DOI: 10.57760/sciencedb.31436
title: Observation dataset of soil water, heat and salt dynamics in the Loess Plateau under different fertilization conditions in the 2023-2024 period
title: 黄土高原不同施肥下2023-2024年度土壤水热盐动态观测数据集

description: The dynamics of soil moisture, temperature and electrical conductivity in the dryland farming area of the Loess Plateau are key to regulating the farmland environment and influencing the stability of dryland ecosystems. Understanding the spatiotemporal variations of soil moisture, temperature and electrical conductivity is crucial for optimizing fertilization management measures. This dataset was derived from the Changwu Loess Plateau Agricultural Ecological Experiment Station in Shaanxi Province (107°40′30″E, 35°12′30″N), and is based on three key fertilization treatments in the corn and wheat continuous cropping systems, respectively: no fertilize (CK), application of nitrogen and phosphorus fertilizer (NP) and combination of NP and organic fertilizer (NPM). The data set recorded the dynamics of soil moisture, temperature and electrical conductivity in the surface layer (0-20 cm) from 2023 to 2024, with a total of 616 data points. CR800 data collector combined with RS-WS790 three parameter sensor were used for continuous automatic monitoring, and the collected data were calculated as daily average. During the monitoring period, drying method was used to measure soil moisture and thermometer was used to measure soil temperature for data quality verification. The dataset, based on the Changwu Loess Plateau Agricultural Ecological Experiment Station in Shaanxi Province, depicts the temporal evolution and response characteristics of soil moisture, temperature and electrical conductivity for wheat and maize under different soil fertility improvement models, filling the data gap of recent annual fine-scale observations of soil micro-environment in the Loess Plateau dryland area. This dataset provides fundamental data support for analyzing the regulatory mechanism of soil physical and chemical properties for maize and wheat by soil fertility improvement measures and crop types, and optimizing regional water and fertilizer management. It has significant academic and application value for deepening the theoretical research on dryland agricultural ecosystems and promoting the transformation of scientific research achievements.
description: The dynamics of soil moisture, temperature and electrical conductivity in the dryland farming area of the Loess Plateau are key to regulating the farmland environment and influencing the stability of dryland ecosystems. Understanding the spatiotemporal variations of soil moisture, temperature and electrical conductivity is crucial for optimizing fertilization management measures. This dataset was derived from the Changwu Loess Plateau Agricultural Ecological Experiment Station in Shaanxi Province (107°40′30″E, 35°12′30″N), and is based on three key fertilization treatments in the corn and wheat continuous cropping systems, respectively: no fertilize (CK), application of nitrogen and phosphorus fertilizer (NP) and combination of NP and organic fertilizer (NPM). The data set recorded the dynamics of soil moisture, temperature and electrical conductivity in the surface layer (0-20 cm) from 2023 to 2024, with a total of 616 data points. CR800 data collector combined with RS-WS790 three parameter sensor were used for continuous automatic monitoring, and the collected data were calculated as daily average. During the monitoring period, drying method was used to measure soil moisture and thermometer was used to measure soil temperature for data quality verification. The dataset, based on the Changwu Loess Plateau Agricultural Ecological Experiment Station in Shaanxi Province, depicts the temporal evolution and response characteristics of soil moisture, temperature and electrical conductivity for wheat and maize under different soil fertility improvement models, filling the data gap of recent annual fine-scale observations of soil micro-environment in the Loess Plateau dryland area. This dataset provides fundamental data support for analyzing the regulatory mechanism of soil physical and chemical properties for maize and wheat by soil fertility improvement measures and crop types, and optimizing regional water and fertilizer management. It has significant academic and application value for deepening the theoretical research on dryland agricultural ecosystems and promoting the transformation of scientific research achievements.