Water Demand Analysis of Sugarcane Based on Crop Simulation Model (Case Study: Kediri Regency, East Java)
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Sugarcane productivity is naturally affected by climate variables and limited by the water availability. This study simulated a water balance model to estimate sugarcane water requirement and to estimate the best planting time as well based on its optimum productivity in Kediri Regency. Water requirement was estimated by water loss of evapotranspiration following FAO No. 24, while the productivity was based on mid-maturing sugarcane growth and development. Sugarcane rainfed area in Kediri Regency needs approximately 26-128 mm water per month based on its loss by evapotranspiration. The value varied due to the growth phase. More than 60% water was used in vegetative phase for developing buds and stem elongation of about 3-9 months after planting. The highest sugarcane productivity was obtained in July-September as the best planting time shown by simulation. Moreover, water deficiency during mid-season of sugarcane growth could decrease productivity by a significant amount. The work presented here could be used as a tool to help decision makers for irrigation management and select the best planting date.Keywords:
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Abstract Providing information on the impacts of climate change on hydrological processes is becoming ever more critical. Modelling and evaluating the expected changes of the water resources over different spatial and time scales can be useful in several fields, e.g. agriculture, forestry and water management. Previously a Budyko-type spatially distributed long-term climate-runoff model was developed for Hungary. This research includes the validation of the model using historical precipitation and streamflow measurements for three nested sub-catchments of the Zala River Basin (Hungary), an essential runoff contributing region to Lake Balaton (the largest shallow lake in Central Europe). The differences between the calculated (from water balance) and the estimated (by the model) mean annual evapotranspiration varied between 0.4% and 3.6% in the validation periods in the sub-catchments examined. Predictions of the main components of the water balance (evapotranspiration and runoff) for the Zala Basin are also presented in this study using precipitation and temperature results of 12 regional climate model simulations (A1B scenario) as input data. According to the projections, the mean annual temperature will be higher from period to period (2011–2040, 2041–2070, 2071–2100), while the change of the annual precipitation sum is not significant. The mean annual evapotranspiration rate is expected to increase slightly during the 21st century, while for runoff a substantial decrease can be anticipated which may exceed 40% by 2071–2100 relative to the reference period (1981–2010). As a result of this predicted reduction, the runoff from the Zala Basin may not be enough to balance the increased evaporation rate of Lake Balaton, transforming it into a closed lake without outflow.
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The requirement for irrigation water would be affected by the variation of meteorological effects under the conditions of climate change, and irrigation water will always be the major portion of the water consumption in Taiwan. This study tries to assess the impact on irrigation water by climate change in Taoyuan in northern Taiwan. Projected rainfall and temperature during 2046–2065 are adopted from five downscaled general circulation models. The future evapotranspiration is derived from the Hamon method and corrected with the quadrant transformation method. Based on the projections and a water balance model in paddy fields, the future crop water requirement, effective rainfall and the demand for water for irrigation can be calculated. A comparison between the present (2004–2011) and the future (2046–2065) clearly shows that climate change would lead both rainfall and the temperature to rise; this would cause effective rainfall and crop water requirement to increase during cropping seasons in the future. Overall, growing effective rainfall neutralizes increasing crop water requirement, the difference of average irrigation water requirement between the present and future is insignificant (<2.5%). However, based on a five year return period, the future irrigation requirement is 7.1% more than the present in the first cropping season, but it is insignificantly less (2.1%) than the present in the second cropping season.
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This article addresses the critical need for a better quantitative understanding of how water resources from the Hérault River catchment in France have been influenced by climate variability and the increasing pressure of human activity over the last 50 years. A method is proposed for assessing the relative impacts of climate and growing water demand on the decrease in discharge observed at various gauging stations in the periods 1961–1980 and 1981–2010. An annual water balance at the basin scale was calculated first, taking into account precipitation, actual evapotranspiration, water withdrawals and water discharge. Next, the evolution of the seasonal variability in hydroclimatic conditions and water withdrawals was studied. The catchment was then divided into zones according to the main geographical characteristics to investigate the heterogeneity of the climatic and human dynamics. This delimitation took into account the distribution of climate, topography, lithology, land cover and water uses, as well as the availability of discharge series. At the area scale, annual water balances were calculated to understand the internal changes that occurred in the catchment between both past periods. The decrease in runoff can be explained by the decrease in winter precipitation in the upstream areas and by the increase during summer in both water withdrawals and evapotranspiration in the downstream areas, mainly due to the increase in temperature. Thus, water stress increased in summer by 35%. This work is the first step of a larger research project to assess possible future changes in the capacity to satisfy water demand in the Hérault River catchment, using a model that combines hydrological processes and water demand. Editor Z.W. Kundzewicz Citation Collet, L., Ruelland, D., Borrell-Estupina, V., and Servat, E., 2014. Assessing the long-term impact of climatic variability and human activities on the water resources of a meso-scale Mediterranean catchment. Hydrological Sciences Journal, 59 (8), 1457–1469. http://dx.doi.org/10.1080/02626667.2013.842073
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<p>Irrigation represents a primary source of anthropogenic water consumption, whose effects impact on the natural distribution of water on the Earth&#8217;s surface and on food production. Over anthropized basins, irrigation often represents the missing variable to properly close the hydrological balance. Despite this, detailed information on the amounts of water actually applied for irrigation is lacking worldwide. In this study, a method to estimate irrigation volumes applied over a heavily irrigated area in the North East of Spain through high-resolution (1 km) remote sensing soil moisture is presented. Two DISPATCH (DISaggregation based on Physical And Theoretical scale CHange) downscaled data sets have been used: SMAP (Soil Moisture Active Passive) and SMOS (Soil Moisture and Ocean Salinity). The SMAP experiment covers the period from January 2016 to September 2017, while the SMOS experiment is referred to the time span from January 2011 to September 2017. The irrigation amounts have been retrieved through the SM2RAIN algorithm, in which the guidelines provided in the FAO (Food and Agriculture Organization) paper n.56 about the crop evapotranspiration have been implemented for a proper modeling of the crop evapotranspiration. A more detailed analysis has been performed in the context of the SMAP experiment. In fact, the spatial distribution and the temporal occurrence of the irrigation events have been investigated. Furthermore, the loss of accuracy of the irrigation estimates when using different sources for the evapotranspiration data has been assessed. In order to do this, the SMAP experiment has been repeated by forcing the SM2RAIN algorithm with several evapotranspiration data sets, both calculated and observed. Finally, the merging of the results obtained through the two experiments has produced a data set of almost 7 years of irrigation estimated from remote sensing soil moisture.</p>
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Competition for limited water supplies continues to exert pressure on agriculture. In addition, climate change, urban growth, and drought influence how farmers manage their water supplies. Water transfers from agriculture to other uses are on the rise. To avoid drying farms one alternative water management strategy is to deficit irrigate. However, to perform a successful managing irrigation under a deficit irrigation regime an accurate crop water consumption monitoring method is required. The objective of this study was to evaluate a crop water stress model that is based on the difference between canopy radiometric temperature and air temperature. Three irrigation treatments were imposed on corn plots grown in northeastern Colorado in 2011. The treatments were: TrT 1 full irrigation (six irrigations), TrT 2 deficit irrigation (two irrigations), and TrT 3 reduced irrigation (six irrigation but half the amount of TrT 1). A local weather station located on a grass field was used to compute reference evapotranspiration. Derived crop water stress indices and water use amounts were evaluated with ET values derived from a Neutron probe-based soil water balance and with a surface energy balance model considering inputs from a remote sensing system. Results indicated that relatively low errors in ET estimation are possible if surface radiometric temperature is acquired earlier in the day.
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A framework for the assessment of relative risk to watershed-scale water resources from systemic changes is presented. It is composed of two experiments, or pathways, within a Monte Carlo structure and provides quantification of prediction uncertainty. One simulation pathway is the no change, or null hypothesis, experiment, and the other provides simulation of the hypothesized system change. Each pathway uses a stochastic weather generator and a deterministic water balance model. For climate change impact analysis, the framework is calibrated so that the differences between thirty-year average precipitation and temperature pathway values reproduce climate trends. Simulated weather provides forcing for identical water balance models. Probabilistic time histories of differences in actual evapotranspiration, runoff, and recharge provide likelihood per magnitude change to water resources availability. The framework is applied to a semi-arid watershed in Texas. Projected climate trends for the site are a 3 °C increase in average temperature and corresponding increase in potential evapotranspiration, no significant change in average annual precipitation, and a semi-arid classification from 2011–2100. Two types of water balance model are used in separate applications: (1) monthly water balance and (2) daily distributed parameter. Both implementations predict no significant change, on average, to actual evapotranspiration, runoff, or recharge from 2011–2100 because precipitation is unchanged on average. Increases in extreme event intensity are represented for future conditions producing increased water availability during infrequent events.
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The impact of climate change on the hydrological regime and water resources in the basin of Venetikos river, in Greece is assessed. A monthly conceptual water balance model was calibrated in this basin using historical hydro meteorological data. This calibrated model was used to estimate runoff under a transient scenario (UKTR) referring to year 2080. The results show that the mean annual runoff, mean winter and summer runoff values, annual maximum and minimum values, as well as, monthly maximum and minimum, will be reduced. Additionally, an increase of potential and actual evapotranspiration was noticed due to temperature increase.
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