Identifying the most critical sub-watershed or dam/reservoir catchment in relation to water distribution, erosion pattern, and groundwater recharge in a basin can be highly useful for land and water conservation. Thus, a study was undertaken to review the different parameters used for morphometric analysis and watershed prioritization. The smaller values of form factor (Ff < 0.78), elongation ratio (Re < 0.80), and circularity ratio (Rc < 0.50) indicate higher soil erosion due to their inverse relationship with erodibility. Furthermore, higher values of Ff (>0.78), Re (>0.80), and Rc (>0.50) indicate a circular basin with a high peak for a shorter duration. The higher values of drainage density (Dd > 0.60), drainage texture (Dt > 0.6), and stream frequency (Fs > 10) indicate higher erosion due to their direct relationship with erodibility in relation to low infiltration rate, high runoff conditions, low potential for groundwater recharge, and presence of a higher number of first-order streams. The morphometric analysis-based watershed prioritization is time-consuming and, hence, can be replaced by modern techniques such as principal component analysis (PCA) using suitable software such as R, SPSS, and XLSTAT. Overall, remote sensing and GIS-based watershed prioritization (based on morphometric analysis or PCA or LULC) can be useful in land and water conservation planning and management.
A study was carried out to develop and evaluate the performance of different machine learning (ML) models for predicting reference evapotranspiration (ET0). The models included multiple linear regression (MLR), least square-support vector machine (LS-SVM), artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS). The daily meteorological data for 50 years (1970–2019) were used to estimate ET0 using FAO-ET calculator. The FAO-ET calculator was compared with ML models to investigate the best-fit ML model for predicting ET. Thereafter, ET predicted by the best-fit ML model was compared with satellite (MOderate resolution Imaging Spectroradiometer – MODIS) ET, which was finally mapped to a larger landscape (over entire Punjab and Haryana). Modeling of ET0 was best performed through LS-SVM followed by ANN2, ANN1, ANFIS10, ANFIS2, MLR and ANFIS9 models. Among developed models, coefficient of determination (R2) value varied from 0.800 to 0.998, being highest (0.998) under LS-SVM model. MODIS overestimated ET when compared with LS-SVM having R2 and root mean square error (RMSE) values of 0.73 and 3.95 mm, respectively. After applying the bias correction factor, R2 and RMSE were 0.74 and 1.19 mm, respectively. The ML and satellite-based ET estimation would be useful for timely water budgeting to manage the water scarcity problems from local to regional levels.
Nine reservoir catchments (Chohal, Damsal, Dholbaha, Januari, Maili, Nara, Patiaria, Selaran and Thana) located in Shivalik foot-hills of Indian Punjab were prioritized using geospatial techniques and principal component analysis (PCA) for soil and water conservation planning. The selected catchments were demarcated using a digital elevation model (DEM) of 12.5 m resolution (ALOS PALSAR) in ArcGIS 10.4.1 software. The higher values of shape parameters (Ff > 0.78, Re > 0.8 and Cc ≥ 1) indicated circular shapes of Saleran and Nara dam catchments with high peaks for a shorter duration, from where the flood flows cannot be easily managed. These basins indicate coarse drainage density (Dd = 2.0–4.0 km km−2). The relative relief (Rrel) was also computed to the highest (0.124) for Saleran and Nara dam catchments, respectively. The geospatial techniques-based morphometric analysis helped to identify the shapes of the reservoir catchments including the factors affecting hydrological conditions and soil erodibility. The PCA application simplified the prioritization process via a reduction in the number of parameters. Thus, geospatial techniques-based morphometric analysis coupled with PCA-based prioritization is significant to identify the most critical reservoir catchment in a region for conservation planning. The study would be useful for implementing appropriate soil and water management measures in the highly prioritized reservoir catchment.
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