Integrating global land-cover and soil datasets to update saturated hydraulic conductivity parameterization in hydrologic modeling


Trinh T., Kavvas M. L., Ishida K., Ercan A., Chen Z. Q., Anderson M. L., ...Daha Fazla

SCIENCE OF THE TOTAL ENVIRONMENT, cilt.631-632, ss.279-288, 2018 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 631-632
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1016/j.scitotenv.2018.02.267
  • Dergi Adı: SCIENCE OF THE TOTAL ENVIRONMENT
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.279-288
  • Anahtar Kelimeler: Soil database, Food and Agriculture Organization (FAO), International Soil Reference and Information Centre (ISRIC), Saturated hydraulic conductivity (Ks), Land use/land cover (LULC), Watershed Environmental Hydrology (WEHY), RUNOFF GENERATION, WEHY MODEL, VARIABILITY, KNOWLEDGE, IMPACT
  • Orta Doğu Teknik Üniversitesi Adresli: Hayır

Özet

Soil properties play an important role in watershed hydrology and environmental modeling. In order to model realistic hydrologic processes, it is necessary to obtain compatible soil data. This study introduces a new method that integrates global soil databases with land use/land cover (LULC) databases to better represent saturated hydraulic conductivity (Ks) which is one of the most important soil properties in hydrologic modeling. The Ks is modified by means of uniting physical infiltration mechanisms with hydrologic soil-LULC complexes from lookup tables from USDA-SCS (1985). This approach enables assimilation of available coarse resolution soil parameters by the finer resolution global LULC datasets. In order to test the performance of the proposed approach, it has been incorporated into the Watershed Environmental Hydrology (WEHY) model to simulate hydrologic conditions over the Cache Creek Watershed (CCW) and Shasta Dam Watershed (SDW) in Northern California by means of different soil datasets. Soil dataset S1 was obtained from the local soil database including SSURGO (Web soil survey, USDA). The second soil dataset (S2) is the global ISRIC soil data SoilGrids-1 km obtained from World Soil Information. Soil dataset S4 is global FAO soil data. The third (S3) and fifth (55) soil datasets were calculated by integrating the LULC into global soil datasets (S2, S4), respectively. The results of this study suggest that the proposed approach can provide a fine resolution soil dataset through integration of LULC and soil data, which can improve the estimation of soil hydraulic parameters and the performance of hydrologic modeling over the target watersheds. Within this framework, the new approach of this study can be applied widely in many parts of the world by means of the global soil and WLC databases. (C) 2018 Elsevier B.V. All rights reserved.