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Report No: 148630 – AFR

Leveraging the Landscape Case Study of Erosion Control through Land Management in the Basin

May 2020

Environment, Natural Resource and Blue Economy Global Practice

The World Bank

© 2020 The World Bank 1818 H Street NW, Washington DC 20433 Telephone: 202-473-1000; Internet: www.worldbank.org

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Table of Contents ABBREVIATIONS AND ACRONYMS ...... iv ACKNOWLEDGMENTS ...... vi EXECUTIVE SUMMARY ...... vii CHAPTER 1. INTRODUCTION ...... 1 CHAPTER 2. OVERVIEW OF LAND DEGRADATION AND SLWM PRACTICES IN LVB ...... 4 2.1 Land Degradation Problems in the LVB ...... 4 2.2 SLWM practices in LVB ...... 5 CHAPTER 3. INTRODUCTION TO CASE STUDY AREA AND METHODOLOGY ...... 8 3.1 Description of the case study area ...... 8 3.2 Methodology used in the case study ...... 11 CHAPTER 4. LAND DEGRADATION AND EFFECTIVENESS OF SLWM–CASE STUDY FINDINGS ...... 17 4.1 Characterization of land degradation in the Catchment ...... 17 4.2 Geo-spatial information of the selected hotspot micro-catchments ...... 24 Spatio-temporal pattern of vegetation degradation in the micro-catchments ...... 29 4.3 Effectiveness of the identified SLWM options ...... 34 4.4 Projected effectiveness of the selected SLWM under the near future climate change scenarios ...... 38 4.5 Summary of the case study’s analytical findings ...... 40 4.6 Beyond technical solutions ...... 41 CHAPTER 5. MONITORING INDICATORS AND MEASURES OF SOIL EROSION REDUCTION ...... 44 5.1 Overview of M&E approaches ...... 44 5.2 M&E Indicators ...... 46 5.3 Methods for M&E of soil erosion and sediment ...... 50 CHAPTER 6. RECOMMENDATIONS AND CONCLUSIONS ...... 54 6.1 Enhancing SLWM ...... 54 6.2 Developing an M&E system for SLWM ...... 55 6.3 Concluding remarks ...... 56 REFERENCES ...... 57

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List of Tables

Table 1. Classification of soil erosion risk...... 13 Table 2. Data used in the SWAT model, sources and their resolutions ...... 13 Table 3. Model parameters used to represent pre-SLWM and Post SLWM conditions ...... 16 Table 4. Land use/cover change in the Simiyu catchment (1986-2016) ...... 17 Table 5. Calibration and validation statistics...... 20 Table 6. Simulated flow, sediment yield, sediment and nutrient loads at the outlet of Simiyu catchment (1980-2009) ...... 21 Table 7. Kabondo micro-catchment land use/cover change (1986-2016) ...... 24 Table 8. Nyamatembe micro-catchment land use/cover change (1986-2016) ...... 25 Table 9. Gully length and density in Kabondo and Nyamatembe micro-catchments ...... 32 Table 10. Annual average flow, sediment and nutrient loads in Kabondo micro-catchment from 1980 to 2009 ...... 34 Table 11. Annual average flow, sediment and nutrient loads in Nyamatembe micro-catchment from 1980 to 2009 ...... 34 Table 12. SLWM interventions found in the pilot micro-catchments of the Simiyu catchment ...... 34 Table 13. Effectiveness of selected SLWM in sediment and nutrient reduction in Nyamatembe micro-catchment in 1980-2009 ...... 37 Table 14. Effectiveness of selected SLWM in sediment and nutrient reduction in Kabondo micro-catchment in1980-2009 ...... 37 Table 15. Effectiveness of selected SLWM in sediment and nutrient reduction in Simiyu catchment in 1980-2009 ...... 38 Table 16. Projected change in average annual temperature and annual rainfall in the near future scenario (2010-2039)...... 38 Table 17. Projected flow, sediment load and concentration, and nutrient loads in Simiyu catchment, Kabondo and Nyamatembe micro-catchments in the near future (2010-2039) without SLWM...... 39 Table 18. Relative change in water quality and quantity parameters in Simiyu catchment induced by the selected SLWM in the near future (2010-2039) under RCP 8.5...... 40 Table 19. Relative change in water quality and quantity parameters in Kabondo micro- catchment induced by the selected SLWM in the near future (2010-2039) under RCP 8.5 40 Table 20. Relative change in water quality and quantity parameters in Nyamatembe micro- catchment induced by the selected SLWM in 2010-2039 under RCP 8.5 ...... 40 Table 21. Farm level SLWM indicators proposed by SLWM specialists in Uganda and ...... 49

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List of Figures

Figure 1. Topography map of the Simiyu River Catchment, Tanzania ...... 8 Figure 2. Soil Map of the Simiyu River Catchment, Tanzania ...... 9 Figure 3. Land use/cover of Simiyu River Catchment ...... 10 Figure 4. Variation of average monthly rainfall, potential evapotranspiration, and discharge at the outlet of the Simiyu River (1999–2004) ...... 10 Figure 5. Land use/cover in Simiyu River Catchment (2016) ...... 17 Figure 6. Soil loss hotspot areas in the Simiyu River Catchment in 2016, assuming no SLWM ...... 19 Figure 7. Percentage of the catchment area under different soil erosion risks in 2016 and 2006 ...... 20 Figure 8. Flow calibration (1979-1987) and validation (1988-1995) results for Simiyu River Catchment ...... 20 Figure 9. Average simulated sediment yield in Simiyu catchment (1980 - 2009) ...... 21 Figure 10. Average simulated sediment yield in Simiyu catchment (2010 - 2016) ...... 22 Figure 11. Vegetation degradation in Simiyu catchment as indicated by NPP, 2001-2015 .... 23 Figure 12. Trend in NDVI across the entire Simiyu catchment (2001-2016) ...... 24 Figure 13. Soil erosion hotspot micro-catchments in Simiyu catchment ...... 25 Figure 14. Proportion of land under different soil erosion risks, without SLWM ...... 26 Figure 15. Soil erosion hotspots in Kabondo sub-catchment, Simiyu catchment (2006) ...... 27 Figure 16. Soil erosion hotspots in Kabondo sub-catchment, Simiyu catchment (2016) ...... 27 Figure 17. Soil erosion hotspots in Nyamatembe micro-catchment, Simiyu catchment (2006) ...... 28 Figure 18. Soil erosion hotspots in Nyamatembe micro-catchment, Simiyu catchment (2016) ...... 28 Figure 19. Spatio-temporal pattern in the NPP state of degradation in Kabondo micro- catchment, 2001-2015 ...... 30 Figure 20. Spatio-temporal pattern in the NPP state of degradation in Nyamatembe micro- catchment, 2001-2015 ...... 31 Figure 21. Gully distribution in Kabondo micro-catchment ...... 33 Figure 22. Gully distribution in Nyamatembe micro-catchment ...... 33 Figure 23. Integrated methodological framework for M&E and assessment of SLWM interventions ...... 45 Figure 24. Elements of the impact of land management interventions ...... 47

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ABBREVIATIONS AND ACRONYMS

AGNPS Annualized Agricultural Non-Point Pollution Sources ANSWERS Areal Non-point source catchment Environmental Response Simulation BMP Best Management Practice CREAMS Chemicals, Runoff, and Erosion from Agricultural Management Systems CMIP5 Coupled Model Inter-comparison Project 5 CV Coefficient of Variation DEM Digital Elevation Model DPSIR Drivers, pressures, state, impact and response EC European Commission ENRM Environmental and Natural Resource Management EO European Observation ESDAC European Soil Data Centre EUROSEM The European Soil Erosion Model FAO Food and Agricultural Organization GCM General Circulation Model GHG Greenhouse Gas GIS Geographical Information System GLASOD Global Assessment of Human Induced Soil Deterioration GPS Global Positioning System ISRIC International Soil Reference and Information Centre KGE Kling and Gupta Efficiency KINEROS Kinematic Runoff and Erosion Model LUCC Land use and cover change LVB Lake Victoria Basin LVBWB Lake Victoria Basin Water Board LVEMP Lake Victoria Environmental Management Project LDN Land Degradation Neutrality M&E Monitoring and Evaluation MODIS Moderate Resolution Imaging Spectroradiometer (NASA/EOS instrument) MoWI Ministry of Water and Irrigation MUSLE Modified Universal Soil Loss Equation NBI Basin Initiative NDVI Normalized Difference Vegetation Index NPP Net Primary Productivity PBIAS Percent bias PDO Project Development Objective RCP Representative Concentration Pathway RS Remote Sensing RUSLE Revised Universal Soil Loss Equation SDG Sustainable Development Goal

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SCS Soil Conservation Service SHETRAN Système Hydrologique Européen TRANsport SLWM Sustainable Land and Water Management SOBEK-RE SOBEK for River and Estuary SOTER Soil and Terrain (database) SQAPP Soil Quality Mobile App SRP Soluble Reactive Phosphorus SSA Sub-Saharan Africa SWAT Soil and Water Assessment Tool TAMP Transboundary Agro-ecosystem Management Project for Basin TDS Total Dissolved Solids TLF TerrAfrica Leveraging Fund TN Total Nitrogen TP Total Phosphorus TSS Total Suspended Solids USGS United States Geological Survey USLE Universal Soil Loss Equation UNCCD United Nations Convention to Combat Desertification UNESCO The United Nations Educational, Scientific and Cultural Organization WEPP Water Erosion Prediction Project WOCAT World Overview of Conservation Approaches and Technologies

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ACKNOWLEDGMENTS

This report is an output of the Study “Effectiveness of Sustainable Land and Water Interventions in Soil Erosion Control in the Lake Victoria Basin: Case Study in Simiyu River Catchment, Tanzania.” The Study was funded by the TerrAfrica Leveraging Fund (TLF) and executed by the World Bank.

The report was written by Guoping Zhang (Sr. Water Resource Management Specialist), Mwanjalolo. J.G. Majaliwa (Consultant), and Jian Xie (Sr. Environmental Specialist) of the World Bank, with input from Fidelis Kaihura (Consultant), Luuk Fleskens (Consultant), and Susanne Leloup (Consultant). Valuable comments and suggestions were provided by Philippe Eric Dardel (Sr Environmental Specialist and TerrAfrica Program Coordinator), Paola Agostini (Lead Natural Resources Management Specialist), Grant Milne (Sr. Natural Resources Management Specialist), and Selamawit Damtew Amare (African Fellow) of the World Bank.

The team gratefully acknowledges the general guidance of Iain Shuker, Practice Manager, Environment, Natural Resources and Blue Economy Global Practice, and Ali Said Matano, Executive Secretary of the Lake Victoria Basin Commission (LVBC). The team would also like to acknowledge the support of the staff of the Tanzania National Project Coordination Team for the Lake Victoria Environmental Management Project (LVEMP), led by Mr. Omari Mwanza and comprising Nesphory Subira, Rose Mgema Rodhmina Mbilinyi, Rose Rwebugisa, Perpetua Masaga, Renatus Machumi, and Simon Msemwa, to the Bank team during field investigations and consultation as well as their provision of relevant data and suggestions to the study. The Lake Victoria Basin Water Board of Tanzania provided hydro-meteorological data for the study. Demetra Aposporos and Marc Massicotte provided editorial support to the report.

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EXECUTIVE SUMMARY Land degradation has been one of the major challenges facing communities in the Lake Victoria Basin (LVB) for a long time. It results in soil erosion and sedimentation and, consequently, contributes to water quality deterioration and eutrophication of the Lake Victoria (LV). Exacerbated by demographic pressures, increasing demands for land, food and energy, and unsustainable land management practices, land degradation will continue and threaten the livelihoods of the people – who are mostly rural and poor – living in the basin.

It is necessary to guide on-the-ground investments to ensure the application and scalability of sustainable land and water management (SLWM) interventions for effective soil erosion and sedimentation control in the LVB. Some SLWM practices have been implemented in selected areas in the LVB, including the Simiyu River Catchment, through the Lake Victoria Environment Management Project (LVEMP) and other projects implemented by the East Africa Community (EAC) and/or the governments of LVB countries, with financial and technical support from the World Bank and other international organizations. However, the adoption rate of SLWM interventions has remained low, and their effectiveness and impact on erosion and sedimentation control are largely unknown due to a lack of systematic monitoring and evaluation (M&E). To address these weaknesses, the study “Effectiveness of Sustainable Land and Water Interventions in Soil Erosion Control in the Lake Victoria Basin: A Case Study in Simiyu River Catchment, Tanzania” was carried out by the World Bank with the financial support of the TerrAfrica Leveraging Fund (TLF). Information from LVEMP was used in this study.

The study’s objectives are to i) assess and identify the SLWM practices effective for erosion control in the LVB, ii) design monitoring indicators for soil erosion control, and iii) share SLWM practice knowledge and experiences throughout the basin. The study emphasized the importance of measuring and monitoring the effects of erosion and sediment reduction from SLWM interventions at specific locations and under different conditions in order to better assess their effectiveness, guide SLWM practices, and ensure the effectiveness and up-scalability of future investment projects. The study adopted a case study approach and focused on the technical assessment and monitoring of soil erosion reduction from SLWM practices employed by LVEMP. Qualitative, quantitative and modelling approaches were developed. Specifically, focal group discussions, local knowledge, field observations and mapping, satellite earth observations, and modeling tools for soil and water assessment were used in selected case study areas. The report’s primary audience is practitioners pursuing catchment landscape management for soil and water conservation and erosion control. The key findings and recommendations of the study, however, should be useful to decision makers across environmental and natural resource management.

The Simiyu River is the fifth largest in terms of flow into LV, but third in total phosphorous (TP) contributions to the lake, behind the LVB’s Kagera and Nzoia Rivers. The Simiyu River Catchment, a major sub-basin of the LVB covering an area of about 11,577 km2, is located southeast of LVB in northern Tanzania. It drains from the National Park plains and the Maswa Game Reserve. The Simiyu River Catchment is important to agricultural activities and other economic activities such as fishing and livestock, and its socio-economic practices are characterized by subsistence

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farming, shifting cultivation, and extensive grazing of cattle, all of which have significant impact on the land cover or land use dynamics.

Major causes of soil degradation in the Simiyu River Catchment include expansion of agricultural land and over-grazing. The Simiyu River Catchment has experienced various degradation processes over the past decades. Despite some scattered SLWM interventions in the Basin, large areas continued to experience further gradual land degradation from 2001 to 2015 as represented by their Net Primary Productivity (NPP). Sheet erosion from agricultural land, gully formation, and riverbank erosion continue to accelerate the sediment and nutrient yield rate in the Simiyu River Catchment and consequently the load into Lake Victoria. Characteristics of the Catchment’s land use and soil erosion are summarized below. • Agriculture and bushland are the dominant land-use/cover in the Simiyu River Catchment. Agricultural land expanded significantly at the expense of bushland, grassland and woodlands, from 8.7% of the total area in 1986 to 71.4% in 2006. The bushland area has remained quasi-constant since 1996, while grassland has increased slightly since 2006. The percentage of the Catchment area is facing a very high and high soil loss risks is 16.1% and 2.2% , respectively. The land with high and very high risk is distributed mainly in the cultivated part of the Catchment. Only about 57% of the Basin is deemed at low or very low risk for soil erosion. • Micro-catchments highly affected by the expansion of agricultural land, poor sustainable land management, and thus high soil erosion, include Bukingwaminze, Kabondo, Ngudama, Nyamatembe, and Sandai. Among these, the Kabondo and Nyamatembe micro-catchments were selected for case study. • The simulated sediment yield has varied over the years, ranging from 0 to 38.83 t/ha/yr for the period 1980-2009, and 0.50 to 11.86 t/ha/yr for the period 2010-2016. The southern and eastern part of the Simiyu River Catchment, which is mainly dominated by bushland with short grasses, exports a relatively larger amount of sediment into the Simiyu River compared to the northern part of the Catchment. • The simulated sediment load in the Simiyu River Catchment has varied over the years (from 0.01 to 5.7 Mt/yr), with an average value of 1.6 Mt/yr from 1980-2009. During this period, the average annual sediment concentration, total nitrogen (TN) and total phosphorous (TP) were 288.0 mg/l, 12.0 t/day and 2.0 t/day, respectively. A variety of SLWM measures that can effectively control soil erosion already exist in the LVB, including terracing, bunding, ridging and other cross slope barrier technologies, runoff flow control measures, as well as some agronomic practices, such as crop rotation, adaptive tillage, soil fertility measures, agro-forestry measures, vegetation strips. Common SLWM practices vary from one country to another in LVB. • SLWM practices and technologies observed in the soil erosion hotspot areas of the Simiyu River Catchment include contour bunds strengthened with trees and grass, tie bunds (also called tie-ridges) combined with cut-off drains, rice bunds (Majaruba), gully plugs (also called gully plugins), woodlot conservation (Ngitiri), river- or stream-bank stabilization, natural pasture regeneration, and reforestation and bee keeping.

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• The effectiveness of four SLWM practices – contour bunds, tie bunds, gully plugs, riverbank stabilization, which are practices introduced by LVEMP in the catchment and have performance data on soil erosion, nutrient losses and runoff generation at plot level available, was evaluated using the Soil and Water Assessment Tool (SWAT). Generally, all the selected SLWM practices tended to reduce sediment loads and concentration in the Simiyu River Catchment’s hotspot micro- catchments. Tie bunds and contour bunds tend to have the highest sediment and nutrient load reduction percentage compared to other SLWM practices. Under this study, their effectiveness appears to exceed 80% in the Simiyu River Catchment’s hotspot micro-catchments. Under climate change scenarios, the effectiveness of tested SLWM practices in erosion control will vary in the projected near future. Available Climate change models (CMCC-MS and GISS-E2-H) showed that on average a 7.75% increase in rainfall is expected over the Simiyu River Catchment for the ensemble of the General Circulation Model (GCM) under the Representative Concentration Pathway (RCP) 8.5 from 2010 to 2039. TP and TN loads in the near future and under the RCP 8.5 are likely to be lower than the corresponding values for the period from 1980-2009. Contour bunds and tie bunds are likely to be the most effective SLWM practices in the study area. Based on the analytical results and findings of this study, key recommendations around institutional and capacity building, technical effectiveness, and M&E are summarized below.

Integrating SLWM into land management planning and programing. SLWM is an integral part of the catchment development and its expected results cannot be achieved independently. Therefore, it is necessary to assist regional and local governments in developing and implementing integrated land use plans and catchment management programs that adopt SLWM practices within and across districts in the LVB. SLWM activities need to be linked with other sectoral programs. Such linkages will help seek synergy and achieve multiple results, thus leading towards socio-economic and environmental sustainability.

Using landscape management approach to strengthen SLWM and governance. To scale up and ensure the effectiveness of SLWM practices, a broader landscape management approach should be adopted to help address erosion control in a comprehensive way in an entire catchment, from its hilltops to lowest reach areas, and engage all relevant stakeholders.

Sensitizing, empowering and capacitating communities for adopting SLWM technologies. It is important to continue to sensitize farmers to the use of SLWM technologies and practices. This can be done through the training of experienced local residents as SLWM trainers, piloting and establishing demonstrations, and organizing farmer field schools. The implementation capacity of local communities and local organizations such as the Catchment Management Committee should be strengthened so they will be able to actively and effectively promote SLWM technologies.

Cross-learning and disseminating SLWM experience and knowledge. Learning and disseminating the knowledge and experience gleaned from existing programs will help

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enhance farmers’ specific SLWM skills and raise a community’s SLWM adoption rate. It is useful to organize learning and knowledge sharing events, including well-targeted field visits, so that officials, practitioners, and farmers learn about positive experiences in neighboring communities, across the basin and even from other basins that have had successes.

Promoting contour bunds and tie-bunds. Contour bunds and tie-bunds are very effective at controlling sediment and nutrient losses on agricultural land, and therefore improving land quality and fertility and increasing crop productivity. There is a need to raise awareness of such good farming and SLWM practices and provide technical support for their implementation.

Promoting riverbank stabilization and gully protection measures to reduce sedimentation. Riverbank stabilization and gully control technologies are recommended for controlling sediment transportation in catchments and reducing sedimentation and nutrient runoff into Lake Victoria. Establishing a water buffer zone along main rivers is required by law in all LVB countries. The buffer zone will help implement riverbank stabilization techniques and enhance their effectiveness at reducing soil erosion and sedimentation. However, the enforcement and sustainability of the buffer zones, including the need for and methods of providing alternative livelihoods to farmers whose life traditionally depending on the zones, are an issue of attention.

A well-developed M&E system is fundamental to SLWM operations. The impacts of SLWM on changes in erosion and ecosystem services are key elements to be measured and monitored. SLWM measures are human responses to land degradation caused by various driving forces that will undermine the functions and services of land and ecosystems. The DPSIR framework is helpful to systematically and holistically understand the linkages among driving forces, effects of degradation, and human responses, and to guide the design of M&E and selection of indicators. Built on the DPSIR framework, a set of indicators was proposed to measure the drivers, pressures, state, impacts and responses related to a land ecosystem. M&E design also needs to be scale- and time-sensitive, as SLWM technologies are normally employed at different scales with impacts and results spanning different time frames, which may go far beyond a project’s implementation period. In addition, indicators should link to the costs and benefits of individual farmers and local communities for better economic evaluations and sustainability assessments. Coordination and consultation of stakeholders at all levels is key to identifying M&E approaches and indicators better suited to project-specific needs.

Project development objective or result level indicators of SLWM projects include: land area where SLWM practices have been adopted, number of land users adopting SLWM practices, number of beneficiaries (% female) directly benefiting from SLWM interventions, changes in crop yields of major crops, and reduction in soil erosion and sediment yield. The first two are recommended as core sectoral indicators by the World Bank for its land management investment operations. Other indicators to monitor project progress or intermediate outcomes can be decreased surface runoff, color of the surface runoff, increased soil organic matter, improvement in soil structure and water holding capacity, increased infiltration rate, etc. A specific SLWM or landscape

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management project will adopt its indicators based on the project’s specific objectives and characteristics.

Bottom-up and top-down monitoring approaches will be employed integratively for measuring and monitoring the impacts of SLWM practices in a cost-effective way. For instance, top-down remote sensing data should be shared with local stakeholders and compared to bottom-up evidence locally gathered on the ground. In this way, the results of local efforts do not go unnoticed at higher levels and, similarly, higher level stakeholders, especially those engaged in monitoring or decision making, will get a level of contextual understanding of their results and validity on the ground that is otherwise impossible to achieve exclusively through top-down approaches. Doing this could further strengthen stakeholder engagement and participation in M&E.

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CHAPTER 1. INTRODUCTION Land degradation is a major environmental issue that affects rural livelihoods and the well-being of inhabitants by substantially impacting the sustainability of food production and other ecosystem services as well as rural infrastructures that are essential to the prosperity of these communities. Land degradation refers to the human- induced reduction or loss of the biological or economic productivity and complexity of land, which is most often attributed to poor land management practices and unsustainable land use. Land degradation consists of a multitude of processes including deforestation, soil erosion, and increased sedimentation, among others. These processes interact in concert to cause severe environmental impacts such as the reduction of biomass and biodiversity, nutrient depletion of soils, loss of organic matter in soil, reduction in soil structure and quality, and destruction of rural infrastructure such as roads or dams, to name a few. The effects of land degradation, both onsite and offsite, are widespread and linked. The onsite consequences include loss of productivity, reductions in resilience leading to higher variability in yields and vulnerability to extreme weather conditions, and a reduction in the capacity to adapt to climate change while the off-site consequences are global or regional, such as increased carbon emissions and poor water regulation, resulting in floods, sedimentation and reduced base flow downstream. Soil erosion is a natural phenomenon which has been accelerated due to anthropogenic factors. It reduces crop productivity by limiting water infiltration and loss of nutrients (Pimentel, 2006). Globally, this has made a big portion of arable land unproductive, particularly in Sub-Saharan Africa (SSA), where the majority of the rural population is dependent on rain-fed agriculture (Kendall & Pimentel, 1994). If soil erosion remains unchecked and the demographic pressure continues to rise, the majority of rural people in SSA will not be able to feed themselves (Nearing, 2013). This has already happened in some areas of Africa that are facing food shortages due to soil erosion and deterioration. The Lake Victoria Basin (LVB) is an important transboundary natural resource asset which is jointly shared by five countries - Burundi, , Rwanda, Tanzania and Uganda. This region is an important agricultural area of East Africa. High environmental pressure from a growing population, and their demand for food and energy, has caused land-use changes over decades, particularly by expanding agricultural areas that have encroached on previously undisturbed land and the widespread deforestation in many of the LVB’s catchments. The pressure has also made a shift in the region’s agricultural practices from traditional mixed perennial agriculture to more intensified cropping with little attention to soil and water conservation. Poor land and water management related to unsustainable agriculture and deforestation in the catchments has led to accelerated erosion and resulted in the loss of soil and nutrients, desertification, and sedimentation of water bodies. The decade-long Lake Victoria Environment Management Project (LVEMP Phase I and II) is one example of the efforts to help address land degradation in the region. The project was jointly implemented by the East Africa Community (EAC) through its regional institution the Lake Victoria Basin Commission (LVBC) and five LVB

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countries and financed by the World Bank. Despite the efforts of LVEMP and other environmental management initiatives, the LVB continues to face environmental challenges and land and water resources in particular are at risk of further deterioration. In addition to external pressure such as a growing population and its demand for agricultural land, a low adoption rate of SLWM interventions is another reason there has been little success in stopping the trend of land degradation in the basin. The low rate is due to the financial constraints, low awareness, lack of know-how and skills, and a weak capacity for promoting and scaling up sustainable land use or landscape approaches that many rural communities in the basin face. The effectiveness of SLWM practices on erosion and sedimentation control is important but largely unmeasured and unknown due to a lack of systematic monitoring and evaluation (M&E). Therefore, future ENRM projects need to improve the monitoring and effectiveness of soil erosion and sediment reduction while scaling up the SLWM and livelihood supports in priority LVB catchments. This study aimed to i) assess and identify SLWM practices effective for erosion control in the LVB; ii) design monitoring indicators for soil erosion control; and iii) share the knowledge and experiences of SLWM practices over the basin. It emphasized the importance of measuring and monitoring the erosion and sediment reduction effects of SLWM interventions at specific locations and conditions in order to better assess their effectiveness, guide SLWM practices, and ensure the effectiveness and up-scalability of future investment projects. The report’s primary audience is the practitioners pursuing catchment landscape management for soil erosion control. The study’s key findings and recommendations, however, should be useful to policy makers in the area of environmental and natural resource management. Identification of sediment and nutrient load hotspot areas, use of robust hydrological modelling, adoption of efficient and cost-effective technologies and practices to control soil erosion and nutrient export into the lake, as well as stakeholder consultations, are key for sustainable land management in the LVB. This study adopted a case study approach and focused on the technical assessment and monitoring of soil erosion reduction of the SLWM practices employed by LVEMP. Qualitative, quantitative and modelling approaches were developed. Specifically used in the selected case study area were focal group discussions, mining local knowledge, field observations and mapping, satellite earth observations, and modeling tools for soil and water assessment. Despite the importance of institutional arrangements and cost-effectiveness in implementing SLWM practices, they were not the emphasis of the technical study. The study employed a nested case study approach to connect the realities across scales and allow for an in-depth analysis. The Simiyu catchment, which is considered to be one of the main contributors to the deterioration of water quality in Lake Victoria, was selected as a case study area. The catchment is relatively large and coupled with expanding agricultural activities that involve the use of agrochemicals, such as fertilizers, herbicides, and pesticides(Ningu, 2000) with high yields of sediment (Lugomela and Machiwa, 2002). A literature review was conducted on various SLWM practices used around the world and in the LVB, with specific focus on soil erosion and sedimentation control in rural

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areas with high agricultural activity using both the WOCAT (World Overview of Conservation Approaches and Technologies) database and stakeholder consultations. A case study approach was selected focusing on two pilot micro-catchments within the Simiyu catchment. Their erosion features were mapped and vegetation degradation was assessed using remote sensing data. Soil erosion hotspots were identified using various ArcGIS tools and techniques. SLWM practices were selected using experimental data based on site-specific parameters, and their respective efficiencies were evaluated using different modelling approaches. Finally, monitoring indicators were identified with the help of specialist consultations in addition to the methods highlighted in existing state of the art monitoring and evaluation (M&E) frameworks, approaches and tools.

After the introductory chapter, Chapter 2 presents an overview of soil erosion, land degradation and SLWM practices in the LVB. Chapter 3 first introduces the case study area – the Simiyu catchment and its constituencies – and then the methodology used. Key findings and results regarding the effectiveness of the various SLWM practices are discussed in Chapter 4. Chapter 5 presents monitoring and evaluation frameworks and soil erosion indicators. Chapter 6 summarizes the recommendations resulting from the case study.

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CHAPTER 2. OVERVIEW OF LAND DEGRADATION AND SLWM PRACTICES IN LVB

Land degradation in the Lake Victoria Basin has caused soil erosion, nutrient runoff, and sediment and contributed to the Lake’s water pollution and eutrophication problems. Various SLWM practices exist in the basin with some introduced through environmental and natural resource management projects such as LVEMP. This Chapter provides an overview of land degradation and SLWM efforts in the basin.

2.1 Land Degradation Problems in the LVB

Land degradation is the result of a broad range of drivers traversing scales and factors, which include biophysical, climatic, demographic and socio-economic drivers, and major drivers are population growth, economic development and land use policy changes (Odada et al., 2009; Thenya et al., 2001 & 2006). In the LVB, the extent of land degradation varies from one country to another. According to Ochola (2006), the absolute extent of land degradation is highest in Tanzania, with soil erosion by water being the dominant land degradation process in the basin followed by vegetation degradation. One main land degradation process found throughout the LVB is land use and cover change (LUCC). LUCC exists primarily in the forms of deforestation and vegetation degradation which are attributed mainly to human activities and occur in the LVB at alarming rates. Wasige (2013) found that the Kagera basin in the Lake Victoria ecosystem had the highest rate of LUCC in the whole of Sub-Saharan Africa. The same study found that from 1901 to 2010 farmland grew 60% at the expense of dense forests (which were reduced from 7% to 2.6%), woodland (from 51% to 6.9%) and savannas (35% to 19.6%). Similar patterns have been reported in other parts of the basin (Mati at al., 2005; Muhati et al., 2008; Maitima et al., 2010; Mango et al., 2011; Waiswa et al., 2011; Kimwaga et al., 2012; Berakhi, 2013; Masanja, 2013; Musamba et al., 2011; Kizza et al., 2017; Kiggundu et al., 2018).

Deforestation has been the result of several factors including weak policy (Thenya et al., 2001 & 2006; Galabuzi et al., 2015) and increased population growth (Odada et al., 2009), which have resulted in large agricultural expansions. Most seasonal wetlands in Uganda have been converted to rice fields and those near urban areas have been allocated to factories, resulting in an increased export of nutrients into water bodies (Mugisha et al., 2007; Pomeroy et al., 2017). Nutrient stocks in soil oscillate near equilibrium with limited fluctuations. When the soil is disturbed, for example in cultivated land, the soil nutrient stock is affected by excessive nutrient losses through leaching, volatilization, soil erosion and crop harvests (Bekunda & Manzi, 2003). To compensate, large quantities of synthetic fertilizer are added to depleted soils. Sediment and nutrient export is one of the major problems affecting water quality in Lake Victoria and its ecosystem over the past two decades (Molina, 2009; van Griensven et al., 2013).

Lake Victoria’s water quality has been declining due to both point and non-point pollution sources from agricultural, domestic and industrial activities (Rwetabula et al., 2007). Tanzanian river basins polluting Lake Victoria are mainly Kagera, Mara, and Simiyu (Crul, 1995). Additionally, salinization, the process by which water-soluble salts accumulate in the soil, is a concern in LVB soils because excess salts hinder crops’ ability to take up water. The rate of salinization in the LVB is currently expected to be

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low and localized. Where it occurs, it results from land degradation caused by mining, e.g., of gold (Sida, 2004), poor disposal of urban wastes (Shayo et al., 2011), point and non-point pollution from industries, and agricultural activities (Odada et al., 2006; Oguttu et al., 2008).

The elevated LUCC in the LVB has caused increased degradation in the form of soil erosion which has led to sediments, the export of nutrients, loss of soil organic matter and increased salinity in the soil. Soil erosion is one of the most important land degradation processes, especially in areas with high rainfall intensities and vulnerable soils, such as the LVB. The magnitude of soil erosion in the LVB varies from one location to another depending on soil type, land use/cover, topography and management. Several researchers have demonstrated that soil loss is highest on cropland, intermediate on rangeland and lowest under forest (Mati et al., 2000; Lufaafa et al., 2002; Angina et al., 2003; Omuto, 2008; Erdogan et al., 2011; Defersha et al., 2012; Kizza et al., 2013; Majaliwa et al., 2015; Karamage et al., 2017). Soil loss ranges of 0.01 to 0.9 t/ha/yr were observed in the forests of Uganda and Kenya (Mati, 2000; Kizza et al., 2013). A relatively higher than expected value of 3 to 16 t/ha/yr was estimated for forestland in the (Defersha et al., 2012). A study by De Meyer et al. (2011) in selected villages within the LVB observed that compounds, landing sites, footpaths and unpaved roads that occupy a small portion of their study area (2.2%), also contributed significantly to the sediment influx into Lake Victoria (Mnyanga et al., 2004). In Tanzania, Kagera and Simiyu catchments lead in terms of total sediment and nutrient loads into Lake Victoria. According to Kimwaga et al. (2012) Simiyu catchment exported about 0.0985 Mt/yr of sediments into Lake Victoria in 2006.

2.2 SLWM practices in LVB

Studies have shown that various SLWM practices have been applied to achieve improved yields and control land degradation in the LVB (Critchley et al.,1999; Reij and Waters-Bayer 2001; Bittar 2001; Abbay et al. 2000; Hatibu and Mahoo 2000; Majaliwa et al., 2015; FAO, 2017). These have involved a wide diversity of interventions, ranging from integrated soil fertility management, soil and water conservation, rainwater and runoff harvesting systems, tillage and soil management systems, and miscellaneous innovative agronomic practices (Mati, 2005). Common SLWM practices vary from one country to another in the LVB. However, the more common SLWM practices include: terracing, vegetative barriers, conservation tillage, runoff harvesting, diversion of surface runoff from rocky areas, pitting systems, bunded basins and ridging including contour bunds and tie- bunds or ridge (McCall 1994; Reij et al. 1996; Hatibu and Mahoo 2000; Thomas 1997; Critchley at al. 1994; Mutunga et al., 2001). The WOCAT database currently contains 129 SLWM technologies reported for the five LVB countries. Many of the interventions returned positive potential impacts in terms of water availability and erosion control, which were estimated based on positive assumptions.

However, the overview of these projects had limited means of assessing the potential operational costs and socio-economic impacts of these interventions, making their evaluations challenging. A study conducted by Giger et al. (2015) showed that in general SLWM technologies that involve structural measures to address erosion or modifying path of water (e.g. terracing, bunding, dam building, walls and palisades,

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runoff channels) had significantly higher establishing costs which range from less than US$ 20 to over US$ 5000 per hectare. Variation among maintenance costs was also quite high due to the variety of SLM measures and their respective needs for upkeep. Overall, the adoption of SLWM though picking up has remained quite low in the region. There is a need to reach as many farmers as possible, and thereby enhance agricultural development in the region.

Many of the previously implemented interventions required consistent maintenance to ensure their continued effectiveness. Grazing management interventions, for example, in Tanzania and Uganda highlighted the elevated efficiency of regenerating grasslands through reseeding, which carries a higher cost than simply implementing controlled access guidelines. The Transboundary Agro-ecosystem Management Project for the Kagera River Basin (TAMP Kagera) project in 2012 found that the average cost to establish one hectare of the technology is US$122 while the maintenance of one hectare is US$42. Hay making is considered to be a supportive practice that improves the effectiveness of the main technology. Similarly, agronomic measures taken, such as temporal crop substitution and the use of SLWM, and recommended crop husbandry to control BXW disease using tie bunds and cover crops, had a maintenance cost (US$234) of almost half of the original implementation cost (US$561) per hectare. Cross-slope barriers, water-harvesting, and agro-forestry measures all have maintenance costs, and thus need to quantify their positive results/benefits in order evaluate cost-benefit ratios. Additionally, local stakeholder engagement was identified as the key driver of success among these interventions as their participation in maintenance and respecting bylaws among other actions is essential for ensuring effectiveness. Vegetative strips required restricting access of grazing livestock to allow for the plants to establish permanent holds in riparian and other high-erosion zones. The World Bank has a long history in financing sustainable land management in Africa and elsewhere around the world. LVEMP is a major one in LVB and some SLWM practices of the project will be discussed in the rest of the report. Ethiopia Sustainable Land Management, and China Loess Plateau Rehabilitation Project, and Rwanda Land Husbandry Project are other examples. In Ethiopia, relevant practices include erosion control and water retention physical structures, generally combined with biological measures, degraded hillside rehabilitation through community-enforced area closures such as ban on grazing of community livestock, forest enrichment, and communal pastureland improvement. In China’s Loess Plateau, terracing, bank land protection/development, sediment control dams and gully control structures, and afforestration and vegetative cover were adopted. They have helped control soil erosion and reduce sediments in river systems. However, there was no on-site monitoring conducted to directly evaluate the effectiveness of specific SLWM practices in soil erosion control. Rwanda Land Husbandry Project implemented sustainable land management practices, mostly radical terracing, as one of its key investment activities. For assessing the change in sedimentation before and after interventions, the project constructed four stream gauge stations, each of which had sensors to collect sediment samples, recording water levels and rainfall on a daily basis. Additionally, the project used the Revised Universal Soil Loss Equation (RUSLE) with GIS and remote sensing data to estimate soil loss from a hillslope caused by raindrop impact and overland flow

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plus rill erosion. The methods indicated significant reduction of soil erosion impacts in treated sites.

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CHAPTER 3. INTRODUCTION TO CASE STUDY AREA AND METHODOLOGY

To assess the effectiveness of SLWM practices in erosion and sediment reduction, a case study approach was used. The Simiyu River Catchment was selected as it is one of the LVEMP project areas and the Simiyu River is one of the major rivers entering Lake Victoria as well as a main contributor to sediments and nutrients in the Lake. This chapter discusses the case study area and presents the methodology applied by the study.

3.1 Description of the case study area

The Simiyu River catchment is located in the southeastern part of LVB in Tanzania. The river is the second largest in Tanzania, after the Kagera River, and the fifth largest in the LVB. Its drainage area is about 11,039 km2 and it flows directly into Lake Victoria. The Simiyu catchment contributes large sediment and nutrient loadings into the LVB as it ranks the third in total phosphorous (TP) contribution to the Lake (Rwetabula et al., 2007; 2012; Ndomba and van Griensven, 2011).

Topography The Simiyu catchment is generally flat with small undulating hills that have an average slope of 1.4% (Rwetabula et al., 2007). The elevation in the catchment ranges between 1100 m and 2000 m (Figure 1).

Figure 1. Topography map of the Simiyu River Catchment, Tanzania

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Soils The catchment’s soils consist of 62.8% planosols (dominantly sandy loam), and a mixture of cambisols (12.9%), solonetz (11.5%), andosols (5%), vertisols (4.9%), and leptosols (2.9%) (Rwetabula et al., 2007).

(Source: FAO, 2002; Rwetabula et al., 2007) Figure 2. Soil Map of the Simiyu River Catchment, Tanzania

Land use/cover The Simiyu River Catchment is dominated mainly by agricultural land use, grassland for grazing and bushland (Figure 3). The south-eastern part is covered by the Serengeti game reserve. Due to rainfall uncertainties, most cropping systems practiced in the area are either staggered planting or intercropping and flat cropping systems (Meertens and Lupeja, 1996). Communal grazing is the most practiced livestock management system in the Catchment.

The main land use/land cover of the Simiyu catchment consists of mixed bare land and short grasses, dense and tall grassland, bushland, cultivated land and medium size grassland (Rwetabula and Smedt, 2005). Agricultural land expanded significantly from 19.33% in 1975 to 73.44% in 2006 (Kimwaga et al., 2012).

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Source: Rwetabula and De Smedt, 2005 Figure 3. Land use/cover of Simiyu River Catchment

Climate The Simiyu River Catchment has a warm tropical savannah climate with distinctive wet and dry seasons (Ndomba and van Griensven, 2011; Rwetabula et al., 2004; Rwetabula et al., 2007). The short rains appear mainly from November to January, and long rains from March to May, resulting in a total average annual precipitation of 700 to 1000 mm (Ndomba and van Griensven, 2011). The total annual potential evapotranspiration of the catchment is about 1300 mm (FAO, 1997) while the average monthly potential evapotranspiration in the catchment ranges from about 80 mm in the short rain season to 140 mm in the dry season. Figure 4 shows the monthly variation of rainfall, potential evapotranspiration and average monthly discharge at the catchment’s outlet (Rwetabula et al., 2004).

Aug

Source: Rwetabula et al., 2004 g Figure 4. Variation of average monthly rainfall, potential evapotranspiration, and discharge at the outlet of the Simiyu River (1999–2004)

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Sediment yield and nutrient loads Various and contradicting estimates of sediment transport/export have been made by different authors in the Simiyu catchment. Myanza et al. (2005) found that the Simiyu River and western shore streams have a sediment yield ranging from 57.35 to 179.25 ton/km²/yr. A study carried out by Kimwaga et al. (2012), comparing the relative impact of land use/cover change between 1975 and 2006 on sediment loading into the Lake Victoria, indicating an increase in sediment yield in the catchment. A sediment yield of about 54t/km2/yr was estimated for an estimated sediment load of 2.07 Gt/yr. Using two different models to determine erosion in the Simiyu catchment, van Griensven et al. (2013) found similar computed total sediment export at the river outlet (2.94 Mt/yr for the SWAT model and 2.72 Mt/yr for SOBEK-RE model).

Considerable amounts of nutrients are lost in the catchment through sediment export, particularly phosphorus (Nsubuga and Orach-Meza, 2005; Alemayehu et al., 2014; Ryken et al., 2014; Turyahabwe et al., 2013). Tamatamah (2010) estimated that about 28.65 tons of Soluble Reactive Phosphorus (SRP) were released into Lake Victoria from the Simiyu catchment in 2000. This makes the catchment one of the largest exporters of SRP into Lake Victoria, after the Kagera catchment (Tamatamah, 2010; Ndomba and Griesven, 2011; Rwetabula, 2012). The use of inorganic fertilizer remains limited, and nutrients are managed predominantly through the recycling of household wastes, manure and organic matter (Bekunda & Manzi, 2003).

3.2 Methodology used in the case study

Identification of effective SLWM practices applicable to the LVB A literature review was made of different categories of SLWM practices globally, with particular reference to rural areas and soil erosion control. Rather than giving a global overview of all soil erosion control measures, the focus was placed on best management practices (BMPs). Here BMPs are considered to be those practices that i) are effective in controlling soil erosion or sediment delivery; ii) can be efficiently implemented by land users and their institutional counterparts (i.e., achieve relatively high cost- effectiveness); and iii) lead to beneficial effects on the livelihoods of land users and downstream communities, either in terms of augmented production or reduced losses.

The literature review was complemented with a review of SLWM technologies adopted in the LVB countries (Burundi, Kenya, Rwanda, Tanzania and Uganda) and documented in the WOCAT (World Overview of Conservation Approaches and Technologies) database. Furthermore, during the fieldwork in the Simiyu River Catchment from February to March 2018, transect walks and consultative meetings were conducted to identify the existing SLWM in the pre-identified erosion-prone micro-catchments of the catchment. The practices and technologies used in these micro- catchments and their utilization were reviewed using the WOCAT methodology.

Assessment of land degradation in the Simiyu River Catchment Mapping of erosion features: Large permanent gullies in the pilot micro-catchments were mapped based on field observations and satellite imagery. Seven large permanent gully erosion features were geo-referenced during fieldwork and overlaid on Sentinel 2 images of the study area to identify key features for their mapping.

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Assessment of vegetation degradation: The land degradation hotspot assessment was based on the cloud-based Trends.Earth tool available from http://trends.earth/docs/en/. Trends.Earth is a recent platform for monitoring land change using an innovative desktop and cloud-based system. The Trends.Earth tool uses the NDVI as a surrogate estimator of Net Primary Productivity (NPP). Three periods were considered in Trends.Earth analysis, namely 2001-2006; 2007-2012; and 2013-2015. The first and last periods cover the first and the second phase of implementation of the Lake Victoria Environmental Management Project (LVEMP). The second period is a transitional one between the two LVEMP phases. The average NPP for each period was compared to that of the previous one. For the first period, the initial two years were taken as the reference period for the comparison period 2003-2006. An additional comparison scenario was done between 2001-2006 and 2013-2015. MODIS (250 m resolution) images were used in this study.

Three parameters are computed in Trends.Earth namely the state, trajectory and trend. The state is measured by the difference in NDVI for a given period compared to the baseline. It is clustered into improved (increase NDVI/NPP), stable (no change in NDVI/NPP) and degraded (reduced NDVI/NPP). Trajectory measures the rate of change in primary productivity over time. It is computed in a linear regression at the pixel level. A Mann-Kendall non-parametric significance test is then applied, considering only significant changes or those that show a p-value ≤ 0.05 and p<0.01 Those with no significant trend (p>0.05) were categorized as stable. Positive significant trends in NDVI would indicate potential improvement in the land’s condition, and negative significant trends indicate potential degradation.

Soil erosion hotspots: Soil erosion hotspots were identified using two approaches: i) a 400-m pixel-based RUSLE model developed using ArcGIS and ii) the ArcGIS based hydrological model - ArcSWAT. (i) Pixel-based RUSLE model

The RUSLE model has been validated in several parts of East Africa (Lufafa et al., 2003; Claessens et al., 2008). The RUSLE soil loss equation is written as follows:

Soil loss = R•K•LS•C•P (1) Where: R = Rainfall erosivity [MJ mm ha−1 h−1per year] K = Soil erodibility [Mg h MJ−1 mm−1] LS = Slope length and slope steepness factor C = Cover factor P = Management practice factor, and soil loss is expressed in Mg ha-1 per year.

The RUSLE was used to estimate the potential soil erosion risk. Soil erosion risk was classified using a slightly modified Singh et al. (1992) classification to account for the fact that Simiyu River Catchment is a generally flat area, as shown in Table 1. The classification includes five risk levels. The very high risk is defined as an annual soil erosion rate larger than 20 ton per hectare while the very low risk is below 2 tons per hectare.

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Table 1. Classification of soil erosion risk. Level of soil erosion risk Soil loss (t/ha/yr) Very low 2 Low 2 – 5 Moderate 5 – 10 High 10 - 20 Very high >20

(ii) Hydrological modelling

Simiyu catchment sediment load and yield into the Lake Victoria were assessed using the ArcSWAT model. For input the ArcSWAT model uses a Digital Elevation Model (DEM), land use/cover, soils, and climate data (Arnold et al., 1998; see Table 2 for an overview of input data used). A 30-m resolution DEM (http://geoportal.rcmrd.org/) was used for catchment delineation and subsequent modelling. The land use/cover map was generated by analyzing the 2016 Landsat image (https://gisgeography.com) using both unsupervised and supervised classifications. Five broad classes were used during the classification including forest, grassland, bushland, agricultural land and wetland. The Soil and Terrain Database (SOTER, https://www.isric.online/progres/soil-and- terrain-soter-database-programme) was used for soil data. Climate and discharge data for the period of 1979-2014 were obtained from the Lake Victoria Basin Water Board (LVBWB). To populate the climate data for the period with missing data, gap filling techniques using the quality assured data from the Nile Basin datasets were used.

Within the Simiyu catchment, two highly erosion prone micro-catchments were selected for detailed studies based on: (i) their human-nature interaction (agriculture, water use, forestry and nature conservation); (ii) the dominant land degradation process (soil erosion, vegetation degradation); and (iii) the level of SLWM use. A spatio- temporal trend in land use/cover was determined after analyzing a series of Landsat images covering the two micro-catchments for the year 1986, 1996, 2006 and the previously analyzed 2016 images. These images were downloaded from https://gisgeography.com. Table 2 summarizes the type of data used, their sources and resolutions.

Table 2. Data used in the SWAT model, sources and their resolutions Data type No of Data availability Source Spatial Temporal datasets resolution resolution Climate 4 stations 2013-2018 MoWI/LVBWB Daily (Maswa, 1969-2018 NBI/ Sagata, 1977-2018 AgMERRA Kisesa, Magu) 1971-2011 Discharge 1 1979-1996 and MoWI/LVBWB Daily 2006-2014 DEM 1 2010 USGS1 30 m Land 6 images 1986, 1996, 2006, Landsat2 30 m 4 time use/cover 2016 series Soil 1 2010 SOTER3 10 km 1 Downloaded from: http://geoportal.rcmrd.org/ 2 Downloaded from: https://gisgeography.com 3 Downloaded from: https://www.isric.online/progres/soil-and-terrain-soter-database-programme

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Assessment of the effectiveness of SLWM technologies in Simiyu River Catchment (i) Parameterization of the SLWM technologies for effectiveness assessment

The ArcSWAT model was used to assess the effectiveness of selected SLWM technologies or practices by evaluating the changes in water flow and water quality parameters including Total Suspended Solids (TSS), Total Nitrogen (TN) and Total Phosphorus (TP). These SLWM were represented in the pre- and post-conditions by modifying one or more channel parameters such as the channel cover factor (CH_COV), channel erodibility factor (CH_EROD), and the Manning’s n value for the main channel. Land management parameters included the curve number (CN2), management practice factor (USLE_P), the average slope length (SLSUBBSN) and the USLE cover factor (USLE_C) (Chow, 1959; Hurni,1985;Herweg and Ludi, 1995; Brancmort et al., 2003; Srinivasan, 2008;Tuppa and Kunnan, 2010 ). USLE-P values, defined as the treatment mean annual soil loss over the control annual soil loss, were computed based on LVEMP field experiment data (Majaliwa et al., 2015).

SLWM practices were selected and evaluated based on their application in the catchment and the availability of their performance data on soil erosion, nutrient losses and runoff generation at plot level since ArcSWAT parameters are site-specific and should reflect the reality of the study area. The selected SLWM practices were (i) contour bunds, (ii) tie-bunds, (iii) gully plugs, and (iv) riverbank stabilization. Each of these SLWM practices has a different effect on flow and sediment variables and is represented by distinct parameter(s) in the ArcSWAT model (Table 3).

The ArcSWAT model was run for two periods 1980-2009 and 2010-2016 without and with selected SLWM practices. The Effectiveness was calculated as percent reduction from the baseline conditions as follows:

Effectiveness i (%) = (postSLWMi - preSLWMi) X 100/preSLWMi) (2)

Where PostSLWMi was the simulated quantity (where i can be load, concentration or flow) with implementation of the SLWM and PreSLWMi the simulated quantity (where i can be load, concentration or flow) without the implementation of the SLWM. Additionally, a paired t-test was conducted to check for significance of the difference between Pre-SLWM and Post-SLWM effectiveness values.

(ii) Effectiveness of selected SLWM practices under climate change conditions

The effectiveness of each SLWM was computed as a relative change of a given parameter with and without climate change conditions assuming that all the other conditions remained constant (soil, land use/cover, management and topography). Only near-future (2010-2039) climatic projections were considered in this study and the 1980-2009 period was taken as a reference period (baseline). The near-future climate scenario of precipitation and temperatures was generated from 29 GCMs using the procedures described in the Guide for Running AgMIP Climate Scenario Generation Tools with R (Hudson and Ruane, 2013). These GCMs were sourced from the Coupled Model Intercomparison Project 5 (CMIP5). The Simple Delta Method was used for statistical downscaling of the GCMs since it preserves the historical patterns of the

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gridded observations (Hamlet et al. 2010). The near-future climate scenarios were analyzed for two Representative Concentration Pathways (RCPs) greenhouse gas (GHG) emission scenarios: RCP 4.5 and RCP 8.5. Although the RCP 4.5 was considered as the most realistic scenario, this study also considers a catastrophic scenario (RCP 8.5) representing high GHG concentration levels (Chaturvedi et al. 2012) to test the effectiveness of the SLWM technologies under extreme conditions. Development of monitoring indicators for soil erosion control Monitoring indicators for soil erosion control were developed after consultation with SLWM specialists in Uganda and Tanzania and the review of existing state of the art monitoring and evaluation (M&E) frameworks, approaches and tools. A systematic framework was developed with M&E activities at multiple levels and involving multiple stakeholders. Indicators include the direct effects of SLWM in terms of water quantity and quality (sediment and nutrient load and yield) associated with the establishment of the SLWM. These indicators are supplemented with field-based M&E indicators that can most effectively reflect the efficacy and effectiveness of the SLWM interventions in soil erosion control.

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Table 3. Model parameters used to represent pre-SLWM and Post SLWM conditions SLWM Target and purpose Parameter Description Pre- Post Reference technology name SLWM SLWM Contour bunds Agricultural land in Simiyu SLSUBBSN (0- USLE equation slope length factor. Represents the distance where 91 20 Hurni (1985) and Herweg catchment 10%) sheet flow is the dominant surface runoff flow process. and Ludi (1995) CN2 (mgt): Initial SCS runoff curve number for moisture condition II. Curve 73 Reduced by SCS Engineering Division Reduce overland flow and conduct number is an empirical parameter used for predicting direct runoff or 5 (1986) runoff to a safe outlet. infiltration from excess rainfall Reduce sheet erosion USLE_P (mgt) USLE equation support practice factor. It is the ratio of soil loss with 1 0.47 Riverbank stabilization a specific support SLWM to the corresponding loss without support practices Tie bunds Agricultural land in Simiyu SLSUBBSN (0- USLE equation slope length factor 91 10 Main River (3rd order and catchment 10%) plus)

Reduce overland flow and conduct CN2 (mgt) A: Initial SCS runoff curve number for moisture condition II. 55 Reduced by runoff to a safe outlet. 5 Reduce sheet erosion USLE_P (mgt) USLE equation support practice factor 1 0.30 Reduced sediment load in stream and channel capacity Porous gully In tributary channels in sub-basin CH_N(1) Manning’s “n” value for the tributary channels. It represents a degree 0.014 0.05 Riverbank stabilization plugs with slope >5%. of resistance/obstruction to the flow Reduce ephemeral gully erosion / Reduce flow velocity / Trap sediment Riverbank Main River (3rd order and plus) CH_N(2) Manning’s “n” value for the main channels. It represents a degree of 0.014 0.03 Chow (1959) stabilization Reduced sediment load in stream resistance/obstruction to the flow and channel capacity CH_S2 Average slope of main channel along the channel length. The lower 0.00361 Reduced by Brancmort et al. (2003) the slope, the lower the sediment in suspension in water. 75% CH_N(1) Manning’s “n” value for the tributary channels. It represents a degree 0.014 0.05 Chow (1959) of resistance/obstruction to the flow Srinivasan (2008)

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CHAPTER 4. LAND DEGRADATION AND EFFECTIVENESS OF SLWM–CASE STUDY FINDINGS This chapter presents findings from the case study. First, the case study applied various modeling and analytic approaches to assess soil erosion risks across the catchment, identified erosion hotspots, then it simulated the effectiveness of selected SLWM technologies in erosion control in two selected hotspot micro-catchments. The study showed that a few technologies introduced in the Simiyu River Catchment were effective at reducing soil erosion and/or sediment in LVB.

4.1 Characterization of land degradation in the Simiyu River Catchment Land use/cover in the Simiyu River Catchment and its temporal trends The land use/cover of the year 2016 in Simiyu is presented in Figure 5 and the coverage of each land use changes over the years from 1986 to 2016 are presented in Table 4. Four types of land use/cover, namely, agricultural, bushland, grassland, and wetlands, were identified in Simiyu River Catchment. Agricultural land is the dominant land use/cover in the catchment, covering 68.43% of the totoal land, followed by bushland and grassland, accounting for 23.74%, and 7.56%, respectively, while wetland occupies the smallest (0.27%) portion.

Figure 5. Land use/cover in Simiyu River Catchment (2016)

Table 4. Land use/cover change in the Simiyu catchment (1986-2016) Land use/cover 1986 1996 2006 2016 % Area % Area % Area % Area (km2) (km2) (km2) (km2)

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Agriculture 961.07 8.71 5408.91 49.0 7880.59 71.39 7554.4 68.43 Bushland 3327.82 30.14 2447.00 22.2 2600.84 23.56 2620.4 23.74 Grassland 6549.80 59.33 3139.56 28.4 526.48 4.77 834.1 7.56 Wetland 173.80 1.57 43.99 0.4 31.45 0.28 30.1 0.27 Woodland 26.00 0.24 0.0 0.0 0.00 0.00 0 0.00

Total 11039 11039 11039 11039

Agricultural land has increased gradually but significantly since 1986 at the expense of grassland, bushland, and woodland and reached a plateau by 2006. The area under bushland has remained quasi-constant since 1996 while grassland has shown a slight increase since 2006. From 2006 to 2016, some areas which were under agricultural land have been converted to grassland and bushland. The results of this study are in line with previous observations by other scholars (Kimwaga et al., 2012; Rwetabula, 2005; van Griensven et al., 2013). Under LVEMP II, agricultural lands adjacent to the River Simiyu and its tributaries were reclaimed through a 60m buffer zone policy.

General land degradation mechanisms in the Simiyu catchment The major causes of land degradation in the Simiyu catchment include grazing and expansion of agricultural land (Oldeman et al., 1991). An assessment conducted by the Tanzania Participatory Poverty Assessment in 2002-2003 revealed that, for example in Meatu district, many trees were cut mainly to clear land for cultivation. This was confirmed by studies in the catchment by several scholars (e.g Kimwaga et al., 2012; Gasmelseid et al., 2010). Deforestation or cutting trees on cultivated lands coupled with poor land management and an increased density of livestock contribute to increased soil erosion (Ministry of Water of Tanzania, 2013, Gasmelseid et al., 2010).

Current soil erosion risk Figure 6 depicts soil loss risk from the Simiyu catchment based on the 2016 land use/cover map obtained in this study showing the area covered by each soil erosion risk class. Only 57% of the catchment experiences low to very low soil erosion risk. Patches of high (16.14%) and very high (2.16%) soil loss risk are distributed mainly in the cultivated part of the catchment, characterized by gentle slopes. The highly affected micro-catchments include: Kabondo, Nyamatembe, Bukingwaminze, Ngudama and Sandai. Bukingwaminze (catchment) includes Bukingwaminze, Kabale, Zanzui, Mlimani villages in the Itilima District. The low soil erosion risk around the outlet of the catchment is due to flat terrain and good grass cover.

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Figure 6. Soil loss hotspot areas in the Simiyu River Catchment in 2016, assuming no SLWM Note: Soil erosion risk classes: Very low (Soil loss = 0-2 t/ha/yr); Low (2-5 t/ha/yr); Moderate (5-10 t/ha/yr); High (10-20 t/ha/yr); Very high (>20t/ha/yr)

The results are consistent with earlier studies which had identified the Simiyu catchment as one of the major sediment contributors in the LVB (Tamatamah, 2010; Ndomba and Griesven, 2011; Rwetabula, 2012). Sediment transfer is a function of connectivity to the outlet. The latter is attributable to topography, soil types, geology and morpho-pedological variables, climate events and the effectiveness of the existing management technologies and practices.

The study also showed that the total land area with moderate, high and very high soil erosion risks in the Simiyu catchment in 2016 is larger than that in 2006 while the area with very low to low risk reduced during the same period (see Figure 7). The change in soil erosion risk is attributed to the change in land-use/cover within the catchment, and especially the expansion of agricultural land since 2006.

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70.00

60.00

50.00

40.00

2016 % area area % 30.00 2006 20.00

10.00

0.00 Very low Low Moderate High Very high Soil erosion risk

Figure 7. Percentage of the catchment area under different soil erosion risks in 2016 and 2006

Sediment yield and load into the Simiyu River The ArcSWAT model was used to assess the sediment yield of the Simiyu catchment and the load of sediment as well as nutrients to Simiyu River. The model was calibrated and validated, and reasonable model performance was obtained (Table 5 and Figure 8).

Table 5. Calibration and validation statistics Parameters Calibration (1979-1987) Validation (1988-1995) Observed Statistics Observed Statistics R2(Coefficient of determination) - 0.73 - 0.62 Nash Sutcliffe Coefficient - 0.61 - 0.59 KGE - 0.75 - 0.74 PBIAS - -1.00 - 11.9 Standard deviation 75.16 90.51 84.2 76.7 Mean daily flow (m3/s) 71.46 72.16 65.0 57.3

Figure 8. Flow calibration (1979-1987) and validation (1988-1995) results for Simiyu River Catchment

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Sediment yield from the Simiyu River catchment is presented by Figure 9. For the period 1980-2009 it varied between 0 - 45t/ha/yr. The southern and eastern part of the catchment, mainly dominated by bushland with short grasses, export a relatively larger amount of sediment into the Simiyu River compared to the northern part of the catchment. Also, patches with relatively moderate sediment yield are observed in the region of . This is mainly attributed to the relatively greater steepness of slope in the eastern part of the catchment compared to the flat terrain in the west.

Figure 9. Average simulated sediment yield in Simiyu catchment (1980 - 2009)

The simulated sediment load in the Simiyu catchment for the period 1980 to 2009 varied from 0.01 to 5.69 Mt/yr, with an average sediment load of 1.64 Mt/yr and an average annual sediment concentration of 287.78 mg/l. TN and TP loads ranges from 0.72 to 55.70 and 0.01 to 12.51 t/day, with their averages of 11.95 t/day and 2.00 t/day, respectively (Table 6). Sediment yield at the Simiyu River outlet varied from 0 to 38.83 t/ha/yr, with an average of 7.73 t/ha/yr. These values are relatively high compared to those reported by Myanza et al. (2005) and low compared to those reported by Ndomba et al. (2011).

Table 6. Simulated flow, sediment yield, sediment and nutrient loads at the outlet of Simiyu catchment (1980-2009) Catchment Annual Sediment Sediment TN TP Sediment Flow load concentration (t/day) (t/day) yield (m3/s) (Mt/yr) (mg/l) (t/ha/yr) Average 57.72 1.64 287.78 11.95 2.00 7.73 Minimum 4.68 0.01 11.75 0.72 0.01 0.00 Maximum 216.61 5.69 733.08 55.72 12.51 38.83 Standard deviation 65.34 1.53 173.86 15.02 2.91 9.10 Coefficient of Variation 113.19 93.64 60.41 125.71 145.48 (%) 117.76

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For the period 2010-2016, the study showed that the average sediment load was 3.60 Mt/yr, with a range of sediment yield between 0.50 and 11.86 t/ha, and the average sediment concentration was 373.51 mg/l. The average TN and TP was 9.61 t/day and 2.39 t/day, respectively. Figure 10 shows the spatial distribution of the average sediment yield for the period 2010-2016. The areas in Itilima and Bariadi had relatively higher sediment yield compared to other parts of the catchment.

Figure 10. Average simulated sediment yield in Simiyu catchment (2010 - 2016)

The few available sediment measurements in the catchment seem to indicate that the catchment exports a large quantity of sediments into Lake Victoria (Ndomba et al., 2005). This suggests that there exist more sediment sources, apart from the sheet erosion unable to be simulted by SWAT. The SWAT model’s limitations in reasonably simulating the sediment from gully erosion, landslides and mass wasting are well noted (Bokan, 2015), particularly in the absence of sufficient flow and water quality data. During the field work, a high density of gullies was observed around the raised grounds due to degradation of vegetation. River bank erosion was observed wherever the tributaries and drainage channels pour into the river. These could explain the difference between the observed and simulated sediment loads.

Monthly flow, sediment yield, and sediment and nutrient loads in the Simiyu catchment were also modelled. The results show that in general, the flow increases from January to April, decreases afterwards up to November, and then starts increasing again in December. The total sediment and nutrient loads are relatively higher from January to May. Except TN, all the other parameters are significantly reduced from June to October, before picking up again from November for the period 1980-2009.

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Net Primary Productivity status and trends The Net Primary Productivity (NPP) represents the net amount of carbon dioxide taken in by vegetation in a particular area. The reduction of plant biomass and NPP below that of non-desertified land under equivalent environmental conditions is proportional to the experienced land degradation (Puigdefabregas et al., 2009) and more particularly to soil erosion and nutrient transfer into surface water bodies (Vegas Legaz et al., 2017). The United Nations Convention to Combat Desertification (UNCCD) has recently proposed NPP as an indicator to report on land degradation (UNCCD 2013, 2016). The NDVI is recognized as a good surrogate of the NPP, thus its annual integrals were used to compute each of the productivity indicators (state and trajectory); and it is strongly associated with soil erosion (Butt et al., 2010). Generally, soil erosion reduces with increasing NDVI (Tadesse et al., 2017).

The current state of the NPP in the Simiyu catchment is shown in Figure 11 and the trend in NVDI from 2001 to 2016 is presented in Figure 12. A majority of the cultivated areas is showing a decline in NPP compared to 2001 conditions. Overall, the catchment shows a declining linear pattern in NPP compared to its 2001 status. This can be attributed to the variability of climatic conditions and anthropogenic activities.

Figure 11. Vegetation degradation in Simiyu catchment as indicated by NPP, 2001-2015

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3200

3100

3000

2900

2800

2700

Integrated 10000) (NDVI NDVI x Integrated 2600

2500 2000 2002 2004 2006 2008 2010 2012 2014 2016 2018 Year

Figure 12. Trend in NDVI across the entire Simiyu catchment (2001-2016)

4.2 Geo-spatial information of the selected hotspot micro-catchments

Based on the previous analysis, two micro-catchments—Kabondo and Nyamatembe shown in Figure 13—were seletced as soil erosion hotspots for more in-depth assessment in this study. Compared to other micro-catchments, these two micro- catchments presented a relatively higher number of patches (acreage) of higher soil erosion risks. In addition, the two micro-catchments heavily depend on agriculture and livestock for their livelihoods, making them prone to more land degradation, and therefore are potential major contributors of sediment and nutrient transfer into surface waters.

Land use changes Table 7 and 8 summarize the trends in land use change in the two micro-catchments. In 1986, grassland, followed by agricultural land, was the most dominant land use/cover in Kabondo. Grassland occupied 57.26% of the micro-catchment, and the agricultural land over a quarter (27.52%). A decade later (1996), 53.29% of the entire micro- catchments were cultivated. Agricultural expansion occurred at the expense of all other land use/cover including wetlands. By the end of 2016, agricultural land covered 90.24% of the entire micro-catchment. The area under wetland declined significantly from 6.37% in 1986 to 0.10% in 1996. Despite a recovery to 3.95% in 2006, the wetland area declined again almost to extinction (only 0.03%) by 2016.

Table 7. Kabondo micro-catchment land use/cover change (1986-2016) Land use/cover 1986 1996 2006 2016 Area % Area % Area % Area % (km2) (km2) (km2) (km2) Agriculture 49.38 27.52 95.72 53.29 100.98 56.27 161.99 90.24 Bushland 15.89 8.86 0.01 0.01 2.35 1.31 9.43 5.25 Grassland 102.75 57.26 83.62 46.60 69.04 38.47 8.04 4.48 Wetland 11.43 6.37 0.18 0.10 7.09 3.95 0.05 0.03 Total 179.5 100 179.54 100.00 179.5 100 179.5 100

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Figure 13. Soil erosion hotspot micro-catchments in Simiyu catchment

Similarly, grassland was the dominant land use/cover in the Nyamatembe micro- catchment in 1986 occupying 55.6% of the total area, followed by agricultural land at 22.6%, wetland at15.6% and then bushland at 6.2%. In 1996, agricultural land surpassed all other land use types to become the most dominant land use type and reached 60.5% of the total area. Agricultural land has since continued to increase linearly over time at the expense of grassland and bushland and reached 91.7%. Grassland dropped significantly from 55.6% in 1986 to 0,1% in 2016. Wetland coverage significantly declined from 15.6% in 1986 to 0,3% in 2006 and then started recovering to 6.3% in 2016.

Table 8. Nyamatembe micro-catchment land use/cover change (1986-2016) Land use/cover 1986 1996 2006 2016 Area % Area % Area % Area % (km2) (km2) (km2) (km2) Agriculture 20.52 22.6 54.91 60.5 72.84 80.3 83.3 91.7 Bushland 5.63 6.2 2.15 2.4 1.31 1.4 1.76 1.9 Grassland 50.43 55.6 18.96 20.9 16.3 18 0.09 0.1 Wetland 14.17 15.6 14.73 16.2 0.3 0.3 5.7 6.3 Total 90.8 100.0 90.8 100.0 90.8 100.0 90.8 100.0

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Soil erosion in the selected hotspot micro-catchments Figure 14 shows a summary of the percentage area covered by different soil erosion risk classes in 2006 and 2016. The erosion hotspot areas for Kabondo and Nyamatembe are shown in Figures 15, 16, 17, and 18, respectively. In 2006, the largest portion of the two micro-catchments had very low soil erosion risk. In 2016, however, the situation had reversed with less than a third of the micro-catchment area is covered by very low to low erosion risk (22.8% for Kabondo and 30.5% for Nyamatembe). Areas with high to very high soil erosion risks respectively covered 43.3% and 35.1% for the two micro- catchments, respectively.

Kabondo (2006) Kabondo (2016)

9% 7% 12% 5% 11% 14% 36%

72% 34%

Very low Low Moderate High Very high

Nyamatembe (2006) Nyamatembe (2016)

9% 10% 13%

10% 26% 17% 16% 64%

35%

Figure 14. Proportion of land under different soil erosion risks, without SLWM

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Figure 15. Soil erosion hotspots in Kabondo sub-catchment, Simiyu catchment (2006)

Figure 16. Soil erosion hotspots in Kabondo sub-catchment, Simiyu catchment (2016)

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Figure 17. Soil erosion hotspots in Nyamatembe micro-catchment, Simiyu catchment (2006)

Figure 18. Soil erosion hotspots in Nyamatembe micro-catchment, Simiyu catchment (2016)

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State and trends in NPP in the selected micro-catchments The productivity state measures differences in NDVI/NPP for a given period compared to the baseline. It was clustered into improved (increase NDVI/NPP), stable (no change in NDVI/NPP) and degraded (reduced NDVI/NPP). The trajectory measured the rate of change in primary productivity over time. It was computed as a linear regression at the pixel level. A Mann-Kendall non-parametric significance test was then applied, considering only those significant changes at p-value ≤ 0.05 and p<0.01. Those with no significant trend (p>0.05) were categorized as stable. Positive significant trends in NDVI would indicate potential improvement in land conditions, and negative significant trends indicate potential degradation.

In the Kabondo micro-catchment, its northwestern part in Buchambi Ward of Maswa District shows a degrading productivity trend. The southern parts of the micro- catchment are relatively stable without change in NPP or show signs of improvement with an increase in NPP. In Nyamatembe, degradation (reduced NPP) is relatively dominant compared to stable and improved areas. Most of the stable areas are located towards the eastern part of the micro-catchment. With respect to the significance of NPP trend, from 2001 to 2015, the northern part of Maswa and the eastern part of Dodoma in Kabondo show a rapid decline in vegetation, a trend also observed in almost the entire Nyamatembe micro-catchment.

Spatio-temporal pattern of vegetation degradation in the micro-catchments Figures 19 and 20 show the state of vegetation degradation in Kabondo and Nyamatembe micro-catchments. From 2001-2006, almost the entire Kabondo micro- catchment experienced degradation compared to its 2001-2003 conditions. Only a small portion had shown some recovery. Between 2006 and 2012, a big portion of the eastern part of the micro-catchment had shown signs of improvement. Between 2012-2015, some improvements were seen. The only part which remained stable compared to 2001- 2003 conditions was the western part of Kabondo. From 2006-2012, the southern parts of the micro-catchment had recovered. Between 2012-2015, most of the micro- catchment was stable compared to its 2006-2012 condition, with recovered patches scattered in the southern and eastern part of the micro-catchment.

In Nyamatembe, the entire micro-catchment generally experienced degradation trends in the period 2001-2006 (P<0.05), and the majority of the micro-catchment was in a degraded state. Signs of recovery were observed between 2006-2012, and a few parts also showed recovery in the period 2012-2015. In the period 2012-2015, a big portion of the micro-catchment was degraded again after the 2006-2012 recovery period.

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2001-2006 2006-2012 2012-2015

Figure 19. Spatio-temporal pattern in the NPP state of degradation in Kabondo micro-catchment, 2001-2015

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2006-2012 2012-2015 2001-2006

Figure 20. Spatio-temporal pattern in the NPP state of degradation in Nyamatembe micro-catchment, 2001-2015

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Gully erosion in the hotspot micro-catchments In the two hotspot micro-catchments, widespread gullies with various scales and dimensions were observed. Large permanent gullies (as shown in the photo below) were mapped based on field observations and satellite imagery in ArcGIS 10.4 (Figure 21 and Figure 22). Seven large permanent gully erosion features were geo-referenced during fieldwork and overlaid on Sentinel 2 images of the study area to identify key features for their mapping (Table 9). Field observations have shown that 2m deep and 5m wide gullies are common in the two micro-catchments. This indicates that gully erosion is very active in the two micro-catchments and likely in the entire Simiyu catchment; and partly explains the high sediment loadings of Simiyu River.

Photo 1. A gully in the Simiyu River Catchment

Table 9. Gully length and density in Kabondo and Nyamatembe micro-catchments Micro- Length (km) Estimated gully density (km/km2) catchment Kabondo 15.6 0.09 Nyamatembe 14.47 0.17

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Figure 21. Gully distribution in Kabondo micro-catchment

Figure 22. Gully distribution in Nyamatembe micro-catchment

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Flow, sediment and nutrient transport in the selected micro-catchments Table 10 and Table 11 present the flow, sediment yield, sediment load and concentration, and nutrient loads for Kabondo and Nyamatembe micro-catchments, respectively. The concentration of sediment was relatively higher in both micro- catchments compared to the Simiyu catchment. Kabondo tends to have far much higher values of flow, sediment and nutrient loads compared to Nyamatembe micro- catchment.

Table 10. Annual average flow, sediment and nutrient loads in Kabondo micro-catchment from 1980 to 2009 Flow Sediment Sediment TN TP Sediment (m3/s) load concentration (Kg/day) (Kg/day) yield (t/yr) (mg/l) (t/ha/yr) Average 1.0 6373.6 9.1 243.6 30.3 12.11 Minimum 0.0 0.0 0.0 3.0 0.0 0.06 Maximum 4.1 38284.6 42.4 1147.9 169.0 36.79 Standard 1.3 11583.1 14.2 337.3 54.1 11.26 deviation CV (%) 135.6 181.7 155.3 138.5 178.2 92.99

Table 11. Annual average flow, sediment and nutrient loads in Nyamatembe micro-catchment from 1980 to 2009 Average Sediment Sediment TN TP Sediment yield Flow load concentration (Kg/day) (Kg/day) (t/ha/yr) (m3/s) (t/yr) (mg/l) Average 0.09 1.18 4.39 29.25 3.56 5.67 Minimum 0.00 0.00 0.00 1.82 0.00 0.00 Maximum 0.52 20.69 59.28 322.13 66.87 34.47 Standard 0.14 3.88 11.53 60.84 12.39 8.64 deviation CV (%) 152.87 328.82 262.30 207.99 348.11 152.47

Monthly average of flow, sediment and nutrient loads for Kabondo and Nyamatembe micro-catchments, respectively for the 1980-2009, and the 2010-2016 period were also simulated. As for the Simiyu catchment, sediment load, sediment yield, sediment concentration and TP load were high from December to April. Flow increases starting in December and reaches its peak in April. October and November have the lowest monthly flows.

4.3 Effectiveness of the identified SLWM options

Experiences with SLWM technologies in erosion hotspot areas Application of some of the SLWM technologies were observed in the soil erosion hotspot areas (Table 12). These included contour bunds strengthened with trees and grass, tie-ridges combined with cut-off drains, gully plugs, traditional woodlot (Ngitiri) conservation, natural pasture regeneration, rice bunds (Majaruba), and reforestation and bee keeping.

Table 12. SLWM interventions found in the pilot micro-catchments of the Simiyu catchment District Village Land use Technology Technology Adoption Type category rate (%)

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Farmland Contours strengthened Introduced 11.2 with trees or grass Busega Shigala Gully plugs Introduced 0 Tie-ridging Introduced <10 Farmyard manure Indigenous 10-50 application Forest Woodlot conservation Indigenous 10-20 (Ngitiri) Kalemela Wetland Rice bunds (Majaruba) Indigenous 10-50 Bariadi Kasoli Grassland Contours with trees Introduced 11.2 Natural pasture Introduced ND* regeneration Itilima Isengwa/ Forest Reforestation and bee Introduced ND* Lugangabilili keeping *ND: not determined

Contour bunds strengthened with trees or grass were introduced by LVEMP II in Shigala village seven years ago. Bunds are constructed along the contour and allowed natural grass, shrub or trees to grow on the contour. They are combined with the application of farmyard manure and construction of tie-ridges in the area between contours in cotton or maize production. The technology has also been adapted with construction of boundary contour strips to prevent water overflow on contours. Only a few members of the community, however, have adopted the technology based on the field study.

Photo 2. Stone contour bunds (Photo credit: http://aashah.blogspot.com/2013/11/contour-bunding.html)

Tie bunds or Tie ridges combined with cut-off drain and gully plugs were found in cassava gardens. Similar to the contour bunds, very few farmers have adopted tie- ridges, mainly due to the fact that tie construction is time consuming, labor intensive, and there is low awareness of the technology.

Gully plugs involve the construction of stone walls at intervals in the gully from its upper to lower slope along the landscape. The technology is well-known by the local extension staff. No individual community member has adopted the technology probably due to lack of observed impact results and the high construction cost. Improvements could be achieved if technically competent land use planning officers were contracted for construction, and the guidelines for gully control were considered.

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Photo 3. Tie bunds or tie-ridge (Photo credit: http://www.fao.org/3/y4690e/y4690e09.htm)

Photo 4. A gully plug (Photo credit: http://newseq.blogspot.com/2013/09/gully-plugging-is-appropriate- technique.html)

Traditional woodlots (Ngitiri) are a traditional Sukumaland practice (practice in the land of the Sukuma people). They involve in-situ conservation of traditional woodlots combined with beekeeping in natural woodlot land use systems. The village, ward and district administration were consulted for endorsing the woodlot as a conservation practice.

Rice bunds (Majaruba) are also a traditional SLWM measure. They involve leveling and bunding to raise the soil around plot boundaries and ensure that water is not drained out of a rice field. This measure was applied by 10-50% of the rural community by almost all the farmers who own land in foot slopes and valley floors.

Simulated effectiveness of selected SLWM in the study area Tables 13, 14, and 15 show the effectiveness of the selected SLWM technologies in controlling sediment and nutrient loading at the outlets of Nyamatembe and Kabondo

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micro-catchments and the Simiyu catchment, based on model results. Generally, all the selected SLWM tended to reduce sediment loads and concentration in both micro- catchments and the Simiyu catchment.

Tie bunds and contour bunds tended to be more effective in sediment and nutrient reduction compared to the other SLWM technologies. Their effectiveness tended to exceed 80% for the Simiyu catchment and both micro-catchments in reducing the sediment and nutrient (TN and TP) loads. These results are in line with the findings from Hulugalle et al. (1990), Baird (1964) and Secchi et al. (2007).

It is clear that sediment in the Simiyu River gets largely contributed by the actively developing gullies in the catchment and the eroding the banks of the Simiyu River and the streams that flow into it. River or stream bank stabilization led to a reduction of sediment and nutrient loads in both micro-catchments and the Simiyu catchment, and was significantly effective in reducing sediment load, sediment concentration and TP in both the Kabondo micro-catchment and Simiyu catchment. Creating and observing a buffer zone of at least 60-meters wide along each side of the rivers has been required by Tanzania’s national law. The buffer zone helps to prevent riverbanks from encroachment and illegal agricultural activities, and also allows riverbank stabilization techniques to be adopted, including planting vegetative materials like bamboo and/or vetiver, and is effective for reducing soil erosion and sedimentation. However, enforcing no encroachment on buffer zones remains a challenge in many locations, as villagers may have a long history of using the area inside of a newly created buffer zone for grazing, cultivation and cutting fuelwood. One of the challenges of enforcement is how to address alternative livelihood supports to the affected local households so that they avoid cultivation and other activities that compromise riverbank stabilization.

Compared to the baseline of two micro-catchments and the Simiyu catchments, gully plugs had the lowest relative change in all the selected parameters. Significant sediment load reduction was observed in both micro-catchments, while TP reduction was observed only in the Kabondo micro-catchment. However, the technology of gully plugs was not adopted by local communities due to their financial, technical and skill constraints.

Table 13. Effectiveness of selected SLWM in sediment and nutrient reduction in Nyamatembe micro-catchment in 1980-2009 Unit: % Sediment Sediment SLWM technology Flow load concentration TN load TP load Riverbank -0.044 -59.02* -40.93 -15.45 -38.52 stabilization Gully Plugs -0.001 -59.02* -40.93 -15.03 -34.18 Tie bunds 123.69* -94.37* -97.92* -38.44 -93.63* 79.19* -71.79* -90.50* -42.48 -72.16* Contour bunds *variation significant at P<0.05 compared to without SLWM, , otherwise variation not significant.

Table 14. Effectiveness of selected SLWM in sediment and nutrient reduction in Kabondo micro- catchment in1980-2009 Unit: % Sediment SLWM technology Flow Sediment load concentration TN TP

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Riverbank 37.13 -95.05* -97.52* -2.01 -93.53* stabilization Gully Plugs -1.45 -46.85* -11.39 -17.97 -34.73* Tie bunds 23.54 -90.10* -94.90* -22.34 -86.80* Contour bunds 21.56 -75.53* -85.76* -42.99 -67.85* *variation significant at P<0.05 compared to without SLWM, otherwise variation not significant

Table 15. Effectiveness of selected SLWM in sediment and nutrient reduction in Simiyu catchment in 1980-2009 Unit: % SLWM technology Flow Sediment load Sediment TN TP concentration Riverbank stabilization -0.06 -24.01 -24.88 -17.10 -30.11* Gully Plugs 0.007 -27.17 -20.31 -15.11 -23.55 Tie bunds 42.19 -87.03* -95.36* -20.20 -71.70* Contour bunds 20.52 -72.93* -85.77* -28.19 -53.06* *variation significant at P<0.05 compared to without SLWM, otherwise variation not significant

4.4 Projected effectiveness of the selected SLWM under the near future climate change scenarios

Projected climate in the near future scenarios (2010-2039) All models also predict an increase in temperatures over the Simiyu catchment for RCP 8.5. The CMCC-MS and GISS-E2-H models predict the highest temperature changes (1.45oC) while MIROC-ESM predicts the smallest change (0.35oC). The projected average daily rainfall amount over the catchment is presented in Table 16. Overall an average temperature increase of 0.94oC is projected in Simiyu catchment under the RCP 8.5. Only CMCC-MS, GISS-E2-H and MPI-ESM models project a reduction in the rainfall amount. On average a relative increment of 7.75% is the expected rainfall amount for the ensemble of GCMs.

Table 16. Projected change in average annual temperature and annual rainfall in the near future scenario (2010-2039). Parameter RCP 4.5 RCP 8.5 ∆T (oC) 0.84 0.94 Relative change in rainfall (%) 5.64 7.75

Projected flow, sediment, and nutrient loads in the near future scenario (2010-2039) Table 17 shows the projected flow, sediment and nutrient loads for the near future in the Simiyu catchment, Kabondo and Nyamatembe micro-catchments under RCP 8.5. The projected flow is higher than that simulated for the 1980-2009 period. However, the projected sediment and nutrient (TN and TP) loads are relatively lower than those simulated for the 1980-2009 period. The low simulated sediment, TP and TN loads could be attributed to the very long projected period of low flows with scanty strong peaks in the near future than for the 1980-2009 period. Kabondo is likely to have more flow, TN and TP loads than the Nyamatembe micro-catchment.

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Table 17. Projected flow, sediment load and concentration, and nutrient loads in Simiyu catchment, Kabondo and Nyamatembe micro-catchments in the near future (2010-2039) without SLWM Catchment Flow Sediment Sediment TN load TP load load concentration m3/s Mt/yr mg/l kg/day Simiyu 75.67 0.95 52.88 11.57 2.39 Kabondo 0.97 0.006 9.40 0.16 0.03 Nyamatembe 0.29 0.004 7.77 0.07 0.01

Projected effectiveness of the selected SLWM in near future (2010-2039) for RCP 8.5 Table 18 summarizes the relative performance of the selected SLWM in the Simiyu catchment in the near future under RCP 8.5. Similar trends to the period 1980-2009 were observed in the projected effectiveness for Simiyu catchment. Contour bunds and tie-bunds achieve the highest relative reduction in the loads while they tended to increase runoff. All the SLWM are likely to contribute to improved water quality in the Simiyu Catchment, particularly TN and TP loads. Gully plugs still have an effect, but lead to a smaller percentage reduction in sediment, sediment concentration, TN and TP loads. In Kabondo micro-catchment, the future effectiveness (Table 19) of the selected SLWM is likely to follow the patterns experienced in the 1980-2009 period. All of the tested SLWM technologies significantly reduced sediment and TP loads. Contour bunds and tie bunds also significantly reduced sediment concentration.

In the Nyamatembe micro-catchment, all of the tested SLWM technologies have a significant reduction effect on sediment load and sediment concentration (Table 20). Comparing the effectiveness of the selected SLWM in the two micro-catchments, one can see that the effectiveness varies between them. For example, gully plugs have a relatively higher reduction effect on sediment load and concentration in Nyamatembe than in Kabondo. This is linked to the relatively higher density of gullies in Nyamatembe than in Kabondo. On the other hand, riverbank stabilization in Kabondo has a relatively higher sediment reduction effect than in Nyamatembe. The results of this study demonstrate that the tested SLWM will have varying effectiveness in the near future. However, contour bunds and tie bunds are likely to be the most effective SLWM in reducing sediment and nutrient loads in Simiyu catchment and its hotspot micro-catchments. The relatively low (simulated) effectiveness of gully plugs in controlling sediment and nutrient load does not imply that gully treatment is not important and ineffecitve, but rather that the connectivity of most gullies is low as they all start from the deforestated hills and end up in the lowland area of the catchment, where the eroded materials are deposited.

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Table 18. Relative change in water quality and quantity parameters in Simiyu catchment induced by the selected SLWM in the near future (2010-2039) under RCP 8.5 Unit: % Sediment SLWM Technologies Flow Sediment Load concentration TN TP Riverbank -0.11 -34.76* -23.25 -23.7 -34.37** stabilization Gully plugs -0.03 -37.11* -21.36 -21.79 -29.16 Contour bunds 7.77 -69.56* -79.96* -41.32* -55.41* Tie bunds 10.59 -48.58* -63.33* -5.7 -47.97* *variation significant at P<0.05 compared to without SLWM, ** significant at P<0.1, otherwise variation not significant

Table 19. Relative change in water quality and quantity parameters in Kabondo micro- catchment induced by the selected SLWM in the near future (2010-2039) under RCP 8.5 Unit: % SLWM Technologies Flow Sediment Sediment TN TP load concentration Riverbank stabilization -0.08 -52.05* -24.63 -28.16 -43.59* - -0.04 -52.05* -24.49 -27.43 Gully plugs 38.67** Contour bunds 7.91 -76.89* -83.96* -17.6 -66.53* Tie bunds 40.98 -94.71* -97.51* -22.68 -92.93* *variation significant at P<0.05 compared to without SLWM, ** significant at P<0.1, otherwise variation not significant.

Table 20. Relative change in water quality and quantity parameters in Nyamatembe micro- catchment induced by the selected SLWM in 2010-2039 under RCP 8.5 Unit: % SLWM Technologies Flow Sediment Sediment TN TP load concentration Riverbank stabilization -5.66 -23.28** -33.93** -32.20 -13.60 Gully plugs -0.10 -54.56* -35.69** -18.91 -27.77** Contour bunds 1.56 -55.39* -79.92* -7.61 -39.63* Tie bunds 28.06** -98.26* -98.83* -46.39** -98.04* *variation significant at P<0.05 compared to without SLWM, ** significant at P<0.1, otherwise variation not significant.

4.5 Summary of the case study’s analytical findings

The case study’s key findings are summarized as follows: • The Simiyu river catchment has experienced land degradation and soil erosion for several decades. The Catchment’s micro-catchments highly affected by soil erosion include Bukingwaminze, Kabondo, Ngudama, Nyamatembe, and Sandai. The major causes of soil degradation in Simiyu catchment include over-grazing and expansion of agricultural land with unsustainable practices. • Agriculture and bushland are the dominant land-use/cover in the Simiyu River Catchment. Since 1986, agricultural land has increased gradually but significantly at the expense of bushland, grassland and woodlands. The bushland area has remained quasi-constant since 1996 while grassland has increased slightly since 2006.

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• The Catchment area facing high soil loss risk is 16.1%, and another 2.2% is categorized as very high risk. This high and very high risk land is distributed mainly in the cultivated part of the Catchment. About 57% of the Catchment has a low to very low risk of soil erosion.The simulated sediment yield has varied over the years, ranging from 0 to 38.83 t/ha/yr for the period 1980-2009, and 0.50 to 11.86 t/ha/yr for the period 2010-2016. The southern and eastern part of the Catchment, mainly dominated by bushland with short grasses, exports a relatively larger amount of sediment into the Simiyu River compared to the northern part of the Catchment. • The simulated sediment load in the Simiyu River Catchment has varied over the years (0.01 to 5.7 Mt/yr), with an average value of 1.6 Mt/yr from 1980-2009. During this period, the average annual sediment concentration, total nitrogen (TN) and total phosphorous (TP) are 288.0 mg/l, 12.0 t/day and 2.0 t/day, respectively. • The flow, sediment yield and load varied across the months, with increases from November to April/May and decreases afterwards. Except TN, all other parameters tend to reduce significantly during the low flow period. • A variety of SLWM measures that can effectively control soil erosion already exist in the LVB, including cross slope barriers, crop rotation, adaptive tillage, soil fertility measures, agro-forestry measures, vegetation strips, and runoff flow and erosion control. • Common SLWM technologies and practices for erosion control vary from one LVB country to another. Those observed in the soil erosion hotspot areas of the Simiyu River Catchment include contour bunds strengthened with trees and grass, tie bunds or tie ridges combined with cut-off drains, rice bunds (Majaruba), gully plugs, woodlot conservation (Ngitiri), natural pasture regeneration, and reforestation and bee keeping. • The effectiveness of four SLWM practices and technologies (contour bunds, tie bunds, gully plugins, riverbank stabilization) was evaluated using the Soil and Water Assessment Tool (SWAT). Generally, all the selected SLWM tended to reduce sediment loads and concentration in the Simiyu River Catchment’s hotspot micro-catchments. Tie bunds and contour bunds had the highest sediment and nutrient load reduction percentage compared to other SLWM practices. Under this study, their effectiveness exceeded 80% in the Simiyu River Catchment and its hotspot micro-catchments. • Available climate change models showed that on average a 7.75% increase in rainfall is expected over the Simiyu River Catchment for the ensemble of GCMs under RCP 8.5 from 2010 to 2039. TP and TN loads in the near future scenario and under the RCP 8.5 are likely to be lower than the corresponding values for the period from 1980-2009. • In sum, the analyzed SLWM practices will have varying effectiveness on soil erosion control for the projected years. Contour bunds and tie bunds are likely to be the most effective SLWM in reducing sediment and nutrient loads in Simiyu catchment and its hotspot micro-catchments.

4.6 Beyond technical solutions

SLWM is an integral part of the catchment development and its expected results cannot be achieved independently. To implement SLWM technologies broadly and enhance

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their effectiveness and sustainability, it is necessary to go beyond technical solutions and tackle land degradation problems from a broader institutional perspective. First, it is important to integrate the practices into regional and local land management plans and programs. It is necessary to assist district governments and agencies in developing and implementing an integrated land use plan and land management program that effectively manages land resources within and across districts in the Simiyu River Catchment and protects the transboundary water resource in Lake Victoria. SLWM activities must be linked with other sectoral programs including forestry, agriculture extension, animal husbandry and biogas. Such linkages can help achieve interrelated multiple results, and also lead towards environmental and socio- economic sustainability.

Second, the landscape approach should be adopted as a comprehensive way to strengthen SLWM and governance. Effective erosion control operations require the application of SLWM practices by many stakeholders throughout an entire catchment—from the hilltops, down to the foot slopes and river mouths. This can only be achieved by using a landscape approach and reviving and strengthening local institutions, including those at the village level, adapting traditional governance practices and considering the prevailing socio-political context. SLWM task forces should be established at various levels, with clear terms of reference within each catchment. And efforts should be made to ensure that the benefits are shared fairly among stakeholders.

Third, at the farm and village levels, an integrated farm planning approach—one which involves stakeholders identifying land degradation and sustainable land management and livelihood objectives and developing plans to achieve that outcome—has already had successful trials in Burundi. As a next step, project activities can be geared towards helping stakeholders reach their goals through training on specific SLWM practices, offering guidance and support, etc., and ultimately stimulating the convergence to a village-level plan. Interdependencies can be integrated in context with upstream and downstream stakeholders, who should all agree on the need to monitor further indicators capable of expressing such interdependencies. This way, individual stakeholders become aware of the need for monitoring and will have a higher willingness to engage in such efforts.

Fourth, sensitizing local communities and individual farmers to adopting SLWM technologies and building their capacity are critical to the success of SLWM applications. Most of the recommended SLWM have been introduced under the LVEMP, TAMP-Kagera and other projects, however their adoption rate in LVB remains low. The bottleneck is the awareness, experience and capacity of local communities. There is a need to analyze the barriers and assess the capacity needs of farmers, particularly women, who are often major users of the land. It is important to continue to sensitize farmers to the use of SLWM technologies and practices which can be done through training farmers at the village level, piloting and establishing demonstrations, organizing farmer field schools, and encouraging the scaling up of SLWM technologies and practices. Local organizations such as the Catchment Management Committee should be involved in sharing, disseminating and promoting SLWM technologies.

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Finally, it would be useful to step up the effort of cross-learning and sharing and disseminating experiences and knowledge among communities. There has been experience and accumulated knowledge from LVEMP and a number of sub-regional and national projects on land resource management and resilience funded by the World Bank and other international organizations. For example, TAMP-Kagera has some successful stories of how SLWM can help address land degradation and erosion issues in the LVB. The technologies and test crops under SLWM in TAMP were all decided upon by farmers, from a basket of options, and improved upon by technicians/experts. Farmer preferences for multipurpose technologies that address several degradation problems concurrently were remarkable. Resource-poor farmers found this approach to be more affordable and effective. It would be useful to organize field visits for officials, practitioners, and farmers to benchmark positive experiences across the basin and even from other basins that have had successful experiences.

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CHAPTER 5. MONITORING INDICATORS AND MEASURES OF SOIL EROSION REDUCTION

As actual measurement and monitoring of soil erosion and sediment reduction has rarely been conducted in land management projects, this chapter discusses in detail M&E approaches and indicators and proposes a set of indicators and methods for monitoring project progress and impacts.

5.1 Overview of M&E approaches

Monitoring and evaluation (M&E) is an integral part of SLWM projects to achieve the project objectives. M&E approches are devised in terms of project nature and the problem to be addressed. Indicators are an important part of an M&E system. Selection and definition of M&E indicators are critical to successful application of the M&E, and therefore meaningful to analytics and assessment of the project outcomes and impacts. Indicators follow SMART criteria (Specific, Measurable, Attainable, Relevant, and Time-Bound) which was originally proposed as a management tool for project and program managers to set goals and objectives (Doran 1981 and others). In development projects aiming at erosion control, indicators are becoming increasingly important for assessing the progress performance and effectiveness of SLWM practices and for communicating information to policy makers and the general public for future action (Kosmas et al., 2015; Sommer et al., 2011; Ferrara et al., 2012).

Many erosion control indicators are technical and capture the trend of a range of biophysical environment, socio-economic conditions, climate impact, and land management characteristics. However, as decision-makers and the public need a limited number of aggregated and less-technical indicators to compare the trends of land changes, a multi-level, it’s necessary to have a multi-stakeholder M&E system. Different types of information are required at different levels of decision-making.. To get a complete picture of successes and concerns, information from lower-level monitoring needs to be fed into higher-level processes through the indicators system at different levels. This systematic bottom-up exchange of information in turn also enables higher level decisions to target specific basins, landscapes, villages, etc. for SLWM interventions and other forms of support.

To better monitor and evaluate the progress, results and effectiveness of erosion and sediment reduction, M&E design and selection of indicators should be integrated into a planning and implementation process of a SLWM program or project. Figure 23 depicts a detailed framework and steps for developing M&E and indicators in SLWM options. Distinct phases in SLWM project planning are: i) establishing goals and context; ii) identifying, evaluating and selecting SLWM strategies; iii) selecting degradation & SLWM indicators; iv) applying SLWM strategies and monitoring (Reed et al., 2011).

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Source: Reed et al., 2011 Figure 23. Integrated methodological framework for M&E and assessment of SLWM interventions

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Soil erosion indicator monitoring systems should consider both spatial and temporal scales (Kosmas et al., 2014). Spatialscale refers to the resolution of the smallest recognizable unit, which can be micro-plot or large units such as river basins. The difference in spatial scale is related to the type of processes taking place at each scale. In general, on small plots, , splash detachment is the dominant process. As the size of the plots increases runoff detachment and transport are predominant until a sediment concentration threshold is reached for transport and deposition to be prevailing. This occur as drainage area increases. Some indicators are localized (e.g., soil depth, vegetation cover type, and land ownership) while others are regional (e.g., rain seasonality or drainage density). Even though data collection will cover the entire spectrum of indicators, information packaging that targets different end-users at different spatial scale is required. Since the majority of land end-users are smallholder farmers, localized indicators would be useful, and a priority, to them.

Figure 24 presents another useful framework based on the DPSIR (drivers, pressures, state, impact and response) approach for organizing indicators for SLWM practices (Schwilch et al., 2016). The framework considers land management one of the direct drivers of environmental changes, whereby SLWM practices can affect soil threats (e.g., soil erosion), the properties of soil (e.g., soil depth), soil processes (e.g., water cycling), and the ecosystem services provided by the soil (e.g., water regulation, biomass production). The ecosystem services in turn have benefits for humans (e.g., crop yield for food) with a certain value (e.g., use value and non-use values). The values will affect the decision making on societal responses that will influence land management practices.

5.2 M&E Indicators

This study adopted the DPSIR framework and stresses the need for the involvement of farmer groups at every level of M&E processes. Using the DPSIR approach the following indicators can be considered:

Drivers indicators: There are higher level drivers for land and ecosystem changes. Some are natural and external such as climate change, land cover and vegetation and many are direct human interventions, such as decisions by land users/farmers to adopt production/SLWM practices, land use changes, land access/ tenure security, soil agronomic potential, costs and benefits. The main indicators associated with direct drivers of land management are farm size, field size, area of SLWM practice application, fertilizer consumption, and the number of grazing animals.

Pressure indicators: Pressure is indicated by the soil threat. The percentage of area affected by soil erosion, and the magnitude of total soil loss by water (both potential and actual soil erosion risk), can both be used. In Simiyu the density of gullies and rills should also be considered. Some simple erosion assessment indicators involve the identification of biophysical factors influencing erosion (e.g., slope characteristics, vegetation, land management), erosion symptoms (paths of overland flow, rill and interrill erosion) and, most importantly, an estimation of rill and gully erosion by measuring the length, depth and width of rills and gullies.

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Source: Schwilch et al., 2016 Figure 24. Elements of the impact of land management interventions

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State indicators: The soil status can be observed through measuring soil parameters such as soil depth and soil organic matter content, etc. As it may be time-consuming and costly to collect local information on soil status, some proxy methods exist. The Soil Quality Mobile App (SQAPP) is a newly released app available on Android and Apple iOS mobile phones, which provides information on 16 soil parameters in global databases for any location in the world (Fleskens et al., 2018) and an approximate indication of the state of soil quality. Soil moisture and other indicators can also be observed by remote sensing. A low-cost Soilcares soilscanner is being intensively tested in East Africa and the device allows assessing a number of soil quality indicators based on spectral reflectance data.

Impact Indicators: Land management interventions potentially lead to changes in cropping systems and soil condition, erosion and sedimentation control, and other impacts on land resource in the short-, medium- and long-term. Soil erosion-related indicators include changes in soil-based ecosystem services (e.g., water infiltration, sedimentation), changes in crop yields, and changes in land use/cover. Some are direct outcomes of the interventions or projects and others can be the long-term results beyond the project implementation period. These impacts are also on-site or off-site. Increase in crop yields is one of the indicators for measuring on-site impacts. Off-site indicators applicable to Simyu catchment are an increase in river flow; reduction of sediment load, reduction in nitrogen and phosphorus load, and reduction in sediment concentration. Other off-site indicators are reduction in river bank erosion, reduction in damage to roads by gullies and the filling of dams. The economic value of crops and other ecosystem services or products are a kind of impact indicator. Finally, other objective higher-level development indicators can be monitored such as food self-sufficiency rate, household income, etc.

Indicators of Responses: Responses can refer to SLWM practices, catchment management plans and programs, commiunity governance of land use and security, and community participation in SLWM activities. SLWM practices include those erosion control interventions identified and introduced in the LVB, i.e., contouring, terracing, strip cultivation, minimum tillage systems, planting cover crops and so on. Many of these practices help increase vegetation cover and therefore directly reduce erosion. The rate of implementation of SLWM practices and any spontaneous adoption of such practices should be monitored. In addition to SLWM practices, other institutional arrangements for the long-term sustainability of SLWM practices after the end of a particular landscape management project need to be considered. Also, project outputs and intermediate outcomes can be classified under this group of response indicators such as the number of seedlings planted, farmers trained, etc.

The following indicators, for example, can be considered as project development objective (PDO) or result level indicators of investment projects: land area where SLWM practices have been adopted, number of land users adopting SLWM practices, number of beneficiaries (% female) directly benefiting from SLWM interventions, changes in the crop yields of major crops, and reduction in soil erosion and sediment yield. The World Bank recommends the first two as core sectoral indicators for its investment operations. Other indicators to monitor project progress or intermediate results can include: decreased surface runoff, color of surface runoff, increased soil organic matter, improvement in soil structure and water holding capacity, increased infiltration rate, etc.

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Many indicators of SWLM projects are geo-localized at the farm, hill slope and catchment levels. Therefore, when designing a project’s M&E system, indicators for SLWM need to be further identified and used at these levels.

Table 21 summarizes the simple key indicators proposed by the SLWM specialists in Uganda and Tanzania at the farm level. Most of these indicators can be monitored and evaluated using visual observations.

Table 21. Farm level SLWM indicators proposed by SLWM specialists in Uganda and Tanzania Parameter indicators Approaches River channel cover Quadrat and transect methods (visual and point intercept quadrat) Soil erodibility Rainfall simulator, monograph based on textural and organic matter content Soil organic matter Color (Munsell color chart), Soil Test Kit, laboratory analysis content Infiltration rate measurements (double rings), pore space analysis, Mean Soil structure Weight Diameter Water-holding Farmers' comments and indicators, comments on plant behavior during capacity drought conditions, pF curves Infiltration rate Double rings infiltrometer Soil workability / ease Farmers' comments, average land tilled by animals per day, dynamometer of soil tillage readings Crop yield Farmers comments and records Increased grass and Vegetation inventory, use of quadrat, Shannon index palatable species Rill density Field observations, farmers' comments and indicators; quadrat, area Soil deposition An estimate of the amount of soil deposited in gullies and contour bunds Field observations using transect, lines, and point, quadrat, Farmers' Gullies density comments and indicators; area under gullies Surface runoff Runoff plot approach, volume of water collected in trenches Quality of the surface Color of the runoff, concentration of sediment in the runoff, laboratory water analysis Rate of adoption of Farmers comments, field observations, survey, farmers expenditure on SLWM technologies SLWM Ratio of abandoned Farmers comments, field observations, survey /degraded area Regular water sample collected at the catchment and micro-catchment outlets, Water quality laboratory analysis for TN, TP, TSS, TDS, EC and turbidity Water quantity Regular flow and cross section measurements Extent of area under local and introduced vegetation with socio-cultural, Vegetation cover medicinal and economic values protected by the communities, extent of new land with planted tree, normalized difference vegetation index

All the above indicators will also be useful at the hillslope or community level. To monitor the actions taken by local communities to plan and implement the SWLM practices at this level, the development of a community driven micro-catchment restoration plan can be included as an indicator.

At catchment level, in most of the catchment studies in the region, monitoring is done at the outlet of the catchment. Establishment of monitoring unit on key sub-catchments is necessary to understand the sediment dynamics in the catchment. Indicators to monitor can include and not limited to reduction of the sediment yield, total nitrogen and total phosphorous will be monitored. It is also anticipated that the NDVI state and trend measurement, regular water quantity and quality monitoring, surveys, participatory rural appraisal, remote sensing tools and modelling approaches could be used to monitor change and progress by SLWM interventions in a catchment.

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5.3 Methods for M&E of soil erosion and sediment

Various M&E methods for soil erosion and sediment transport have been developed and are readily available for application. Applicability and efficiency of these methods and, therefore, the option to use these methods, depends on the objectives, processes, spatio- temporal scales, environmental conditions, and available resources. Monitoring methods range from simple in-situ ground measurements to state-of-the-art earth observation technologies, some of which are runoff plot method, erosion pin method, radionuclide tracer method, model estimation, and 3S (GPS - Global Positioning System, GIS - Geographical Information System, and RS - Remote Sensing) based method. Evaluation methods are typically quantitative methods using various sediment models (e.g., hydrological models incorporating soil erosion and sediment transport based on the USLE or RUSLE approach), and/or semi-quantitative methods when data are limited. A large body of literature has documented the methods for monitoring and evaluation of soil erosion and sediment transport (e.g., De Graaff et al., 2007; Roose, 2008; Fulajtar et al., 2017; Yin et al., 2018; Borrelli et al., 2019). The following presents a brief introduction to a few commonly applied monitoring and evaluation methods as an initial reference guide to the practitioners who may need them in the M&E of soil erosion. Earth Observation based methods Earth observation (EO) generally refers to the observation and collection of information and data about the physical, chemical, and biological systems of the Earth through remote- sensing (RS) technologies. It often refers to satellite-based remote sensing, if not otherwise specifically elaborated. EO is typically used to monitor and evaluate the status and changing trends of the natural system and built environments. The advantage of satellites is that they provide spatially continuous, replicable and homogeneous information on the condition, distribution and dynamics of the environment in a cost-effective manner and over large areas. The RS based methods have proven to be cost-effective at the regional scale for soil erosion monitoring and assessment (e.g. Žížala et al., 2019). The RS methods, with the traditional application of aerial images and more recent satellite imageries have been widely applied. They enable viewing soil erosion M&E of larger areas in a timely manner and make the quantification of land degradation and erosion more accurate. For example, the RUSLE fed with EO-derived inputs can predict the average annual soil loss caused by water erosion from data that characterizes rainfall, soil type, topography, cropping system and land management practice. Such a model helps to identify and trace hotspot areas with high erosion potential and informs the planning of restoration activities. Yengoh et al., (2018) provides useful guidance, methods and a toolbox for assessing and monitoring the status and trends of land degradation using remote sensing technology. Many RS-based datasets from the public domain are freely available for use in soil erosion monitoring and assessment. Examples are the Global Soil Erosion maps from the European Soil Data Centre (ESDAC), New Land Cover Classification Maps from NASA, and other global soil maps and databases from various sources including, e.g., FAO/UNESCO soil map of the world and ISRIC World Soil Information etc.

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Models and erosion assessment As described above, models often have to be applied, in combination with the 3S tools and technologies, to assist in quantification and evaluation of the land degradation, soil erosion and sediment transport. Depending on the nature of the modelling approaches, models can be classified into two types: Empirical models and process-based models. Empirical models are based on the statistic regression between the best explanatory factors and erosion results. Models using USLE, RUSLE or MUSLE are the typical empirical erosion models. These models, if locally adapted, are able to rather accurately estimate erosion hazards (Roose, 1996). The process-based models (either conceptual or physical models labeled in some literature) attempt to represent the physical processes of soil water erosion through spatial and temporal partition of the processes and intensity and mimic the erosive functioning in relation to factors like forcing rainfall, topographic situations, land uses, and strategies of water and fertility management. Models in this type include ANSWERS, AGNPS, CREAMS, SWAT, KINEROS, EUROSEM, WEPP, and SHETRAN etc. Some of these models also embed an empirical model (e.g. RUSLE) as a module to represent the erosion process coupled with forcing functions. Ground in situ measurements Likewise, there are also many different methods of ground measurement for soil erosion. Typical measurements range from the approximate approach such as measuring soil surface level changes, to the sediment volume aggregation approach such as hillslope soil loss measurement and stream flow and sediment measurement. A few of these methods are briefly introduced below as examples. Measuring surface level change This is a widely used method that can be applied in rural areas with the flexibility to manage periodic observations, low cost for installation and maintenance, and requires low operation skills. It allows a long observation period for the evolution of the topsoil surface, rills, gullies, cattle tracks, and mass movement. This method basically sets up a network of reference marks in a field to be monitored. The reference marks can be a soil monitoring board with ruler or metering marks, erosion pins, pegs, spikes, stakes or rods, which can be wood, bamboo, iron or any material that will not rot or decay and is readily (and cheaply) available. This method drives pins or rods into the soil so the top of the pin gives a datum from which changes in the soil surface level can be measured (Hudson, 1993). Measuring soil loss This type of method measures accumulated sediment volume in a plot of field to indicate the soil loss in a given period of time. Sediment catchpits are often used to make quantitative estimates of erosion. The simple catchpits can be used to evaluate the effect of erosion control (SLWM) interventions (Hudson, 1993). One can set up two small plots with simple catchpits downstream from the slope: one plot is left bare and the other employs SLWM measures (e.g. reforested, terraced etc.). After a certain timeframe, the sediment volume (or weight) accumulated in the two catchpits is measured and compared to determine the volume difference, which indicates the effect of the SLWM interventions.

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Photo 5. Soil measuring boards were planted to measure the earth movement as a result of soil erosion (Photo credit: The MaMaSe Sustainable Water Initiative)

Measuring stream suspended sediments Another important indicator of soil erosion is the sediment in rivers and streams that catch eroded soils in their catchments. Therefore, measuring a stream’s sediment concentration can help monitor and evaluate soil erosion in the catchment. This method usually measures suspended sediment of the stream in question by taking water flow samples. Sampling methods can be categorized into: (i) manual sampling approaches capable of capturing a mass of material which is representative of the sediment flux; (ii) devices capable of collecting discrete samples which can be passive or deliberately controlled to sample during events of interest; and (iii) devices capable of collecting material that is potentially representative of the ambient flux over the entire monitoring period (Perks, 2014). There are many types of instruments (samplers) available for suspended sediment monitoring. They range from simple mechanical samplers to sophisticated optical and acoustical (electronic) sensors; some are manually operated and some are automated. One type of sampler is categorized as a point-integrating sampler, which takes water-sediment samples at a fixed point above the bed in the stream continuously during the sampling period until the sampler is full. The other type used is depth-integrating samplers, which sample continuously by moving the sampler over the water depth at a constant speed. This provides a single sample that’s combined from small sub-samples taken at different points over the depth of the stream (Hudson, 1993). Van Rijn (1986) and Van Rijn and Roberti (2019) provide comprehensive elaboration and guidance on sediment measurements.

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Photo 6. Calibrated flume (V-notch) used by the U.S. Geological Survey to measure water flow and loading of nutrients and sediment. (Photo credit: https://www.nrcs.usda.gov/wps/portal/nrcs/detail/national/water/quality/tr/?cid=stelprdb1240285)

Photo 7. Time-integrating sediment sampler (Photo credit: Virginia Tech Watershed Hydrology Lab website https://hydro.vwrrc.vt.edu/about/tyler_sampler/)

Photo 8. Depth-Integrating Suspended-Sediment Sampler (Photo credit: Mike Nolan, USGS, https://www.usgs.gov/special-topic/water-science-school/science/sediment-and-suspended-sediment?qt- science_center_objects=0#qt-science_center_objects)

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CHAPTER 6. RECOMMENDATIONS AND CONCLUSIONS

Based on the findings presented in previous chapters, this chapter provides the recommendations, starting with institutional and capacity building, and then effective technologies, and M&E. The chapter ends with issues to be further studied in order to increase the adoption rate of SLWM technologies in the LVB.

6.1 Enhancing SLWM

Integrating SLWM into land management planning and programing. SLWM is an integral part of the catchment development and its expected results cannot be achieved independently. Therefore, it is necessary to assist regional and district governments in developing and implementing integrated land use plans and catchment management programs that adopt SLWM practices within and across districts in the LVB. SLWM activities need to be linked with other sectoral programs. Such linkages will help create synergy and achieve multiple results and thus lead towards socio-economic and environmental sustainability.

Using a landscape management approach to strengthen SLWM and governance. To scale up and ensure the effectiveness of SLWM technologies, a broader landscape management approach should be adopted to help address erosion control in a comprehensive way in an entire catchment from its hilltops to lowest reach areas and to engage all relevant stakeholders.

Sensitize the community and build capacity for adopting SLWM technologies. It is important to continue to sensitize farmers to the use of SLWM technologies and practices. This can be done through training experienced local residents to be SLWM trainers, piloting and establishing demonstrations, and organizing farmer field schools. The implementation capacity of local communities and local organizations such as the Catchment Management Committee should be strengthened so they will be able to actively and effectively promote SLWM technologies.

Cross-learning and disseminating SLWM experience and knowledge. Learning and disseminating the knowledge and experience from existing programs will help enhance farmers’ specific SLWM skills and raise the SLWM adoption rate of a community. It is useful to organize learning and knowledge sharing events, including well-targeted field visits, for officials, practitioners, and farmers to learn about positive experiences in neighboring communities, across the basin, and even from other basins with successful experiences.

Promote contour bunds and tie-bunds. Contour bunds and tie-bunds are very effective in controlling sediment and nutrient losses on agricultural land, and therefore improve land quality and fertility and increase crop productivity. There is a need to raise awareness of such good farming and SLWM practices and provide technical support for their implementation.

Promote riverbank stabilization and gully protection measures to reduce sedimentation. Riverbank stabilization and gully control technologies are recommended for controlling sediment transportation in catchments and reducing sedimentation and nutrient runoff into

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Lake Victoria. Establishing a water buffer zone along main rivers has been required by law in all LVB countries. The buffer zone helps implement riverbank stabilization techniques and enhances their effectiveness to reduce soil erosion and sedimentation. However, the enforcement and sustainability of the buffer zones, including the need for and methods of providing alternative livelihoods to farmers whose life traditionally depending on the zones, are an issue of attention.

6.2 Developing an M&E system for SLWM

For a complex SLWM program with regional and global environmental management objectives and local rural development targets, it is important to have a well-defined M&E system and appropriated indicators.

A well-developed M&E system is fundamental to a SLWM operation. Impacts of SLWM on the changes in erosion and ecosystem services are key elements to be measured and monitored. SLWM measures are human responses to land degradation which is caused by various driving forces and will undermine the functions and services of land and ecosystems. The DPSIR framework is helpful to systematically and holistically understand linkages among driving forces, effects of degradation, and human responses and to guide the design of M&E and selection of indicators. Built on DPSIR framework, a set of indicators was proposed to measure the drivers, pressures, state, impacts and responses related to a land ecosystem. M&E design also needs to be scale- and time-sensitive as SLWM technologies are normally employed at different scales with impacts and results spanning into different timeframes, which may go far beyond a project implementation period. In addition, indicators should link to the costs and benefits of individual farmers and local communities for better economic evaluation and sustainability assessment. The coordination and consultation of stakeholders at all levels is key to identifying M&E approach and indicators better suited to project-specific needs.

Project development objective or result level indicators of SLWM projects include: land area where SLWM practices have been adopted, number of land users adopting SLWM practices, number of beneficiaries (% female) directly benefiting from SLWM interventions, changes in the crop yields of major crops, and reduction in soil erosion and sediment yield. The World Bank recommends the first two as core sectoral indicators for its land management investment operations. Other indicators to monitor project progress or intermediate outcomes can be decreased surface runoff, color of surface runoff, increased soil organic matter, improvement in soil structure and water holding capacity, increased infiltration rate, etc. A specific SLWM or landscape management project will adopt its indicators based on the project’s specific objectives and characteristics.

Bottom-up and top-down monitoring approaches will be integratively employed for measuring and monitoring the impacts of SLWM practices in a cost-effective way. For instance, top-down remote sensing data should be shared with local stakeholders and compared to bottom-up evidence gathered locally on the ground. Therefore, the results of local efforts do not go unnoticed at higher levels and, similarly, higher level stakeholders, especially those engaged in monitoring or decision making, will get a level of contextual understanding and validity of their results on the ground that is otherwise impossible to get through top-down approaches alone. Doing this could further strengthen stakeholder engagement and participation in M&E.

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6.3 Concluding remarks

The overall adoption of SLWM technologies in the LVB has remained low, and their on- site impacts—at micro-catchment scale and at a larger catchment scale—are largely unknown. Taking Tanzania’s Simiyu River Catchment as a case study, the report presented a useful study on the effectiveness of SLWM practices introduced in the catchment by LVEMP. The study provided a unique ex-post assessment. It applied various modeling and analytic approaches to assess soil erosion risks of the catchment, identify erosion hotspots, and simulate the effectiveness of selected SLWM technologies in erosion control. A few technologies were effective and are recommended for LVB. As actual measurement and monitoring of soil erosion and sediment reduction has rarely been conducted in land management projects, this report discussed M&E approaches and indicators in detail and proposed a set of indicators and methods for monitoring a project’s progress and impacts.

The report, however, is primarily on the technical aspects of SLWM and M&E. Whether SLWM technologies can be successfully and widely adopted in the basin still depends on many non-technical factors. For instance, adequate policy and regulatory framework needs to be further studied and strengthened, so does the capacity and awareness of relevant government agencies and local communities in SLWM implementation. It is important to reach as many farmers as possible through teaching and the sharing of good practices, and thereby enhance both erosion control and agricultural development in the basin. This also requires assessing the potential operational costs and socio-economic impacts of these SLWM interventions and making recommendations for adopting SLWM technologies based on strong economic and financial gains. Furthermore, practitioners often wrestle with how much investment on a specific site is “enough” to impart measurable impacts but not to over-invest. The use of high-quality site data and decision support system tools can help. These issues should be further investigated in future studies and well incorporated into future investments.

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