Soil information is valuable for many disciplines (e.g. agriculture, geomorphology, geology, archaeology) and can be used to produce maps or statistics on soil productivity. As part of the project CRC1070 ResourceCulture, we collected information on the soil quality in the Dohuk province of the Kurdistan region of Iraq. In total, 561 samples were collected at 136 locations in 2017, 2018, 2022, and 2023. These samples were collected at different depth increments (0 - 10, 10 - 30, 30 - 50, 50 - 70 and 70 - 100 cm) with an auger before being prepared and measured with mid-infrared (MIR) spectroscopy. Part of these samples (109) were selected to be analyzed in a laboratory, measuring texture, pH, organic and total carbon, nitrogen, sulfur, electrical conductivity, bulk density and calcium carbonate. A Cubist model was used to predict the remaining samples based on the MIR spectra. We then modelled digital soil mapping with machine learning methods (ensemble learning, linear regression, decision trees) for these soil components. Additionally, we mapped the soil depth using the information collected in the field. This dataset can help any researcher regarding soil information, forming a unique regional database.
Here, samples were air dried (35 - 45 °C) for 24 h; root fragments were removed and sieved (< 2 mm); for the CNS analysis (Ct, Nt and Corg, with Vario EL III, Elementar), samples were ground below 1 µm (Fritsch, Pulverisette 5/4, classic line). The texture was measured with wet sieving (2 - 0.063 mm fraction) and SediGraph III (Micrometrics) for the lower fractions (0.063 - 0.000063). pH was measured with a ProfiLine pH 3310 (WTW) in Kcl solution, while the CaCO3 was calculated using the calcimeter method. The conductivity was measured in micro siemens per second [µS/cm], with a Cond 330i/340i (WTW). Finally, we calculated the mean weight diameter of the aggregate (mm) based on the texture results and the following formula MWD=Xi∗Wi/100.
