This study calibrated the Soil Conservation Service Curve Number (SCS-CN) model to predict decadal runoff in Peninsula Malaysia and found a correlation between the reduction of forest area, urbanization, and an increase in runoff volume. The conventional SCS-CN runoff model was found to commit a type II error in this study and must be pre-justified with statistics and calibrated before being adopted for any runoff prediction. Between 1970 and 2000, deforestation in Peninsula Malaysia caused a decline in forested land by 25.5%, resulting in a substantial rise in excess runoff by 10.2%. The inter-decadal mean runoff differences were more pronounced in forested and rural catchments (lower CN classes) compared to urban areas. The study also found that the CN value is a sensitive parameter, and changing it by ±10% can significantly impact the average runoff estimate by 40%. Therefore, SCS practitioners are advised not to adjust the CN value for better runoff modeling results. Additionally, NASA’s Giovanni system was used to generate 20 years of monthly rainfall data from 2001–2020 for trend analysis and short-term rainfall forecasting. However, there was no significant uptrend in rainfall within the period studied, and occurrences of flood and landslide incidents were likely attributed to land-use changes in Peninsula Malaysia. Full article

The objective of the study was to configure the Hydrological Modeling System (HEC-HMS) in such a way that it could simulate all-important hydrological components (e.g., streamflow, soil moisture, snowmelt water, terrestrial water storage, baseflow, surface flow, and evapotranspiration) in the Three-River Headwater Region. However, the problem we faced was unsatisfactory simulations of these hydrological components, except streamflow. The main reason we found was the auto-calibration method of HEC-HMS because it generated irrational parameters, especially with the inclusion of Temperature Index Method and Soil Moisture Accounting (an advanced and complex loss method). Similar problems have been reported by different previous studies. To overcome these problems, we designed a comprehensive approach to estimate initial parameters and to calibrate the model manually in such a way that the model could simulate all the important hydrological components satisfactorily. Full article

Plain farmland areas without significant topographic slope exhibit microtopographic features of different scales. Quantitative assessment of the effects of microtopography at different scales on runoff generation in typical farmland areas is of great significance for regional water resources management and flood disaster forecasting. The main objective of the study was to develop an event-based rainfall–runoff model based on the layered Green–Ampt model (LGAM) with the consideration of plot-scale microtopographic features in plain farmland areas. Our experimental field, located in Taihu Lake Basin, was classified into three types of topographic subunits (i.e., main field, rill, and ditch) according to the average elevation. To simplify the concentration process for three topographic subunits, the average concentration time method was employed. Here, various experimental scenarios were simulated, including two classical unsteady rainfall events in homogeneous soil, one ponding infiltration experiment, and two typical rainfall–runoff events in the experimental field. We found that the multilayered setting showed higher accuracy than the homogeneous setting for simulating infiltration in the ponding infiltration experiment in the field. The RMSE of simulated ponding water depth reduced from 0.166 cm to 0.035 cm and NSE rose from 0.988 to 0.999. The simulated hydrograph considering microtopography effects proved higher accuracy than that under unified topography assumption. After classifying topography, the RMSE and NSE of simulated hydrographs decreased and increased, respectively. The lower the topographic subunit, the earlier the outflow occurred. At the early stage, the runoff mostly originated from the relatively low topographic subunits. Infiltration-excess regime under saturated condition may initially dominate in the low-lying ditch under intense rainfall, with extremely high runoff coefficient. Concentration process in the plain farmland area was affected by both rainfall intensity and microtopography. The greater the rainfall intensity, the shorter the average concentration time. The concentration velocity under heavy rainfall was four times faster than that under light rainfall. The lower topographic subunit was characterized by shorter concentration pathway and average concentration time. Ditches reduced the peak flow and advanced the time to peak. This quantitative study provides new insights into effects of microtopography on runoff generation in plain farmland area as well as an effective alternative for plot-scale rainfall–runoff modeling. Full article

Flood Frequency Analysis (FFA) and the non-stationary FFA approaches are used in flood study, water resource planning, and the design of hydraulic structures. However, there is still a need to develop these methods and to find new procedures that can be used in estimating simple distributions in controlled catchments. The aim of the study is a comparison of three-parameter distributions in controlled catchments for stationary and non-stationary data series and further to develop the procedure of the estimation the simple distributions. Ten rivers from the Czech Republic and Poland were selected because of their existing or planned reservoirs as well as for flood protection reasons. The annual maximum method and the three-parameter Weibull, Log-Normal, Generalized extreme value, and Pearson Type III distributions were used in this study. The analyzed time series are stationary and non-stationary. The methodology used in this study, which makes use of the Maximum Likelihood Estimation, allows one to simplify the analysis whenever there is a series of data that is both stationary and non-stationary. The novelty in our research is the standardization and development of a new procedure for a stationary and non-stationary data series, taking into account to read a specific value of the maximum flow with a given exceedance probability from the lower or upper tail. It determines the optimal choice of the theoretical distribution that can be used, for example in the design of weirs in rural areas (lower quantiles) or in the design of hydrotechnical structures in areas at risk of flooding (upper quantiles). Full article