scholarly journals The impact of expanding flooded land area on the annual evaporation of rice

2016 ◽  
Vol 223 ◽  
pp. 181-193 ◽  
Author(s):  
Dennis Baldocchi ◽  
Sara Knox ◽  
Iryna Dronova ◽  
Joe Verfaillie ◽  
Patty Oikawa ◽  
...  
2017 ◽  
Vol 1 (1) ◽  
Author(s):  
La Ode Jabuddin ◽  
Ayub M Padangaran ◽  
Azhar Bafadal Bafadal

This study aims to: (1) Knowing the dynamics of fiscal policy and the performance of the agricultural sector, (2) Analyze the factors that influence fiscal policy and the performance                   of the agricultural sector, and (3) Analyzing the impact of fiscal policy on the performance of the agricultural sector. The data used in this study were pooled 2005-2013 data in the aggregate. Econometric model the impact of fiscal policy on the performance of the agricultural sector is built in the form of simultaneous equations, consisting of 7 equations with 25 total variables in the model, 7 endogenous variables, 12 exogenous variables, and 6 variables lag. The model is estimated by 2SLS method SYSLIN procedures and historical simulation with SIMNLIN procedure.The results showed that: (1) The development of fiscal policy in Southeast Sulawesi from year to year tends to increase, (2) The performance of the agricultural sector from the aspect of GDP has decreased, from the aspect of labor is still consistent, in terms of investment to grow positively, and assign roles which means to decrease the number of poor people, (3) factors affecting fiscal policy is local revenues, equalization funds, other revenues, as well as the lag fiscal policy, (4) the factors that affect the performance of the agricultural sector from the aspect GDP is labor, direct expenditure and GDP lag; from the aspect of labor is the total labor force, investment, land area, direct expenditure, as well as the lag of labor; from the aspect of investment is influenced by GDP per capita, land area, interest rates and investment lag; as well as from the aspect of poor people, are affected by population, investments, direct expenditure and poverty lag, (5). Fiscal policy impact on the agricultural sector GDP increase, a decrease in the number of poor, declining agricultural laborers, and a decrease in the amount of investment in the agricultural sector.Keywords: Fiscal policy, the performance of the agricultural sector, the simultaneous equations


2021 ◽  
Vol 10 (4) ◽  
pp. 209
Author(s):  
Chih-Ming Tseng ◽  
Yie-Ruey Chen ◽  
Chwen-Ming Chang ◽  
Yung-Sheng Chue ◽  
Shun-Chieh Hsieh

This study explores the impact of rainfall on the followed-up landslides after a severe typhoon and the relationship between various rainfall events and the occurrence, scale, and regional characteristics of the landslides, including second landslides. Moreover, the influence of land disturbance was evaluated. The genetic adaptive neural network was used in combination with the texture analysis of the geographic information system for satellite image classification and interpretation to analyze land-use change and retrieve disaster records and surface information after five rainfall events from Typhoon Morakot (2009) to Typhoon Nanmadol (2011). The results revealed that except for extreme Morakot rains, the greater the degree of slope disturbance after rain, the larger the exposed slope. Extreme rainfall similar to Morakot strikes may have a greater impact on the bare land area than on slope disturbance. Moreover, the relationship between the bare land area and the index of land disturbance condition (ILDC) is positive, and the ratio of the bare land area to the quantity of bare land after each rainfall increases with the ILDC. With higher effective accumulative rainfall on the slope in the study area or greater slope disturbance, the landslide area at the second landslide point tended to increase.


2016 ◽  
Vol 20 (7) ◽  
pp. 2877-2898 ◽  
Author(s):  
Hannes Müller Schmied ◽  
Linda Adam ◽  
Stephanie Eisner ◽  
Gabriel Fink ◽  
Martina Flörke ◽  
...  

Abstract. When assessing global water resources with hydrological models, it is essential to know about methodological uncertainties. The values of simulated water balance components may vary due to different spatial and temporal aggregations, reference periods, and applied climate forcings, as well as due to the consideration of human water use, or the lack thereof. We analyzed these variations over the period 1901–2010 by forcing the global hydrological model WaterGAP 2.2 (ISIMIP2a) with five state-of-the-art climate data sets, including a homogenized version of the concatenated WFD/WFDEI data set. Absolute values and temporal variations of global water balance components are strongly affected by the uncertainty in the climate forcing, and no temporal trends of the global water balance components are detected for the four homogeneous climate forcings considered (except for human water abstractions). The calibration of WaterGAP against observed long-term average river discharge Q significantly reduces the impact of climate forcing uncertainty on estimated Q and renewable water resources. For the homogeneous forcings, Q of the calibrated and non-calibrated regions of the globe varies by 1.6 and 18.5 %, respectively, for 1971–2000. On the continental scale, most differences for long-term average precipitation P and Q estimates occur in Africa and, due to snow undercatch of rain gauges, also in the data-rich continents Europe and North America. Variations of Q at the grid-cell scale are large, except in a few grid cells upstream and downstream of calibration stations, with an average variation of 37 and 74 % among the four homogeneous forcings in calibrated and non-calibrated regions, respectively. Considering only the forcings GSWP3 and WFDEI_hom, i.e., excluding the forcing without undercatch correction (PGFv2.1) and the one with a much lower shortwave downward radiation SWD than the others (WFD), Q variations are reduced to 16 and 31 % in calibrated and non-calibrated regions, respectively. These simulation results support the need for extended Q measurements and data sharing for better constraining global water balance assessments. Over the 20th century, the human footprint on natural water resources has become larger. For 11–18% of the global land area, the change of Q between 1941–1970 and 1971–2000 was driven more strongly by change of human water use including dam construction than by change in precipitation, while this was true for only 9–13 % of the land area from 1911–1940 to 1941–1970.


2018 ◽  
Vol 10 (10) ◽  
pp. 3556 ◽  
Author(s):  
Gang Liu ◽  
Lu Shi ◽  
Kevin Li

This paper develops a lexicographic optimization model to allocate agricultural and non-agricultural water footprints by using the land area as the influencing factor. An index known as the water-footprint-land density (WFLD) index is then put forward to assess the impact and equity of the resulting allocation scheme. Subsequently, the proposed model is applied to a case study allocating water resources for the 11 provinces and municipalities in the Yangtze River Economic Belt (YREB). The objective is to achieve equitable spatial allocation of water resources from a water footprint perspective. Based on the statistical data in 2013, this approach starts with a proper accounting for water footprints in the 11 YREB provinces. We then determined an optimal allocation of water footprints by using the proposed lexicographic optimization approach from a land area angle. Lastly, we analyzed how different types of land uses contribute to allocation equity and we discuss policy changes to implement the optimal allocation schemes in the YREB. Analytical results show that: (1) the optimized agricultural and non-agricultural water footprints decrease from the current levels for each province across the YREB, but this decrease shows a heterogeneous pattern; (2) the WFLD of 11 YREB provinces all decline after optimization with the largest decline in Shanghai and the smallest decline in Sichuan; and (3) the impact of agricultural land on the allocation of agricultural water footprints is mainly reflected in the land use structure of three land types including arable land, forest land, and grassland. The different land use structures in the upstream, midstream, and downstream regions lead to the spatial heterogeneity of the optimized agricultural water footprints in the three YREB segments; (4) In addition to the non-agricultural land area, different regional industrial structures are the main reason for the spatial heterogeneity of the optimized non-agricultural water footprints. Our water-footprint-based optimal water resources allocation scheme helps alleviate the water resources shortage pressure and achieve coordinated and balanced development in the YREB.


Land ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 81 ◽  
Author(s):  
Dingde Xu ◽  
Zhuolin Yong ◽  
Xin Deng ◽  
Linmei Zhuang ◽  
Chen Qing

Labor force rural-urban migration will lead to changes to the land use patterns of farmers. Using the survey data on dynamic migration of the Chinese labor force in 2014, iv-probit and iv-tobit models were used to analyze the impact of labor migration on the land transfer of farmers. The results show that: (1) Off-farm employment would significantly impact land transfer of farmers and the results are robust. With every 10% increase in the proportion of off-farm employment of farmers, the average probability of rent-in land of farmers decreases by 1.55%, and the average transfer in land area of farmers decreased by 1.04%. Similarly, with every 10% increase in the proportion of off-farm employment of farmers, the average probability of rent-out land of farmers increases by 4.77%, and the average transfer out land area of farmers increases by 3.98%. (2) Part-time employment also has a significant impact on land transfer of farmers, but the impact of part-time employment on land transfer in is not robust. Specifically, with every 10% increase in part-farm employment, the average probability of rent-out land of farmers increases by 7.64%, and the average transfer out land area of farmers increases by 6.85%.


2021 ◽  
Vol 13 (2) ◽  
pp. 183
Author(s):  
Ram Avtar ◽  
Deepak Singh ◽  
Deha Agus Umarhadi ◽  
Ali P. Yunus ◽  
Prakhar Misra ◽  
...  

The COVID-19 related lockdowns have brought the planet to a standstill. It has severely shrunk the global economy in the year 2020, including India. The blue economy and especially the small-scale fisheries sector in India have dwindled due to disruptions in the fish catch, market, and supply chain. This research presents the applicability of satellite data to monitor the impact of COVID-19 related lockdown on the Indian fisheries sector. Three harbors namely Mangrol, Veraval, and Vankbara situated on the north-western coast of India were selected in this study based on characteristics like harbor’s age, administrative control, and availability of cloud-free satellite images. To analyze the impact of COVID in the fisheries sector, we utilized high-resolution PlanetScope data for monitoring and comparison of “area under fishing boats” during the pre-lockdown, lockdown, and post-lockdown phases. A support vector machine (SVM) classification algorithm was used to identify the area under the boats. The classification results were complemented with socio-economic data and ground-level information for understanding the impact of the pandemic on the three sites. During the peak of the lockdown, it was found that the “area under fishing boats” near the docks and those parked on the land area increased by 483%, 189%, and 826% at Mangrol, Veraval, and Vanakbara harbor, respectively. After phase-I of lockdown, the number of parked vessels decreased, yet those already moved out to the land area were not returned until the south-west monsoon was over. A quarter of the annual production is estimated to be lost at the three harbors due to lockdown. Our last observation (September 2020) result shows that regular fishing activity has already been re-established in all three locations. PlanetScope data with daily revisit time has a higher potential to be used in the future and can help policymakers in making informed decisions vis-à-vis the fishing industry during an emergency situation like COVID-19.


2010 ◽  
Vol 14 (5) ◽  
pp. 783-799 ◽  
Author(s):  
P. Döll ◽  
J. Zhang

Abstract. River flow regimes, including long-term average flows, seasonality, low flows, high flows and other types of flow variability, play an important role for freshwater ecosystems. Thus, climate change affects freshwater ecosystems not only by increased temperatures but also by altered river flow regimes. However, with one exception, transferable quantitative relations between flow alterations and ecological responses have not yet been derived. While discharge decreases are generally considered to be detrimental for ecosystems, the effect of future discharge increases is unclear. As a first step towards a global-scale analysis of climate change impacts on freshwater ecosystems, we quantified the impact of climate change on five ecologically relevant river flow indicators, using the global water model WaterGAP 2.1g to simulate monthly time series of river discharge with a spatial resolution of 0.5 degrees. Four climate change scenarios based on two global climate models and two greenhouse gas emissions scenarios were evaluated. We compared the impact of climate change by the 2050s to the impact of water withdrawals and dams on natural flow regimes that had occurred by 2002. Climate change was computed to alter seasonal flow regimes significantly (i.e. by more than 10%) on 90% of the global land area (excluding Greenland and Antarctica), as compared to only one quarter of the land area that had suffered from significant seasonal flow regime alterations due to dams and water withdrawals. Due to climate change, the timing of the maximum mean monthly river discharge will be shifted by at least one month on one third on the global land area, more often towards earlier months (mainly due to earlier snowmelt). Dams and withdrawals had caused comparable shifts on less than 5% of the land area only. Long-term average annual river discharge is predicted to significantly increase on one half of the land area, and to significantly decrease on one quarter. Dams and withdrawals had led to significant decreases on one sixth of the land area, and nowhere to increases. Thus, by the 2050s, climate change may have impacted ecologically relevant river flow characteristics more strongly than dams and water withdrawals have up to now. The only exception refers to the decrease of the statistical low flow Q90, with significant decreases both by past water withdrawals and future climate change on one quarter of the land area. However, dam impacts are likely underestimated by our study. Considering long-term average river discharge, only a few regions, including Spain, Italy, Iraq, Southern India, Western China, the Australian Murray Darling Basin and the High Plains Aquifer in the USA, all of them with extensive irrigation, are expected to be less affected by climate change than by past anthropogenic flow alterations. In some of these regions, climate change will exacerbate the discharge reductions, while in others climate change provides opportunities for reducing past reductions. Emissions scenario B2 leads to only slightly reduced alterations of river flow regimes as compared to scenario A2 even though emissions are much smaller. The differences in alterations resulting from the two applied climate models are larger than those resulting from the two emissions scenarios. Based on general knowledge about ecosystem responses to flow alterations and data related to flow alterations by dams and water withdrawals, we expect that the computed climate change induced river flow alterations will impact freshwater ecosystems more strongly than past anthropogenic alterations.


2017 ◽  
Vol 1 (T4) ◽  
pp. 274-281
Author(s):  
Ve Ngoc Hoang ◽  
Thai Hong Tran

Climate change is occurring increasingly complex and unpredictable, therefore the phenomenon of saltwater intrusion at coastal areas is also increasingly serious. The saltwater intrusion threatens the production and life of people in Nghe An’s coastal areas. Our study used MIKE11, MIKE 21 and ArcGIS software to assess the effects of saltwaters intrusion on agricultural land. The results indicate that the agricultural lands in Nghe An’s coastal areas are at high hazards of saltwater intrusion. Cua Lo town is the most affected by the saltwater intrusion, typically with land for cultivation of perennial trees (BHK), paddy land (LUC, LUK), land for production forests (RST), and land for aquaculture (TSL) are at high risk from the base (with more than 90 % of the total land area).


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