scholarly journals Effect of climate change on land suitability for surface irrigation and irrigation potential of the shallow groundwater in Ghana

2019 ◽  
Vol 157 ◽  
pp. 110-125 ◽  
Author(s):  
Abeyou W. Worqlul ◽  
Yihun T. Dile ◽  
Jaehak Jeong ◽  
Zenebe Adimassu ◽  
Nicole Lefore ◽  
...  
Keyword(s):  
Climate Change ◽  
Shallow Groundwater ◽  
Land Suitability ◽  
Surface Irrigation ◽  
Irrigation Potential

Assessment of the potential for irrigation development in Albert Nile basin: A case study of Nebbi district

2020 ◽  
Author(s):  
Nicholas Kiggundu ◽  
Charles Bwire ◽  
Joshua Wanyama
Keyword(s):  
Water Resources ◽  
Drip Irrigation ◽  
Sprinkler Irrigation ◽  
Land Suitability ◽  
Surface Irrigation ◽  
Irrigation Development ◽  
Available Water ◽  
Irrigation Potential ◽  
Water Resources Assessment ◽  
Resources Assessment

<p>There has been limited research conducted on irrigation potential in Uganda. The existing studies provide a wide number of estimates of irrigation potential for Uganda and thus constrain reliable medium term planning and investment in the subsector. This research was aimed at assessing the potential for irrigation development in Nebbi District, which cover 195,300 km<sup>2</sup>, with a view of guiding planning and strategic investment in irrigation. Irrigation potential was assessed as an aggregation of the land suitability, water requirement and the available water for irrigation for three systems (drip, sprinkler and surface). Land suitability evaluation for the three systems was determined based upon topography and soil characteristics. The FAO CROPWAT model was used to determine the water requirements for the selected crops. Water resources assessment was carried out using rainfall data and the stream flow analysis of the available water resources in the study area. For surface irrigation, no area was classified as highly suitable or moderately suitable. Only 0.03% (48.91 ha) is marginally suitable, 36% (68,445.55 ha) currently not suitable whereas 64% (121,606.33 ha) permanently not suitable. For drip irrigation, 58.7% (111,591 ha) is marginally suitable and 25.8% (49,084 ha) is moderately suitable. Furthermore, 15% (28,492 ha) and 0.5% (989 ha) are currently not suitable and permanently not suitable respectively. There was no area classified as highly suitable under drip irrigation. For sprinkler irrigation, 14.1% (26 815.8 ha) of the area is marginally suitable and 0.03% (48.1 ha) is classified as moderately suitable for sprinkler irrigation. 47.5% (90 291.4 ha) and 38.4 % (72 987.2 ha) of the area is currently not suitable and permanently not suitable respectively. The mean capability index (Ci) for surface irrigation was 36.1 (currently not suitable), 45.4 (marginally suitable) for drip irrigation while sprinkler irrigation Ci was 42.8 (marginally suitable). Crop evapotranspiration (ET<sub>c</sub>) for the selected crops (tomatoes, cabbages and onions) varied from 2.46 to 5.76 mm/day; 2.87 to 5.92 mm/day and 2.87 to 4.78 mm/day respectively. The results from water resources assessment revealed that the total catchment yield was 2.69 x 10<sup>9</sup> m<sup>3</sup> which permits irrigation for an area of 141,817.65 ha. The results showed that drip irrigation system was more suitable for the Nebbi district.</p>

scholarly journals Predicting Shifts in Land Suitability for Maize Cultivation Worldwide Due to Climate Change: A Modeling Approach

Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 295
Author(s):  
Yuan Gao ◽  
Anyu Zhang ◽  
Yaojie Yue ◽  
Jing’ai Wang ◽  
Peng Su
Keyword(s):  
Climate Change ◽  
Crop Production ◽  
Large Scale ◽  
Land Suitability ◽  
Large Scale Assessment ◽  
Scale Assessment ◽  
Maize Cultivation ◽  
Large Scale Screening ◽  
Selection Of

Suitable land is an important prerequisite for crop cultivation and, given the prospect of climate change, it is essential to assess such suitability to minimize crop production risks and to ensure food security. Although a variety of methods to assess the suitability are available, a comprehensive, objective, and large-scale screening of environmental variables that influence the results—and therefore their accuracy—of these methods has rarely been explored. An approach to the selection of such variables is proposed and the criteria established for large-scale assessment of land, based on big data, for its suitability to maize (Zea mays L.) cultivation as a case study. The predicted suitability matched the past distribution of maize with an overall accuracy of 79% and a Kappa coefficient of 0.72. The land suitability for maize is likely to decrease markedly at low latitudes and even at mid latitudes. The total area suitable for maize globally and in most major maize-producing countries will decrease, the decrease being particularly steep in those regions optimally suited for maize at present. Compared with earlier research, the method proposed in the present paper is simple yet objective, comprehensive, and reliable for large-scale assessment. The findings of the study highlight the necessity of adopting relevant strategies to cope with the adverse impacts of climate change.

Modeling the current land suitability and future dynamics of global soybean cultivation under climate change scenarios

2021 ◽  
Vol 263 ◽  
pp. 108069
Author(s):  
Lu Feng ◽  
Hongyan Wang ◽  
Xiaowei Ma ◽  
Hongbo Peng ◽  
Jianrong Shan
Keyword(s):  
Climate Change ◽  
Land Suitability ◽  
Climate Change Scenarios

scholarly journals Land in Central America will become less suitable for coffee cultivation under climate change

2021 ◽  
Vol 21 (3) ◽  
Author(s):  
Leonel Lara-Estrada ◽  
Livia Rasche ◽  
Uwe A. Schneider
Keyword(s):  
Climate Change ◽  
Central America ◽  
Relative Concentration ◽  
Land Suitability ◽  
Land Evaluation ◽  
Climate Change Scenarios ◽  
Coffee Production ◽  
Policy Makers ◽  
Goods And Services ◽  
Coffee Cultivation

AbstractCoffee cultivation in Central America provides goods and services at local, national, and international levels. Climate change is likely to affect the magnitude and continuity of these benefits by reducing the land suitability for coffee cultivation. To quantify the impacts of climate change on land suitability, we use the Bayesian network model Agroecological Land Evaluation for Coffea arabica L. (ALECA) and estimate the land suitability for coffee production in 2000, 2050, and 2080 under three climate change scenarios based on relative concentration pathways (RCPs) 2.6, 4.5, and 8.5. Results indicate that even under the less severe climate scenarios, over half of the current coffee area in Central America will experience a decline in its land suitability for coffee production, from excellent or good to moderate and marginal, and that the change will not happen in the more distant future of 2080, but by 2050. Under RCP 8.5, most coffee areas become of marginal and moderate suitability. The findings show that the continuity of coffee cultivation in a large portion of coffee areas in Central America is under threat and that farmers and policy-makers should develop adaptation portfolios for their farms and regions in a timely manner.

scholarly journals Analysing the sensitivity of Hungarian landscapes based on climate change induced shallow groundwater fluctuation

2019 ◽  
Vol 68 (4) ◽  
pp. 355-372 ◽  
Author(s):  
Zoltán Zsolt Fehér ◽  
János Rakonczai
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Water Resource ◽  
Climatic Factors ◽  
Shallow Groundwater ◽  
Subsurface Water ◽  
Groundwater Fluctuation ◽  
Current Parameter ◽  
Local Water ◽  
The One

One of the undoubtedly recognizable consequences of the ongoing climate change in Hungary is the permanent change of groundwater depth, and consequently the sustainably reachable local water resources. These processes trigger remarkable changes in soil and vegetation. Thus, in research of sensitivity of any specific landscape to the varying climatic factors, monitoring and continuous evaluation of the water resources is inevitable. The presented spatiotemporal geostatistical cosimulation framework is capable to identify rearrangements of the subsurface water resources through water resource observations. Application of the Markov 2-type coregionalization model is based on the assumption, that presumably only slight changes have to be handled between two consecutive time instants, hence current parameter set can be estimated based on the spatial structures of prior and current dataset and previously identified parameters. Moreover, the algorithm is capable to take into consideration the significance of the geomorphologic settings on the subsurface water flow. Trends in water resource changes are appropriate indicators of certain areas climate sensitivity. The method is also suitable in determination of the main cause of the extraordinary groundwater discharges, like the one, observed from the beginning of the 1980’s in the Danube–Tisza Interfluve in Hungary.

Using machine learning to downscale simulations of climate change induced changes to the shallow groundwater table

2021 ◽  
Author(s):  
Raphael Schneider ◽  
Hans Jørgen Henriksen ◽  
Julian Koch ◽  
Lars Troldborg ◽  
Simon Stisen
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Hydrological Model ◽  
Shallow Groundwater ◽  
Groundwater Table ◽  
Training Data ◽  
Computational Time ◽  
Hydrological Models ◽  
Shallow Groundwater Table ◽  
Induced Changes

<p>The DK-model (https://vandmodel.dk/in-english) is a national water resource model, covering all of Denmark. Its core is a distributed, integrated surface-subsurface hydrological model in 500m horizontal resolution. With recent efforts, a version at a higher resolution of 100m was created. The higher resolution was, amongst others, desired by end-users and to better represent surface and surface-near phenomena such as the location of the uppermost groundwater table. Being presently located close to the surface across substantial parts of the country and partly expected to rise, the groundwater table and its future development due to climate change is of great interest. A rising groundwater table is associated with potential risks for infrastructure, agriculture and ecosystems. However, the 25-fold jump in resolution of the hydrological model also increases the computational effort. Hence, it was deemed unfeasible to run the 100m resolution hydrological model nation-wide with an ensemble of climate models to evaluate climate change impact. The full ensemble run could only be performed with the 500m version of the model. To still produce the desired outputs at 100m resolution, a downscaling method was applied as described in the following.</p><p>Five selected subcatchment models covering around 9% of Denmark were run with five selected climate models at 100m resolution (using less than 3% of the computational time for hydrological models compared to a national, full ensemble run at 100m). Using the simulated changes at 100m resolution from those models as training data, combined with a set of covariates including the simulated changes in 500m resolution, Random Forest (RF) algorithms were trained to downscale simulated changes from 500m to 100m.</p><p>Generalizing the trained RF algorithms, Denmark-wide maps of expected climate change induced changes to the shallow groundwater table at 100m resolution were modelled. To verify the downscaling results, amongst others, the RF algorithms were successfully validated against results from a sixth hydrological subcatchment model at 100m resolution not used in training the algorithms.</p><p>The experience gained also opens for various other applications of similar algorithms where computational limitations inhibit running distributed hydrological models at fine resolutions: The results suggest the potential to downscale other model outputs that are desired at fine resolutions.</p>

Evaluation of the Impacts of Climate Change on Land Suitability for Jatropha Cultivation

2014 ◽  
Vol 955-959 ◽  
pp. 3777-3782 ◽  
Author(s):  
Xiao Feng Zhao ◽  
Bin Le Lin
Keyword(s):  
Climate Change ◽  
Rank Order ◽  
Global Scale ◽  
Land Suitability ◽  
Climate Change Scenarios ◽  
Climate Scenarios ◽  
The West ◽  
The North ◽  
North And South ◽  
Impacts Of Climate Change

We evaluated land suitability for Jatropha cultivation at a global scale under current and future climate scenarios. Areas that are suitable for Jatropha cultivation include southern South America, the west and southeast coasts of Africa, the north of South Asia, and the north and south coasts of Australia. In the predicted climate change scenarios, areas near the equator become less suitable for Jatropha cultivation, and areas further from the equator become more suitable. Our analyses suggest that the rank order of the six climate change scenarios, from the smallest to the largest effects on Jatropha cultivation, was as follows: B1, A1T/B2, A1B, A2, and A1FI.

scholarly journals Observed groundwater temperature response to recent climate change

2014 ◽  
Vol 18 (11) ◽  
pp. 4453-4466 ◽  
Author(s):  
K. Menberg ◽  
P. Blum ◽  
B. L. Kurylyk ◽  
P. Bayer
Keyword(s):  
Climate Change ◽  
Heat Transfer ◽  
Air Temperature ◽  
Shallow Groundwater ◽  
Regime Shifts ◽  
Future Climate Change ◽  
Groundwater Temperature ◽  
Recent Climate Change ◽  
Recent Climate ◽  
Groundwater Dependent Ecosystems

Abstract. Climate change is known to have a considerable influence on many components of the hydrological cycle. Yet, the implications for groundwater temperature, as an important driver for groundwater quality, thermal use and storage, are not yet comprehensively understood. Furthermore, few studies have examined the implications of climate-change-induced groundwater temperature rise for groundwater-dependent ecosystems. Here, we examine the coupling of atmospheric and groundwater warming by employing stochastic and deterministic models. Firstly, several decades of temperature time series are statistically analyzed with regard to climate regime shifts (CRSs) in the long-term mean. The observed increases in shallow groundwater temperatures can be associated with preceding positive shifts in regional surface air temperatures, which are in turn linked to global air temperature changes. The temperature data are also analyzed with an analytical solution to the conduction–advection heat transfer equation to investigate how subsurface heat transfer processes control the propagation of the surface temperature signals into the subsurface. In three of the four monitoring wells, the predicted groundwater temperature increases driven by the regime shifts at the surface boundary condition generally concur with the observed groundwater temperature trends. Due to complex interactions at the ground surface and the heat capacity of the unsaturated zone, the thermal signals from distinct changes in air temperature are damped and delayed in the subsurface, causing a more gradual increase in groundwater temperatures. These signals can have a significant impact on large-scale groundwater temperatures in shallow and economically important aquifers. These findings demonstrate that shallow groundwater temperatures have responded rapidly to recent climate change and thus provide insight into the vulnerability of aquifers and groundwater-dependent ecosystems to future climate change.

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