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<p>Accurately predicting domestic sewage volume is crucial for designing and optimizing treatment infrastructure in data-scarce rural areas. However, such efforts in Northwest China are hindered by the pervasive lack of monitoring data and the scattered nature of settlements. This study developed a novel macro-scale assessment framework by integrating open-source Area-of-Interest data with standardized quota methods to bridge this gap. We first identified and rigorously validated a total of 35,372 rural residential patches across the five northwestern provinces. The domestic sewage discharge was then predicted using the Comprehensive Water Quota Method and the Drainage Quota Method, with key parameters calibrated from national standards and local socio-economic conditions. The results revealed distinct spatial distribution patterns and significant inter-provincial disparities in sewage generation. The two prediction methods demonstrated strong consistency, revealing a clear gradient in the average daily discharge per settlement, with Ningxia and Xinjiang generating the highest volumes and Qinghai the lowest. A critical finding was the pronounced right-skewed distribution of discharge at the settlement level, indicating that over 75% of villages are low-discharge entities, which necessitates a decentralized treatment strategy for the vast majority. The peak discharges, calculated by applying a total variation coefficient, were more than double the average values, providing essential guidance for resilient system design. This study provides the first comprehensive, data-driven baseline for rural sewage discharge in Northwest China, offering a transferable methodology for infrastructure planning in other data-scarce regions.</p>

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Prediction of domestic sewage volume in villages and towns in Northwest China based on area-of-interest data

  • 期刊论文

  • 发表日期：

    2026年3月12日

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  • Rui Dong,
  • Zhao Guo,
  • Muhammad Awais Baloch,
  • Xukuo Gao

摘要

Accurately predicting domestic sewage volume is crucial for designing and optimizing treatment infrastructure in data-scarce rural areas. However, such efforts in Northwest China are hindered by the pervasive lack of monitoring data and the scattered nature of settlements. This study developed a novel macro-scale assessment framework by integrating open-source Area-of-Interest data with standardized quota methods to bridge this gap. We first identified and rigorously validated a total of 35,372 rural residential patches across the five northwestern provinces. The domestic sewage discharge was then predicted using the Comprehensive Water Quota Method and the Drainage Quota Method, with key parameters calibrated from national standards and local socio-economic conditions. The results revealed distinct spatial distribution patterns and significant inter-provincial disparities in sewage generation. The two prediction methods demonstrated strong consistency, revealing a clear gradient in the average daily discharge per settlement, with Ningxia and Xinjiang generating the highest volumes and Qinghai the lowest. A critical finding was the pronounced right-skewed distribution of discharge at the settlement level, indicating that over 75% of villages are low-discharge entities, which necessitates a decentralized treatment strategy for the vast majority. The peak discharges, calculated by applying a total variation coefficient, were more than double the average values, providing essential guidance for resilient system design. This study provides the first comprehensive, data-driven baseline for rural sewage discharge in Northwest China, offering a transferable methodology for infrastructure planning in other data-scarce regions.