Different agricultural practices affect soil carbon, nitrogen and phosphorous in Kilombero -Tanzania

Alavaisha, Edmond; Manzoni, Stefano; Lindborg, Regina

doi:10.1016/j.jenvman.2018.12.039

Cited by 47 publications

(35 citation statements)

References 41 publications

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“…The SOC in the paddy field decreased as the soil depth increased, and the SOC fluctuation of 0-10 cm was larger than the SOC fluctuations of 10-20 cm and 20-40 cm. These results were essentially consistent with those of previous studies [39]. The results ( Figure 6) showed that the simulated values of rice yield under different water and carbon treatments in the calibration and verification periods were close to the observed data, that is, to the line 1:1.…”

Section: Validation Of Model Parameterssupporting

confidence: 91%

Modeling Climate Change Effects on Rice Yield and Soil Carbon under Variable Water and Nutrient Management

et al. 2021

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Soil organic carbon (SOC) conservation in agricultural soils is vital for sustainable agricultural production and climate change mitigation. To project changes of SOC and rice yield under different water and carbon management in future climates, based on a two-year (2015 and 2016) field test in Kunshan, China, the Denitrification Decomposition (DNDC) model was modified and validated and the soil moisture module of DNDC was improved to realize the simulation under conditions of water-saving irrigation. Four climate models under four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5), which were integrated from the fifth phase of the Coupled Model Intercomparison Project (CMIP5), were ensembled by the Bayesian Model Averaging (BMA) method. The results showed that the modified DNDC model can effectively simulate changes in SOC, dissolved organic carbon (DOC), and rice yield under different irrigation and fertilizer management systems. The normalized root mean squared errors of the SOC and DOC were 3.45–17.59% and 8.79–13.93%, respectively. The model efficiency coefficients of SOC and DOC were close to 1. The climate scenarios had a great impact on rice yield, whereas the impact on SOC was less than that of agricultural management measures on SOC. The average rice yields of all the RCP 2.6, RCP 4.5, RCP 6.0, and RCP 8.5 scenarios in the 2090s decreased by 18.41%, 38.59%, 65.11%, and 65.62%, respectively, compared with those in the 2020s. The long-term effect of irrigation on the SOC content of paddy fields was minimal. The SOC of the paddy fields treated with conventional fertilizer decreased initially and then remained unchanged, while the other treatments increased obviously with time. The rice yields of all the treatments decreased with time. Compared with traditional management, controlled irrigation with straw returning clearly increased the SOC and rice yields of paddy fields. Thus, this water and carbon management system is recommended for paddy fields.

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Section: Validation Of Model Parameterssupporting

confidence: 91%

Modeling Climate Change Effects on Rice Yield and Soil Carbon under Variable Water and Nutrient Management

et al. 2021

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“…In addition, forest loss would directly translate into further habitat loss, biodiversity loss and negative impacts on local livelihoods that depend on their ecosystem services. Hence, further agricultural development must rely on measures to increase productivity, e.g., moderate irrigation, use of fertilizer, leveling, weeding, bunding [106,107]. Such options must be weighed carefully, as also agricultural intensification without areal extension can have detrimental effects on the environment, if not done in a sustainable manner, causing soil compaction, erosion or pollution through input of chemicals [108].…”

Section: Lulc Changementioning

confidence: 99%

Long-Term Land Use/Land Cover Change Assessment of the Kilombero Catchment in Tanzania Using Random Forest Classification and Robust Change Vector Analysis

Thonfeld

Steinbach²,

Muro

et al. 2020

Remote Sensing

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Information about land use/land cover (LULC) and their changes is useful for different stakeholders to assess future pathways of sustainable land use for food production as well as for nature conservation. In this study, we assess LULC changes in the Kilombero catchment in Tanzania, an important area of recent development in East Africa. LULC change is assessed in two ways: first, post-classification comparison (PCC) which allows us to directly assess changes from one LULC class to another, and second, spectral change detection. We perform LULC classification by applying random forests (RF) on sets of multitemporal metrics that account for seasonal within-class dynamics. For the spectral change detection, we make use of the robust change vector analysis (RCVA) and determine those changes that do not necessarily lead to another class. The combination of the two approaches enables us to distinguish areas that show (a) only PCC changes, (b) only spectral changes that do not affect the classification of a pixel, (c) both types of change, or (d) no changes at all. Our results reveal that only one-quarter of the catchment has not experienced any change. One-third shows both, spectral changes and LULC conversion. Changes detected with both methods predominantly occur in two major regions, one in the West of the catchment, one in the Kilombero floodplain. Both regions are important areas of food production and economic development in Tanzania. The Kilombero floodplain is a Ramsar protected area, half of which was converted to agricultural land in the past decades. Therefore, LULC monitoring is required to support sustainable land management. Relatively poor classification performances revealed several challenges during the classification process. The combined approach of PCC and RCVA allows us to detect spatial patterns of LULC change at distinct dimensions and intensities. With the assessment of additional classifier output, namely class-specific per-pixel classification probabilities and derived parameters, we account for classification uncertainty across space. We overlay the LULC change results and the spatial assessment of classification reliability to provide a thorough picture of the LULC changes taking place in the Kilombero catchment.

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“…To the north and west of the Kilombero wetland are the Udzungwa Mountains, and to the south-east, the Mahenge highlands. The natural vegetation is dominated by Miombo forest, extending from mountains to lowland, which has been little impacted by the agricultural encroachment [34][35][36] The valley wetland is a sedimentary basin dominated by cambisols, leptosols and fluvial soils with seasonal flooding. Rainfall is the main driver of streamflow within wetland and average annual runoff between about 310 and 495 mm [37].…”

Section: Description Of Study Areamentioning

confidence: 99%

“…The main valley floor is a core area for agriculture where farms with well-established irrigation schemes have been using chemical fertiliser over the last decade [36]. The irrigation schemes began in the 1980s and used traditional canals until the 2000s, when concrete canals were built.…”

Section: Description Of Study Areamentioning

confidence: 99%

Assessment of Water Quality Across Irrigation Schemes: A Case Study of Wetland Agriculture Impacts in Kilombero Valley, Tanzania

Alavaisha

Lyon

Lindborg

2019

Water

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Coupled change in land and water use due to increased farming intensity is a main factor affecting water quality and quantity, ecological functions and biodiversity globally. Prolonging growing seasons and increasing productivity in wetlands through irrigation have been targeted for increasing food security, particularly in developing countries. Nevertheless, irrigation and drainage have often been associated with degradation of water quality through increased agrochemical and fertiliser runoff and leaching at local scales. In this study, we investigated water quality in streams used for irrigation in a wetland area in Kilombero Valley, Tanzania. We measured physical-chemical water parameters and collected macroinvertebrates with different sensitivity to water quality across several small irrigation schemes covering various conditions. Turbidity, temperature, nitrate-N, and ammonium-N were significantly higher at sampling sites downstream of irrigation compared to upstream. Macroinvertebrate diversity, richness and average score per taxa (ASPT) were higher in general in sampling sites upstream of irrigation, with more sensitive macroinvertebrates decreasing in abundance downstream. There was a positive correlation between physical-chemical parameters and macroinvertebrate indices across the sites. We demonstrate that macroinvertebrate indices can be used as a quick assessment of water quality in response to irrigation schemes in small-scale farming systems of Tanzania. This in turn can allow us to track changes affecting wetland ecosystem function and biodiversity at higher trophic levels and across larger scales, thereby providing useful early warnings to help avoid widespread degradation under widespread agricultural intensification.Water 2019, 11, 671 2 of 22 extent and magnitude of impacts of anthropogenic activity at small scales to support management decisions and avoid compounded impacts at larger scales.Usually, the main source of agricultural irrigation water in wet landscape environments comes from surface water. Because of spatial variation of water chemistry in wetlands, streams and rivers, assessment and monitoring programs are necessary to provide robust insights into the quality and quantity of surface water supplies [11][12][13]. Increased use of chemicals and excess draining of wetlands for agriculture and the associated irrigation can have impacts not only on aquatic ecosystem, but also on human health. Fertilisers and agrochemicals impact physical-chemical characteristics of surface water and biota at different spatial scales [7,14]. Excess nitrate-N in drinking water, for example, impacts young livestock, pregnant women and infants on a local scale [15]. Ammonia and phosphorous in excess cause unpleasant colour, taste and odour of water [6]. At larger scales, leaching of excess nutrients can cause overproduction, algal accumulation and decrease dissolved oxygen in aquatic and wetland environments [16,17]. When pollution goes beyond the self-purifying ability of wetland ecosystems, death of aqu...

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Different agricultural practices affect soil carbon, nitrogen and phosphorous in Kilombero -Tanzania

Cited by 47 publications

References 41 publications

Modeling Climate Change Effects on Rice Yield and Soil Carbon under Variable Water and Nutrient Management

Modeling Climate Change Effects on Rice Yield and Soil Carbon under Variable Water and Nutrient Management

Long-Term Land Use/Land Cover Change Assessment of the Kilombero Catchment in Tanzania Using Random Forest Classification and Robust Change Vector Analysis

Assessment of Water Quality Across Irrigation Schemes: A Case Study of Wetland Agriculture Impacts in Kilombero Valley, Tanzania

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