Assessment of Water Availability and Stress in Louisiana using Multi-Scale Datasets and Model Outputs Hisham Eldardiry 1,3, Emad Habib 1,3, David M. Borrok.

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Presentation transcript:

Assessment of Water Availability and Stress in Louisiana using Multi-Scale Datasets and Model Outputs Hisham Eldardiry 1,3, Emad Habib 1,3, David M. Borrok 2,3, Whitney Broussard 3 1 Department of Civil Engineering, University of Louisiana at Lafayette 2 School of Geosciences, University of Louisiana at Lafayette 3 Institute for Coastal and Water Research, University of Louisiana at Lafayette

Outline 1.Study Objectives 2.Data Availability 3.Water Supply Stress Index (WaSSI) 4.Conclusions

The objective of this study is to integrate different datasets to assess water stresses in Louisiana. Study Objectives The assessment is based on the balance between availability of surface and groundwater resources, and the historical groundwater and surface water use.

Outline 1.Project Objectives 2.Data Availability 3.Water Supply Stress Index (WaSSI) 4.Conclusions

Water Budget Water Supply SW NHDPlus-2 GW Water Use SWGW Data Availability National Hydrography Dataset Temporal Scale: Monthly and Annual average ( ) Spatial Scale: Streamlines Order of Stream Lines in LA

Water Budget Water Supply SW NHDPlus-2 GW Recharge Rate Water Use SWGW Data Availability Generated by multiplying a grid of base- flow index (BFI) values (Wolock, 2003) by a grid of mean annual runoff values (Gebert et al., 1987). Mean Annual Recharge (mm/year)

Water Budget Water Supply SW NHDPlus-2 GW Recharge Rate Water Use SW Irrigation Industrial Public Supply Power Generation GW Irrigation Industrial Public Supply Rural Domestic Data Availability Parish Scale Every 5 Years

Water Use Surface Water (SW) Groundwater (GW) USGS data available on Parish Scale  Disaggregation into watershed scale (HUC12) Water Use

Area of HUC12 / Area of Parish Weight (W1) (A) Crop Area in HUC12 / Crop Area in Parish Weight (W2) (CA) Max(SO) in HUC12 / SUM(Max(SO)) in Parish Weight (W3) (SO) Highly Developed area in HUC12 / Highly Developed area in Parish Weight (W4) (HD) SW Disaggregation

w huc =(W 1(A) *W 2(CA) *W 3(SO) ) (1/3) Total Irrigation SW Use in 2010 (HUC12 Scale-Disaggregation) Total Irrigation SW Use in 2010 (Parish Scale-USGS)

Disaggregation of Industrial Supply Use Based on Weighted Area, Stream Order, and Highly Developed Area Industrial Supply Use (Parish Scale) w huc =(W 1(A) *W 3(SO) *W 4(HD) ) (1/3)

Disaggregation of Public Supply Use Based on Weighted Area and Highly Developed Area w huc =(W 1(A) *W 4(HD) ) (1/2) Power Generation Use Diehl & Harris, 2014

GW Disaggregation Disaggregation of GW Withdrawals based on casing diameter of wells. Irrigation Industrial Public Supply Rural Domestic (Credit: Fabiane Barato and Whitney Broussard)

Outline 1.Project Objectives 2.Data Availability 3.Water Supply Stress Index (WaSSI) 4.Conclusions

Water Supply Stress Index (WaSSI) Water Use WW : total water withdrawal by SW/GW. WS: Water supply by SW/GW. ENV: factor accounting for environmental flow (taken as 50% of WS SW ) SW GW

Water Supply Stress Index (WaSSI) (Eldardiry et al., in prep.)

Sectoral-Based Stresses Irrigation Industrial Public Supply Power Generation

Source-Based Stresses (SW/GW) Stresses on SW sources due to SW Withdrawals Stresses on GW sources due to GW Withdrawals

Outline 1.Project Objectives 2.Data Availability 3.Water Supply Stress Index (WaSSI) 4.Conclusions

Conclusions The disaggregation into a HUC12 scale captures a greater level of spatial heterogeneity as compared to the parish or county scale. The sensitivity of WaSSI to surface water supply indicates that water stressed areas with large water consumption for thermoelectric facilities or irrigation have a higher probability of becoming stressed under climate variability. Identifying new opportunities for reallocation of surface water use to reduce groundwater over pumping and improve water sustainability in Louisiana.

Thank You! Hisham Eldardiry Cellphone: (337)