The influence of El Niño Southern Oscillation (ENSO) on the north Indian temperature, precipitation, and potential evapotranspiration (PET) change patterns were evaluated during the monsoon season across the last century. Trends and shifts in 146 districts were assessed using nonparametric statistical tests. To quantify their temporal variation, the concept of apportionment entropy was applied to both the annual and seasonal scales. Results suggest that the El Niño years played a greater role in causing hydro-climatological changes compared to the La Niña or neutral years. El Niño was more influential in causing shifts compared to trends. For certain districts, a phase change in ENSO reversed the trend/shift direction. The century-wide analysis suggested that the vast majority of the districts experienced significant decreasing trends/shifts in temperature and PET. However, precipitation experienced both increasing and decreasing trends/shifts based on the location of the districts. Entropy results suggested a lower apportionment of precipitation compared to the other variables, indicating an intermittent deviation of precipitation pattern from the generic trend. The findings may help understand the effects of ENSO on the hydro-climatological variables during the monsoon season. Practitioners may find the results useful as monsoon is the most important season for India causing climate extremes.

The study focused on investigating the presence of change patterns in 600 unimpaired streamflow stations across the continental U.S. at different time intervals to understand the change patterns that can provide significant insight regarding climate variability and change. Each station had continuous streamflow data of at least 30 years (the entire dataset covered a range of 109 years). Presence of trends and shifts were detected in water year and the four seasons (fall, winter, spring, and summer) analyzing the water year and seasonal mean flows. Two non-parametric tests, namely, the Mann-Kendall test and the Pettitt’s test were used to identify the trends and the shifts, respectively. The results showed an increasing trend in the northeast and upper-mid regions, whereas southeast and northwest regions underwent a decrease. Shifts followed similar patterns as trends with higher number of stations with significant change. Fall and spring showed the highest number of stations with increasing and decreasing change, respectively, in the seasonal analyses. Results of this study may assist water managers to understand the streamflow change patterns across the continental U.S., especially at the regional scale since this study covers a long range of years with a large number of stations in each region.

Understanding the interconnections between oceanic-atmospheric climate variables and regional streamflow of the conterminous United States may aid in improving regional long lead-time streamflow forecasting. The current research evaluates the time-lagged relationship between streamflow of six geographical regions defined from National Climate Assessment and sea surface temperature (SST), 500-mbar geopotential height (Z₅₀₀), 500-mbar specific humidity (SH₅₀₀), and 500-mbar east-west wind (U₅₀₀) of the Pacific and the Atlantic Ocean using singular value decomposition (SVD). The spatio-temporal correlation between streamflow and SST was developed first from SVD and thus obtained correlation was later associated with Z₅₀₀, SH₅₀₀, and U₅₀₀ separately to evaluate the coupled interconnections between the climate variables. Furthermore, the associations between regional streamflow and the El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation, and Atlantic Multidecadal Oscillation were evaluated using the derivatives of continuous wavelet transform. Regional SVD analysis revealed significant teleconnection between several regions and climate variables. The warm phase of equatorial SST had shown a stronger correlation with the majority of streamflow. Both SVD and wavelet analyses concluded that the streamflow variability of the regions in close proximity to the Pacific Ocean was strongly associated with the ENSO. Improved knowledge of teleconnection of climate variables with regional streamflow variability may help in regional water management and streamflow prediction studies.

The study investigated the impact on water supply and demand as an effect of climate change and population growth in the Las Vegas Valley (LVV) as a part of the Thriving Earth Exchange Program. The analyses evaluated future supply and demand scenarios utilizing a system dynamics model based on the climate and hydrological projections from the Coupled Model Intercomparison Project phases 3 and 5 (CMIP3 and CMIP5, respectively) using the simulation period expanding from 1989 to 2049. The main source of water supply in LVV is the water storage in Lake Mead, which is directly related to Lake Mead elevation. In order to assess the future water demand, the elevation of Lake Mead was evaluated under several water availability scenarios. Fifty-nine out of the 97 (27 out of the 48) projections from CMIP5 (CMIP3) indicated that the future mean elevation of Lake Mead is likely to be lower than the historical mean. Demand forecasts showed that the Southern Nevada Water Authority’s conservation goal for 2035 can be significantly met under prevalent conservation practices. Findings from this study can be useful for water managers and resource planners to predict future water budget and to make effective decisions in advance to attain sustainable practices and conservation goals.

Increase in the demand of food and fiber due to a rapid increase in population has imposed heavy stress on the water resource of the world, which has given rise to competition for this resource particularly in those areas where usage has exceeded the limits of availability. With the passage of time, this competition not only intensified but has escalated to the position of conflict, moreover improper management and inequitable distribution has added more stress on the water resources. The Indus Basin Irrigation System (IBIS) Pakistan being the largest contiguous irrigation system is not an exception to twin problem of improper management and inequitable distribution. Water management and distribution in the IBIS are governed by the Indus Water Treaty (IWT) among the India and Pakistan, and via Water Apportionment Accord (WAA) within the provinces in Pakistan. In this paper, we have developed a basin scale decision support system using water evaluation and planning (WEAP) modeling framework to evaluate the water distribution among provinces based on Water Apportionment Accord and suggest the way towards conflict management and mitigation. WEAP model simulates the reservoir (Tarbela, Mangla, and Chashma), rivers, canal, and link canals at the supply nodes; and canal command areas for agriculture and domestic demand nodes. Simulating the water system historically for 23 years from 1991 to 2013, it was observed that every year Sindh has experienced deficiency and cut off from its allocated share. Punjab has also faced deficiency and cut off from an allocated share in every Kharif Season but in a lower proportion, whereas Punjab has extracted excess of its share 11 times in 23 years in Rabi Season.

The study developed a preliminary system dynamics model to explore several water management scenarios in the major river systems of the Indus River Basin (IRB) in Pakistan. The performance of the two major reservoirs i.e., Tarbela and Mangla, located on the Indus and Jhelum Rivers, respectively, were evaluated under different flow conditions. Empirical relationships between upstream and downstream locations of each of the existing reservoirs and barrages were developed and were validated against historical flow data. Inflows to the reservoirs were varied across a wide range. The environmental flows in terms of the net contribution to the Arabian Sea, the most downstream location of the IRB, were also calculated under each of the scenarios. The results suggest that the existing conditions can be improved by proper regulations of the reservoirs under different scenarios. However, with the high variation in seasonal flows, infrastructural development will be required to tackle extreme conditions.