Forecasting of suspended sediment concentration in the Pindari-Kafni glacier valley in Central Himalayan region considering the impact of precipitation: using soft computing approach

Spatiotemporal snowline status and climate variability impact assessment: a case study of Pindari River Basin, Kumaun Himalaya, India

“…Changuch (6322 m asl), Nandakhat (6611 m asl), Nandakot (6860 m asl), Pawalidwar (6663 m asl), and Baljuri (5922 m asl) are the peaks near the Pindari glacier regions. The rationale for selecting the Pindari region as the study site included three key factors: (1) its clear visibility on satellite imagery, (2) minimal cloud cover, and (3) the presence of climate change impacts, such as a sustained rise in temperatures and human-induced activities leading to the rapid melting of glacial reserves in the Pindari region [8,47].…”

“…This cryosphere region in Uttarakhand is retreating at an accelerated pace compared to that in other high-mountain Asia regions. Glacier depletion in the Pindari Valley is an example of glacial depletion in the Uttarakhand Mountains [8,47]. The land framework changes in the locale have been connected to exhausting stream flows, financial contemplations, and spontaneous land change.…”

Forecasting of stage-discharge in a non-perennial river using machine learning with gamma test

“…Machine learning and artificial intelligence models have become very popular in recent decade [ [34] , [35] , [36] , [37] , [38] ]. Forecasting of the stream discharge various models such as multiple-linear regression (MLR) [ 2 , [39] , [40] , [41] , [42] ], rating curve [ [43] , [44] , [45] , [46] , [47] ], wavelet-based MLR (WMLR) [ 48 , 49 ], support vector machine (SVM) [ 39 , 44 , [50] , [51] , [52] , [53] ], artificial neural network (ANN) [ 45 , [53] , [54] , [55] , [56] , [57] ], wavelet-based artificial neural network (WANN) [ 2 , 39 , 58 ], adaptive neuro-fuzzy inference system (ANFIS) [ [59] , [60] , [61] ], wavelet-based support vector machine (WSVM) [ 39 , 62 ], wavelet–bootstrap–ANN (WBANN) [ 48 , 63 ], M5-model trees [ 46 , 64 ], random forest (RF) [ 65 ], ARIMA [ 65 , 66 ], gene expression programming (GEP) [ 32 , 67 , 68 ], genetic algorithm (GA) [ 3 , 33 , 69 ], genetic programming (GP) [ 32 ], Bagged M5P [ 65 ], integrating long-short-term memory (LSTM) [ 69 , 70 ], wavelet–bootstrap–multiple linear regression (WBMLR) [ 48 ], Fuzzy logic and fuzzy neuro systems [ 59 , 71 ] multi-objective evolutionary neural network (MOENN) [ 59 ], and Gaussian process regre...…”