Multiscale assessment of TRMM (3B42 V7) and GPM (IMERG V5) satellite precipitation products over a Mediterranean mountainous watershed with sparse rain gauges in the Moroccan High Atlas (case study of Zat basin)

The performance of Tropical Precipitation Measurement Mission (TRMM) and its successor, Global Precipitation Measurement (GPM), has provided hydrologists with a source of critical precipitation data for hydrological applications in basins where ground-based observations of precipitation are sparse, or spatially undistributed. The very high temporal and spatial resolution satellite precipitation products have therefore become a reliable alternative that researchers are increasingly using in various hydro-meteorological and hydro-climatological applications. This study aims to evaluate statistically and hydrologically the TRMM (3B42 V7) and GPM (IMERG V5) satellite precipitations products (SPPs), at multiple temporal scales from 2010 to 2017, in a mountainous watershed characterized by the Mediterranean climate. The results show that TRMM (3B42 V7) and GPM (IMERG V5) satellite precipitation products have a significant capacity for detecting precipitation at different time steps. However, the statistical analysis of SPPs against ground observation shows good results for both statistical metrics and contingency statistics with notable values (CC > 0.8), and representative values relatively close to 0 for the probability of detection (POD), critical success index (CSI), and false alarm ratio (FAR). Moreover, the sorting of the events implemented on the hydrological model was performed seasonally, at daily time steps. The calibrated episodes showed very good results with Nash values ranging from 53.2 % to 95.5 %. Nevertheless, the (IMERG V5) product detects more efficiently precipitation events at short time steps (daily), while (3B42 V7) has a strong ability to detect precipitation events at large time steps (monthly and yearly). Furthermore, the modeling results illustrate that both satellite precipitation products tend to underestimate precipitation during wet seasons and overestimate them during dry seasons, while they have a better spatial distribution of precipitation measurements performance, which shows the importance of their use for basin modeling and potentially for flood forecasting in Mediterranean catchment areas.

On the occurrence of three new Lycaenid butterflies (Lepidoptera) from Jammu and Kashmir, India

The present communication deals with three butterfly species belonging to family Lycaenidae and subfamily Theclinae, recorded for the first time from different localities in a mountainous watershed in the Union Territory of Jammu and Kashmir during 2020. These include Esakiozephyrus icana, Spindasis ictis and Tajuria jehana. The information on their current extent and known occurrence will be helpful in updating the range distribution of butterflies in north-western Himalayas.

Subsurface mechanisms control hydrologic response to a multi-year drought in a mountainous watershed with a Mediterranean climate

<p>Mountain watersheds often act as water towers that supply water to large human populations in valley aquifers. Therefore, their susceptibility and resilience to droughts are of outsize importance particularly, as global climate change projections suggest more frequent droughts in the future. Previous studies have examined the impact of climate warming on mountain hydrology, but they have not explicitly linked impacts of multi-year droughts to subsurface water storage. In this study, we use the 2012-2015 California drought to examine the mechanisms via which subsurface flow paths and storage affect the hydrologic response to drought in the Kaweah River watershed in the Sierra Nevada mountains. We build and test an integrated hydrologic model using the coupled land surface-groundwater model ParFlow.CLM. The model is able to simulate the observed hydrology with a high degree of accuracy. Results reveal that mountain aquifer recharge sourced from snowmelt (<em>MAR</em><sub><em>snow</em></sub>) is the primary input to the groundwater system, and much of the simulated streamflow. We find that increases in air temperature and decreases in precipitation during the drought reduces snow water equivalent (<em>SWE</em>), and causes a 73% reduction in <em>MAR</em><sub><em>snow</em></sub> compared to the pre-drought period. Reduction in <em>MAR</em><sub><em>snow</em></sub> initially results in subsurface storage losses along the ridgelines and areas of low topographic convergence. Topography induced draining of the regolith storage causes groundwater depletion and provides supplemental water to maintain streamflow and riparian evapotranspiration (<em>ET</em>). As the drought develops, drying of the subsurface alters lateral connectivity of the shallow groundwater system, and reduces streamflow and riparian <em>ET</em>. We apply machine learning models to examine the spatial patterns in groundwater storage depletion and recovery. These models reveal that topography induced draining and filling of subsurface storage in response to drought and precipitation recovery, respectively, is the key control on the streamflow response in this mountainous watershed. Warmer conditions and more frequent droughts that reduce <em>SWE</em> in the future are likely to amplify this cycle.</p>