Dataset Description This dataset contains hydrological measurements collected from water bodies using multiple sensors. It is provided in two versions: an original dataset and a preprocessed dataset, enabling both raw data analysis and reproducible research workflows. Files Included • original_water_dataset.csv — raw measurements without preprocessing• preprocessed_water_dataset.csv — cleaned and transformed dataset ready for analysis Original Dataset The original dataset consists of 27,296 observations and 20 variables. It contains raw measurements collected directly from sensors without temporal aggregation or smoothing. Data Structure • Rows: 27,296• Columns: 20 Data Types • 18 float variables• 1 integer variable• 1 object variable (timestamp stored as string) Variables Description • water_id — Identifier of the measurement point or water body segment• time — Timestamp of the measurement (stored as string)• flowavg — Average water discharge calculated across sensors (flow1–flow4)• velocityavg — Average water velocity calculated across sensors (velocity1–velocity4) Sensor Measurements • depth1, depth2, depth3, depth4 — Water depth measured at different sensor levels• flow1, flow2, flow3, flow4 — Water discharge recorded by different sensors• temp1, temp2, temp3, temp4 — Water temperature recorded at different depths• velocity1, velocity2, velocity3, velocity4 — Water velocity measured at different points Preprocessed Dataset The preprocessed dataset contains 8,424 observations and 20 variables, obtained through temporal aggregation and smoothing techniques. Data Structure • Rows: 8,424• Columns: 20 Data Types • 1 datetime variable• 19 float variables Variables Description • time — Timestamp converted to datetime format and used as the dataset index• water_id — Identifier of the measurement point or water body segment • flowavg — Average water discharge calculated across sensors (flow1–flow4)• velocityavg — Average water velocity calculated across sensors (velocity1–velocity4) Sensor Measurements • depth1, depth2, depth3, depth4 — Water depth measured at different sensor levels• flow1, flow2, flow3, flow4 — Water discharge recorded by different sensors• temp1, temp2, temp3, temp4 — Water temperature recorded at different depths• velocity1, velocity2, velocity3, velocity4 — Water velocity measured at different points Preprocessing Steps The dataset was transformed using the following procedures: • Datetime ConversionThe time variable was converted into datetime format and used as the dataset index. • ResamplingThe data were aggregated to an hourly frequency using mean values:df_resampled = df[numeric_cols].resample('1h').mean() • Smoothing (Rolling Mean)A moving average with a window size of 3 was applied:df_roll = df_resampled.rolling(window=3, min_periods=1).mean() Purpose and Applications This dataset can be used for: • Time series analysis and forecasting• Hydrological modeling• Environmental monitoring• Seasonal pattern detection• Machine learning applications (e.g., regression, anomaly detection)