scholarly journals Water balance studies for the crop planning in Ranchi, Jharkhand

MAUSAM ◽  
2021 ◽  
Vol 61 (2) ◽  
pp. 233-238
Author(s):  
P. K. SINGH ◽  
A. K. BHARGAVA ◽  
VASU MITRA ◽  
AWADHESH PRASAD ◽  
M. JAYAPALAN

The rainfall data of 35 years was analyzed to quantify the rainfall efficiency for increased production for Ranchi region. The actual evaporation in driest year due to prolonged dry spell gives rise to severe drought condition affecting the crop growth adversely. No surplus water was recorded during driest year. In respect of coefficient of variation, the month of July registered the lowest coefficient of variation of 35 per cent followed by August (38 per cent) indicating lesser variability during this month. The threshold level of coefficient of variation ranges of 50-100 per cent was associated with April to October and indicated the dependability of rainfall in these months as compared to other months. The maximum length of growing season of 28 week, while minimum 12 week was recorded. In normal conditions, the length of growing season were recorded 18 week. Therefore, short duration paddy variety Birsa Gora-101, maize, i.e., Devki, Ganga-11, Suran and kharif pulses are suitable for the region.  

2021 ◽  
Vol 13 (6) ◽  
pp. 1147
Author(s):  
Xiangqian Li ◽  
Wenping Yuan ◽  
Wenjie Dong

To forecast the terrestrial carbon cycle and monitor food security, vegetation growth must be accurately predicted; however, current process-based ecosystem and crop-growth models are limited in their effectiveness. This study developed a machine learning model using the extreme gradient boosting method to predict vegetation growth throughout the growing season in China from 2001 to 2018. The model used satellite-derived vegetation data for the first month of each growing season, CO2 concentration, and several meteorological factors as data sources for the explanatory variables. Results showed that the model could reproduce the spatiotemporal distribution of vegetation growth as represented by the satellite-derived normalized difference vegetation index (NDVI). The predictive error for the growing season NDVI was less than 5% for more than 98% of vegetated areas in China; the model represented seasonal variations in NDVI well. The coefficient of determination (R2) between the monthly observed and predicted NDVI was 0.83, and more than 69% of vegetated areas had an R2 > 0.8. The effectiveness of the model was examined for a severe drought year (2009), and results showed that the model could reproduce the spatiotemporal distribution of NDVI even under extreme conditions. This model provides an alternative method for predicting vegetation growth and has great potential for monitoring vegetation dynamics and crop growth.


2010 ◽  
Vol 14 (4) ◽  
pp. 627-638 ◽  
Author(s):  
H. Makurira ◽  
H. H. G. Savenije ◽  
S. Uhlenbrook

Abstract. Smallholder rainfed farming systems generally realise sub-optimal crop yields which are largely attributed to dry spell occurrences during crop growth stages. However, through the introduction of appropriate farming practices, it is possible to substantially increase yield levels even with little and highly variable rainfall. The presented results follow research conducted in the Makanya catchment in northern Tanzania where gross rainfall amounts to less than 400 mm/season which is insufficient to support staple food crops (e.g. maize). The yields from farming system innovations (SIs), which are basically alternative cultivation techniques, are compared against traditional farming practices. The SIs tested in this research are runoff harvesting used in combination with in-field trenches and soil bunds (fanya juus). These SIs aim to reduce soil and nutrient loss from the field and, more importantly, promote in-field infiltration and water retention. Water balance components have been observed in order to study water partitioning processes for the "with" and "without" SI scenarios. Based on rainfall, soil evaporation, transpiration, runoff and soil moisture measurements, a water balance model has been developed to simulate soil moisture variations over the growing season. Simulation results show that, during the field trials, the average productive transpiration flow ranged between 1.1–1.4 mm d−1 in the trial plots compared to 0.7–1.0 mm d−1 under traditional tillage practice. Productive transpiration processes accounted for 23–29% while losses to deep percolation accounted for 33–48% of the available water. The field system has been successfully modelled using the spreadsheet-based water balance 1-D model. Conclusions from the research are that the SIs that were tested are effective in enhancing soil moisture retention at field scale and that diversions allow crop growth moisture conditions to be attained with early rains. From the partitioning analysis, it is also concluded that there is more scope for efficient utilisation of the diverted runoff water if storage structures could be installed to minimise runoff and deep percolation and, hence, regulate water flow to the root zone when required.


1988 ◽  
Vol 24 (3) ◽  
pp. 385-391 ◽  
Author(s):  
D. Jena ◽  
C. Misra

SUMMARYRice, pigeonpea and rice + pigeonpea systems (in the row proportions of 1:2 and 2:5) were compared. Soil water depletion and percolation were determined during selected dry spells and yields ascertained after harvest. The mean evapotranspiration rates of rice, pigeonpea, rice + pigeonpea (1:2) and rice + pigeonpea (2:5) were 0.28, 0.79, 0.40 and 0.35 cm d−1, respectively, during a dry spell around 60 days after sowing. In general low rainfall intensity and frequent dry spells in the growing season increased pigeonpea yield but depressed that of rice. Intercropping thus ensured yield stability and hence the profitability of the system as a whole.


2009 ◽  
Vol 6 (4) ◽  
pp. 5537-5563 ◽  
Author(s):  
H. Makurira ◽  
H. H. G. Savenije ◽  
S. Uhlenbrook

Abstract. Smallholder rainfed farming systems generally realise sub-optimal crop yields which are largely attributed to dry spell occurrences during crop growth stages. However, with improved farming practices, it seems possible to significantly increase yield levels even with little and highly variable rainfall. The presented results follow research conducted in the Makanya catchment in northern Tanzania where gross rainfall amounts to less than 400 mm/season which is insufficient to support staple food crops (e.g. maize). Alternative cultivation techniques such as runoff harvesting and in-field micro-storage structures are compared. These techniques aim to reduce soil and nutrient loss from the field but, more importantly, promote in-field infiltration and water retention. Water balance components have been observed in order to study water partitioning processes under different cultivation techniques. Based on rainfall, soil evaporation, transpiration, runoff and soil moisture measurements, a water balance model has been developed to simulate soil moisture variations over the growing season. It appears that about 50% of the diverted water leaves the root zone through deep percolation. Modelling shows that during the field trials the average productive transpiration flow ranged between 1.1–1.4 mm d−1 in the trial plots compared to 0.7–1.0 mm d−1 under traditional tillage practice. Productive transpiration processes accounted for 23–29% while losses to deep percolation accounted for 33–48% of the available water. Conclusions from the research are that the innovations tested are effective in enhancing soil moisture retention at field scale and that diversions allow crop growth moisture conditions to be attained with early rains. It is also concluded that there is more scope for efficient utilisation of the diverted runoff water if storage structures could be installed to regulate water flow to the root zone when required.


2010 ◽  
Vol 7 (3) ◽  
pp. 3733-3763 ◽  
Author(s):  
F. Yemenu ◽  
D. Chemeda

Abstract. Agricultural practices and water resources management in the central highlands of Ethiopia is highly dependant and associated with climatic resources and their pattern and hence wise use of those resources is a priority for the region. Accordingly, a study was conducted to asses and critically quantity the climate resources of the central high lands of Ethiop, Bishoftu district. Thirty three years of weather record data has been used for the work. The onset, duration and end of the growing seasons were defined and quantified based on FAO and Reddy models while the dry and wet spell distributions and the drought events were calculated using the Markov chain models and the standardized precipitation index (SPI) respectively. The results revealed that the mean onset of the main (Kiremt) growing season was found to occur during the second meteorological decade and ended during the end of September. Similarly, though unreliable and only few occurred during the entire study period, the mean onset of the shorter (Belg) season was found to occur during the beginning of the first decade of April. The length of the growing season during the main rainy season, (Kiremt,) ranged from 112 to 144 days with a standard deviation of 9.6 days and coefficient of variation of 7.5%. However, the mean growing length during the Belg season was found to be 22.4 days with a standard deviation of 27 days and coefficient of variation of 122%. The results of analysis obtained both from the Markov Chain and Reddy models indicated higher probabilities of dry spell occurrences during the shorter season (Belg) but the occurrences of the same in the main rainy season (Kiremt) was very minimal. Like wise, the SPI model detected some drought events ranging from mild to severe classes in both seasons based on one a month time scale analysis. A considerable attention of maximizing crop harvest during the main rainy season is practically important.


2018 ◽  
Vol 24 (2) ◽  
pp. 87-96
Author(s):  
Iput Pradiko ◽  
Eko Novandy Ginting ◽  
Nuzul Hijri Darlan ◽  
Winarna Winarna ◽  
Hasril Hasan Siregar

El Niño 2015 is one of the strongest El Niño. Drought stress due to El Niño could affect oil palm performances. This study was conducted to determine rainfall pattern and oil palm performance in Sumatra and Borneo Island during El Niño 2015. Data employed in this study is monthly rainfall data, Southern Oscillation Index (SOI) January-December 2015, andoil palm performances. Pearson correlation between SOI and rainfall data was used to analyze rainfall pattern, while oil palm performances were observed based on morphological conditions. Result shows that southern part of Sumatra and mostly part of Borneo suffer from more dry spell, dry month, and water deficit such as 37-133 days, 3-5 months, and 349-524 mm respectively. Analysis of rainfall pattern shows that Jambi, South Sumatra, Lampung, Central, South, and East Borneo are significantly (r ≥ +0,60) affected by El Niño 2015. Oil palms in southern part of Sumatra and mostly part of Borneo are suffer from drought stressmarked by the emergence of more than two spear fronds, appearing of many male flowers, malformations on bunches, fronds tend to hanging down, and lower fronds tend to dry.


1978 ◽  
Vol 14 (1) ◽  
pp. 1-5 ◽  
Author(s):  
J. L. Monteith

SUMMARYFigures for maximum crop growth rates, reviewed by Gifford (1974), suggest that the productivity of C3 and C4 species is almost indistinguishable. However, close inspection of these figures at source and correspondence with several authors revealed a number of errors. When all unreliable figures were discarded, the maximum growth rate for C3 stands fell in the range 34–39 g m−2 d−1 compared with 50–54 g m−2 d−1 for C4 stands. Maximum growth rates averaged over the whole growing season showed a similar difference: 13 g m−2 d−1 for C3 and 22 g m−2 d−1 for C4. These figures correspond to photosynthetic efficiencies of approximately 1·4 and 2·0%.


2018 ◽  
Vol 66 (2) ◽  
pp. 232-245 ◽  
Author(s):  
Vakhtang Shelia ◽  
Jirka Šimůnek ◽  
Ken Boote ◽  
Gerrit Hoogenbooom

AbstractAccurate estimation of the soil water balance of the soil-plant-atmosphere system is key to determining the availability of water resources and their optimal management. Evapotranspiration and leaching are the main sinks of water from the system affecting soil water status and hence crop yield. The accuracy of soil water content and evapotranspiration simulations affects crop yield simulations as well. DSSAT is a suite of field-scale, process-based crop models to simulate crop growth and development. A “tipping bucket” water balance approach is currently used in DSSAT for soil hydrologic and water redistribution processes. By comparison, HYDRUS-1D is a hydrological model to simulate water flow in soils using numerical solutions of the Richards equation, but its approach to crop-related process modeling is rather limited. Both DSSAT and HYDRUS-1D have been widely used and tested in their separate areas of use. The objectives of our study were: (1) to couple HYDRUS-1D with DSSAT to simulate soil water dynamics, crop growth and yield, (2) to evaluate the coupled model using field experimental datasets distributed with DSSAT for different environments, and (3) to compare HYDRUS-1D simulations with those of the tipping bucket approach using the same datasets. Modularity in the software design of both DSSAT and HYDRUS-1D made it easy to couple the two models. The pairing provided the DSSAT interface an ability to use both the tipping bucket and HYDRUS-1D simulation approaches. The two approaches were evaluated in terms of their ability to estimate the soil water balance, especially soil water contents and evapotranspiration rates. Values of thedindex for volumetric water contents were 0.9 and 0.8 for the original and coupled models, respectively. Comparisons of simulations for the pod mass for four soybean and four peanut treatments showed relatively highdindex values for both models (0.94–0.99).


2020 ◽  
Author(s):  
Karen Hei-Laan Yeung ◽  
Carole Helfter ◽  
Neil Mullinger ◽  
Mhairi Coyle ◽  
Eiko Nemitz

<p>Peatlands North of 45˚ represent one of the largest terrestrial carbon (C) stores. They play an important role in the global C-cycle, and their ability to sequester carbon is controlled by multiple, often competing, factors including precipitation, temperature and phenology. Land-atmosphere exchange of carbon dioxide (CO<sub>2</sub>) is dynamic, and exhibits marked seasonal and inter-annual variations which can effect the overall carbon sink strength in both the short- and long-term.</p><p>Due to increased incidences of climate anomalies in recent years, long-term datasets are essential to disambiguate natural variability in Net Ecosystem Exchange (NEE) from shorter-term fluctuations. This is particularly important at high latitudes (>45˚N) where the majority of global peatlands are found. With increasing pressure from stressors such as climate and land-use change, it has been predicted that with a ca. 3<sup>o</sup>C global temperature rise by 2100, UK peatlands could become a net source of C.</p><p>NEE of CO<sub>2</sub> has been measured using the eddy-covariance (EC) method at Auchencorth Moss (55°47’32 N, 3°14’35 W, 267 m a.s.l.), a temperate, lowland, ombrotrophic peatland in central Scotland, continuously since 2002. Alongside EC data, we present a range of meteorological parameters measured at site including soil temperature, total solar and photosynthetically active radiation (PAR), rainfall, and, since April 2007, half-hourly water table depth readings. The length of record and range of measurements make this dataset an important resource as one of the longest term records of CO<sub>2</sub> fluxes from a temperate peatland.</p><p>Although seasonal cycles of gross primary productivity (GPP) were highly variable between years, the site was a consistent CO<sub>2</sub> sink for the period 2002-2012. However, net annual losses of CO<sub>2</sub> have been recorded on several occasions since 2013. Whilst NEE tends to be positively correlated with the length of growing season, anomalies in winter weather also explain some of the variability in CO<sub>2</sub> sink strength the following summer.</p><p>Additionally, water table depth (WTD) plays a crucial role, affecting both GPP and ecosystem respiration (R<sub>eco</sub>). Relatively dry summers in recent years have contributed to shifting the balance between R<sub>eco</sub> and GPP: prolonged periods of low WTD were typically accompanied by an increase in R<sub>eco</sub>, and a decrease in GPP, hence weakening the overall CO<sub>2</sub> sink strength. Extreme events such as drought periods and cold winter temperatures can have significant and complex effects on NEE, particularly when such meteorological anomalies co-occur. For example, a positive annual NEE occurred in 2003 when Europe experienced heatwave and summer drought. More recently, an unusually long spell of snow lasting until the end of March delayed the onset of the 2018 growing season by up to 1.5 months compared to previous years. This was followed by a prolonged dry spell in summer 2018, which weakened GPP, increased R<sub>eco</sub> and led to a net annual loss of 47.4 ton CO<sub>2</sub>-C km<sup>-2</sup>. It is clear that the role of Northern peatlands within the carbon cycle is being modified, driven by changes in climate at both local and global scales.</p>


2011 ◽  
Vol 8 (3) ◽  
pp. 6291-6329 ◽  
Author(s):  
X. Xu ◽  
D. Yang ◽  
M. Sivapalan

Abstract. Understanding the interactions among climate, vegetation cover and the water cycle lies at the heart of the study of watershed ecohydrology. Recently, considerable attention is being paid to the effect of climate variability (e.g., precipitation and temperature) on catchment water balance and also associated vegetation cover. In this paper, we investigate the general pattern of long-term water balance and vegetation cover (as reflected in fPAR) among 193 study catchments in Australia through statistical analysis. We then employ the elasticity analysis approach for quantifying the effects of climate variability on hydrologic partitioning (including total runoff, surface and subsurface runoff) and on vegetation cover (including total, woody and non-woody vegetation cover). Based on the results of statistical analysis, we conclude that annual runoff (R), evapotranspiration (E) and runoff coefficient (R/P) all increase with vegetation cover for catchments in which woody vegetation is dominant and annual precipitation is relatively high. Annual evapotranspiration (E) is mainly controlled by water availability rather than energy availability for catchments in relatively dry climates in which non-woody vegetation is dominant. The ratio of subsurface runoff to total runoff (Rg/R) also increases with woody vegetation cover. Through the elasticity analysis of catchment runoff, it is shown that precipitation (P) in the current year is the most important factor affecting the change in annual total runoff (R), surface runoff (Rs) and subsurface runoff (Rg). The significance of other controlling factors is in the order of the annual precipitation in the previous year (P−1 and P−2), which represent the net effect of soil moisture, and the annual mean temperature (T) in the current year. Change of P by +1 % causes a +3.35 % change of R, a +3.47 % change of Rs and a +2.89 % change of Rg, on average. Likewise a change of temperature of +1° causes a −0.05 % change of R, a −0.07 % change of Rs and a −0.10 % change of Rg, on average. Results of elasticity analysis on the maximum monthly vegetation cover indicate that incoming shortwave radiation during the growing season (Rsd,grow) is the most important factor affecting the change in vegetation cover. Change of Rsd,grow by +1 % produces a −1.08 % change of total vegetation cover (Ft) on average. The significance of other causative factors is in the order of the precipitation during growing season, mean temperature during growing season and precipitation during non-growing season. The growing season precipitation is more significant than the non-growing season precipitation to non-woody vegetation cover, but the both have equivalent effects to woody vegetation cover.


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