Preventing waterlogging in irrigated agriculture with a multi-satellite sensor approach

2021 ◽  
Author(s):  
Nadja den Besten ◽  
Susan Steele-Dunne ◽  
Richard de Jeu ◽  
Pieter van der Zaag
Keyword(s):  
Water Stress ◽  
Brightness Temperature ◽  
Passive Microwave ◽  
Sensor Data ◽  
Optical Data ◽  
Irrigated Agriculture ◽  
Small Scale ◽  
Drought Event ◽  
Flooding Event ◽  
Microwave Data

<p>Satellite sensors have been used widely to determine water shortages to detect crop stress, with special emphasis on water stress. However, stress resulting from waterlogging has so far received little attention. This is surprising because approximately twenty percent of the global agricultural land suffers from the consequences of waterlogging and secondary soil salinization. While irrigation is expected to increase productivity, excess water can hamper the crop growth and decrease water use efficiency.</p><p>Traditionally, satellite driven water accounting for irrigation assistance uses optical and/or thermal sensors that can detect crop stress. The observed crop stress is often interpreted as water stress, whereby stress resulting from waterlogging cannot be distinguished. We hypothesize that a multi-sensor approach is required to distinguish waterlogging from water shortage, by including microwave observations that can determine the soil moisture status. However, localizing a small-scale phenomena as waterlogging with multi-sensor data with different resolutions is a major challenge.</p><p>In our research we focus on an irrigated sugarcane plantation along the river Incomati in Xinavane, Mozambique. Waterlogging is a common issue in the estate and is threatening productivity. We assess and combine optical and passive microwave data for a large drought (2016) and flooding event (2012) to look at the possibility of downscaling the data for detection of waterlogging. We find that optical indices are able to localize waterlogged areas. Additionally, the built up of the drought event and retreat of the flooding event are clearly visible in the brightness temperature in different frequencies. We demonstrate a procedure to combine brightness temperature with optical data to detect waterlogging at a higher spatial resolution. </p><p>The results show that a combination of optical and passive microwave data can detect regions within the sugarcane plantation of waterlogging. However, high resolution topographic data is required to enhance the detection of waterlogging to finer scales. </p>

scholarly journals Constructing a Multifrequency Passive Microwave Hail Retrieval and Climatology in the GPM Domain

2019 ◽  
Vol 58 (9) ◽  
pp. 1889-1904 ◽  
Author(s):  
Sarah D. Bang ◽  
Daniel J. Cecil
Keyword(s):  
United States ◽  
Brightness Temperature ◽  
Microwave Radiometer ◽  
Central Africa ◽  
Tropical Rainfall Measuring Mission ◽  
The United States ◽  
Low Earth Orbit ◽  
Passive Microwave ◽  
Central United States ◽  
Microwave Data

AbstractLarge hail is a primary contributor to damages and loss around the world, in both agriculture and infrastructure. The sensitivity of passive microwave radiometer measurements to scattering by hail led to the development of proxies for severe hail, most of which use brightness temperature thresholds from 37-GHz and higher-frequency microwave channels on board weather satellites in low-Earth orbit. Using 16+ years of data from the Tropical Rainfall Measuring Mission (TRMM; 36°S–36°N), we pair TRMM brightness temperature–derived precipitation features with surface hail reports in the United States to train a hail retrieval on passive microwave data from the 10-, 19-, 37-, and 85-GHz channels based on probability curves fit to the microwave data. We then apply this hail retrieval to features in the Global Precipitation Measurement (GPM) domain (from 69°S to 69°N) to develop a nearly global passive microwave–based climatology of hail. The extended domain of the GPM satellite into higher latitudes requires filtering out features that we believe are over icy and snowy surface regimes. We also normalize brightness temperature depression by tropopause height in an effort to account for differences in storm depth between the tropics and higher latitudes. Our results show the highest hail frequencies in the region of northern Argentina through Paraguay, Uruguay, and southern Brazil; the central United States; and a swath of Africa just south of the Sahel. Smaller hot spots include Pakistan, eastern India, and Bangladesh. A notable difference between these results and many prior satellite-based studies is that central Africa, while still active in our climatology, does not rival the aforementioned regions in retrieved hailstorm frequency.

scholarly journals Geographic and seasonal variations in the surface properties of the ice sheets by satellite-radar altimetry

1993 ◽  
Vol 39 (133) ◽  
pp. 687-697 ◽  
Author(s):  
Curt H. Davis ◽  
H. Jay Zwally
Keyword(s):  
Brightness Temperature ◽  
Extinction Coefficient ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Passive Microwave ◽  
East Antarctica ◽  
Grain Sizes ◽  
Wave Forms ◽  
Microwave Data

AbstractGeosat-altimeter wave forms from the Greenland and Antarctic ice sheets are analyzed using an algorithm based upon a combined surface-and volume-scattering model. The results demonstrate that sub-surface volume-scattering occurs over major parts of the ice sheets. Quantitative estimates of geographic variations in the near-surface ice-sheet properties are derived by retracking individual altimeter wave forms. The derived surface properties correlate with elevation, latitude and microwave brightness-temperature data. Specifically, the extinction coefficient of snow obtained by this method varies from 0.48 to 0.13 m−1 over the latitudes from 65° to 72°N on the central part of the Greenland ice sheet and from 0.20 to 0.10 m−1 over a section of Wilkes Land in East Antarctica where the elevation increases from 2550 to 3150 m.Analysis of passive-microwave data over East Antarctica shows that the brightness temperature increases with elevation as the extinction coefficient decreases. Larger snow grain-sizes occur at lower elevations of the ice sheet because of higher mean annual temperatures. The larger grain-sizes increase the extinction coefficient of snow and decrease the emitted energy (brightness temperature) from greater snow depths. The passive-microwave data are also used to determine the average number of melt d year−1 (1979–87) for the central part of the Greenland ice sheet. For latitudes from 65° to 68.5° N, the average number of melt days decreases from 3.5 to 0.25 d year, whereas no melt events are observed for latitudes above 69°N over the 8 year period. Snow subjected to alternate melting and freezing has enhanced grain-sizes compared to that of dry snow. This accounts for the larger values and larger spatial variations of ke on the Greenland ice sheet compared to East Antarctica, where surface temperatures are never high enough to cause surface melting.

scholarly journals Spatio-temporal Patterns of High Mountain Asia's Snowmelt Season Identified with an Automated Snowmelt Detection Algorithm, 1987–2016

2017 ◽  
Author(s):  
Taylor Smith ◽  
Bodo Bookhagen ◽  
Aljoscha Rheinwalt
Keyword(s):  
Climate Change ◽  
Time Series ◽  
Tibetan Plateau ◽  
Single Point ◽  
Detection Algorithm ◽  
Passive Microwave ◽  
Small Scale ◽  
High Mountain ◽  
The Tibetan Plateau ◽  
Microwave Data

Abstract. High Mountain Asia (HMA), encompassing the Tibetan Plateau and surrounding mountain ranges, is the primary water tower for much of Asia, serving more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow, which is poorly monitored by sparse in-situ weather networks. Both the timing and volume of snowmelt play critical roles in downstream water provision, as many applications – such as agriculture, drinking-water generation, and hydropower – rely on consistent and predictable snowmelt runoff. Here, we leverage passive microwave data across five sensors (SSMI, SSMIS, AMSR-E, AMSR2, and GPM) from 1987–2016 to track the onset and end of snowmelt across HMA. Compared against a control dataset (n = 2100, 3 variables at 25 locations over 28 years), our algorithm is generally within 3–5 days of the onset and end dates of melt. Using the algorithm-generated snowmelt dates, we examine the spatiotemporal patterns of the snowmelt season across HMA. The climatically short (29 year) time series, along with complex inter-annual snowfall variations, makes determining trends in melt onset and end dates at a single point difficult. We instead identify trends in snowmelt timing by using hierarchical clustering of the passive microwave data to determine trends in self-similar regions. We make the following four key observations: (1) The end of the snowmelt season is trending almost universally earlier in HMA (negative trends). Changes in the end of the snowmelt season are generally between 2 and 8 days/decade over the 29-year study period (5–25 days total). The length of the snowmelt season is thus shrinking in many, though not all, regions of HMA. Some areas exhibit later snowmelt onset dates (positive trends), but with a generally smaller magnitudes than trends in snowmelt end. (2) Areas with long snowmelt periods, such as the Tibetan Plateau, show the strongest compression of the snowmelt season (negative trends). These trends are apparent regardless of the time period over which the regression is performed. (3) While trends averaged over three decades indicate earlier snowmelt onset and end, data from the last 14 years (2002–2016) exhibit positive trends in both snowmelt onset and end dates in many regions, such as parts of the Pamir and Kunlun Shan. Due to the short nature of the time series, it is not clear whether this change is a reversal in a long-term trend or simply inter-annual variability. (4) Some regions with stable or growing glaciers – such as the Karakoram and Kunlun Shan – see slightly later snowmelt onset and longer snowmelt periods. It is likely that changes in the snowmelt regime of HMA account for some of the observed heterogeneity in glacier response to climate change. While the decadal increases in regional temperature have in general caused earlier snowmelt onset and shortened melt seasons, changes in HMA's crysophere have been spatially and temporally heterogeneous. The complex response of HMA's cryosphere to climate change highlights the importance of both regional and small-scale studies for effective water planning.

scholarly journals Geographic and seasonal variations in the surface properties of the ice sheets by satellite-radar altimetry

1993 ◽  
Vol 39 (133) ◽  
pp. 687-697 ◽  
Author(s):  
Curt H. Davis ◽  
H. Jay Zwally
Keyword(s):  
Brightness Temperature ◽  
Extinction Coefficient ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Greenland Ice Sheet ◽  
Passive Microwave ◽  
East Antarctica ◽  
Grain Sizes ◽  
Wave Forms ◽  
Microwave Data

AbstractGeosat-altimeter wave forms from the Greenland and Antarctic ice sheets are analyzed using an algorithm based upon a combined surface-and volume-scattering model. The results demonstrate that sub-surface volume-scattering occurs over major parts of the ice sheets. Quantitative estimates of geographic variations in the near-surface ice-sheet properties are derived by retrackingindividualaltimeter wave forms. The derived surface properties correlate with elevation, latitude and microwave brightness-temperature data. Specifically, the extinction coefficient of snow obtained by this method varies from 0.48 to 0.13 m−1over the latitudes from 65° to 72°N on the central part of the Greenland ice sheet and from 0.20 to 0.10 m−1over a section of Wilkes Land in East Antarctica where the elevation increases from 2550 to 3150 m.Analysis of passive-microwave data over East Antarctica shows that the brightness temperature increases with elevation as the extinction coefficient decreases. Larger snow grain-sizes occur at lower elevations of the ice sheet because of higher mean annual temperatures. The larger grain-sizes increase the extinction coefficient of snow and decrease the emitted energy (brightness temperature) from greater snow depths. The passive-microwave data are also used to determine the average number of melt d year−1(1979–87) for the central part of the Greenland ice sheet. For latitudes from 65° to 68.5° N, the average number of melt days decreases from 3.5 to 0.25 d year, whereas no melt events are observed for latitudes above 69°N over the 8 year period. Snow subjected to alternate melting and freezing has enhanced grain-sizes compared to that of dry snow. This accounts for the larger values and larger spatial variations ofkeon the Greenland ice sheet compared to East Antarctica, where surface temperatures are never high enough to cause surface melting.

Morphological, Physiological and Biochemical Responses of Poplar Plants to Drought Stress

2018 ◽  
Vol 5 (03) ◽  
Author(s):  
ARADHNA KUMARI ◽  
IM KHAN ◽  
ANIL KUMAR SINGH ◽  
SANTOSH KUMAR SINGH
Keyword(s):  
Water Stress ◽  
Drought Stress ◽  
Biochemical Parameters ◽  
Sugar Content ◽  
Soluble Sugar ◽  
Field Capacity ◽  
Drought Event ◽  
Total Biomass ◽  
Biochemical Responses ◽  
Physiological And Biochemical

Poplar clone Kranti was selected to assess the morphological, physiological and biochemical responses under drought at different levels of water stress, as it is a common clone used to be grown in Uttarakhand for making paper and plywood. The cuttings of Populus deltoides L. (clone Kranti) were exposed to four different watering regimes (100, 75, 50 and 25% of the field capacity) and changes in physiological and biochemical parameters related with drought tolerance were recorded. Alterations in physiological (i.e. decrease in relative water content) and biochemical parameters (i.e. increase in proline and soluble sugar content and build-up of malondialdehyde by-products) occurred in all the three levels of water stress, although drought represented the major determinant. Drought treatments (75%, 50% and 25% FC) decreased plant height, radial stem diameter, harvest index, total biomass content and RWC in all the three watering regimes compared to control (100% FC). Biochemical parameters like proline, soluble sugar and MDA content increased with severity and duration of stress, which helped plants to survive under severe stress. It was analyzed that for better wood yield poplar seedlings should avail either optimum amount of water (amount nearly equal to field capacity of soil) or maximum withdrawal up to 75% of field capacity up to seedling establishment period (60 days). Furthermore, this study manifested that acclimation to drought stress is related with the rapidity, severity, and duration of the drought event of the poplar species.

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