On the performance of conceptual and physically based modelling approach to simulate a headwater catchment in Brazil

Quality Assessment of Small Urban Catchments Stormwater Models: A New Approach Using Old Metrics

“…It is important to note that the proximity of the values of NSE, KGE and r 2 to optimal values is higher than in most cases in the literature and may derive from the approach applied in this work. As mentioned in Section 2.1, most of the NSE values reported in the calibration of hydrological or hydraulic urban drainage models range from 0.5 to 0.9, with most being greater than 0.7 [2,7,10,20,22,[46][47][48][50][51][52][53]. However, NSE values above 0.95 are also reported [1,53,55].…”

“…In urban catchments, important rainfall events last a few hours or even minutes, and therefore the time step of measurement records is usually only of a few minutes. The urban drainage literature reports NSE values from the calibration of hydrologic or hydraulic models, normally between 0.5 and 0.9 [2], most of them being greater than 0.7 [7,10,20,22,[46][47][48][50][51][52][53]. However, in some cases, NSE values above 0.95 are reported [1,53,55], while in other specific cases, usually for water quality parameters, very low values, close to zero, are considered as acceptable [9].…”

“…The Percent bias, or Percent deviation (PBIAS, Equation (7)) is used to assess the average tendency of the predicted data to be smaller or greater than the observed data. Positive values of PBIAS indicate underestimation, and negative values indicate overestimation.…”

“…Urban drainage models usually aim at supporting decisions on flooding mitigation, pollution control, sewer system management and, increasingly, city planning and regeneration [1][2][3]. Depending on the objectives of the work and the availability of hydrological and asset data, the models can be either distributed and physically based or more aggregated and conceptual [4][5][6][7]. The increasing implementation of decentralized measures and nature-based solutions, i.e., solutions that seek to replicate natural phenomena across the catchment, often requires distributed models and, in some cases, more detailed modelling of infiltration, evapotranspiration and water quality [8,9].…”

Hydrological Model Performance in the Verde River Basin, Minas Gerais, Brazil

“…The MHD-INPE [16] is a distributed model that was developed at the Instituto Nacional de Pesquisas Espaciais (INPE), and it is an adaptation of the Large Basin Model that was developed at the Instituto de Pesquisas Hidráulicas (MGB-IPH). The MHD-INPE has been successfully applied to basins of varying sizes, ranging from 5 to 1.4 million km 2 , for studies on land-use and land-cover changes, climate change and hydropower, discharge forecasting, and water sustainability, for which it has consistently yielded satisfactory results [17][18][19][20][21].…”