1
Significant differences between different climate scenarios result in different simulated recharge. All scenarios show increasing trend in temperature while trend in precipitation can decrease or increase (see Table 1). As shown in Figure 5, the GFDL climate model under A1FI scenario shows highest decrease in estimated recharge due to lower precipitation, higher temperature and higher solar radiation (Table.1). Moreover, in Figure 6, recharge estimated by the RI map shows excellent agreement with the estimated recharge by the HELP3 model in terms of average and total recharge amount to the aquifer system. The computed runoff data is from 1950 to 1999. Then, we use HELP3 to predict recharge in this period to calculate a recharge index (RI) and delineate the recharge index map for the Southern Hills aquifer system. The recharge index is defined as the percentage of precipitation that recharges aquifers. Finally, the HELP3 model is applied to recharge estimation from 2001 to 2100. A high-resolution recharge index map is obtained to quantify the spatial impact of different climate model scenarios on the long-term groundwater availability for the Southern Hills aquifer system overlain by sixteen HUCs. The computed runoff from USGS WaterWatch database, and the USGS Base Flow Index map (BFI) is used to determine the amount of runoff over each HUC. Then, the HELP3 is calibrated by comparing the estimated runoff to WaterWatch runoff from 1950 to 1999. Then we use the calibrated HELP3 model to simulate temporal and spatial recharge under considered climate scenarios on the Southern Hills aquifer system from 2001 to 2100. Delineating the spatial impact is valuable not only in the context of groundwater resource protection, but also for general land use management. Climate Change Impact on Groundwater Recharge in Southeastern Louisiana and Southwestern Mississippi H13B Characterization of Groundwater Systems III | AGU Fall Meeting 2012, San Francisco, CA, USA | 5-9 December 2012 Ehsan Beigiand Frank T.-C. Tsai Department of Civil and Environmental Engineering, Louisiana State University, Baton Rouge, LA 70803 E-mail: [email protected]; [email protected] [1] Introduction We employ the Hydrologic Evaluation of Landfill Performance (HELP3) model as our hydrologic model in conjunction with geographic information system (GIS) to estimate spatial- temporal distribution of potential recharge for a regional scale over the next century[3]. The approach uses daily precipitation, temperature and solar radiation records in addition to land use/land cover and soil data, which is similar to the method of Jyrkama et al. (2007)[2]. The HELP3 model is especially suitable for our recharge study due to Louisiana humid climate and the use of a regional-scale water budget approach. Figure 2 shows the framework, where the HELP3 model links with the climate model scenarios to estimate recharge. We calibrate the HELP3 model using the computed runoff of individual hydrologic units in terms of Hydrologic Unit Codes (HUCs) from the USGS WaterWatch database. Increases on concentrations of CO 2 and other greenhouse gases have a significant effect on climate, precipitation and hydrology, which in turn influence on aquifer recharge. Recharge is an important hydrologic process to replenish an aquifer and plays an important role in groundwater resources availability. To study climate impact on groundwater availability, this study develops a GIS-based integrated framework to connect several climate model scenarios to a high-resolution hydrologic model to quantify long-term groundwater recharge for the Southern Hills Aquifer System. Acknowledgements: The project is partially funded by the National Science Foundation EAR-10450646, the USGS-NIWR under Grant No. G10AP00136, and the Louisiana Water Resources Research Institute. [7] Temporal Result [2] Case Study [4] HELP3 Input Data 1) Soil and Land Use Data Detailed surficial soil property and land cover are obtained from the NRCS and the USGS database to derive a map of curve number for the HELP3 model. Well logs and driller’s logs are analyzed to determine stratigraphic lithology up to the top-most major sand encountered beneath the soil layer. 2) Evapotranspiration Data Leaf Area Index (LAI) is obtained from LAI data sets for land surface and climate modeling[4]. Evaporative zone depth is calculated based on the maximum rooting depth of vegetation [1]. 3) Daily Weather Data and Climate Change Scenarios For a regional scale, we use global circulation model (GCM) downscaled daily meteorological data (daily precipitation, temperature and solar radiation) obtained from USGS CASCaDE Project Climate Data as the forcing input to the HELP3 model. The emission scenarios considered in this study are A2, B1 and A1FI from Parallel Climate Model 1 (PCM) and from the NOAA Geophysical Fluid Dynamics Lab's GFDL CM2.1 model. Table 1 lists the annual trend in precipitation, temperature and solar radiation for the aquifer system. Table 2 shows main assumptions and consequences under the considered climate scenarios[5]. [8] Conclusions • Future recharge estimation is highly dependent on selected climate scenarios due to the substantial differences between the scenarios. While groundwater recharge is predicted to decrease under GFDL(A1FI, A2) and PCM (A1FI), it will increase under other scenarios. Also, the average annual recharge rate is predicted to decease from 313 to 264 mm/year under GFDL-A1FI scenario for the Southern Hills aquifer system. • The GFDL climate model predicts more intense change in precipitation and temperature compared to those of the PCM model. • The recharge map shows recharge variation in different areas in the Southern Hills aquifer system due to variations in land use, underlying soil characteristics and groundwater level. • The calculated recharge index map shows good agreement to the total estimated recharge by the HELP3 model under all considered scenarios. • [1] Canadell,J., Jakson, R.B., Ehleniger,J.R., Mooney, H.A., SALA, O.E., Schulze, E.D, 1996. Maximum rooting depth of vegetation type at the global scale. Oecologia, 108:583-595. • [2] Jyrkama, M.I., Sykes, J.F., 2007. The impact of climate change on spatially varying groundwater recharge in the Grand River watershed (Ontario). Journal of Hydrology 338, 237–250. • [3] Schroeder, P.R., Dozier, T.S., Zappi, P.A., McEnroe, B.M., Sjostrom, J.W., Peyton, R.L., 1994. The Hydrologic Evaluation of Landfill Performance (HELP) Model: Engineering Documentation for Version 3. EPA/600/R-94/168b. United States Environmental Protection Agency, Office of Research and Development, Washington, DC, USA. • [4] Yuan, H., Dai, Y., Xiao, Z., Ji, D., Shangguan, W., 2011. Reprocessing the MODIS Leaf Area Index Products for Land Surface and Climate Modelling. Remote Sensing of Environment, 115(5), 1171-1187. doi:10.1016/j.rse.2011.01.001 • [5] IPCC. 2008. Climate Change and Water. IPCC Technical Paper VI References H13B- 1317 [3] Methodology Figure 2: The framework for groundwater recharge estimation. The Southern Hills aquifer system shown in Figure 1, located in southeastern Louisiana and southwestern Mississippi, is one of the sole source aquifer which provides more than 50 percent of the drinking water consumed in the area overlying the aquifer and has no substitute drinking water source(s). The aquifer system covers 14 counties of Mississippi State and 10 parishes of Louisiana State. The study area is divided into 145,256 different subareas, each of which has a unique climate zone, land use, and soil type characteristic. Climate Downscaled Model Annual Trend Scenarios Precipitation (mm/year) Temperature (°C/year) Solar radiation (Langley/year) PCM B1 A2 A1FI −0.25 +0.18 −0.92 +0.022 +0.030 +0.042 −0.0018 −0.0024 −0.0014 GFDL B1 A2 A1FI +0.61 −1.77 −2.78 +0.028 +0.047 +0.059 +0.003 +0.009 +0.0011 Table 1: Annual trend in Precipitation, Temperature and Solar Radiation from 1950 to 2100 for Southern Hills Aquifer System [5] Model Application and Result [3] Methodology [6] Spatial Result Figure 5: Cumulative difference in recharge with respect to the average recharge from 1950 to 1999 for all scenarios. -0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 2000 2020 2040 2060 2080 2100 Recharge Difference(m) Time (year) GFDL-A1FI-HELP3 GFDL-A1FI-Recharge Index 0 5 10 15 20 25 30 35 2000 2020 2040 2060 2080 2100 Recharge Cumulative (m) Time (year) GFDL-A1FI-Recharge index GFDL-A1FI-HELP3 Figure 6: Cumulative recharge estimated by the HELP3 compared to that using the recharge index map under the same precipitation. The recharge index map in Figure 3(a) is obtained from the HELP3 estimated recharge divided by precipitation during 1950 to 1999. The recharge time lag map in Figure 3(b) is obtained by time delay between precipitation and recharge. Recharge index map can be applied to estimating recharge for each subarea given precipitation. In this study, the estimated recharge using the RI map is compared to the HELP3 simulated recharge. Moreover, the mean annual recharge change in the Southern Hills aquifer system from 1950 to 2100 is shown in Figure 4 under A1FI scenario and GFDL model. The average annual recharge rate decreases 49 mm/year from 313 to 264 mm/year, according to the Table 1, which shows decrease trend in the amount of precipitation and increase in temperature. Figure 3: (a) Recharge index map and (b) recharge time lag map for the Southern Hills aquifer system. -6 -5 -4 -3 -2 -1 0 1 2 2000 2020 2040 2060 2080 2100 Recharge Cumulative Difference (m) Time (year) GFDL-A1FI GFDLA2 GFDLB1 PCM-A1FI PCMA2 PCMB1 B1 A2 A1FI homogeneous world Globalization Sustainableand Environmental 1.1 -2.9 °C heterogeneousworld Regionalization Economic development 2.0 -5.4 °C homogeneous world Regionalization Rapid economic growth 1.4 -6.4 °C Table 2: Characteristic of Emission Scenarios Used
