Large-Scale Total Water Storage and Water Flux Changes over the Arid and Semiarid Parts of the Middle East from GRACE and Reanalysis Products

© 2016 The Author(s). Previous studies indicate that water storage over a large part of the Middle East has been decreased over the last decade. Variability in the total (hydrological) water flux (TWF, i.e., precipitation minus evapotranspiration minus runoff) and water storage changes of the Tigris–Euphrates river basin and Iran’s six major basins (Khazar, Persian, Urmia, Markazi, Hamun, and Sarakhs) over 2003–2013 is assessed in this study. Our investigation is performed based on the TWF that are estimated as temporal derivatives of terrestrial water storage (TWS) changes from the Gravity Recovery and Climate Experiment (GRACE) products and those from the reanalysis products of ERA-Interim and MERRA-Land. An inversion approach is applied to consistently estimate the spatio-temporal changes of soil moisture and groundwater storage compartments of the seven basins during the study period from GRACE TWS, altimetry, and land surface model products. The influence of TWF trends on separated water storage compartments is then explored. Our results, estimated as basin averages, indicate negative trends in the maximums of TWF peaks that reach up to -5.2 and -2.6 (mm/month/year) over 2003–2013, respectively, for the Urmia and Tigris–Euphrates basins, which are most likely due to the reported meteorological drought. Maximum amplitudes of the soil moisture compartment exhibit negative trends of -11.1, -6.6, -6.1, -4.8, -4.7, -3.8, and -1.2 (mm/year) for Urmia, Tigris–Euphrates, Khazar, Persian, Markazi, Sarakhs, and Hamun basins, respectively. Strong groundwater storage decrease is found, respectively, within the Khazar -8.6 (mm/year) and Sarakhs -7.0 (mm/year) basins. The magnitude of water storage decline in the Urmia and Tigris–Euphrates basins is found to be bigger than the decrease in the monthly accumulated TWF indicating a contribution of human water use, as well as surface and groundwater flow to the storage decline over the study area

Assimilation of Streamflow Observations

Streamflow is arguably the most important predictor in operational hydrologic forecasting and water resources management. Assimilation of streamflow observations into hydrologic models has received growing attention in recent decades as a cost-effective means to improve prediction accuracy. Whereas the methods used for streamflow data assimilation (DA) originated and were popularized in atmospheric and ocean sciences, the nature of streamflow DA is significantly different from that of atmospheric or oceanic DA. Compared to the atmospheric processes modeled in weather forecasting, the hydrologic processes for surface and groundwater flow operate over a much wider range of time scales. Also, most hydrologic systems are severely under-observed. The purpose of this chapter is to provide a review on streamflow measurements and associated uncertainty and to share the latest advances, experiences gained, and science issues and challenges in streamflow DA. Toward this end, we discuss the following aspects of streamflow observations and assimilation methods: (1) measurement methods and uncertainty of streamflow observations, (2) streamflow assimilation applications, and (3) benefits and challenges streamflow DA with regard to large-scale DA, multi-data assimilation, and dealing with timing errors