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Data · dataset · 2026

Dataset on Water Quality Status of Farmland Irrigation Sources in Eastern Henan Region of the Huang-Huai Plain from 2008 to 2020

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Irrigation water quality is a core element that affects the stable development of agricultural ecosystems.

Description

Conducting long-term monitoring of irrigation water quality allows for a more effective and timely understanding of the ecological conditions of the surrounding flowing surface water and groundwater. This is beneficial for in-depth analysis of the relationship between farmland nutrients and the water environment, and holds significant scientific value and importance for ensuring sustainable agricultural development and food security.

This dataset collects and compiles indicators of water quality conditions from six shallow groundwater sites and two flowing surface water sites in Shangqiu from 2008 to 2020. Specific indicators include key physicochemical parameters such as water temperature, pH, Ca²+, Mg²+, K+, Na+, CO₃²-, HCO₃-, Cl-, and SO₄²-. Throughout the processes of sample collection, preservation, transportation, and laboratory analysis, strict adherence was maintained to the quality control system established by the "Protocols for standard water environment observation and measurement in terrestrial ecosystems", ensuring the completeness and accuracy of the data.

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Furthermore, this dataset is an important component of the CNERN platform data. It serves as a critical data foundation for studying regional farmland water cycles, soil nutrient migration, and water quality changes. It can provide more reasonable scientific evidence for the formulation of regional farmland irrigation standards and agricultural water environment assessments, offering significant guidance for regional farmland water safety and green, efficient agricultural water use.

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Catalogue records · 1

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Inferred from text
Pollution and contamination 71%
Provenance · 1 source records, 11 field assertions
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ScienceDB10.57760/sciencedb.2751611 d agoJSON v1
FieldAssertionExtractorEvidence
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