Manoj K. Jha

Spatio-temporal long-term (1950–2009) temperature trend analysis in North Carolina, United States

This study analyzed long-term (1950–2009) annual and seasonal time series data of maximum and minimum temperature from 249 uniformly distributed stations across the State of North Carolina, United States. The Mann-Kendall and Theil-Sen approach were applied to quantify the significance and magnitude of trend, respectively. A pre-whitening technique was applied to eliminate the effect of lag-1 serial correlation. For most stations over the period of the past 60xa0years, the difference between minimum and maximum temperatures was found decreasing with an overall increasing trend in the mean temperature. However, significant trends (confidence levelu2009≥u200995xa0%) in the mean temperature analysis were detected only in 20, 3, 23, and 20xa0% of the stations in summer, winter, autumn, and spring, respectively. The magnitude of the highest warming trend in minimum temperature and the highest cooling trend in maximum temperature was +0.073xa0°C/year in the autumn season and −0.12xa0°C/year in the summer season, respectively. Additional analysis in mean temperature trend was conducted on three regions of North Carolina (mountain, piedmont, and coastal). The results revealed a warming trend for the coastal zone, a cooling trend for the mountain zone, and no distinct trend for the piedmont zone. The Sequential Mann-Kendall test results indicated that the significant increasing trends in minimum temperature and decreasing trend in maximum temperature had begun around 1970 and 1960 (change point), respectively, in most of the stations. Finally, the comparison between mean surface air temperature (SAT) and the North Atlantic Oscillation (NAO) concluded that the variability and trend in SAT can be explained partially by the NAO index for North Carolina.

Hydrological response due to projected climate variability in Haw River watershed, North Carolina, USA

ABSTRACT Global climate variations are expected to cause serious challenges to water resources planning and management, including an increase in sea level, abrupt changes in rainfall patterns and changes in ecosystems. This study evaluates impacts of mid-century climate variability as projected by climate models in the Haw River watershed, which contributes significantly to Jordan Lake, a major source of drinking water supply in central North Carolina, USA. The watershed-based hydrological model, Soil and Water Assessment Tool (SWAT), was successfully calibrated with very good to excellent performance. Projected precipitation and temperature information for 2040–2069 from four dynamically downscaled regional climate models (RCMs) was used to force the SWAT modeling set-up of the watershed. On a long-term basis, a 38% decrease in the precipitation in early fall is expected while spring months are expected to receive 30% higher precipitation compared to the baseline condition (1980–2009). Water yield was found to increase in spring months, with a maximum of 74% increase on average. Summer months are expected to have on average 8% higher evapotranspiration (ET) than the baseline. Analysis of the change in average monthly streamflow at the watershed outlet (which leads to Lake Jordan) shows that there might be, on average, an 80% increase in streamflow in spring months (February, March, April and May), with the greatest increase (107%) in May. In general, simulation results indicated that the hydrological response of the watershed is very sensitive to the potential variation in climate (precipitation and temperature), with precipitation being one of the decisive factors in water yield increase. Editor Z.W. Kundzewicz Associate editor N. Verhoest

Groundwater Flow Modeling in the Shallow Aquifer of Buffalo Creek, Greensboro

U.S. Environmental Protection Agency categorized Buffalo Creek as one of the impaired waters in Cape Fear River Basin, North Carolina, due to high concentrations of metals and pathogens. These contaminants originate from effluents discharged from industries and agricultural activities. This study used a numerical groundwater flow modeling approach to investigate the surface and groundwater interaction in the Buffalo Creek watershed for the fate and transport of contaminants. The movement of groundwater flow was simulated using MODFLOW while the particle tracking was analyzed by the MT3D model. MODFLOW solves groundwater flow equation using the finite-difference approximation. The flow region which covers both North and South Buffalo Creek was subdivided into blocks or cells in which the medium properties were assumed to be uniform. The cells are made from a grid of mutually perpendicular lines that are variably spaced depending upon the location. Spatial locations and distributions of stream networks, elevations, boundary conditions (no flow and constant, variable head zones), existing well locations, and industrial as well as wastewater effluent discharge locations were developed within ArcGIS environment. The modeling tasks of this study are domain characterization (database for surface elevation and stream network), modeling setup, and calibration and validation of the model using observed data. The observed data for baseflow was obtained using the baseflow filter algorithm, which basically separates baseflow from streamflow based on nature of the hydrograph. The modeling setup and initial calibration results for the steady-state simulation are presented in this chapter.

Trend of Climate Variability in North Carolina During the Past Decades

Trend of climate variability in North Carolina for the period of 1950–2009 was investigated in this study with annual scale minimum temperature (T min), maximum temperature (T max), mean temperature (T mean), and precipitation data series from 249 evenly distributed meteorological stations. The trends were tested using Mann–Kendall (MK) test. Theil–Sen approach (TSA) and Sequential Mann–Kendall (SQMK) test were also applied to detect the magnitude and abrupt change of trend, respectively. Lag-1 serial correlation and double mass curve analysis were adopted to check the independency and in homogeneity of the data sets, respectively. For most regions and over the period of past 60 years, trend of T min was found increasing (on 73% of the stations) while for T max, it was found decreasing (on 74 % of the stations). Although the difference between T max and T min trends were decreasing, but increasing trend in T mean represent the overall temperature increasing pattern in North Carolina. Magnitude of T max, T min, and T mean were found to be −0.05 °C/decade, +0.08 °C/decade, and +0.02 °C/decade, respectively, as determined by the TSA method. The SQMK test identified a significant positive shift of T mean during 1990s. For precipitation trends analysis, almost equal nos. of stations was showing statewide positive and negative trends in annual time series. Annually, positive (negative) significant trends, seven (three) nos. of stations were observed at the 95 and 99 % confidence levels. A magnitude of precipitation trend of +3.3 mm/decade was calculated by the TSA method. No abrupt shift was found in precipitation data series over the period by the SQMK test.

Designing a Remote In Situ Soil Moisture Sensor Network for Small Satellite Data Retrieval

This chapter introduces an application of small satellite for environmental monitoring using real-time data that focuses on measured soil moisture and temperature using in situ sensor network. Soil Moisture Active Passive Mission (SMAP) uses microwave radar and radiometer to sense surface soil moisture condition but gives coarser result than the in situ data. To overcome the limitation of accuracy in SMAP mission, the proposed architecture will provide sensor data via a Ground Monitoring Wireless Sensor Network (GM-WSN) where data is collected by small satellite(s) operating in Lower Earth Orbit (LEO). The satellite will store the data until it passes over a ground station whereby it is communicated back to earth. The motivation for developing satellite accessible in situ measurements is to retrieve information from remote areas like Lake Tana in Ethiopia, where human accessibility is difficult. Hence, those important and unattended places would be covered by the proposed system. Another key attribute of this architecture is that it addresses four (climate, carbon, weather, and water) out of six NASA’s earth science strategic focus areas. The GM-WSN will consist of a sensor network that will measure soil moisture and temperature. The base station function is to fuse the data from the sensors, provide a time stamp, and format the data to be transmitted to satellite. It will also act as transceiver for ground to space communication using the amateur VHF/UHF radio band that has a maximum data rate of 9.6 kbps and will provide health maintenance and power management of network.

Assessment of Climate Change Impact on Watershed Hydrology

Evidence of pronounced fluctuation in climate variability has caused numerous impact assessment studies of climate variability and change on watershed hydrology. Several methods of impact assessment have been used over the last decade which basically incorporates atmospheric-ocean circulation-based climate models’ projection of changes in meteorological variable into the simulation of land surface hydrological processes. In this study, we have evaluated two methods, frequency perturbation and direct use of data, through forcing of a simulation model with data from a suite of global climate models. Hydrologic response of a typical watershed in Midwest was evaluated for the change in climatic condition. Frequency perturbation method found precipitation decrease by 17 % and reduction in temperature by 0.43 °C on an average annual basis. The changes when applied through the watershed simulation model resulted in 13 % reduction in evapotranspiration (ET) and 25 % reduction in water yield. In contrast, direct method with 1.25 % decrease in precipitation and 0.2 °C decrease in temperature on annual basin found an increase of 1.8 % for ET and 5 % reduction in water yield. Changes in ET and water yield on temporal and spatial scale due to changes in future climate are likely to have severe implications for the water availability. However, more research is needed to evaluate several impact assessment methods for more accurate analysis.

Watershed modeling of Haw River Basin for Hydrology, Water Quality and Climate Change Study

Global climate change is expected to cause lot of serious challenges such as increase in sea level, difficulties in agriculture, abrupt changes in rainfall patterns and changes in ecosystem. Extreme climatic events are also expected to occur more frequently in the future. The study was undertaken to evaluate water availability issues in for the Jordan Lake in North Carolina under various extreme climatic conditions as influenced by the potential climate change. The widely used hydrologic simulation model Soil and Water Assessment Tool (SWAT) was calibrated from January 2000 to October 2009 using two USGS gage station monthly observed streamflow data. The calibrated SWAT model evidenced very good to excellent performance (R2 from 0.87 to 0.90 and Nash-Sutcliffe Efficiency (E) from 0.86 to 0.90). During Validation phase SWAT model showed very good performance (R2 from 0.86 to 0.89 and E from 0.76 to 0.88). Initial modeling results are promising, which form the basis for hydrological impact assessment of the potential climate change in the Haw River Watershed. This will be accomplished by coupling the calibrated modeling setup with climate models recommended in the IPCC Climate Change Assessment report.