Abstract The SWAT model is a semi-distributed hydrological watershed model with an explicit physical mechanism, which is widely applied in areas characterized by a wide variety of precipitation distributions and slope conditions. However, the Soil Conservation Service-Curve Number (SCS-CN) value and precipitation initial abstraction ratio were not related to slope, soil moisture content, precipitation intensity, and land cover interception within the original SWAT model. Thus, a modified SCS-CN model is proposed by considering the slope, rainfall intensity, soil moisture, and interception effects of the landscape in this study, specifically revising the critical sensitive parameters including CN2 and initial abstraction ratio (λ). The modified SCS-CN model was added to the original SWAT model and named the SWAT-CH model, which is applied to Chao River watershed which experiences obvious differences in precipitation and slope. For this application, the daily streamflow was simulated for the calibration and validation periods of 1993–2005 and 2006–2013, respectively. The simulated variable is monthly runoff at watershed outlet, namely Xiahui hydrological station. The parameter sensitivity and uncertainty and the model applicability were analyzed using as Chao River watershed as a case study. The main results are as follows. ① Compared with the original SWAT model, the parameters of SOL-K, HRU-SLP, SLSUBBSN, and CANMX were identified as the most sensitive parameters for the runoff simulation in the new SWAT-CH model. ② The prediction efficiency of the SWAT-CH model surpasses that of the original SWAT model. The Nash-Sutcliffe efficiency, KGE index, and the PBIAS were 0.94, 0.83 and 4.55%, respectively for SWAT-CH during the calibration stage; while, those corresponding indexes were 0.91, 0.84, and 7.00% for the validation period. The modified SWAT-CH model can better reproduce the hydrological process than the SWAT model. In detail, the Nash-Sutcliffe efficiency, KGE index, and the PBIAS were improved by 0.02, 0.10, −4.01 percentage points for the calibration period, as well as by 0.18, 0.25, and −28.55 percentage points for the validation period in the modified SWAT-CH model compared with the original SWAT model. ③ Influenced by soil moisture, there is a substantial difference between the SWAT-CH and SWAT models in wet periods at various temporal scales. ④ Parameter uncertainty is the main source of the uncertainty in hydrological estimation for the Chao River watershed. The modified SWAT-CH model has, to some extent, reduced the effect of parameter uncertainty with increasing structure uncertainty from 6.00% for the SWAT model to 9.00% for the SWAT-CH model. The model adaptability has been enhanced by introducing terrace slope, precipitation intensity, and soil moisture for the modification of CN2 and the abstraction ratio, which makes the revised SWAT-CH model have better simulation performance in areas with the obvious characteristics of terrain & rainfall heterogeneity and drastic dry-wet cycles in the soil profile.

中文翻译：

---

基于坡度条件和降水强度的修正 SWAT 模型的开发和测试

摘要 SWAT模型是一种物理机制明确的半分布式水文流域模型，广泛应用于降水分布和坡度条件多样的地区。然而，在原始 SWAT 模型中，土壤保持服务曲线数 (SCS-CN) 值和降水初始提取率与坡度、土壤含水量、降水强度和土地覆盖截获无关。因此，本研究考虑坡度、降雨强度、土壤水分和景观截留效应，提出了一种改进的SCS-CN模型，特别是修改了CN2和初始取水比（λ）等关键敏感参数。修改后的 SCS-CN 模型被添加到原来的 SWAT 模型中，并命名为 SWAT-CH 模型，适用于降水量和坡度差异明显的潮江流域。对于该应用，分别模拟了 1993-2005 年和 2006-2013 年校准和验证期的每日流量。模拟变量为流域出水口，即夏汇水文站的月径流量。以潮江流域为例，分析了参数敏感性和不确定性以及模型的适用性。主要结果如下。① 与原 SWAT 模型相比，SOL-K、HRU-SLP、SLSUBBSN 和 CANMX 参数被确定为新 SWAT-CH 模型中径流模拟最敏感的参数。② SWAT-CH 模型的预测效率超过了原始 SWAT 模型。Nash-Sutcliffe 效率，KGE 指数，在校准阶段，SWAT-CH 的 PBIAS 分别为 0.94、0.83 和 4.55%；而相应的指标在验证期内分别为 0.91、0.84 和 7.00%。改进后的 SWAT-CH 模型比 SWAT 模型能更好地再现水文过程。具体而言，Nash-Sutcliffe 效率、KGE 指数和 PBIAS 在校准期提高了 0.02、0.10、-4.01 个百分点，在验证期提高了 0.18、0.25 和 -28.55 个百分点。与原始 SWAT 模型相比，修改后的 SWAT-CH 模型。③受土壤水分影响，SWAT-CH和SWAT模型在不同时间尺度的湿润期存在显着差异。④参数不确定性是潮江流域水文估算不确定性的主要来源。改进后的 SWAT-CH 模型在一定程度上降低了参数不确定性的影响，结构不确定性从 SWAT 模型的 6.00% 增加到 SWAT-CH 模型的 9.00%。通过引入阶地坡度、降水强度和土壤水分对CN2和取水比进行修正，增强了模型的适应性，使得修正后的SWAT-CH模型在地形和降雨非均质性特征明显的地区具有更好的模拟性能和土壤剖面中剧烈的干湿循环。