The Implementation of a Hybrid Model for Hilly Sub-Watershed Prioritization Using Morphometric Variables: Case Study in India

Using morphometric analysis for assessment of flash flood susceptibility in the Mediterranean region of Turkey

Flash floods are one of the most severe natural disasters around the world because of their rapid and unpredictable nature. It is expected that the frequency and intensity of flood events will increase because of extreme rainfall events induced by climate change. In this context, the generation of a flood susceptibility map contributes to effective flood management in a basin. The present study aims to generate a flash flood susceptibility map for the Imali Stream Basin (ISB) situated within the Mediterranean region of Turkey. For this purpose, morphometric analysis, geographic information system (GIS), remote sensing (RS), and principal component analysis (PCA) were used in this study. ASTER GDEM (v.3) was used to delineate 9 sub-watersheds and to obtain the required morphometric parameters. To generate a flash flood susceptibility map, the original compound values ​​calculated for each sub-watershed were transformed into values ​​between 0 and 1 by using the min-max normalization method. Then, these values were divided into 3 classes called low, moderate, and high by using the equal interval classification method in ArcGIS. According to both flash flood susceptibility maps produced by using morphometric analysis and PCA, sub-watershed 5 has the highest flash flood susceptibility in the basin. The flash flood that occurred in sub-watershed 5 in 2016 contributes to these results. Therefore, flood management based on morphometric analysis can be a highly effective method for decision-makers and planners in the Mediterranean region, one of the hotspots to be affected by climate change.

Prioritization of water erosion-prone sub-watersheds using three ensemble methods in Qareaghaj catchment, southern Iran

Water-induced erosion poses severe harm to the sustainable development of land and water resources that is essential for attaining agricultural sustainability in Qareaghaj catchment of Fars Province, Iran. This study evaluates the topo-hydrological, morphometric, climatic, and environmental characteristics of Qareaghaj catchment for prioritizing the sub-watersheds that are susceptible to erosion caused by water. We tested and compared a novel ensemble multi-criteria decision-making (MCDM) model, namely the weighted aggregated sum product assessment-analytical hierarchy process (WASPAS-AHP) with prevailing benchmark ensemble MCDM models including VlseKriterijumska optimizacija I Kompromisno Resenje (VIKOR)-AHP and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS)-AHP for ranking sub-watersheds and determining the most significant parameter that influences water erosion (WE) in Qareaghaj catchment. The outcome of weights using pairwise comparison matrix (PCM) of AHP reveals that normalized difference vegetation index (NDVI), mean annual rainfall (MAR), slope degree (SD), and slope length and steepness factor (LS) governs the WE in Qareaghaj catchment. The prioritization rankings of sub-watersheds obtained using the VIKOR-AHP, TOPSIS-AHP, and WASPAS-AHP models demonstrate that SW31, SW63, and SW94 had the highest priority rank with a score of 0.047, 0.69, and 0.477, respectively. The comparison of rankings from the models using Spearman's correlation coefficient tests (SCCT) and Kendall's tau correlation coefficient tests (KTCCT) revealed that WASPAS-AHP had a higher correlation with TOPSIS-AHP and VIKOR-AHP ensemble models. The outcome of MCDM models was validated based on the erosion potential method (EPM), which displayed that the VIKOR-AHP model was better for mapping the erosion susceptibility than TOPSIS-AHP and WASPAS-AHP models. Thus, the erosion susceptibility mapping based on the VIKOR-AHP ensemble model can be considered for developing new strategies and land use policies in order to control WE in Qareaghaj catchment.

Morphometric Prioritization, Fluvial Classification, and Hydrogeomorphological Quality in High Andean Livestock Micro-Watersheds in Northern Peru

Anthropic activity affects the hydrogeomorphological quality of fluvial systems. River and valley classifications are fundamental preliminary steps in determining their ecological status, and their prioritization is essential for the proper planning and management of soil and water resources. Given the importance of the High Andean livestock micro-watershed (HAL-MWs) ecosystems in Peru, an integrated methodological framework is presented for morphometric prioritization that uses a Principal Component Analysis (PCA) and Weighted Sum Approach (WSA), geomorphological fluvial classifications (channel, slope, and valley), and hydrogeomorphological evaluations using the Hydrogeomorphological Index (IHG). Of six HAL-MWs studied in Leimebamba and Molinopampa (Amazonas region), the PCWSA hybrid model identified the San Antonio HAL-MW as a top priority, needing the rapid adoption of appropriate conservation practices. Thirty-nine types of river course were identified, by combining 13 types of valley and 11 types of riverbed. The total assessment of the IHG indicated that 7.6% (21.8 km), 14.5% (41.6 km), 27.9% (80.0 km), and 50.0% (143.2 km) of the basin lengths have “Poor”, “Moderate”, “Good”, and “Very good” quality rankings, respectively. The increase in the artificial use of river channels and flood plains is closely linked to the decrease in hydrogeomorphological quality.

A Multivariate Geomorphometric Approach to Prioritize Erosion-Prone Watersheds

Soil erosion is considered one of the main degradation processes in ecosystems located in developing countries. In northern Mexico, one of the most important hydrological regions is the Conchos River Basin (CRB) due to its utilization as a runoff source. However, the CRB is subjected to significant erosion processes due to natural and anthropogenic causes. Thus, classifying the CRB’s watersheds based on their erosion susceptibility is of great importance. This study classified and then prioritized the 31 watersheds composing the CRB. For that, multivariate techniques such as principal component analysis (PCA), group analysis (GA), and the ranking methodology known as compound parameter (Cp) were used. After a correlation analysis, the values of 26 from 33 geomorphometric parameters estimated from each watershed served for the evaluation. The PCA defined linear-type parameters as the main source of variability among the watersheds. The GA and the Cp were effective for grouping the watersheds in five groups, and provided the information for the spatial analysis. The GA methodology best classified the watersheds based on the variance of their parameters. The group with the highest prioritization and erosion susceptibility included watersheds RH24Lf, RH24Lb, RH24Nc, and RH24Jb. These watersheds are potential candidates for the implementation of soil conservation practices.