Understanding temporal and spatial characteristics of regional climate is essential for decision making in water resource management. Established statistical and GIS techniques were used to evaluate annual and seasonal variations of rainfall and temperature in time and space from 1979 to 2013 in the Limpopo River Basin (LRB). Annual means of rainfall in the LRB varied between 160 and 1109 mm, generally from west to east of the basin during the study period. Annual minimum and maximum temperature ranged from 8 °C in the south to 20 °C in the east of the basin, and 23 °C in the south of the basin to 32 °C in the east. The respective coefficients of variation (CVs) of these variables showed an inverse pattern to the annual values, with rainfall having high CV values (28% to 70% from east to west of the basin) compared to temperature CV values. Seasonal variations followed similar patterns as annual variations for the individual variables examined. Trend analysis showed upward trends for both annual and seasonal rainfall in most parts of the basin, except for the winter season which showed a decreasing trend. Analysis of minimum temperature on an annual basis and for the winter season and spring season shows upward trends during the study period over the whole basin while minimum temperature for summer and autumn showed decreasing trends. Maximum temperature, by contrast, showed decreasing trends on an annual, summer, autumn, and spring basis but an increasing trend for winter during the study period in most parts of the basin.

Trends in high, moderate, and low streamflow conditions from United States Geological Survey (USGS) gauging stations were evaluated for a period of 1951–2013 for 18 selected watersheds in South Dakota (SD) using a modified Mann-Kendall test. Rainfall trends from 21 rainfall observation stations located within 20-km of the streamflow gauging stations were also evaluated for the same study period. The concept of elasticity was used to examine sensitivity of streamflow to variation in rainfall and land cover (i.e., grassland) in the study watersheds. Results indicated significant increasing trends in seven of the studied streams (of which five are in the east and two are located in the west), nine with slight increasing trends, and two with decreasing trends for annual streamflow. About half of the streams exhibited significant increasing trends in low and moderate flow conditions compared to high flow conditions. Ten rainfall stations showed slight increasing trends and seven showed decreasing trends for annual rainfall. Streamflow elasticity analysis revealed that streamflow was highly influenced by rainfall across the state (five of eastern streams and seven of western streams). Based on this analysis, a 10% increase in annual rainfall would result in 11%–30% increase in annual streamflow in more than 60% of SD streams. While streamflow appears to be more sensitive to rainfall across the state, high sensitivity of streamflow to rapid decrease in grassland area was detected in two western watersheds. This study provides valuable insight into of the relationship between streamflow, climate, and grassland cover in SD and would support further research and stakeholder decision making about water resources.

Baseflow plays an important role in maintaining streamflow. Seventeen gauged watersheds and their characteristics were used to develop regression models for annual baseflow and baseflow index (BFI) estimation in Michigan. Baseflow was estimated from daily streamflow records using the two-parameter recursive digital filter method for baseflow separation of the Web-based Hydrograph Analysis Tool (WHAT) program. Three equations (two for annual baseflow and one for BFI estimation) were developed and validated. Results indicated that observed average annual baseflow ranged from 162 to 345 mm, and BFI varied from 0.45 to 0.80 during 1967–2011. The average BFI value during the study period was 0.71, suggesting that about 70% of long-term streamflow in the studied watersheds were likely supported by baseflow. The regression models estimated baseflow and BFI with relative errors (RE) varying from −29% to 48% and from −14% to 19%, respectively. In absence of reliable information to determine groundwater discharge in streams and rivers, these equations can be used to estimate BFI and annual baseflow in Michigan.