This paper aims to address the limitations of distribution number and uniformity Continuously Operating Reference Stations (CORS) their impact on reliability inverting regional groundwater storage (GWS) based Green’s function method using global navigation satellite system (GNSS) data. A fusion inversion GWS changes from GNSS Gravity Recovery Climate Experiment (GRACE) was proposed in this pape...

The large-scale quantification of accurate evapotranspiration (ET) time series has substantially been developed in recent decades using automated approaches based on remote sensing data. However, there are still several model-related uncertainties that require precise assessment. In this study, the Surface Energy Balance Algorithm for Land (SEBAL) and meteorological data from Global Data Assimi...

The spatial and temporal distribution of precipitation is great importance for the rain-fed agricultural production socioeconomics Mato Grosso (MT), Brazil. MT has a sparse network ground rain gauges that limits effective use information sustainable water resources in region. Several gridded products from remote sensing reanalysis land surface models are currently available can enhance such inf...

ارزیابی خشک‌سالی، ازنظر زمانی و مکانی، برای برنامه‌ریزی‌های کاهش خسارات در استان کردستان اهمیت بسیاری دارد. این تحقیق، از شاخص بارش استانداردشده همچنین، پوشش گیاهی بارزشدة استخراجی تصاویر ماهواره‌ای، به‌منزلة پارامتر تعیین‌کنندة استفاده شده است. به‌این‌منظور، داده‌های آماری ایستگاه‌های هواشناسی شامل حداکثر دمای ماهیانه، مجموع سالیانه نیز سنجندة مادیس به‌کار رفته با مقایسة پارامترهای میانگین سال...

تحلیل ‌میزان ‌و ‌چگونگی آسیب‌پذیری ‌بافت‌‌های‌ ‌شهری‌ به ‌‌برنامه‌ریزان‌‌ و ‌مدیران ‌‌شهری ‌در ‌‌تصمیم‌گیری‌های ‌مناسب ‌انتخاب راه حل‌‌های‌ کنترل‌ ‌مقابل ‌با ‌مخاطرات‌ احتمالی‌کمک ‌مؤثری ‌می‌کند. بنابراین در تحقیق حاضر میزان بافت جدید (منطقۀ یک) قدیمی چهار) شهر ارومیه بر اساس شاخص‌های پدافند غیرعامل حملات هوایی ارزیابی تطبیقی می‌شود. برای رسیدن هدف، پس از مطالعۀ منابع مرتبط، تعداد 10 شاخص بین ع...

Abstract We develop a deep learning based convolutional-regression model that estimates the volumetric soil moisture content in top ~5 cm of soil. Input predictors include Sentinel-1 (active radar), and Sentinel-2 (multispectral imagery) as well geophysical variables from SoilGrids modelled fields SMAP-USDA GLDAS. The was trained evaluated on data ~1000 in-situ sensors globally over period 2015...

A surface soil moisture (SSM) product at a 1-km spatial resolution derived from the Envisat Advanced Synthetic Aperture Radar (ASAR) Global Monitoring (GM) mode data was evaluated over the entire African continent using coarse spatial resolution SSM acquisitions from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and the Noah land surface model from the Global La...

A method using a nonlinear auto-regressive neural network with exogenous input (NARXnn) to retrieve time series soil moisture (SM) that is spatially and temporally continuous and high quality over the Heihe River Basin (HRB) in China was investigated in this study. The input training data consisted of the X-band dual polarization brightness temperature (TB) and the Ka-band V polarization TB fro...

In this article, the performance of the Visible and Shortwave infrared Drought Index (VSDI), a drought index recently developed and validated in Oklahoma, United States, is further explored and validated in China. The in-situ measured soil moisture from 585 weather stations across China are used as ground-truth data, and five commonly used drought indices are compared with VSDI for surface drou...

Assessing reliability of global models is critical because of increasing reliance on these models to address past and projected future climate and human stresses on global water resources. Here, we evaluate model reliability based on a comprehensive comparison of decadal trends (2002-2014) in land water storage from seven global models (WGHM, PCR-GLOBWB, GLDAS NOAH, MOSAIC, VIC, CLM, and CLSM) ...