Urban Water Management Considering Reclaimed Wastewater and Runoff as a New Water Resource for City of Tehran, Iran

Tehran, the capital of Iran, like many megacities in the world is faced with increasing freshwater demand and water resources limitation due to the rapid growth of population. In this paper, water reuse and wastewater recycling are considered as a sustainable solution for water supply and wastewater management of Tehran. A linear programming optimization model with the object of cost minimization is used to allocate water between users and resources, concerning the water quantity and quality of each one. Ultimately the economic and environmental effects of this strategy will be presented as the conclusion of this study. According to this study, improving wastewater treatment plants and control of water quality in canals and streams in order to substitute these two new resource for freshwater and groundwater have positive environmental and economic effects. The examples of environmental benefits are reducing pollution loads to receiving streams, adjusting increasing water demand and preventing groundwater level drawdown especially in the period of drought. In addition to the environmental benefits, although improving wastewater treatment plants and control of water quality in canals and streams need considerable investments, long usage of these two new recourses is more worthwhile

Mapping Surface Heat Fluxes by Assimilating SMAP Soil Moisture and GOES Land Surface Temperature Data

Surface heat fluxes play a crucial role in the surface energy and water balance. In situ measurements are costly and difficult, and large-scale flux mapping is hindered by surface heterogeneity. Previous studies have demonstrated that surface heat fluxes can be estimated by assimilating land surface temperature (LST) and soil moisture to determine two key parameters: a neutral bulk heat transfer coefficient (CHN) and an evaporative fraction (EF). Here a methodology is proposed to estimate surface heat fluxes by assimilating Soil Moisture Active Passive (SMAP) soil moisture data and Geostationary Operational Environmental Satellite (GOES) LST data into a dual-source (DS) model using a hybrid particle assimilation strategy. SMAP soil moisture data are assimilated using a particle filter (PF), and GOES LST data are assimilated using an adaptive particle batch smoother (APBS) to account for the large gap in the spatial and temporal resolution. The methodology is implemented in an area in the U.S. Southern Great Plains. Assessment against in situ observations suggests that soil moisture and LST estimates are in better agreement with observations after assimilation. The RMSD for 30 min (daytime) flux estimates is reduced by 6.3% (8.7%) and 31.6% (37%) for H and LE on average. Comparison against a LST-only and a soil moisture-only assimilation case suggests that despite the coarse resolution, assimilating SMAP soil moisture data is not only beneficial but also crucial for successful and robust flux estimation, particularly when the uncertainties in the model estimates are large.Water Resource