An Integrative Information Aqueduct to Close the Gaps between Satellite Observation of Water Cycle and Local Sustainable Management of Water Resources DOI Open Access
Zhongbo Su, Yijian Zeng, Nunzio Romano

et al.

Water, Journal Year: 2020, Volume and Issue: 12(5), P. 1495 - 1495

Published: May 23, 2020

The past decades have seen rapid advancements in space-based monitoring of essential water cycle variables, providing products related to precipitation, evapotranspiration, and soil moisture, often at tens kilometer scales. Whilst these data effectively characterize variability regional global scales, they are less suitable for sustainable management local resources, which needs detailed information represent the spatial heterogeneity vegetation. following questions critical exploit from remotely sensed situ Earth observations (EOs): How downscale scale using multiple sources scales EO data? explore apply downscaled level a better understanding soil-water-vegetation-energy processes? can such fine-scale be used improve resources? An integrative flow (i.e., iAqueduct theoretical framework) is developed close gaps between satellite necessary resources. integrated framework aims address abovementioned scientific by combining medium-resolution (10 m–1 km) Copernicus with high-resolution (cm) unmanned aerial system (UAS) data, observations, analytical- physical-based models, as well big-data analytics machine learning algorithms. This paper provides general overview introduces some preliminary results.

Language: Английский

Standardised soil profile data to support global mapping and modelling (WoSIS snapshot 2019) DOI Creative Commons
N.H. Batjes, Eloi Ribeiro,

Ad van Oostrum

et al.

Earth system science data, Journal Year: 2020, Volume and Issue: 12(1), P. 299 - 320

Published: Feb. 10, 2020

Abstract. The World Soil Information Service (WoSIS) provides quality-assessed and standardised soil profile data to support digital mapping environmental applications at broadscale levels. Since the release of first “WoSIS snapshot”, in July 2016, many new were shared with us, registered ISRIC repository subsequently accordance licences specified by providers. managed WoSIS contributed a wide range providers; therefore, special attention was paid measures for quality standardisation property definitions, values (and units measurement) analytical method descriptions. We presently consider following chemical properties: organic carbon, total carbonate equivalent, nitrogen, phosphorus (extractable P, P retention), pH, cation exchange capacity electrical conductivity. also physical texture (sand, silt, clay), bulk density, coarse fragments water retention. Both these sets properties are grouped according procedures that operationally comparable. Further, each we provide original classification (FAO, WRB, USDA), version horizon designations, insofar as have been source databases. Measures geographical accuracy (i.e. location) point data, well approximation uncertainty associated defined methods, presented possible consideration subsequent earth system modelling. latest (dynamic) set called “wosis_latest”, is freely accessible via an OGC-compliant WFS (web feature service). For consistent referencing, time-specific static “snapshots”. present snapshot (September 2019) comprised 196 498 geo-referenced profiles originating from 173 countries. They represent over 832 000 layers (or horizons) 5.8 million records. actual number observations varies (greatly) between depth, generally depending on objectives initial sampling programmes. In coming years, aim fill gradually gaps geographic distribution themselves, this subject sharing wider selection so far under-represented areas our existing prospective partners. Part work foreseen conjunction within Global System (GloSIS) being developed Partnership (GSP). – September 2019” archived https://doi.org/10.17027/isric-wdcsoils.20190901 (Batjes et al., 2019).

Language: Английский

Citations

290
A global-scale dataset of direct natural groundwater recharge rates: A review of variables, processes and relationships DOI
Christian Moeck,

Nicolas Grech-Cumbo,

Joel Podgorski

et al.

The Science of The Total Environment, Journal Year: 2020, Volume and Issue: 717, P. 137042 - 137042

Published: Feb. 1, 2020

Language: Английский

Citations

225
Advances and perspectives on soil water research in China’s Loess Plateau DOI
Laiming Huang,

Mingan Shao

Earth-Science Reviews, Journal Year: 2019, Volume and Issue: 199, P. 102962 - 102962

Published: Oct. 19, 2019

Language: Английский

Citations

215
Soil structure is an important omission in Earth System Models DOI Creative Commons
Simone Fatichi, Dani Or,

R. L. Walko

et al.

Nature Communications, Journal Year: 2020, Volume and Issue: 11(1)

Published: Jan. 27, 2020

Abstract Most soil hydraulic information used in Earth System Models (ESMs) is derived from pedo-transfer functions that use easy-to-measure attributes to estimate parameters. This parameterization relies heavily on texture, but overlooks the critical role of structure originated by biophysical activity. Soil omission pervasive also sampling and measurement methods train pedotransfer functions. Here we show how systematic inclusion salient structural features origin affect local global hydrologic climatic responses. Locally, including models significantly alters infiltration-runoff partitioning recharge wet vegetated regions. Globally, coarse spatial resolution ESMs their inability simulate intense short rainfall events mask effects surface fluxes climate. Results suggest although affects response, its implications global-scale climate remains elusive current ESMs.

Language: Английский

Citations

213
Soil hydrology in the Earth system DOI
Harry Vereecken, Wulf Amelung, Sara L. Bauke

et al.

Nature Reviews Earth & Environment, Journal Year: 2022, Volume and Issue: 3(9), P. 573 - 587

Published: Aug. 2, 2022

Language: Английский

Citations

212
Root-induced changes of soil hydraulic properties – A review DOI

Jianrong Lu,

Qi Zhang, Adrian D. Werner

et al.

Journal of Hydrology, Journal Year: 2020, Volume and Issue: 589, P. 125203 - 125203

Published: June 21, 2020

Language: Английский

Citations

206
Root zone soil moisture estimation with Random Forest DOI Creative Commons
Coleen Carranza, Corjan Nolet, Michiel Pezij

et al.

Journal of Hydrology, Journal Year: 2020, Volume and Issue: 593, P. 125840 - 125840

Published: Dec. 10, 2020

Accurate estimates of root zone soil moisture (RZSM) at relevant spatio-temporal scales are essential for many agricultural and hydrological applications. Applications machine learning (ML) techniques to estimate limited compared commonly used process-based models based on flow transport equations in the vadose zone. However, data-driven ML present unique opportunities develop quantitative without having assumptions processes operating within system being investigated. In this study, Random Forest (RF) ensemble algorithm, is tested demonstrate capabilities advantages RZSM estimation. Interpolation extrapolation a daily timescale was carried out using RF over small catchment from 2016 2018 situ measurements. Results show that predictions have slightly higher accuracy interpolation similar comparison with simulated model combined data assimilation. extreme wet dry conditions were, however, less accurate. This inferred be due infrequent sampling such led poor trained incomplete representation subsurface study sites covariates. Since does not depend parameters required water flow, it more advantageous than data-poor regions where hydraulic or missing, especially when primary goal only estimation states.

Language: Английский

Citations

188
Estimation of saturated hydraulic conductivity with pedotransfer functions: A review DOI Creative Commons
Yonggen Zhang, Marcel G. Schaap

Journal of Hydrology, Journal Year: 2019, Volume and Issue: 575, P. 1011 - 1030

Published: May 21, 2019

Language: Английский

Citations

187
A Global High‐Resolution Data Set of Soil Hydraulic and Thermal Properties for Land Surface Modeling DOI Creative Commons
Yongjiu Dai, Qinchuan Xin, Nan Wei

et al.

Journal of Advances in Modeling Earth Systems, Journal Year: 2019, Volume and Issue: 11(9), P. 2996 - 3023

Published: Aug. 28, 2019

Abstract Modeling land surface processes requires complete and reliable soil property information to understand hydraulic heat dynamics related processes, but currently, there is no data set of thermal parameters that can meet this demand for global use. In study, we propose a fitting approach obtain the optimal water retention from ensemble pedotransfer functions (PTFs), which are evaluated using coverage National Cooperative Soil Survey Characterization Database show better performance applications than our original estimations (median values PTFs) as done in Dai et al. (2013, https://doi.org/10.1175/JHM‐D‐12‐0149.1 ). conductivities still estimated median multiple PTFs, results shown perform comparably estimates existing precision‐advanced models. properties following schemes identified by (2019a, http://arxiv.org/abs/1908.04579 ), several highly recommended based on their modeling applications. Using these approaches, develop two high‐resolution sets Global Dataset Earth System Models (GSDE) SoilGrids composition databases. The delivered variables include six basic properties, four Campbell (1974, https://doi.org/10.1097/00010694‐197406000‐00001 ) model, five van Genuchten (1980, https://doi.org/10.2136/sssaj1980.03615995004400050002x properties. available at 30″ × geographical spatial resolution provide vertical profiles resolutions SoilGrids, Noah‐Land Surface (LSM), Joint UK Land Environment Simulator (JULES), Common Model/Community Model (CoLM/CLM). be used both regional

Language: Английский

Citations

183
Global Groundwater Modeling and Monitoring: Opportunities and Challenges DOI
Laura E. Condon, Stefan Kollet, Marc F. P. Bierkens

et al.

Water Resources Research, Journal Year: 2021, Volume and Issue: 57(12)

Published: Dec. 1, 2021

Abstract Groundwater is by far the largest unfrozen freshwater resource on planet. It plays a critical role as bottom of hydrologic cycle, redistributing water in subsurface and supporting plants surface bodies. However, groundwater has historically been excluded or greatly simplified global models. In recent years, there an international push to develop scale modeling analysis. This progress provided some first steps. Still, much additional work will be needed achieve consistent framework that interacts seamlessly with observational datasets other earth system circulation Here we outline vision for platform monitoring prediction identify key technological data challenges are currently limiting progress. Any this type must interdisciplinary cannot achieved community isolation. Therefore, also provide high‐level overview system, approaches current state representations, such readers all backgrounds can engage challenge.

Language: Английский

Citations

177