Watershed management plays a dynamic role in water resource engineering. Estimating surface runoff is an essential process of hydrology, since understanding the fundamental relationship between rainfall and runoff is useful for sustainable water resource management. To facilitate the assessment of this process, the Natural Resource Conservation Service-Curve Number (NRCS-CN) and Geographic Information Systems (GIS) were integrated. Furthermore, land use and soil maps were incorporated to estimate the temporal variability in surface runoff potential. The present study was performed on the Haridwar city, Uttarakhand, India for the years 1995, 2010 and 2018. In a context of climate change, the spatiotemporal analysis of hydro meteorological parameters is essential for estimating water availability. The study suggested that runoff increased approximately 48% from 1995 to 2010 and decreased nearly 71% from 2010 to 2018. In turn, the weighted curve number was found to be 69.24, 70.96 and 71.24 for 1995, 2010 and 2018, respectively. Additionally, a validation process with an annual water yield model was carried out to understand spatiotemporal variations and similarities. The study recommends adopting water harvesting techniques and strategies to fulfill regional water demands, since effective and sustainable approaches like these may assist in the simultaneous mitigation of disasters such as floods and droughts.

Slopy agricultural lands are more susceptible to soil erosion and hence are priority sites for the application of protective soil management practices. A conservation agriculture field experiment was established at a 6% field slope in 2011 at the ICAR-IISWC Research Farm, Dehradun, Uttarakhand, which is situated in the Northwestern Himalayan Region, India. The objective of this study was to experimentally determine the long-term effects of tillage practices on runoff and soil erosion. The tillage practices opted for were conventional tillage (CT), minimum tillage (MT), and zero tillage (ZT). Event-based runoff and soil loss were monitored during three monsoon seasons (June to September) from 2018 to 2020. Results showed lower runoff and soil loss in the ZT plot than in CT and MT plots. CT produced 1.51 and 2.53 times higher runoff than MT and ZT, respectively. Moreover, this increased runoff generated 1.84 and 5.10 times higher soil erosion in CT than in MT and ZT, respectively. The extreme rainfall events being less than 10% generated 54.93%, 57.35%, and 63.43% of the total runoff volume which resulted in 82.08%, 85.49%, and 91.00% of the total soil loss in CT, MT, and ZT plots, respectively. For the same amount of rainfall, the reduction in soil loss was 39% and 68% in the CT and ZT plots, respectively, at the highest growth stage in comparison to the initial crop growth stage. The values of runoff reduction benefit (RRB) and sediment reduction benefit (SRB) showed a reduction in runoff (63.53%) and soil loss (80.39%) in the CT. Results concluded that conservation tillage reduced runoff and soil loss significantly even in extreme rainfall events.

This study investigated the variation in soil hydrological properties—saturated water-holding capacity (SWHC), field capacity (FC), total porosity (TP), and saturated hydraulic conductivity (Ks)—across different land use systems in the Semalta watershed of the north Himalayan foothills. Soil samples were collected from four land use types (agriculture, barren land, deodar forest, and oak forest) at two depths (0–15 cm and 15–30 cm). Key parameters were measured using mini-disk infiltrometers and standard laboratory techniques. Statistical analyses included redundancy analysis (RDA), variance partitioning analysis (VPA), and multiple linear regression (MLR) for predictive modelling. Results showed that forested lands exhibited superior soil structure and water dynamics: porosity was highest in deodar (TP: 0.49) and oak (TP: 0.48) soils, while barren land had the lowest (TP: 0.41). Similarly, Ks values were higher in deodar (0.15 cm/hr) and oak (0.14 cm/hr) soils, indicating better permeability than agricultural and barren soils. RDA and VPA highlighted the dominant influence of aggregate stability, bulk density, and soil organic carbon on hydrological responses. MLR models achieved adjusted R² values above 0.90, confirming their utility in predicting soil-water dynamics. These findings underscore the importance of vegetation in maintaining soil hydraulic function and provide a framework for land use planning and sustainable watershed management.

River bank protection is a vital component of sustainable development. This study investigates and compares the scour and flow features around two different types of groynes, an unsubmerged I-head groyne (IHG) and T-head groyne (THG), to provide insights into their performance and efficiency in river reaches. Experiments were conducted to examine the scouring pattern, mean and turbulent flow characteristics including 3D mean flow velocity distribution, Reynolds stresses, turbulent kinetic energy, and bed shear stress near the bed region around the groynes under similar flow conditions. The results indicated that THG had a maximum equilibrium scour depth over three-fold greater than IHG. For both the IHG and THG cases, it was observed that there is a direct correlation between the location of maximum negative vertical velocity and its magnitude to the region of maximum local scour and its depth. All the stresses of high magnitude are found along the propagation of the detached shear layer profile, which turns back sharply downstream towards the bank containing the IHG while remaining mostly away from the bank in the case of THG. The effective bank protection length was estimated to be two-fold the groyne length in the case of IHG and three-fold the groyne transverse length in the case of THG. Cost–benefit analysis of the two groyne types shows IHG as the more cost-efficient groyne with respect to bank protection lengths. This study provides valuable insights for developing design methodologies aimed at promoting the wider utilization of different head-shape groynes in river reaches and aids in selecting appropriate groyne head configurations that align with specific field requirements.

Urban air pollution poses significant risks to cultural heritage buildings, particularly in polluted megacities like Delhi, India. The Red Fort, a UNESCO World Heritage Site and a symbol of India’s rich history, is highly susceptible to degradation caused by air pollutants. Despite its great importance as an Indian and world heritage site, no studies have focused on characterizing its constituent materials or the degradation phenomena taking place. This study was developed in the framework of the MAECI (Italian Ministry of Foreign Affairs) and the Department of Science and Technology under the Ministry of Science and Technology, India, project: Indo—Italian Centre of Excellence for Restoration and Assessment of Environmental Impacts on Cultural Heritage Monuments. To understand their composition and degradation, Vindhyan sandstone and black crust samples were studied. Scanning Electron Microscopy with Energy Dispersive X-ray Spectroscopy (SEM-EDX), X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) indicated that the red sandstone predominantly consisted of quartz and microcline, while the black crusts mainly comprised gypsum, bassanite, weddellite, quartz, and microcline. The analysis attributed the formation of gypsum to exogenous sources, such as construction activities and cement factory emissions. This pioneering study provides a basis for further research into the impacts of air pollution on Indian patrimony and promotes conservation strategies.

Environmental sustainability assessment is a crucial part of the management of natural resources. Remote Sensing based environmental land cover indices such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Water Index (NDWI), Normalized Difference Built-up Index (NDBI), Normalized Difference Moisture Index (NDMI), and its associated Land Surface Temperature (LST) are the major governing factors for the environmental processes that happen on the surface of the earth . These NDVI, NDWI, NDBI, NDMI, and LST are generated for 2020 using the Landsat satellite datasets. The process-based relationship among them is complex and involves various parameters but may be easily represented by multiple linear regression models. Principal Component Analysis (PCA) is one such type that efficiently handles and evaluates the contribution of each of these factors to each other based on the sampling units. The study area is the upper Ramganga catchment in the Indian Himalayas, consisting of 117 sub-catchments. These catchment units (samples) are entangled with these environmental factors. The results of the PCA reveal the relationship between each of the environmental factors and their priority. Based on the uncorrelated factors priority suggestion from the PCA, catchment units were classified as high, moderate, or low categories based on their dominance in the relationship among the factors. These spatial variations in the environmental factors can help to assess the sustainability of resources in the Himalayan catchment.