Understanding of rainfall is an important issue for Uttarakhand, India which having varied topography and due to that extreme rainfall causes quick runoff which warns structural and functional safety of large structures and other natural resources. In this study, an attempt has been made to determine the best-fit distribution of the annual series of rainfall data for the period of 1991–2002 of 13 districts of Uttarakhand. A best-fit distribution such as Chi-squared, Chi-squared (2P), exponential, exponential (2P), gamma, gamma (3P), gen. extreme value (GEV), log-Pearson 3, Weibull, Weibull (3P) distributions was applied. Comparisons of best distributions were based on the use of goodness-of-fit tests such as Kolmogorov–Smirnov, Anderson–Darling, and Chi squared. Results showed that the Weibull distribution performed the best with 46% of the total district, while the second best distribution was Chi squared (2P) and log-Pearson. The results of this study would be useful to the water resource engineers, policy makers and planners for the agricultural development and conservation of natural resources of Uttarakhand.

Highlights Spring flows are the primary source of water for rural Himalayan communities. An attempt was made to understand the potential of spring discharge as an alternative irrigation source. Improved management of resources is vital to account for agricultural water use. Managing water resources is a collective endeavor for achieving water security. Abstract.With increasing population and restricted water and land resources, there is a growing concern for better planning of the available water and land resources. In the mountainous regions or mountains, there is limited land with uncertain water availability as the rainfall patterns pose a major threat to the livelihood of the people. Therefore, it becomes necessary to quantify and manage the available water resources in a sustainable way. People in the Himalayas are mainly dependent on the springs for drinking water, but not much attention has been dedicated to the development and conservation of these springs. A spring in the Tehri-Garhwal district of Uttarakhand state of India, has been continuously monitored to quantify the available water for domestic use and agriculture. In this study, an attempt is made to understand the potential of a spring for agricultural water use by evaluating the crop water requirement and potential improved strategies to increase the water productivity. Analysis proves that crop evapotranspiration is higher (946-1062 mm) for crops with extended duration (165-180 days) as compared to evapotranspiration (92.91 mm) of short duration (60 days) crops. The total water requirement for major crops in the area is 6411.35 mm and the monitored spring has the potential to supplement this water requirement. Adopting the system of rice intensification to increase the rice yield (by 49%), increases the water productivity. The sensitivity analysis of benefit to cost suggests that, an increase in the crop yield by 30% can increase the revenue in the study area by Rs.3687197, which is 217% more than the input costs. Therefore, it is essential to optimize the available water and area for irrigation to achieve the global water security for increasing population. Further, utilizing springs as potential irrigation sources will support rural community in meeting domestic water requirement and achieving environmental sustainability. Findings of this study will help in planning and implementing management strategies that are resilient in the face of future changes and improve the economic condition of farmers. Keywords: Crop evapotranspiration, Himalaya, Optimization, Sensitivity analysis, Spring.

Dar es Salaam, like other cities in Africa, experiences flash floods during the rainfall season that destroy infrastructure due to the overflow of rivers and blocked sewage. This study investigates the historical and future variability and changes in spatial and temporal rainfall over Dar es Salaam. Station data and Climate Hazards Group Infrared Precipitation with Stations (CHIRPS) gridded data crossing 38 years (1982–2019) were used as a baseline and the Coordinated Regional Climate Downscaling Experiment (CORDEX) dataset from 2021 to 2050 was used for projection under Representative Concentration Pathway (RCP 4.5) forcing scenarios. A trend analysis of historical data was conducted at monthly, seasonal, and annual timescales. Mann–Kendall statistical tests and Sen’s slope estimator were applied to identify the current trend direction and magnitude of changes in rainfall patterns over time. A standardized anomaly index (SAI) was also employed to detect the region’s trends in wetness and dryness. The spatial distribution of rainfall in the city was investigated using an inverse distance weighted (IDW) interpolation technique. The statistical results reveal that a non-significant trend in rainfall was observed on monthly, seasonal, and annual timescales. Generally, in the future (2021–2050), the annual cycle of rainfall shows a slight decrease in monthly rainfall, especially from January to August, and an increase from September to December compared to historical (1982–2019) rainfall, for most of studied locations. Spatially, the distribution of projected rainfall shows that the southern part of the city will experience higher rainfall than other parts. The most significant findings were a decrease in annual projected rainfall by 20%, the MAM projected rainfall season increased by 42%, and an increase of 38% of the OND-projected rainfall season. The findings of this study will be useful for the improved management and planning of the city.