Evaluation of Actual Evapotranspiration and Crop Coefficient in Carrot by Remote Sensing Methodology Using Drainage and River Water to Overcome Reduced Water Availability

Searching for alternative methods for traditional irrigation is World trend at days due to a reduction in water and increased of drought due to climate changes therefore farmers need use modern methods of scheduling water and minimizing water losses while also increasing yield. To meet the future increasing demands water and food there is a need to utilize alternative methods to reduce evaporation, transpiration and deep percolation of water. Any countries use recycled water (drain and sewage) and desalination water from the sea or drains to irrigate crops plus computing actual crop evapotranspiration (ETc) so as to calculate the amount of water to apply to a crop. The paper aims to assess the actual evaporation and evaporation coefficient of carrots, by planting carrots in a field and the crop was exposed to several sources of water (DW and RW) and comparing ETc, Kc and production among plots of three sites (A, B and C). The study used two types of irrigation water (drain water (DW) and river water (RW)). The results were to monthly rate and accumulated actual evapotranspiration to C (irrigation by RW only) more than A (67% RW and 33% DW) and B (17% RW and 83% DW) via 7% and 58%, respectively. The yield to C more than A and B by 17% and 75%, respectively. In conclusion the use of DW can cause a reduction in crop consumptive of carrot crops also causes a reduction in yield, crop length, root length, root size, canopy of crop, number of leaves and biomass of the plant therefore, the drainage water needs to treated before irrigating crops And making use of it to irrigate the fields and fill the shortfall in the amount of water from the river. The drain water helped on filling the water shortage due to climate changes and giving production of carrot crop but less than river water.

SPATIO-TEMPORAL VARIATION OF ACTUAL EVAPOTRANSPIRATION AND ITS RELATION WITH CLIMATE PARAMETERS IN THE PEARL RIVER BASIN,CHINA

Spatio-temporal variation of actual evapotranspiration(ETa) in the Pearl River basin from 1961 to 2010 are analyzed based on daily data from 60 national observed stations. ETa is calculated by the Advection-Aridity model(AA model) in the current study, and Mann-Kendall test(MK) and Inverse Distance Weighted interpolation method(IDW)were applied to detect the trends and spatial variation pattern. The relations of ETa with climate parameters and radiation/dynamic terms are analyzed by Person correlation method. Our findings are shown as follows: 1) Mean annual ETa in the Pearl River basin is about 665.6 mm/a. It has significantly decreased in 1961-2010 at a rate of-24.3mm/10 a. Seasonally, negative trends of summer and autumn ETa are higher than that of spring and winter. 2) The value of ETa is higher in the southeast coastal area than in the northwest region of the Pearl River basin, while the latter has shown the strongest negative trend. 3) Negative trends of ETa in the Pearl River basin are most probably due to decreasing radiation term and increasing dynamic term. The decrease of the radiation term is related with declining diurnal temperature range and sunshine duration, and rising atmospheric pressure as well. The contribution of dynamic term comes from increasing average temperature, maximum and minimum temperatures in the basin. Meanwhile, the decreasing average wind speed weakens dynamic term and finally, to a certain extent, it slows down the negative trend of the ETa.

Changes and determining factors of crop evapotranspiration derived from satellite-based dual crop coefficients in North China Plain

Evaluating actual crop evapotranspiration(ET) variations and their determining factors under changing climates is crucial for agricultural irrigation management and crop productivity improvement in nonhumid regions.This study analyzed the spatiotemporal characteristics and detected the determining factors of ETfor winter wheat and summer maize rotation system from 2000 to 2017 in the North China Plain(NCP),by combining the FAO-56 dual crop coefficient approach with remotely sensed vegetation indices(VIs).The results indicated that daily air temperature increased in varying degrees while wind speed and sunshine hours decreased slightly during the growing season of winter wheat and summer maize over the study period.The trends of relative humidity and effective precipitation varied in crop growing seasons.Based on the validated relationship of dual crop coefficients and VIs,the estimated multi-year average ETof winter wheat(370.29±31.28 mm) was much higher than summer maize(281.85±20.14 mm),and the rotation cycle was 652.43±27.67 mm.Annual ETof winter wheat and the rotation cycle increased by 2.96 mm aand 1,77 mm a,respectively.However,the ETof summer maize decreased with distinct spatial variation.Spatially,winter wheat ETincreased significantly in the northeast NCP,covering the Beijing-Tianiin-Hebei areas.Meanwhile,significant increases in summer maize ETwere detected in the southwest NCP.The sensitivity and contribution analysis showed that ETof winter wheat and summer maize was positively sensitive to temperature,wind speed,and sunshine hours while negatively to relative humidity.Moreover,wind speed and sunshine hours contributed most to changes in ET(around 20%-40%).

A daily drought index based on evapotranspiration and its application in regional drought analyses

With climate warming, frequent drought events have occurred in recent decades, causing huge losses to industrial and agricultural production, and affecting people’s daily lives. The monitoring and forecasting of drought events has drawn increasing attention. However, compared with the various monthly drought indices and their wide application in drought research,daily drought indices, which would be much more suitable for drought monitoring and forecasting, are still scarce. The development of a daily drought index would improve the accuracy of drought monitoring and forecasting, and facilitate the evaluation of existing indices. In this study, we constructed a new daily drought index, the daily evapotranspiration deficit index(DEDI), based on actual and potential evapotranspiration data from the high-resolution ERA5 reanalysis dataset of the European Center for Medium-Range Weather Forecasts. This new index was then applied to analyze the spatial and temporal evolution characteristics of four drought events that occurred in southwest, north, northeast, and eastern northwest China in the spring and summer of 2019. Comparisons with the operationally used Meteorological Drought Composite Index and another commonly used index, the Standardized Precipitation Evapotranspiration Index, indicated that DEDI characterized the spatiotemporal evolution of the four drought events reasonably well and was superior in depicting the onset and cessation of the drought events,as well as multiple drought intensity peaks. Additionally, DEDI considers land surface conditions, such as vegetation coverage,which enables its potential application not only for meteorological purposes but also for agricultural drought warning and monitoring.

Evapotranspiration estimation using SEBAL algorithm integrated with remote sensing and experimental methods

Evapotranspiration is one of the most important elements of the hydrological cycle.Estimation of evapotranspiration is imperative for effective forest,irrigation,rangeland and water resources management as well as to increase yields and for better crop management.This study aims to evaluate the effectiveness of the Surface Energy Balance Algorithm for Land(SEBAL)in estimating evapotranspiration and crop coefficient of corn in the Mediterranean region of Adana province,Turkey.The Landsat 8 satellite images from March to September 2018 were used to acquire the coefficients of the respective bands.Then,the net radiation flux on the earth’s surface and the earth’s heat flux is obtained using incoming-outgoing radiation fluxes from albedo,surface emissivity coefficients,land surface temperature,and plant indicators.Next,the sensible heat flux is calculated by determining the hot and cold pixels under consideration via the atmospheric stability conditions.Finally,evapotranspiration maps are plotted.The crop coefficient of corn is also estimated with the respected maps being plotted.To validate the outcomes from the SEBAL algorithm,experimental methods were employed to calculate the evapotranspiration values and evaluated using suitable performance metrics.The results showed that the SEBAL generated evapotranspiration values are in high agreement with the FAO Penman-Monteith method registering the highest correlation(R=0.91)and the lowest error(RMSE=1.14).In addition,the SEBAL method registered the highest correlation values of 0.89,0.87 and 0.68 with Turk,Makkink and Hargreaves experimental methods,respectively.Moreover,the crop coefficients estimated using SEBAL also manifested an acceptable correlation with all methods.The highest correlation value registered was with the FAO Penman-Monteith method(R=0.98).The outcomes show that since the performance of the SEBAL algorithm in estimating the actual evapotranspiration and crop coefficient using Landsat 8 satellite images is acceptable,the SEBAL algorithm could be a very convenient method.Moreover,it could easily be assimilated into farming management systems and precision agriculture for better decision-making and higher yield.

Mapping groundwater dependent ecosystem potential in a semi-arid environment using aremote sensing-based multiple-lines-of-evidence approach

Groundwater dependent ecosystems(GDEs)are vulnerable to groundwater regime changes.However,their protection is often hampered by challenges in their identification.Within is presented a remote sensing-based GDE potential mapping approach based on the persistency of relevant vegetation parameters during prolonged dry periods as an indicator of potential‘consistency’of water supply(e.g.groundwater).The study uses a novel approach to characterising persistency for selected vegetation parameters based on a normalised difference measure and an adaptation of the coefficient of variation statistic.Aggregation of parameters was facilitated through the analytic hierarchy process providing a structured weighting approach to minimise parameter bias.The approach is demonstrated in the semi-arid Flinders Ranges of South Australia where new groundwater resources are being sought to support local domestic and industry needs.Variations in GDE potential were mapped to better target areas where exploration of groundwater should be avoided.Mapping results indicated a high-level of agreement of 77%with an independent springs dataset,along with an 87%agreement with areas coinciding with known phreatophyte species and depths to groundwater.The index-based mapping approach has potential applicability across landscapes,as it normalises for variations in vegetation cover,minimises technical overheads,and employs continental-wide remote sensing data-products.