bodies to prevent the contamination of water resources. There are numerous case studies regarding the higher levels of N and P in the water resources (Wu et al. 2016; Asadi et al. 2018; Liu et al. 2019; Zhao et al. 2019; Ebrahimi et al. 2020).
Pollutants can be delivered to the natural waters through several ways in which the runoff is among the critical ones. Like many other parts of the world, the rainfall rate is high in northern Iran and the produced runoff discharge N and P from agricultural lands and other sources to the rivers. These harmful substances will lead to eutrophication phenomenon in the Anzali Wetland. This wetland holds health, tourism, economic, and social importance and serves as a prominent ecosystem constituent in the Caspian Sea countries. The Pasikhan River is the most important feeding source of Anzali Wetland. Identifying the pollution level and dominant forms of pollutants in this river is crucial for managing and rehabilitating the wetland. Many factors are marking the Paskihan river as a distinguished benchmark or a model for similar watersheds. Among them, one can point to erosion heterogeneity, high slope variations, and high diversity in land-use and vegetation cover (i.e., including paddy fields, urban and industry degraded rangeland, and dense forests).
Among the most important factors adversely affecting the phosphorus and nitrogen removal from the basin, one can point to changes in the vegetation, extent, and duration of precipitation. Vegetation cause changes in the depletion of particles and elements from the soil due to its contribution to the erosion rate and runoff reduction. In the case of rainfall, various characteristics such as duration, intensity, and droplet size have a considerable effect on the erosion and depletion of particles from the basin. Therefore, it is essential to acquire insightful data on the effect of precipitation extent and duration (in different vegetations) on the P and N emission to manage the basin better.
To the best of our knowledge, there is no comprehensive study on the effect of rainfall rate and sediment (load) concentration on temporal and spatial changes of different forms of N and P in the Anzali Wetland watershed. Therefore, the objective of this study was to (1) explore the role of sediment concentration and rainfall on the discharge of different forms of N and P, (2) investigate the time-dependent variation in discharge extent, and (3) evaluate the trophic state index (TSI), as a pollution classifier, of the river at different locations.
MATERIALS AND METHODS
As mentioned earlier, in the southern part of the Caspian Sea, Pasikhan River is the major contributor to feed the Anzali Wetland. Two main tributaries of the Pasikhan River are Imamzadeh Ebrahim River and Siahmazgi River; both originated from the mountain Lateberehne (mean elevation about 2,867 m) (Figure 1(a)). Both tributaries are flowing north-northeast and join about 19 km southwest of the Rasht city and form the Pasikhan River. There are three active hydrometric stations along the Pasikhan river located on lands of different types. One of them is named Forest 1 (on the Imamzadeh Ebrahim river), where the land cover is mainly forest. The other one is Forest 2 (on the Siahmazgi river), where the land type is forest and rangelands, and Agriculture (on the Pasikhan river), where the major part of the land is under agricultural use (Figure 1(a)). The geographical coordinates of the Pasikhan River are 41°8′–41°34′ longitude and 36°54′–37°27′ latitude. The length of the Pasikhan River in the studied area is 94.45 km, and its average slope is 3.08%. Residential areas and farmlands are primarily distributed along the river networks. The river watershed area is about 670.9 km2, its average elevation is 475.7 m, and its mean weight slope is 19.62%. The average annual rainfall (base on decennial reports) is approximately 1,557 mm. The land-use cover map of the Pasikhan watershed is shown in Figure 1(b). The southern part of the watershed has rangeland and forest land uses, while the northern part is mainly used for agricultural purposes. About 43, 61, and 73% of the watershed area are covered with forest land use in Agriculture, Forest 1, and Forest 2 sub-watersheds, respectively. Agriculture land use is also covered 38.64% of the studied watershed. The ratio of degraded rangeland in two sub-watersheds of Forest 1 and Forest 2 is 24.20 and 16.19%, respectively.
Water sampling and analysis
Sampling was performed monthly from November 2017 to October 2018 from the river water at three studied stations mentioned above. Four-liter river water was sampled each time, then immediately transferred to the laboratory in a sealed condition and stored at the temperature of 4 °C before the analysis. Two factors of pH and electrical conductivity (EC) of the samples were measured by pH meter and EC meter. Total suspended solids (TSS) in water samples were measured through a desiccation process at an elevated temperature in the oven (110 °C). The weight of solids was measured from weight loss before and after desiccation in oven.
Phosphorous exists in various forms in nature. However, only the phosphate () and orthophosphate () can be measured. Hence, the P in the water samples must be converted to phosphate and orthophosphate ions to be measurable. To do so, the potassium persulfate (K2S2O8) was used for sample digestion in the autoclave (121 °C, 150 kPa), and then total P (TP) concentration was measured through the ammonium molybdate reaction technique (Carlson & Simpson 1996). The measurement of total dissolved P (soluble phosphorus, SP) is similar to TP, except that samples must be filtered through Whatman 44 filter paper before digestion (Carlson & Simpson 1996). The amount of particulate P (PP) was calculated through the difference between TP and SP values. Total reactive P (TRP) and dissolved reactive P (DRP) were also measured using the ammonium molybdate reaction technique with ascorbic acid reduction (Murphy & Riley 1962). For TRP measurement, P in the water sample was directly measured with the molybdenum blue reaction using a spectrophotometer at 880 nm. The same method was followed to measure DRP, except that water samples were initially passed through a 0.24 μm filter.
Like many elements, nitrogen exists in various forms in nature. However, during the digestion procedure, all N-induced compounds in the sample are converted to ammonium sulfate to be measurable (Standard Analytical Procedures for Water Analysis 1999). Total Kjeldahl N (TKN) and soluble N (SN) were measured using their corresponding method, and particulate N (PN) was estimated from the difference between TKN and SN. The colorimetric method was employed to measure the concentration of ammonium () and nitrate () in the water samples (Varian, Cary-100).
All measurements were carried out in three replications, and mean comparisons were made through the Duncan method (P < 0.05) using the SPSS-20 software package. Data visualization, as well as correlation analysis, were performed using Microsoft Excel 2013. The GIS software package was also used to prepare the maps.
In this section, the analysis result of the acquired data is presented. The statistical characteristics of the studied parameters and their correlations, as well as the detail on the alteration of different forms of N and P contents, are presented. Finally, the condition of the watershed was classified considering different alternatives. These results are expected to be further used on the qualitative prediction of overall pollution condition of the Anzali watershed and the effect of major contributors.
Table 1 presents the statistical characteristics of the studied parameters in the Pasikhan River. The values attributed to each parameter are the average values taken in different months and at three sampling stations. The range of TP was 1.65–4.70 mg l−1, with an average of 3.04 mg l−1. The mean pH value (7.54) of the river water manifests weak alkalinity, and the range of TKN was 0.10–0.33 mg l−1. Moreover, the EC range was 0.22–0.97 dS m−1, with an average of 0.39 dS m−1.
|Parameter .||Unit .||Minimum .||Maximum .||Mean .||Std. Deviation .|
|Parameter .||Unit .||Minimum .||Maximum .||Mean .||Std. Deviation .|
pH, acidity; EC, electrical conductivity; TP, total P; SP, total dissolved P; PP, particulate P; TRP, total reactive P; DRP, dissolved reactive P, TKN, total Kjeldahl N; SN, soluble N; PN, particulate N; , ammonium; , nitrate.
Table 2 presents the Pearson correlation between the studied parameters. There was a negative correlation between pH and all forms of P (except PP) and N in the river water. Correlation between EC and all forms of N and P (except SP) was also significant (P < 0.05). Besides, a considerable correlation was seen between TKN and all forms of N and P.
|.||TP .||TRP .||SP .||DRP .||PP .||PH .||EC .||TKN .||SN .||PN .||.||.|
|.||TP .||TRP .||SP .||DRP .||PP .||PH .||EC .||TKN .||SN .||PN .||.||.|
*, ** indicate significant correlation at P < 0.05 and P < 0.01, respectively.
pH, acidity; EC, electrical conductivity; TP, total P; SP, total dissolved P; PP, particulate P; TRP, total reactive P; DRP, dissolved reactive P, TKN, total Kjeldahl N; SN, dissolved N; PN, particulate N; , ammonium; , nitrate.
P and N forms
Mean comparisons for different forms of P and N are presented in Figure 2. There were no significant differences (P < 0.05) between SP and DRP, and SN and concentrations in the river water. The predominant form of P in the studied river water found to be SP (Figure 3).
Monthly variations of different forms of P
Monthly variations in TP, SP, and PP concentrations at three stations of Forest 1, Forest 2, and Agriculture are shown in Figure 4. The ranges of TP variation at Forest 1 and Agriculture stations were 1.8–3.8 and 2.2–4.7 mg l−1, respectively (Figure 4(a)). The monthly averages of TP at the above-mentioned locations were 2.9 and 3.5 mg l−1. The highest monthly TP concentration (4.7 mg l−1) at the Agriculture station was observed in October (Figure 4(a)). Like TP, SP also reached its highest level at the Agriculture station. The results did not represent a specific trend for SP variation at the Forest 1 station. However, it showed an extreme peak in February and March at Agriculture and Forest 2 stations, respectively (Figure 4(b)). The PP variation at the Agriculture station lies within the range of 1.17–3 mg l−1. On average, the higher PP concentration was measured at the Forest 1 station (1.56 mg l−1) compared with the Forest 2 station (1.44 mg l−1) (Figure 4(c)). The highest amount of PP was observed at the Agriculture station in October (Figure 4(c)). The results showed that with increasing rainfall and TSS, the concentrations of TP, SP, and PP were also increased. The monthly trends of TP, SP, and PP almost followed the trend of monthly rainfall and TSS. From August to October, TSS was relatively constant, and precipitation and phosphorus outflow showed an increasing trend.
Monthly variations in TRP and DRP at different sampling stations are shown in Figure 5. As can be seen, the highest concentration of TRP was measured at the Agriculture station in May (2.13 mg l−1), and its lowest value was recorded at the Forest 1 station in June (0.63 mg l−1). The concentration of TRP was recorded the highest at the Agriculture station among the rests (Figure 5(a)). The concentration of DRP in the Pasikhan River varied from 0.02 (Forest 2 station in July) to 0.1 mg l−1 (Agriculture station in March) (Figure 5(b)). The highest DRP concentrations were measured in March and February at the Agriculture station. Like other forms of P, the DRP concentration was the highest at the Agriculture station. The average annual DRP concentration at the Forest 2 station (0.046 mg l−1) was slightly higher than its value at the Forest 1 station (0.042 mg l−1). Overall, the difference between measurements is highly dependent on the location when P concentration is high. Although a consistency was seen between the changes in monthly rainfall and TSS and monthly DPR changes, the TRP was not significantly affected by rainfall and TSS.
Monthly variations in different forms of N
Figure 6 shows the monthly variations in TKN, SN, and PN at different sampling stations. The highest concentration of TKN was measured at the Agriculture station in May (2.13 mg l−1). The Agriculture station had a higher TKN concentration among the rest due to the larger sub-watershed area and more agricultural, livestock, and residential wastewater drains entering the river upstream. The TKN range was 0.14–0.32 mg l−1 at the Agriculture station, with a monthly average of 0.20 mg l−1 (Figure 6(a)). The slight difference between the annual average TKN concentration at Forest 2 (0.15 mg l−1) and Forest 1 (0.16 mg l−1) stations was possibly due to the relative similarity of land cover and topography at these two sub-watersheds. The overall trend of SN changes was similar to TKN. The Agriculture station had more SN concentration than the other two stations (Figure 6(b)). The range of SN changes in the Pasikhan River varied from 0.08 (Forest 2 station in July) to 0.25 mg l−1 (Agriculture station in September). The PN changes are related to the TKN and SN changes, and as expected, the highest PN value was observed at the Agriculture station (Figure 6(c)). The PN level was lower than SN, which is attributed to the chemical properties and behavior of N. Its concentration varied in the range of 0.017 mg l−1 at the Forest 1 station (August) to 0.073 mg l−1 at the Agriculture station (September and February). Although the average annual PN concentration at Forest 1 (0.045 mg l−1) and Forest 2 (0.044 mg l−1) stations was almost the same, its concentration at the Agriculture station (0.055 mg l−1) was higher than the other two stations (Figure 6(c)). As shown in Figure 6, the results indicate that the changes in different forms of N (TKN, SN, and PN) are a function of precipitation.
Monthly variations of and at sampling stations are shown in Figure 7. The mean concentration of showed temporal variation at three stations and was the highest at the Agriculture station (Figure 7(a)). The range of concentration varied from 0.02 mg l−1 (in October at the Forest 1 station) to 0.11 mg l−1 (in September, July, and October at the Agriculture station). The average annual concentration of at Forest 1 (0.06 mg l−1) and Forest 2 (0.06 mg l−1) stations was nearly the same but lower than the Agriculture station (0.09 mg l−1). The range of temporal variation of at the Agriculture station was 0.06–0.11 mg l−1 (Figure 7(a)). concentration at the Agriculture station was significantly higher than the other stations, and its highest concentration (0.28 mg l−1) was observed in September (Figure 7(b)). The range of variations at the Agriculture station was 0.13–0.28 mg l−1, while its highest concentrations in Forest 1 (in September and October) and Forest 2 stations (in January) were 0.17 and 0.13 mg l−1, respectively. The similarity between these values at the above-mentioned stations over time was presumably due to their sub-watersheds' similarity.
Trophic state index
The TSI variations in the studied river are shown in Figure 8. According to the TN-based TSI, the studied river is in the mesotrophy–oligotrophy borderline state, while in September and October (numbers 11 and 12 on the X-axis), it is in the mesotrophy state. According to the TP-based trophy index, it is in an oligotrophic state, meaning that the precipitated P will be stored in the sediments.
Various sources have been identified as P inlet in the river water, including weathering of rocks, atmospheric precipitations (Holtan et al. 1988), wastewater effluents (Edwards & Withers 2008), road runoff (Edwards et al. 2007), and runoff from agricultural lands (Asadi et al. 2018; Houria et al. 2020). As presented in Table 1, the TP concentration is high in the Pasikhan River. According to Asadi (2016), the amount of P load entering the Anzali wetland through the Pasikhan River is considerably high, which confirms our finding.
It can be inferred from this study that the P loss from the watershed is a temporal–spatial function. In this regard, Latifi et al. (2018), Yang et al. (2013), and Spears et al. (2012) reported similar findings.
The results showed that the amount of P in the water is higher than the eutrophication phenomenon's critical level. Many researchers suggested the critical range of P concentration that causes harmful algae growth in water bodies as 0.01–0.015 mg l−1 (Smith et al. 1993; Foy & Withers 1998). There are also different critical boundary values for P concentration presented by researchers (Grover 1989; Neguyen & Sukias 2002; Sharpley et al. 2003). This study also showed that the N concentration in the watershed is below the critical value. According to the United States Environmental Protection Agency (USEPA 2000), the value of 0.59 mg l−1 can be the critical N limit for surface water. The results showed a significant difference between the concentration of various forms of N and P (Figures 2 and 3). This difference also depends on the chemical nature of these elements and the type of predominant erosion type in the watershed. In the studied area, all mentioned contributors are influential factors and may raise TP and TKN concentrations in the river water.
The cause for high phosphorus and nitrogen content in the river is the excessive consumption of chemical and organic fertilizers in the study area. Cultivated lands in this area mainly comprise rice, tea, and orchards, where farmers use fertilizer above the standard. Also, in pastures, due to high surface erosion and weathering of rocks, some phosphorus is added to surface runoff and subsequently to the river.
To further investigate the quantitative relation between different forms of N and P, the Pearson correlation was carried out. As presented in Table 2, a significant positive correlation between TKN and TP was found which is similar to Pu et al.’s (2018) report. A significant correlation between different forms of N was also found which can be seen in other research such as Zhang et al. (2017).
Another interesting finding was a strong correlation between pH and different forms of P. In general, pH change alters P forms. In the pH range of 4–7.5, surface adsorption is the primary retention mechanism of P on particles. Outside of this pH range, complexion of P with calcium and other metals are responsible (Heathwaite 1993). Reduction of the pH value may induce P release from Ca-/Mg-mineral structures in water bodies (Boström et al. 1988). After pH increases, OH− (hydroxyl) ion concentration increases, and it can be substituted with anions on iron oxyhydroxides as a ligand exchange mechanism (Cooke et al. 1993).
The higher TP and TKN concentrations at the Agriculture station compared with the two other stations (Figures 4 and 6) can be attributed to four critical factors. The higher level of precipitation, sediment concentration, land use, and self-purification are the main reasons behind this amount of TP and TKN in the Agriculture station. Various studies have shown that high N existence in the river is due to the overuse of chemical and organic fertilizers by farmers (Rasouli et al. 2014). Nitrogen-induced fertilizers efficiency in most paddy fields is only about 25–40% (Dobermann & Fairhurst 2000).
Many reports indicate that the presence of mineral nutrients at high levels in the soils of the eroded area is the main factor enriching river sediments (Mihara et al. 2005; Noori et al. 2011). Napoli et al. (2017) investigated the soil erosion rate and outflow of nutritional elements from the soil in Italian vineyards and concluded that the rate of mineral element loss increases with the increase in the erosive power of rain. The concentration of TP and TKN can be considered time-dependent values. They decreased in the spring season compared with winter, which can be attributed to more winter erosion. In the spring season, the area's vegetation cover was sufficient, and the severity of soil erosion was reduced. In August and September, more TKN was discharged from the watershed due to the high rainfall rate. In October, the amount of TKN decreased while the rainfall rate was still high, possibly due to the dilution effect and less dischargeable N from the watershed.
The predominant form of P was found to be PP, which accounted for 53% (average for three stations) of TP (Figures 2 and 3), also indicated by Asadi et al. (2018) and Asadi (2016). The level of PP and PN is highly dependent on the amount of suspended sediments in the river and is a function of the rainfall rate and the occurrence of erosion in the watershed. These landforms have degraded covers, and due to the high slope, they play an essential role in supplying sediment, PP, and PN. Considering that the sheet erosion rate and the transfer of soil particles decrease as the soil gets frozen. The higher slope of these rangelands also accelerated the soil erosion rate. Many studies (Han et al. 2019; Gao et al. 2020; Huang et al. 2020) have shown that soil erosion increases with slope. It is also observed that the PP discharge was increased with an increase in TSS.
Seasonal variation of nutritional elements is closely related to watershed soil characteristics. During particle transfer by runoff, many changes occur in the type, quantity, and quality of nutrients and organic matter. The difference between peak values of PP concentration at the Forest 1 sub-watershed and Forest 2 (Figure 4) can be attributed to more agricultural land use (3.18% more) and degraded rangeland (8% more) in Forest 1. Due to the lack of suitable vegetation cover and low organic matter content of the soil, surface erosion occurred in the degraded rangelands in the studied watershed, which causes the release of soil and PP. The amount of PN concentration decreased in all three stations in August when paddy fields left for a dry period to harvest rice; hence, there was no runoff. Liu et al. (2018) showed that PN accounts a tiny part of TKN, and in contrast to P, N binds less to soil particles, which is consistent with the results of this study.
A possible reason for SP increase in February and March could be low temperature and frost in upper parts of the watershed (mountains) (Figure 4). This can be confirmed by Asadi (2016). The concentration of SN decreased during the summer season (Figure 6) due to better land vegetation cover and lower rainfall rates, reducing soil erosion and the nutritional element leaching process. In general, SP and SN changes are similar to changes in monthly rainfall in the studied watershed.
The most reactive form of P, TRP, was accounted for 40% of TP in the Pasikhan River (Figure 3). Overall, as shown in Figure 5, the results indicate that TSS has increased with the rise in the rainfall rate, which has led to more TRP and DRP outflows. In January, February, and March, DRP outflows increased, which can be ascribed to weak forest and rangeland cover in the region during the winter season. It generally can be inferred that TRP variation is a function of time and location. Cooper & Thomsen (1988) reported that the range of DRP in different land uses varied from 14 to 38% of TP. The values of DRP reported by Shoja et al. (2017) for a semi-arid region are less than the values recorded in the temperate region in this study, which attributes to the less rainfall rate and less transfer of P from agricultural lands to the dam reservoir.
The concentration in the river water was lower than the concentration in this study (P < 0.05) (Figure 2(b)). This result is in full agreement with Liu et al. (2018), Dubrovsky et al. (2010), Heiskary & Lindon (2010), and Pu et al. (2018). Wall (2013) declared that TN also includes NO2− beside TKN and , and the predominant forms are and TKN, respectively. As the TKN includes dissolved (or NH3 in the aqueous phase), TN, the sum of TKN and , in river water was 0.61 mg l−1. However, in the present study, the TKN level in the river water was more than , possibly due to the higher organic matter load of the river water originated from agricultural land and eroded rangelands in the upper parts of the watershed. Sheet erosion in the rangelands occurred at a high rate annually, and soil particles with organic matter were transported to the river water and also reported similar results. The reason for the decrease in the level in March at the Agriculture station can be attributed to the slowing down of the river flow that provides binding to soil particles and sedimentation, as well as consumption by algae. Dunne et al. (2005) showed that in river water has high temporal variations and reaches its maximum concentrations in the autumn. dos Santos Simoes et al. (2008) specified that wastewater is a source of N pollution in water, which typically contains 60% of ammonia N. In the studied area, there are frequent domestic animal farms and wood industries with a potential role in ammonium pollution of the Pasikhan River water. Agricultural lands were regarded as the most important source of N in river water (Lai et al. 2011; Zhang & Huang 2011). The results of this study showed that has temporal variability. Noori et al. (2017) stated that water quality has temporal variations and is one of the most detrimental factors in river water quality. Due to the concentration of P and N in the river, its situation is in the borderline condition leading it to possibly reach a critical state over time.
The effect of precipitation and sediment concentration on the loss of various forms of N and P in Pasikhan River was investigated in this study. Statistical approaches were employed to find the possible correlation between N and P subsets and the mechanism of their transfer to the watershed. Based on the results, the highest concentration of various forms of P and N was measured at downstream of the watershed where it connected to the Anzali wetland. Considering the inevitable detrimental effects of these elements to the water system, it is crucial to investigate their transferring mechanism. Once the mechanism is found, controlling the delivery extent and optimizing the preventive approaches are feasible. The predominant forms of P and N were PP and SN, respectively. level in the river water was increased in some specific times of the year and adversely affected the river water quality. Overall, it was observed that increased rainfall caused severe surface erosion leading to an increase in sediment production. Besides, the increased water flow rate provided a considerable amount of energy and transfer capacity to carry various forms of N and P to the river waters.
The predominant sources providing N and P subsets in this study were agricultural lands and degraded pastures. In particular, P adhering to the particles is removed from the soil in those areas, and to control them, surface erosion mechanism should be given special attention. In the case of N contamination, fertilization should also be managed since N pollution is mainly related to chemical and organic fertilizers. Chemical fertilizer applications management, erosion control, and wastewater collection in the Pasikhan River watershed are essential factors to prevent P and N transport and are highly recommended to be considered.
According to the P trophy index, the studied river (Pasikhan) is at a high risk of trophy possibly imposing the Anzali Wetland to eutrophication. This trophy situation is due to the cumulative effect on other rivers in this area. To extend this study and to further reduce pollution in the Pasikhan River and the Anzali Wetland, appropriate erosion protection actions such as reducing runoff production, protecting the river wall, and restoration of destroyed rangelands need to be done.
The subject of plagiarism has been considered by the authors and this article is without problem.
AUTHOR CONTRIBUTION STATEMENTS
Eisa Ebrahimi, Hossein Asadi and Mohammad Rahmani conceived of the presented idea. Eisa Ebrahimi, Hossein Asadi and Mohammad Bagher Farhangi developed the theoretical framework. Eisa Ebrahimi, Hossein Asadi and Afshin Ashrafzadeh developed the theory and performed the computations. Hossein Asadi, Mohammad Bagher Farhangi and Afshin Ashrafzadeh verified the analytical methods. Eisa Ebrahimi and Mohammad Rahmani carried out the experiments.
All authors discussed the results and contributed to the final manuscript.
DATA AVAILABILITY STATEMENT
All relevant data are included in the paper or its Supplementary Information.