Research Data for “Sensor-based evaluation of superabsorbent polymer-amended growing media under treated-wastewater irrigation: water retention, irrigation performance, and salinity trade-offs"
Description
This dataset contains the research data supporting the study entitled “Sensor-based evaluation of superabsorbent polymer-amended growing media under treated-wastewater irrigation: water retention, irrigation performance, and salinity trade-offs.” It includes preliminary and main soil-moisture monitoring records, ambient temperature and relative-humidity measurements, raw gravimetric water-holding-capacity measurements, irrigation-event records, and a Python script for reproducing the irrigation-performance and WHC analyses. The treatments consisted of peat–sand growing media amended with 0%, 2%, 4%, and 6% (w/w, dry basis) sodium polyacrylate-based superabsorbent polymer, designated S1, S2, S3, and S4, respectively. During the 27-day treatment-specific monitoring phase, sensor-derived relative soil moisture was recorded at 30-min intervals, and irrigation events were identified from abrupt increases of ≥5 percentage points in the relative soil-moisture time series. Each irrigation event corresponded to a fixed application of 50 mL treated wastewater. The dataset supports the evaluation of dose-dependent changes in water retention, moisture-depletion behavior, irrigation frequency, irrigation interval, and cumulative irrigation water application under treated-wastewater irrigation.
Files
Steps to reproduce
The main irrigation dataset contains 30-min measurements of ambient temperature, relative humidity, and sensor-derived relative soil moisture for four treatments: S1 (0% SAP), S2 (2% SAP), S3 (4% SAP), and S4 (6% SAP). Irrigation events were identified as abrupt increases of at least 5 percentage points in the sensor-derived relative soil-moisture time series. A fixed volume of 50 mL of treated wastewater was applied at each irrigation event. Irrigation frequency was calculated as the total number of detected irrigation events, mean irrigation interval as the mean elapsed time between consecutive irrigation events, and total irrigation water applied as the number of irrigation events multiplied by 50 mL. Percentage changes were calculated relative to S1. Gravimetric water-holding capacity (WHC) was determined from four replicate measurements for each SAP application rate. WHC data were summarized as mean ± standard deviation and analyzed using one-way ANOVA followed by Tukey’s HSD test. To reproduce the analyses, place “02_Main_Irrigation_Records.xlsx” and “03_Water_Holding_Capacity_Raw.xlsx” in the same folder as “04_Analysis_Reproduction.py” and run the Python script. The script requires pandas, numpy, and scipy; statsmodels is additionally required for Tukey’s HSD test.
Institutions
- Bilecik Şeyh Edebali ÜniversitesiBilecik, Bilecik