Climate change refers to long-term alterations in climate patterns across various regions of the world. As per the data availability and explanations given by different researchers, human exercises, particularly the burning of coal, deforestation, and the use of oil, have increased the temperature of the Earth by significantly improving the engagement of heat-absorbing gases in the environment. The above-stated ratio will increase proportionally in the future. Therefore, climate change is one of our biggest global challenges, and urgent action must be taken to reduce greenhouse gas emissions, and adapt to its effects, and ensure a long and healthy life for all. This paper examines the different aspects of the effects of climate change on different ecosystem elements, such as air, water, plants, animals, and human beings, with a notable focus on economic aspects. Finally, to better understand the situation, data in this report were collected from different media platforms, research mechanisms, guideline papers, newspapers, and other references. This review paper considers climate change mitigation and transformation worldwide in different sectors like human health, crop productivity, and the related economic impact. The conclusions emphasize that government monitoring is essential for countries' long-term growth through responsible resource management.

A large population depends on water resources generated due to runoff from Himalayan River basins. They provide enough water for drinking, domestic, industrial, and irrigation. Also, these rivers have a high hydropower potential. A lack of in-depth studies has made it difficult to understand how these rivers respond hydrologically to climate change (CC) and, thus, impact the environment. In this paper, Alaknanda River Basin (ARB) has been modelled using the Soil and Water Assessment Tool (SWAT) to understand the hydrological response and assess its water balance components. The result shows that the basin's water yield and evapotranspiration (ET) vary from 58–63% and 34–39% of total precipitation. The average annual contribution of snowmelt to the total riverine flow will range from 20–24% throughout the simulation period. SFTMP, TLAPS, SMTMP, CN2, SMFMX, and GW_DELAY is found to be most sensitive at the significance level of less than 0.05, showing the contribution of the snowmelt is significant in streamflow, while delay in the groundwater will affect the contribution of surface runoff and groundwater in the streamflow. Based on the results, it is highly recommended that the spatial and temporal hydro-meteorological should be investigated in-depth to find out the actual water potential of the basin.

The estimation of stream discharge is an essential component of planning and decision-making. It is highly correlated with many development activities involving water resources. The study of transportation of sediments in the rivers will help us to develop policies and plans for soil conservation, flood control, irrigation, navigation, and aquatic biodiversity problems. Using data-driven models such as Artificial Neural Networks (ANNs), modeling of streamflow and sediment transport is frequently adopted due to their applicability and problem-solving ability. This study has used three training algorithms such as Scaled Conjugate Gradient (SCG), Bayesian Regularization (BR), and Levenberg-Marquardt (LM) to simulate the streamflow and Suspended Sediments Concentration (SSC). After optimizing the best training algorithm based on the model efficiency parameters, L-M based-ANN model has been used to predict streamflow for two years and the modeling of suspended sediments was validated with the help of observed data. The result shows that the simulated results tracked the streamflow as well as SSC with the desired accuracy based on the model efficiency parameters such as coefficient of Determination (R2), Nash Sutcliffe Efficiency (NSE), Root Mean Square Error (RMSE), and Root Mean Square Deviation (RMSD). The study's outcomes reveal that in the streamflow the concentration of suspended sediments is significantly affected by the base rock material, glaciers covered by debris, and moraine-laden ice. The transportation of the sediments is high in the Alaknanda basin as compared to the other basins and the previous studies. This might happen due to the severe anthropogenic activities in the surrounding basin.

Floods are one of the most devastating natural disasters, causing land destruction, economic loss, and massive disruptions to humans. The present study was conducted in the Alaknanda river basin with medium to high drainage density and stream frequency. The flood vulnerable zones (FVZ) are identified using geomorphometric analysis, and flood vulnerability zones are identified through analytical hierarchy processes (AHPs). Three factors, such as linear, relief, and aerial, have been used in the geomorphometric analysis of the Alaknanda basin. The weights were assigned on a scale of 1 for flood-induced factors such as slope (0.386), rainfall (0.192), drainage density (0.129), LULC (0.096), geology (0.077), soil (0.064), and DEM (0.055) have been determined using 7×7 decision matrix of multi-criteria decision making- analytical hierarchy processes (MCDM-AHP) model accounting for their varying importance from high to low priorities. A consistency ratio (CR) of 0.083 (less than 0.1) signifies the acceptance of the weights derived in the case. The high shape index, form factor, and rotundity factor indicate the basin allows quick drainage of surface runoff with a lesser time of concentration; as a result, sharp peaks of the hydrograph will be obtained at the outlet of the basin. However, most of the basin area is under the moderate vulnerability category, while the entire river banks along the valley are the most vulnerable. Additionally, a small-scale sociological study indicates that for a population that resides close to highly susceptible locations, temporary relocation is the most common strategy.

Hydropower is one of the best renewable energy sources to meet India's rapidly growing energy demand. The Remote Sensing and GIS tools provide reliable information for assessing the available water of the Himalayan rivers. In this study, the basin is divided into 12 elevation zones, and temperature and precipitation were extrapolated within these zones. The MODIS (Terra&Aqua) cloud-free images have been used for mapping the Snow Cover Area and it was found that the SCA will vary from 18–72 % during the simulation period. The model simulation period is divided into calibration (2003–2015) and validation (2016–2019). During the study, it was observed that the model efficiency parameters significantly exceeded the acceptable range. In this study, the snowmelt's contribution increases until zone 8; after this, the snowmelt contribution decreases, and the snow accumulation increases. Also, the Hydro-Electric Power (HEP) generation of the basin is modeled with the help of a power equation for a turbine efficiency of 0.8. The simulation of daily streamflow and generated HEP are compared with the measured values, and both tracked the observed pattern very precisely. The findings of the present study will be implemented on the other ungauged basins and could help us to identify the potential sites for HEP with the help of RS and GIS tools.

Assessment of vulnerability is the primary objective of flood hazard management. One of the most significant purposes of flood vulnerability appraisal is to make a precise relationship between the theoretical conceptions of flood vulnerability and the ground level management policies. A variety of approaches have been defined by many researchers to evaluate vulnerability. As such, the selection of the most suitable methodology is essential for policymakers to adequate mitigation policies. The purpose of the present study is to review all the vulnerability methods floating over the research universe and compare their benefits and drawbacks. This study evaluated more than 250 selected articles related to the assessment of vulnerability published between 1980 and 2020 to determine their competence in the estimation of flood vulnerability. The findings show that most of the research works are related to statistical methods, and the methods used to allocate weight to different indicators associate to the vulnerability. Moreover, most of the vulnerability assessment methods are centred around the single type of hazard, i.e., flood, drought, etc. As such, the results recommend the necessity for developing a new integrated vulnerability assessment framework applicable to worldwide considering multiple risks.