Effects of physical and morphometric factors on nutrient removal properties were studied in small agricultural ponds with different depths, volumes, and residence times in western Japan. Average residence time was estimated to be >15 days, and it tended to decrease from summer to winter because of the increase in water withdrawal for agricultural activity. Water temperature was clearly different between the surface and bottom layers; this indicates that thermal stratification occurred in summer. Chlorophyll-a was significantly high (>20 μg/L) in the surface layer (<0.5 m) and influenced by the thermal stratification. Removal ratios of dissolved total nitrogen (DTN) and dissolved total phosphorus in the ponds were estimated to be 53–98% and 39–98% in August and 10–92% and 36–57% in December, respectively. Residence time of the ponds was longer in August than in December, and DTN removal, in particular, was more significant in ponds with longer residence time. Our results suggest residence time is an important factor for nitrogen removal in small agricultural ponds as well as large lakes.

INTRODUCTION

Small ponds and reservoirs have been used as important water resources in agriculture areas with little rainfall. However, intensive agriculture increases the load of nutrients such as nitrogen (N) and phosphorus (P) in surface water and groundwater, which often causes eutrophication and phytoplankton blooms in ponds and reservoirs (Burt et al. 1993; Vitousek et al. 1997; Carpenter et al. 1998; Gruber & Galloway 2008; Schindler 2012). Consequently, negative impacts such as clogging of irrigation facilities are observed on agricultural activities.

Seitzinger et al. (2006) have reported that a large but variable proportion of aquatic N removal occurs in freshwater ecosystems, including groundwater, wetlands, streams, and lakes. For sustainable water use in agricultural areas with little rain, greater understanding of the potential of nutrient removal in small ponds and reservoirs is required for effective management and enhancement of removal processes to improve water quality. In aquatic systems, it is essential to understand the hydrodynamic effect on transport processes of nutrients. Previous studies have reported that physical and morphometric factors such as water level fluctuations (Garcia de Emiliani 1997), changes in flushing rate (Vollenweider 1976; Garcia de Emiliani 1993; Boynton et al. 1995; De M. Huszar & Reynolds 1997), and water residence time (Olding et al. 2000; Valiela et al. 2000; Jones & Elliott 2007) play a role in influencing the nutrient condition and phytoplankton community composition in the surface water environment. Finlay et al. (2013) confirmed that N removal efficiency (NRE) via denitrification or permanent burial in lakes (mean depth, >20 m) was primarily influenced by water residence time, with longer residence times resulting in increased NRE. However, the mechanisms by which these factors affect nutrient removal in small agricultural ponds were not examined in detail in the previous studies.

In the present study, we aimed to examine the effects of physical and morphometric factors on nutrient removal properties in small ponds highly influenced by agricultural activity.

STUDY AREA

The study area is located on Ikuchijima Island, which is one of the islands on the Seto Inland Sea, western Japan (Figure 1(a)). The coastal area of the Seto Inland Sea is one of the lowest precipitation areas in Japan, and it is characterized by a temperate and marine climate. Onodera et al. (2007) reported that annual precipitation in the area has been decreasing by about 40 mm per decade over the last five decades, and they suggested an increased frequency of drought in the future. Many small ponds in the area are used as important water resources for agricultural activities.
Figure 1

Study area: (a) location of the study area, (b) Ikuchijima Island, and (c) study ponds and their watersheds.

Figure 1

Study area: (a) location of the study area, (b) Ikuchijima Island, and (c) study ponds and their watersheds.

Ikuchijima Island is characterized by a steep terrain and granite bedrock; the total area is 32.7 km2 (Figure 1(b)). Mean annual precipitation and temperature on the island are 1,100 mm and 15.6 °C, respectively. However, annual precipitation has ranged from 400 to 1,700 mm over the last four decades. Citrus trees such as orange and lemon are widely cultivated in more than 30% of the total area of the island. Annual input of N fertilizer in citrus farms is estimated to be 0.24 kg·m−2·year−1 (Saito et al. 2008). One dam and many small ponds can be found on the island. The dam is located in the upstream area of pond 3 (P3; Figure 1(c)), and it has about 416,000 m3 of storage capacity. The dam as well as the small ponds have been used for irrigation and crop protection in citrus farms. However, most of the small ponds are in eutrophic conditions and phytoplankton blooms occur especially in summer. To compare and examine the effects of physical and morphometric factors on nutrient condition and removal properties in the small ponds, field surveys were conducted using seven ponds (P1–P7) (Figure 1(c)). These ponds were selected because they were formed during the same period about 150 to 200 years ago; however, the ponds are characterized by different morphometric factors and scales such as water depths, volumes, and watershed areas (Table 1). P1 has the largest volume (>20,000 m3) among the seven ponds. P2 is located downstream of P1. P4, P5, P6, and P7 have relatively small watershed areas, water depths, and volumes. These ponds are also characterized by a higher coverage of citrus farms on the watersheds (Table 1).

Table 1

Morphometric and geographical information on the ponds

  Watershed area (104 m2Land use
 
Mean depth (m) Mean volume (m3Mean residence time (day) 
Citrus farm (%) Forest (%) River, dam & pond (%) Waste land (%) Building & structures (%) 
P1 110 32 66 5.4 21,002 62 
P2 222 35 64 2.2 4,237 15 
P3 117 14 85 3.4 8,982 52 
P4 82 18 2.0 1,256 17 
P5 10 65 35 2.1 1,449 2,348 
P6 28 41 43 16 1.9 3,212 378 
P7 74 24 1.4 1,397 35 
  Watershed area (104 m2Land use
 
Mean depth (m) Mean volume (m3Mean residence time (day) 
Citrus farm (%) Forest (%) River, dam & pond (%) Waste land (%) Building & structures (%) 
P1 110 32 66 5.4 21,002 62 
P2 222 35 64 2.2 4,237 15 
P3 117 14 85 3.4 8,982 52 
P4 82 18 2.0 1,256 17 
P5 10 65 35 2.1 1,449 2,348 
P6 28 41 43 16 1.9 3,212 378 
P7 74 24 1.4 1,397 35 

METHODS

We conducted sampling and measurements in the seven ponds (P1–P7) every three months between August 2012 and October 2013. Pond water samples were collected and water depth, vertical profiles of water temperature, electric conductivity (EC), and chlorophyll-a were measured using the CTD sensor (CTD Diver, Schlumberger) and chlorophyll sensor (INFINITY-CLW, JFE Advantech Co., Ltd) in the central part of the ponds. The vertical profiles were measured in approximately 10 cm intervals. Volumes of inflow and outflow of surface water to the ponds through channels were measured, and water samples were collected. These water samples were filtered using 0.2 μm cellulose ester filters in the field and stored in a freezer until analysis.

Bathymetric measurements were conducted in August and December 2012. Mean volume of the ponds was estimated using water depths in the two periods and the topography data analyzed by a geographical information system calculation tool. Residence time, also called retention time, is one of the first-order transport timescales commonly used for estimation of water-mass retention in aquatic systems. At a steady state, it can be simply estimated by dividing the volume with the flow in or out of the systems. We confirmed that the rates of inflow and outflow were nearly balanced in the study ponds during the observation periods. Therefore, mean residence times were estimated by dividing the volume of the ponds with the inflow rate. Thus, mean residence time indicates the time for displacement of pond water by the inflow in the present study.

In addition to temporal observations, water temperature was monitored at 30 min intervals at multiple depths from the surface to the bottom in four ponds (P1, P4, P6, and P7) between June and October 2013 by using temperature data loggers (HOBO Water Temp Pro v2; Onset Computer Corp., USA). As mentioned before, P2 and P3 are located downstream of P1 and the dam, respectively. This suggests that P2 and P3 are influenced by the inflow of water from P1 and the dam. In P5, mean residence time was estimated to be much longer (>2,000 days) than that in the other ponds because both inflow and outflow rates were significantly low. For these reasons, P1, P4, P6, and P7 were selected as typical ponds for further monitoring of water temperature. Concentrations of dissolved nutrients (N, P, and silica) in the water samples were analyzed using a spectrophotometric auto-analyzing system (SWAAT; BL TEC K. K., Japan).

RESULTS AND DISCUSSION

Residence time and variations in water temperature and chlorophyll-a

Estimated mean depth and volume of pond water were 1.4 m to 5.4 m and 1,256 m3 to 21,002 m3, respectively (Table 1). Mean residence time for water was estimated to be about 15 to >2,000 days, and it was much longer in P5 and P6. Saito et al. (2013) suggested that these two ponds are in a relatively stagnant condition because of little surface water inflow, except in the rainy season. Pond water volume and residence time tend to decrease from summer to winter. This suggests the effect of water withdrawal for irrigation and crop protection (Saito et al. 2013).

Figure 2 shows the variations in precipitation in the study area and water depths of the ponds (a) and water temperature in P1 and P7 (b) between June and October 2013. Water depth fluctuated between 4.0 and 6.5 m in P1 and 1.0 and 2.5 m in other ponds (P4, P6, and P7). It responded quickly to the variation in precipitation, especially at the end of August with 380 mm of total rainfall. Water temperature monitored at five different depths from the surface to the bottom is shown for P1 and P7 in Figure 2(b). The variation range for temperature was much larger in the surface layer, and it decreased towards the bottom. Besides, temperatures were clearly different between the surface and bottom layers before the end of August. These results indicate that thermal stratification occurred in summer. In winter, however, pond water was well mixed vertically, except for just under the surface (Saito et al. 2013).
Figure 2

Variations in precipitation and water depth in the ponds (a) and water temperature in P1 and P7 (b) between June and October 2013.

Figure 2

Variations in precipitation and water depth in the ponds (a) and water temperature in P1 and P7 (b) between June and October 2013.

Figure 3 shows the vertical profiles of water temperature (a) and chlorophyll-a (b) in P1, P4, P6, and P7 in October 2013. Both water temperature and chlorophyll-a were relatively high near the surface and decreased towards the bottom in all ponds. Chlorophyll-a exceeded 20 μg/L in the surface layer (<0.5 m) and was nearly 100 μg/L at some depths in the shallower ponds (P4, P6, and P7). On the basis of the classification of trophic state described by Carlson & Simpson (1996), these ponds were classified as eutrophic or hyper-eutrophic condition (mean chlorophyll-a, >14.3 μg/L). When compared with the results for December reported by Saito et al. (2013), chlorophyll-a in the surface layer was higher in October than in December. This suggests that primary production and nutrient uptake by phytoplankton are significant in the study ponds and that the existence of thermal stratification affects the distribution of phytoplankton. The temperature profile in P7 was unique, and it was lower than that in the other ponds with similar depth. This suggests that groundwater with lower temperature than pond water discharges from the bottom or side of the pond in P7. Little inflow of surface water to P7 suggests that the main inflow source of nutrients is attributable to groundwater.
Figure 3

Vertical profiles of water temperature (a) and chlorophyll-a (b) in the ponds in October 2013.

Figure 3

Vertical profiles of water temperature (a) and chlorophyll-a (b) in the ponds in October 2013.

Effect of residence time on nutrient removal properties

The budget of dissolved total nitrogen (DTN) and dissolved total phosphorus (DTP) was evaluated for the ponds in August and December 2012. Input and output of nutrients (kg/day) were estimated by the inflow and outflow volumes of surface water and nutrient concentration. The removal ratios of DTN and DTP were estimated by dividing the difference between input and output with input as a dimensionless indicator of nutrient removal efficiency in the ponds. Estimated DTN and DTP removal ratios were 53–98% and 39–98% in August and 10–92% and 36–57% in December, respectively. These results indicate that the ponds acted as a nutrient sink for the downstream environment. Regarding variation from August to December, nutrient removal efficiency was higher in August than in December. Figure 4 shows the relationship between residence time and the ratios of DTN removal (a) and DTP removal (b) in the ponds. The results show that residence time of the pond was longer in August than in December and that DTN removal was more significant in ponds with longer residence time (Figure 4(a)). Finlay et al. (2013) confirmed that ecosystem NRE (the proportion of TN inputs removed via denitrification or permanent burial) increases with an increase in residence time for large-scale lakes with mean depth >27 m and water residence time 1–191 years. Our results also suggest that residence time is an important factor for N removal in such small agricultural ponds. In addition, relatively high chlorophyll-a in the surface layer in October than in December suggests that nutrient uptake by phytoplankton is more significant in summer with strong thermal stratification. Conversely, the trend for DTP was not clear when compared with that for DTN (Figure 4(b)). In contrast to N, P is easily desorbed from sediments to a water column under anoxic conditions. This suggests that P supply from the bottom sediment possibly increases in ponds with longer residence time. The characteristics would cause a different trend for removal efficiency of N and P with changes in water residence time. Besides, Finlay et al. (2013) pointed out that NRE increases under P-rich conditions. This suggests that we need to consider the balance of N and P loads to the ponds for more information on nutrient removal properties.
Figure 4

Relationship between residence time and ratios of DTN removal (a) and DTP removal (b) in the ponds.

Figure 4

Relationship between residence time and ratios of DTN removal (a) and DTP removal (b) in the ponds.

CONCLUSIONS

In the present study, the effects of physical and morphometric factors on nutrient removal properties in agricultural ponds were evaluated in seven small agricultural ponds (P1–P7) with different depths, volumes, and residence times in western Japan.

Estimated water residence time tends to decrease from summer to winter because of the increase in water withdrawal for irrigation and crop protection. Water temperature was clearly different between the surface and bottom layers; this indicates that thermal stratification occurred in summer. Chlorophyll-a was significantly high in the surface layer and was influenced by the existence of thermal stratification.

Removal ratios of DTN and DTP were estimated to be more than 53% and 39% in August and more than 10% and 36% in December, respectively. These results indicate that the ponds acted as a nutrient sink to the downstream environment and that nutrient removal efficiency was higher in summer than in winter. Residence time of the ponds was longer in August than in December, and DTN removal was more significant in ponds with longer residence time. Our results suggest that residence time is an important factor for N removal in small agricultural ponds as well as large lakes.

ACKNOWLEDGEMENTS

The present study was financially supported by Grants-in-Aid for Scientific Research from JSPS (Principal investigator: Shin-ichi ONODERA, Research project number: 25241028) and MEXT Grant-in-Aid for Science and Technology Human Resource Development (Program to Disseminate and Secure the Tenure Track System, Okayama University). We are also grateful to Mr Daiki Aritomi for his help in field observations in the study area.

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