ABSTRACT This study presents a procedure to determine improved curve numbers (CNImp) for application of the enhanced Soil Conservation Service - Curve Number (SCS-CN) model developed by Verma et al. for improved runoff prediction. To this end, five different mathematical relationships, i.e. linear, exponential, power, logarithmic and polynomial, are developed for 57 US Department of Agriculture – Agricultural Research Service (USDA-ARS) watersheds to compute CNImp with the aid of CN derivable from the National Engineering Handbook, Section-4 (NEH-4) table (CNT) and from the enhanced SCS-CN model (CNV) with significant R 2 values. Using these relationships, CNImp values are computed for another 57 watersheds for validation. Based on common performance criteria, all five developed relationships for CNImp are found to be superior to the original model in runoff computation. When compared, CNImp are close to CNV and very different from CNT. Despite the fact all the relationships performed equally well, with similar performance statistics, the exponential relationship performed the best of all and the power relationship was the worst.

中文翻译：

---

改进了美国大量流域的径流曲线数

摘要 本研究提出了确定改进曲线数 (CNImp) 的程序，以应用由 Verma 等人开发的增强型土壤保护服务 - 曲线数 (SCS-CN) 模型。以改进径流预测。为此，为美国农业部 - 农业研究服务 (USDA-ARS) 的 57 个流域开发了五种不同的数学关系，即线性、指数、幂、对数和多项式，以借助可从国家统计局推导出的 CN 计算 CNImp。工程手册，第 4 节 (NEH-4) 表 (CNT) 和来自具有显着 R 2 值的增强型 SCS-CN 模型 (CNV)。使用这些关系，计算另外 57 个流域的 CNImp 值以进行验证。基于共同的性能标准，发现 CNImp 的所有五个开发的关系在径流计算中都优于原始模型。相比之下，CNImp 与 CNV 接近，与 CNT 非常不同。尽管事实上所有关系都表现得同样好，并且具有相似的性能统计数据，但指数关系的表现最好，而权力关系最差。