HARMONIC ANALYSIS AND MODELLING OF ANNUAL SOIL TEMPERATURE VARIATIONS

Harmoni c analysi s using se ries is applied to th e annual variation s of so il tem pe rature From th esurface down to I III depth. TIle fir st harmo nic alon e expla ins about 99% of the variation .II is also shO\\TI th at heat conduction is nor valid in a soil med iuIIIunder exothermic conditions. especially in th euppermost layer of abom 20 em. as neither the thermal properties. exp ressed by the damping depth (D), nor th e meansoil temperature (nremai n constant with depth . and th e am plitude ofoscilla tio n (.4:) does nOI vary strictly expcnen rially.Thi s is as sumed to be con sider ably reduced soil moisture of thi s in compari son with deeper layers,Finally. cons truction of a mod el to predict mon thly or ten-d ay period mean soil temper atures is based' onwr-at h e r vari ab les (difference between precipitation and pan evaporation), providing an ind ex for the soil moisturede ficit and an est imate of D. and overcomes the difficulties of ch angi ng T and A: with depth.

Data Intelligence Model and Meta-Heuristic Algorithms-Based Pan Evaporation Modelling in Two Different Agro-Climatic Zones: A Case Study from Northern India

Precise quantification of evaporation has a vital role in effective crop modelling, irrigation scheduling, and agricultural water management. In recent years, the data-driven models using meta-heuristics algorithms have attracted the attention of researchers worldwide. In this investigation, we have examined the performance of models employing four meta-heuristic algorithms, namely, support vector machine (SVM), random tree (RT), reduced error pruning tree (REPTree), and random subspace (RSS) for simulating daily pan evaporation (EPd) at two different locations in north India representing semi-arid climate (New Delhi) and sub-humid climate (Ludhiana). The most suitable combinations of meteorological input variables as covariates to estimate EPd were ascertained through the subset regression technique followed by sensitivity analyses. The statistical indicators such as root mean square error (RMSE), mean absolute error (MAE), Nash–Sutcliffe efficiency (NSE), Willmott index (WI), and correlation coefficient (r) followed by graphical interpretations, were utilized for model evaluation. The SVM algorithm successfully performed in reconstructing the EPd time series with acceptable statistical criteria (i.e., NSE = 0.937, 0.795; WI = 0.984, 0.943; r = 0.968, 0.902; MAE = 0.055, 0.993 mm/day; and RMSE = 0.092, 1.317 mm/day) compared with the other applied algorithms during the testing phase at the New Delhi and Ludhiana stations, respectively. This study also demonstrated and discussed the potential of meta-heuristic algorithms for producing reasonable estimates of daily evaporation using minimal meteorological input variables with applicability of the best candidate model vetted in two diverse agro-climatic settings.

Growth and productivity assessments of peanut under different irrigation water management practices using CSM-CROPGRO-Peanut model in Eastern Mediterranean of Turkey

Irrigation water scheduling is crucial to make the most efficient use of ever-decreasing water. As excessive irrigation decreases yield, while imprecise application also causes various environmental issues. Therefore, efficient management of irrigation frequency and irrigation level is necessary to sustain productivity under limited water conditions. The objective of the current study is to assess the water productivity at various irrigation regimes during peanut crop growing seasons (2014 and 2015) in Eastern Mediterranean, Turkey. The field experiments were conducted with treatments consisting of three irrigation frequencies (IF) (IF1: 25 mm; IF2: 50 mm; and IF3: 75 mm of cumulative pan evaporation (CPE)), and four irrigation water levels (WL1 = 0.50, WL2 = 0.75, WL3 = 1.0, and WL4 = 1.25). WL1, WL2, WL3, and WL4 treatments received 50, 75, 100, and 125 of cumulative pan evaporation. The CSM-CROPGRO-Peanut model was calibrated with experimental data in 2014 and evaluated with second-year experimental data (2015). The model simulated seed yield and final biomass (dry matter) reasonably well with low normalized root mean square error (RMSEn) in various irrigation intervals. The model simulated reasonably well for days to anthesis (RMSE = 2.53, d-stat = 0.96, and r2 = 0.90), days to physiological maturity (RMSE = 2.55), seed yield (RMSE = 1504), and tops biomass dry weight at maturity (RMSE = 3716). Simulation results indicated good agreement between measured and simulated soil water content (SWC) with low RMSEn values (4.0 to 16.8% in 2014 and 4.3 to 18.2% in 2015). Further results showed that IF2I125 irrigation regime produced the highest seed yield. Generally, model evaluation performed reasonably well for all studied parameters with both years’ experimental data. Results also showed that the crop model would be a precision agriculture tool for the extrapolation of the allocation of irrigation water resources and decision management under current and future climate.

Estimation Standard And Seeded Pan Evaporation Using Modelling Approach

Evaporation is an important meteorological variable that has also a great impact on water management. In this study, FAO-56 Penman-Monteith equation (FAO56-PM), multiple stepwise regression (MLR) and Kohonen self-organizing map (K-SOM) techniques were used for the estimation of daily pan evaporation (Ep) in three treatments, where C was the standard class A pan with top water, S was A pan with sediment covered bottom, and SM was class A pan containing submerged macrophytes (Myriophyllum sipctatum., Potamogeton perfoliatus, and Najas marina), in an six-season experiment. The modelling approach included six measured meteorological variables; daily mean air temperatures (Ta), maximum and minimum air temperatures, global radiation (Rs), relative humidity (RH), and wind speed (u) in the 2015–2020 growing seasons (from June to September), at Keszthely, Hungary. Average Ep varied from 0.6 to 6.9 mm d−1 for C, 0.7 to 7.9 mm d−1 for S, whereas from 0.9 to 8.2 mm d−1 for SM during the growing seasons studied. Correlation analysis and K-SOM visual representation revealed that Ta and Rs had stronger positive correlation, while RH had a negative correlation with the Ep of C, S and SM. Performances of the different models were compared using statistical indices, which included the root mean square error (RMSE), mean absolute error (MAE), scatter index (SI) and Nash-Sutcliffe efficiency (NSE). The results showed that the MLR method provided close compliance with the observed pan evaporation values, but the K-SOM method gave better estimates than the other methods. Overall, K-SOM has high accuracy and huge potential for Ep estimation for water bodies where freshwater submerged macrophytes are present.

Recent variations and trends in pan evaporation over India

Thirty years pan evaporation time series data (1971-2000) recorded from US class-A evaporation pans for twenty well distributed locations in India, have been utilized in the present study. For all the locations, basic statistical parameters of annual evaporation [minimum, maximum, range, mean, standard deviation (S.D.) and coefficient of variation (C.V.)] have been computed. Annual, seasonal and monthly trends have been studied using linear trend analysis technique. Suitable graphs have been plotted to study the variations and changes in pan evaporation trends and to identify the specific periods as and when significant changes occur. The mean annual pan evaporation was found to be lowest (1107 mm) at Buralikson and highest (3004 mm) at Rajkot. The highest C.V. of nearly 11% was observed at Rajamundry, Jodhpur, Buralikson and Nellore. The lowest C.V. of nearly 2% was observed at Ambikapur. Out of twenty locations, significant decreasing trend in annual pan evaporation was observed at fifteen locations and no significant trend at five locations. The annual dE/dt values varied from -6.27 (Canning) to -29.30 (Jodhpur) mm/year. The average annual dE/dt over India was found to be -14.90 mm/year. Linear relationship was obtained to quantitatively estimate annual dE/dt, at a given location, using pan evaporation range. On an average, over India, the contribution of seasonal dE/dt towards annual dE/dt (mm/year) is highest -5.63 (37.8 %) in Season-2 (March-April-May) and lowest -2.07 (13.9 %) in Season-1(January- February). On an average, over India, the contribution of monthly dE/dt towards annual dE/dt (mm/year) is highest - 2.08 (14.0 %) in May and lowest -0.77 (5.2 %) in August. Non linear relationships were obtained (a) to quantitatively estimate the average monthly dE/dt values over India, in any particular month (b) to quantitatively estimate the average cumulative dE/dt values over India (mm/year) upto any particular month and (c) to quantitatively estimate the contribution (per cent) towards average annual dE/dt over India, upto any particular month.

Traditional salt processing activities of rural women in Ebonyi State, Nigeria

The traditional salt processing activities of rural women in Ebonyi State, Nigeria was investigated. Two Local Government Areas were purposively selected out of the 13 LGAs in the state and a total of 90 respondents were used for the study. Frequency, percentage and mean score were used in data analysis. Most (68%) of the respondents belonged to salt makers group. The majority (98.9%) of the salt makers indicated that their method of salt production involved pan evaporation with firewood. About 63% of the salt makers engaged in salt production during the dry season. A greater percentage (63.2%) indicated that they fetch brine as the need arises. The majority (86.6%) indicated using ash to filter the brine, while the majority (97.2%) reported that it takes less than 1 day to produce filtrate. About 67% of the women produced 6-10 bags of salt in a month while 53.4% sold 7-10 bags in a month. Salt makers sold salt at an average price of N3,650 per bag. Findings show that 24.7% earned N10,000- N19,999 per month. Major contributions of salt making to the wellbeing of households were: medicinal value (M=2.96), payment of children/ward school fees (M=2.96), better feeding and nutrition (M=2.93). Government should provide aids to the salt processors by providing the basic infrastructure to improve the quality and quantity of salt produced.

Pan evaporation and sensor based approaches of irrigation scheduling for crop water requirement, growth and yield of okra

The results of this study revealed that the pan evaporation and sensor based irrigation scheduling along with fertigation scheduling significantly affected the plant height, fruit weight, fruit length, crop water requirement, crop yield and water use efficiency of okra crop. The pan evaporation and crop evapotranspiration (ETc) values significantly vary over different stages of okra crop. The maximum and minimum average daily pan evaporation was recorded 8.4 mm day-1 and 4.5 mm day-1 at mid stage and late stage of okra crop respectively while, the maximum average daily ETc was recorded 7 mm day-1 at mid stage of okra crop. A approach of irrigation scheduling with 100 per cent field capacity, based on soil moisture sensor under automated drip irrigation system along with 100 per cent RDF through fertigation in equal splits at 4 day intervalor 80 % per cent of volume of crop water requirement based on pan evaporation under automated drip irrigation along with 100 per cent RDF through fertigation in equal splits at 2 day interval, can be used for irrigating okra crop with significant water saving, crop yield and water use efficiency under limited availability of daily weather datain climatic condition of Udaipur district of Rajasthan.