1. Introduction
Nowadays, point source pollution has been effectively controlled, while nonpoint source pollution (NPS) has become one of the most important reasons resulting in the deterioration of the surface water environment. However, NPS assessment is usually limited for insufficient monitoring data in some areas.
As the largest tropical lake in the world, Lake Victoria has a basin area of 193,000 km
2 and a water area of about 68,800 km
2 [
1]. The lake water is shared by Kenya, Tanzania, and Uganda, and the lake basin covers parts of Burundi, Kenya, Rwanda, Tanzania, and Uganda [
2]. The Lake Victoria basin is one of the most densely populated areas in Africa. It is estimated that between 2000 and 2010, the population of this basin increased from 54.5 to 73.6 million people who directly or indirectly relied on Lake Victoria for survival and development [
3,
4]. The lake is also home to a variety of flora and fauna [
5]. Rapid population growth in the past few decades, coupled with the continuous expansion of agricultural and urban land, has put great pressure on the water quality of Lake Victoria [
6,
7]. Due to the deficiencies in the environmental management systems, untreated emissions from domestic garbage, sewage, agricultural pesticides, and fertilizers have been prevalent in the highly populated areas around the lake, leading to serious eutrophication of Lake Victoria [
8,
9]. As a result, the ecosystem within the lake and the safety of drinking water in the lake zone have been seriously affected [
10,
11,
12,
13]. According to a five-year (1997–2002) management experience of the Lake Victoria Environmental Management Project (LVEMP), launched unitedly by Kenya, Tanzania, and Uganda in 1994, NPS has become the major contributor to the deterioration of water quality in Lake Victoria [
14]. With the effective control of point source pollution, more scholars now focus on NPS in the Lake Victoria basin [
15,
16].
NPS in Lake Victoria has become an important factor limiting the sustainable water quality management of this basin. Therefore, relevant research such as the quantification of pollution load and the analysis of pollution output characteristics is beneficial to the ecological and environmental protection of Lake Victoria. At present, the model method is often used to study NPS [
17,
18,
19]. Among numerous models, the soil and water assessment tool (SWAT) has a wide range of successful applications in the field of NPS research [
20,
21]. The SWAT model is composed of a hydrological cycle module, a soil land erosion module, and a pollutant load module, which can simulate runoff, sediment, nutrients, and other transport processes in the basin [
22,
23,
24]. The data input to the SWAT model mainly includes the digital elevation model (DEM), land use, soil and meteorological data, and output runoff and nutrient data of the river cross-section and basin. Because it can fully consider the hydrological cycle and nutrient migration process and can make full use of spatial data by combining with other models or methods, SWAT could be applied to a wider range of research fields [
25,
26].
The SWAT model is mainly based on the water balance equation, which is the driving force for all processes in the basin. High-quality hydrological and water quality monitoring data are critical in the calibration and validation of SWAT parameters. However, there are relatively few hydrological stations in Africa [
27,
28]; and accurately measured hydrological and water quality data only exist in a few cities in African countries such as Niger and Togo [
16]. Therefore, the lack of data has hindered the application of SWAT in the Lake Victoria basin, though a few related studies existed. For example, Kimwaga et al. [
29] simulated the NPS in the Simiyu catchment in Tanzania using the SWAT model. The results from the study indicated an underestimation of the sediment production because only seven sediment monitoring data were used to calibrate the SWAT parameters, which were insufficient. Another study from Cheruiyot and Muhandiki [
30] failed to obtain ideal simulation results of the NPS in the Sondu watershed in Kenya due to less and discontinuous water quality data. As a result, obtaining reliable simulation results with insufficient data has become a central challenge to researchers trying to simulate current or future NPS in the Lake Victoria Basin.
Unlike SWAT, the long-term hydrological impact assessment (L-THIA) model, which was jointly developed by the U.S. Environmental Protection Agency (EPA) and Purdue University, has relatively lower requirements for data and is more applicable in data-poor areas and situations [
31,
32]. The core of the L-THIA model is the classic SCS-CN model, so the long-term rainfall, soil, and land use data are used to simulate runoff volume [
33,
34]. The output data include the runoff and total NPS load of different land use types. The event mean concentration (
) is the critical parameter of the L-THIA model to simulate NPS loads. However, numerous studies have shown that the default
values should be localized. For example, when studying the AXL watershed located in DeKalb County, Northeastern Indiana state, Liu et al. [
35] expressed that total nitrogen (TN) and total phosphorus (TP) loads simulated using the default
values were relatively small. Nejadhashemi et al. [
36] indicated that because the default
values were too small, the NPS of the Pomona Lake watershed in North-east Kansas state simulated by the L-THIA model was also too small, and if accurate
values could be obtained, nitrogen and phosphorus pollution in this watershed would be well simulated. So far, no scholars have applied the L-THIA model to the Lake Victoria basin to study NPS, and there are no relevant
values to be defined in this region. If we select a catchment with relatively complete data to build the SWAT model and use the high temporal resolution flow and non-point source data obtained from the model simulation, the required
parameters can be derived for L-THIA model construction. Thus, the innovative integrated use of these two models is expected to achieve NPS simulation in data-deficient areas.
The Simiyu catchment is located in the southeast of Lake Victoria. The increasing population and the development of economic activities such as agriculture and livestock have exacerbated nutrient pollution in this catchment, resulting in severe deterioration of water quality [
37]. As an important channel into Lake Victoria, the Simiyu River accounts for 4.6% of the total annual lake flux and collects and delivers a large share of NPS into Lake Victoria [
38,
39]. Besides, the Simiyu catchment is a typical agricultural catchment in the area around Lake Victoria, and the agricultural activities in this catchment strongly affect the lake characteristics in the southeast [
40]. Therefore, controlling the NPS of the Simiyu catchment is key to improving the water quality of both the Simiyu River and Lake Victoria. Currently, there are no
monitoring activities in the Simiyu catchment or in the entire Lake Victoria Basin. Thus, the application of the L-THIA model in this area would be difficult.
In this article, we analyze the temporal and spatial distribution characteristics of the nonpoint source TN and TP pollution in the Simiyu River catchment; the values of TN and TP pollution for different land use types are also derived based on the SWAT model. The results of this study are expected to provide a relevant reference for the management of NPS, both currently and in the future, not only in the Simiyu catchment but also in other similar catchments with poor or no data.
5. Conclusions
Insufficient data often limits NPS assessment and pollution control in some areas. In this study, we demonstrated that assessment of the spatial distribution of NPS with extremely limited water quality monitoring data can be achieved by integrating multiple models. The Simiyu watershed with complete data was employed to establish the SWAT model, and then through the simulation of the SWAT model, the localized values were derived, which served as the key parameters for the L-THIA model. Through the combined utilization of these two models, we can overcome the difficulty and challenge of insufficient data and reasonably evaluate the distribution of NPS in the Simiyu River catchment. The results indicated that the average monthly output of TN and TP in the rainy season was 1360.6 t and 336.2 t, respectively, while in the dry season was much lower, only 13.5 t and 3.0 t, respectively. TP output was significantly lower than TN output. However, the temporal variation trends for TN and TP outputs were almost the same; in view of spatial distribution among 32 sub-basins, TN load ranged from 2.051 to 24.288 kg/ha with an average load of 12.940 kg/ha, and TP load ranged from 0.263 to 8.103 kg/ha with an average load of 3.321 kg/ha during the 16 month study period. In addition, sub-basins 3, 4, 6, 8, and 10 were areas with high TN and TP loads. In general, the load of TN and TP in the downstream area was higher than that in the upstream area. For different land use types, the cropland contributed the highest proportion of TN and TP pollution, with 50.28% and 76.29%, respectively, while the effect of forest on NPS was minimal, with 0.05% and 0.02% for TN and TP, respectively. Therefore, taking pollution prevention and control measures during the rainy season, such as controlling crop fertilization, reducing the direct discharge of sewage from livestock and poultry breeding as well as human living, and strengthening forest protection, can effectively reduce TN and TP pollution in the study area. More importantly, the derived values based on this study are promising to be applied to other similar data-lacking catchments by simply adopting the L-THIA model.