Evaluation of Hydrological Application of CMADS in Jinhua River Basin, China

Evaluating the hydrological application of reanalysis datasets is of practical importance for the design of water resources management and flood controlling facilities in regions with sparse meteorological data. This paper compared a new reanalysis dataset named CMADS with gauge observations and investigated the performance of the hydrological application of CMADS on daily streamflow, evapotranspiration, and soil moisture content simulations. The results show that: CMADS can represent meteorological elements including precipitation, temperature, relative humidity, and wind speed reasonably for both daily and monthly temporal scales while underestimates precipitation compared with gauge observations slightly (<15%). The hydrological model using CMADS dataset as meteorological inputs can capture the daily streamflow chracteristics well overall (with a NS value of 0.56 during calibration period and 0.61 during validation period) but underestimates streamflow obviously (with a BIAS of − 42.42 % during calibration period and a BIAS of − 33.29 % during validation period). The underestimation of streamflow simulated with CMADS dataset is more seriously in dry seasons ( − 48.40 %) than that in wet seasons ( − 39.41 %) for calibration period. The model driven by CMADS estimates evapotranspiration and soil moisture content well compared with the model driven by gauge observations.

How might recharge change under projected climate change in western US?

Although groundwater is a major resource of water in the western US, little research has been done on the impacts of climate change on groundwater storage and recharge in the West. Here we assess the impact of projected changes in climate on groundwater recharge in the near (2021-2050) and far (2071-2100) future across the western US. Recharge is expected to decrease slightly (highly certain) in the West (-1.6%) and Southwest (-2.9%) regions in the near future and decrease considerably (highly certain) in the South region (-10.6%) in the far future. The Northern Rockies region is expected to get more recharge (highly certain) in both the near (+5.0%) and far (+9.0%) future. In general, southern portions of the western US are expected to get less recharge in the future and northern portions will get more. This study also shows that climate change interacts with land surface properties to affect the amount of recharge that occurs in the future.

Development of a gridded meteorological dataset over Java island, Indonesia 1985-2014

We describe a gridded daily meteorology dataset consisting of precipitation, minimum and maximum temperature over Java Island, Indonesia at 0.125°×0.125° (~14 km) resolution spanning 30 years from 1985-2014. Importantly, this data set represents a marked improvement from existing gridded data sets over Java with higher spatial resolution, derived exclusively from ground-based observations unlike existing satellite or reanalysis-based products. Gap-infilling and gridding were performed via the Inverse Distance Weighting (IDW) interpolation method (radius, r, of 25 km and power of influence, α, of 3 as optimal parameters) restricted to only those stations including at least 3,650 days (~10 years) of valid data. We employed MSWEP and CHIRPS rainfall products in the cross-validation. It shows that the gridded rainfall presented here produces the most reasonable performance. Visual inspection reveals an increasing performance of gridded precipitation from grid, watershed to island scale. The data set, stored in a network common data form (NetCDF), is intended to support watershed-scale and island-scale studies of short-term and long-term climate, hydrology and ecology.

Interaction between Soil Moisture and Air Temperature in the Mississippi River Basin

Increasing air temperatures are expected to continue in the future. The relation between soil moisture and near surface air temperature is significant for climate change and climate extremes. Evaluation of the relations between soil moisture and temperature was performed by developing a quantile regression model, a wavelet coherency model, and a Mann-Kendall correlation model from 1950 to 2010 in the Mississippi River Basin. The results indicate that first, anomaly air temperature is negatively correlated to anomaly soil moisture in the upper and lower basin, and however, the correlation between them are mixed in the middle basin. The correlation is stronger at the higher quantile (90^th) of the two variables. Second, anomaly soil moisture and air temperature show strong coherency in annual frequency, indicating that the two variables are interannually correlated. Third, annual air temperature is significant negatively related to soil moisture, indicating that dry (wet) soil leads to warm (cool) weather in the basin. These results have potential application to future climate change research and water resource management. Also, the strong relationship between soil moisture and air temperature at annual scale could result in improved temperature predictability.

Integrating Remote Sensing Information Into A Distributed Hydrological Model for Improving Water Budget Predictions in Large-scale Basins through Data Assimilation

This paper investigates whether remote sensing evapotranspiration estimates can be integrated by means of data assimilation into a distributed hydrological model for improving the predictions of spatial water distribution over a large river basin with an area of 317,800 km². A series of available MODIS satellite images over the Haihe River basin in China are used for the year 2005. Evapotranspiration is retrieved from these 1×1 km resolution images using the SEBS (Surface Energy Balance System) algorithm. The physically-based distributed model WEP-L (Water and Energy transfer Process in Large river basins) is used to compute the water balance of the Haihe River basin in the same year. Comparison between model-derived and remote sensing retrieval basin-averaged evapotranspiration estimates shows a good piecewise linear relationship, but their spatial distribution within the Haihe basin is different. The remote sensing derived evapotranspiration shows variability at finer scales. An extended Kalman filter (EKF) data assimilation algorithm, suitable for non-linear problems, is used. Assimilation results indicate that remote sensing observations have a potentially important role in providing spatial information to the assimilation system for the spatially optical hydrological parameterization of the model. This is especially important for large basins, such as the Haihe River basin in this study. Combining and integrating the capabilities of and information from model simulation and remote sensing techniques may provide the best spatial and temporal characteristics for hydrological states/fluxes, and would be both appealing and necessary for improving our knowledge of fundamental hydrological processes and for addressing important water resource management problems.