SOIL COLUMN STUDY WITH POLYMER GEL

Transcription

1 SOIL COLUMN STUDY WITH POLYMER GEL FINAL REPORT Submitted to USDA WATER MANAGEMENT INTERNSHIP PROGRAM MAY 15, 2013 NAME: JAIDEEP CHOWDHURY UNVIERSITY NAME: CALIFORNIA STATE UNIVERSITY, FRESNO TIME PERIOD: January - May 2013 ADVISOR S NAME: PATRICK BARNES ORGANIZATION: CALIFORNIA WATER INSTITUTE, CALIFORNIA STATE UNIVERSITY, FRESNO

2 TABLE OF CONTENTS 1. ACKNOWLEDGEMNTS 2 2. INTRODUCTION OBJECTIVE RESEARCH MOTIVATION PREVIOUS EXPERIMENTS AND RESULTS HYDROGEL 6 7. MATERIALS AND METHODS DARCY S LAW RESULTS CONCLUSION APPENDIX A

3 ACKNOWLEDGMENTS This project was supported by Agriculture and Food Research Initiative Competitive Grant no from the USDA National Institute of Good and Agriculture. I would like to thank my advisor Patrick Barnes for constant guidance throughout the internship and providing equipment and laboratory needed for the internship. Whenever I was stuck or needed help, Patrick Barnes was there. Additionally, I would like to acknowledge other researchers at the Center for Irrigation Technology and California Water Institute for proper guidance. Special thank goes to University Enterprise Corporation at California State University, San Bernardino, for their support. 2

4 INTRODUCTION California Water Institute at California State University, Fresno conducts a study to explore the influence of the liquid and dry particle gel on hydraulic conductivity in the soil domain. The trials were conducted on one soil type (Center for Irrigation Technology sandy loam) in the columns at three different depths of 6,9, and 12 inches below the soil surface of the column. OBJECTIVE The primary objective of this study was to evaluate the effect of the hydrogel products on hydraulic conductivity and in the soil domain and under soil wetting through flow under a constant pressure head. RESEARCH MOTIVATION Over irrigation, soil salinization and leaching of nitrate into groundwater continue to be issues of great concern in the San Joaquin Valley. It is estimated that roughly 80 lb. /N/acre/year leach into the groundwater (Harter 2009) in irrigated lands in California. This has led to a continued interest in developing agronomic practices and products that can improve crop water use efficiency and optimize nutrient uptake, which includes the development of polymers to improve water and nutrient retention in the root zone of a crop. However, a lack of research on the viability of these products highlights the need for continued investigation in the lab and at the field scale. A recent study at CSUF have been completed a preliminary trial to evaluate the use of a polymer gel and its effect on yield of fresh tomatoes under drip irrigation. The results of this 3

5 study prompted us to conduct another experiment in the laboratory to observe the effects of these polymers on hydraulic conductivity in the soil at varying depths of product application. PREVIOUS EXPERIMENT AND RESULTS The experimental trial was conducted in a field site. The size of the study area was approximately 16,900 square feet and contained largely sandy loam soils. The field was divided into 36 plots split evenly between control and treated plots with an additional three control plots that received no fertilizer. The control plots received the same rates of irrigation water and fertilizer but without any gel applied. A total of twelve treatment combinations were employed in this study where irrigation amounts to account for 100 and 75 percent evapotranspiration (ET) were paired with 200 and 150 lbs/acre rates of fertilizer respectively. The plot layout describing different irrigation and fertilizer treatments are shown in Figure 1,where F1 = 200 lbs/acre N, F 2 = 150 lbs/acre N, E 1 =100% ET, E 2 =75% ET, C=Control (no gel), T 1 = 30 kg/acre of polymer gel, and T 2 =10 kg/acre 4

6 West 30 ft 20 ft 30 ft 20 ft 30 ft 130 ft North 130 ft 10 ft 10 ft 10 ft 10 ft 10 ft 10 ft 10 ft 10 ft 10 ft 10 ft 10 ft 10 ft 10 ft T 1 E 1 F 1 1 CE 2 F 1 1 T 1 E 2 F 1 2 T 1 E 1 F 1 2 T 2 E 2 F 1 1 T 1 E 1 F 2 2 T 2 E 1 F 1 1 CE 2 F 1 2 T 1 E 1 F 2 1 CE 1 F 2 2 CE 2 F 1 3 T 2 E 2 F 1 3 Buffer: to be planted but without any moasis Product Buffer: to be planted but without any moasis Product T 2 E 1 F 2 1 T 1 E 2 F 2 2 CE 1 F 1 1 T 1 E 2 F 2 3 T 1 E 2 F 1 3 CE 1 F 2 1 E 1 E 2 T 1 E 1 F 2 3 T 2 E 2 F 2 3 CE 1 F 2 3 T 2 E 1 F 2 2 T 1 E 2 F 2 1 CE 2 F 2 2 Buffer: to be planted but without any moasis Product Buffer: to be planted but without any moasis Product CE 1 F 1 2 CE 2 F 2 3 T 2 E 2 F 2 2 CE 1 F 1 3 CE 2 F 2 1 T 1 E 1 F 1 3 T 2 E 1 F 1 3 T 1 E 2 F 1 1 T 2 E 1 F 1 2 T 2 E 1 F 2 3 T 2 E 2 F 1 2 T 2 E 2 F 2 1 Figure 1 : Plot Layout describing different irrigation and fertilizer treatments F 1 = 200 lbs/acre N, F 2 = 150 lbs/acre N, E 1 = 100% ET, E 2 = 75% ET, C = Control (no gel), T 1 = 30 kg/acre ofpolymer gel, and T 2 = 10 kg/acre The harvested tomatoes were graded into red, breaker, diseased, and non-marketable varieties. All the data were processed using Microsoft Excel for tabulation and graphing purposes. Because some trends were observed, a paired t-test was utilized to determine if the differences in the parameters of interest were statistically significant. The findings are as follows: 1. When the raw biomass of all tomatoes was totaled, the treated plots showed a greater weight for green, breakers, disease and non-marketable fruits (Figure 3). 2. Increases in weight of green tomatoes reached 52% and 35% at 30 and 10kg/acre of gel respectively with 100% ET and 200 lbs/acre N (Table 2). These differences decreased to -70% and 2% when 150 lbs/acre N was used. 3. For both treated and control plots, non-marketable tomatoes were produced in the largest numbers. Despite this, average of extrapolated yields for all treatments (Table 4) was 5

7 above the average in California for Fresh Market Tomatoes of 12.5 tons/acre in 1999 (source: 4. Two Pair t-test results: a. A statistically significant decrease in count and weight of green tomatoes was observed at 100% ET and 150 lbs/acre N with 30 kg/acre of gel applied. b. A statistically significant decrease in the number of green tomatoes was observed at 75% ET and 150 lbs/acre N with 10 kg/acre of gel applied. c. A statistically significant increase in the number and weight of diseased tomatoes was observed at 100% ET and 150 and 200 lbs/acre N for both gel treatments d. A significant increase in the weight of non marketables was also observed at 100% ET and 200 lb/acre with 10 kg/acre of gel applied. 5. Recorded plant data from six plants in each experimental plot show consistently greater height and width in the treated plots at 100%ET/200lbs/acre N and 75% ET/150 lbs/acre N (Figures 12-13, 18-19). HYDROGEL Hydrogel is a network polymer chains that are water-insoluble, sometimes found as a colloidal gel in which water is the dispersion medium. Hydrogels are superabsorbent (they can contain over 99% water) natural or synthetic polymers. Water absorbing polymers which are cross-linked are often classified as hydrogels. Hydrogels absorb aqueous solutions through hydrogen bonding with water molecules. A Super Absorbent polymers ability to absorb water is a factor of the ionic concentration of the aqueous solution. 6

8 MATERIALS AND METHODS A total of 18 soil columns (height: 24 in., diameter: 4.5 in.) were used to test one soil type (CIT sandy loam) and a number of polymer gel product applications. The chunks of the collected soil needed to be grinded into fine particles and transferred in foil containers for drying. Each container was kept within a dryer for hours till the soil gets dried completely.the columns were filled with the dried soil and it was made sure that the soil was packed tightly within the columns. These columns were used to create three replicates of each treatment. These treatments included three control columns where no product was applied and three columns each with dry gel applied at 6, 9, and 12 inches below the surface. For the liquid gel, the product was applied at depths of 6 and 12 inches. Application rates were grams/column or 10 kg/acre for the dry gel and 0.26 grams/column or 100 liters/acre of the liquid gel (based on the density of the product). Before applying the product, 30 ml of water was added to each column to wet the application site s surface area uniformly. For the liquid gel, 15 ml was mixed with the product to add it to the column while an additional 5 ml was used to thoroughly rinse each vial and apply the remaining product. To ascertain the water discharge rate, records were kept of the volume of water that left the system every 24 hours (shown in Table A). Two tanks were used to provide the columns with water. Both tanks were located at an identical fixed elevation above the columns to supply a constant pressure head to the columns below. Darcy s Law was used to convert the flow rates into hydraulic conductivity values shown in Figures 1 and 2. The data were recorded until the system was able to achieve a steady state of flow (after 34 days). 7

9 The columns setup that is used for our research is shown in Figure 2: Figure 2: Columns Setup 8

10 DARCY S LAW Henri Darcy established empirically that the flux of water through a permeable formulation is proportional to the distance between top and bottom of the soil column. The constant of proportionality is called hydraulic conductivity (K). V=Q/A, V - h and V -1/ L Where Q is flow rate; V is the specific discharge (Darcy velocity); A is total cross-sectional area of material Thus, V= - K( h/ L) and since Q=V*A Hence, Q= -K*A*(( h/ L) K represents a measure of the ability for flow through porous media. Darcy s Law holds for saturated and unsaturated flow, and also steady-state and transient flow. It allows an estimate of: The velocity or flow rate moving within the aquifer The average time of travel from the head of the aquifer to appoint located downstream. Darcy s law provides an accurate description of the flow of ground water in almost all hydro geologic environments. 9

11 RESULTS Each treatment exhibited a difference in saturated hydraulic conductivity over time. This difference was largely a decrease in saturated hydraulic conductivity with product application. On average, only treatment 6D showed an increase in hydraulic conductivity when compared to the control columns. Average percent difference for each treatment is shown in Table B. At a 95 percent confidence interval, based on the Pearson correlation and p-values, we can see that there was not a statistically significant difference between treated and control columns for treatments 6D and 9D. Conversely, for treatments 6L, 12D, and 12L, we can reject the null hypothesis and conclude that there is a statistically significant difference between treated and control columns in each treatment case. CONCLUSION From the results, it can be concluded that there was a significant difference between columns that contained the product and those that did not. However, further studies are required to better ascertain the extent of this difference between application rates. This internship provided an opportunity for research experiences, developing analytical skills and professional development that one needs in industry. In addition, individuals who have background in physical and engineering field with master s degree support the agency research mission. Physical Science Technician with electronics and programming knowledge background provide direct support to the research scientists in completing their scientific research projects. Research Technicians are critical to the completion of many research projects. I am interested in ARS employs professional, administrative and technical employees in Architecture & Engineering, and Program Analysis & Information Technology USDA career path. 10

12 APPENDIX A Table A: Percolation rate values from the soil column trials Percolation rate for varying soil columns over time (ml/day) (± SE) Treatment Day Control 6" - Dry Gel 6" - Liquid Gel 9" - Dry Gel 12" - Dry Gel 12" - Liquid Gel (71.6) 575 (36.3) 376 (232) 634 (151) 835 (387) 499 (88.6) (35.8) 529 (144) 265 (147) 493 (118) 576 (246) 362 (74.1) (44.6) 452 (155) 206 (102) 404 (93.9) 493 (222) 288 (62.1) (38.8) 407 (120) 202 (67.2) 357 (72.5) 461 (219) 256 (43.8) (24.3) 359 (104) 178 (59.3) 298 (58.4) 420 (203) 219 (32.4) (17.6) 353 (92.9) 165 (31.7) 309 (26.4) 397 (182) 223 (26.8) (14.8) 324 (103) 177 (35.5) 272 (51.2) 382 (172) 206 (42.5) (21.2) 346 (76.4) 173 (31.1) 257 (45.5) 366 (156) 217 (27.1) (19.6) 332 (76.2) 187 (39.2) 255 (48.8) 348 (144) 210 (22.6) (17.6) 325 (76.4) 182 (40.3) 245 (47.8) 335 (139) 202 (21.7) (21.7) 303 (73.9) 157 (40.3) 225 (46.2) 319 (118) 192 (19.5) (19.1) 278 (72.4) 144 (36.0) 207 (41.8) 278 (117) 177 (9.20) (13.8) 278 (69.9) 153 (36.3) 212 (41.0) 277 (112) 158 (27.0) (13.3) 285 (69.2) 152 (38.6) 204 (43.7) 278 (114) 200 (19.3) (14.2) 281 (64.6) 158 (31.2) 216 (44.2) 275 (110) 202 (25.4) (11.3) 283 (65.8) 161 (30.3) 216 (41.6) 275 (104) 197 (23.9) (8.8) 281 (66.5) 162 (31.6) 216 (39.7) 268 (102) 195 (23.4) (7.7) 269 (65.1) 146 (34.8) 204 (37.8) 269 (95.8) 183 (20.1) (9.2) 267 (70.7) 141 (35.6) 196 (39.0) 261 (113) 168 (24.2) (6.2) 260 (67.8) 144 (36.4) 192 (38.5) 256 (104) 185 (37.7) (6.3) 259 (61.3) 138 (34.7) 194 (37.3) 246 (103) 191 (37.9) (6.3) 256 (58.8) 141 (34.6) 191 (36.2) 249 (103) 188 (35.3) (16.2) 263 (68.4) 131 (28.0) 170 (36.2) 245 (101) 181 (27.7) (24.2) 271 (71.3) 137 (29.5) 171 (34.8) 259 (116) 181 (28.6) (23.2) 270 (76.1) 137 (34.9) 173 (35.2) 245 (96.5) 177 (29.7) (23.7) 265 (75.4) 136 (29.1) 173 (34.3) 232 (91.5) 167 (28.6) (21.6) 272 (75.9) 137 (33.0) 178 (33.3) 237 (89.7) 172 (30.6) (21.5) 263 (77.0) 128 (30.4) 173 (32.9) 225 (90.4) 163 (29.1) (20.1) 269 (75.8) 144 (35.5) 181 (36.2) 236 (93.5) 176 (28.2) (19.0) 272 (80.8) 144 (31.8) 188 (30.3) 236 (90.6) 174 (29.9) (18.7) 270 (83.3) 134 (34.2) 178 (34.2) 234 (92.3) 168 (33.8) (20.7) 278 (83.4) 141 (30.3) 181 (32.9) 235 (91.5) 170 (32.3) (15.6) 271 (86.6) 127 (33.1) 178 (35.3) 258 (99.9) 167 (34.1) (28.3) 279 (87.8) 133 (34.0) 182 (34.2) 248 (109) 170 (34.6) 11

13 Saturated Hydraulic Conductivity (cm/day) Saturated Hydraulic Conductivity (cm/day) K sat Values in Treated and Control Columns Day Ctrl 6D 6L 9D 12D 12L Figure 3 : Observe K over time in treated and control column for all treatments K sat Values in Treated and Control Columns Day Ctrl Dry gel Avg Liquid Avg Figure 4 : Observed K averages for dry and liquid gel vs. control over time (6-in. and 12-in. depths) 12

14 Q (ml/day) Discharge (Q) Values in Treated and Control Columns Day Ctrl Dry gel Avg Liquid Avg Figure 5 : Observed Q averages for dry and liquid gel vs. control over time (6-in. and 12-in. depths) Table B: Results of statistical test and observed percent difference in K sat t-test: Paired Two Sample for Means (Results) Treatment Pearson Correlation p-value % Reduction in K sat 6D % 6L E % 9D % 12D E % 12L E % 13