TY - GEN A1 - Frimpong, Bernard Fosu A1 - Molkenthin, Frank T1 - Tracking Urban Expansion Using Random Forests for theClassification of Landsat Imagery (1986–2015) and PredictingUrban/Built-Up Areas for 2025: A Study of the KumasiMetropolis, Ghana T2 - Land N2 - Kumasi is a nodal city and functions as the administrative and economic capital of the Ashanti region in Ghana. Rapid urbanization has been experienced inducing the transformation of various Land Use Land Cover (LULC) types into urban/built-up areas in Kumasi. This paper aims at tracking spatio-temporal LULC changes utilizing Landsat imagery from 1986, 2013 and 2015 of Kumasi. The unique contribution of this research is its focus on urban expansion analysis and the utilization of Random Forest (RF) Classifier for satellite image classification. Change detection, urban land modelling and urban expansion in the sub-metropolitan zones, buffers, density decay curve and correlation analysis were methodologies adopted for our study. The classifier yielded better accuracy compared to earlier works in Ghana. The evaluation of LULC changes indicated that urban/built-up areas are continually increasing at the expense of agricultural and forestlands. The urban/built-up areas occupied 4622.49 hectares (ha) (23.78%), 13,447.50 ha (69.18%) and 14,004.60 ha (72.05%) in 1986, 2013 and 2015, respectively of the 19,438 ha area of Kumasi. Projection indicated that urban/built-up areas will occupy 15,490 ha (79.70%) in 2025. The urban expansion was statistically significant. The results revealed the importance of spatial modeling for environmental management and city planning. KW - urban/built-up areas KW - land use land cover KW - Kumasi KW - random forest classifier KW - urban expansion analysis Y1 - 2021 UR - https://www.mdpi.com/2073-445X/10/1/44 U6 - https://doi.org/10.3390/land10010044 SN - 2073-445X VL - 10 IS - 1 SP - 1 EP - 21 ER - TY - GEN A1 - He, Qianwen A1 - Molkenthin, Frank T1 - Improving the integrated hydrological simulation on a data-scarce catchment with multi-objective calibration T2 - Journal of Hydroinformatics N2 - The process-based hydrological model Soil and Water Assessment Tool ensures the simulation's reliability by calibration. Compared to the commonly applied single-objective calibration, multi-objective calibration benefits the spatial parameterization and the simulation of specific processes. However, the requirements of additional observations and the practical procedure are among the reasons to prevent the wider application of the multi-objective calibration. This study proposes to consider three groups of objectives for the calibration: multisite, multi-objective function, and multi-metric. For the study catchment with limited observations like the Yuan River Catchment (YRC) in China, the three groups corresponded to discharge from three hydrometric stations, both Nash–Sutcliffe efficiency (NSE) and inversed NSE for discharge evaluation, and MODIS global terrestrial evapotranspiration product and baseflow filtered from discharge as metrics, respectively. The applicability of two multi-objective calibration approaches, the Euclidean distance and nondominated sorting genetic algorithm II, was analyzed to calibrate the above-mentioned objectives for the YRC. Results show that multi-objective calibration has simultaneously ensured the model's better performance in terms of the spatial parameterization, the magnitude of the output time series, and the water balance components, and it also reduces the parameter and prediction uncertainty. The study thus leads to a generalized, recommended procedure for catchments with data scarcity to perform the multi-objective calibration. KW - multi-objective calibration KW - NSGA-II KW - parameter uncertainty KW - SWAT Y1 - 2021 U6 - https://doi.org/10.2166/hydro.2021.132 SN - 1464-7141 VL - 23 IS - 2 SP - 267 EP - 283 ER - TY - GEN A1 - Trinh, Manh Xuan A1 - Molkenthin, Frank T1 - Flood hazard mapping for data-scarce and ungauged coastal river basins using advanced hydrodynamic models, high temporal-spatial resolution remote sensing precipitation data, and satellite imageries T2 - Natural Hazards N2 - This paper presents an integrated approach to simulate flooding and inundation for small- and medium-sized coastal river basins where measured data are not available or scarce. By coupling the rainfall–runoff model, the one-dimensional and two-dimensional models, and the integration of these with global tide model, satellite precipitation products, and synthetic aperture radar imageries, a comprehensive flood modeling system for Tra Bong river basin selected as a case study was set up and operated. Particularly, in this study, the lumped conceptual model was transformed into the semi-distributed model to increase the parameter sets of donor basins for applying the physical similarity approach. The temporal downscaling technique was applied to disaggregate daily rainfall data using satellite-based precipitation products. To select an appropriate satellite-derived rainfall product, two high temporal-spatial resolution products (0.1 × 0.1 degrees and 1 h) including GSMaP_GNRT6 and CMORPH_CRT were examined at 1-day and 1-h resolutions by comparing with ground-measured rainfall. The CMORPH_CRT product showed better performance in terms of statistical errors such as Correlation Coefficient, Probability of Detection, False Alarm Ratio, and Critical Success Index. Land cover/land use, flood extent, and flood depths derived from Sentinel-1A imageries and a digital elevation model were employed to determine the surface roughness and validate the flood modeling. The results obtained from the modeling system were found to be in good agreement with collected data in terms of NSE (0.3–0.8), RMSE (0.19–0.94), RPE (− 213 to 0.7%), F1 (0.55), and F2 (0.37). Subsequently, various scenarios of flood frequency with 10-, 20-, 50-, and 100-year return periods under the probability analysis of extreme values were developed to create the flood hazard maps for the study area. The flood hazards were then investigated based on the flood intensity classification of depth, duration, and velocity. These hazard maps are significantly important for flood hazard assessments or flood risk assessments. This study demonstrated that applying advanced hydrodynamic models on computing flood inundation and flood hazard analysis in data-scarce and ungauged coastal river basins is completely feasible. This study provides an approach that can be used also for other ungauged river basins to better understand flooding and inundation through flood hazard mapping. Y1 - 2021 UR - https://link.springer.com/article/10.1007/s11069-021-04843-1 U6 - https://doi.org/10.1007/s11069-021-04843-1 SN - 0921-030X SN - 1573-0840 VL - 109 IS - 1 SP - 441 EP - 469 ER -