This page has only limited features, please log in for full access.

Unclaimed
Claudio Piani
Department of Computer, Mathematics and Environmental Science, American University of Paris, Bamako BP 320, France

Basic Info

Basic Info is private.

Honors and Awards

The user has no records in this section


Career Timeline

The user has no records in this section.


Short Biography

The user biography is not available.
Following
Followers
Co Authors
The list of users this user is following is empty.
Following: 0 users

Feed

Journal article
Published: 27 January 2018 in Agronomy
Reads 0
Downloads 0

Climate change is estimated to substantially reduce crop yields in Sub-Saharan West Africa by 2050. Yet, a limited number of studies also suggest that several adaptation measures may mitigate the effects of climate change induced yield loss. In this paper, we used AquaCrop, a process-based model developed by the FAO (The Food and Agriculture Organization, Rome, Italy), to quantify the risk of climate change on several key cereal crops in the Niger Basin. The crops analyzed include maize, millet, and sorghum under rain fed cultivation systems in various agro-ecological zones within the Niger Basin. We also investigated several adaptation strategies, including changes in the sowing dates, soil nutrient status, and cultivar. Future climate change is estimated using nine ensemble bias-corrected climate model projection results under RCP4.5 and RCP8.5 (RCP—Representative Concentration Pathway) emissions scenario at mid future time period, 2021/25–2050. The results show that on average, temperature had a larger effect on crop yields so that the increase in precipitation could still be a net loss of crop yield. Our simulated results showed that climate change effects on maize and sorghum yield would be mostly positive (2% to 6% increase) in the Southern Guinea savanna zone while at the Northern Guinea savanna zone it is mostly negative (2% to 20% decrease). The results show that at the Sahelian zone the projected changes in temperature and precipitation have little to no impact on millet yield for the future time period, 2021/25–2050. In all agro-ecological zones, increasing soil fertility from poor fertility to moderate, near optimal and optimal level significantly reversed the negative yield change respectively by over 20%, 70% and 180% for moderate fertility, near optimal fertility, and optimal fertility. Thus, management or adaptation factors, such as soil fertility, had a much larger effect on crop yield than the climatic change factors. These results provide actionable guidance on effective climate change adaptation strategies for rain fed agriculture in the region.

ACS Style

Uvirkaa Akumaga; Aondover Tarhule; Claudio Piani; Bouba Traoré; Ado A. Yusuf. Utilizing Process-Based Modeling to Assess the Impact of Climate Change on Crop Yields and Adaptation Options in the Niger River Basin, West Africa. Agronomy 2018, 8, 11 .

AMA Style

Uvirkaa Akumaga, Aondover Tarhule, Claudio Piani, Bouba Traoré, Ado A. Yusuf. Utilizing Process-Based Modeling to Assess the Impact of Climate Change on Crop Yields and Adaptation Options in the Niger River Basin, West Africa. Agronomy. 2018; 8 (2):11.

Chicago/Turabian Style

Uvirkaa Akumaga; Aondover Tarhule; Claudio Piani; Bouba Traoré; Ado A. Yusuf. 2018. "Utilizing Process-Based Modeling to Assess the Impact of Climate Change on Crop Yields and Adaptation Options in the Niger River Basin, West Africa." Agronomy 8, no. 2: 11.

Journal article
Published: 16 October 2012 in Geophysical Research Letters
Reads 0
Downloads 0

[1] In common climate model bias‐correction procedures, temperature and precipitation are corrected separately, thereby degrading the dynamical link represented within the model. We propose a methodology that advances the state‐of‐the‐art by correcting not just the 1D intensity distributions separately but the full two‐dimensional statistical distribution. To assess the effectiveness of the proposed method, it is applied to the REMO regional climate model output using point measurements of hourly temperature and precipitation from 6 weather stations over Germany as observations. A standard cross‐validation is performed by dividing the data into two nonoverlapping 15 year periods. Results show that the methodology effectively improves the temperature‐precipitation copula in the validation period, unlike separate 1D temperature and precipitation corrections which, by construction, leave the copula unchanged. An unexpected result is that a relatively small number (<5) of temperature bins are required to achieve significant improvements in the copula. Results are similar for all stations.

ACS Style

Claudio Piani; Jan O Haerter. Two dimensional bias correction of temperature and precipitation copulas in climate models. Geophysical Research Letters 2012, 39, 1 .

AMA Style

Claudio Piani, Jan O Haerter. Two dimensional bias correction of temperature and precipitation copulas in climate models. Geophysical Research Letters. 2012; 39 (20):1.

Chicago/Turabian Style

Claudio Piani; Jan O Haerter. 2012. "Two dimensional bias correction of temperature and precipitation copulas in climate models." Geophysical Research Letters 39, no. 20: 1.