scholarly journals Remote sensing depicts riparian vegetation responses to water stress in a humid Atlantic region

2021 ◽  
Vol 772 ◽  
pp. 145526
Author(s):  
G. Pace ◽  
C. Gutiérrez-Cánovas ◽  
R. Henriques ◽  
F. Boeing ◽  
F. Cássio ◽  
...  
Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1117
Author(s):  
Anatoly Mikhailovich Zeyliger ◽  
Olga Sergeevna Ermolaeva

In the past few decades, combinations of remote sensing technologies with ground-based methods have become available for use at the level of irrigated fields. These approaches allow an evaluation of crop water stress dynamics and irrigation water use efficiency. In this study, remotely sensed and ground-based data were used to develop a method of crop water stress assessment and analysis. Input datasets of this method were based on the results of ground-based and satellite monitoring in 2012. Required datasets were collected for 19 irrigated alfalfa crops in the second year of growth at three study sites located in Saratovskoe Zavolzhie (Saratov Oblast, Russia). Collected datasets were applied to calculate the dynamics of daily crop water stress coefficients for all studied crops, thereby characterizing the efficiency of crop irrigation. Accordingly, data on the crop yield of three harvests were used. An analysis of the results revealed a linear relationship between the crop yield of three cuts and the average value of the water stress coefficient. Further application of this method may be directed toward analyzing the effectiveness of irrigation practices and the operational management of agricultural crop irrigation.


2021 ◽  
Author(s):  
Luz Karime Atencia ◽  
María Gómez del Campo ◽  
Gema Camacho ◽  
Antonio Hueso ◽  
Ana M. Tarquis

<p>Olive is the main fruit tree in Spain representing 50% of the fruit trees surface, around 2,751,255 ha. Due to its adaptation to arid conditions and the scarcity of water, regulated deficit irrigation (RDI) strategy is normally applied in traditional olive orchards and recently to high density orchards. The application of RDI is one of the most important technique used in the olive hedgerow orchard. An investigation of the detection of water stress in nonhomogeneous olive tree canopies such as orchards using remote sensing imagery is presented.</p><p>In 2018 and 2019 seasons, data on stem water potential were collected to characterize tree water state in a hedgerow olive orchard cv. Arbequina located in Chozas de Canales (Toledo). Close to the measurement’s dates, remote sensing images with spectral and thermal sensors were acquired. Several vegetation indexes (VI) using both or one type of sensors were estimated from the areas selected that correspond to the olive crown avoiding the canopy shadows.</p><p>Nonparametric statistical tests between the VIs and the stem water potential were carried out to reveal the most significant correlation. The results will be discussing in the context of robustness and sensitivity between both data sets at different phenological olive state.</p><p><strong>ACKNOWLODGEMENTS</strong></p><p>Financial support provided by the Spanish Research Agency co-financed with European Union FEDER funds (AEI/FEDER, UE, AGL2016-77282-C3-2R project) and Comunidad de Madrid through calls for grants for the completion of Industrial Doctorates, is greatly appreciated.</p>


Author(s):  
Smriti Chaulagain ◽  
Mark Stone ◽  
Daniel Dombroski ◽  
Tyler Gillihan ◽  
Li Chen ◽  
...  

Riparian vegetation provides many noteworthy functions in river and floodplain systems including its influence on hydrodynamic processes. Traditional methods for predicting hydrodynamic characteristics in the presence of vegetation involve the application of static roughness ( n) values, which neglect changes in roughness due to local flow characteristics. The objectives of this study were to: (1) implement numerical routines for simulating dynamic hydraulic roughness ( n) in a two-dimensional (2D) hydrodynamic model; (2) evaluate the performance of two dynamic roughness approaches; and (3) compare vegetation parameters and hydrodynamic model results based on field-based and remote sensing acquisition methods. A coupled vegetation-hydraulic solver was developed for a 2D hydraulics model using two dynamic approaches, which required vegetation parameters to calculate spatially distributed, dynamic roughness coefficients. Vegetation parameters were determined by field survey and using airborne LiDAR data. Water surface elevations modeled using conventional and the proposed dynamic approaches produced similar profiles. The method demonstrates the suitability in modeling the system where there is no calibration data. Substantial spatial variations in both n and hydraulic parameters were observed when comparing the static and dynamic approaches. Thus, the method proposed here is beneficial for describing the hydraulic conditions for the area having huge variation of vegetation. The proposed methods have the potential to improve our ability to simulate the spatial and temporal heterogeneity of vegetated floodplain surfaces with an approach that is more physically-based and reproducible than conventional “look up” approaches. However, additional research is needed to quantify model performance with respect to spatially distributed flow properties and parameterization of vegetation characteristics.


2020 ◽  
Author(s):  
Ilham Ali ◽  
Jay Famiglietti ◽  
Jonathan McLelland

Water stress in both surface and groundwater supplies is an increasing environmental and sustainable management issue. According to the UN Environment Program, at current depletion rates almost half of the world's population will suffer severe water stress by 2030. This is further exacerbated by climate change effects which are altering the hydrologic cycle. Understanding climate change implications is critical to planning for water management scenarios as situations such as rising sea levels, increasing severity of storms, prolonged drought in many regions, ocean acidification, and flooding due to snowmelt and heavy precipitation continue. Today, major efforts towards equitable water management and governance are needed. This study adopts the broad, holistic lenses of sustainable development and water diplomacy, acknowledging both the complex and transboundary nature of water issues, to assess the benefits of a “science to policy” approach in water governance. Such negotiations and frameworks are predicated on the availability of timely and uniform data to bolster water management plans, which can be provided by earth-observing satellite missions. In recent decades, significant advances in satellite remote sensing technology have provided unprecedented data of the Earth’s water systems, including information on changes in groundwater storage, mass loss of snow caps, evaporation of surface water reservoirs, and variations in precipitation patterns. In this study, specific remote sensing missions are surveyed (i.e. NASA LANDSAT, GRACE, SMAP, CYGNSS, and SWOT) to understand the breadth of data available for water uses and the implications of these advances for water management. Results indicate historical precedent where remote sensing data and technologies have been successfully integrated to achieve more sustainable water management policy and law, such as in the passage of the California Sustainable Groundwater Management Act of 2014. In addition, many opportunities exist in current transboundary and interstate water conflicts (for example, the Nile Basin and the Tri-State Water Wars between Alabama, Georgia, and Florida) to integrate satellite-remote-sensed water data as a means of “joint-fact finding” and basis for further negotiations. The authors argue that expansion of access to satellite remote sensing data of water for the general public, stakeholders, and policy makers would have a significant impact on the development of science-oriented water governance measures and increase awareness of water issues by significant amounts. Barriers to entry exist in accessing many satellite datasets because of prerequisite knowledge and expertise in the domain. More user-friendly platforms need to be developed in order to maximize the utility of present satellite data. Furthermore, sustainable co-operations should be formed to employ satellite remote sensing data on a regional scale to preempt problems in water supply, quantity, and quality.


Author(s):  
Élvis da S. Alves ◽  
Roberto Filgueiras ◽  
Lineu N. Rodrigues ◽  
Fernando F. da Cunha ◽  
Catariny C. Aleman

ABSTRACT In regions where the irrigated area is increasing and water availability is reduced, such as the West of the Bahia state, Brazil, the use of techniques that contribute to improving water use efficiency is paramount. One of the ways to improve irrigation is by improving the calculation of actual evapotranspiration (ETa), which among other factors is influenced by soil drying, so it is important to understand this relationship, which is usually accounted for in irrigation management models through the water stress coefficient (Ks). This study aimed to estimate the water stress coefficient (Ks) through information obtained via remote sensing, combined with field data. For this, a study was carried out in the municipality of São Desidério, an area located in western Bahia, using images of the Landsat-8 satellite. Ks was calculated by the relationship between crop evapotranspiration and ETa, calculated by the Simple Algorithm for Evapotranspiration Retrieving (SAFER). The Ks estimated by remote sensing showed, for the development and medium stages, average errors on the order of 5.50%. In the final stage of maize development, the errors obtained were of 23.2%.


2019 ◽  
Vol 11 (14) ◽  
pp. 1684 ◽  
Author(s):  
Chao Zhang ◽  
Jiangui Liu ◽  
Taifeng Dong ◽  
Elizabeth Pattey ◽  
Jiali Shang ◽  
...  

Accurate information of crop growth conditions and water status can improve irrigation management. The objective of this study was to evaluate the performance of SAFYE (simple algorithm for yield and evapotranspiration estimation) crop model for simulating winter wheat growth and estimating water demand by assimilating leaf are index (LAI) derived from canopy reflectance measurements. A refined water stress function was used to account for high crop water stress. An experiment with nine irrigation scenarios corresponding to different levels of water supply was conducted over two consecutive winter wheat growing seasons (2013–2014 and 2014–2015). The calibration of four model parameters was based on the global optimization algorithms SCE-UA. Results showed that the estimated and retrieved LAI were in good agreement in most cases, with a minimum and maximum RMSE of 0.173 and 0.736, respectively. Good performance for accumulated biomass estimation was achieved under a moderate water stress condition while an underestimation occurred under a severe water stress condition. Grain yields were also well estimated for both years (R2 = 0.83; RMSE = 0.48 t∙ha−1; MRE = 8.4%). The dynamics of simulated soil moisture in the top 20 cm layer was consistent with field observations for all scenarios; whereas, a general underestimation was observed for total water storage in the 1 m layer, leading to an overestimation of the actual evapotranspiration. This research provides a scheme for estimating crop growth properties, grain yield and actual evapotranspiration by coupling crop model with remote sensing data.


2020 ◽  
Vol 12 (9) ◽  
pp. 1362 ◽  
Author(s):  
Christine M. Albano ◽  
Kenneth C. McGwire ◽  
Mark B. Hausner ◽  
Daniel J. McEvoy ◽  
Charles G. Morton ◽  
...  

Dryland riparian areas are under increasing stress due to expanding human water demands and a warming climate. Quantifying responses of dryland riparian vegetation to these pressures is complicated by high climatic variability, which can create strong, transient changes in vegetation vigor that could mask other disturbance events. In this study, we utilize a 34-year archive of Landsat satellite data to (1) quantify the strength and timescales of vegetation responses to interannual variability in drought status and (2) isolate and remove this influence to assess resultant trends in vegetation vigor for riparian areas across the state of Nevada, the driest state in the USA. Correlations between annual late-summer Normalized Difference Vegetation Index (NDVI) and the Standardized Precipitation–Evapotranspiration Index (SPEI) were calculated across a range of time periods (varying timing and durations) for all riparian pixels within each of the 45 ecoregions, and the variability of these values across the study area is shown. We then applied a novel drought adjustment method that used the strongest SPEI–NDVI timescale relationships for each ecoregion to remove the influence of interannual drought status. Our key result is a 30 m resolution map of drought-adjusted riparian NDVI trends (1985–2018). We highlight and describe locations where impacts of invasive species biocontrol, mine water management, agriculture, changing water levels, and fire are readily visualized with our results. We found more negatively trending riparian areas in association with wide valley bottoms, low-intensity agricultural land uses, and private land ownerships and more positive trends in association with narrow drainages, public lands, and surrounding perennial water bodies (an indication of declining water levels allowing increased vegetative cover). The drought-adjusted NDVI improved the statistical significance of trend estimates, thereby improving the ability to detect such changes. Results from this study provide insight into the strength and timescales of riparian vegetation responses to drought and can provide important information for managing riparian areas within the study area. The novel approach to drought adjustment is readily transferrable to other regions.


Ecohydrology ◽  
2012 ◽  
Vol 6 (3) ◽  
pp. 413-424 ◽  
Author(s):  
Rui Rivaes ◽  
Patricia M. Rodríguez-González ◽  
António Albuquerque ◽  
António N. Pinheiro ◽  
Gregory Egger ◽  
...  

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1418
Author(s):  
Elisabet Carpintero ◽  
Ana Andreu ◽  
Pedro J. Gómez-Giráldez ◽  
Ángel Blázquez ◽  
María P. González-Dugo

Mediterranean oak savannas (known as dehesas in Spain) are exposed to numerous threats from natural and economic causes. A close monitoring of the use of water resources and the status of the vegetation in these ecosystems can be useful tools for maintaining the production of ecological services. This study explores the estimation of evapotranspiration (ET) and water stress over a dehesa by integrating remotely sensed data into a water balance using the FAO-56 approach (VI-ETo model). Special attention is paid to the different phenology and contribution to the system’s hydrology of the two main canopy layers of the system (tree + grass). The results showed that the model accurately reproduced the dynamics of the water consumed by the vegetation, with RMSE of 0.47 mm day−1 and low biases for both, the whole system and the grass layer, when compared with flux tower measurements. The ET/ETo ratio helped to identify periods of water stress, confirmed for the grassland by measured soil water content. The modeling scheme and Sentinel-2 temporal resolution allowed the reproduction of fast and isolated ET pulses, important for understanding the hydrologic behavior of the system, confirming the adequacy of this sensor for monitoring grasslands water dynamics.


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